THE ROLE AND USABILITY OF CLIMATE FORECASTS FOR

FLOOD CONTROL AND WATER SUPPLY AGENCIES IN ARIZONA:

A CASE STUDY OF THE 1997-98 EL NIÑO

by

Thomas Christopher Pagano

A Thesis Submitted to the Faculty of the

DEPARTMENT OF HYDROLOGY AND WATER RESOURCES

In Partial Fulfillment of the Requirements

For the Degree of

MASTER OF SCIENCE

In the Graduate College

THE UNIVERSITY OF ARIZONA

1 9 9 9

STATEMENT BY AUTHOR

This thesis has been submitted in partial fulfillment of requirements
for an advanced degree at The University of Arizona and is deposited in
the University Library to be made available to borrowers under rules of
the Library.

Brief quotations from this thesis are allowable without special
permission, provided that accurate acknowledgment of source is made.
Requests for permission for extended quotation from or reproduction of
this manuscript in whole or in part may be granted by the head of the
major department or the Dean of the Graduate College when in his or her
judgment the proposed use of the material is in the interests of
scholarship. In all other instances, however, permission must be
obtained from the author.

SIGNED: \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_

#### APPROVAL BY THESIS DIRECTOR

This thesis has been approved on the date shown below:

\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_

Soroosh Sorooshian Date

Professor of Hydrology

**TABLE OF CONTENTS**

######### Page

ABSTRACT [10](#abstract)

1\. INTRODUCTION [13](#chapter-i)

1.1 Problem Statement [13](#problem-statement)

1.2 Objectives [16](#objectives)

1.3 Thesis Organization [17](#thesis-organization)

2\. ENSO AND THE SOUTHWESTERN US [19](#enso-and-the-southwestern-us)

2.1 Introduction [19](#introduction-1)

2.2 The El Niño/Southern Oscillation
[20](#the-el-niñosouthern-oscillation)

2.3 Teleconnections [26](#teleconnections)

2.3.1 Large Scale Circulation [26](#large-scale-circulation)

2.3.2 Precipitation in Arizona [34](#precipitation-in-arizona)

2.3.3 Streamflow in Arizona [40](#streamflow-in-arizona)

2.3.4 Extreme Events in Arizona [42](#__RefHeading___Toc462466168)

2.3.5 Summary of Teleconnections [45](#summary-of-teleconnections)

2.4 The 1997-98 El Niño [46](#the-1997-98-el-niño)

2.4.1 Introduction [46](#introduction-2)

2.4.2 Initial Conditions [46](#initial-conditions)

2.4.3 The Tropical Pacific [55](#the-tropical-pacific)

2.4.4 Large Scale Circulation [58](#large-scale-circulation-1)

2.4.5 Southwestern US Precipitation [58](#southwestern-us-precipitation)

2.4.6 Streamflow & Extreme Flooding [76](#streamflow-extreme-flooding)

2.4.7 Hurricane Nora [79](#hurricane-nora)

2.4.8 Summary of 1997-98 El Nino [86](#summary-of-1997-98-el-nino)

3\. EVOLVING SEASONAL FORECASTING ABILITY
[87](#evolving-seasonal-forecasting-ability)

3.1 Introduction [87](#introduction-3)

3.2 Climate Forecasts [88](#climate-forecasts)

TABLE OF CONTENTS (continued)

####### Page

3.3 Hydrological Forecasts [97](#hydrological-forecasts)

3.4 Seasonal Forecast Evaluation [102](#seasonal-forecast-evaluation)

3.4.1 Hydrologic Forecasts [102](#hydrologic-forecasts)

3.4.2 CPC Climate Outlooks [110](#cpc-climate-outlooks)

3.4.3 Summary [118](#summary)

4\. WATER MANAGEMENT IN ARIZONA [119](#water-management-in-arizona)

4.1 Introduction [119](#introduction-4)

4.2 Water Supply Management [121](#water-supply-management)

4.2.1 Salt River Project [122](#salt-river-project)

4.2.2 Colorado River Management [127](#colorado-river-management)

4.2.3 Gila River Water Commissioner
[134](#gila-river-water-commissioner)

4.3 Extreme Event Management [137](#extreme-event-management)

4.4 Recent Extreme Flooding Events
[143](#recent-extreme-flooding-events)

4.4.1 The 1983 Colorado River Flood
[144](#the-1983-colorado-river-flood)

4.4.2 Southeast Arizona Flood October 1983
[148](#southeast-arizona-flood-october-1983)

4.4.3 The 1993 Central Arizona Flood
[149](#the-1993-central-arizona-flood)

4.5 Summary [152](#summary-1)

5\. CASE STUDY RESULTS [154](#case-study-results)

5.1 Introduction [154](#introduction-5)

5.2 Case Study Approach [155](#case-study-approach)

5.3 Sources of Information [159](#sources-of-information)

5.3.1 National Weather Service and Agency Briefings
[160](#national-weather-service-and-agency-briefings)

5.3.2 Inter- and Intra-Agency Communication and In-House Research
[162](#inter--and-intra-agency-communication-and-in-house-research)

5.3.3 The Internet [166](#the-internet)

5.3.4 The Public Media [167](#the-public-media)

5.3.5 Universities [169](#universities)

5.4 Interpretation of Information [170](#interpretation-of-information)

TABLE OF CONTENTS (continued)

####### Page

5.5 Agency Response [173](#agency-response)

5.5.1 Water Providers [174](#water-providers)

5.5.2 Flood Control Districts & Emergency Management
[181](#flood-control-districts-emergency-management)

5.6 Internal Factors Affecting Forecast Use
[184](#internal-factors-affecting-forecast-use)

5.6.1 Introduction [184](#introduction-6)

5.6.2 Enhanced Rainfall Does Not Always Imply Flooding.
[185](#enhanced-rainfall-does-not-always-imply-flooding.)

5.6.3 Excessive Technical Jargon and Multiple Sources of Information.
[186](#excessive-technical-jargon-and-multiple-sources-of-information.)

5.6.4 Disconnect between Data Needs and Current Products.
[187](#disconnect-between-data-needs-and-current-products.)

5.6.5 Forecast Implications are not Clear.
[189](#forecast-implications-are-not-clear.)

5.6.6 Measure of Accuracy of the Forecasts Unavailable.
[190](#measure-of-accuracy-of-the-forecasts-unavailable.)

5.6.7 "Normal" is a Misleading Concept.
[192](#normal-is-a-misleading-concept.)

5.7 External Factors Affecting Forecast Use
[193](#external-factors-affecting-forecast-use)

5.7.1 Introduction [193](#introduction-7)

5.7.2 Systems are invariant to interannual variability
[193](#systems-are-invariant-to-interannual-variability)

5.7.3 Unavailable agency resources [195](#unavailable-agency-resources)

5.7.4 Climate variability is one of many factors
[197](#climate-variability-is-one-of-many-factors)

5.7.5 Existing water law limits flexibility
[198](#existing-water-law-limits-flexibility)

5.7.6 Agencies are unfamiliar with products/lack access
[199](#agencies-are-unfamiliar-with-productslack-access)

5.7.7 Not every agency is sensitive to every forecast
[200](#not-every-agency-is-sensitive-to-every-forecast)

5.7.8 Use of forecasts may increase user exposure to risk
[201](#use-of-forecasts-may-increase-user-exposure-to-risk)

6\. RECOMMENDATIONS [203](#recommendations)

7\. CONTRIBUTIONS [212](#contributions)

8\. REFERENCES [215](#references)

##### LIST OF ILLUSTRATIONS

####### Page

Figure 1 Map of locations mentioned throughout report:
[11](#__RefHeading___Toc463882011)

Figure 2 CPC Climate forecast divisions
[12](#__RefHeading___Toc463882012)

Figure 3 SST Comparison of La Niña, normal and El Niño conditions.
[21](#__RefHeading___Toc463882013)

Figure 4 Schematic of major Tropical features under normal conditions..
[22](#__RefHeading___Toc463882014)

Figure 5 Southern Oscillation Index time series 1880-1998
[23](#__RefHeading___Toc463882015)

Figure 6 Multivariate ENSO Index time series 1950-99.
[26](#__RefHeading___Toc463882016)

Figure 7 Southern Oscillation Index correlation with Oct-Mar 700 mb
Geopotential Height (top) and Oct-Mar 200 mb wind speed (bottom)..
[29](#__RefHeading___Toc463882017)

Figure 8 October-March 700 mb Geopotential Height Climatology (1968-96)
(top) and mean anomaly for all El Nino years 1963-96 (bottom)..
[30](#__RefHeading___Toc463882018)

Figure 9 October-March 700 mb Geopotential Height Anomaly 1982-83 (top)
and 1997-98 (bottom). [31](#__RefHeading___Toc463882019)

Figure 10 October-March 200 mb wind climatology (1968-96) (top) and mean
anomaly for all El Nino years 1963-96 (bottom)..
[32](#__RefHeading___Toc463882020)

Figure 11 October-March 200 mb wind anomaly 1982-83 (top) and 1997-98
(bottom). [33](#__RefHeading___Toc463882021)

Figure 12 October to May total precipitation versus June to November SOI
(1934-98), Upper Colorado River basin regions..
[37](#__RefHeading___Toc463882022)

Figure 13 October to May total precipitation versus June to November SOI
(1934-98), Western Lower Colorado River basin regions..
[38](#__RefHeading___Toc463882023)

Figure 14 October to May total precipitation versus June to November SOI
(1934-98), Eastern Lower Colorado River basin regions.
[39](#__RefHeading___Toc463882024)

Figure 15 Spring-melt streamflow versus June-November SOI. January-May
Cumulative Streamflow for Salt, Verde, Gila (1934-98)
[42](#__RefHeading___Toc463882025)

Figure 16 Spring-melt daily peak flow versus June-November SOI.
January-May peak Streamflow for Salt, Verde, Gila (1934-98)
[44](#__RefHeading___Toc463882026)

Figure 17 Salt River water balance 1914-98..
[47](#__RefHeading___Toc463882027)

Figure 18 Verde River water balance 1938-98
[48](#__RefHeading___Toc463882028)

Figure 19 Gila River water balance 1915-98
[49](#__RefHeading___Toc463882029)

Figure 20 Colorado River water balance 1922-98
[50](#__RefHeading___Toc463882030)

Figure 21 Colorado River reservoir status 1922-98.
[51](#__RefHeading___Toc463882031)

Figure 22 Colorado reservoir status 1990-98..
[52](#__RefHeading___Toc463882032)

Figure 23 Salt River Project and Gila River reservoir status 1990-98
[53](#__RefHeading___Toc463882033)

Figure 24. Multivariate ENSO Index comparison for strong El Nino events
[56](#__RefHeading___Toc463882034)

Figure 25 Monthly (top) and water year cumulative (bottom) precipitation
for Area 48 (Western Colorado).. [61](#__RefHeading___Toc463882035)

Figure 26 Monthly (top) and water year cumulative (bottom) precipitation
for Area 49 (Southwestern Wyoming).. [62](#__RefHeading___Toc463882036)

Figure 27 Monthly (top) and water year cumulative (bottom) precipitation
for Area 83 (Northeastern Utah).. [63](#__RefHeading___Toc463882037)

Figure 28 Monthly (top) and water year cumulative (bottom) precipitation
for Area 84 (Southeastern Utah).. [64](#__RefHeading___Toc463882038)

##### LIST OF ILLUSTRATIONS (continued)

####### Page

Figure 29 Monthly (top) and water year cumulative (bottom) precipitation
for Area 94 (Southeastern California).
[65](#__RefHeading___Toc463882039)

Figure 30 Monthly (top) and water year cumulative (bottom) precipitation
for Area 95 (Las Vegas Region Nevada)..
[66](#__RefHeading___Toc463882040)

Figure 31 Monthly (top) and water year cumulative (bottom) precipitation
for Area 96 (Southwestern Arizona).. [67](#__RefHeading___Toc463882041)

Figure 32 Monthly (top) and water year cumulative (bottom) precipitation
for Area 97 (Northeastern Arizona).. [68](#__RefHeading___Toc463882042)

Figure 33 Monthly (top) and water year cumulative (bottom) precipitation
for Area 98 (Southeastern Arizona).. [69](#__RefHeading___Toc463882043)

Figure 34 Monthly (top) and water year cumulative (bottom) precipitation
for Area 99 (Northern New Mexico). [70](#__RefHeading___Toc463882044)

Figure 35 Monthly (top) and water year cumulative (bottom) precipitation
for Area 101 (Central New Mexico). [71](#__RefHeading___Toc463882045)

Figure 36 Monthly (top) and water year cumulative (bottom) precipitation
for Area 102 (Southern New Mexico).. [72](#__RefHeading___Toc463882046)

Figure 37 Upper Colorado River Basin regions October to May
precipitation exceedence probabilities (1961-90).
[73](#__RefHeading___Toc463882047)

Figure 38 Western Lower Colorado River Basin regions October to May
precipitation exceedence probabilities (1961-90)..
[74](#__RefHeading___Toc463882048)

Figure 39 Eastern Lower Colorado River Basin regions October to May
precipitation exceedence probabilities (1961-90)..
[75](#__RefHeading___Toc463882049)

Figure 40 1960-91 Ranked Spring-melt Streamflow versus 1997-98 (dashed.
[77](#__RefHeading___Toc463882050)

Figure 41 1960-91 Ranked Water Year peak flow versus 1997-98 (dashed).
[78](#__RefHeading___Toc463882051)

Figure 42 1997 Eastern Pacific Hurricane Track Chart
[83](#__RefHeading___Toc463882052)

Figure 43 GOES 9 Infrared Satellite Images Sept 21-27 1997..
[84](#__RefHeading___Toc463882053)

Figure 44 Hurricane Nora Storm track, predicted September 23 (left) and
September 24 (right). [85](#__RefHeading___Toc463882054)

Figure 45 Official SST Forecast. [89](#__RefHeading___Toc463882055)

Figure 46 CPC Climate Outlook legend. [91](#__RefHeading___Toc463882056)

Figure 47 CPC Climate Outlooks. [92](#__RefHeading___Toc463882057)

Figure 48 CPC Climate Outlook DJF Precipitation Class Limit Maps
[95](#__RefHeading___Toc463882058)

Figure 49 Sample Water Supply Outlook
[100](#__RefHeading___Toc463882059)

Figure 50 Water Supply Outlooks (Solid) versus observations (dashed) for
winter 1997-98 on Salt and Verde Rivers.
[104](#__RefHeading___Toc463882060)

Figure 51 Water Supply Outlooks (Solid) versus observations (dashed) for
winter 1997-98 on Gila and Colorado Rivers
[105](#__RefHeading___Toc463882061)

Figure 52 January 1^st^ Water Supply Outlooks versus observations
[106](#__RefHeading___Toc463882062)

Figure 53 January 1^st^ Water Supply Outlooks vs observations (log-log
scale). [107](#__RefHeading___Toc463882063)

Figure 54 Lake Powell Inflow Water Supply Outlooks 1964-98.
[108](#__RefHeading___Toc463882064)

Figure 55. Guide to CPC Climate Outlook forecast verification plots.
[112](#__RefHeading___Toc463882065)

##### LIST OF ILLUSTRATIONS (continued)

[Page]{.underline}

Figure 56. CPC Climate Outlook precipitation forecasts (top) versus
observations (bottom) for Area 83 (Northeast Utah), 1995-1998
[113](#__RefHeading___Toc463882066)

Figure 57 CPC Climate Outlook precipitation forecasts (top) versus
observations (bottom) for Area 94 (Southeast California), 1995-1998.
[114](#__RefHeading___Toc463882067)

Figure 58 CPC Climate Outlook precipitation forecasts (top) versus
observations (bottom) for Area 98 (Southeast Arizona), 1995-1998
[115](#__RefHeading___Toc463882068)

Figure 59 CPC Climate Outlook precipitation forecasts (top) vs
observations (bottom) for Area 101 (Central western New Mexico),
1995-1998. [116](#__RefHeading___Toc463882069)

Figure 60 Salt River Project Interannual Management Plan..
[126](#__RefHeading___Toc463882070)

Figure 61 Example Parker Strip residences for sale along the Lower
Colorado River.. [131](#__RefHeading___Toc463882071)

Figure 62 1982-83 (top) Grizzly Peak, CO Snow Water Equivalent versus
1997-98 (bottom). [146](#__RefHeading___Toc463882072)

Figure 63 Survey participant locations.
[156](#__RefHeading___Toc463882073)

Figure 64 Lake Powell Water Supply Outlook error versus Southern
Oscillation Index (1967-98).. [165](#__RefHeading___Toc463882074)

####  

##### LIST OF TABLES

######## Page

Table 1. Arizona Reservoir Status 1997-98
[54](#__RefHeading___Toc462466292)

Table 2. Water Supply Outlook Forecast Points in Arizona
[99](#__RefHeading___Toc462466293)

Table 3. Salt River Project Reservoirs
[123](#__RefHeading___Toc462466294)

Table 4. SRP Management Time Scales, Activities and Guidance Tools
[124](#__RefHeading___Toc462466295)

Table 5. Colorado River Bureau of Reclamation Major Reservoirs
[129](#__RefHeading___Toc462466296)

Table 6. January 1 Water Supply Outlooks of the 1992-93 Flood
[150](#__RefHeading___Toc462466297)

Table 7. Sources of Information Summary
[159](#__RefHeading___Toc462466298)

Table 8. Select Planning Meetings in Preparation for the 1997-98 El Niño
[162](#__RefHeading___Toc462466299)

Table 9. Forecasts versus Agency Expectations
[170](#__RefHeading___Toc462466300)

Table 10. Water Provider Agency Response Summary
[176](#__RefHeading___Toc462466301)

Table 11. Extreme Event Management Agency Response Summary
[184](#__RefHeading___Toc462466302)

#  

# ABSTRACT

The 1997-98 El Niño provided a unique opportunity for climate
information and forecasts to be utilized by water management agencies in
the Southwestern U.S. While Arizona has experienced high streamflow
associated with previous El Niño events, never before had an event of
such magnitude been predicted with advance warning of several months.
Likewise, the availability of information, including Internet sources
and widespread media coverage, was higher than ever before. Insights
about use of this information in operational water management decision
processes are developed through a series of semi-structured in-depth
interviews with key personnel from a broad array of agencies responsible
for emergency management and water supply, with jurisdictions ranging
from urban to rural and local to regional. The interviews investigate
where information was acquired, how it was interpreted and how it was
incorporated into specific decisions and actions. The interviews also
investigate agency satisfaction with the products available to them,
their operational decisions, and intentions to utilize forecast products
in the future. Study findings lead to recommendations about how to more
effectively provide intended users of forecasts with information
required to enact mitigation measures and utilize opportunities that
some climatic events present.

[]{#__RefHeading___Toc463882011 .anchor}**Figure 1** Map of locations
mentioned throughout report:

![](media/image1.png){width="4.9375in" height="5.479166666666667in"}

1\) Painted Rock Dam

2\) Hoover Dam/Lake Mead

3\) Glen Canyon Dam/Lake Powell

4\) Coolidge Dam/San Carlos Reservoir

5\) Salt River Dams

(Roosevelt Dam and others)

6\) Verde River Dams

(Horseshoe, Bartlett)

7\) City of Tucson

8\) City of Phoenix

9\) City of Yuma

10\) City of Clifton

11\) The "Parker Strip"

> ![](media/image2.jpeg){width="5.989583333333333in"
> height="6.051388888888889in"}

[]{#__RefHeading___Toc463882012 .anchor}Figure 2 CPC Climate forecast
divisions. Shaded divisions contation portions of the Upper and Lower
Colorado River Basins. These divisions are referred to throughout the
report with respect to precipitation in the Southwestern US (e.g.
Chapters 2 and 3)

# CHAPTER I

# INTRODUCTION

## 1.1 Problem Statement

The ultimate test of a scientific theory is its ability to reduce
uncertainty about the unknown. To this end, one powerful contribution of
science to society is its predictions and forecasts. For decades,
meteorologists have had a strong tradition of forecasting, helping to
prevent damages and ensure safety. There is a growing sense among the
hydrological community that it should contribute in a similar manner.
This is reflected in the recent expansion of the focus of large
hydrological research programs. Assisting decision-makers through the
development of forecasts and useful applications is equally important as
the development of models and observations (Sorooshian and Imam, 1999).
However, in order to improve the services that the scientific community
provides to society, current performance must be evaluated first.

The success of forecasters does not solely reside in their physical
"products", nor does improvement solely consist of improving these
products. Forecasters' success depends on their ability to influence
decisions to the benefit of an individual and/or of all society.
Therefore, evaluating forecast accuracy and format plays one role in
assessing forecast performance, but evaluating how well forecasts are
integrated into decision-making processes is of equal or greater
importance. As Gilbert White noted, "a forecast is of no value unless
those who receive it are prepared to act promptly and efficiently."
(White, 1939)

This concept is an expansion of the previous philosophy of the
scientific community: improve forecast products and passively allow the
benefit to "trickle down" to users. Under this previous philosophy,
forecasting tools and methodologies rapidly advanced, propelling the
science into the 21^st^ century. However, evidence suggests that users
have been left behind. Studies by Changnon (1992), Sonka et al. (1992),
Pulwarty and Redmond (1997), Callahan et al. (1999) and others
consistently report that seasonal climate forecasts play a marginal role
in decision making. Changnon attributes this to an underdeveloped
forecaster-user interface, a lack of communication and interaction
between producers and users. Clearly, this situation cannot continue.

A new philosophy is necessary not only to assess the performance of the
forecasts, but to ensure their use, as well. Forecasts need to be
produced by scientists aware of and directed by user needs. An early
attempt at this process in the United States (US) includes forecasting
lake levels of the Great Lakes (Hartmann and Donahue, 1990). National
and Regional Climate Assessments are currently in development to help
science reduce the US's vulnerability to climate change and climate
variability. These multidisciplinary programs are specifically focused
on developing relationships with user communities and developing a
collective understanding of how to increase community resilience. The
Southwestern US Regional Climate Assessment Project (CLIMAS), formed in
1997, is currently developing an understanding of user needs and
decision-making processes with an emphasis on water management.

Providing users with forecasts is increasingly recognized as an
end-to-end process, as should be forecast assessment. The value of a
forecast can only be defined by following it from producer, through
distribution channels, to the user and into decisions. Evaluation of
this process would be valuable, but as stated previously, seasonal
climate forecast use has been marginal and there are limited examples of
how these forecasts have been applied (this, in and of itself, suggests
that a major problem exists). However, there is one notable exception:
the 1997-98 El Niño event.

This event represents a turning point in both seasonal forecasting and
water management in the Southwestern US. Prior to the event, the
scientific community was unable to produce seasonal forecast products
with sufficient accuracy or confidence for them to be used in water
management. However, in 1997, climate forecasts of the impending, large
El Niño and its potentially devastating impacts were more widely
distributed and visible than ever before. There was a perceived need by
agencies to gather sufficient information and consider appropriate
action before the event. The climate forecasts crossed the threshold of
utility and were incorporated into operational decisions. This
represents a rare opportunity to investigate how these forecasts
traveled through various channels to their users and how the forecasts
were applied *in practice*.

Due to the relatively strong signal of El Niño in Arizona, with several
examples of exceptional floods, and the paramount importance of water
management in the region, the capability to use climate forecasts in
Arizona may be advanced over those regions where teleconnections are not
as strong. This indicates that the Southwest has the potential of being
one of the vanguards (along with the Pacific Northwest and the Gulf
Coast states) of seasonal forecast use in the continental United States.
Although a number of studies have investigated the use of seasonal
forecasts in water management in the Pacific Northwest (e.g. Callahan et
al., 1999; Pulwarty and Redmond, 1997), no detailed examination has been
performed in the Southwestern US, suggesting that such studies are
clearly appropriate and necessary, if not overdue.

Understanding how water management agencies can and do utilize seasonal
forecasts, and what barriers are currently present in the forecast
process are important to both the scientific community, as a whole, and
CLIMAS in particular. Hydrology and seasonal forecasting have excelled
in recent decades, and the opportunity is ripe to apply these advances
to serve the needs of water resources decision-makers. Only through
interacting with users and understanding how these forecasts may be used
can the gulf between scientists and users be bridged. Without it, the
forecasts will continue experiencing marginal use and may ultimately
have less than zero value.

## 

## 1.2 Objectives

This study seeks to develop an understanding of how water management
agencies in Arizona utilized the advance warning of the 1997-98 El Niño
and how the seasonal forecasting system performed during this period. It
intends to direct and advise the forecasters in more effectively serving
the user community. This includes evaluating the forecasts from top to
bottom, from accuracy to application. This is done through investigating
the following:

1.  How accurate were the 1997-98 seasonal forecasts compared to
    previous years?

2.  Through what channels did climate information and forecasts travel
    to agencies? Were some channels more effective than others, in terms
    of retaining original forecast content, their clarity, and ability
    to reach their intended audience?

3.  How did water management agencies translate the information they
    received into how it would affect their operations? Was this
    interpretation appropriate?

4.  What types of activities did agencies perform, in preparation? What
    factors influenced how (and to what extent) agencies prepared?

5.  What aspects of the forecasts (both technical and stylistic) need to
    be enhanced to increase the overall usefulness of the forecasts to
    agencies?

6.  How can the forecasting community focus its research efforts, in
    general, to achieve the greatest tangible benefit to agencies?

7.  What institutional structures and practices are incompatible with
    climate forecasts and information?

8.  How, if at all, can the flexibility and durability of agencies be
    increased in the face of climate variability and change?

## 1.3 Thesis Organization

This thesis begins in chapter 2 with an assessment of the state of
knowledge about El Niño and its impacts on the Southwestern US. It
reviews the state of knowledge about El Niño in general, how it
influences large-scale circulation and ultimately impacts precipitation,
streamflow and flooding in Arizona. It continues with a description of
the 1997-98 El Niño, similarly investigating its evolution in the
Tropical Pacific, shifts in large-scale circulation and impacts on
Arizona, with special attention paid to Hurricane Nora. Chapter 3
reviews the current state of seasonal climate and hydrologic forecasting
and concludes with an evaluation of the 1997-98 forecasts compared with
previous years. Chapter 4 documents some of the major characteristics of
water management in Arizona, cataloging the responsibilities,
objectives, yearly planning and use of forecasts of various agencies.
Extended discussion is provided of three specific water supply
management agencies: the Salt River Project, the Colorado River Bureau
of Reclamation, the Gila River Water Commissioner. To better understand
how these agencies are impacted by and react to floods, three specific
recent extreme flooding events are also discussed: the spring 1983
Colorado River flood, the October 1983 Southeast Arizona flood and the
winter 1993 Arizona flood. Chapter 5 discusses the case study approach
and findings. It documents the flow of information from forecast
producers to users through various distribution channels. It also
evaluates how agencies interpreted this information and incorporated it
into specific decisions. It reveals some of the factors that affect
forecast use, including internal factors pertaining to forecast format,
style, etc. as well as external factors, including institutional
barriers. Based on the findings of this study, chapter 6 provides
recommendations to the scientific community as a whole and CLIMAS, in
particular. Finally, chapter 7 assesses the original contributions of
this work to science and society.

#   {#section-3 .unnumbered}

# CHAPTER 2

# ENSO AND THE SOUTHWESTERN US

## 

## 2.1 Introduction

This section provides an overview of the relationship between the El
Niño/Southern Oscillation (ENSO) phenomenon and the hydroclimatology of
Arizona. It focuses primarily on the surface hydrology (namely
precipitation and streamflow) of the region, although undoubtedly other
climate aspects have the potential to affect water management (such as
temperature and snowfall). However, the intent of this section is to
establish an understanding of ENSO's primary teleconnections to Arizona,
to investigate the potential for interannual predictability and to
provide an objective context for evaluating the performance of 1997-98
climate and hydrologic forecasts.

It begins with a discussion of the physical aspects of the ENSO
phenomenon, and investigates its influence on large-scale atmospheric
circulation. It progressively narrows its focus onto the Southwestern
US, reviewing the current understanding of ENSO's impact on
precipitation, streamflow and extreme events. The final section will
describe the 1997-98 El Niño in a similar, telescoping fashion,
beginning in the Tropical Pacific and concluding with the impacts in
Arizona.

## 2.2 The El Niño/Southern Oscillation 

El Niño is the oceanic component of a coupled atmosphere-ocean
interaction occurring in the tropical Pacific. It is characterized by
anomalously warm Sea Surface Temperatures (SSTs) in the eastern Tropical
Pacific Ocean (see figure 3). In contrast, anomalously cold SSTs are
referred to as La Niña (or a "cold event"). These shifts in ocean
temperatures induce a regional atmospheric response that, in turn, has
an impact on global atmospheric circulation. The local atmospheric
response is referred to as the "Southern Oscillation" and the entire
phenomenon is collectively known as the El Niño/Southern Oscillation or
ENSO. For the purposes of this study, the terms "El Niño" and "ENSO
events" are used interchangeably to indicate warm ocean conditions and
the accompanying atmospheric response. Figure 4 illustrates the major
climate features influenced by El Niño, discussed subsequently (shown
during normal conditions).

The phenomenon as a whole is the dominant global climate signal on
interseasonal and interannual timescales and it is the subject of an
extensive body of research dating back to the early part of this
century. The early history of ENSO-related research is summarized by
Rasmusson (1984). Walker's publications in the early 1920's documented
the existence of three atmospheric oscillations, what are commonly known
today as the North Atlantic Oscillation, the North Pacific Oscillation
and the Southern (or more properly "Equatorial") Oscillation (Walker,
1928). At the time, the Southern Oscillation was recognized as an
atmospheric regime shift in the Tropical Equatorial Pacific that
influenced the Indian Monsoon. The intensity of the Southern Oscillation
is

[]{#__RefHeading___Toc463882013 .anchor}Figure 3![](media/image3.png)
SST Comparison of La Niña, normal and El Niño conditions. Warm colors
indicate anomalously warm SSTs, measured in degrees Celcius (From TAO
Project Office/PMEL/NOAA)

[]{#__RefHeading___Toc463882014 .anchor}Figure
4![](media/image4.png){width="5.995833333333334in" height="3.0375in"}
Schematic of major Tropical features under normal conditions. During El
Nino conditions, the cooler water of the eastern Pacific becomes warmer,
the trade winds slow (or change direction) and atmospheric convection
shifts to the east. During La Nina, cool water in the eastern Pacific
becomes cooler and the major atmospheric features become intensified.

typically measured by the surface pressure difference between Tahiti
Island and Darwin, Australia. A time series of this "Southern
Oscillation Index" (SOI) is shown in figure 5 and the locations of
Darwin and Tahiti are shown in figure 4.

In the 1960's, Bjerknes established the connection between the Tropical
atmosphere, ocean and global circulation, despite a lack of adequate
ocean data (Bjerknes, 1966). Bjerknes hypothesized that during normal
periods, the SST gradient from the western (warm) Pacific to the east
(cold) induced a latitudinal Walker Circulation cell. This included
atmospheric convection in the western Pacific, subsidence in the east,
an east to west transport of air at the surface and the opposite in the
upper

[]{#__RefHeading___Toc463882015 .anchor}Figure 5

parts of the atmosphere (a clockwise circulation as viewed in cross
section from the south). However, during El Niño episodes, this SST
gradient is reduced and the trade winds weaken, causing a shift in the
surface pressure patterns (linking it to the Southern Oscillation).
Figure 3 compares SSTs during normal conditions and during a strong El
Niño event. The two events were then recognized collectively as the El
Niño/Southern Oscillation. Subsequent researchers (Angel, 1981;Arkin,
1982; Pan and Oort, 1983; Rasmusson, 1984) have further refined these
concepts.

The ocean influences the atmosphere, but the trade winds influence the
amount of oceanic upwelling in the Eastern Pacific Ocean. Wyrtki
proposed that the trade winds help contain the pool of warm water in the
western Pacific (causing higher sea levels and a deepened thermocline).
When this circulation begins to fail, the pool responds by shifting the
warm water to the east. This warm water then inhibits oceanic upwelling
at the eastern end of the tropical Pacific and prevents new cool water
from reaching the surface (Wyrtki, 1975). Along with its manifestations
at the ocean-atmosphere interface (through surface pressure and SSTs),
it has been increasingly recognized that the ocean subsurface
temperatures and currents are crucial to determining the evolution and
intensity of various El Niño events. However, it was not until the early
1990's that this kind of ocean data was routinely collected by the
Tropical Ocean Global Atmosphere (TOGA) monitoring array.

Although the mechanism that causes ENSO is still unclear, despite
in-depth research (e.g. Battisti and Sarachik (1995), Wallace and Jiang
(1987), and Graham and White (1988), among others), its persistence,
alone, makes it valuable for seasonal prediction. The early signs of
development of a warm El Niño event (falling sea level pressures and
warming ocean temperatures) precede Northern Hemisphere winter
teleconnections by several months (Horel and Wallace, 1981). Beyond the
tropical ocean's striking persistence from June to January within one
year, events can last up to several years (as is evidenced by the
persistent weak El Niño from 1990-95). La Niña events also have a
propensity for extending beyond one year (e.g. 1954-57). Generally, warm
events occur non-periodically approximately once in four years with a
range from two to seven years between events. However, the frequency of
El Niño events (and the relative lack of La Niña events) in the latter
part of this century is believed to be exceptional. (Eltahir and Wang,
1999).

As research has fostered an understanding of ENSO as a multifaceted
phenomenon, developing a robust index of the strength and development of
ENSO events has been a challenge. In contrast to indices that provide a
limited description of events (such as SSTs or SOI), the Multivariate
ENSO index (MEI) blends gridded information about SSTs, total
cloudiness, sea level pressure, air temperatures and wind fields (Wolter
and Timlin, 1993). A time series of this index is included in figure 6.

The direct impact of ENSO on the local climate of the Pacific is
significant. For example, the cessation of upwelling of nutrient-rich
water in the eastern Pacific can contribute to the migration of fish and
the collapse of local fishing industries. Additionally it can bring
heavy flooding to western equatorial South America and severe droughts
to Indonesia. (Glantz, 1984). However, it can also impact extratropical
regions through disturbances in the large-scale atmospheric circulation.
Further reading on the manifestation of ENSO in the tropical Pacific and
attempts to model it can be found in: Rasmusson (1984), Rasmusson and
Carpenter (1982), Delecluse et al. (1998),
Philande![](media/image6.png){width="6.0in"
height="2.1041666666666665in"}r (1992) and Graham and White (1988) among
others.

[]{#__RefHeading___Toc463882016 .anchor}Figure 6 Multivariate ENSO Index
time series 1950-99. Positive values indicate El Nino conditions, and
negative values indicate La Nina. See figure 24 for a monthly comparison
of strong El Nino events. MEI is a composite index, considering numerous
oceanographic and meteorological aspects of El Nino, in a spatially
distributed manner, leading to a more robust measure of the phenomenon.
MEI developed by Wolter and Timlin. (From NOAA/CDC)

## 

## 

## 2.3 Teleconnections

### 2.3.1 Large Scale Circulation

The effect of ENSO on mid-latitude circulation has been investigated and
modeled in many studies (e.g. Alexander, 1992a; Alexander, 1992b; Fu et
al., 1986; Hamilton, 1988; Horel and Wallace, 1981; Keables, 1992;
Kiladis and Diaz, 1989; Lau, 1997; Lau and Nath, 1996; Pan and Oort,
1983; Trenberth et al., 1988; Trenberth and Guillemot, 1996; Wallace and
Gutzler, 1981; Wallace and Jiang, 1987 to begin with). In brief, the
changes in atmospheric convection patterns in the Tropical Pacific
perturb the extratropical circulation through a Rossby wave train.
Briefly, atmospheric convection in the tropics and subduction in the
midlatitudes are a connected system and when the location of convection
in the tropics changes, this disturbance is propagated to the
midlatitudes through a series of waves. This wave train deepens and
shifts southward the Aleutian low, creates a ridge in western Canada and
produces a trough in the Southeastern US. Additionally, the
strengthening of the jet stream is related to increased northward flux
of angular momentum from an enhanced Hadley circulation (Schonher and
Nicholson, 1989). These features, shown in figures 7-11 (especially
figure 7), bear a strong resemblance to a similar analysis by other
researchers (Horel and Wallace, 1981; Wright, 1977; Wright, 1978; Arkin,
1982). Horel and Wallace note the similarity of this pattern to the
Pacific North American (PNA) and West Pacific patterns. The PNA pattern
does not appear exclusively under warm ENSO conditions, but it is
recognized as one of the "bridges" through which the Tropical Pacific
affects the extratropics. However, PNA lacks interseasonal persistence,
limiting PNA indices' value as stand alone long-lead forecast variables
(Redmond, 1988).

The atmospheric response to individual ENSO events depends on several
factors. The timing of the ENSO event (i.e. its season of development)
influences how it impacts large-scale circulation (Kumar and Hoerling,
1997; Piechota and Dracup, 1997). In addition, where the event develops
in the Pacific (e.g., events confined to the eastern pacific versus warm
pools that extend farther west) is important (Fu et al., 1986). Strong
warm ENSO events (e.g., the 1982-83 and 1997-98 events) have an
influence that is different from other, weaker events both in terms of
anomaly magnitude and configuration (for example, compare figures 8 and
9). Finally, rarely is ENSO the only influencing factor. Northern
Pacific SSTs play a critical role in Northern Hemisphere circulation,
serving to enhance or diminish the impacts of ENSO on the Southwestern
US. However, in total, these seasonal patterns are favorable to guiding
more frequent and stronger individual systems into the Southwestern US
(Rasmusson, 1983; Rasmusson, 1984).

[]{#__RefHeading___Toc463882017
.anchor}![](media/image7.png){width="4.395833333333333in"
height="3.9791666666666665in"}**Figure 7** Southern Oscillation Index
correlation with Oct-Mar 700 mb Geopotential Height (top) and Oct-Mar
200 mb wind speed (bottom). Positive values indicate lower
heights/reduced wind speeds during El Nino events. The lower figure
indicates an enhanced, southward-displaced jet stream during El Nino and
vice versus during La Nina.

[]{#__RefHeading___Toc463882018 .anchor}Figure 8 October-March 700 mb
Geopotential Height Climatology (1968-96) (top) and mean anomaly for all
El Nino years 1963-96 (bottom). The lower figure indicates a tendency
for enhanced zonal flow during El Nino years.

![](media/image9.png){width="4.385416666666667in" height="3.875in"}

[]{#__RefHeading___Toc463882019
.anchor}![](media/image11.png){width="4.28125in" height="3.875in"}Figure
9 October-March 700 mb Geopotential Height Anomaly 1982-83 (top) and
1997-98 (bottom). Compare with figure 8 (note scale change).

[]{#__RefHeading___Toc463882020
.anchor}![](media/image13.png){width="4.28125in"
height="3.8645833333333335in"}Figure 10 October-March 200 mb wind
climatology (1968-96) (top) and mean anomaly for all El Nino years
1963-96 (bottom). Lower figure indicates southerly displacement and
enhancement of jet stream during El Nino years.

[]{#__RefHeading___Toc463882021
.anchor}![](media/image15.png){width="4.291666666666667in"
height="3.875in"}Figure 11 October-March 200 mb wind anomaly 1982-83
(top) and 1997-98 (bottom). Compare with figure 10 (note scale change).

### 2.3.2 Precipitation in Arizona

Early research indicated that ENSO could be responsible for changes in
precipitation and temperature patterns in North America (Nemias and
Cayan, 1984; Ropelewski and Halpert, 1986). Ropelewski and Halpert
recognized, among other things, the tendency for above normal
precipitation in northern Mexico in October to March during warm ENSO
conditions. Andrade and Sellers uncovered a relationship between warm
ENSO events and wetter than normal fall and spring (but not winter)
conditions in New Mexico and Arizona (Andrade Jr and Sellers, 1988).
This correlation was regionally strongest over the Salt and Upper Gila
river basins. They attribute this relationship partly to anomalously
warm SSTs off the coast of California and western Mexico during El Niño
causing more and stronger west-coast troughs. Warm Californian coastal
SSTs also favor the low-level transport of moisture into the region. The
dynamics associated with this interaction between coastal SSTs and
southwestern rainfall is explored further by Douglas and Englehart
(1983) and Ramage (1975). Andrade and Sellers also note that only during
the strongest warm ENSO events would Tropical Pacific hurricanes (like
Nora and Octave) impact Arizona and/or California. In September, the
peak month for tropical Pacific hurricane recurvature (i.e. when storm
tracks become increasingly northward instead of westward), 3.4 tropical
cyclones per year are generated, on average, during warm ENSO years
versus 2.3 developing during non-ENSO years (Webb and Betancourt, 1992).

While there is a vast body literature on the impact of ENSO on
California (e.g. Haston and Michaelsen, 1994; Haston and Michaelsen,
1997; Michaelson and Daily, 1983; Mitchell and Blier, 1997; Mo and W,
1998; Ramage, 1975; Raphael and Mills, 1996; Schonher and Nicholson,
1989; Yarnal and Diaz, 1986 among others), few studies have specifically
addressed the impacts of ENSO on Arizona. This imbalance is surprising,
considering that ENSO's signal in Arizona is stronger than California
(partially because California rainfall is strongly influenced by local
ocean conditions weakly related to ENSO). The impact of ENSO on Arizona
was emphasized in Redmond and Koch's definitive work on western surface
hydrology and ENSO (Redmond and Koch, 1991). They begin by synthesizing
a series of past works that identify an out-of-phase relationship
between the climate of the Pacific Northwest and the Southwestern US,
noting this as one of the dominant modes of western climate variability.
Their exhaustive analysis of climate division precipitation and
temperature data shows that this north-south dipole is a manifestation
of the impacts of ENSO. During warm El Nino events, the wintertime storm
track (jet stream) is displaced to the south and intensified, increasing
the likelihood that storms will affect the Southwestern US (and, in
turn, reduce the likelihood that they will affect the Pacific
Northwest). Their study finds that the influence ENSO on precipitation
is most clear in Arizona. With the exception of one division in Utah,
the division in Arizona with the *lowest* correlation coefficient
between October-March precipitation and June-November SOI is still
*greater* than any of the other divisions in the Western US. This means
that ENSO-based seasonal precipitation forecasts have the potential for
being the most accurate specifically in Arizona, when compared to the
rest of the Western US.

Redmond and Koch then discuss the impact of PNA on the western US,
finding that the relationship in the Southwestern US is not as clear as
with SOI. Subsequently it has been discovered that the PNA index can be
modified to better reflect Southwestern US precipitation (Keables, 1992;
Woodhouse, 1997). Aside from Andrade and Sellers, Woodhouse is the only
study focusing specifically on ENSO and Southwestern US
hydrometeorology, in detail. She finds that the impact of ENSO on
temperature is clearer than the number of rainy days. Future research
remains to identify exactly what qualities of precipitation are
influenced by ENSO, be it number of rainy days, intensity of
precipitation or some other variable. Preliminary research suggests,
however, that at least in the Salt River region, the enhanced
precipitation manifests itself primarily as the most intense storm
events (Cayan and Webb, 1993).

The relationship between El Niño and Arizona precipitation is far from
deterministic. As shown in plots of October-May precipitation totals
versus June-November SOI in figures 12-14 (following the methodology of
Redmond and Koch, 1991), there is significant scatter during El Niño
events, some being extremely wet, others relatively mild. The impacts of
El Niño and La Niña are also not completely symmetrical: while La Niña
implies drier than normal conditions, there is considerably less
variability during La Niña years than El Niño years. For example, in
Southeast Arizona, there have been wet and dry El Niño winters, but
there have almost never been any "wet" La Niña winters. Finally, the
existence of extremely wet years when SOI is neutral reaffirms that El
Niño is not the sole influence over Arizona's winter rainfall.

[]{#__RefHeading___Toc463882022
.anchor}![](media/image17.wmf){width="6.0in"
height="7.013888888888889in"}Figure 12 October to May total
precipitation versus June to November SOI (1934-98), Upper Colorado
River basin regions. Area 48: Western Colorado, Area 49: Southwestern
Wyoming, Area 83: Northeastern Utah, Area 84: Southern Utah. Correlation
coefficent of all years provided by each graph. 1997-98 indicated by
circled dot. See figure 2 for regions.

[]{#__RefHeading___Toc463882023
.anchor}![](media/image18.wmf){width="6.0in"
height="7.013888888888889in"}Figure 13 October to May total
precipitation versus June to November SOI (1934-98), Western Lower
Colorado River basin regions. Area 94: Southeastern California, Area 95:
Las Vegas region, Nevada, Area 96: Southwestern Arizona, Area 97:
Northeastern Arizona. Correlation coefficent of all years provided by
each graph. 1997-98 indicated by circled dot. See figure 2 for regions.

[]{#__RefHeading___Toc463882024
.anchor}![](media/image19.wmf){width="6.0in"
height="7.013888888888889in"}Figure 14 October to May total
precipitation versus June to November SOI (1934-98), Eastern Lower
Colorado River basin regions. Area 98: Southeastern Arizona, Area 99:
Northwestern Arizona, Area 101: Western Central New Mexico, Area 102:
Southwestern New Mexico. Correlation coefficent of all years provided by
each graph. 1997-98 indicated by circled dot. See figure 2 for regions.

### 2.3.3 Streamflow in Arizona 

The influence of ENSO on streamflow is more robust than its influence on
precipitation. Streamflow integrates the response of an entire watershed
and it can be thought of as a low-pass filter for atmospheric
variability. Typically, point measurements of rainfall posses
significant noise because they do not capture the spatial variability of
precipitation. Additionally, rainfall measurements are frequently taken
at lower elevations in more easily accessible locations. While radar and
satellite estimates of rainfall alleviate this problem somewhat,
long-term records exist only for low altitude raingauge measurements.
However, streamflow measurements also have problems. Prior to the late
1980's, researchers were reluctant to extend precipitation studies into
streamflow, primarily because of complicated surface processes such as
evapotranspiration. For example, in deserts, only 3 percent of the
precipitation entering a system reappears as streamflow (Sellers, 1965).

Cayan and Peterson show that the Western US rivers with the strongest
correlation between seasonal SOI and seasonal streamflow are located in
Arizona (the Virgin, Salt, Gila and San Pedro) and the Pacific Northwest
(Cayan and Peterson, 1989). Rivers in Arizona have correlation
coefficients on the order of --0.5 (indicating El Niño implies wet
conditions), whereas the Pacific Northwest have coefficients of 0.5 (El
Niño/dry), bearing a remarkable resemblance to Redmond and Koch's
north-south dipole.

Redmond and Koch (1991) also discuss the impacts of ENSO on streamflow,
using split sample correlation analysis on, among others in the Western
US, the Gila River in eastern Arizona. Comparing water year
precipitation with June-November SOI, they arrive at conclusions similar
to Cayan and Peterson, although with a more modest correlation
coefficient (-0.39). The correlation is only reduced in the Southwest
however; the relationship in the Pacific Northwest is still strong. One
explanation is that Cayan and Peterson's analysis is seasonally based,
whereas Redmond and Koch's analysis is based on water year totals.
Water-year streamflow totals in Arizona are contaminated by summer
monsoon streamflow, which is largely uninfluenced by ENSO
teleconnections. In addition, northern basins are snow dominated and
will exhibit more of the high-frequency noise filtering type behavior as
discussed previously in this section.

The influence of Type 1 ENSO events (such as 1982-83 and 1997-98) on
Southwestern US streamflow are stronger than typical ENSO events. Type 1
events have the largest regions of anomalously warm SSTs, extending from
the coastal eastern Pacific to far into the western Pacific warm pool
(see Fu et al., (1986) for further discussion of the classification of
ENSO events). In addition, while the Upper Colorado River basin does not
have a consistent signal during all El Niño years, the relation during
only Type 1 events is clear and strong (wet). (Kahya and Dracup, 1993;
Kahya and Dracup, 1994)

Similar to precipitation, streamflow conditions during La Niña are more
reliably dry than during El Niño, as shown in figure 15. In the case of
Gila River inflow to San Carlos Reservoir, the lack of wet years during
La Niña is striking. Several El Niño years experienced less than normal
streamflow, indicating that the impacts of El Niño and La Niña may not
be completely symmetrical.

[]{#__RefHeading___Toc463882025
.anchor}![](media/image20.wmf){width="6.0in"
height="7.013888888888889in"}Figure 15[]{#__RefHeading___Toc462466168
.anchor} Spring-melt streamflow versus June-November SOI. January-May
Cumulative Streamflow for Salt, Verde, Gila (1934-98). April-July
Cumulative Streamflow for Lake Powell (1963-98). Correlation coefficent
of all years provided by each graph. 1997-98 indicated by circled dot.
Streamflow units are Millions of acre-feet.

### 2.3.4 Extreme Events in Arizona

There are several examples of extreme flooding events during El Niño
years but the limited number of ENSO events, combined with the rare
nature of flooding makes it difficult to establish statistically
significant relationships. Most of the largest floods on large rivers in
Arizona have occurred during or within six months following the
cessation of El Niño conditions (Cayan and Webb, 1993). Large Arizona
and Southern Utah winter floods occur almost exclusively during
conditions when the 5-year running mean of SOI is negative, indicating
persistent El Niño conditions (Ely, 1997). Exceptions to this rule
appear during brief strong El Niño events amidst longer La Niña events
(eg. 1957, 1976).

Webb and Betancourt refine this by indicating that on the Santa Cruz
River, near Tucson, flooding is only more intense during ENSO events,
not more frequent (Webb and Betancourt, 1992). This view is reinforced
by Cayan and Webb's 1993 analysis of Salt River flows. Additionally, the
mean discharge is not increased, but the variance and skew are different
when comparing warm ENSO and non-ENSO flooding populations. In brief,
large floods during warm ENSO events are much larger than non-ENSO
floods. However, a forecast for flooding, based on knowledge of ENSO
conditions alone, has no skill above climatology, at least in terms of
frequency. This is reinforced by figure 16, which shows that there exist
many El Niño years where flooding did not occur, but, when it did occur,
it was extreme. A history of recent large floods occurring during warm
ENSO events is provided in chapter four.

[]{#__RefHeading___Toc463882026
.anchor}![](media/image21.wmf){width="6.0in"
height="7.013888888888889in"}Figure 16 Spring-melt daily peak flow
versus June-November SOI. January-May peak Streamflow for Salt, Verde,
Gila (1934-98). April-July peak streamflow for Lake Powell (1963-98).
Correlation coefficent of all years provided by each graph. 1997-98
indicated by circled dot. Streamflow units are 1000's of cfs.

### 2.3.5 Summary of Teleconnections

El Nino indicates the presence of anomalously warm SSTs in the eastern
Tropical Pacific whereas La Nina indicates anomalously cold SSTs. Its
associated tropical atmospheric response/forcing is known as the
Southern Oscillation and the coupled interaction between ocean and
atmosphere is the El Nino/Southern Oscillation (ENSO). The occurrence of
El Nino is aperiodic, with an average frequency of once every four
years, but several years can go between events and events can last more
than one year. Standard measures of the strength of an El Nino event
include the Southern Oscillation index, Nino 3.4 Sea Surface
Temperatures and the Multivariate ENSO index.

El Nino impacts Western US atmospheric winter circulation by
intensifying and shifting southward the Jet Stream causing more frequent
and stronger storms to affect the Southwestern US. It also favors
PNA-like circulation, with a deepened Aleutian low. El Nino is
associated with wetter winter conditions (both in terms of precipitation
and streamflow). Early winter wetness (September-October) is caused by
tropical cyclones entering Arizona (e.g. Hurricane Nora, Octave). La
Nina is associated with drier winter conditions. While the impacts of El
Nino and La Nina are somewhat symmetrical, La Nina impacts on Arizona
are more reliable than El Nino. There are several examples of
exceptionally large floods which have occurred in past El Nino years,
but it is believed that flooding is not more frequent during El Nino,
only more intense when it does occur.

## 

## 2.4 The 1997-98 El Niño

### 2.4.1 Introduction

Although hailed as the "climatic event of the century", the 1997-98 El
Niño must be placed objectively in the context of the historical record.
The following section examines the event's evolution in the Pacific
compared to past events, as well as its hydrologic impacts in Arizona.
Also, the parallel development of these natural events and Arizona
agencies' preparation are examined, with special emphasis paid to the
event's primary impact on Arizona: Hurricane Nora. This chapter provides
a foundation for assessing the accuracy of the hydrologic and climate
forecasts (performed in chapter three).

### 2.4.2 Initial Conditions

The actions taken by agencies in Arizona in preparation for the winter
of 1997-98 can be partially understood by considering the status of
Arizona reservoirs prior to the event. After the 1992-93 winter floods,
Arizona entered extended dry conditions with 1995-96 standing out as a
historically dry year (figures 17-21). Within Arizona, low reservoir
levels provided an extra buffer against the potential of flooding on
some major rivers (figures 22-23). At the most extreme, the San Carlos
reservoir along the Upper Gila was 92.7% empty and special actions were
taken in the summer of 1997 to retain water in the reservoir to prevent
the devastation of fish populations.

[]{#__RefHeading___Toc463882027
.anchor}![](media/image22.wmf){width="6.0in"
height="7.013888888888889in"}Figure 17 Salt River water balance 1914-98.
Top: Water year inflow, white bars indicate Jan-May relative
contribution. Middle: Water year outflow (deliveries). Bottom: Total
reservoir storage, dashed lines indicate maximum\' storage. All units
Million acre-feet.

[]{#__RefHeading___Toc463882028
.anchor}![](media/image23.wmf){width="6.0in"
height="7.013888888888889in"}Figure 18 Verde River water balance
1938-98. Top: Water year inflow, white bars indicate Jan-May relative
contribution. Middle: Water year outflow (deliveries). Bottom: Total
reservoir storage, dashed lines indicate maximum\' storage. Compare the
interannual variability of the Verde reservoirs with those of the Salt
(figure 17). All units Million acre-feet.

[]{#__RefHeading___Toc463882029
.anchor}![](media/image24.wmf){width="6.0in"
height="7.013888888888889in"}Figure 19 Gila River water balance 1915-98.
Top: Water year inflow, white bars indicate Jan-May relative
contribution. Middle: Water year outflow (deliveries). Bottom: Total
reservoir storage, dashed lines indicate maximum\' storage. All units
Million acre-feet.

[]{#__RefHeading___Toc463882030 .anchor}Figure 20 Colorado River water
balance 1922-98. Top: Water year inflow to lake Powell, Second: Lees
Ferry Streamflow (Powell Outflow) white bars indicate Apr-Jul relative
contribution. Third: Hoover Dam Water year outflow\' (deliveries).
Bottom: Water Year deliveries at Mexican-US Border.

![](media/image25.wmf){width="6.0in" height="7.013888888888889in"}

[]{#__RefHeading___Toc463882031 .anchor}Figure 21 Colorado River
reservoir status 1922-98. Top: Lake Powell storage versus maximum.
Middle: Lake Mead Storage and maximum conservation. Bottom: Lake Mead
and Lake Powell total conservation storage. All units Million Acre-Feet.
Current Reservoir levels similar to 1983-86 period.

![](media/image26.wmf){width="6.0in" height="7.013888888888889in"}

[]{#__RefHeading___Toc463882032
.anchor}![](media/image27.wmf){width="6.0in"
height="7.013888888888889in"}Figure 22 Colorado reservoir status
1990-98. Top: Lake Powell, Middle: Lake Mead, Bottom: Combined storage
of Mead and Powell. The increased variability of Lake Powell storage
reflects a different management style than Lake Mead.All units Million
Acre-feet.

[]{#__RefHeading___Toc463882033
.anchor}![](media/image28.wmf){width="6.0in"
height="7.013888888888889in"}Figure 23 Salt River Project and Gila River
reservoir status 1990-98. Top: Salt (dashed) and Verde (solid)
reservoirs versus maximum capacity. Note lowering of Verde reservoirs in
Summer/Fall 1997 in anticipation of El Nino. Bottom: San Carlos
reservoir. Note cessation of releases Summer 1997 to preserve fish
populations. All units Million Acre-feet.

[]{#__RefHeading___Toc462466292 .anchor}Table 1. Arizona Reservoir
Status 1997-98

+----------+------+------+------+------+------+-------+-----+-------+
| R        | R    |      |      |      | Min  |       | Pe  |       |
| eservoir | eser |      |      |      | imum |       | ak\ |       |
| System   | voir |      |      |      |      |       | Da  |       |
|          | Sto  |      |      |      | D    |       | ily |       |
| Name     | rage |      |      |      | aily |       | S   |       |
|          |      |      |      |      | Sto  |       | tor |       |
|          |      |      |      |      | rage |       | age |       |
+----------+------+------+------+------+------+-------+-----+-------+
|          | Oct  |      | Oct  |      |      |       |     |       |
|          | 1    |      | 1    |      |      |       |     |       |
|          | ^st^ |      | ^st^ |      |      |       |     |       |
|          | 1997 |      | 1998 |      |      |       |     |       |
+----------+------+------+------+------+------+-------+-----+-------+
|          | kA   | \%   | kA   | \%   | \%   | Date  | \%  | Date  |
|          | c-Ft | full | c-Ft | full | full |       | f   |       |
|          |      |      |      |      |      |       | ull |       |
+----------+------+------+------+------+------+-------+-----+-------+
| Salt     | 6    | 30.7 | 9    | 48.3 | 29.6 | Oct   | 6   | Jun 2 |
|          | 22.5 |      | 78.5 |      |      | 26    | 1.2 |       |
+----------+------+------+------+------+------+-------+-----+-------+
| Verde    | 1    | 43.8 | 1    | 55.5 | 31.6 | Dec 6 | 99. | Apr   |
|          | 35.6 |      | 71.7 |      |      |       | 2\* | 10    |
+----------+------+------+------+------+------+-------+-----+-------+
| Upper    | 64.6 | 7.3  | 85.0 | 9.6  | 7.2  | Oct   | 3   | May 3 |
| Gila     |      |      |      |      |      | 16    | 0.6 |       |
+----------+------+------+------+------+------+-------+-----+-------+
| Lake     | 23   | 90.1 | 25   | 96.1 | 90.1 | Oct 1 | 9   | Sept  |
| Mead     | ,779 |      | ,140 |      |      |       | 6.7 | 18    |
+----------+------+------+------+------+------+-------+-----+-------+
| Lake     | 22   | 93.8 | 22   | 92.1 | 83.2 | Mar   | 9   | July  |
| Powell   | ,802 |      | ,404 |      |      | 27    | 8.0 | 11    |
+----------+------+------+------+------+------+-------+-----+-------+

\* From April 11-14 1998, 50 kAc-Ft was released from bottom of Verde
system, matching inflow

This situation in Arizona is in contrast to California, which
experienced devastating floods during the winter of 1996-97, and where
there was a special need to repair damaged structures to withstand
consecutive flooding years. In addition, in contrast to Arizona, the
1990's were a wet series of years for the Upper Colorado River basin.
Prior to the event, the major reservoirs along the Lower Colorado River
were the most full they had been since the 1983 floods (see chapter 4
for discussion of the 1983 floods). Table 1 illustrates the status of
reservoirs prior to, during and after the 1997-98 water year.

### 2.4.3 The Tropical Pacific

Determining which aspects of the 1997-98 El Niño were normal or
exceptional is difficult because only one event stands in its class: the
1982-83 event. However, some comparisons can be made between these
events and other El Niño events, revealing some unique aspects of the
1997-98 El Niño, namely its prediction, timing and magnitude.

Advance warning of the 1997-98 El Niño can be traced as far back as
November 1996 when the Scripps Institution for Oceanography's tropical
Pacific Ocean model indicated that an event was impending (Barnett,
1997). This is the first exceptional aspect of the event, because *never
before had such a large event been predicted this far in advance*. (The
Cane-Zebiak model accurately predicted the onset of the 1991 ENSO event
24 months in advance but this event was considerably weaker than the
1997-98 event and, at the time, these model results were ignored by
climate forecasters (Kerr, 1992). Ironically, while frequently viewed as
the best ocean model available, the Cane-Zebiak model performed the
poorest of all models prior to and during the extraordinarily strong
1997-98 El Nino, indicating that, instead, a La Nina event was underway
(Barnston et al., 1999)). In contrast, the 1982-83 El Niño event caught
the scientific community largely by surprise, without predictions or
even knowledge that it was occurring until it had been fully developed
for several months. Part of this surprise was related to aerosols from
the eruption of El Chichon (Mar-Apr 1982) obscuring SST measurements
from space (D Enfield, personal communication 1999).

*The second exceptional aspect of the event was the timing of its
development.* Various El Niño indices, such as the Multivariate ENSO
Index, peaked very early in the season; usually reaching their greatest
magnitude during winter, this event was well established during the
summer (figure 24). The 1982-83 event peaked during the winter and
persisted into the following summer. This may explain why Hurricane Nora
occurred in the fall *before* the 1997-98 event and tropical storm
Octave impacted Arizona in the fall *after* the 1982-83 event.

[]{#__RefHeading___Toc463882034 .anchor}Figure
24![](media/image29.png){width="5.625in" height="4.15625in"}.
Multivariate ENSO Index comparison for strong El Nino events. The rapid
evolution of the 1997-98 event during the summer of 1997 was cause for
alarm. See also figure 6. (From NOAA/CDC)

Despite some indications that something major was developing, it was not
until a number of models agreed and SSTs raised significantly in May
1997 that it was clear that an event was imminent. Also, due to the
persistence of SSTs in the Tropical Pacific ocean from July to January,
once the event was established, the probability was very low that it
would disappear before its impacts were felt in the extratropics. In
June 1997, official announcements were made by the Climate Prediction
Center that a strong El Niño was developing and that this event could
rival the magnitude of the 1982-83 event (CPC/NCEP, 1997).

Equally as unusual as its development was its rapid departure in June
1998. In contrast, the 1982-83 event lingered especially long into
October 1983. In 1998, warm SSTs were replaced by cold SSTs within two
weeks. This was caused by the slow migration of a large pool of
anomalously cool water, at depth, from the western Pacific to the
eastern parts during the winter of 1997-98. The rejuvenation of the
trade winds favored upwelling and brought this pool rapidly to the
surface. This is an example of how knowledge of sea sub-surface
temperatures can greatly expand ones understanding of events (and,
without doubt, their predictability).

*The third, and most well known, exceptional aspect of this event was
its magnitude.* Prior to this event, the magnitude of the 1982-83 El
Niño stood out as a singularity. By several measures, this event was
greater than the 1982-83 event (figure 24). While 1997-98 SOI did not
rival the 82-83 event, various SST indices from June to December 1997
broke existing records, with temperature anomalies as much as five
degrees Celsius above normal.

### 2.4.4 Large Scale Circulation

Large-scale circulation during the 1997-98 El Niño possesses the
distinguishing features of past large El Niño events: a deepened
Aleutian Low, high pressures over Canada and low pressures in the
southeastern US. These features are not as extreme as anomalies during
the 1982-83 event, but their configurations are similar (figures 7-11).
The distinctly non-ENSO features in the large-scale circulation
surrounding the Atlantic and US Gulf Coast are due to the strong North
Atlantic Oscillation event occurring simultaneously to the 1997-98 El
Niño event.

### 2.4.5 Southwestern US Precipitation

Precipitation in the Southwest during the 1997-98 El Niño has three
interesting features. The first aspect, Hurricane Nora, commands special
attention because of its unusual nature and the impact that it had on
preparations for the impending winter. In addition, an exceptionally wet
February and March were accompanied by an unusually dry January across
many parts of the state.

In September 1997, two hurricanes, Linda and Nora threatened the
Southwestern US. On September 12, Hurricane Linda entered the record
books as the strongest eastern Pacific Hurricane with wind speeds up to
160kts. However, the damages that it incurred were minimal because it
largely avoided land, although some of the long-range forecasts
indicated that it would impact California. A Pacific Hurricane track map
of the 1997 season is included at the end of this section (figure 42) to
illustrate the path of Linda. In contrast, while weaker, Hurricane Nora
caused considerable damage because of its path over land, causing
hundreds of millions of dollars in agricultural damages alone. Hurricane
Nora is described in more detail at the end of this section.

Precipitation totals for individual months during the water year 1997-98
for every CPC climate forecast division in the Colorado River Basin is
provided in figures 25-36. In addition, cumulative water year
precipitation totals are plotted. Precipitation during the 1997-98
event, the 1982-83 event and the 1961-90 historical record are compared.
A map of area numbers and corresponding regions is provided in figure 2.

In December, six significant storms passed through central and southeast
Arizona, resulting in above average rainfall in these areas (#96-102).
However, this period was largely uneventful for the upper portions of
the Colorado River Basin with regions 48,49, 83 and 84 having cumulative
water year precipitation totals to this point falling within the driest
tercile of the 1961-90 record.

January, in contrast, was completely without precipitation in some
regions of southeast Arizona and New Mexico, returning water year totals
to the 1961-90 median. During this period, among agencies and in the
media, there was doubt as to the accuracy of the forecasts and whether
El Niño was going to \"happen\" in Arizona. However, by this time,
preparations were completed and there was little agencies could do but
wait.

In February, normally dry Southeast California (areas 93,94 and 95)
experienced extraordinary precipitation. The precipitation totals in
this region for January were beyond the maximum experienced during
1961-90, making water year totals from October to February greater than
what would be seen by the end of an entire "normal" year. Additionally,
in southeastern Arizona (area 98), heavy precipitation fell, granting
Tucson its second wettest February of record. Nearby mountains received
a record 110 inches of snowfall. During this time, media attention to
and mention of El Niño was pervasive. While all of the regions
experienced above median rainfall in February and March, only in
Southern California could it be characterized as "extreme".

Finally, in contrast to 1982-83, rainfall totals in the Upper Colorado
River Basin remained near or below normal for the water year. July was
unseasonably wet contributing somewhat to the inaccuracy of water supply
outlooks in this region. However, the overall the season was mild. This
was also the case for most of New Mexico, which experienced an
exceptionally dry spring, bringing pre-monsoon water year totals closer
to the 1961-90 median.

In summary, with the exception of Southern California and Hurricane
Nora, the peculiarity of rainfall in Arizona during the 1997-98 El Niño
depends on one's perspective. Consistent with past impacts from moderate
El Niño years, above median rainfall was experienced in Arizona, with
many regions experiencing winter cumulative totals marginally within the
wettest third of the record from 1961-90. Additionally, in Arizona,
*winter* rainfall totals were on par with what was experienced during
the winter of the 1982-83 event (but not fall 1983). But, at least as
was portrayed in the media, these were not the anticipated impacts.
These impacts can not be considered *extreme* in the context of 1961-90,
much less the entire period of record. While viewed as the "climatic
event of the century" (implying a return period on the order of 100
years), the 1997-98 El Niño's impacts in Arizona had return period
closer to one decade (figures 37-39).

[]{#__RefHeading___Toc463882035 .anchor}Figure 25 Monthly (top) and
water year cumulative (bottom) precipitation for Area 48 (Western
Colorado). Solid indicates 1997-98, with 1982-83 shown as dashed. In
comparsion, stars indicate the minimum, 66%, 50%, 33% exceedence and
maximum precipitation of 1961-1990. See text for discussion, and see
figure 2 for regions.

![](media/image30.wmf){width="6.0in" height="7.263888888888889in"}

[]{#__RefHeading___Toc463882036
.anchor}![](media/image31.wmf){width="6.0in"
height="7.263888888888889in"}Figure 26 Monthly (top) and water year
cumulative (bottom) precipitation for Area 49 (Southwestern Wyoming).
See figure 25 for explanation, figure 2 for regions and text for
discussion.

[]{#__RefHeading___Toc463882037
.anchor}![](media/image32.wmf){width="6.0in"
height="7.263888888888889in"}Figure 27 Monthly (top) and water year
cumulative (bottom) precipitation for Area 83 (Northeastern Utah). See
figure 25 for explanation, figure 2 for regions and text for discussion.

[]{#__RefHeading___Toc463882038
.anchor}![](media/image33.wmf){width="6.0in"
height="7.263888888888889in"}Figure 28 Monthly (top) and water year
cumulative (bottom) precipitation for Area 84 (Southeastern Utah). See
figure 25 for explanation, figure 2 for regions and text for discussion.

[]{#__RefHeading___Toc463882039
.anchor}![](media/image34.wmf){width="6.0in"
height="7.263888888888889in"}Figure 29 Monthly (top) and water year
cumulative (bottom) precipitation for Area 94 (Southeastern California).
See figure 25 for explanation, figure 2 for regions and text for
discussion.

[]{#__RefHeading___Toc463882040
.anchor}![](media/image35.wmf){width="6.0in"
height="7.263888888888889in"}Figure 30 Monthly (top) and water year
cumulative (bottom) precipitation for Area 95 (Las Vegas Region Nevada).
See figure 25 for explanation, figure 2 for regions and text for
discussion.

[]{#__RefHeading___Toc463882041
.anchor}![](media/image36.wmf){width="6.0in"
height="7.263888888888889in"}Figure 31 Monthly (top) and water year
cumulative (bottom) precipitation for Area 96 (Southwestern Arizona).
See figure 25 for explanation, figure 2 for regions and text for
discussion.

[]{#__RefHeading___Toc463882042
.anchor}![](media/image37.wmf){width="6.0in"
height="7.263888888888889in"}Figure 32 Monthly (top) and water year
cumulative (bottom) precipitation for Area 97 (Northeastern Arizona).
See figure 25 for explanation, figure 2 for regions and text for
discussion.

[]{#__RefHeading___Toc463882043
.anchor}![](media/image38.wmf){width="6.0in"
height="7.263888888888889in"}Figure 33 Monthly (top) and water year
cumulative (bottom) precipitation for Area 98 (Southeastern Arizona).
See figure 25 for explanation, figure 2 for regions and text for
discussion.

[]{#__RefHeading___Toc463882044
.anchor}![](media/image39.wmf){width="6.0in"
height="7.263888888888889in"}Figure 34 Monthly (top) and water year
cumulative (bottom) precipitation for Area 99 (Northern New Mexico). See
figure 25 for explanation, figure 2 for regions and text for discussion.

[]{#__RefHeading___Toc463882045
.anchor}![](media/image40.wmf){width="6.0in"
height="7.263888888888889in"}Figure 35 Monthly (top) and water year
cumulative (bottom) precipitation for Area 101 (Central New Mexico). See
figure 25 for explanation, figure 2 for regions and text for discussion.

[]{#__RefHeading___Toc463882046
.anchor}![](media/image41.wmf){width="6.0in"
height="7.263888888888889in"}Figure 36 Monthly (top) and water year
cumulative (bottom) precipitation for Area 102 (Southern New Mexico).
See figure 25 for explanation, figure 2 for regions and text for
discussion.

[]{#__RefHeading___Toc463882047
.anchor}![](media/image42.wmf){width="6.0in"
height="7.013888888888889in"}Figure 37 Upper Colorado River Basin
regions October to May precipitation exceedence probabilities (1961-90).
1997-98 indicated by dashed lines. Area 48: Western Colorado, Area 49:
Southwestern Wyoming, Area 83: Northeastern Utah, Area 84: Southern
Utah. See figure 2 for regions, and text for discussion.

[]{#__RefHeading___Toc463882048
.anchor}![](media/image43.wmf){width="6.0in"
height="7.013888888888889in"}Figure 38 Western Lower Colorado River
Basin regions October to May precipitation exceedence probabilities
(1961-90). See also figure 37. Area 94: Southeastern California, Area
95: Las Vegas region, Nevada, Area 96: Southwestern Arizona, Area 97:
Northeastern Arizona.

[]{#__RefHeading___Toc463882049
.anchor}![](media/image44.wmf){width="6.0in"
height="7.013888888888889in"}Figure 39 Eastern Lower Colorado River
Basin regions October to May precipitation exceedence probabilities
(1961-90). See also figure 37. Area 98: Southeastern Arizona, Area 99:
Northwestern Arizona, Area 101: Western Central New Mexico, Area 102:
Southwestern New Mexico.

### 2.4.6 Streamflow & Extreme Flooding

Seasonal streamflow totals in Arizona were greater than median but no
significant flooding occurred. The streamflow duration was exceptional,
with accounts of stretches of the rivers that usually cease flowing in
March still flowing in June. However, according to study participants,
less flooding occurred this year than during normal years, Hurricane
Nora being the only example of flooding leading to an emergency. The
cause of this lack of flooding is the subject of debate. Some study
participants attribute the lack of flooding to the extremely dry
conditions in the years prior to the event. Others believe that the even
timing of storms coupled with the dry period in January was optimal for
seasonal streamflow quantities while keeping maximum flow rates below a
hazardous level. The Tucson NWS attributes the lack of flooding to a
split polar jet-stream (as opposed to a tropical jet-stream) bringing
cool temperatures and relatively low snow line altitudes, allowing the
snow to melt evenly over a longer period of time. Compared to 1960-91,
streamflow return intervals were on the order of five years, whereas
peak streamflow along major rivers was, in several locations, below
median.

[]{#__RefHeading___Toc463882050 .anchor}Figure 40 1960-91 Ranked
Spring-melt Streamflow versus 1997-98 (dashed). X axis indicates the
probability of exceedence in any given year. Spring-melt period varies
by basin (eg. Jan-May on Gila, Apr-Jul on Colorado River). The 1997-98
event's exceedence probability is approximately 30%; an event larger
than this can be expected, on average, three times per decade.

![](media/image45.wmf){width="6.0in" height="7.013888888888889in"}

[]{#__RefHeading___Toc463882051 .anchor}Figure 41 1960-91 Ranked Water
Year peak flow versus 1997-98 (dashed). X axis indicates the probability
of exceedence in any given year. Notice the strong skew to the
distribution. All units 1,000 cubic feet/second. Peak flow, here, is
defined as the maximum daily average flow which occurred during a water
year. Exceedence probabilities of the 1997-98 event were near or below
median, supporting the finding that, at least on major rivers, flooding
did not occur.

![](media/image46.wmf){width="6.0in" height="7.013888888888889in"}

### 2.4.7 Hurricane Nora

Arguably, Hurricane Nora was the most significant weather event during
the fall and winter of 1997-98. It was the third tropical storm to
affect Arizona in the last 100 years (Joanne in October 1972 and
Kathleen in September 1976 being the others). In the southwestern
regions of Arizona, as much rain fell in 24 hours as is normally
received during the course of an entire year (1-4 inches). Additionally,
a 24-hour state rainfall record was broken when 11.97 inches fell at a
Maricopa FCD ALERT raingauge on Harquahala Mountain west of Wickenberg.
Runoff from the storm caused the evacuation and inundation of several
towns and damages have been estimated in the hundreds of millions of
dollars.

How the Nora forecasts were used, and how they were perceived have
interesting parallels and contrasts to how agencies used and perceived
the El Niño forecasts. While water management has its seasonal
components, ultimately, it is a day by day activity (as confirmed in
Changnon and Kunkel (1999)). The remainder of this section will be
devoted to analyzing the forecasts of and preparation for Hurricane
Nora.

On September 16, the first evidence of a closed circulation appeared in
the tropical Pacific. As winds increased, the system was upgraded from a
tropical storm to a hurricane on September 18. A full description of the
evolution and dynamics of the hurricane at sea is provided in Rappaport
(1997). As early as September 20, forecasts indicated that the hurricane
would impact coastal regions of Mexico. On September 21 and 22, a system
unrelated to Hurricane Nora deposited rain in the far eastern regions of
Arizona, and western New Mexico (see panel one of figure 43). It caused
significant streamflow in the Upper Gila River (e.g. 9,960-cfs at the
head of Safford Valley, approximately a 5-10 year peak streamflow
event). When forecasts on September 23 indicated that the eye of the
storm would pass through central Arizona and metropolitan Phoenix, it
was cause for alarm (figure 44). A tropical storm traversing the already
saturated soils in the eastern part of the state would have proven
disastrous.

Immediately the Governor held a meeting of state agencies to ensure
preparedness and coordination. Sandbag filling and preparedness field
exercises occurred in central and southwest Arizona. Anticipation for
the event was great and it was extensively covered by the media. Sample
headlines from the Arizona Republic include "Nora Seems On Track For
Arizona. \'Edgy\' Residents Stockpile Supplies; Hull Calls Council."
(9/24) and "State Braces For Rain. Remnants Of Hurricane Expected To
Wreak Havoc On Yuma Area" (9/25). Hurricane Nora also represented the
first time in the office's history that the Tucson National Weather
Service issued a 100% probability of precipitation (Tucson NWS, personal
communication, 1997).

Interestingly, despite widespread alarm and quantitative precipitation
forecast (QPF) estimates of greater than four inches of rainfall on
their basin, the managers of the Salt River Project *did not* alter
their operations. The managers preferred not to act until *monitoring
systems* in the upper reaches of their basin indicated that extreme
streamflow was headed towards the reservoirs. This example is
illustrative of the conservative nature of water providers and it makes
SRP's decision to release water in anticipation of El Niño (detailed
further in chapter five) seem surprising. If this water provider did not
have sufficient confidence in the short-term weather forecasts to act
three days before a major event, releasing water several months in
advance based on a climate forecast appears audacious. However, this
could also mean that SRP recognizes that some climate forecasts are not
necessarily less accurate than weather forecasts, a common misconception
among users (Changnon, 1990).

Late on September 25, Nora entered the United States and brought
precipitation to Southwestern Arizona and Southern California. The
hydrometeorological impacts of Nora on Arizona are investigated in depth
in a report prepared by the Maricopa County Flood Control District
(Waters, 1997). The forecasted rainfall in the central and eastern parts
of the state did not materialize, primarily because the forecast for the
storm's path was displaced hundreds of miles to the east (figure 44) and
the storm passed through the state relatively quickly. Phoenix Sky
Harbor Airport registered 0.03 inches of rainfall and Tucson recorded a
trace, prompting the media in these cities to rename the event
"Hurricane Tracy" and declare "Nada from Nora" and "Nora Fizzles as It
Reaches Arizona" in the headlines. There was very poor perception of the
quality of the forecasts in these major cities. After the event, the
media questioned whether the apocalyptic forecasts for El Niño were as
(in-)accurate as the forecasts for Hurricane Nora.

However, Hurricane Nora did cause considerable damage in the western
part of the state and the perception of the forecasts in that region was
much more favorable. Many regions experienced 1-4 inches of rainfall
with select regions experiencing in excess of 5 inches. The resulting
runoff was mostly confined by flood retention structures. However,
Narrows Dam, on Centennial Wash in La Paz County, was filled and
breached after midnight on the 27^th^. The resulting flow inundated the
city of Aguila (Waters, 1997). In addition, flooding on the Nasagampa
River damaged the city of Wickenberg. While Yuma did not experience
serious flooding, the region is one of the major agricultural centers of
the state and crop damage was estimated in the hundreds of millions of
dollars (\~\$300M), with \$30M damage to lemon trees alone (Rappaport,
1997). Preparation for and cleanup from the event required \$3M of the
Arizona State Department of Emergency Management's (ADEM) \$4M annual
emergency contingency funds (ADEM, personal communication, 1997). ADEM
believes that preparations based on the forecasts for Hurricane Nora
helped mitigate damages, although the precise amount saved is, as
always, difficult to quantify.

In summary, while enhanced fall precipitation from Tropical storms has
been associated with past strong ENSO events (Andrade Jr and Sellers,
1988), Hurricane Nora was viewed as an unusual event that influenced
preparations for the oncoming winter. Damages in the western part of the
state lent credibility to the seasonal forecasts and the possibility for
an extreme winter event. In contrast, poor weather forecasts in the
large cities and eastern part of the state shook the confidence in the
climate forecasts. This lack of confidence in climate forecasts due to
poor weather forecasts has been observed in Pulwarty and Redmond (1997)
and Changnon (1990). Finally, SRP's reluctance to act on the short-range
QPFs illustrates the conservative nature of water providers and further
emphasizes how unusual SRP's actions were to release water from the
Verde system several months in advance.

[]{#__RefHeading___Toc463882052 .anchor}Figure 42 1997 Eastern Pacific
Hurricane Track Chart. The observed paths of Hurricanes Linda and Nora
are 12 and 14, respectively. Hurricane Linda set records for Pacific
Hurricane strength and had an influence on SSTs which, in turn,
influenced Hurricane Nora's path. (From NHC)

![](media/image47.png)

[]{#__RefHeading___Toc463882053 .anchor}Figure 43 GOES 9 Infrared
Satellite Images Sept 21-27 1997. These images depict the approach and
dissipation of Hurricane Nora. Note the heavy storms in New Mexico and
Eastern Arizona on the 21st and 22nd.

![](media/image48.png){width="2.3958333333333335in"
height="3.9270833333333335in"}

[]{#__RefHeading___Toc463882054
.anchor}![](media/image49.png){width="2.359722222222222in"
height="3.9298611111111112in"}Figure 44 Hurricane Nora Storm track,
predicted September 23 (left) and September 24 (right). Solid lines
indicate observed, dotted lines indicate forecasts, colors represent
wind speed. The misplaced storm track from the September 23 forecast
caused forecasts to overestimate rainfall in central Arizona. (From NHC)

### 2.4.8 Summary of 1997-98 El Nino

Three exceptional aspects of the 1997-98 El Nino include its early
prediction, early rapid development and large magnitude. The impacts of
the 1997-98 El Nino on large-scale circulation and the Southwestern US
are consistent with the impacts of previous El Nino events. Arizona
experienced wetter than normal conditions during the winter, especially
December, February and March. However, characterizing the impacts of
this event as extreme is debatable since return intervals for
precipitation and streamflow totals were on the order of 5-10 years. No
significant flooding occurred except when Hurricane Nora traversed the
southwest part of Arizona (whose occurrence is consistent with past El
Nino events), causing approximately \$300M worth of crop damages and
setting a new Arizona 24-hr precipitation record (11.97 inches). The
absence of flooding and non-extremity of precipitation in Arizona during
the 1997-98 El Niño event has the potential to cause confusion about the
accuracy of the forecasts (i.e. the forecasts performed well, but they
were misinterpreted by users who subsequently perceived poor forecast
performance).

# CHAPTER 3

# EVOLVING SEASONAL FORECASTING ABILITY

## 

## 3.1 Introduction

Varieties of climate information products exist, including seasonal
forecasts, produced by an equally varied number of agencies, at
different levels of complexity. The rate of evolution of these climate
products is striking when one considers that the 1982-83 El Niño event
was not only not predicted, but not even discovered until it was near
its peak and well underway for several months. These advances are
occurring as a result of advances in computing facilities, modeling
capability, the availability of remotely sensed data, the extensive
tropical pacific monitoring buoy array, and enhanced overall
understanding of the physical system. Based on continuing technological
advances, and barring a radical shift in climate (physical or
political), one can safely assume that these products will become more
accurate and sophisticated in time. Additionally, dissemination via the
Internet allows this data to be available to scientists and the public
in a timely manner that has not been possible previously. The following
section catalogs some of the major forecast products that are currently
available and characterizes their potential for evolution in the
following years. The final section evaluates the accuracy of some of
these products in more detail, specifically focusing on the 1997-98
seasonal forecasts. A thorough review of hydroclimatic forecast products
applicable to the Southwestern US is provided in Hartmann (1999).

Hartmann (1999) also makes the important distinction between forecasts
and other sources of climate data. Because of the lagged relationship
between activity in the tropical Pacific Ocean and its effects in the
extratropics, some **observed data** has forecasting value but is not
explicitly a forecast product. Realtime measurements of SSTs, SOI, Line
Island Precipitation, MEI and others are examples of this. Analyzing
statistics based on past conditions, any individual can produce
provisional regional forecasts (with varying levels of accuracy). For
example, knowledge that the 1997-98 El Niño would rival the strength of
the 1982-83 El Niño event, allowed some agencies to extrapolate that the
impacts of the 1997-98 El Niño would be much like the 1982-83 event.
This example has very low skill because rarely, if ever, will two years
be climatically identical even if a strong climate driver is in a
similar state in both years.

## 3.2 Climate Forecasts

As of late 1998, the three official seasonal climate forecasts issued by
various offices within the NWS are:

1.  the Tropical Pacific SST forecasts

2.  Seasonal Climate Outlooks

3.  CPC Special Summaries.

4.  ![](media/image50.png){width="5.99375in"
    height="3.761111111111111in"}

[]{#__RefHeading___Toc463882055 .anchor}Figure 45 Official SST Forecast.
Sea Surface Temperatures (left) and anomalies (right) are predicted out
to three seasons ahead. Temperatures depicted in degrees Celsius. These
figures were included in CPC Special Summary 97-3. Accompanying text
warns that, while SSTs anomalies are reduced in Feb-April, absolute
magnitudes will remain high.

The **SST forecasts** (figure 45) are produced monthly and depict the
anticipated state of the tropical Pacific Ocean, predicting the sign,
magnitude and spatial configuration of SST anomalies, indicating the
state of ENSO. An additional product forecasts a time series of the
Niño3.4 SST Index. It forecasts out to two years, although the general
consensus is that the skill of the forecast increases greatly for the
winter season less than one year ahead, during the proceeding spring
(i.e. a forecast produced in May-June of 1999 has high skill for the
winter of 1999-2000). These forecasts have been produced experimentally
by the CPC since September 1992, and were transferred into operational
mode in December 1994. Accompanying the maps is a text discussion of
what tools were subjectively combined to produce the forecast, including
a qualitative measure of the forecaster's confidence in the current
product. The accuracy of these forecasts has been greatly enhanced with
the incorporation of sub-surface ocean data collected by the TOGA moored
buoy array into a host of Tropical Pacific Ocean models. If this
monitoring array remains, it is reasonable to anticipate that the SST
forecasts will improve in coming years.

[]{#__RefHeading___Toc463882056
.anchor}![](media/image51.png){width="6.0in" height="8.0in"}Figure 46
CPC Climate Outlook legend, as provided to users.

[]{#__RefHeading___Toc463882057
.anchor}![](media/image52.png){width="3.8020833333333335in"
height="5.5625in"}Figure 47 CPC Climate Outlooks for precipitation (as
distributed with CPC Special Summary 97-3). Notice the strong
probability shifts over the Southwest in both figures. While the colors
of these figures do not match those colors of the legend (figure 46),
this has since been adjusted. These represent only two of the 13 maps
that are included in the full Climate Outlook product. For
interpretation, refer to figure 46.

Additionally, CPC produces **Seasonal Climate Outlooks** of temperature
and precipitation across the United States (figures 46-47). In its
current form, the outlook has been produced monthly since 1995 although
30 day outlooks have a history as far back as 1947. The current format
includes US maps of probability anomalies for the next single month and
the thirteen consecutive three-month segments (eg. DJF, JFM, FMA) of
average temperature and cumulative precipitation. The contours of the
map indicate the probability of a region experiencing conditions which
would fall into the "above normal", "normal" and "below normal" terciles
of the historical record 1961-1990. For instance, in the absence of
contours, there is an equal (33.3%) chance of the given forecast period
falling into each of the terciles. In this instance, the methods used to
produce the forecasts indicated either this would be so or there was not
any skill above climatology. This distinction is not provided on the
maps. The presence of contours indicates a shift of probabilities from
one end of the distribution into the opposite extreme. For example, a
contour signifying 5-10% probability anomaly of below normal
precipitation indicates that there is a 38-43% probability of the
observed three-month cumulative precipitation totals being below normal,
a 23-28% probability of being above normal and a 33% probability of
being normal (compared to 1961-90). This is true except in the case of
anomalies indicating very large probability shifts, in which the
remaining probability is removed from the middle tercile. The presence
of anomalies indicates that the tools used to produce the forecast have
consensus and/or possess skill.

The CPC Outlooks are produced using a variety of methods, blending
dynamic modeling and statistical techniques, incorporating atmospheric
conditions, SSTs and a variety of other observed data. Each forecast is
a subjective combination of tools that are perpetually upgraded,
incorporating new findings of the scientific community. In this respect,
advances in computer models, the resources available to conduct ensemble
runs and the breadth of data coverage provided by satellites and
Tropical Ocean buoys have greatly enhanced seasonal forecasting
capabilities in recent years. The climate forecasting community
advocates an increased use of dynamic modeling tools in the future, as
the models improve, and less reliance on purely statistical techniques.

The seasonal outlooks were previously distributed in print with the
Experimental Climate Forecast Bulletin including the climatological data
necessary to translate the maps from probabilities to quantities for
various regions. Products earlier than 1995 also included 500-mb charts
and verification data of past forecasts. The CPC climate outlooks are
now freely and widely available via the Internet in a variety of
locations including NOAA sites, regional climate centers and others. The
five components necessary to accurately interpret the CPC outlooks (the
outlooks, their legend, climatological data maps indicating the physical
quantities associated with the tercile boundaries, maps of forecast
skill and a text discussion) more frequently than not become separated
when distributed through sources other than the CPC. Unfortunately, for
the Southwest, having the precipitation climatological data maps (*for
any season*) does not help the user translate the forecasts into
quantities. As shown in figure 48, there is no visible difference
between wet and dry conditions for all seasons.

A host of experimental forecasts, such as the outlooks provided by the
International Research Institute, provides similar information as the
CPC outlooks but are not endorsed by NOAA and are not intended for
general use. Nonetheless, these products are accessible on the Internet
to the public.

Several times a year, as circumstances warrant, a **Special Summary** of
an event and/or special forecast is produced, providing extended
discussion not present in the normal products. Discussion can involve
analysis of a recent event such as flooding, drought or some radical
change in climate conditions and/or the implications of an event on
future conditions. For instance, in November 1997 a special summary was
issued (CPC 97-3) describing El Niño, its anticipated impacts on the US
and the forecasts of SSTs throughout the remainder of the event. A
section of this summary was directed towards the anticipated impacts of
El Niño on various regions around the globe and the United States, with
two sentences devoted to the Southwest US (reproduced here).
"Southwestern United States: This region can expect enhanced wintertime
rainfall at lower elevations and increased snowfall at higher
elevations. The chances of wintertime
![](media/image53.png){width="3.079861111111111in"
height="3.276388888888889in"}drought are significantly reduced across
the region." (CPC, 1997a).

[]{#__RefHeading___Toc463882058 .anchor}

Figure 48 CPC Climate Outlook DJF Precipitation Class Limit Maps. These
maps are provided at the CPC web site and are used to indicate the
definition of "drier than normal" (top) and "wetter than normal"
(bottom) conditions as used in the Climate Outlooks (fig 46-47). Notice
that, for the entire Colorado River Basin, there is no visible
difference between wet and dry conditions. This occurs on all 12 maps,
for all seasons.

In July 1997, a special summary (CPC 97-2) "El Niño Implications for the
1997 Southwest Drought and Fall/Winter Precipitation" analyzed the
current conditions, the extent of the drought in the region and the
anticipated effect of the impending El Niño (CPC, 1997b). It is
exclusively devoted to the Southwestern US and is presumably directed
towards water management entities. The summary presents the results of a
12-day computer climate model simulation forced with "typical El Niño
SST", showing that large-scale circulation patterns are disturbed,
causing higher than normal precipitation in the southwest. It presents
precipitation data about the severity of the current drought across the
Western US. The summary concludes with the CPC climate outlook for the
1997-98 winter and a qualitative forecast that the drought would be
relieved based on compositing of summer, fall and winter precipitation
data from select El Niño events. Strangely, each of the three composites
considers different El Niño events (summer: six events, fall: eleven
events, winter: ten events), and the text provides no explanation as to
why. Additionally, no streamflow or reservoir data is considered in the
report.

Other institutions issue similar special climate products and technical
attachments, such as the Western Regional Climate Center and the
National Weather Service. "El Niño and California Precipitation" and "El
Niño: Is It Just Hot Air?" are two examples from the National Weather
Service Western Region Headquarters (Monteverdi and Null, 1997;
Staudenmaier Jr, 1997). These special summaries often include historical
data about previous El Niño events and their effects. While advances in
computer technology may not enhance the ability to analyze historical
data, the Internet makes this information available to the public.
Interactive Internet sites, such as the NCDC climate division page or
the Western Regional Climate Center's Western U.S. Climate Historical
Summaries page allow general users to investigate the historical record
to conduct independent research free of charge.

## 3.3 Hydrological Forecasts

There are a number of seasonal outlooks provided by the hydrologic
community. The primary hydrologic seasonal forecast, the Water Supply
Outlook (WSO), is produced cooperatively between the Natural Resources
Conservation Service, the National Weather Service, and for select local
rivers, the Salt River Project. There are a number of forecasts similar
to the WSOs, but they are not available to the public and are intended
for internal agency use. For example, forecasts of monthly inflow to
Lake Powell are provided to the Upper Colorado Bureau of Reclamation,
but the public only receives the "lumped" forecast for an entire melt
season. Due to the restricted access to these forecasts, they will not
be considered further here, although, clearly, these individual monthly
forecasts play a significant role in water management. The individual
monthly and seasonal forecasts have been produced in their present form
since the mid-1930's. For the remainder of this text, the terms
"hydrologic forecasts" and "water supply outlooks" will interchangeably
be used to refer to the WSOs.

During select months of the melt season, the WSOs are issued at the
beginning and midpoint of each month. The number of forecasts produced
each year varies on the point being forecasted. With the exception of
the Colorado River, all of the rivers in Arizona are forecast bimonthly
from January 1 to April 1, whereas other basins extend the forecasts out
to June 1. Each of these forecasts provides an estimate of the
naturalized quantity of cumulative streamflow that will pass a forecast
point during a specific period. Naturalized flow is observed streamflow
adjusted for upstream diversions and return flows. The period varies
from one basin to the next and from one forecast to the next because of
the characteristics of the watershed. For example, the inflow to Lake
Powell forecast always describes the period April-July. However, January
forecasts for the Salt River will predict the cumulative streamflow from
January-May.

For the majority of forecast periods, estimates of the 90%, 70%, median,
30%, and 10% exceedence probabilities of quantities of streamflow are
provided (based primarily on forecast error analysis). In other periods,
only the 70%, median and 30% forecasts are provided, and in still
others, only the Median forecast is available. The median forecast is
described as the "Most Probable" outcome and the upper and lower
forecasts as "Reasonable Maximum" and "Reasonable Minimum". Despite the
complicated mix of forecast points, lead times, periods and error
estimates, the forecasts generally remain internally consistent from
year to year. If a point, lead-time and period is forecast one year,
usually the same combination will be forecasted next year.

Table 2 shows WSO forecast points in Arizona, including the period that
the forecast predicts. A sample WSO is included in figure 49. Ancillary
information includes text and numerical descriptions of basin-wide
snowpack, cumulative precipitation, and reservoir status. While,
nationally, the core forecasts are largely similar, the total forecast
packet (including graphics) varies by producing agency or office.

[]{#__RefHeading___Toc462466293 .anchor}Table 2 Water Supply Outlook
Forecast Points in Arizona

  ----------------- ------------------------------------ -----------------
  Watershed         Forecast Point                       Forecasted
                                                         Period\*

  Salt              Salt River near Roosevelt            Jan-May

                    Tonto Creek near Roosevelt           Jan-May

  Verde             Verde River above Horseshoe Dam      Jan-May

  Gila              San Francisco River at Clifton       Jan-May

                    Gila River near Solomon              Jan-May

                    San Carlos Reservoir inflow          Jan-May

  Little Colorado   Little Colorado River above Lyman    Jan-June
                    Lake                                 

                    Little Colorado River at Woodruff    Jan-May

                    Lake Mary inflow                     Jan-May

                    Rio Nutria above Upper Nutria        Jan-May

                    Ramah Reservoir inflow               Jan-May

                    Black Rock Reservoir inflow          Jan-May

  Chuska Mountains  Captain Tom Wash near Two Gray Hills Mar-May

                    Wheatfields Creek near Wheatfields   Mar-May

                    Bowl Canyon Creek above Assayi Lake  Mar-May

                    Clear Creek near Winslow\*\*         Jan-May

                    Chevelon Creek near Winslow\*\*      Jan-May

  Colorado          Virgin River near Littlefield        April-July

                    Lake Powell inflow                   April-July

  San Pedro         San Pedro River near Charleston\*\*  Jan-May
  ----------------- ------------------------------------ -----------------

\* The first forecast of the season is issued January 1 and then
bimonthly until April 1. Forecasts after January 1 are for streamflow
during the remainder of the season. For example, the Verde River
forecast issued on February 1 predicts Feb-May cumulative streamflow.

\*\* Forecast point not available in Basin Outlook Reports, but is
available in the "Spring and Summer Streamflow Forecast Tables" product.

=============================================================

VERDE RIVER BASIN

Streamflow Forecasts - January 1, 1998

> \|\<=== Drier === Future Conditions === Wetter ===\> \|

Forecast Pt \|=============== Chance of Exceeding \* ========\|

Forecast \| 90% 70% \| 50% (Most Prob) \| 30% 10% \| 30 Yr Med

Period \|(kac-ft) (kac-ft) \|(kac-ft) (% median)\|(kac-ft) (kac-ft) \|
(kac-ftAF)

VERDE R abv Horseshoe Dam

JAN-MAY 176 300 380 182 460 571 209

JAN-VOL 40 174 23

\* 90%, 70%, 30%, and 10% chances of exceeding are the probabilities
that the

actual volume will exceed the volumes in the table.

The average and median are computed for the 1961-1990 base period.

\(1\) - The values listed under the 10% and 90% Chance of Exceeding are

actually 5% and 95% exceedance levels.

\(2\) - The value is natural volume - actual volume may be affected by
upstream

water management.

VERDE RIVER BASIN

Reservoir Storage (1000AF) End of December

Usable \*\*\*\*\*\*\*\*\*\* Usable Storage \*\*\*\*\*\*\*\*\*

Reservoir Capacity This Year Last Year Average

VERDE RIVER RES SYSTEM 310.0 104.9 72.0 123.5

VERDE RIVER BASIN

Watershed Snowpack Analysis - January 1, 1998

Number of This Year as Percent of

Watershed Data Sites Last Year Average

VERDE RIVER BASIN 6 0 113

SAN FRANCISCO PEAKS 0 0 0

[]{#__RefHeading___Toc463882059 .anchor}Figure 49 Sample WSO from
NRCS/USDA. Issued January 1^st^ 1998, this WSO predicts the Verde
River's cumulative streamflow during the 1997-98 El Nino winter.
Supplemental information provided in Arizona WSOs include plots of
water-year cumulative precipitation and a time series of snowpack.

The methods used to produce the WSOs are relatively uncomplicated,
performing multiple linear regression forecasting based on variables
such as basin-wide precipitation and snow water equivalent (measured at
individual SNOTEL sites with about 5 to 10 sites per basin). Forecasters
have the option of including "exotic" variables, such as SOI, in the
regression equations but rarely is this option exercised and climate
information is generally not used in WSOs. The linear regression
produces a median estimate of inflow. The remaining 10%, 30%, 70%, and
90% exceedence probabilities are determined using a standard error
analysis assuming normally distributed error. In reality, these
remaining exceedence probabilities are a function of the forecasting
procedure, not the unique circumstances of the season being forecasted.

The techniques of hydrologic seasonal forecasting are relatively stable
and unchanged in recent years. Recent scientific advances have the
potential to enhance the accuracy and sophistication of the forecasts,
such as the availability of remotely sensed snow cover estimates,
advanced hydrologic and climate models, improved scientific
understanding of hydroclimatology and interannual variability, and
sophisticated forecasting tools like neural networks. Additionally, the
Extended Streamflow Prediction (ESP) system is available in parts of the
country but remains to be operationally applied in the Southwest. ESP
enables continuous probabilistic forecast statements, beyond the current
10, 30, 50, 70 and 90% exceedence probabilities, based on ensemble
dynamical model prediction techniques. The lack of progress in
hydrologic seasonal forecasting accuracy could primarily be due to
institutional barriers and constraints imposed on the forecasting
community (Hartmann, 1999; Lee, 1999).

## 

## 3.4 Seasonal Forecast Evaluation

The value of a forecast is ultimately rooted in its accuracy. This
section reviews the performance of the 1997-98 hydrologic and climate
seasonal forecasts; however, an in-depth analysis is beyond the scope of
this research. Forecast evaluation is an arena of new and exciting
research and has the potential to greatly improve future products and
enhance user confidence in existing products. Regrettably, these types
of assessments have only rarely occurred (e.g., Barnston et al., 1994;
Shafer and Huddleston, 1984) and have not focused on the Southwestern US
in detail. The intent of this section is to determine:

1.  What is the typical error/performance of these forecasts in the
    past?

2.  How did the 1997-98 Seasonal forecasts perform compared to
    observations?

3.  How does the performance of the 1997-98 forecasts compare to
    previous forecasts?

### 3.4.1 Hydrologic Forecasts

For the sake of brevity, only forecasts for direct inflow to the major
Arizona reservoirs are considered here. Undoubtedly, other forecast
points have an impact on water allotments to users upstream of
reservoirs (e.g. users in Safford Valley, upstream of the San Carlos
Reservoir). However, preliminary analysis of the other forecasts reveals
that their performance is similar to forecasts for major reservoir
inflow.

The reservoirs considered are Colorado River inflow to Lake Powell, Gila
River inflow to San Carlos Reservoir, Verde River inflow to Horseshoe
Lake and Salt and Tonto Creek inflow to Roosevelt Lake. As described
earlier, each of these forecasts gives a prediction of the cumulative
streamflow from the forecast issuance date to the end of May. The
exception is inflow to Lake Powell, which is a forecast for the
cumulative streamflow from April-July. Plots of the forecasts from
January 1 until April 1 1998 are provided in figures 50-51. These
forecasts are compared to observed cumulative streamflow during the same
period.

January 1 hydrologic median forecasts from 1964 (1954 for Salt and
Verde) to 1998 are compared to observations in figure 52. Because the
1992-93 WSOs grossly underestimated the observations on three of the
basins, logarithms of forecasts and observations are compared in figure
53, to better illustrate the performance of the remaining forecasts. In
a general sense, compared to previous years, the performance of the
1997-98 WSOs is exceptional in all basins. All of the observations fell
within the reasonable maximum and reasonable minimum, with the exception
of Gila River flow after March 1, and many of them fell within the 30%
and 70% confidence bounds.

This remarkable performance can be attributed to two factors. Firstly,
the wet December was indicative of the remainder of the season.
Intraseasonal variability is not captured well by the WSOs and heavy
late winter and spring precipitation can cause serious errors in the
early forecasts. For example, the exceptionally dry January caused

[]{#__RefHeading___Toc463882060
.anchor}![](media/image55.wmf){width="6.0in"
height="7.013888888888889in"}Figure 50. Water Supply Outlooks (Solid)
versus observations (dashed) for winter 1997-98 on Salt and Verde
Rivers. Forecasts are issued bi-monthly on the 1^st^ and 15^th^ of each
month starting January 1^st^. Stars indicate the median forecast (that
the streamflow has a 50% probability of exceeding this amount) and ticks
indicate 10%, 30%, 70% and 90% exceedence probability forecasts
("Reasonable Max and Min"). The y-axis indicates cumulative streamflow
from date of issuance to the end of May. See section 3.3 for further
discussion.

[]{#__RefHeading___Toc463882061 .anchor}Figure 51 Water Supply Outlooks
(Solid) versus observations (dashed) for winter 1997-98 on Gila and
Colorado Rivers. See figure 50 for explanation. It is important to note
that the Colorado River forecast is for *April-July* cumulative
streamflow whereas others are from date of issuance to May (and
therefore, the "observation" for Colorado River flow does not decrease
in time because each forecast is for the same period).

![](media/image56.wmf){width="5.979861111111111in"
height="7.020833333333333in"}

[]{#__RefHeading___Toc463882062 .anchor}Figure 52 January 1^st^ Water
Supply Outlooks versus observations. Years included are 1954-98 for Salt
and Verde and 1964-98 for Gila and Colorado River. 1998 Denoted by a
star.

![](media/image57.wmf){width="6.520138888888889in"
height="7.036111111111111in"}

[]{#__RefHeading___Toc463882063 .anchor}Figure 53 January 1^st^ Water
Supply Outlooks versus observations. Years included are 1954-98 for Salt
and Verde and 1964-98 for Gila and Colorado River. 1998 Denoted by a
star. Same as figure 52 except log scale on both axes.

![](media/image58.wmf){width="6.520138888888889in"
height="7.036111111111111in"}

[]{#__RefHeading___Toc463882064 .anchor}Figure 54 Lake Powell Inflow
Water Supply Outlooks 1964-98. Top: Time Series of forecasts, Bottom:
Forecasts vs Observations with 1998 denoted by a star. Size of dot
indicates issuance date Large black: Jan 1, Blue: Feb 1, Green: Mar 1,
Small red: Apr 1. Blue dot/line: Observations. See text for discussion.

![](media/image59.wmf){width="7.1in" height="7.3597222222222225in"}

all of the February 1 forecasts to drop to a level that underestimated
the observations. If December had been dry, the forecast performance
would have been considerably poorer. As shown in chapter two, ENSO has
an impact on spring precipitation: perhaps using climate information can
increase the accuracy of these forecasts early in the season.

Second, WSOs perform best under "normal" conditions. As is shown in
figures 52-53, the tendency of the forecasts is to underestimate high
streamflows and overestimate low streamflows. For example, the Verde and
Gila forecasts always underestimate streamflow above 500,000 acre-feet
(something that has occurred during 9 of the past 35 years on the Gila).
While the maximum difference between observations and forecasts seems to
be roughly 300%, when this difference is translated to physical
quantities, the volume of unanticipated streamflow can be disastrous.
This is especially true when reservoirs are full, as was the case in
1983 along the Colorado River. Because the 1997-98 season was somewhat
above normal, but certainly not exceptionally wet, the forecasts fared
well. However, on January 1, 1998, like most other years, water
providers did not know if the forecasts were underestimating an
exceptional event.

As a final observation, a time series of the Lake Powell inflow
forecasts is provided in figure 54. While each year is unique and the
last decades of this century have been especially variable, significant
improvement of the forecasts is not visible since their inception in the
1960's. Because the current hydrologic forecasting techniques do not
perform well under extreme conditions (dry or wet), if the future holds
increased variability, forecast performance may degrade.

### 3.4.2 CPC Climate Outlooks

The accuracy of the CPC climate outlooks is related to the accuracy of
the tropical SST forecasts. While a review of these forecasts is beyond
the scope of this work (especially considering that study participants
reported minimal use of these forecasts), several authors have engaged
in such analysis. Briefly, Barnston et al. (1999) thoroughly compare and
contrast the performance of individual statistical and dynamical
forecasts of the onset, development and demise of the 1997-98 El Niño.
This study provides a generally favorable view of the forecasts compared
to persistence. In contrast, Landsea and Knaff argue that the SST
forecasts did not have skill above a more rigorous standard: persistence
and climatology (Landsea and Knaff, 1999). Regardless, the early rapid
development of the 1997-98 El Niño makes the performance of the SST
forecasts moot.

In comparison to the point WSOs, the CPC Climate Outlooks are a
spatially distributed product, forecasting over both space and time. The
heterogeneous nature of rainfall makes the precipitation outlooks
difficult to evaluate. Additionally, in their current form, the Outlooks
have only been produced since January 1995. Since they are probabilistic
forecasts, it would take decades, if not centuries, to collect enough
samples for proper evaluation of the performance of the forecasts (a
similar problem exists for detecting improvement in forecasts, see
Lettenmaier (1984) for further discussion). In the meantime, forecast
techniques would have changed many times over and the evaluation would
reflect the accuracy of the past forecasts, not the *future* forecasts.

To overcome these difficulties, two assumptions are possible. First,
spatially distributed rainfall is aggregated into averages, represented
by the CPC climate forecast divisions (shown in figure 2). This analysis
will consider only four such divisions (83, 94, 98 and 101). Secondly,
the probabilistic forecasts can be considered deterministic. A forecast
for increased probability of wet conditions can be considered a binary
positive forecast for wet conditions. Forecasts indicating high
probability of wet conditions can be a proxy for forecasts of very wet
conditions. Although its accompanying materials explicitly indicate that
this second assumption is an improper interpretation of the forecast,
interviews with water managers (discussed subsequently) indicated this
is a common (mis-) interpretation of the forecasts.

For Northeastern Utah (Area 83), Southeastern California (94),
Southeastern Arizona (98) and Central New Mexico (101) the CPC Climate
Outlooks are compared to observations in figures 56-59. In the top
figures, the forecast probability of being in the wettest 1/3 of 1961-90
is plotted against time for each of these regions. On the bottom, the
quantities of rainfall demarking the tercile boundaries are also plotted
against time, including where the rainfall observations of this period
fell. See also figure 55.

Four qualities are visible at a first glance. First, in the northern
parts of the Colorado River Basin (area 83), and Southeast California
(area 94), rarely, if ever, is a forecast beyond climatology offered.
However, these regions do experience considerable interannual
variability, especially the Upper Colorado River Basin. The forecasts
are for climatology, primarily because the causes of precipitation
variability in the region are not well understood. Therefore, any
forecast would have low skill. In contrast, because of the strong ENSO
signal in the Southwestern US, Arizona and New Mexico frequently have
non-climatology winter precipitation forecasts.

[]{#__RefHeading___Toc463882065
.anchor}![](media/image60.wmf){width="6.0in" height="4.8in"}Figure 55.
Guide to CPC Climate Outlook forecast verification plots. Each month,
CPC issues forecast maps of "probability anomalies" indicating the
enhanced (or diminished) probability of various regions experiencing
wetter than normal conditions. Wet is defined as the wettest tercile of
the historical record from 1961 to 1990, whereas dry is defined as the
driest tercile. These tercile boundaries are plotted on the bottom
figure (in solid, with median of 1961-90 also plotted). The CPC
forecasts are for the 13 consecutive 3-month periods following the
issuing of the forecast (e.g. DJF, JFM, FMA...) and the precipitation
forecasts are for *cumulative* precipitation during this period
(indicated by \* in lower figure, where x's are individual months).
Therefore, the forecast (top figure) is predicting the probability that
the cumulative 3-month precipitation total (indicated by a \*) will be
wetter than the wet tercile boundary. Forecasts for region 98 (Southeast
Arizona) issued in June 1998 are plotted in the top figure. The largest
dot indicates the forecast with the shortest lead (1 month), whereas the
smallest of the dots shown indicates the longest lead (12 months into
the future). A forecast for 33.3% indicates climatology whereas higher
numbers indicate a higher probability of being wet. For example, the top
figure indicates that there is a 45% probability of JFM 1998
precipitation totals being in the wettest 33% of record (1961-90) and
this period was indeed wet.

[]{#__RefHeading___Toc463882066 .anchor}Figure 56. CPC Climate Outlook
precipitation forecasts (top) versus observations (bottom) for Area 83
(Northeast Utah), 1995-1998. See figure 2 for locations. See figure 55
for explanation of plots. Notice the relative lack of forecasts beyond
climatology for this region, despite its high level of interannual
variability.

![](media/image61.wmf){width="6.0in" height="7.013888888888889in"}

[]{#__RefHeading___Toc463882067 .anchor}Figure 57 CPC Climate Outlook
precipitation forecasts (top) versus observations (bottom) for Area 94
(Southeast California), 1995-1998. See figure 2 for locations. See
figure 55 for explanation of plots. This region experienced extreme
impacts from El Nino in February, verifying the forecasts for all
forecast periods from DJF to FMA. This region is one example of where a
single wet month (e.g. September 1997) can create wet seasonal
conditions, even though the remainder of the season was dry.

![](media/image62.wmf){width="6.0in" height="7.013888888888889in"}

[]{#__RefHeading___Toc463882068 .anchor}Figure 58 CPC Climate Outlook
precipitation forecasts (top) versus observations (bottom) for Area 98
(Southeast Arizona), 1995-1998. See figure 2 for locations. See figure
55 for explanation of plots. This region frequently has forecasts for
increased probability of wet conditions (ie "Bulls-eyes" located over
the region) although it experiences less veriability than the Upper
Colorado River Basin. Note also how exceptional the 1997-98 forecasts
are compared to previous years.

![](media/image63.wmf){width="6.0in" height="7.013888888888889in"}

[]{#__RefHeading___Toc463882069
.anchor}![](media/image64.wmf){width="6.0in"
height="7.013888888888889in"}Figure 59 CPC Climate Outlook precipitation
forecasts (top) versus observations (bottom) for Area 101 (Central
western New Mexico), 1995-1998. See figure 2 for locations. See figure
55 for explanation of plots. Although the forecast was exceptionally
strong, the impacts of El Nino, in this region, were relatively weak.
The forecast was correct, by definition, but only marginally so which
may have caused confusion in users about the accuracy of the forecast.

This bodes well for forecast users in Arizona, because the forecasts
have skill, at least in the winter (forecasts beyond climatology in
Arizona had never been offered for the summer). However, it also gives
Arizona users a false impression that, of all the western states,
interannual variability is most severe in their region because of the
consistent "Bull's-eye" located over the area. Comparing observations
from areas 83 and 98, one clearly sees that this is not the case.

Second, Arizona water management agencies recognize the last few years
as a dry period with 1996 as the single driest year of modern record.
However, the CPC climate forecasts for Arizona and New Mexico
consistently forecasted a higher probability of wetter than normal
conditions (approximately a 40% probability of being in the wettest 33%
of record) for every winter since 1995. This forecast also indicated
approximately a 25% probability of being in the driest 33% of record.
However, "poor" prior performance of the forecasts may have damaged
their credibility among seasoned users.

Third, in many instances, heavy precipitation from a single month can be
followed by extreme dry in the next two months or vice versus.
Technically, if the rainfall from that single month is sufficient, it
can register three consecutive three-month seasons as being wet. For
example, in February 1998, Southern California (area 94) experienced 5
inches of rainfall, placing Dec-Jan-*Feb*, Jan-*Feb*-Mar and
*Feb*-Mar-April 1998 all in the wettest 1/3 of record even though the
adjoining months were dry. In comparison, three equally wet months can
qualify a three-month season as being wet. The CPC climate outlooks do
not provide any information about which will occur, although the
implications for water resources management for these two scenarios are
radically different. This is not unique to the 1997-98 forecasts, but
is, instead, a fundamental problem with the format of the outlooks.

Finally, according to the definition of the forecast, the Southwestern
US could be considered wet during the winter of 1997-98, although only
marginally so in many regions in Arizona and New Mexico. In several of
the maps not shown (areas 96-102) three-month precipitation totals were
within ½ inch above the wet tercile boundary. This difference is
arguably within the limits of observation errors. As discussed
previously in chapter two, while the 1997-98 winter could be considered
wet, it certainly was not exceptionally wet. This could have caused
confusion to some users who believed that the forecasts were poor
because they misinterpreted them as indicating that an extreme event was
imminent.

### 3.4.3 Summary

The 1997-98 hydrologic and climate forecasts performed well compared to
previous years. A consistently wet non-extreme winter allowed the WSOs
to anticipate the enhanced streamflow. With the exception of a slight
underestimation on the Verde River causing spillage, major water
providers could have relied solely on the WSOs to safely conduct
business as usual without a noticeable difference. In contrast, while
the climate forecasts performed generally well, their probabilistic
format is currently incompatible with objective evaluation. However, if
the forecasts were assumed deterministic, forecast performance during
1997-98 was better than the consistently poor performance in Arizona and
New Mexico since 1995.

# CHAPTER 4

# WATER MANAGEMENT IN ARIZONA

## 4.1 Introduction

The semi-arid nature of the Southwestern U.S. desert requires extensive
water management to capture, store and distribute the limited supplies.
According to the Arizona Department of Water Resources (ADWR) statewide
assessment (ADWR, 1994), roughly half of Arizona's seven million
acre-feet demand for water is fulfilled using groundwater reserves that
have spatially varying sensitivities to interannual fluctuations in
precipitation and streamflow. Sandstone aquifers in the northern half of
the state and some of the shallow aquifers in the southern half of the
state, for instance, drain quickly and a period of several dry years can
stress supplies. However, deep alluvial aquifers are believed to be
insensitive to all but the longest scales of climate variability (on the
order of hundreds to thousands of years or more). The remaining half of
Arizona's water supply is withdrawn from existing surface supplies in
reservoirs or diverted from rivers, including the Colorado River,
directly, and via the Central Arizona Project (CAP), indirectly. Less
than a quarter of all demand is for municipal and industrial purposes
while the remaining three-quarters are utilized for irrigated
agriculture. Population and agriculture centers are mostly concentrated
in the southern, central and southwestern regions of the state. Five
areas with problematic groundwater overdraft have been designated as
Active Management Areas (AMAs), attempting to slow or halt the decline
of the water table due to groundwater pumping. These areas, through
ADWR, encourage conservation measures, limit the expansion of
irrigation, and seek usage of alternative water supplies, such as CAP.
The AMAs along with ADWR were established by the 1980 Groundwater
Management Act in recognition of the non-sustainability of unrestricted
water use. A complete discussion of water availability and usage in
Arizona can be found in ADWR's Water Resources Assessment (ADWR, 1994)
as well as USGS Water Supply Papers 2350 and 2375 (Eychaner and Rehmann,
1990; Wilson, 1990, respectively). Briefly, water in Arizona is provided
by a diverse and complex patchwork of agencies to an equally diverse
array of water users.

The reduction of groundwater pumping rates combined with projections for
population growth in Arizona emphasize concern over increased
vulnerability of water supplies to interannual and decadal scale climate
variability. The uncertain status of Native American water rights,
concern for endangered species and maintenance of riparian habitats
complicate existing issues. In total, various water management agencies
exist in a political landscape as complicated as the physical landscape.
While the availability of water and the conflicts over its ownership
have played a role in Arizona history since its inception, it is clear
that the need for effective water management is becoming more critical
than ever before (see WWPRAC (1998) for further discussion). The rise in
frequency of extreme non-monsoonal flooding events since the 1970's
combined with development in the floodplain also indicate an increasing
need for effective flood management and mitigation (Webb and Betancourt,
1992).

This chapter describes water management agencies, both in terms of water
supply and extreme events. Based on existing literature and statements
made by study participants, it documents the decision making processes,
issues, concerns and planning horizons of various agencies. Three water
providers are investigated in depth to provide examples of how water
management practices are influenced by a number of factors, including
resources, basin characteristics and legal constraints. The final
section of this chapter provides examples of three extreme flooding
events that occurred during recent El Niño events to illustrate the
types of flooding that extreme event managers face.

## 4.2 Water Supply Management

Water supply management agencies are as complicated as the basins they
inhabit, and vary from one region to the next as the physical and social
landscapes change. While they utilize many of the same tools, such as
reservoirs, canals and groundwater pumps, the management plans,
objectives, planning horizons and resources for each agency are unique.
Understanding how various agencies operate and plan allows scientists to
provide information that easily meshes with agency procedures. This
section describes yearly and interannual planning by three surface water
management agencies: the Salt River Project, the Colorado River Bureau
of Reclamation and the Gila River Water Commissioner.

A significant portion (approximately half) of the state's water supply
is from groundwater. In contrast to surface water management, the
acquisition and distribution of groundwater supplies is, for the most
part, relatively straightforward. Water providers (e.g. Tucson Water) or
private well owners pump water in a fashion which satisfies demand yet
generally does not violate conservation measures imposed by the Active
Management Areas, where applicable, or interfere with surface supplies.
For the most part, groundwater management agencies consider themselves
more vulnerable to long-term climate variability, social factors (such
as population growth) and political factors than they are to individual
dry or wet years. Seasonal forecasts have limited utility to these
groundwater management agencies with three exceptions:

1.  Inclusion of climate data into water demand forecasting (e.g. summer
    temperature)

2.  Use of forecasts to mitigate damage to water delivery infrastructure
    during extreme events

3.  Use for planning by agencies with stressed groundwater supplies that
    are sensitive to interannual variability (e.g. communities along the
    north of the Mogollon Rim in sandstone aquifers as described above).
    In this case, a forecast for a wet year would have less utility than
    a forecast for drought.

### 4.2.1 Salt River Project

Founded at the turn of the century as the Bureau of Reclamation's oldest
project, the Salt River Project (SRP) is a quasi-governmental
organization which operates reservoirs along the Salt and Verde
watersheds, delivering water to a region within Arizona's largest
metropolitan center, Phoenix. SRP delivers water from watersheds
totaling 7,787,520-acres (3,960,320 acres on the Verde and 3,827,200
acres along the Salt) to a fixed 240,000-acre service area. The water
demand in the service area has been relatively static at 1 Maf/year, but
there has been a steady transfer from agricultural to domestic uses
within the service area and an explosive population growth surrounding
it. Spring melt (January-May) volumes are highly variable, averaging
0.68 Maf/year (0.25 and 0.43 Maf/year from the Verde and Salt watersheds
respectively) with water year totals averaging slightly in excess of 1.2
Maf/year. Spring melt streamflow from the two watersheds can range from
slightly under 3.8 Maf (1993) to 0.13 Maf (1996). Additionally, SRP
augments surface flows through groundwater pumping (by as much as 1/3 of
the demand: this option of augmenting surface flow with groundwater is
unique within Arizona) and has recently investigated the purchase of
Colorado River water.

[]{#__RefHeading___Toc462466294 .anchor}Table 3. Salt River Project
Reservoirs

  ---------------- ------------------ ------------------ ------------------
  Watershed        Dam                Lake               Storage (kaf)

  Verde            Horseshoe          Horseshoe          131.4

  Verde            Bartlett           Bartlett           178.2

  Verde            Total                                 309.6

  Salt             Roosevelt          Roosevelt          1,653.0\*

  Salt             Apache             Horse Mesa         245.1

  Salt             Canyon             Mormon Flat        57.9

  Salt             Saguaro            Stewart Mtn.       69.8

  Salt             Total                                 2,025.8\*

  Salt & Verde     Total                                 2,335.4\*
  ---------------- ------------------ ------------------ ------------------

\* Prior to recent modifications, ending in April 1996, Roosevelt Dam's
storage capacity was 1,336.7 kaf. The numbers presented above are
storage to the top of the active conservation level. Between this level
and the top of the new dam, there is 1,802-kaf *additional* flood
surcharge storage (3,455-kaf in total).

The project operates six reservoirs on the basin. See Table 3 for a
summary of SRP reservoirs. The primary storage capacity of the system
resides in Roosevelt Lake. The remaining reservoirs provide a limited
amount of storage and, instead, are involved extensively with hydropower
generation (and thus are kept as close to capacity as is possible). SRP
generates on the order of \$1,500M in hydropower revenues (compared with
\$11M from water revenues) and hydropower plays a major role in their
daily operations. Prior to the recent modifications at Roosevelt Dam,
none of SRP's storage capacity was reserved for flood control. The
notable imbalance of storage capacity on the Salt and Verde is due to
environmental constraints on water resource development for the Verde.
With the renovation of Roosevelt dam, the Salt River's flood risk is
"effectively" eliminated, while the Verde watershed remains at-risk.

While all water management agencies in Arizona are unique, SRP sets
itself apart from the others in several important ways: the resources
available to the agency, the sophistication of its management, and the
relative liberty the agency enjoys (although the agency perceives itself
as generally conservative). SRP shares a building with the state office
of the NWS and these two agencies have extensive contact on a daily
basis. Additionally, the agency employs three meteorologists and three
hydrologists, full-time, to monitor and manage the watershed using a
sophisticated array of tools, providing guidance on a range of
time-scales. A full description of these tools and how they affect
management decisions is available in Reigle et al. (1992). Table 4
summarizes various management activities. While the immediate and
short-term forecasting is still of interest, for the sake of brevity,
this report will focus on the intra- and inter-seasonal management of
the watershed.

[]{#__RefHeading___Toc462466295 .anchor}Table 4. SRP Management Time
Scales, Activities and Guidance Tools

+---------------------+------------------------+----------------------+
| **Time scale**      | **Activity**           | **Guidance**         |
+---------------------+------------------------+----------------------+
| Short-term          | Water delivery         | Quantitative         |
|                     |                        | precipitation        |
| (immediate to       | Hydropower operations  | forecasts,           |
| weekly)             |                        | observations,        |
|                     | Flood management       | hydrologic runoff    |
|                     |                        | models               |
+---------------------+------------------------+----------------------+
| Medium-term         | Flood storage          | WSOs, in-house       |
|                     |                        | climate forecasting, |
| (intra-annual)      | Water allotments       | CPC climate outlooks |
+---------------------+------------------------+----------------------+
| Long-term           | Drought planning       | ###### H             |
|                     |                        | istorical statistics |
| (interannual and    | Infrastructure         |                      |
| beyond)             | development            |                      |
+---------------------+------------------------+----------------------+

SRP is also unique because it is involved with the NRCS and NWS in the
creation of seasonal hydrologic outlooks for its basin. This involvement
increases the level of confidence that SRP has in these outlooks. SRP
utilizes the forecasts in a manner similar to the Colorado River Bureau
Reclamation (see next section).

Prior to the 1997-98 El Niño, SRP used the CPC climate outlooks only to
the extent that it would "flavor their thinking" when entering a season.
These products were one of a suite that SRP used, including several
proprietary models such as the Entropy Ltd. Winter Outlook that
provides, in October, an estimate of December-March precipitation.
Additionally it uses the ThinkNet Runoff model to produce a cumulative
distribution frequency forecast of runoff in acre-feet, incorporating
SST, surface air pressure, and Arizona temperature and precipitation
data. It also produces analog years and their actual runoff volumes.
These tools are similar to the forecasting method described in Young and
Gall (1992).

SRP also engages in multi-year planning, focused primarily on drought.
Through their long-range plan, SRP ensures that the current system will
survive the worst drought the region has experienced in modern history.
This drought occurred from 1898-1904 and produced only an average of 38%
of average runoff (with average being 1.231 Maf). As reservoir levels
decrease, groundwater pumping is increased and eventually allocations
are reduced (figure 60). SRP does not use any forecast products, aside
from the historical data, to provide guidance in multi-year planning due
to a lack of confidence in these types of forecasts.

[]{#__RefHeading___Toc463882070 .anchor}Figure 60 Salt River Project
Interannual Management Plan. Current reservoir levels (left) are used as
guidance to determine groundwater pumping (right). Eventually, as
reservoir levels decrease, allocations (bottom left) will be reduced.

### ![](media/image65.png)  {#section-10 .unnumbered}

### 4.2.2 Colorado River Management

Volumes have been written about the complexity of management and issues
surrounding the Colorado River. This section is primarily based on one
such report (LCR-USBR, 1996). In contrast to SRP, the activities along
the Colorado River are tightly bound and closely scrutinized. However,
one notices a distinct difference between the management in the upper
and lower basin. The end of this section will describe the two agency
units separately, but it will begin with issues facing both basins,
collectively.

An interstate compact from 1922 administers the waters of the Colorado
River. The compact divides the waters evenly between the upper (Wyoming,
Colorado, Utah and New Mexico) and lower (California, Arizona, and
Nevada) basin states, providing 75 Maf to each basin per ten year
period. An additional 1.5 Maf is delivered to Mexico each year. This
interstate compact is the keystone to over forty agreements, court
cases, laws and regulations collectively known as the "Law of the
River". Other relevant major elements of the Law of the River are the
Supreme Court's finding in Arizona vs. California, the Boulder Canyon
Project Act of 1928, and the Flood Control act of 1944.

The ruling of Arizona vs. California (373 U.S. 546) determines, among
other things, the exact quantities of water that various lower basin
states are entitled to, how water will be divided in times of shortage
and the operational priorities of the river. In order of importance, the
reservoirs of the Colorado River are operated:

1.  "For river regulation, improvement of navigation, and flood control;

2.  For irrigation and domestic uses, including the satisfaction of
    present perfected rights; and

3.  For power;"

Additionally, the delivery of 1.5 Maf per year to Mexico is a paramount
objective of the Colorado River Bureau of Reclamation. Through later
agreements, the United States also has obligations to meet water quality
standards on deliveries to Mexico.

The Boulder Canyon Project Act authorized the construction of Hoover Dam
and established flood control as the highest priority purposes of the
dam. The Flood Control act of 1944 established the Army Corps of
Engineers as responsible for flood control regulations for all
reservoirs constructed wholly or in part with Federal funds. The Los
Angeles District of the Army Corps published in December of 1982 the
current guidelines for Hoover Dam in the "Water Control Manual for Flood
Control Hoover Dam and Lake Mead Colorado River, Nevada and Arizona".
Revisions are expected. A similar document exists for the new flood
capacity at SRP's Roosevelt Dam.

Sample guidelines in the Hoover Dam manual include preparatory
(pre-melt) reservoir space requirements and deterministic application of
hydrologic seasonal outlooks to determine releases. The guidelines are
fairly explicit (and lengthy), including monthly reservoir elevation
targets and thresholds that must be passed before certain emergency
releases are made (succinctly summarized in Burke and Stevens (1984)).
Additionally, besides their obvious hydrologic interconnections, Lake
Mead and Lake Powell are somewhat jointly managed in that the Upper and
Lower Bureau attempt to equilibrate their reservoirs. For example, this
was one of the operational considerations during the 1997-98 El Niño in
that Lake Powell would need to be lowered to match its level with Lake
Mead.

Finally, during conditions short of a need for flood control, but with
high streamflow, the Secretary of the Interior, at his discretion as
Watermaster, can declare surplus. Water users can then increase their
demand by a fixed maximum specified amount outlined by the Law of the
River (50% to California, 46% to Arizona and 4% to Nevada). The
remainder released beyond the excess demand travels as surplus to
Mexico. Since Mexico can currently use only a maximum of 0.2 Maf above
their 1.5 Maf of water entitlement, due to structural and resource
limitations, any deliveries beyond 1.7 Maf travel to the Gulf of Mexico
unused (CNA, personal communication 1999).

[]{#__RefHeading___Toc462466296 .anchor}Table 5 Colorado River Bureau of
Reclamation Major Reservoirs

  ----------------- ----------------- ----------------- -----------------
  **Watershed**     **Dam**           **Lake**          **Capacity
                                                        (kaf)**

  Upper Basin       Glen Canyon       Powell            24,322

  Lower Basin       Hoover            Mead              27,377

  Lower Basin       Davis             Mohave            1,810

  Lower Basin       Parker            Havasu            619

  Lower Basin       Total                               29,806

  Powell & Lower    Total                               54,128
  ----------------- ----------------- ----------------- -----------------

The Lower Colorado Bureau of Reclamation (herein the "Lower Bureau")
operates eight dams from Lee's Ferry to the Mexican International
border; Hoover, Davis, Parker, Headgate Rock, Palo Verde Diversion,
Imperial, Laguna, and Morelos Dams. Although estimates of the capacity
of these dams can conflict (possibly related to sedimentation), the
majority of the storage occurs at Lake Mead (with 1,500-kaf minimum
flood storage), Lake Mohave and Lake Havasu. The Upper Colorado Bureau
of Reclamation (herein the "Upper Bureau") operates Lake Powell along
with other reservoirs higher up in the basin. Lake Powell has no
explicit flood storage capacity (Table 5). With an average yearly inflow
of approximately 11.5 Maf (maximum 24 Maf, minimum 5 Maf), these four
dams have a storage capacity equivalent to over 4.5 years of average
inflow. This ratio is exceptionally high when compared to other basins
within the United States.

**The Lower Bureau** operates its reservoirs primarily to satisfy user
demands and to safely maintain the exact flood control requirements of
the Army Corps of Engineers. Within the management plan, operations are
as fixed as possible, partially as an institutional preference and
partially to satisfy the numerous conflicting interests along the river.
Satisfying these interests is an especially challenging task. The
livelihood of many business (recreation and otherwise) depend on the
reservoir levels downstream remaining static (and predictable). Prior to
the recent El Niño, these stakeholders preferred that the Lower Bureau
not conduct elevated releases beforehand, but they also sought to avoid
elevated *uncontrolled* releases afterwards. Additionally, in the region
below Havasu City, near Parker (collectively known as "The Parker
Strip"), residences have been built close enough to the river that they
will be inundated when the Army Corps activates the second of six levels
of flood releases (figure 61).

In light of these conflicting interests and the potential for perpetual
argument over the management of the river, the Lower Bureau rigidly
maintains the status quo. Recent environmental concerns and potential
revisions of the Law of the River may cause changes in the reservoirs
operations, but this remains to be seen.

The management of the reservoirs in the Upper Basin by **the Upper
Bureau** is

![](media/image66.jpeg){width="3.4722222222222223in"
height="2.2777777777777777in"}

![](media/image67.jpeg){width="3.4722222222222223in"
height="2.263888888888889in"}[]{#__RefHeading___Toc463882071 .anchor}

Figure 61 Example Parker Strip residences for sale along the lower
Colorado River. Valued at \$249,900, the top residence advertises 50
feet of water frontage. These residences can expect damage when Hoover
Dam engages in its second, of six, levels of flood control releases.

distinctly different from the Lower Basin. For Glen Canyon Dam at Lake
Powell, the Upper Bureau has adopted a formal adaptive management
approach. This approach monitors the effects of management actions on
the environment and then adjusts the management actions, reflecting the
new understanding of the system. In contrast to the populated regions
along the lower stretches of the Colorado, the stretch of river between
Lake Powell and Lake Mead (the Grand Canyon) is relatively unpopulated.
The primary concerns in this region are dam safety, water delivery and
maintenance of the riverine environment. This includes repairing of
beach erosion that has occurred because of the slow steady releases from
the reservoirs, in contrast to the quick, punctuated floods and long
recessions that occurred prior to the building of the dam. The
controlled flood of 1996 demonstrated that contrary to expectations,
large flows do not contribute to erosion but, in fact, assist in
building of beaches (Konieczki et al., 1997). Consequently, the Upper
Bureau is contemplating integrating controlled maintenance floods into
routine operations.

While the Upper Bureau manages Lake Powell inter-seasonally in a manner
similar to Lake Mead (using WSOs), it seeks (and is allowed the freedom)
to adaptively adjust its operations to the benefit of environmental
concerns. Additionally, the managers of Lake Powell, in contrast to Lake
Mead, schedule releases to be high prior to the melt season, low during
the melt season and then high afterwards. This allows flexibility of the
system in the face of inaccurate WSOs; if the forecasts overestimate the
streamflow, reduced releases can be conducted at the end of the season.
If the forecasts underestimate the streamflow, more releases can be
conducted during the season. The Upper Bureau estimates that it can
adjust for inaccuracies in the forecasts on the order of 1.5-Maf per
month. This adjustment of the timing of releases is one part of a
sophisticated method of risk management that is employed at Lake Powell,
which has been investigated by other researchers (Pulwarty and Melis,
1999).

For long range planning, both Bureaus develop an "Annual Operating Plan"
which predicts reservoir levels and monthly releases for all of the
reservoirs out to two years in advance. Projections are based primarily
on:

1.  recent streamflow

2.  flood control criterion

3.  hydrologic forecasts (WSOs)

4.  equilibration of Lake Mead and Lake Powell

5.  other (such as system maintenance etc)

The WSOs for inflow to Lake Powell officially begin on January 1 and
provide estimates of each month's streamflow until the peak snowmelt
period, and then individual months within the snowmelt season
(April-July). The public can receive the cumulative streamflow estimate
for April-July but the remaining hosts of products are considered
in-house between the Bureau and the Colorado Basin River Forecast
Center. (A similar situation exists with SRP's forecasts, as only a
small subset of all of the products is available to the public). Beyond
the time range of the WSOs, the Bureau assumes climatology into the
second year of streamflow. *This "annual" operating plan is revised
monthly, as new, revised WSOs are available.* This new plan is available
via the Internet. In contrast, SRP's annual operating plan is not
available to the public for a variety of reasons, including the possible
legal repercussions of actual releases being different from forecast
releases.

In summary, while existing in a hydrologically linked system, the Upper
and Lower Bureaus have similar, yet distinct management objectives and
philosophies. The ability of these agencies to incorporate new
scientific tools and information into operations also varies, with
increased flexibility in the Upper Basin and fixed operations in the
Lower Basin. Additionally, these agencies do not act within a vacuum: a
host of conflicting interests along the Lower Colorado make it one of
the most highly politicized rivers of the United States.

### 4.2.3 Gila River Water Commissioner

The Mid- to Upper-Gila River initially appears to be a relatively simple
system. Its only reservoir is the San Carlos Reservoir, constructed in
1924 with a capacity of 880,000 acre-feet. Its rules are also relatively
simple, as administered by the Globe Equity decree #59 of 1935. Each
year, based on the reservoir level and the January 1 WSO, the Gila River
Water Commissioner determines the water allocation available to users,
with a maximum of six acre-feet per year, less during periods of water
shortage. Reservoir releases are based on the number of acres that
downstream users claim need irrigation, with the maximum number of acres
predetermined by the Globe Equity decree. Upstream users are able to
divert an equivalent per-acre allocation from the river, although
inaccurate WSOs have a greater negative impact on upstream users because
the difference cannot be made up from storage. Instead, the users are
required make up the difference with more expensive groundwater pumping.
The primary task of water management agencies along the river is
accounting for diversions. There is relatively little flexibility,
strategy or risk management involved. The managers of the river have
recently contemplated adjusting operations based on the short-term
weather forecasts. For example, if the forecast is for rainfall, the
managers will hold off on going out into the field to cut off diversions
if the river is low. However, they are still reluctant to do so because
of legal constraints and lack of confidence in weather forecasts.
Finally, San Carlos Reservoir's operations are not complicated by flood
storage criterion as the reservoir has none designated.

However, a closer look reveals an increasingly complex situation. The
San Carlos Reservoir is the largest reservoir owned by the Bureau of
Indian Affairs and a significant portion of the water goes to local
Native American tribes. While the water allocations for all tribes play
a role in water management everywhere in Arizona, along the Gila it has
been especially problematic. Historically, the amount of water available
to the Indian tribes is not well quantified and this has become a
serious issue at the general stream adjudication. Adjudication aims to
quantify (and finalize) the water rights of every user on a system, and
the Gila adjudication has been a long, complicated, legal battle since
the 1970's, involving thousands of participants with tens of thousands
of water claims. It has been one of the largest lawsuits ever litigated
in the Arizona court system. Between \$150 million and \$200 million
have been spent so far on the Adjudication and only one water right has
been settled since 1972 (Glennon and Maddock III, 1994). Until the
adjudication is settled, however, the Globe Equity Decree remains the
operating rule for the San Carlos Reservoir.

To further complicate issues, the streamflow along the Gila could be
best described as "moody." From 1947 to the present, the main reach of
the river at Calva has delivered as little as 10,706 acre-feet (in
1956-57) into the reservoir and as much as 998,833 acre-feet (in
1991-92), with a median of 110,657 acre-feet per streamflow season
(October-May). The average streamflow is 212,700 acre-feet, almost twice
the median, suggesting that "dry" years are relatively more common than
wet years. The reservoir was designed during an exceptionally wet period
and it greatly overestimated the amount of streamflow, above demands,
that the reservoir would receive, leaving it dry for many periods in the
1940's, 1950's and 1960's. At its dedication in 1930, Will Rogers
prophetically remarked, "If this was my lake, I'd mow it" (Tellman et
al., 1998). This serious over-allocation periodically denies many junior
users the opportunity to receive their full claims to water.

Finally, the management of the system is constrained by limited
resources, a common occurrence in primarily rural communities. In
contrast to SRP, the managers of the Gila River do not have the
resources to produce independent forecasts. The resources available are
primarily for operations and maintenance of the system. Additionally,
the overtaxing of resources of the Bureau of Indian affairs, poor
construction and lack of maintenance of Coolidge Dam have caused it to
be deemed one of the least safe dams of a nationwide assessment done
prior to the 1993 flooding event. Since the 1993 flood, however, the
Bureau of Reclamation has built structural reinforcements to the dam to
increase its safety, at the Bureau of Indian Affairs' request in 1990.

In short, the water providers of the Gila River system do not employ a
significant amount of interannual management strategy, for a variety of
reasons. The basin and its users represent a microcosm of the challenges
facing water management agencies in Arizona today, from legal battles
and constraints to Native American water issues to balancing perpetual
shortages of water with an excess of demands. Integrating seasonal
forecasts into this management framework represents a special challenge.

## 4.3 Extreme Event Management

In regions where extensive surface water management structures exist
(such as along the Colorado and Salt Rivers) it is the responsibility of
the water provider and the Army Corps of Engineers to operate reservoirs
to provide reasonable flood space to prevent flood damage. However,
other agencies also provide protection against flood damages. Not
surprisingly, the management and operations (and information needs) of
these agencies are very different from those of the water providers. Not
as obvious, however, is how different these agencies are from one region
to the next. This section overviews some of the agencies related to
extreme event management, their objectives, methods, planning schedules
and use of forecasts.

In case of flooding, Emergency Management Agencies (EMAs), at various
levels of jurisdiction, coordinate response to the disaster. The
agencies involved include but are not limited to:

1.  Red Cross (providing relief to citizens)

2.  National Guard (search and rescue)

3.  Department of Transportation (ensuring the safety of transportation
    structures and blocking off access to bridges and flooded streets)

4.  Local Police (assisting the Department of Transportation, crowd
    control near flooding rivers, prevent civil disruption)

5.  National Weather Service (storm prediction and monitoring)

6.  Flood Control Districts (ALERT gauge monitoring and maintenance)

7.  Departments of Emergency Management (to coordinate response)

The duties for each agency are predetermined locally through Emergency
Management plans of action, reinforced by periodic drills and are
somewhat flexible, as necessary, as events unfold. The primary objective
of Emergency Management is to ensure the continuity of government, the
protection of lives, and the minimization of damages during natural and
technological disasters. There is a wide range of crises that activate
emergency management, from domestic terrorism, nuclear disasters and
hazardous material spills to earthquakes, and fires. Floods, while one
of the most frequent and expensive disasters in Arizona, are only one
example of the many crises that face Emergency Managers. Drought
emergencies can also be declared, in which case the National Guard would
"assist in the protection of life and property". Several states have
established drought emergency response plans; currently Arizona's plan
is ad hoc but there is interest in formalizing it.

There are two major factors that cause water supply management and
emergency management, as sectors, to be different from each other: the
**spatial** and **temporal scales** at which they operate. Surface water
providers typically have fixed structures (reservoirs, diversions and
channels) that collect and distribute water. In contrast, flooding can
occur at any point on the river or its tributaries to varying degrees of
intensity. While certain "hot spots" exist that are perpetually at
greater flood risk than others (e.g., buildings in the floodplain), and
some structures are generally considered more important than others
(e.g., major bridges vs. farmland), emergency managers must operate at a
variety of locations, encompassing varying size areas. Partially to
reflect this, EMAs exist within a multi-tiered system, ranging from
local police to city and county emergency management to the state
division of emergency management and eventually to FEMA. Each tier
provides support to the next when the scope of the disaster becomes
large enough that it begins to stress local resources.

Additionally, with the exception of late spring, Arizona is vulnerable
to floods during all seasons (Hirschboeck, 1991). In contrast, with the
exception of floods, water providers generally have a fixed spring
snowmelt season for which they prepare. Winter frontal and summer
monsoon flooding have distinct characteristics in that summer flooding
tends to be locally intense whereas winter flooding is more widespread
and causes difficulty on larger spatial scales. Depending on the
circumstances of the individual events, the Monsoon represents more of a
threat from flash flooding and urban flooding, whereas winter events
threaten the larger washes and rivers. That is not to say that the
Monsoon cannot produce major floods; the seasonality of major flooding
has shifted in Arizona from primarily summer flooding before the 1970's
to winter and fall flooding afterwards (Webb and Betancourt, 1992). A
third type of flooding that can be especially devastating may occur in
September and October, caused by tropical Pacific storms, such as
Hurricane Nora or Hurricane Octave (October 1983). EMAs must know how to
mitigate and be prepared to respond to each and every type of these
events.

Furthermore, while WSOs provide guidance to water providers with several
months advance notice, EMAs typically must rely on weather forecasts
with lead times of only 1-3 days for guidance. While there are
exceptions to this, (e.g. the millenium computer bug) this level of
advance warning is typical of many of the emergencies that these
agencies must face (if they receive any warning at all, e.g., during
earthquakes).

On longer time scales, a different flood mitigation strategy is
employed, both structural and non-structural. The county **Flood Control
District** (FCD) assumes responsibility for regulating building in the
floodplain and ensuring that new developments maintain proper drainage.
They also assist in the design of public structures, such as bridges.
The guidance for design is typically:

1.  Analysis of historical statistics

2.  Use of a pre-computed estimate of the 20-, 50-, 100- or 500-year
    flood and/or

3.  Use of the NOAA Atlas of precipitation return intervals.

All of these methods assume climate stationarity, despite the evidence
to the contrary (Webb and Betancourt, 1992). These structures are built
to withstand many years of climate variability and, hence, individual
seasonal forecasts are not useful for this activity. Longer-term climate
forecasts and extended historical records (e.g. tree-ring chronologies)
would be more appropriate.

The balance of structural and non-structural long-term flood mitigation
and the type of strategies that agencies employ also vary from one
region to the next. For example, in Maricopa County (including Phoenix),
extensive concrete lined channels exist to prevent erosion. However, in
Pima County (including Tucson), FCDs are able to remove only a limited
amount of vegetation from channels, in accordance with the Clean Water
Act. This is a reflection of the philosophies of each of these
communities where one is seeking efficiency and the other desires to
maintain the aesthetic beauty and natural values of unlined channels.
Additionally, various communities have varying policies about preventing
building in the floodplain and retiring previously developed floodplain
property.

Between immediate and long-term time scales, State and County EMAs and
FCDs coordinate yearly flood drills with local agencies. EMAs conduct
numerous drills each year, dealing with a variety of emergencies (e.g.,
hazardous material spills, floods) involving an array of agencies (e.g.,
hospitals, nursing homes, schools), practicing response to individual
hypothetical events. It is at the discretion of the EMAs which, and how
many, other agencies are included in the drills. The focus of the drill
is also at the discretion of the EMAs (for example, large flooding
versus localized flash floods).

The protocol for the drills and for responding to individual events is
published in a guidebook, unique to each community, that the local EMA
maintains. This book provides guidance on all emergencies, points of
contact, maps of inundation in the event of a dam break, and so on. The
extent to which it is updated depends on the community (typically once a
decade or more). This book also discusses mitigation and preparation for
disasters, although sections on mitigation are generally brief (2-3
pages of 300+ total) and vague (generally encouraging it, without
specific details).

One factor defining the character of each EMA is the amount of resources
that it has available. Like water providers, the amount of resources
range from one extreme to the other in Arizona. In some communities,
especially regions of low population density, emergency management can
be the responsibility of one individual who simultaneously holds other
positions in the community, such as fire chief, police chief, city
engineer and so on. Some of these low-resource agencies do not even have
access to the Internet. In contrast, large urban areas can have
resource-rich EMAs, with dedicated personnel and sophisticated
communication and monitoring systems. Typically, the latter agencies
have the resources to engage in more mitigation type activities, instead
of solely response. Of course, each community has its own personality
and the extent to which it engages in mitigation activities is not only
determined by resources; some low-resource EMAs are especially
enthusiastic towards mitigation and vice versa. To the frustration of
some EMAs, communities may be skeptical and reluctant to provide funding
for mitigation measures and will focus resources on more tangible
threats (e.g., health care and education).

Finally, based on the response during previous events, EMAs recognize
that their efficiency ultimately hinges on the clarity of communication
and level of coordination that agencies have with each other prior to
and during events. Analyzing the response to the October 1983 Tucson
Flood, Saarinen observes that "Pima County Emergency Management Services
is an organization with a tiny staff and small budget. Since the
agency's main emphasis is on nuclear preparedness or chemical spills on
Interstate 10, it devoted little time or energy to preparing for floods.
Sporadic efforts in the past to organize meetings to discuss flood
preparedness had failed because of a lack of interest, a lack of high
priority, and a lack of leadership." He also observes that the
ineffectiveness of the community to respond to the 1983 event did not
reflect ineffectiveness on the part of the agencies involved, but rather
a lack of prior communication and coordination between agencies
(Saarinen et al., 1983). Agencies are currently attempting to rectify
this situation through a statewide high-speed communications system
(completed in late 1998) and further utilization of the Internet.

In summary, extreme event managers are concerned with a diverse number
of emergencies at a variety of spatial and temporal scales. Because of
the need to apply resources effectively, EMAs attempt to realistically
assess the threat posed to the community and, at the same time, not
underestimate what needs to be done. As a sector, they are less in tune
to a seasonal cycle as water providers are because floods can happen at
any time. However, some annual activities do occur, such as flood
drills. Furthermore, EMAs are not as tightly bound as water providers in
that they have flexibility to mitigate a disaster as they see fit,
without high levels of debate, scrutiny and legal controversy. At the
same time, limited resources and the apathy of some communities means
that some EMAs are not able to adequately prepare for floods.

## 4.4 Recent Extreme Flooding Events

The remainder of this section will briefly focus on three exceptional
flooding events in Arizona, the 1983 floods along the Colorado River,
the 1983 floods in Southeast Arizona and the 1993 Central Arizona
Floods. All of these events are relatively recent and linger in memory
of many local residents. They also occurred during recent ENSO events,
the 1983 event being of similar magnitude to the 1997 event and the 1993
event being considerably weaker but more persistent. Each of these
events is considered separately because each provides unique insights
about flooding and flood mitigation in Arizona, namely that

1.  Water management based on grossly inaccurate hydrologic forecasts
    can be disastrous,

2.  Vulnerability results from the interaction between natural and
    social systems, and

3.  Current flood magnitude estimation procedures design structures to
    withstand past, and not necessarily future, floods.

### 4.4.1 The 1983 Colorado River Flood

The common perception of floods is as natural disasters. In reality,
floods are the collision of natural forces with vulnerable social
structures. The 1983 floods along the Colorado River occurred partially
because of gross WSO errors combined with poor management of reservoirs.
It also stands out as a highly unfortunate event in the history of the
Bureau of Reclamation and lives in the memory of stakeholders along the
Lower Colorado as something to be avoided in the future at all costs.
This section summarizes the accounts of study participants and the
compiled history of Yuma
(<http://www.ci.yuma.az.us/history/history.htm)>.

As late as May 1983, the WSOs predicted that the runoff into Lake Powell
for the spring melt season would be slightly above normal (8Maf). The
Bureau of Reclamation used these forecasts to schedule Lake Powell water
levels to be within one foot from full at the peak of the melt season
(April-July). However, late spring storms starting mid-March deposited a
significant snowpack in the upper basin. By May, when the snowpack
typically begins to peak and diminish, SNOTEL sites were reporting 150%
normal snow water equivalent. As late as June, the snowpack was still
significantly above normal (figure 62). On June 1, the WSOs began to
change, indicating that 9.1 Maf would arrive.

The Bureau raised releases to 28,000 cfs from Lake Mead. On June 6,
these releases caused a 2.1-foot rise in the river levels in Yuma,
inundating low campgrounds. Residents of the unleveed community of
Parker began to sand bag riverfront properties. However, by June 10
several resorts were reporting widespread damage.

Again, the forecast changed on June 15, this time to 11.3Maf. On the
next day, the city of Yuma declared a flood emergency to protect
municipal water supply structures. According to the Yuma Daily Sun (June
16):

"The U.S. Bureau of Reclamation\'s announcement of dramatic new releases
of water upriver sort of strained the imagination. The release story...
predicted four more feet of water in the river downstream. By the time
\[Yuma city public services director\] Larry Hunt got to the river to
look over needed work, he reported, \"Now they\'re talking about six
feet of water.\" That made it convenient because Hunt\' assistant, Tom
Long, was with him. He marched around the various points and at 6-foot-2
could tell everybody how high the water would be by measuring just at
his hairline. They noted that much more rockpiling was needed over the
city\'s 30-inch water line that runs along the river and goes under the
levee to the city water treatment plant."

[]{#__RefHeading___Toc463882072
.anchor}![](media/image68.png){width="5.3125in"
height="3.0208333333333335in"}Figure 62 1982-83 (top) Grizzly Peak, CO
Snow Water Equivalent versus 1997-98 (bottom). Dotted green lines
indicate cumulative water year precipitation, versus normal (solid).
Dotted blue lines indicate Snow Water Equivalent, versus normal (solid).
This SNOTEL site is located in central Colorado. (from Western Regional
Climate Center)

> ![](media/image69.png){width="5.3125in" height="3.0208333333333335in"}

Between June 16 and July 1, the state of emergency was extended to all
counties along the lower Colorado (Yuma, La Paz and Mohave). The Coast
Guard halted recreation on the river, although several irate resort
operators threatened to file a suit to lift the ban. Additionally, a
suit was raised by the city of Needles, Mohave County and the Quechan
Indian tribe to stop discharges from Hoover, Davis and Parker dams.
Private damage at this point was estimated to be in the millions of
dollars. On July 1, the forecast was upgraded to 14.6Maf.

In the meantime, reservoir operators at Lake Mead and Powell were in a
difficult situation. Using the WSO to schedule high releases during the
springmelt season, the reservoir operators had forfeited their option to
safely raise releases if the forecasts were inaccurate. Hoover Dam
experienced its first spill since it was built in 1935. Flashboards
(wooden extensions) were installed on the top of Lake Powell to provide
temporary extra storage. Releases in excess of 95,000 cfs at Powell
caused cavitation in the spillway tunnels. House-sized boulders were
being thrown from the tunnels. However, by August, the flooding began to
abate.

The final estimate of damage to Glen Canyon Dam was \$40M. One estimate
of the total damage to communities was \$80M, although this did not
include damages caused by rising groundwater levels in Yuma
(deteriorating roads, filling septic tanks, lifting empty swimming
pools, etc). Throughout April-July 1983, 14.5 Maf arrived in Lake
Powell, approximately 200% of average for this period.

Then 15.2 Maf arrived during the following year. The early WSOs
indicated this, and the excess water was passed safely through the
system without incurring any damages. However, was not until 1986 that
flows returned to normal, with the basin experiencing four consecutive
years of high streamflow. The beneficial impact of the 1983 flood on the
Grand Canyon environment was erased by the steady elevated releases in
1984-1986. Regardless, this example is testament to the economic
importance of the WSOs because management based on a poor forecast
caused \$80M worth of damage. It also shows the Bureau of Reclamation's
ability to adjust to (*consecutive*) extreme wet events, even if
reservoirs are full, using only the WSOs.

### 4.4.2 Southeast Arizona Flood October 1983

During October of 1983, severe flooding in the southeastern portion of
the state occurred as a result of a dissipating tropical cyclone, which
caught many agencies unprepared and caused extensive damage. The peak
floods associated with this event were in excess of the estimate for the
100-year flood in several regions, prompting reevaluation of this
estimate after the event. It also exceeded the previous maximum flood of
record in several regions of Southeast Arizona. On Aravaipa Creek and in
Tucson, the discharge exceeded the previous maximum by 3.5 times and 2.2
times, respectively (Roeske et al., 1989). The tropical cyclone and the
resulting flood has been extensively studied (Hjalmarson, 1990; Roeske
et al., 1989; Saarinen et al., 1983). Flooding and lateral erosion
caused damages in Pima County alone in excess of \$63M ((Eychaner and
Rehmann, 1990), a higher estimate is \$105M by the Army Corps of
Engineers (1994)). Total damages were estimated at \$226.5M, with eight
lives lost and 975 injuries. The 1983 flood was unparalleled in the
Tucson community's history and had lasting impacts on flood control and
building ordinances.

Flood damage in Arizona is fundamentally different from the kind of
damage that is incurred in other parts of the country. FEMA regulations
focus on building away from areas that would be inundated by a major
flood. In the downcut arroyos of the desert southwest, damages are more
frequently incurred by lateral erosion. This is one example of how
standard practices and guidelines for other parts of the nation simply
do not apply in Arizona and can leave local communities vulnerable. In
addition, piecemeal floodplain planning and the build-damage-repair
mentality of some communities place them at risk. For example, Clifton
Arizona in the Upper Gila basin has experienced at least 13 damaging
floods in the past 100 years (including 1983 and 1993 (Hjalmarson,
1990)). Relocation efforts are only now beginning in order to prevent
future damages. The extensive damages that floods produce can be as much
the result of natural variability as they are the result of social
systems, values and policies.

### 4.4.3 The 1993 Central Arizona Flood

Severe flooding also occurred in January of 1993 across many portions of
the state, causing Presidential Disaster Declarations in all of the
counties in Arizona except La Paz and Mojave. While the peak flow of the
1993 event was smaller than the peak of the 1983 event, January and
February 1993 saw several peaks of similar magnitude, resulting in a
cumulative flow volume much greater than the 1983 event (MacNish et al.,
1993). The cumulative streamflow of the Salt and Verde Rivers during the
1993 event dwarfed the magnitude of previous flooding events, providing
1.8 Maf of streamflow in January and over 1 Maf in February 1993. With
an average annual flow close to 1 Maf, this meant that *the equivalent
to three full years of streamflow arrived in two months.*

As shown in Table 6 the WSOs grossly underestimated the amount of
streamflow. For both Coolidge Dam and the Salt River Project reservoirs,
an accurate forecast would not have prevented flooding, since the
observed flow exceeded the total capacity of each dam. The January 1993
Gila River streamflow into Coolidge dam was 884.9 kaf. The total
reservoir capacity is 880 kaf, although only 239.5 kaf of storage was
available at the time. The resulting spillway discharge was 32,800 cfs
on January 20, the maximum since the building of the dam. (MacNish et
al., 1993)

[]{#__RefHeading___Toc462466297 .anchor}Table 6. January 1 Water Supply
Outlooks of the 1992-93 Flood

  ----------------------- ------------- ----------- ----------- -----------
  River Forecast Point    January-May                           
                          Cumulative                            
                          Streamflow                            
                          1,000 ac-ft                           

                          Forecast      Observed    1960-91 Ave Obs/Fcst

  Salt River Nr Roosevelt 780           1,991       384         2.55

  Tonto Ck Abv Gun Ck,    105           436         43          4.15
  Near Roosevelt                                                

  Verde R Blw Tangle Ck,  350           1,371       209         3.91
  Abv Horseshoe Dam                                             

  Gila River At Calva     300           722         78          2.40

  Gila River At Safford   350           1,465       122         4.18
  Valley                                                        
  ----------------------- ------------- ----------- ----------- -----------

The flood caused unprecedented spills at all major dams within Arizona,
including Roosevelt Dam, which sustained serious damages to its
electrical facilities. The damages were most expensive in Greenlee and
Yuma counties. The largest expense in Greenlee County was from damage to
the Phelps Dodge Mine in Morenci (in excess of \$50M damage to a mine
tailings pond (US Army Corps of Engineers, 1994)).

Yuma was damaged when Painted Rock Dam (an Army Corps flood control
structure with a capacity of 2.5Maf (figure 1)) went from virtually
empty on January 4 to full on February 21. The peak discharge from the
dam was 25,600 cfs (compared to the inflow of 186,000 cfs), damaging all
of the nine major downstream crossings (primarily designed to withstand
5,000-10,000 cfs). The dam prevented an estimated \$100M in damages, but
Yuma county still sustained \$130M worth of public and private damage,
not including the extensive salinity damage to irrigable land because of
raised water tables. Total damages to the state exceeded \$400M,
including eight deaths and 112 injuries (US Army Corps of Engineers,
1994), making the 1993 flood the most expensive flood in Arizona's
history.

The 1993 event proved that current flood design techniques still
underestimate the magnitude of large floods. The magnitude of this event
is unprecedented in recent history, as are its damages. The 1993 event
is the crescendo of the resurgence of floods since the 1970's. Design
structures that were based on parts of the relatively flood-free period
from the 1920's to the 1970's all underestimate the current extreme
events. However, climate data suggests large-scale climate shifts in the
1920's and 1970's make the current period more like the turn of the
century (when large flooding happened in Arizona in 1891, 1905, and
1916) than the years in-between. Seasonal forecasts may not play a role
in design, but information about climate shifts and frequency of ENSO
events can play a role in determining which part of the record is most
appropriate to emphasize.

## 4.5 Summary

Perhaps there exists a simple guiding principle which adequately
captures the complex array of factors influencing water management
across the Southwestern US, but this study has not been able to discover
one. Water management practices and agencies in the Southwestern US are
as complicated and diverse as the watersheds they inhabit. While a few
practices are similar among all agencies, each agency is unique because
of a variety of factors, including, among others, water quantity,
quality and variability, monetary and personnel resources, and
management sophistication and flexibility. For example, while some large
water providers have the resources to create in-house climate forecasts,
other agencies only have resources for infrastructure operations and
maintenance. The capacities of these agencies to utilize a seasonal
forecast varies. In addition, several agencies have fixed operations to
satisfy many conflicting interests, relinquishing their ability to
interannually adjust operations based on a climate forecast. Some water
suppliers are required by law to use WSOs, and, while climate forecasts
may not directly impact decisions, incorporating climate information
into WSOs has the greatest potential for influencing actions. Also,
extreme event management information needs and options are distinct from
water suppliers, primarily because of the spatial and temporal scales
involved. Extreme events occur at any time in any place and, as a
result, extreme event managers have attempted to ensure as much safety
as possible with limited warning, making use of interannual forecasts a
new practice.

Finally, vulnerability results from the interaction between natural and
social systems and frequently a community can become highly vulnerable
because of its social practices. Therefore, changing social practices
can have as much or greater impact on reducing the impacts of flooding
than will incorporating seasonal forecasts into agency operations.

# CHAPTER 5

# CASE STUDY RESULTS

## Introduction

A survey was used to investigate the use of seasonal forecasts by water
management agencies in Arizona during the 1997-98 El Niño. It
investigated the sources of information which agencies found useful, as
well as how that information was integrated into decisions. The primary
objectives of the survey are to document:

1.  Which participants, if any, utilized climate information *prior to*
    the 1997-98 El Niño? What kinds of information? If so, how did they
    use it?

2.  What sources of information did participants consult during the
    1997-98 El Niño?

3.  What sources were considered valuable and why?

4.  What did the participants perceive the 1997-98 forecasts were
    expressing?

5.  How were the forecasts translated into operations?

6.  What options for action were available to agencies?

7.  What actions did the agencies commit, based on the forecasts?

It is reasonable to assume that, since climate forecasting and its
products are still in their infancy, the current products and actions
mentioned here do not represent the full utilization of climate
forecasting's potential. Additionally, management structures, objectives
and planning schedules may not be receptive to current or future
products. Section 5.2 discusses the approach of this survey, whereas
sections 5.3-5.5 discuss the acquisition of the forecasts through
various distribution channels, forecast interpretation by agencies and
their application, respectively. Section 5.6 investigates the internal
(technical) factors preventing full use of climate forecasts whereas 5.7
discusses the factors hindering use that are external to the climate
forecasts products. Chapter 6 synthesizes these findings and concludes
with recommendations to the climate forecasting community on future
directions.

## Case Study Approach

There is an extensive array of individuals involved with Arizona water
management, including numerous agencies as well as multiple individuals
within agencies. Arizona also has a diverse mix of communities, ranging
from urban centers to primarily agricultural regions to those supported
by tourism or mining industries. Climate information needs and
availability for these regions varies, along with available resources.
In some of the communities, extensive water management and flood control
structures exist (e.g. the Lower Colorado and Salt watersheds), whereas
others reside downstream of completely unimpeded flow (e.g. the San
Pedro and Upper Gila watersheds). This study balances the representation
of a wide range of interests with maintaining an in-depth analysis. For
this reason, sectors with populations so large that a representative
sampling could never be achieved with the resources available to this
study (such as individual water users), are represented by agencies
concerned with the interests and needs of these sectors, (such as state
level agencies). During preliminary analysis, several sectors also
identified themselves as being solely involved with water accounting and
distribution and did not perceive any potential in which their duties
could change from year to year. These agencies play a major role in
water management, yet they consider themselves insensitive to seasonal
forecasts. Additionally, there was a limited window of opportunity in
which this study could be conducted, as discussion revolved around a
specific event and the details of the agencies' experiences and actions
were susceptible to inaccurate recall if the interviews occurred too
long after the event. Interviews were conducted between May 1998 and
January 1999, with most occurring during the Summer of 1998.

[]{#__RefHeading___Toc463882073
.anchor}![](media/image1.png){width="3.9in" height="4.25in"}Figure 63
Survey participant locations (indicated by stars). Locations are
approximate to preserve participant anonymity.

The agencies included in this study relate primarily to water
management. Since conflicts exist between retaining water in reservoirs
and providing extra flood storage, EMAs as well as water providers are
investigated. Participants in this study included key personnel from the
Arizona Division of Emergency Management (statewide), five county level
EMAs, the Salt River Project, Tucson Water, the Gila River Water
Commissioner, Arizona Department of Water Resources (statewide), Santa
Cruz Active Management Area, the Upper and Lower Colorado River Basin
Bureaus of Reclamation, Maricopa and Pima County FCDs and the office of
the Governor (figure 63). With the exception of agencies with statewide
jurisdiction, all of the agencies chosen were located in regions that
experienced adverse effects from previous El Niño events, including the
1983 and 1993 floods. Although there are many additional agencies that
could be included, such as the Department of Transportation, the
Department of Public Services, the Department of Health, water users
(such as farmers) and various utilities, including wastewater
management, it is beyond the scope of this research.

The study format consists of a series of semi-structured interviews,
generally conducted in person and tape-recorded. Interviews lasted, on
average, approximately an hour and a half, with the shortest and the
longest single interviews lasting one hour and five hours, respectively.
The structured aspect of the interviews provided comparability between
interviews, yet the format was flexible enough to address issues unique
to certain communities and/or agencies. The first interview documented
the sources of information that various agencies used and what actions,
if any, were taken in preparation for El Niño. The second interview
focused on factors currently hindering the agency's use of forecasts;
participants were asked to review certain products (e.g. products from
NOAA, other sources with which they were familiar) and recommend format
and communication improvements. If necessary, a third interview was
performed. In addition, participants were allowed to subsequently review
their statements and provide clarifications, elaboration and
corrections.

Prior to the first interview, each subject received an eleven-page
questionnaire containing interview topics (Appendix A). This packet also
contained a timeline of events prior to and during the El Niño
(available from author), including a plot of MEI (figure 24), to aid the
subject in dating the reception of information about El Niño, and
actions taken by the agency. Some participants requested (and were
provided) an abbreviated version of the questionnaire. Several
participants received a packet of information about La Niña that was
distributed at a prior local NWS La Niña briefing (available from
author). Subjects were asked to provide feedback in the final interview
on the format and utility of the information and specific products
within. The packets of information and the questionnaire provide a
framework for the interviews, but the participants were allowed to
diverge and express concerns specific to their community, agency or
situation that were not foreseen in drafting the questionnaire. The
responses of individual participants are confidential, except with
explicit permission from the participant. Full written and tape recorded
notes of the interviews are archived and available from the author, in a
manner consistent with the confidentiality agreements.

The methodology of this study is consistent with other past studies
including Changnon's 1992 survey of agricultural decision-makers and
Pulwarty and Redmond's 1997 survey of Pacific Northwest agencies. While
this study may include fewer agencies (16 versus Changnon's 27 and
Pulwarty and Redmond's 19), previous studies did not conduct repeated
interviews. In addition, the majority of interviews of this study were
performed within four months whereas Changnon's study lasted two years.

One recognized limitation of conducting in-depth interviews with a
select population is that the resulting data does not lend itself easily
to quantitative analysis. While the frequency of a specific response to
a particular question can be explicitly counted, the results could be
misleading and would not be representative of the pool of participants,
nor of the water management sector as a whole. However, one advantage of
this study is its in-depth nature and the amount of freedom that the
participants were given to express their concerns and contribute their
ideas. The results of this study are a valuable contribution to the
scientific community's understanding of the role of climate forecasts in
water management, yet should not be considered a definitive guide.

## Sources of Information

[]{#__RefHeading___Toc462466298 .anchor}Table 7. Sources of Information
Summary

+-----------+---------------------------+-----------------------------+
| *         | **Advantages**            | **Disadvantages**           |
| *Source** |                           |                             |
+-----------+---------------------------+-----------------------------+
| NWS       | Trusted expertise;        | Limited resources; Has      |
|           | Established contacts with | lesser involvement in       |
|           | agencies                  | remote communities          |
+-----------+---------------------------+-----------------------------+
| Agency    | Good for intra-,          | Infrequent; Occasionally    |
| briefings | inter-agency              | difficult to understand if  |
|           | coordination; Interactive | non-interactive             |
+-----------+---------------------------+-----------------------------+
| In-house  | Integrates well into      | Not all agencies have       |
| research  | operations;               | sufficient resources,       |
|           |                           | capacity to conduct         |
|           | High confidence in        |                             |
|           | findings                  |                             |
+-----------+---------------------------+-----------------------------+
| Internet  | Wealth of data for        | Information overload;       |
|           | conducting independent    | Unregulated; Some agencies  |
|           | in-house research;        | lack access; Time consuming |
|           | Participatory, active     |                             |
+-----------+---------------------------+-----------------------------+
| Public    | Understandable, timely,   | Alarmist, superficial, low  |
| media     | pervasive                 | skill                       |
+-----------+---------------------------+-----------------------------+
| Uni       | Extensive expertise,      | Difficult to approach and   |
| versities | resources                 | utilize; Lack of central    |
|           |                           | contact point               |
+-----------+---------------------------+-----------------------------+

### 5.3.1 National Weather Service and Agency Briefings

All of the participants located in cities with NWS forecasting offices
reported having contact with NWS meteorologists in obtaining valuable
information about El Niño. This is partly because agencies have
established contacts with the NWS from previous weather-related events
such as flash flooding. It is also partly because the NWS was active in
a series of agency briefings in several cities before the event (Table
8). These meetings were sponsored and organized by local or state EMAs.
Where appropriate, large water providers participated in these meetings
and provided information about reservoir levels and their estimate of
the threat of spillage, or lack thereof. The material presented at these
meetings often focused on describing the El Niño phenomenon, providing
the latest status of the Pacific Ocean and reviewing historical impacts
of El Niño on the Southwestern U.S.. Frequently presented were NOAA
products, including the CPC outlooks, along with some historical data
specific to the city where the meeting was being held.

Some of the participants located in cities where NWS briefings did not
occur reported having contact with the NWS, although the contact was not
as frequent or in-depth as with participants located in cities with
local NWS offices. ADEM and the state office of the NWS were also
involved in at least ten briefings across the state in communities that
do not have NWS forecasting offices. These briefings were part of the
assistance provided by ADEM upon request of various counties.

For the participants that had no contact with the NWS, it is not clear
if they knew the NWS had resources available for them. When one user was
asked if he received information from the NWS, he replied sincerely,
"National Weather Service? That would be the Weather Channel,
\[right\]?" While one would not expect their forecasts to diverge
wildly, the Weather Channel is a private company not officially
affiliated with the NWS.

In addition, the University of Arizona held a regional climate
vulnerability workshop in September 1997. This workshop was one of a
series of US Global Change Research Program workshops held nationwide in
1997 and 1998. Three individuals participating in this study attended
the workshop, and each reported that it was helpful although for
different reasons. One participant reported that he found the
presentations informative and still refers to the materials distributed.
Another reported that he usually "learns more during the coffee breaks
than the actual seminar". While many of the details presented were too
technical for his tastes, he had the valuable opportunity to interact
and establish contacts with scientists and other agencies. *Establishing
and strengthening links of communication between agencies was an
integral part of the preparation for the El Niño event, the results of
which will have lasting beneficial impacts during future events.*

[]{#__RefHeading___Toc462466299 .anchor}

Table 8. Select Planning Meetings in Preparation for the 1997-98 El Niño

+-----------------------+-----------------------+----------------------+
| [Coconino             | [La Paz               | [Maricopa            |
| County]{.underline}   | County]{.underline}   | County]{.underline}  |
|                       |                       |                      |
| Oct 3, 1997,          | Nov 12, 1997, Parker  | Oct 2, 1997, Tempe   |
| Flagstaff, AZ         | AZ                    | AZ                   |
+-----------------------+-----------------------+----------------------+
| [Mohave               | [Yavapai              | [Pima                |
| County]{.underline}   | County]{.underline}   | County]{.underline}  |
|                       |                       |                      |
| Oct 16, 1997          | Dec 12, 1997,         | Sept 26, 1997,       |
| Laughlin, NV          | Prescott AZ           | Tucson AZ            |
+-----------------------+-----------------------+----------------------+
| [Pinal                | [Navajo               | [Yuma                |
| County]{.underline}   | County]{.underline}   | County]{.underline}  |
|                       |                       |                      |
| Oct 22, 1997,         | Nov 18, 1997, Kayenta | July 1, 1997, Yuma   |
| Collidge AZ           | AZ                    | AZ                   |
|                       |                       |                      |
|                       | Nov 20, 1997, Piñon,  | July 18, 1997, Yuma  |
|                       | AZ                    | AZ                   |
|                       |                       |                      |
|                       |                       | Aug 15, 1997, Yuma   |
|                       |                       | AZ                   |
+-----------------------+-----------------------+----------------------+
| Western States FEMA   | Committee on          | Committee on         |
|                       | Science's             | Resources'           |
| "El Niño Community    | subcommittee on       | subcommittee on      |
| Preparedness Summit"  | Energy & Environment  | Water & Power        |
|                       | "Preparing for El     | "Oversight Hearing   |
| Oct 14, 1997          | Niño" Sept 11, 1997,  | on the Water         |
| California            | Washington DC         | Management           |
|                       |                       | Implications of the  |
|                       |                       | 1997-98 El Niño" Oct |
|                       |                       | 30, 1997, Washington |
|                       |                       | DC                   |
+-----------------------+-----------------------+----------------------+

### 5.3.2 Inter- and Intra-Agency Communication and In-House Research

In addition to meetings involving the NWS, more frequently informal
gatherings of agency personnel proved useful in exchanging information,
coordinating efforts and helping agencies prepare. These meetings were,
in some cases, periodic meetings between agencies and the subject arose
of what was known about El Niño, what could be expected from it and what
can be done about it. In other cases the meetings were called out of a
special need to specifically address El Niño and were not periodic.
Likewise, inside agencies, similar meetings occurred to coordinate
internal activities.

In many cases, an agency or individual assumed responsibility for or was
assigned the task of gathering information, tracking the event and
briefing others on their findings and predictions. Occasionally this
person had meteorology training, but often it was out of their personal
interest in the subject and availability of free time and resources. For
example, ADEM dedicated an intelligence officer with a background in
climatology and flooding to gathering and tracking El Niño information.
In a mid-sized community, one city worker was a pilot, had an interest
in aviation weather, and was pro-active about briefing other agencies.
These people were often surprised by how much the others already knew
about El Niño from other sources, although the information previously
received was not necessarily accurate (for example, information from the
media).

In September 1997, the office of the Governor of Arizona coordinated the
activities of various (primarily state) agencies to prepare for and
respond to Hurricane Nora. This special arrangement was transformed into
an **"El Niño Task Force"** which originally intended to hold periodic
monthly meetings before and throughout the winter to brainstorm possible
preparations. Status reports were provided to the Governor on a
bi-weekly basis and the task force disseminated information through an
Internet site maintained by ADEM. As the winter progressed, it was clear
that no flooding would occur and that the threat had passed, the
meetings became less periodic. The meetings that did occur included a
meteorologist from the NWS who provided information about El Niño, its
historical impacts and the CPC climate outlooks. Interactively, the NWS
and agencies crafted a series of scenarios and their probability of
occurrence (e.g. Is the inundation of Flagstaff with snow a likely
occurrence? If so, what is our plan of response? What are our plan's
weaknesses? What can be done to remedy the situation?). In the last
aspect, the NWS informally recommended that major structural activity to
prepare for El Niño in Arizona (as opposed to California) was not
necessary. It would be more efficient to prepare for and respond to
individual events as they materialized.

For those participants that perceived themselves vulnerable to El Niño
and desired to commit major tangible preparatory activity, the process
of gathering information was always buttressed with in-house research.
For instance, actions taken by SRP were accompanied by in-house analysis
of streamflow during El Niño years in order to increase their confidence
in releasing water from reservoirs. The Lower Colorado Bureau of
Reclamation's research showed that streamflow from the Upper Colorado
River Basin did not have a strong or consistent enough signal for the
agency to commit to serious action. However, the Upper Colorado Bureau
of Reclamation's in-house research revealed a tendency for the WSOs to
underestimate actual streamflow during strong El Niño years and they
manually adjusted their operations appropriately (figure 64, see also
Pulwarty and Melis (1999)). While individual agencies may not have the
sophisticated research tools available to climate forecasters, the
confidence agencies have in in-house research (no matter how elementary)
and internal products is always greater than external products. Although
one water provider joked that they only consider external forecasts,
products and information that are consistent with their internal
findings, beliefs and intuitions, there is an element of truth to the
statement. Conservative by nature, water providers require a thorough
understanding of and a higher level of confidence in forecast products
than other users. *These examples highlight the special desire and need
of water providers for confident, local and complex climate products and
agencies' inability to incorporate national products, at face value,
into actions.*

In a rudimentary way, experiencing previous floods and mentally
associating those events with El Niño is a form of in-house research.
Only one participant did not report being in his current position and/or
living in Arizona during past flooding events. Some participants
recalled floods as early as the 1970's. The experience of past flooding
events such as the 1983 or 1993 floods combined with the early
comparison of the 1997-98 event with the 1983 event lent credibility to
the threat of flooding and the desire to be proactive. For the
participant that had not experienced past events, the threat of flooding
was less tangible. The rarity of flowing water (much less high flows) in
many of Arizona's rivers and the stereotypically dry nature of the
region can cause one to discredit ![](media/image70.wmf){width="3.5in"
height="3.0in"}the potential for large flooding, until one has
experienced it.

[]{#__RefHeading___Toc463882074 .anchor}Figure 64 Lake Powell Water
Supply Outlook error versus Southern Oscillation Index (1967-98). June
to November average SOI is plotted on the x-axis, with strong El Nino
events located on the left. Observed minus forecast is plotted on the
y-axis and positive value indicate underestimation. For example, note
severe underestimation during 1982-83 El Nino. 1997-98 denoted by star.
The correlation coefficient between variables is --0.47.

### 5.3.3 The Internet

At the NWS/EMA meetings, the addresses of official web-sites pertaining
to El Niño were provided. All but four of the participants surveyed
stated that they used the Internet and that it was a very useful tool in
gathering information. *Several participants stated that this year's
experience with El Niño was radically different from previous
experiences because of the wealth of information on the Internet.* The
Internet was non-existent in 1980's and was very limited in scope and
accessibility in the early 1990's. In the late 1990's, the Internet is
pervasive and exponentially growing, containing extensive data (but not
necessarily "information"). One participant developed a strong
appreciation for the Internet as a result of El Niño because of the
convenience and quantity of information available, noting that
previously he would have had to travel to local libraries to seek out
scientific publications. Likewise, users appreciated the Internet as a
tool for actively gathering information, as opposed to public media,
which provides a passive method for gathering information.

Sites visited included a spectrum ranging from NOAA sites about El Niño
that provided technical information and forecast products to sites
providing more regional information, such as the Western Regional
Climate Center. Also included were general media sites such as \"USA
Today\" and \"The Weather Channel\" that provided more generic
qualitative information about El Niño. Participants were more inclined
to believe information presented on the Internet than on television,
despite some of the sites being sponsored by the media. Users perceived
the Internet material to be better researched and more in-depth. Several
agencies also monitor near real-time conditions for precipitation and
streamflow via the Internet and find use for this information in
operations. They expressed concern, however, that these sites become
busy and data transfer rates slow to a crawl precisely during the
periods they are most needed: during events.

One disadvantage of the Internet is that climate data can be taken out
of context when included in a setting other than its original format.
The separation of the CPC seasonal outlooks from the full package of
data (including the legend) necessary to interpret them is a clear
example of this. Another, more subtle, example seen on both the Internet
and in the media, is when a prediction is provided without acknowledging
who produced the forecast, what methods were used to produce it, the
past performance of the forecaster, the confidence in the forecast and
so on.

### 5.3.4 The Public Media

Media coverage of the event proved to be both positive and negative.
Many users reported that they first heard about this event and the
possibility that it would be a large event from the general media.
Widespread coverage of the event also increased public awareness about
flooding and preparedness. Anxiety caused by alarmist predictions from
the media also caused EMAs to seek out more information to assess the
credibility of such forecasts. As more information was obtained,
individuals recognized that the media predictions were unrealistic and
instead relied on the NWS and/or the Internet. Participants reported
that the prime motivation in gathering information was to
*realistically* assess the threat that El Niño posed. This included
discounting inflated, alarmist predictions, while at the same time
taking them seriously enough in case the threat was real.

While increased public awareness was considered beneficial, EMAs often
found themselves trying to correct misconceptions and ease the fears of
citizens concerned about the predictions from the media. For example,
one EMA reported seeing a local news report discussing El Niño that
provided information on how to protect one's house from damage against
high winds. As far as he was aware, of all the impacts in Arizona
anticipated from El Niño, gale force winds was not among them. A FCD
also stated that the media predictions caused an unprecedented number of
phone calls to the agency from panicked citizens, demanding, among other
things, that the agency provide sandbags (a task that is not of the
FCD's responsibilities). This user also reported a great number of false
alarms from citizens, lengthening its response time and reducing its
effectiveness during events.

Participants with less access to information felt that the qualitative
forecasts by the media were sufficient to help them determine to what
extent they should prepare. However, when these participants were asked
to describe what El Niño was, some of them had only a cloudy, and in one
case completely inaccurate, understanding. Low resource EMAs tended to
have the least clear understanding of El Niño, but as one manager aptly
stated, it's not important that they know about everything, but rather
that they know who to contact. This is understandable because EMAs are
involved in a wide range of threats from hazardous materials to domestic
terrorism, not just El Niño. Some EM personnel have not had formal
meteorology or climatology training and several stated that, before this
year, El Niño was an unfamiliar concept to them.

### 

### 5.3.5 Universities

When asked to what extent the users had direct contact with scientists
while obtaining information about El Niño, aside from the climate
variability workshop, only two individuals reported having extensive
contact with researchers at local universities. One user had recently
left the university and existing contacts were easily re-established,
while the other has a long-standing relationship with local
universities. One participant stated that if the NWS had not been as
active in providing information as early as it did, he would have
approached the local university as an alternative source. Contact with
the NWS was preferable for users with no previous University contact.
One user said of the University, "There's a perception of
inaccessibility\... It's a huge resource that's not easily tapped."

The University Agricultural Extension agencies are an exception to this
inaccessibility. They are generally viewed as valued resources of
practical information for the agricultural community (which constitutes
at least three-quarters of Arizona's yearly water demand). They are an
effective mechanism for transferring research findings and technology
from a previously inaccessible research setting to users, providing
contact on a regional and personal scale. The success of Agricultural
Extension agencies deserves investigation and emulation by agencies
wishing to transfer research products to users.

## 5.4 Interpretation of Information

Few users formally used probabilistic distributions in their
decision-making processes. Those that did generally received their
information from a technical specialist interpreting a NOAA product.
Instead, most used a simple qualitative forecast that the winter would
be wetter than normal and there was an increased chance of flooding.
These users more often relied on the media or some other source of
information that did not emphasize the probabilistic nature of the
forecasts. *Universally, the farther the information traveled from CPC
products, the less quantitative and probabilistic it became, suggesting
that its format is at fault.*

[]{#__RefHeading___Toc462466300 .anchor}Table 9 Forecasts versus Agency
Expectations

+------------------------------------+---------------------------------+
| *What the Climate Forecasts        |                                 |
| Expressed:*                        |                                 |
|                                    |                                 |
| Approximately a 50% Probability of |                                 |
| Seasonal Rainfall Totals           |                                 |
|                                    |                                 |
| being in the Wettest 33% of Record |                                 |
| (1961-90)                          |                                 |
+------------------------------------+---------------------------------+
| *What Agencies Prepared For:*      |                                 |
+------------------------------------+---------------------------------+
| Business as Usual                  | 100% Above Normal Rainfall      |
|                                    |                                 |
| 5-10% Above Normal Rainfall        | Flooding equivalent to 1992-93  |
|                                    | Flood Flooding worse than       |
| 50% Above Normal Rainfall          | 1992-93 Flood                   |
+------------------------------------+---------------------------------+

The participants that actively prepared for the event first needed to
translate the forecasts into *quantitative* estimates of how much
rainfall or streamflow was expected. Sample participant responses are
included in table 9. On occasion, a translation was provided by other
agencies, by in-house research, or informally by the NWS. The wide range
of expectations may represent an accurate downscaling of CPC products to
the microclimates of various regions, or it may indicate
misunderstandings between the scientific community and users as to the
meaning of the forecasts and products, or a combination of both.
Evidence from this study suggests that the latter is a more reasonable
and likely explanation than the former.

The Phoenix NWS provided state agencies and the governor's task force
with data about El Niño and what to expect, but also with informal
recommendations on the level of preparations that agencies should engage
in. The NWS expressed that, while the worst case scenario of widespread
flooding was possible, something considerably less than that was more
likely to occur. Consequently, the NWS advised that agencies should wait
and see as the event progressed before serious action should be taken.
Various agencies, including ADEM, developed a list of structures and
communities at risk if the worst case scenario were to occur. Based on
the NWS's recommendations, agencies focused resources on some of the
higher risk entities (i.e. Yuma and the crossing of I10 at the Gila
River) but did not take extraordinary measures to address every risk.
*Agencies found this interpretation, by local scientists, of information
into something closer to what the forecasts meant for operations
extremely useful*. Likewise, agencies in metropolitan Phoenix were
appreciative of the Salt River Project's advice that, given the
available storage in their reservoirs, flooding would be unlikely and
panic was unnecessary. Previous studies suggest that lack of "special
handling" and enrichment of forecasts prevent their routine (Callahan et
al. (1999), Pulwarty and Redmond (1997), and others).

Six of the 15 agencies surveyed had the advantage of having a person on
staff who was well educated about climate and weather, often a
professional meteorologist. This person often assumed responsibility for
tracking the event and providing others with information about El Niño
and what to expect from it. In general, if the resources are available
and climate variability has a major impact on the agency, then it will
have the capacity to internally translate CPC forecasts into a useable
form. This is not the case for agencies that do not have resources
available, despite their climate vulnerability.

Especially for EMAs, a sense of urgency and need for action was not
solely (or even mostly) based on the official climate forecast products,
such as the CPC outlooks. In an atmosphere of widespread awareness of El
Niño and a general belief that flooding could occur, most agencies
wanted to be prepared for possible flooding. Interagency meetings and
interest at the state level (and to a lesser extent public interest)
encouraged agency awareness and, proactively, preparedness. These
agencies did not utilize the specific details of the forecasts but they
tried to, in one user's words, "Prepare for the worst, but hope for the
least". If the occurrence of a large El Niño indicates to agencies to
prepare for the worst, the benefits of increasingly detailed forecasts
are questionable.

Additionally those structures that were determined as being at risk were
structures that are *always* at risk for flooding, with the exception of
new projects in the floodplain. This assessment was similar to the
strategy employed by the Governor's El Niño task force who "identified
what the worst \[flooding event\] would be. We went back to the previous
flooding to identify where the pockets of devastation were and the
damage was done and tried to say 'Well, have we cleaned that up since
the last flooding?' and if we haven't cleaned it up since the last
flooding, what can happen this time and what will we have to do to be
prepared to handle that?" For preparations like this, forecast details
are not utilized and/or are not necessary and that if a large El Niño
event were to reoccur, preparations would not be substantially different
than preparations engaged in before the 1997-98 event. *In summary,
increasingly detailed products may not change how certain agencies
(especially EMAs) prepare for an event.*

## 5.5 Agency Response

Federal interest in the event was great, especially with concern over
the potential negative impacts in California. While indices, such as the
MEI, rapidly grew during the summer of 1997 (figure 24), agencies and
the public became involved and interested in preparations for the event.
In September and October, congressional hearings on preparing for El
Niño were held and in October, FEMA sponsored the El Niño Community
Preparedness Summit in California. As Hurricane Nora approached Arizona,
a task force was developed at the state level to coordinate a response.
Remnants of this task force were formed into Governor Jane Dee Hull's
"El Niño Task Force", described earlier in section 5. Most activities by
agencies involved mindset, reviewing emergency response plans and
improving links of communication between agencies. While the majority of
physical activities related to preparing for El Niño occurred on a
community level, the interest expressed by the state government
encouraged local agencies to engage in El Niño related activities.
Statewide activities however, were purposefully conducted away from the
public eye to avoid citizen panic (e.g. the clearing of vegetation and
deepening of the channel of the Gila River near the crossing of I10, the
major interstate between Tucson and Phoenix).

The remainder of this section details the activities engaged in by
agencies in Arizona in preparation for the 1997-98 El Niño, including
discussion of some of the factors influencing these decisions. Due to
the sampling procedure used in this study, there is the distinct
possibility that other activities may have occurred by agencies not
represented. However, special attention has been paid to documenting at
least the major activities.

### 5.5.1 Water Providers

The activities of water providers in Arizona, for the most part, were
unchanged by the El Niño forecasts and the anticipated impacts. This is
partly because a large portion of water providers rely solely on
**groundwater pumping**. The exceptions were those agencies that took
structural measures to protect pumping infrastructure that could have
been damaged by high flows in the rivers. Many surface water agencies
were already facing low reservoir levels and, given the amount of flood
control space available, further water releases were inappropriate.
During the summer of 1997, special activity occurred along the Upper
Gila to retain water in the San Carlos reservoir (behind Coolidge Dam).
Falling reservoir levels promised a massive fish kill, unless releases
to downstream users were halted. A variety of agencies coordinated to
purchase 17,000 acre-feet of CAP water (at \$650,000) to be delivered to
downstream irrigators through the **Gila River Commissioner**, in place
of reservoir water. Reservoir inflow from a storm during the week prior
to Hurricane Nora raised the storage to an amount sufficient for
releases to be resumed.

While, in this case and others, inactivity was an appropriate action, it
is difficult to determine if the inactivity arose from a thoughtful and
thorough analysis of the threat of flooding or apathy. For example, if
Arizona's reservoirs had been full entering the 1997-98 water year, it
is impossible to determine if water providers actions would have been
the same, especially since the interviews of this study were conducted
after the completion of the event. Investigating water providers'
actions when reservoirs are full and the forecast is for wetter than
normal conditions (or vice versus with empty reservoirs and a dry
forecast) would prove more revealing.

[]{#__RefHeading___Toc462466301 .anchor}Table 10 Water Provider Agency
Response Summary

+--------------+------------------+------------------+-----------------+
| **Agency**   | **Action**       | **Reasoning**    | **Result**      |
+--------------+------------------+------------------+-----------------+
| Primarily    | Business as      | Groundwater      | Recharge        |
| groundwater  | usual. Protect   | supply not       | indeterminable. |
| providers    | pumping          | visibly affected | Flood damage    |
|              | equipment        | by interannual   | did not occur   |
|              |                  | variability      |                 |
+--------------+------------------+------------------+-----------------+
| Gila River   | Business as      | Adequate storage | Streamflow not  |
| Commissioner | usual            | for potential    | exceptional,    |
|              |                  | flood already    | dry conditions  |
|              |                  | existed, legal   | persist         |
|              |                  | constraints      |                 |
+--------------+------------------+------------------+-----------------+
| Salt River   | Reduction of     | Small storage    | Verde           |
| Project      | groundwater      | capacity on      | reservoirs      |
|              | pumping by       | Verde watershed, | fill, with      |
|              | 41,000           | past history of  | minimal spill   |
|              | acre-feet, water | flooding.        | (\<52,000       |
|              | replaced with    | Adequate storage | acre-feet).     |
|              | surface water    | in Salt River    |                 |
|              | from Verde basin | reservoirs       | \$1M in         |
|              | reservoirs       |                  | groundwater     |
|              |                  |                  | pumping costs   |
|              |                  |                  | avoided         |
+--------------+------------------+------------------+-----------------+
| Upper        | Additional       | Poor performance | Hydrologic      |
| Colorado     | releases to      | of hydrologic    | forecasts did   |
| River Bureau | provide 2 Maf    | forecasts during | underestimate   |
| of           | storage in Lake  | 1983 (8 Maf      | streamflow but  |
| Reclamation  | Powell beyond    | forecast, 15 Maf | uncontrolled    |
|              | what was         | observed) and    | flood releases  |
|              | available during | 1995 spring melt | not necessary   |
|              | the 1983 flood   | (6 Maf fcst,     |                 |
|              | (4 Maf total)    | 11.8 Maf obs)    |                 |
+--------------+------------------+------------------+-----------------+
| Lower        | Receive water    | Equilibration of | See Upper       |
| Colorado     | from Lake        | reservoir levels | Colorado River  |
| River Bureau | Powell.          | with Lake        | Bureau of       |
| of           | Additional flood | Powell. Space    | Reclamation     |
| Reclamation  | control releases | building         |                 |
|              | in April 1998    |                  |                 |
+--------------+------------------+------------------+-----------------+
| Comision     | Reduce           | 1996-97 high     | 1.7 Maf         |
| Nacional del | groundwater      | flows, Colorado  | utilized,       |
| Agua         | pumping. Utilize | R reservoir      | remainder (2.3  |
| (Colorado    | excess flows     | status and       | Maf) flowed to  |
| River in     |                  | declaration of   | Gulf of         |
| Mexico)      |                  | 1997-98 surplus  | California.     |
+--------------+------------------+------------------+-----------------+

One notable action taken by water providers is the reduction of
groundwater pumping by the **Salt River Project** (SRP) in August 1997.
In any given year SRP satisfies at least 2/3 of its one million
acre-feet per year demand with surface water from the Salt and Verde
River watersheds. The agency originally anticipated pumping 184,000
acre-feet of groundwater but reduced this amount by 41,000 acre-feet.
The reduction in pumped water was replaced with reservoir water from the
Verde watershed. When the confidence was sufficiently high that it would
be a wetter than normal winter, groundwater pumping was reduced to its
monthly legal minimum and maintained at those levels until increasing
the rate of pumping would be necessary. SRP drew up a contingency plan
that if the anticipated rainfall had not begun by March 1, the project
would have resumed groundwater pumping. Had the contingency plan been
enacted, it would have cost an anticipated \$5-6M in groundwater pumping
to make up for the releases and water recreation would have been
disrupted during the summer of 1998. Since the winter was wetter and the
contingency plan not activated, the project ended up saving \$1M by
their actions.

The water was released from reservoirs on the Verde Watershed because of
its relatively small reservoir storage compared to the Salt Watershed.
The annual streamflow from each watershed is roughly comparable, but
environmental regulations prevent structural development of the Verde
and, hence, it is viewed as being a much higher flood risk. An in-house
meteorologist assumed responsibility for tracking the event, and
considerable in-house research augmented SRP's confidence in taking
their actions. From in-house research, SRP had determined that an
enhanced and late streamflow season could be expected from El Niño.
Therefore, they were not surprised by the great lack of precipitation in
January and they did not shift to their contingency plan during this
time.

There are two perspectives on SRP's actions, in that they were both
minor and major. The quantity of water released (41,000 acre-feet)
represents approximately 13% of the Verde system storage, 2% of the
entire project's storage capacity and approximately 4% of the project's
yearly demand. It is less than two thirds of the estimated annual
evaporation rate from Roosevelt Lake, alone (68,000 acre-feet/year
(ADWR, 1994)). The advance warning for one of the largest El Niño events
of the century influenced what could be considered an insignificant
portion of the project's water. Likewise, \$1M represents less than 10%
of the yearly water and irrigation revenues and is dwarfed by SRP's
\$1,500M total operating revenues (mostly consisting of hydropower
revenues (SRP, 1999)). However, before this year, SRP had never formally
incorporated a climate forecast in their reservoir operations and so
acting on these forecasts was a new and important development.

In contrast to SRP, the management agencies along the mainstem of the
**Colorado River** faced a more challenging situation. As discussed
further in chapter 4, prior to the filling of Lake Powell, the mainstem
of the Colorado did not experience much, if any flooding. Management
decisions based on poor WSOs caused unprecedented flooding in 1983, the
last major El Niño event. In addition, flooding in 1992-93 (another El
Niño episode) from the Gila River caused significant damage to Yuma
below the confluence of these rivers.

During the period from the mid-eighties to the mid-nineties, the
reservoirs on the Colorado fell to significantly below capacity but,
starting in 1996-97, they had returned to conditions identical to those
prior to the 1982-83 event: full. Needless to say, when the comparison
between the 1997-98 and 1982-83 events were made, it had stakeholders
along the Colorado concerned, especially those in Yuma who perceived
themselves doubly vulnerable to flooding from each of the rivers.
Section 5.5.2 discusses some of the emergency management activities that
occurred in this region, and the remainder of this section will focus on
the activities of the **Colorado River Bureau of Reclamation.**

Chapter 4 illustrates the different management strategies of the upper
and lower basin Bureaus, and, not surprisingly, the response to the
event also varied between the basins. With SOI time series data
personally provided by NOAA scientists, the **Upper Bureau** conducted
in-house research that suggested that strong El Niño conditions favored
late snowpack and a cold spring, something that can cause the WSOs to
underestimate streamflow. Indeed, the January 1 WSO of the 1998 spring
melt season for inflow to Lake Powell was very similar to the early
forecasts of the 1983 and 1995 seasons (7.8, 6 and 6.5 Maf in 1983, 1995
and 1998, respectively). Anticipating that the WSOs would underestimate
the flow for the season, the Upper Bureau manually adjusted the
forecasts and operated their reservoirs accordingly in an attempt to
provide extra flood space (4 Maf space in total). Since a strong El Niño
was underway, avoiding uncontrolled flooding took precedence over
attempting to capture as much streamflow as was possible. In the end,
the WSOs did underestimate the streamflow by approximately two Maf
(\~25%).

In contrast to the Upper Bureau, the **Lower Bureau** responded with
different objectives. To equilibrate the reservoirs, Lake Mead received
and stored the excess water that Lake Powell was releasing. Lake Mead
has explicit space for flood control so the threat of this reservoir
losing control was less than that of Lake Powell, which has none. With
the exception of April, the Lower Bureau relied exclusively on the
releases from Lake Powell and the WSOs to determine its releases. During
April 1998, although the WSO did not call for it, releases were
continued at 20-25,000 cfs, but then were reduced at the end of the
month when the threat of flooding diminished.

The Mexican counterpart to the Bureau of Reclamation, the Comision
Nacional del Agua (CNA), like SRP, balance deliveries of surface and
groundwater. CNA reduced groundwater pumping by 0.2 Maf in anticipation
of a surplus of Colorado River water (CNA, personal communication 1999).
The 1.7 Maf represents the maximum that Mexican water users utilize
because of water delivery infrastructure limitations and lack of
resources to put additional fields into production in wet years. Any
excess water flows to the Gulf of California. Although an exact figure
is not available, the financial savings from the reduced groundwater
pumping can be estimated at approximately \$5M, based on SRP's estimated
savings per acre-foot of water.

Water management is a very complicated activity and various water
providers have different capacities and options to act on a seasonal
forecast. During the 1997-98 El Niño, agencies engaged in preparatory
activities based on a number of factors, including (but not limited to),
reservoir status, legal constraints and management flexibility.
Activities that took advantage of the forecast, leading to financial
gain, were from agencies that manage both surface and groundwater (SRP
and CNA). Other agencies used the forecasts primarily to enhance
protection against flooding without any obvious financial benefit
(Bureau of Reclamation). The remaining water providers were unaffected
by the forecasts and engaged in business as usual (Gila River,
Groundwater Providers).

### 5.5.2 Flood Control Districts & Emergency Management

With the increased awareness of El Niño, the **FCDs'** additional
preparation involved expanding, and focusing their yearly training. One
participant reported adjusting the yearly drills to focus on flooding on
the major rivers rather than local flooding from thunderstorms. His
in-house research revealed that flooding during El Niño years tends to
occur on the major rivers. Additionally, this FCD performed extra field
maintenance on their ALERT raingauge system to ensure proper monitoring
capability. The other FCD felt that no action is necessary because it
perceived itself as always being maximally prepared, regardless of El
Niño. The structures of the FCDs are designed to withstand the 100- or
500-year floods, and strong El Niño years are already included in those
computations. This participant perceived that there was nothing that he
could do that is not already done every year, qualifying his statements
by observing that it would not be feasible to engage in *fewer*
activities during La Niña years. However, this participant also stated
that El Niño temporarily halted, but did not reverse, budget reduction
trends.

FCDs also participated in meetings and flood drills sponsored by
**EMAs**. All of the EMAs surveyed sponsored some type of interagency
briefing, as described at the beginning of this section. ADEM was
involved with the NWS in a number of briefings in various cities in
Arizona (see Table 8) and also provided all counties with the
opportunity to request help in mitigation; the level of assistance
provided was based on the response received from the counties.
High-resource EMAs also sponsored agency briefings about El Niño,
providing information, reviewing flood response plans, strengthening
lines of communication with other agencies and assuring that adequate
resources (e.g., sandbags) were at hand. Low-resource EMAs faced a
difficult task; they undertook some similar activities but in one
manager's words, \"El Niño showed us where we weren't\". This user was
concerned about the lack of preparedness in the community and frustrated
with the lack of available resources. In general, major structural
activities were avoided by EMAs and FCDs because they considered it more
efficient to respond to individual storms rather than attempt to broadly
reduce flood risk.

EMAs also engaged in gathering and distributing information (through
printed and other materials) about El Niño to other agencies, to the
public and to the media. For example, one participant prepared a mailer
about El Niño and flood preparedness for a member of the city
government, at her request, to distribute to her constituents. This
mailer was then picked up and used by other city government members in a
similar fashion. Frequently this information was gathered through the
Internet, although several emergency managers expressed frustration with
the amount of time that was spent trying to find useful information.

Of the communities concerned with flooding, Yuma was the most concerned
and took the most action. With a history of flooding from two different
rivers in 1983 and 1993, rising water tables, and damage from Hurricane
Nora, the community perceived that the threat was very serious. ADEM
focused its earliest special activities of the season in the city of
Yuma, and La Paz, Mohave, and Yuma counties. This included identifying
potential hazards in the field, prioritizing mitigation opportunities,
engaging in public education and providing information about flood
insurance. Minimal structural flood mitigation occurred, instead the
intent was to maximize flood response capacity and efficiency. This
model was first applied in Yuma and then, on a smaller scale, in the
rest of the state.

Several communities purchased mechanical sandbaggers (automatic or
manual), including one of the participants of the study. This
participant stated that his reason for buying it was that FEMA was
selling them at an especially low rate. After prompting, the participant
conceded that they might have had their price reduced because of El
Niño, although he could not say definitely if this was the case. It
should be noted that while *some* equipment was purchased, it did not
begin to approach the amount that was purchased by California EMAs. In
California, emergency funds were distributed in advance of the event,
and this did not occur in Arizona, preventing serious preparation
expenditures.

Preparations for the 1997-98 El Niño by Extreme Event Management
Agencies were primarily designed to increase the effectiveness of
agencies to respond to flooding, were an event to occur. Major
structural activity did not occur mostly because agencies lack resources
and/or attempt to keep structures safe during all years, not only during
El Niño events. Use of the forecasts was largely qualitative (such as
the comparison of the 1997-98 El Niño to the 1982-83 event). Other
factors, such as publicity of the event and interest by the State,
played as much of a role as the forecasts in prompting action.

[]{#__RefHeading___Toc462466302 .anchor}Table 11 Extreme Event
Management Agency Response Summary

  ----------------- ----------------------- ------------------- ------------
  **Agency**        **Action**              **Reasoning**       **Result**

  Governor's El     State agency            Strong public       No flooding
  Niño task force   organization. deepening interest. Hurricane 
                    of Gila River crossing  Nora damage         
                    at interstate 10                            

  Arizona Division  Joint briefings tour    Precedent for       No Flooding
  of Emergency      with NWS, Support to    flooding on major   
  Management (State Arizona County EM,      rivers during El    
  ADEM)             mainly on Lower         Niño.               
                    Colorado, Yuma.                             

  Large urban       Agency briefings.       See ADEM            No flooding
  emergency         Coordination. Enhanced                      
  management        focus on flooding for                       
                    yearly preparations.                        
                    Equipment purchase                          

  Other emergency   Awareness. Double-      See ADEM            No flooding
  management        checking and augmenting                     
                    supplies                                    

  Flood control     Including more agencies In house research   No flooding
  district A        in yearly planning.     showed El Niño      
                    Prepared for large      caused major rivers 
                    river flooding instead  to flood            
                    of flash flooding.                          
                    Maintain/repair ALERT                       
                    system                                      

  Flood control     Business as usual.      Preparedness is     No flooding
  district B        Participation in        equal for all       
                    emergency mgmt          events, not only El 
                    briefings               Niño years          
  ----------------- ----------------------- ------------------- ------------

## 5.6 Internal Factors Affecting Forecast Use

### 5.6.1 Introduction

While all participants reported that they were satisfied with the
quantity and quality of information that they received, several provided
insights on why certain products were more useful than others. Several
participants also reviewed specific forecast products, such as the CPC
seasonal outlooks and provided recommendations on how they could be
improved. This section will review some of the challenges that users
face in incorporating current forecasts into operations.

### 5.6.2 Enhanced Rainfall Does Not Always Imply Flooding. 

While select hydrologic forecasts provide an estimate of the maximum
flow rate during the snowmelt season, there is no official long-range
forecast for flooding. Participants recognized that scientists might
never be able to predict floods with advance warning beyond a couple of
weeks. Therefore, forecasts for flooding sometime during the season were
provided informally by the media or scientists based more on personal
instinct than forecast skill. It is flooding and not the occurrence of
above normal seasonal precipitation or streamflow that is of concern to
EMAs. While there is a correlation between seasonal streamflow and
winter flooding, there are a number of exceptions to this rule from past
years with low seasonal streamflow occurring primarily in a single brief
episode, to high, uneventful streamflow seasons. As a result, EMAs won't
refer to the seasonal outlooks on a consistent basis, but only in the
cases of extreme events (something that is not currently forecast by any
of the seasonal outlooks).

### 5.6.3 Excessive Technical Jargon and Multiple Sources of Information. 

EMAs sought information, not only for possible preparations, but also to
relay this information to others. It is important that EMAs have a
sufficient and appropriate understanding of the potential event,
especially when approaching legislators to request funding. Intimidating
technical jargon hinders the transfer of knowledge from the scientific
community to the public, not only in the climate forecasting, but also
in many areas of science. Occasionally, in the process of removing
jargon, the content of the original message is changed or lost, so there
is a need to balance the complexity of the content with its
understandability. Scientists, in fact, did provide useful information
to many agencies. However, those users that did not have access to clear
interpretation of the products relied instead on less sophisticated (and
sometimes less accurate) but more understandable sources such as the
media.

Users also expressed confusion about conflicting or differing accounts
coming from different sources (such as the potential severity of the
event). This is true not only for El Niño, but also when agencies
address long-term anthropogenic climate change. The perceived lack of
consensus by scientists on anthropogenic climate change causes agencies
to be skeptical of the information they receive, as well as the ulterior
motives of those conveying the information, leaving their final
impression based more on personal opinion and interests than scientific
facts. This may be especially problematic when distributing national
forecast products in the Southwestern US with its tradition of a
heightened level of distrust of the federal government. Also, one
participant believed that the responses to his questions when
telephoning the NWS are a function of which forecaster is on duty and
stated that he would prefer consistent contact with one individual.
While other public agencies have identified central contacts to interact
with other agencies, the NWS and scientists at the local universities do
not.

### 

### 5.6.4 Disconnect between Data Needs and Current Products. 

Climate forecasts, such as the CPC seasonal outlooks, forecast the
probability distribution shift for a region in a given time period. In
the words of one participant, "So many people were confused about what
they meant". The tendency by those unfamiliar with the forecasts is to
translate the shift in probability into the quantity expected. For
example, where large shifts are indicated on the maps, users may
anticipate greater quantities of rainfall than those locations with
smaller shifts. This would have implied that Arizona was expected to
receive absolutely or proportionately more rainfall than regions in
California (which normally receive much more rainfall than Arizona)
because of a "Bull's-eye" of contours around Arizona for the winter of
1997-98. This interpretation is incorrect since the forecast, in truth,
indicated a greater likelihood of Arizona's precipitation being in the
"above normal" category for the region, and that the forecasts in
California were not as "confident" as Arizona. This improper
interpretation was reinforced by the separation of the outlooks from
their legend. For example, surprisingly, both CPC special summaries 97-2
and 97-3 include the CPC outlooks without their legends.

The tendency to mistake the forecasts of probabilities for quantities
suggests a confusing style of the forecasts, a preference for quantities
to be incorporated into the decision-making process or a combination of
both. For those that understood the shifts in probability, it was still
unknown what quantity of rainfall indicated the transition from "normal"
conditions to "above normal". This information is available on the
Internet (figure 48), but based on the lack of contact participants had
with it and their call to have something like that, it can be considered
currently inaccessible. One participant also expressed that it is
important to place predictions of quantities in a perspective with the
historic record. For example, the prediction of twice normal
precipitation may sound alarmist, but the participant desired to know
how extraordinary it is to receive twice-normal precipitation in any
given year and if twice normal is legitimate cause for alarm. It is also
not clear in a region such as the Southwestern US, which has a large
skew to its precipitation record, whether "normal" indicates the median
or the mean. Probabilities are not foreign to agencies, however:
seasonal streamflow forecasts blend quantities and probabilities that
are used commonly and widely in surface water management.

Additionally, there is a spatial scale disconnect between forecast
products and users needs. For those products that did provide data about
rainfall during previous El Niño years, the gauges were typically
located within major cities (e.g. rainfall totals at Tucson Airport).
While this may appeal to the public, water providers would prefer data
within their own watershed in regions where the streamflow originates,
specifically the mountains. It is plausible that at higher altitudes,
the impacts of El Niño may be different and perhaps emphasized.

### 

### 5.6.5 Forecast Implications are not Clear. 

As part of the Governor's "El Niño task force", various climate
scenarios and their probabilities were crafted by the NWS and the
agencies used these to effectively direct available resources to
mitigation efforts. The presence of a scientist able to provide an
accurate assessment of the gravity of the situation (both in terms of
the likelihood of various things happening and the human impact they
would have) was very important. In addition, one participant joking
stated that "a check" would be the most important material to include in
a forecast packet tailored to water management agencies. He added that,
especially in the case of drought, an estimate of the *economic* impacts
of a climatic event are important as well as confidence in the forecast
and that this is what water providers need to determine if the cost of
mitigation would be worth the effort. Not only does this information
help the agency determine which course of action is most attractive, it
is required to approach the legislature for mitigation funds as well.
The desire for economic information and societal impacts was reiterated
by other users. A similar lack of forecast "decision-process" models has
been identified among agricultural users (Changnon, 1992). At the
opposite end of the spectrum, it is not clear to agencies how to apply
raw climatological data such as the spatial details of SST anomalies to
realtime operations. There is no shortage of climate data available per
se, but the extent to which the data can be translated into implications
for agency operations is seriously lacking and should be augmented.
Localized integrated interdisciplinary climate assessments (e.g. CLIMAS)
and outreach are the best options for direct integration of climate
information into decisions.

### 

### 5.6.6 Measure of Accuracy of the Forecasts Unavailable. 

Three factors affecting the perceived accuracy of a forecast are its
proven track record of forecasting similar past events, a consensus with
other forecasting tools using different methods and its endorsement by
authoritative sources. As many of the agencies surveyed were unfamiliar
with the CPC seasonal outlooks previous to the 1997-98 El Niño event,
the accuracy of the forecast was based mostly on a) the consistency of
what authoritative scientists were expressing was going to happen, b)
the forecast's consistency with the findings of in-house research and c)
the memory of previous detrimental flooding events during El Niño years.
The magnitude of the El Niño event allowed agencies to overlook the
details of the climate forecasts and accept at least the qualitative
outlook that it would be a wetter than normal winter with a chance of
flooding. This will not be the case, however, in non-large El Niño
years.

For those wishing to routinely incorporate seasonal forecasts into their
operations, the accuracy of the forecast must be proven first, as
expressed by the USBR among others. When asked about their perceived
accuracy of the forecasts, responses from participants were generally
high (from 60% to 90% with many expressing that their assessment would
be only a guess because they had no concept of the accuracy). Evidence
suggests that this is higher than the actual capability of the
forecasts. One user stated that he recalled a mention in previous years
that the accuracy of the forecasts was 55% (where random guessing would
yield 50% accuracy, perfect accuracy being 100%). He added that at least
55% was a step in the right direction. An inflated perception of the
accuracy of the forecasts may be due to the accurate forecasts during
the recent El Niño overshadowing past performance. Likewise, when asked
if users believed the forecast methodologies are frequently upgraded,
integrating the latest technology and research findings, or relying on
tested and reliable methods, the response was almost universally yes.
This is indeed true for climate forecasts but not hydrologic forecasts
where consistency is favored over innovation (Hartmann, 1999).

It is extremely important that forecasts must be evaluated with an
objective function that accurately reflects agencies' vulnerabilities.
For example, when agencies are most vulnerable to the forecast being
wildly incorrect (e.g., when five to ten years of marginal gains are
offset by one year of major loss because of a forecast), comparing the
mean of a forecast to the mean of the observed may be inappropriate.
Regrettably, this study cannot suggest a specific objective function
that would apply to all water management agencies (if one does exist),
but this is an exciting opportunity for future research.

###  

### 5.6.7 "Normal" is a Misleading Concept. 

The CPC climate forecasts define "normal" as being the middle tercile of
the historical record from 1961-90. However, participants often defined
"normal" in a subjective manner. For example, "normal" can imply a year
free of extreme events (as in "business as usual"). With this
definition, forecast users could have perceived the El Niño event as a
"no-show" in Arizona and that the forecasts were incorrect. However,
strictly speaking, many regions in Arizona received "above normal"
rainfall, as defined by the CPC outlooks (yet this does not make the
forecasts "correct" or "incorrect" because they are probabilistic by
nature and will always be "semi-correct"). Alternate methods of wording
the forecast may be more informative. A hypothetical example would be:
"There is a 60% probability that more than 4 inches of precipitation
will fall in December, January and February. Of the previous thirty
years, this occurred five times, in 1973, 1983, 1992, 1995, and 1998. Of
these years, forecasters believe that the current conditions are the
most similar to 1973." This would provide not only a quantitative
measure for evaluating the forecast, but a historical context to place
the forecast in, as well.

Accompanying climate forecasts with historical analog years has been
suggested by several researchers (Changnon, 1992; Pulwarty and Redmond,
1997). However, Nicholls warns that use of analog years should be
avoided because it can anchor a user's expectations on an event which
may or may not be repeated (Nicholls, 1999). For example, comparing the
1997-98 El Nino with the 1982-83 El Nino may cause users to ignore
subsequent information about the uncertainty associated with a forecast
or forecast qualifications (e.g. "This event is as large as the 1982-83
event, but the 1982-83 event's impacts were atypical of all other El
Nino years"). According to the findings of this study, providing
historical analogs along with a climate forecast *should not* be
avoided. Instead, special care should be placed in choosing
*appropriate* analog years.

## 5.7 External Factors Affecting Forecast Use 

### 5.7.1 Introduction 

While extensive effort is directed towards improving the technical
aspects of climate forecasts, there are factors external to the products
themselves which inhibit their use. Before a sector, such as water
management, is identified as potentially benefiting from the forecasts,
these factors must be taken into consideration by forecast producers.
This section reviews some of the themes contained within participant
responses when discussing barriers to forecast use, external to the
forecast products themselves.

### 

### 5.7.2 Systems are invariant to interannual variability

As stated earlier, many of the agencies involved in water management
were involved with accounting and infrastructure maintenance and did not
perceive their mandate as being flexible during years of surplus water
versus normal years, or did not perceive any kind of decision-making
process where forecasts could be useful. The FCDs are also an example of
this, in that structural flood control involves assessing the magnitude
of the 100-year flood and designing structures to withstand that. These
structures are static and provide protection every year, regardless of
it being an El Niño year or not. However, other, longer-range
information about the non-stationarity of climate has potential benefit
to those involved with design. While the designers consider periods of
the past while preparing for the future, climate information (including
information about decadal shifts in climate) could be useful in
determining what specific parts of the past are most appropriate to use.

Some of the systems that are not invariant are only able to respond on
time scales that are too slow to utilize advance warning of several
months. For example, participants reported that the process of adding
personnel to staff often takes at least one year. Likewise, one
participant expressed that most of the structures in his jurisdiction
that could have benefited from repairs before the El Niño event are
located in an environmentally sensitive region. Recent environmental
regulations require that the agency obtain a complex set of permits to
do the repairs. He pointed out that in the several years it would have
taken to negotiate and acquire the permits, the El Niño event would have
come and gone. He deferred action, realizing that if El Niño related
flooding had caused structural damage, the city would have been allowed
to conduct emergency repairs without environmental restrictions.

EMAs expressed that flexibility and adaptability is part of their
mandate in that they are permitted to reduce the risk of a potential
disaster as they see fit. However, they also expressed that if flooding
can occur in any year, it does not make any sense to be more prepared in
an El Niño year than it does to be less prepared in a non-El Niño year.
Analogously, it is not practical to seek out flood insurance only
directly before an event is pending. If additional resources could be
available there is no reason to delay their use for an El Niño year, as
there are a litany of other emergencies that need to be addressed (e.g.
domestic terrorism, nuclear meltdown, fire, etc). Efforts were not made
to expedite the completion of the new statewide communication system
before the El Niño event because the project was already progressing as
rapidly as possible. However, forecasts for extreme events can provide
managers with the opportunity to increase community awareness of a
hazard, encouraging preparation that has been deferred in the past.

Although several participants in the study perceived their operations as
insensitive to seasonal forecasts, this does not imply that this is
necessarily the case. While some FCDs and EMAs currently consider
themselves optimally prepared for flooding every year without using
forecasts, this study cannot objectively state whether this is true or
not. It is especially difficult to determine because no flooding
occurred to test the preparedness of these agencies.

### 5.7.3 Unavailable agency resources 

Some local water providers have a minimal budget to employ personnel and
conduct repairs to existing infrastructure only. The availability of
these agencies to conduct independent research on climatic events such
as El Niño is dwarfed by demands imposed by their other
responsibilities. In a similar fashion, the individuals engaged in
emergency management occasionally share several other responsibilities,
such as law enforcement or fire control. Due to the multitude of
potential threats, it is not possible for these individuals to do
independent investigation into all emergencies and assess the threat
that they pose. To help this, ADEM is engaged in providing support and
assistance to all communities, not only during emergencies, but in doing
mitigation work as well, as was evidenced by their activities for El
Niño. ADEM's assistance provides equity in safety for those communities
that do not have the resources to do investigation and mitigation on
their own. Similar assistance should be provided from the scientific
community, directly or via ADEM.

As shown in the previous example, agencies can defer proper mitigation
activities because it is more efficient to respond to it after an
emergency occurs. EMAs stated that they have a static budget that only
grows after an emergency occurs. This management structure discourages
proactive measures, but a change in philosophy at the national level may
change this, in that FEMA is contemplating changes that would encourage
proactivity. However, it is most likely that the majority of this
mitigation activity will be structural (and non-structural through
floodplain regulation and community relocation) and seasonal climate
forecasts will not play a major role. In total, the activities of
agencies occurred under static budget, with no additional hiring of
personnel, effectively stretching what are most often already overtaxed
resources.

### 5.7.4 Climate variability is one of many factors 

While the most common emergency that activates Arizona EMAs, flooding
remains one of a long list of potential emergencies that they must
consider when planning. Additionally, El Niño is one of several
influencing factors on climate and floods. Therefore, information about
El Niño (especially during years where the El Niño event is not extreme)
may not be a first order influence on management decisions. For example,
although winter precipitation forecasts during La Niña are among the
most confident in the Southwest (dry), EMAs were too engrossed in
preparations for the "Year 2000 Millenium Bug" to act on the La Niña
forecasts the following year.

Additionally the options available to agencies may be restricted because
of these types of factors. While the action recommended by a forecast
may be enhanced flood releases, environmental concerns, for example, can
complicate matters. In late 1996, the Upper Bureau and scientists
conducted a controlled flood experiment to research the river's dynamics
and to attempt to rebuild beaches worn down by erosion. In late 1996,
the Upper Bureau needed to balance maintaining safe conditions in the
reservoir and not damaging the recently rebuilt beaches. At the time, it
was also uncertain what level of releases would cause damage. The Bureau
decided on steady elevated releases. Since then, the scientific
understanding of natural floods has shifted to suggest that high,
punctuated releases may have been more beneficial to the beaches.

Likewise, while forecasts in general may help the Bureau operate its
reservoirs more efficiently, to maximize capture and minimize water
loss, this increased efficiency comes at the expense of the natural
system of the Colorado River Delta wetlands. When one starts to consider
all of the interactions and ramifications that various agencies'
activities have, it becomes impossible to determine what actions would
be of the greatest good to all, even without considering a climate
forecast. This near-bottomless complexity contributes to the state of
gridlock that afflicts many agencies along the Colorado. To alleviate
the situation and to prevent perpetual conflict between interests, many
water management agencies have fixed, agreed upon standard operating
procedures- perhaps relinquishing their flexibility to act upon seasonal
climate forecasts.

### 

### 5.7.5 Existing water law limits flexibility 

Existing regulations on the distribution of water in many watersheds
come from long standing legal agreements. These arrangements were
primarily established to manage water in times of shortage, not excess.
If the current system were altered so as to increase consumptive water
usage during wet years, this would detract from the amount of water
which would have otherwise been stored in reservoirs, defeating the
purpose of having the reservoirs to begin with, aside from providing
safety from floods. With the exception of drawing down reservoirs to
prevent spillage during a season, actions taken on the forecasts could
potentially benefit some users at the expense of others. As the
restructuring of existing water laws to accommodate seasonal climate
forecasts is not likely, the most effective method of incorporating the
forecasts is to integrate them into the hydrologic forecasts which are
already widely utilized in water management. Increasing the accuracy of
the hydrologic forecasts would have direct economic benefit to several
sectors, including water delivery, power and water users. If the
forecast is for dry conditions when water supplies are low, the climate
forecast will be met with institutional inflexibility under legal
obligations and mandates. In this case, it may be more effective to use
the forecast to encourage a change in behavior of water
[users]{.underline} rather than of water [managers]{.underline}.

### 5.7.6 Agencies are unfamiliar with products/lack access

Due to the highly visible nature of the 1997-98 El Niño forecasts,
unfamiliarity with seasonal forecasting concepts and products will
undoubtedly be less of an issue in the future. However, because many
users did not have experience with the forecasts prior to this event,
there was confusion about how to interpret and apply them. For example,
in the packet of forecast products provided, participants universally
singled out the SST forecast (figure 45) as being the least informative
and most difficult to integrate into operations. This is most likely
because the details of SST patterns are so far removed from the types of
information that agencies normally consider. In this light, it is not
surprising that many users were only able to gather qualitative
information about the forecasts and the details were not utilized. This
was helped when scientists and NWS forecasters assisted agencies in
interpretation. Without a formal network for climate forecast
dissemination this will not occur during future years or for new users.

Additionally there is evidence in this study that, especially without
assistance, users were not able to gain access to products that may have
been helpful to them. For example, although the entire product was
specifically focused on the impact of El Niño on water resources in the
Southwestern US, only one participant reported having knowledge of the
existence of CPC special summary 97-2. In contrast, the majority of
agencies recognized the widely distributed CPC special summary 97-3,
although it only devotes two sentences to the Southwestern US. The
non-use of CPC special summary 97-2 is disturbing, but it is also
testament to the power of effective advertisement.

### 

### 5.7.7 Not every agency is sensitive to every forecast 

It is unrealistic to expect that every forecast or climate information
product will have some utility to every agency. The majority will not.
Likewise, depending on the agency's situation, only a limited number of
forecasts would imply that action is needed. For example, consider the
simple combinations of forecast conditions (dry, normal and wet) and
reservoir conditions (near empty, normal or near capacity). Of these
nine combinations, only two imply action (a forecast for wet conditions
with full reservoirs and a forecast for dry with nearly empty
reservoirs). EMAs may only be interested in forecasts predicting an
extreme flooding event. This may appear unfortunate to those wishing to
find wide use for climate forecast products to as many sectors as
possible. However, instead, this allows a regional group of scientists
with limited resources to ascertain, in advance, the vulnerabilities
that various agencies and sectors have and then effectively focus their
special handling efforts in any given year on the agencies that could
utilize the forecast.

### 5.7.8 Use of forecasts may increase user exposure to risk

The intent of many agencies in considering and acting on the 1997-98 El
Niño forecasts was primarily to avert disaster. This is especially true
of the Colorado River Bureau of Reclamation, who specifically wanted to
avoid a repeat of the 1982-83 floods. If the forecasts were inaccurate,
the repercussions because of the "false alarm" would have been much less
than if the agency ignored the forecast and flooding occurred.
Undoubtedly, not every year will be like this.

One defining characteristic of water supply agencies, as opposed to
other agencies, is their conservative nature. Water supply agencies seek
to provide continuous service without disruption by avoiding as much
risk of shortage or excess as possible. "Optimizing" a water management
system is not as attractive of a prospect as ensuring stability and
security (partially because there is little incentive to increase
efficiency since water is valued so low and agencies lack competition.
This is in contrast to hydropower generation.) Agencies will be
reluctant to use a forecast to "hedge one's bet" against climate
variability if it means increasing their exposure to risk. For example,
if a forecast indicates dry conditions and reservoir operators decide to
keep water levels higher than normal, and the season is, in fact, wet,
then worse flooding will occur than if the operators had used no
forecast at all.

By way of example, this situation is the equivalent to a farmer having
to chose between planting seeds that are insensitive to climate, or
seeds that could benefit if the forecast is right, or be severely
damaged if the forecast is wrong. In this sense, water providers bear a
stronger resemblance to subsistence farmers whose livelihoods depend on
their crops, than an agribusiness farmer who can tolerate more risk.
Clearly, the analogy is not universal and some water providers are more
progressive than others. However, after recognizing the appropriate
parallels, many insights about forecast use and risk management in water
management can be learned from the well-established body of literature
about forecast use in agriculture.

To remedy this situation, climate forecast providers need to shift their
focus away from emphasizing that using forecasts will benefit the user
in the long-term, on the average. Instead, simulations and
demonstrations need to show that using climate forecasts will ensure
users' *security and stability* over not using any forecasts at all,
even when the forecasts are wrong. Else the forecasts may never find
routine use among water management agencies. Measuring and conveying the
accuracy of the forecasts plays a critical role here.

# CHAPTER 6

# RECOMMENDATIONS

Based on the findings of this study, several recommendations to CLIMAS
and the climate forecasting community as a whole are provided to
increase the utility of forecasts of and information about interannual
variability. Ultimately, the process of incorporating climate
information into water management practices will be an interactive,
iterative process involving agencies and scientists. Many of these
recommendations have been endorsed before by Callahan et al. (1999),
Pulwarty and Redmond (1997), and Glantz (1998). Their reiteration here
serves to more firmly establish their need beyond the unique
circumstances of prior studies. However, several of these
recommendations have not been put forth in past studies (e.g.,
incorporating climate information into hydrologic forecasts, focusing
efforts on low-resource agencies and continuing study during the present
La Niña event). The recommendations are as follows:

**Improve the Format, Credibility and Availability of Current
Products.** Without additional information and interpretation, agencies
are unable to use the details of current products, such as the CPC
outlooks. Users either sought additional information or were limited to
using the outlooks as solely qualitative forecasts. Agencies prefer
quantitative (or at least specific) precipitation climate forecasts: it
does not aid them to know that the probability of above-normal
conditions is (marginally) increased when there is no concept of what
\"above-normal\" signifies, much less \"normal\" or the threat which
"above-normal" presents. Likewise, "normal" is a subjective term and a
forecast for "above-normal" conditions can come true by the forecaster's
standards, but the intended user may still believe the forecast was
poor. Users also desire a measure of the forecaster's confidence in the
product and a record of how the forecast has performed in the past
(preferably under similar conditions to the period being forecasted).
While the Internet has radically changed the availability of products,
participants reported that it is not effective time management to
conduct unassisted searching for information when, instead, it could be
obtained from an easily accessible, central "One Stop Shop" for climate
information.

**Thoroughly Evaluate the Accuracy of Seasonal Climate and Hydrologic
Forecasts.** If scientists develop a methodology whose evaluation
criterion accurately reflect how errors in forecasts impact various
agencies, retrospective analysis of the hydrologic and climate forecasts
should be performed. If the analysis reveals low forecast skill,
agencies may have reduced confidence in the forecasts, but at least
their expectations will be realistic. This type of analysis has not been
thoroughly performed in the past, and it represents a critical gap
between forecasts and users, a sentiment echoed in many studies
including Pulwarty and Redmond (1997) and Callahan et al. (1999).
According to Pulwarty and Redmond, the [most]{.underline} frequently
requested supplemental material to accompany forecasts is information
about trends in accuracy of the forecasts. This study has attempted to
lay a framework, but clearly, this work is far from finished and this is
an opportunity for exciting future research.

**Improve and Formalize Communication Links with Agencies and Integrate
Scientists in Risk Assessment.** Repeatedly study participants provided
examples of how preferred methods of communication involved established
contacts and conversely how they had lesser confidence in unfamiliar
sources. In light of this, it is not feasible for products generated at
a national level to satisfy the needs of every region and every sector
under every circumstance. Agencies will find some specific forecasts,
under certain conditions, more applicable than others. It would be more
efficient for a regional group of scientists with an awareness of sector
vulnerabilities and management practices to focus in-person special
handling efforts on those agencies to which the forecasts apply. The
effectiveness of such an institution in providing information relies on
the extent of its outreach, establishment and involvement in the
community. It also depends on how much the institution allows its
activities to be interactive and iterative, allowing users a sense of
participation in or "ownership" of the forecasts. To this end, periodic
or a-periodic agency briefings and focus groups may prove the most
valuable and effective method of forecast dissemination. Finally, these
institutions should utilize the existing, trusted channels of
communication as much as possible (such as the National Weather Service
and the Agricultural Extension agencies).

**Increase the Availability of Information to Low-Resource Agencies.**
Agencies that have limited resources and restricted access to
information are no less vulnerable to climate variability than others.
If the resources are available, many agencies are able to understand and
utilize some of the forecast products with the aid of the NWS and/or
in-house meteorologists. Agencies that *do not* have the time and/or
ability to seek out and decipher information about climate on their own
would benefit the most from external assistance. Information providers,
such as CLIMAS, will need to decide for themselves whether they will
focus their efforts on these at-risk, marginal communities or on
high-resource agencies. Focusing on low-resource agencies may make,
proportionally, a world of difference to the agencies themselves, but
focusing on high resource agencies may yield, absolutely, greater
benefit (e.g. in terms of money or lives saved). CLIMAS may also face
initial resistance and distrust from these historically neglected
low-resource agencies. There is a special need to be sensitive to the
circumstances and decision-making processes of these agencies.

**Assist Public Media in Providing Information.** Media coverage of the
1997-98 event had its benefits and detriments. While it brought
attention to the event, many agencies found themselves trying to make
rational and informed decisions in an atmosphere of panic. Because the
media provides information to a very broad base, it would aid agencies
if the media presented accurate and unexaggerated information about
events. However, one participant believed that the current
sensationalism is intentional and unlikely to abate. Increased outreach
may or may not lessen media sensationalism but it has definite potential
to identify clear, credible contact points in the scientific community
and lessen the dissemination of inaccurate or inappropriate information.

**Enhance Short-term Weather Forecasting Ability.** When asked where
they would like to see future efforts focused, almost all EMAs
*explicitly* stated that they could utilize improved short-term weather
forecasting, nowcasting and monitoring. If more resources were
available, the FCDs stated that they would augment the number of stream
and raingauges. The benefits from these advances are more tangible and
immediate than what could be derived from better seasonal products.
Several EMAs expressed that preparation for an event with 24 hours
advance notice is radically different from 48 or 72 hours. A recently
initiated NWS weekly threats assessment for the U.S., if successful, may
increase the advance warning for agencies to five to ten days.
Additionally, advances in radar and satellite monitoring, as well as
evolving hydrologic modeling capability all have obvious benefit to
short-term forecasting. It is important to realize, however, that other
important factors inhibit short-term weather forecasting ability, namely
a lack of personnel in forecast offices and, for Arizona, lack of
reliable upper-air data in Mexico (A. Haffer, NWS, personal
communication 1999). Finally, participants expressed a need for accurate
forecasts of short-term human related variables, such as a heat stress
and discomfort indexes, to assist large urban emergency management in
curbing heat related emergencies. This same information can also be
useful for adjusting hydropower operations to anticipate peak demands.

**Integrate Climate Forecasts into Seasonal Streamflow Forecasts.** Many
water supply agencies incorporate WSOs directly into operations. In its
most extreme form, the USBR is *required by law* to operate reservoirs
using WSOs issued by the Colorado River Basin Forecast Center. Current
WSOs often do not utilize climate information or ENSO indices. If
research shows that the accuracy of the forecasts is significantly
increased using El Niño indices then it may be useful to incorporate
them into WSO forecast regression equations. Again, this is another
exciting arena of potential research. If the climate forecasts are
transparently meshed into the existing forecasts, their influence will
be more broadly reaching. However, the transfer of research products to
the operational hydrologic forecasting community presents its own
challenges (Hartmann, 1999).

If climate forecasters desire to mesh their products with the WSOs, two
important tasks must be completed first. First, CPC climate outlooks (or
some new product) must be provided in a numerical format, instead of a
map. This numerical forecast can be used as a variable in the standard
hydrologic forecasting regression equations, whereas maps cannot (this
problem also currently hinders the use of many remotely sensed snow map
products). Second, since the CPC long lead outlooks have only been
produced since 1995, hindcasts must be made extending back twenty years
or more. Hydrologic forecasters can then evaluate the performance of the
new equations to determine if the accuracy is sufficient for the climate
forecast to be included as a variable in operational hydrologic
forecasts. While an attempt has been made to circumvent this by a using
time series of SOI as a hydrologic forecast variable, SOI is only one of
the many factors that the CPC outlooks consider. Therefore using the CPC
outlooks should (theoretically) provide more accuracy than using SOI
alone. However, since the CPC outlooks are created using a subjective
combination of tools, objective hindcasting would be a daunting task and
would only evaluate the current tools (which undoubtedly, will be
outdated in the near future).

**Increase the Ability of Agencies to Adjust to Climate Variability.**
Increasing the usefulness of climate information to agencies does not
just include improving the products and their interpretation. Adaptation
of decision-making processes to accommodate climate variability may be
valuable, but also difficult. Currently, several agencies operate by
standard operating procedures that do not allow them to adjust to
advance warning of potentially extreme climate conditions. While no
agencies made proactively inappropriate responses to El Niño, some
missed opportunities for more effective response, primarily through
inaction.

**Assist Agencies in Developing Drought Mitigation Strategies.** Drought
mitigation strategies generally receive much less attention than
flooding (if any at all). Some participants speculated that a multi-year
(two to seven) year forecast would be useful to assist during droughts,
but those same agencies expressed that they would be immediately
skeptical of the skill of such a long-range forecast. If a drought was
to occur or was forecast, users would seek information about:

1.  The current intensity of the drought

2.  Historical analogs

3.  Predicted intensity and duration of the drought

4.  A measure of forecast accuracy and confidence

5.  Predicted damages and economic hardships that will occur

6.  How costly various mitigation strategies would be

Although this study did not explicitly investigate it, it is anticipated
that a new set of even more challenging barriers hinder agencies from
using forecasts during droughts (see final recommendation). Note that
the subsequent La Niña and its possible multi-year persistence offer the
opportunity to investigate water management decision-making processes
under drought conditions; however, such a study is currently not
underway.

**Track Future Agency Use of Climate Information.** This study provides
a snapshot of the use of current climate products and seasonal forecasts
during a specific event for a specific sector. While heeding the
recommendations posed here would enhance the utility of the products,
undoubtedly additional concerns will arise as agencies continue to
integrate forecasts into operations. There is a need for ongoing
interactive and iterative research with agencies to facilitate their
evolving use of products.

**Investigate Use of Forecasts during 1999-2000 La Niña.** While La Niña
and El Niño may have symmetrically opposite impacts in Arizona, agency
reactions to these different types of events are far from symmetrical. A
whole new host of challenges face agencies when dealing with a water
shortage, instead of excess. Likewise, the public's involvement in
drought is significantly different from its reaction to flood.
Additionally drought can be orders of magnitude more costly to a
community than flooding. After enduring a historically dry winter at the
end of a dry decade, the current forecasts indicate the continuation of
La Niña (dry) conditions into at least the winter of 1999-2000. Here the
opportunity exists to investigate how agencies deal with drought
*before, during and after* the event. The producers of this study
implore CLIMAS to seize this rare, nearly over-ripe opportunity by
commencing such a study as soon as possible.

# CHAPTER 7

# CONTRIBUTIONS

The findings of this study both contribute to and reinforce the existing
understanding of seasonal forecast use in water management. Many of the
findings of this study are consistent with previous studies by Pulwarty
and Redmond (1997), Pulwarty and Melis (1999) Callahan et al. (1999),
Changnon, (1992), Changnon and Kunkel (1999), Sonka et al. (1992) and
others. For example, the National Research Council recognized, as early
as 1980, the gulf that exists between users and forecasters, at least on
the Columbia River. It called for increased communication and
interaction between forecasters and users and this is a recommendation
that still holds true, nearly twenty years later (Callahan et al.,
1999). Our study also recognizes that a similar gulf exists in Arizona
between forecasters and water management agencies. This study reinforces
the need for forecasters or some intermediate entity (e.g. CLIMAS) to
work with users to illustrate how to apply forecasts and how they have
value above considering no climate information at all.

In addition, past studies have consistently recognized that past
forecast evaluation must be performed before agencies can have
sufficient confidence in making decisions based on the forecasts. Along
with increased interaction between forecasters and users, forecast
evaluation of existing products has been repeatedly recommended as a top
priority for the forecasting community. Yet, why is this information
still not provided? This evaluation, possibly one of the most important
aspects of the forecast, is not available in the CPC outlooks after 1995
(but is available in the previous format). Nor is evaluation provided
for the hydrologic forecasts. This study points out that, clearly, the
benefit to both agencies and forecasters would be enormous.

In contrast, several aspects of this study are unique. First, the
in-depth nature of this study reveals details of water management
decision-making processes that have otherwise been lost in previous
studies. While involving a wider array of users, prior studies were only
able to engage users in a superficial manner. Therefore, it is not
surprising that the core findings of this study are consistent with
those of past studies. However, to scientists seeking to provide water
management agencies in Arizona with climate information, the details
gleaned from this in-depth study are absolutely necessary. For example,
none of the past studies addresses the issue of equity in forecast
distribution, special handling and use. Rarely, if ever, have
low-resource agencies been involved in studies investigating the use of
forecasts in the United States. Evidence from this study suggests that
this will play a very important role in the future and merits further
investigation.

Second, this study lays a framework for evaluation of seasonal
forecasts. Further research is needed to establish the proper
methodology of evaluating the forecasts, but the creation of archives of
seasonal climate and hydrologic forecasts is a recent critical
development. The door is now open to an arena of exciting and novel
research that is long overdue.

Third, this study developed an understanding of water management
decision-making processes in a structured manner, directly involving
users. Previous studies have primarily focused on agricultural users and
utilities although there is a growing recognition of the importance of
water management. Prior to this study, no documented understanding of
decision making by water management agencies in Arizona existed. While
this understanding is far from fully developed, this study represents
the critical first step towards satisfying the climate information needs
of Arizona's users.

Finally, this study focuses on a specific climatic event in a timely
manner. Previous studies address the use of forecasts in an abstract
sense during ordinary conditions. The 1997-98 ENSO event required
agencies to utilize forecasts and consider action. Investigating the use
of forecasts during an event better reveals the difficulties that
agencies face, *in practice*. A study similar to this was conducted in
California (where the signal of ENSO is not as clear), but no other
study was conducted in Arizona, specifically. The timeliness of this
study allowed valuable information to be gained that would have
otherwise been unavailable. The caliber of this study and its findings
are testament to the kind of valuable work that can be done when
institutions are granted the flexibility to seize unique research
opportunities as they arise on short notice. These institutions should
be applauded for their proactivity and ingenuity.

# CHAPTER 8

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