![](media/image1.wmf){width="1.2in" height="0.99375in"}

**Evaluation Report for AWARDS ET Toolbox and RiverWare Decision Support
Tools**

*The AWARDS ET Toolbox is developed by the U.S. Bureau of Reclamation.
RiverWare is developed through a cooperative effort between Reclamation
and the University of Colorado\'s Center for Advanced Decision Support
for Water and Environmental Systems.*

Hydrological Sciences Branch

NASA Goddard Space Flight Center (Code 614.3)

Greenbelt, MD 20771

Acknowledgments

This work was supported by the NASA Earth Science Applications
Directorate, NASA Solid Earth and Natural Hazards program under grant
number NAG5-13260-2 and also supported by a NOAA GAPP grant. The work
has been conducted at NASA Goddard Space Flight Center, University of
Idaho, Desert Research Institute, and the U.S. Bureau of Reclamation.

+----------------------------------+-----------------------------------+
| AWARDS ET Toolbox and RiverWare  |                                   |
| Teams                            |                                   |
+----------------------------------+-----------------------------------+
| Kristi Arsenault*--Team Leader*  |                                   |
+----------------------------------+-----------------------------------+
| [NASA GSFC]{.underline}          | [U.S. Bureau of                   |
|                                  | Reclamation]{.underline}          |
| Kristi Arsenault                 |                                   |
|                                  | Steven Hunter                     |
| Ana Pinheiro                     |                                   |
|                                  | Richard Stodt                     |
| David Toll                       |                                   |
|                                  | Tom Pruitt                        |
| Ted Engman                       |                                   |
|                                  | Al Brower                         |
| Jonathan Triggs                  |                                   |
|                                  | Donald Frevert                    |
| Joseph Nigro                     |                                   |
|                                  | Edmond Holroyd                    |
| [Desert Research Institute,      |                                   |
| Reno, NV]{.underline}            | Steve Bowser                      |
|                                  |                                   |
| Douglas Boyle                    | Steve Hansen                      |
|                                  |                                   |
| Justin Huntington                | Warren Sharp                      |
|                                  |                                   |
| [University of Idaho,            |                                   |
| ID]{.underline}                  |                                   |
|                                  |                                   |
| Richard Allen                    |                                   |
+----------------------------------+-----------------------------------+

# Table of Contents

[**Table of Contents 3**](#table-of-contents)

[Tables 4](#tables)

[Figures 4](#figures)

[Executive Summary 5](#executive-summary)

[1. Introduction 6](#introduction)

[1.1. The Water Management Need 6](#the-water-management-need)

[1.2. Partnering with Reclamation 6](#__RefHeading___Toc129688127)

[1.3. Decision Support Tools: AWARDS ET Toolbox and RiverWare
7](#__RefHeading___Toc129688128)

[1.4. Pilot Study Regions 7](#__RefHeading___Toc129688129)

[1.5. Systems Engineering Approach 10](#__RefHeading___Toc129688130)

[2. Overview of the DSTs 11](#overview-of-the-dsts)

[2.1. Components of the AWARDS ET Toolbox
11](#components-of-the-awards-et-toolbox)

[2.2. Components of RiverWare 14](#components-of-riverware)

[3. Consideration of NASA Inputs 16](#consideration-of-nasa-inputs)

[3.1. Potential NASA ESE Products for Reclamation DSTs
16](#potential-nasa-ese-products-for-reclamation-dsts)

[3.1.1. NASA's Satellite-Derived Products
16](#nasas-satellite-derived-products)

[3.1.2. NASA's Model-Derived Products 18](#nasas-model-derived-products)

[3.2. Potential NASA Inputs to AWARDS ET Toolbox
18](#__RefHeading___Toc129688138)

[3.3. Potential NASA Inputs to RiverWare
21](#__RefHeading___Toc129688139)

[3.4. Meeting Technical Requirements with NASA Products
23](#__RefHeading___Toc129688140)

[3.5. Gaps in Meeting DST Needs 23](#__RefHeading___Toc129688141)

[4. Next Steps 24](#next-steps)

[4.1. Conceptual Plans for Verification and Validation of NASA Inputs
24](#__RefHeading___Toc129688143)

[5.0 References 25](#references)

[**6.0 Abbreviations and Acronyms 27**](#references)

#  

# Tables

[**Table 1**. Current inputs to AWARDS ET Toolbox
**12**](#__RefHeading___Toc129423358)

[**Table 2**. Current inputs to RiverWare
**15**](#__RefHeading___Toc129423359)

[**Table 3**. Satellite Product Input into AWARDS ET Toolbox and
RiverWare (see Section 3.1.1 for description)
**17**](#__RefHeading___Toc129423360)

[**Table 4**. Potential NASA Model Product Input into AWARDS ET Toolbox
and RiverWare (see Section 3.1.2 for description).
**18**](#__RefHeading___Toc129423361)

# Figures

[***Figure 1***. A map of the three main river basin regions where the
Reclamation DSTs will be evaluated and benchmarked with NASA data
products. **8**](#__RefHeading___Toc129421802)

[***Figure 2***. Illustration of the architecture underlying the
activities of the Earth Science Applications Program and its specific
application to the Reclamation DSTs.
**11**](#__RefHeading___Toc129421803)

[***Figure 3**.* The AWARDS ET Toolbox includes this typical interactive
web map of effective rainfall (left) and a plot of total
evapotranspiration and stream flow (in cfs; right).
**13**](#__RefHeading___Toc129421804)

[***Figure 4***. Example MODIS and LIS products that are being tested
with the AWARDS ET Toolbox DST. The land cover classification map (upper
left) is the MODIS product 12, version 4, and is blended with Landsat
and the Reclamation LUTA land cover. Total rainfall and
evapotranspiration (in mm) is from LIS and the Noah LSM for August,
2003, for the Albuquerque region (upper and middle right, respectively).
**19**](#__RefHeading___Toc129421805)

[***Figure 5.*** METRIC-derived ET maps from MODIS (left image is for
the 57^o^ view angle; the center is for the 2^o^ view angle) and from
Landsat (right image). **21**](#__RefHeading___Toc129421806)

[***Figure 6***. Cloud-free MODIS MOD02 visible images were processed
for Water Year 2000 --2005 for the Truckee-Carson Region with view
angles \< 30 degrees to calculate the Normalized Difference Snow Index
(NDSI). Fractional snow cover maps are generated from this MODIS product
and can be used in PRMS and RiverWare (based on *Salomonson and Appel,
2004*). **22**](#__RefHeading___Toc129421807)

# Executive Summary

In the western United States, water supply is relatively limited, thus
it is critical to understand both supply and total demand. Much of the
water in the West comes from melting mountain snow in the spring and
summer, which runs into reservoirs for later use by cities, agriculture,
and the natural environment.

The U.S. Department of the Interior's Bureau of Reclamation
(Reclamation) is responsible for many of the critical water management
decisions in the West and relies heavily on Decision Support Tools
(DSTs) to make more informed decisions. One DST is the AWARDS ET Toolbox
which was developed by Reclamation primarily to estimate water use by
crops and riparian areas. The AWARDS ET Toolbox is a data acquisition
system for developing site-based spatially distributed products for
irrigation, reservoir-river systems management, and inputting water use
estimates into RiverWare. RiverWare is a modeling system developed by
CADSWES (Center for Advanced Decision Support for Water and
Environmental Systems) and supported by Reclamation and the Tennessee
Valley Authority. It is used to model water availability in several
regions of the U.S., primarily to inform water policy decision makers
and water managers on water availability and best management practices.

By partnering with Reclamation, NASA can provide remotely sensed and
modeled data that may improve the results from RiverWare and AWARDS ET
Toolbox. Examples of satellite-derived data that NASA can provide
include land cover and snow cover data from the Terra/Aqua MODIS,
topography from SRTM, and other land variables from Landsat, ASTER,
Aqua's AMSR. In addition, modeled outputs from the Land Information
System (LIS) project are also potentially useful to Reclamation.
Additionally, other algorithms and models used and developed by
Reclamation and partners, such as the Mapping EvapoTranspiration at High
Resolution with Internalized Calibration (METRIC) or the
Precipitation-Runoff Modeling System (PRMS), can incorporate NASA
satellite and modeled products and then provide the outputted data as
inputs to the above DSTs. The ultimate goal for NASA's Applied Sciences
Directorate is to determine which NASA products can improve DST results,
thereby allowing better information for improved decision making by
partnering agencies, like Reclamation. The primary purpose of this
report is to provide an "Evaluation" of the NASA satellite and modeling
products for possibly improving the performance of Reclamation DSTs.

# 1. Introduction

# 1.1. The Water Management Need

As a major driver of our Earth-climate system, there is much to be
understood about water. Water drives local and global scales of energy
and moisture, and it is the most critical element to human survival. As
the global population rises, the need for proper management of fresh
water resources is becoming increasingly critical.

Within the U.S. alone, water disasters such as drought and flooding can
occur in any region in any season. Long- and short-term climate cycles
can impact the regional availability of water for human use, thus it is
essential that decision makers consider water availability on many
temporal scales. Particularly in the western half of the U.S., where the
driest conditions exist in our country and a population boom is
occurring, proper management of water supply is essential, requiring the
best cutting-edge technologies and information to ensure high-quality
management decisions.

One agency responsible for such decisions is the U.S. Bureau of
Reclamation (Reclamation), a component of the Department of Interior.
They manage the largest quantity of wholesale water in the U.S. and are
responsible for many aspects of water management, including flood
control, irrigation, maintaining sufficient water levels for healthy
wildlife and endangered species habitat, hydroelectric power, and other
public- and industrial-related uses. They rely heavily on ground
observation networks, including many from other agencies, but these
networks usually do not cover all important areas that contribute to the
river systems for which Reclamation must monitor, predict, and make
decisions. Also, due to the lack of some of the spatial information
needed, they must calibrate models with just these point measurements,
making many assumptions to do so.

[]{#__RefHeading___Toc129688127 .anchor}**1.2. Partnering with
Reclamation**

In response to this need for more spatially and temporally complete
information, Reclamation has partnered with NASA and other government
agencies to explore the use of remotely sensed and remote sensing-based
model products and to employ different models and techniques to work
further with the remote sensing products. Remotely sensed and enhanced
observation-based products are currently being and will be tested and
benchmarked as inputs to Reclamation's decision support tools (DSTs),
RiverWare and AWARDS ET Toolbox (Agricultural Water Resources Decision
Support system Evapotranspiration Toolbox). RiverWare is a dually
supported DST by Reclamation and the Tennessee Valley Authority (TVA),
and it is mainly developed by the Center for Advanced Decision Support
for Water and Environmental Systems (CADSWES) at the University of
Colorado at Boulder. By collaborating with Reclamation's national and
regional offices and their partnering agencies, like USGS and NOAA, we
aim to validate and benchmark an integrated NASA observation and
modeling framework that will help meet the needs of water managers,
engineers, and farmers alike for the different regions and the different
water-related problems affecting those regions (e.g., flooding, drought,
etc.). An MOU between NASA and Reclamation is being finalized to help
facilitate this partnership further, and a five year project plan has
been prepared to identify how this partnership will be carried out for
near-term and long-term goals. These goals are outlined and described in
the NASA ESE Water Management Plan, which can be obtained at
<http://aiwg.gsfc.nasa.gov/esappdocs/progplans/water_ver1-1.pdf>.

A few pilot studies are now underway in certain regions of the western
U.S. to evaluate, verify & validate, and benchmark the datasets of the
MODIS (Moderate Resolution Imaging Spectroradiometer) sensor aboard the
Earth Observing System (EOS) Terra and Aqua satellites, Landsat TM data,
ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer),
SRTM (Shuttle Radar Topography Mission), AMSR-E (Advanced Microwave
Scanning Radiometer - EOS) and other remote sensing platforms provided
by NASA and NOAA. The use of these datasets will be further enhanced by
assimilating them into land surface models as part of the NASA land
modeling system known as the Land Information System (LIS), providing
outputs of soil moisture, runoff, evapotranspiration, snowpack, and
energy fluxes.

The Water Management Applications (WMA) team of the Hydrological
Sciences Branch at NASA Goddard Space Flight Center (GSFC) has partnered
with researchers and water resource managers at Reclamation offices in
Denver, CO, and their regional offices. In addition, project
collaborations, supporting work with Reclamation, have been established
with the Desert Research Institute (DRI), University of Nevada, Reno,
and the University of Idaho, Kimberly, ID. The main focus of these
projects is to integrate, validate, and benchmark NASA Earth Science
products, involving a suite of remotely sensed datasets and model
produced output in RiverWare and AWARDS ET Toolbox.

[]{#__RefHeading___Toc129688128 .anchor}**1.3. Decision Support Tools:
AWARDS ET Toolbox and RiverWare**

The AWARDS ET Toolbox was designed and implemented by researchers at
Reclamation to address the water resource needs of irrigation farmers,
reservoir managers, and for a wide range of other applications. The main
goal of this DST is to monitor effective rainfall amounts and predict
evapotranspiration (ET), water consumption by different land surface
types and account for evaporation of open water sources.

Reclamation's river management decision support tool, RiverWare, is
dually supported by Reclamation and the Tennessee Valley Authority
(TVA), and it is mainly developed by the Center for Advanced Decision
Support for Water and Environmental Systems (CADSWES) at the University
of Colorado at Boulder. Selected outputs from the AWARDS ET Toolbox
project, like daily riparian and crop water use estimates, can be
automatically ingested into RiverWare, the main river modeling and water
accounting system used by several of the regional Reclamation offices.
Due to this connection between the AWARDS ET Toolbox and RiverWare, they
are included together in this evaluation report.

[]{#__RefHeading___Toc129688129 .anchor}**1.4. Pilot Study Regions**

#### Three river basin regions of major interest to Reclamation have been selected for this study -- the Truckee-Carson Rivers, the Yakima-Columbia Rivers, and the Upper/Middle Rio Grande River. Figure 1 shows these three main river basin regions. The key NASA remote sensing and model products will be tested, validated and benchmarked for use in these two DSTs for those regions. Both retrospective studies and 

#### ![](media/image2.jpeg){width="5.697916666666667in" height="3.807638888888889in"}

[]{#__RefHeading___Toc129421802 .anchor}*Figure 1*. A map of the three
main river basin regions where the Reclamation DSTs will be evaluated
and benchmarked with NASA data products.

near real-time simulations are being evaluated and made available to
investigate where monitoring and forecasting of water supply and extreme
events, like flooding, may be enhanced. The knowledge gained and
technology developed for these efforts are also intended to be
transferred to other basins managed by Reclamation. The NASA GSFC team
has been customizing the Land Information System (LIS) software and
accompanying land surface models (LSMs) to be run specifically for these
project basins. A brief overview of each pilot study basin follows.

#### *Upper and Middle Rio Grande River Basins, Colorado and New Mexico* 

The main region of interest for the Rio Grande River spans from the San
Juan Mountains in southern Colorado to Elephant Butte Reservoir near
southern New Mexico. From southern Colorado to about Cochiti Dam in New
Mexico is considered the Upper Rio Grande, and from where Cochiti Dam is
located to Elephant Butte Reservoir is considered to be the Middle Rio
Grande reach. A 1996 meeting of six federal agencies, including
Reclamation, recognized the need for a unified water operations model
for the Upper Rio Grande Basin and the need for a better way to monitor
and manage the Rio Grande River. This unified operations model became
known as the Upper Rio Grande Water Operations Model (URGWOM), and is a
set of daily time-step, river-reservoir models for the Upper Rio Grande
basin, utilizing RiverWare. It is capable of simulating river and
reservoir hydrology, water accounting and operation logic in the Rio
Grande upstream of Elephant Butte Reservoir in New Mexico, and flood
control from Elephant Butte Dam to American Dam near Fort Quitman,
Texas.

#### *Yakima-Columbia River Basins, Washington* 

The Yakima River Basin, a tributary of the Columbia River system, was
selected as a pilot study area because it has the most complete set of
Watershed and River Systems Management Program (WaRSMP) research
products that link the RiverWare modeling and decision support framework
to other modeling components or DSTs, like AWARDS ET Toolbox. In the
Yakima basin, Reclamation is conducting research to improve the
operation of the river system to provide a more sustainable environment
to meet complex demands. These demands include hydropower generation,
irrigation, and municipal and industrial deliveries of water for
beneficial use, which must be met while maintaining water quality
standards to protect ecosystems and fisheries.

Reclamation investigators are actively involved in research applications
under the WaRSMP, an applied research program that is sponsored by
Reclamation's Science and Technology Program. The WaRSMP budget is
leveraged with funds and/or services from partnering agencies including
NOAA's Office of Global Programs, the U.S. Geological Survey (USGS), the
Tennessee Valley Authority (TVA), the U.S. Army Corps of Engineers and
the WSR-88D Radar Operations Center. WaRSMP develops, demonstrates, and
deploys advanced decision support systems and models of river systems to
Reclamation's water resource managers for operational decision-making
(Frevert et al., 2000). The key pieces of the WaRSMP framework include
RiverWare, Reclamation's Oracle relational database, Hydrologic Database
(HDB), and the AWARDS ET Toolbox. USGS contributes a distributed
hydrologic runoff model, the Precipitation-Runoff Modeling System
(PRMS), within the Modular Modeling System (MMS).

#### *Truckee-Carson River Basins, Nevada and California*

The headwaters of the Carson River flow without significant regulation
from the Sierra Nevada down the East and West Forks of the Carson River
to the mountain front in the Carson Valley in Nevada. Near the mountain
front, the East and West Forks of the Carson River converge, then flow
across the Carson Valley to the Lahontan Reservoir. The demand side of
the Truckee-Carson system differs considerably from the Rio Grande.
There is a major diversion of the Truckee at Derby Dam. The diverted
water flows along the Truckee Canal to Lahontan Reservoir and on to a
major agricultural area near Fallon, Nevada. There is major agricultural
activity served by the entire canal. The key to operating the Truckee
and Carson efficiently is to accurately forecast the streamflow rates at
Farad, NV and Fort Churchill, NV. The primary errors associated with
these streamflow forecasts are associated with the major agricultural
uses (diversions) along the Carson Valley (between the East and West
Fork gauging stations and Fort Churchill) and the evaporative losses in
Lake Tahoe.

The MMS-PRMS (see description below) and RiverWare software packages
have also been applied throughout the Truckee-Carson system as part of
the WaRSMP. Daily values of observed precipitation and temperature at
existing SNOTEL and NOAA/NWS Cooperative Observer Network sites are used
to estimate daily values of precipitation and temperature at the
centroid of each hydrologic response unit (HRU) for the calibration and
real time operation of PRMS using regional relationships between the
elevation, latitude, and longitude.

[]{#__RefHeading___Toc129688130 .anchor}**1.5. Systems Engineering
Approach**

The primary purpose of the partnership between NASA and Reclamation is
to benchmark the results of using NASA Earth Science products in
Reclamation's decision support systems. To attain these results, a
systems engineering approach will be employed.

The first phase of this approach is to evaluate applicable Reclamation
DSTs and determine which NASA products show the most potential for
improving DST performance and/or outcomes. **This report describes the
results of this process**.

The second phase of this effort will be to Verify and Validate (V&V)
NASA Earth Science products within AWARDS ET Toolbox and RiverWare. The
V&V process ensures that NASA products can be added to or substituted
within the DST without further DST development. The V&V stage will also
be used to demonstrate that inclusion of NASA products in the DST allows
the user to achieve the desired results. Finally, during the V&V
process, benchmarking metrics and procedures will be defined. A V&V
Report will be provided at the end of this second stage.

The final phase of this approach will be to Benchmark relevant NASA
products. Individual products will be substituted and/or included during
DST runs over the same region and for the same timeframe. Then,
combinations of NASA products will be tested and compared against
baseline runs made prior to the inclusion of NASA data. The benefit of
this Benchmarking approach to Reclamation will be to show the impact of
using NASA data and modeling products in RiverWare and AWARDS ET
Toolbox. The benefits to NASA include continuation of its mission
"\...to understand and protect our home planet." In the long run, there
are many potential societal benefits that could result from this work
(see Figure 2). For example, better data may lead to better management
decisions by Reclamation, in turn ensuring clean water for human
consumption, recreation, and the environment.

This project aims to demonstrate successful use of the Integrated
Systems Solution Approach proposed by the NASA Applied Sciences
Directorate. A flowchart describing this approach is shown in Figure 2
below.

[]{#__RefHeading___Toc129421803 .anchor}***Figure 2***. An illustration
of the architecture underlying the activities of the Earth Science
Applications Program and its specific application to the Reclamation
DSTs.

# 2. Overview of the DSTs

Two of the main DSTs for which Reclamation has supported development are
RiverWare and the AWARDS ET Toolbox. While RiverWare and AWARDS ET
Toolbox can be operated as standalone DSTs, using output from AWARDS ET
Toolbox in RiverWare can provide water managers with better information
for making decisions. In addition, Reclamation works with other
government agencies from local to Federal levels to incorporate
additional modeling tools and data into these two DSTs. These more
integrated and comprehensive DST environments enable Reclamation to test
and ingest other layers of information and models, like those from NASA.
Descriptions of these two DSTs and their various modeling and data
components are included in the following paragraphs.

# 2.1. Components of the AWARDS ET Toolbox 

***AWARDS***

The Agricultural WAter Resources Decision Support (AWARDS) system is an
automated information system to assist water managers and users by
providing easy access to rainfall and daily crop water use estimates.
These estimates are based on real-time data obtained from the WSR-88D
(Weather Surveillance Radar -- 1988 Doppler) radar system and automated
weather stations. The purpose of the AWARDS system is to improve the
efficiency of water management and irrigation scheduling by providing
guidance on when and where to deliver water, and how much. Recent
research has been focused on improving the radar-based quantitative
precipitation estimates (QPE) and developing a runoff enhancement. The
goal is to input watershed QPEs to distributed hydrologic model(s),
which will generate real-time side-wash inflows into the main stem of a
river system, and subsequent streamflows into Reclamation's reservoir
facilities (Hunter et al., 2002).

***The AWARDS ET Toolbox***

Reclamation has developed the Evapotranspiration Toolbox (ET Toolbox),
which builds on the AWARDS system, adding GIS land use to specify crop,
riparian, and open water surface acreage, as well as vegetation type and
coverage within selected Hydrologic Rainfall Analysis Project (HRAP)
grid cells, or defined sub areas and river reaches (Hartzell et al.,
2002). The AWARDS ET Toolbox is now operational in portions of Oklahoma,
Oregon, Washington, Montana, Arizona, and New Mexico (Hartzell et al.,
2000; Hartzell et al., 2002).

The ET Toolbox estimates the daily surface water use requirements at a
resolution useful for implementation in integrated modeling systems
(Figure 3), like the Upper Rio Grande Water Operations Model (URGWOM).
The ET Toolbox project was designed and developed to automatically input
daily riparian and crop water use estimates, open water evaporation
estimates, and WSR-88D-based rainfall estimates to RiverWare. Table 1
lists some of the required inputs to AWARDS ET Toolbox. Recently,
consumptive use forecasts have been added to the ET Toolbox. These
72-hour forecasts are based on the National Centers for Environmental
Prediction (NCEP) Eta model weather forecast parameters at a 12-km grid
resolution. The ET Toolbox uses Eta model 3-hr forecasts of fields, like
temperature, relative humidity, and wind speed. Forecast crop and
riparian ET, and open water evaporation are then determined from these
parameters.

Formerly within the ET Toolbox in the Middle Rio Grande region, the land
cover and land use information was defined by a Land Use Trend Analysis
(LUTA) map until spring of 2004. Since then, Reclamation has fit the
AWARDS ET Toolbox with a very high resolution land cover classification
derived from satellite- and airborne multi-spectral resolution land use
data sets (Utah State University; and Brower, 2003). The high resolution
land cover classes are aggregated to sub-HRAP grid areas and used to
calibrate and calculate ET values for the AWARDS and URGWOM model
components.

**[Table 1.]{.underline} Current inputs to AWARDS ET Toolbox**

  ---------------------------- ----------------------- -------------------
  Product                      Source                  System Operator

  Doppler Radar                Doppler Radar           NOAA
  Derived-Precipitation                                

  GIS-based land-use and land  Very high resolution    Reclamation / Utah
  cover classifications        remotely sensed         State University
                               measurements; field     
                               observations            

  Automated streamflow gaging  Field site data          USGS/MRGCD
  stations                                             

  Automated operational        Field site data         Reclamation/MRGCD
  weather stations                                     
  ---------------------------- ----------------------- -------------------

[]{#__RefHeading___Toc129421804 .anchor}

![](media/image3.jpeg){width="5.519444444444445in" height="3.2625in"}

*Figure 3.* The AWARDS ET Toolbox includes this typical interactive web
map of effective rainfall (left) and a plot of total evapotranspiration
and stream flow (in cfs; right).

The crop, land use and water evaporation coefficients (referred to
generically as K~c~) that are used in the ET Toolbox are expressed as
functions of either the Growing Degree Days or the Month of the year.
The K~c~ is multiplied by the reference ET (ET~o~) to determine the
daily ET, where daily ET~o~ is calculated by a modified Penman equation
using ground measurements of solar radiation, air temperature, vapor
pressure and wind speed (Brower, 2003). The ET Toolbox, as described by
Brower (2003), contains potential K~c~ curves for about 20 agricultural
crops and about five natural vegetation systems plus open water and wet
soil. A primary challenge in applying the potential K~c~ curves is that
they represent upper limits of ET under high management conditions.
Therefore, even though relatively accurate and location specific land
use information is utilized inside the ET Toolbox and AWARDS,
substantial uncertainty exists in the appropriate (real) values to use
for the crop and land use coefficients. The K~c~ curves utilized in the
ET Toolbox tend to represent ET under potential growing conditions where
water, crop and agronomic management are optimal (Brower, 2003). The
development of K~c~ information representing actual conditions along the
valley for specific crop types and other land uses on a grid-cell basis
has potential to significantly improve water demand forecast accuracy by
URGWOM.

# 2.2. Components of RiverWare

RiverWare provides a flexible framework for developing and running site
specific models that incorporate the "law of the river," other policy
constraints, and physical processes including hydrology, structural and
natural operating constraints imposed dams, hydropower generating
turbines, spillways, diversions and conveyance structures (canals),
river channels and bank storage (Zagona et al., 2001). Within each river
system, RiverWare requires streamflow hydrograph estimates as input at
many locations throughout the system. A streamflow forecast model is
used to estimate daily runoff hydrographs for portions of the basin
based on March--July volumetric forecasts developed by the USDA Natural
Resources Conservation Service (NRCS) for various points within the
basins. NRCS volumetric forecasts are converted to daily estimates
through a "similar years" approach where a hydrograph from a historical
database is selected to estimate the future runoff based on its
similarity to the forecasted volume and shape up to the point when the
forecast is made. Some required inputs for RiverWare can be found in
Table 2 below. Additional details about RiverWare can be found at
[http://cadswes.colorado.edu.]{.underline}

The Hydrologic Database (HDB) is a relational database developed for the
Oracle software environment. The schema is focused to support RiverWare
and MMS modeling environments. Several applications serving the
RiverWare and MMS environments permit storing and managing historic and
real-time data observations as well as storing and managing modeled
output. Connections between models and data stores, called Data
Management Interfaces (DMIs), have been developed and maintained by
Reclamation. A DMI provides a utility application by which users may
write their own routines to access data from external sources, including
databases, and instruct RiverWare to load them into the model.
Similarly, user routines can export results of model runs in any desired
format. A menu-driven Graphical User Interface (GUI) within RiverWare
provides access to the DMIs, so large amounts of data may be loaded with
a single menu selection.

[]{#__RefHeading___Toc129423359 .anchor}[Table 2]{.underline}. Current
inputs to RiverWare

  ----------------------------------- ------------------- -------------------
  Product                             Source              System Operator

  Geographic Names Information System N/A                 USGS
  Dam Locations                                           

  Stream Gage Height and Flow         N/A                 USGS

  Water percolation and canal seepage N/A                 Reclamation

  Land Cover Classification           Very high           Reclamation
                                      resolution          
                                      satellite and       
                                      airborne            
                                      measurements; field 
                                      observations        

  Cooperative Observer Network        Station Instruments NOAA

  Evapotranspiration estimates        AWARDS ET Toolbox   Reclamation

  Diversion information (flow)        AWARDS              Reclamation/MRGCD

  Weather and stream data             Gage                MRGCD
  ----------------------------------- ------------------- -------------------

***MMS-PRMS***

The USGS Precipitation Runoff Modeling System (PRMS) (Leavesley et al.,
1983), within the MMS (Leavesley et al., 1996), has been applied
throughout the Upper Rio Grande and the Truckee-Carson basins as an
alternative approach to real-time hydrograph generation for input to
RiverWare. MMS-PRMS is used to generate streamflow forecasts by
estimating important hydrologic state variables (e.g., soil moisture
storage, snow water equivalent, etc.) at the time of the forecast and
running the model forward in time with estimates of future daily
precipitation and temperature from a variety of different approaches.

PRMS is a modular-design, distributed parameter, physical-process
watershed model that was developed to evaluate the effects of various
combinations of precipitation, climate and land use on watershed
response. Watershed response to normal and extreme rainfall and snowmelt
can be simulated to evaluate changes in water-balance relations, flow
regimes, flood peaks and volumes, soil-water relations, sediment yields,
and ground-water recharge. Parameter-optimization and
sensitivity-analysis capabilities are provided to fit selected model
parameters and to evaluate their individual and joint effects on model
output. A water balance and an energy balance are computed daily for
each (HRU). The sum of the responses of all HRUs, weighted on a
unit-area basis, produces the daily watershed responsse.

***URGWOM***

URGWOM employs RiverWare and inputs from the AWARDS ET Toolbox. A lack
of adequate or available physical data precludes the precise, reliable
simulation of many physical features operating in the Rio Grande Basin.
In these cases, URGWOM uses the best available (or sometimes the only
available) data, to simulate physical processes. As a result, some of
the simulations require data extrapolations that would not normally be
considered. One of the benefits of URGWOM development is that it serves
as a tool for identifying areas where additional data or investigations
are needed for optimal model operation and, therefore is an excellent
platform to test and benchmark the value of new information such as NASA
Earth Science products.

# 3. Consideration of NASA Inputs

# 3.1. Potential NASA ESE Products for Reclamation DSTs

The NASA Earth Science Enterprise (ESE) programs support both science
and applications, and the products developed from within are derived
from both satellite data and models. The subsequent sections highlight
both the satellite and modeled data that have been identified to be used
as potential products in Reclamation's DSTs: RiverWare, AWARDS ET
Toolbox, and their related model components.

# 3.1.1. NASA's Satellite-Derived Products 

The primary NASA satellite products to be tested in a systems
engineering context for use by Reclamation include:

• Snowpack fields

• Evapotranspiraton (ET) estimates

• Land cover, vegetation index, and other vegetative datasets

• Soil moisture and soil temperature

A summary of the NASA data products from the following satellite sensors
that will be investigated with Reclamation DSTs include:

> ***MODIS*.** The MODIS (Moderate Resolution Imaging Spectrometer)
> sensors on both ***Terra*** and ***Aqua*** satellites provide
> estimates from 250m to 1km of land cover classes, vegetation
> conversion, land cover change, surface albedo, surface temperature,
> greenness indexes and other land surface variables at 1-2 times each
> day (i.e., during daylight). Most of these products may be used in the
> suite of land surface models within LIS.
>
> ***ASTER*.** ASTER products are similar to Landsat but can be used in
> backward viewing for stereoscopic observation. With multispectral
> thermal bands between 8-12 µm, ASTER has 4 (VNIR) 15m bands, 6 (SWIR)
> 30m bands and 5 (TIR) 90m bands with a swath of 60km. ASTER provides
> many of the capabilities of Landsat, but data availability is more
> limited.
>
> ***AMSR-E***. The Advanced Microwave Scanning Radiometer-EOS is a six
> frequency, dual polarization microwave instrument on EOS Aqua used to
> measure microwave emitted radiation at spatial resolutions previously
> unattainable. The AMSR-E team is developing a suite of products,
> including snow water equivalent. Unfortunately, due to signal problems
> the frequency for soil moisture data is also limited.

Other satellite sensors to be evaluated include the NASA Landsat, EO-1
Advanced Land Imager (ALI), and spatial precipitation (i.e., NOAA radar
datasets and "CMORPH" using a suite of satellite-based data including
TRMM). Table 3 summarizes the list of remotely sensed products which
could be applied directly or indirectly to Reclamation's DSTs.

Also some of these satellite products will be used in conjunction with
certain modeling systems or algorithms, like LIS or "METRIC." For
example, snowpack fields, such as snow water equivalent, can be derived
using a combination of NASA MODIS snow cover, AMSR-E snow water
equivalent and LIS water availability modeling. Another example involves
employing the Mapping EvapoTranspiration at High Resolution with
Internalized Calibration (METRIC) technique and model which uses MODIS,
Landsat ETM+, and/or ASTER as inputs to estimate ET. These modeling
aspects and projects are described further in the following sections.

[]{#__RefHeading___Toc129423360 .anchor}[Table 3]{.underline}. Satellite
Product Input into AWARDS ET Toolbox and RiverWare (see Section 3.1.1
for description)

+---------+--------+-------------+-----------------------------------+
| Sa      | Sensor | System      | Product                           |
| tellite |        | Operator    |                                   |
+---------+--------+-------------+-----------------------------------+
| L       | ETM+   | USGS        | GTOPO30                           |
| andsat7 |        |             |                                   |
|         |        |             | Digital Elevation Models (DEM)    |
+---------+--------+-------------+-----------------------------------+
| TERRA   | ASTER  | NAS         | AST04 -- Brightness Temperature   |
|         |        | A/JPL/Japan |                                   |
|         |        |             | AST09 -- Surface Radiances for    |
|         |        |             | VNIR, SWIR, TIR                   |
+---------+--------+-------------+-----------------------------------+
| TERRA/  | MODIS  | NASA        | MOD02 -- Top of the Atmosphere    |
|         |        |             | Radiance                          |
| AQUA    |        |             |                                   |
|         |        |             | MOD09 -- Land Surface             |
|         |        |             | Reflectivity                      |
|         |        |             |                                   |
|         |        |             | MOD10 -- Snow cover               |
|         |        |             |                                   |
|         |        |             | MOD11 -- Land surface temperature |
|         |        |             |                                   |
|         |        |             | MOD12 -- Land Cover               |
|         |        |             | Classification                    |
|         |        |             |                                   |
|         |        |             | MOD15 -- Leaf Area Index          |
|         |        |             |                                   |
|         |        |             | MOD43b -- Albedo and BRDF         |
|         |        |             |                                   |
|         |        |             | MOD44b -- Continuous Vegetative   |
|         |        |             | Fields                            |
+---------+--------+-------------+-----------------------------------+
| SRTM    | SRTM   | NA          | Radar-DEM elevation dataset       |
|         |        | SA/JPL/USGS |                                   |
+---------+--------+-------------+-----------------------------------+

# 3.1.2. NASA's Model-Derived Products

NASA's Land Information System (LIS) modeling capabilities, in
combination with NASA satellite data products, such as MODIS land
surface temperature and land cover, are directed toward capturing the
most realistic representations of land surface dynamics and their
interactions with the atmosphere over large areas and at relatively high
resolutions (examples shown in Figure 4). The main hydrometeorological
variables that LIS produces include soil moisture, evaporation, snow
cover, runoff, precipitation, and radiation and energy budget variables.
Nearly all of these LIS outputs can in some capacity be used in the
AWARDS ET Toolbox or RiverWare. Many of the relevant LIS modeled water
and energy output variables are listed and summarized in Table 4 below.

The NASA North America Land Data System (NLDAS; Mitchell et al., 2004,
Cosgrove et al., 2003) forcing data fields, which drive the LIS LSMs,
can be used for real-time and retrospective simulations for within
AWARDS ET Toolbox or used also to drive RiverWare. In addition,
different atmospheric forecast fields can be used for AWARDS ET Toolbox
and are currently available from LIS and the NLDAS forcing fields (i.e.,
NCEP Eta-12 km, FSL RUC-20 km). All three modes (i.e., retrospective,
real-time, and forecast) can be used to generate soil moisture,
evapotranspiration and heat fluxes out to 72 hours. Also at NASA,
diurnal (2-5 day) to intraseasonal (30-90 days) to annual (1-5 year)
predictions of precipitation and temperature generated by the NASA
Global Modeling and Assimilation Office (GMAO), could be tested and
validated in the DSTs.

[]{#__RefHeading___Toc129423361 .anchor}[Table 4]{.underline}. Potential
NASA Model Product Input into AWARDS ET Toolbox and RiverWare (see
Section 3.1.2 for description).

  ---------------- -------------------- --------- ---------------------------
  Model            Variable             Units     Input to DST

  Noah, CLM2,      Snow water           mm,       RiverWare
  Mosaic           equivalent           inches    

  Noah, CLM2,      Surface temperature  K         AWARDS ET Toolbox
  Mosaic                                          

  Noah, CLM2,      Evapotranspiration   mm        AWARDS ET Toolbox ,
  Mosaic                                          RiverWare

  NLDAS Forcing    Precipitation, air   mm, K,    AWARDS ET Toolbox,
  Fields           temperature, etc.    etc.      RiverWare
  ---------------- -------------------- --------- ---------------------------

[]{#__RefHeading___Toc129688138 .anchor}**3.2. Potential NASA Inputs to
AWARDS ET Toolbox**

The focus of validating and benchmarking both the NASA Earth Sciences
products in AWARDS ET Toolbox involves all the listed partners. For this
DST, satellite and model variables and parameters which are relevant to
computing the hydrological processes, like evaporation and
transpiration, are of main interest. Also, the various methods to
calculate ET are being compared and evaluated, since each model or
method entails slightly different input needs. The goal is to make the
best estimates of ET and related variables, so it can be determined how
much moisture is being released back to the atmosphere and not remaining
in the river or reservoirs.

The LIS LSMs (mainly CLM2, Mosaic, and Noah) will be used to generate ET
and moisture and energy budget components for use in and comparison with
the current AWARDS ET Toolbox ET estimates. Each LSM consists of a
different ET calculation method, so each model will be validated against
in-situ moisture and energy measurements along with the current AWARDS
ET Toolbox ET method. Also, the NLDAS forcing datasets can be downscaled
appropriately and used in AWARDS ET Toolbox, in place of the current
in-situ observations employed for many of the regions. The NLDAS fields
provide more spatially continuous information versus the current station
observations, which only extend information from a point to an entire
area of varying terrain, vegetation and soil conditions.

![](media/image4.jpeg){width="6.15in" height="4.717361111111111in"}

[]{#__RefHeading___Toc129421805 .anchor}***Figure 4***. Example MODIS
and LIS products that are being tested with the AWARDS ET Toolbox DST.
The land cover classification map (upper left) is the MODIS product 12,
version 4, and is blended with Landsat and the Reclamation LUTA land
cover. Total rainfall and evapotranspiration (in mm) is from LIS and the
Noah LSM for August, 2003, for the Albuquerque region (upper and middle
right, respectively).

Another modeling-observation merged process in estimating ET involves
the two programs: the SEBAL procedure (Surface Energy Balance Algorithm
for Land) and the METRIC procedure. METRIC is an extension of SEBAL that
utilizes ground-based reference ETo from weather data to improve the
internalized calibration and is the preferred application by the
University of Idaho. The procedures index sensible heat flux from the
land surface to satellite-measured surface temperatures at specific
surface boundary conditions. The ET maps created by METRIC and SEBAL for
daily, monthly and seasonal time periods have been compared against
lysimeter measurements of ET in southern Idaho and show good consistency
and agreement (e.g., Allen et al., 2003).

The University of Idaho researchers have identified different MODIS
products to update and refine seasonal crop and other land-use
coefficient (Kc) curves for areas along the Middle Rio Grande which can
be used to generate METRIC-based ET maps and an accurate crop-specific
land use classification. These MODIS and METRIC-based ET maps are
designed to work within the AWARDS 4 km x 4 km grid cells. For the Upper
Rio Grande and Truckee-Carson regions, METRIC-based ET maps can be
derived using multiple MODIS satellite imagery augmented by periodic
high resolution Landsat imagery. ET derived from Landsat images may be
used to validate MODIS-based ET maps, due to Landsat's ability to
isolate thermal and short-wave characteristics for individual vegetation
types, and to assist with land use cover identification (see Figure 5).
Developed Kc information can be fed into the AWARDS and ET Toolbox to be
combined with daily reference ET to produce daily ET demands.

MODIS data products have also been prepared and enhanced to parameterize
and constrain the LIS LSMs. For example, the MODIS leaf area index (LAI;
MOD15), vegetation and land cover classification (MOD12), and continuous
vegetation fraction (MOD44b) have been used as parameters in most to all
of the LSMs. The other MODIS products that could be incorporated and
assimilated into the LSMs and are relevant to potentially improving the
AWARDS ET Toolbox include the land surface temperature (LST; MOD11) and
snow-free albedo (MOD43b) products. As for METRIC, other approaches for
calculating the LST, using additional lower level MODIS products, are
needed due to certain documented issues with the MOD11 product. Some of
these other issues being addressed include geolocation errors and
coregistration of Terra and Aqua MODIS products, and the off-nadir
stretching of pixels (where pixels can expand from a 1 km to a size of a
2 km x 3 km area and therefore reduce clarity of energy balance within
narrow river corridors such as the Middle Rio Grande), and striping
imbedded in some reflectance and albedo products. These analyses have
been done to ensure the integrity of the final ET product and to
increase familiarity with quality and accuracy of various MODIS
products.

The METRIC ET method has been proven to work well with MODIS images once
reflectance and LST images have been reconstructed, starting with lower
level radiance data. Current work in METRIC has included automation of
the energy balance calibration when applied to MODIS products.
Application of METRIC with Landsat imagery has provided means for
verifying calibration accuracy of applications to MODIS, since the high
resolution TM (120 m thermal pixels) permits isolation of ET and energy
balance components for individual types of vegetation including
individual irrigated fields and riparian vegetation that are common
along the Middle Rio Grande corridor.

![](media/image5.jpeg){width="6.1in" height="2.564583333333333in"}

[]{#__RefHeading___Toc129421806 .anchor}***Figure 5.*** METRIC-derived
ET maps from MODIS (left image is for the 57^o^ view angle; the center
is for the 2^o^ view angle) and from Landsat (right image).

The greatest need for improving ET Toolbox consumptive use estimates and
forecasts is the frequent and accurate updating of the crop and riparian
vegetation indexing. At a minimum, these updates are needed at least
once each year when vegetation is at maturity level. To be useful
operationally, these updates need to be timely (i.e., quick turnaround
time of about one month or less) and relatively low cost. Other needs
for improving the ET Toolbox include the incorporation of soil moisture
data (especially estimates of soil moisture in the root zone) and
estimates of effective precipitation.

Currently, several regions that the AWARDS ET Toolbox is being run for
do not include a soil moisture variable in estimating demand or
calculating consumptive use, for example, the Middle Rio Grande region.
Soil moisture is one of the key output fields generated by the LSMs in
LIS. Accurate estimates of soil moisture would be useful for forecasting
irrigation water demand. Soil moisture is essential for successful
tillage and planting, seed germination, root extension, mineral nutrient
absorption by roots, and soil microbiological and chemical processes.
Water movement through the root zone of irrigated soils is essential for
leaching to maintain a favorable salt balance, a growing problem for
many states in the Western U.S.

[]{#__RefHeading___Toc129688139 .anchor}**3.3. Potential NASA Inputs to
RiverWare**

In working with Reclamation to see how NASA products may benefit the use
of RiverWare, several key steps are being made to further develop NASA
remotely sensed datasets, like from NASA satellite and the LIS modeled
output datasets to be evaluated in RiverWare. Since RiverWare's main
functions are to produce the most accurate streamflow estimates
possible, accounting for overall water storage in a river system, one
major goal is to help improve this DST with NASA data by providing
inputs that support generation of real-time and forecast hydrographs.
Some of the output fields from LIS LSMs, such as surface and baseflow
runoff, snow water equivalent and ET, could be used as inputs to
RiverWare to generate such hydrographs. However, with surface and
baseflow water routing schemes implemented in LIS, modeled water flow
from over the land could be accounted for and be collected at points to
generate streamflow hydrographs. This hydrograph information could then
be used directly in RiverWare, similar to the way that MMS-PRMS modeled
outputs are used in RiverWare. These streamflow hydrographs will be
compared with USGS hydrographs for the V&V and benchmark stages. The
NLDAS variables that drive the LSMs in LIS, such as precipitation, wind
velocity, and surface radiation balance terms, will be evaluated in
RiverWare as well, since the meteorological forcing for MMS-PRMS tends
to be mostly station-based observations.

![](media/image6.jpeg){width="6.1in" height="3.0444444444444443in"}

[]{#__RefHeading___Toc129421807 .anchor}*Figure 6*. Cloud-free MODIS
MOD02 visible images were processed for Water Year 2000 --2005 for the
Truckee-Carson Region with view angles \< 30 degrees to calculate the
Normalized Difference Snow Index (NDSI). Fractional snow cover maps are
generated from this MODIS product and can be used in PRMS and RiverWare
(based on *Salomonson and Appel, 2004*).

The key MODIS datasets identified to be validated and benchmarked for
indirect or direct use within RiverWare include the daily and/or 8-day
snow products (MOD10, MYD10), leaf area index (MOD15, MYD15),
top-of-the-atmosphere radiances (MOD02), and albedo (MOD43b). The MOD02
bands are being used to calculate the Normalized Difference Snow Index
(NDSI; see Figure 6) which is then used to derive fractional snow cover
at higher resolutions, based on a method by Salomonson and Appel (2004).
The resultant fractional snow cover in used as inputs into PRMS-MMS and
then RiverWare. Other MODIS products, like land cover classification
(MOD12), NLCD land cover, and other high resolution elevation datasets
(i.e., NED and SRTM) are all datasets that can be used within LIS and
MMS-PRMS and be tested in RiverWare.

To incorporate relevant LSM output variables and streamflow hydrographs
into RiverWare, the LIS \~1 km grid output will need to be partitioned
or collected into sub areas, then the flow aggregated to the appropriate
RiverWare node as stream runoff in some fashion. So far, LIS has been
customized with moderate to high resolution parameter datasets for each
of these three regions, and currently LSM output being generated (e.g.,
precipitation components - snowfall and rainfall, SWE, ET, etc.) for use
in RiverWare. CLM2 is the first targeted LSM to be benchmarked due to
its improved ability to capture realistic snow cover and snow water
equivalency (SWE) estimates.

For long-term hydrologic forecasting capabilities, the U.S. National
Weather Service's Extended Streamflow Prediction (ESP) modified program
usually provides short-term and seasonal forecasting for floods and
water supply for RiverWare forecasts. NASA GMAO seasonal forecasts could
provide the essential hydrometeorological forcing fields required for
such long-term forecast inputs into RiverWare. However, those fields
could be used in some of the LSMs in LIS to provide the needed inputs to
generate the modeled hydrographs for long-term forecasts. MMS is
currently configured to output ESP runs via DMIs to HDB at different
river nodes or modeled positions where the stream gages are located.

[]{#__RefHeading___Toc129688140 .anchor}**3.4. Meeting Technical
Requirements with NASA Products**

While following a systems engineering approach, it is critical that all
NASA products tested conform to the existing DSTs' technical
requirements. With this in mind, neither AWARDS ET Toolbox nor RiverWare
will be further developed or changed to accommodate potential NASA
inputs. Rather, all NASA data products that are to be tested will be
formatted and adapted as necessary to be useful as input to the DSTs.

Efforts are currently underway to customize LIS for the various test
basins defined for this project. LIS provides a flexible framework,
allowing output of many physical variables required as input to both
AWARDS ET Toolbox and RiverWare. It is possible to tailor LIS to meet or
exceed existing input variables' resolutions. In addition, LIS can be
run using input from NASA satellite sensors such as MODIS. Because of
the flexibility of both spatial and temporal scales of LIS, it will be
possible to adapt NASA data products to meet the technical requirements
of Reclamation DSTs.

[]{#__RefHeading___Toc129688141 .anchor}**3.5. Gaps in Meeting DST
Needs**

Currently, these two DSTs and their model components rely most heavily
on station or point measurements, which are used to represent spatially
heterogeneous regions. Some regions, like the Upper Rio Grande River,
include very diverse land cover, terrain, and climate over a very small
area. Due to the nature of this diversity, point measurements will not
capture such variability, thus the DSTs may tend to only represent
certain atmospheric conditions and phenomena which are used to obtain
stream hydrographs and ET estimates, which go into generating the
hydrographs. Using more spatially representative datasets that are also
up-to-date and are available sub-diurnally (i.e., on 1-6 hourly
intervals) would provide the DSTs with more complete and updated
information. Using such information could lead to less frequent tuning
or recalibrating of the DST model components and may improve the
parameters and inputs to the DST operational capabilities.

In addition to providing more spatially based datasets to Reclamation,
it is a goal of the V&V and benchmarking stages to demonstrate the value
added by inclusion of the four times daily, weekly and/or semi-weekly
MODIS land cover products over the currently used static land use/land
cover maps that may be more than a decade old. Frequently updating
vegetation and land cover maps by more than a few months to a year is a
very costly and time consuming task that Reclamation has identified as a
priority of major interest to their user groups. One other advantage of
MODIS involves the MODIS Rapid Response System (RSS), which is currently
being used to download and archive a series of different MODIS products
for these regions. The Rapid Response System is able to retrieve and
process a few key products to MODIS Level 2 production standards, like
land surface temperature, within about 4 hours of the satellite passing
overhead. Once the RSS data products are quality controlled and
questionable scenes removed, more current information can be processed
quickly and ingested into LIS, METRIC, and PRMS-MMS and then into the
DSTs on much shorter time scales, an important aspect to water resource
managers who need such relevant information in a timely manner.

# 4. Next Steps

[]{#__RefHeading___Toc129688143 .anchor}**4.1. Conceptual Plans for
Verification and Validation of NASA Inputs**

After Reclamation's RiverWare and AWARDS ET Toolbox have been evaluated,
the next step is to begin to apply the most promising NASA data products
to these DSTs. The Verification and Validation (V&V) stage starts by
determining methods and procedures for incorporating NASA data products
into these DSTs. Efforts are currently underway to customize LIS for
each pilot basin. Also, satellite products such as from MODIS will be
ordered and subset to include these basins.

Early in the V&V stage, sample runs will be performed using currently
existing products (mostly non-NASA) and procedures. These runs will form
the basis for the Benchmarking stage. As each NASA product is tested,
specific benchmark metrics will be defined. For example, the most
appropriate benchmark statistic for many applications may be comparing
modeled stream flow estimates at a particular gauging station using LIS
input with stream flow estimated prior to the inclusion of the NASA data
product during the baseline runs. For other NASA products, it may be
more useful to compare total evaporation statistics over the entire
basin, or for a subset of a pilot basin.

As these procedures are developed, care will be taken to ensure that
inclusion of NASA data products does not change or compromise the
technical or user requirements of the decision support system. For each
NASA product, it is necessary to verify that it fits with system goals,
then validate that DST output is in the same format that is currently
used by Reclamation decision makers.

Upon completion of the V&V stage, a formal report will be presented to
the NASA Applied Sciences Directorate in accordance with NASA's Water
Management Program Plan. Following the V&V Report, benchmark metrics
will be used to compare RiverWare and AWARDS ET Toolbox output before
and after the inclusion of NASA data and modeling products. It is hoped
that improvements to Reclamation DSTs using NASA products will lead to
operational use by Reclamation and other partnering agencies.

#  

# 5.0 References

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Matthews, 2005: The use of land data assimilated products to improve
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Allen, R. G., A. Morse and M. Tasumi, 2003: Application of SEBAL for
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Leavesley, G. H., Restrepo, P. J., Markstrom, S. L., Dixon, M., and
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**6.0 Abbreviations and Acronyms**

ACE U.S. Army Corps of Engineers

ALI Advanced Land Imager

AMSR-E Advanced Microwave Scanning Radiometer-EOS

ASTER Advanced Spaceborne Thermal Emission and Reflection Radiometer

AWARDS Agricultural Water Resources Decision Support system

CADSWES Center for Advanced Decision Support for Water and Environmental
Systems

cfs cubic feet per second

CLM2 Community Land Model, Version 2

CMORPH CPC Morphing Technique

Corps U.S. Army Corps of Engineers

CPC Climate Prediction Center

DEM Digital Elevation Model

DMI Data Management Interface

DRI Desert Research Institute

DST Decision Support Tool

EO-1 NASA's Earth Observing System -- 1 satellite

EOS NASA's Earth Observing System

ESE NASA's Earth Science Enterprise

ESP NWS Extended Streamflow Prediction

ET Evapotranspiration

ETM+ Landsat 7 Enhanced Thematic Mapper Plus

ET~o~ Reference evapotranspiration

FSL NOAA's Forecast Systems Laboratory

GAPP NOAA's GEWEX Americas Prediction Project

GEWEX Global Energy and Water Cycle Experiment

GIS Geographic Information System

GMAO NASA's Global Modeling and Assimilation Office

GNIS Geographic Names Information System

GSFC NASA's Goddard Space Flight Center

GUI Graphical User Interface

HDB Hydrologic Database

HRAP Hydrologic Rainfall Analysis Project

HRU Hydrologic Response Unit

JPL NASA's Jet Propulsion Laboratory

K Kelvin

K~c~ Crop ET Coefficient

LAI Leaf Area Index

LIS NASA's Land Information System

LSMs Land Surface Models

LST Land Surface Temperature

LUTA Land Use Trend Analysis

METRIC Mapping EvapoTranspiration at High Resolution with Internalized
Calibration

MMS Modular Modeling System

MODIS Moderate Resolution Imaging Spectroradiometer

MOU Memorandum of Understanding

MRGCD Middle Rio Grande Conservation District

NASA National Aeronautics and Space Administration

NCEP National Centers for Environmental Prediction

NED National Elevation Dataset

NLCD National Land Cover Data

NLDAS North American Land Data Assimilation System

NOAA National Oceanic and Atmospheric Administration

NRCS Natural Resources Conservation Service

NWS National Weather Service

PRMS Precipitation-Runoff Modeling System

QPE Quantitative Precipitation Estimates

Reclamation U.S. Bureau of Reclamation

RSS Rapid Response System

RUC Rapid Update Cycle model

SEBAL Surface Energy Balance Algorithm for Land

SNOTEL SNOwpack TELemetry

SRTM NASA's Shuttle Radar Topography Mission

SWE Snow Water Equivalent

SWIR Short Wavelength Infrared

TIR Thermal Infrared

TM Landsat Thematic Mapper

TRMM Tropical Rainfall Measuring Mission

TVA Tennessee Valley Authority

URGWOM Upper Rio Grande Water Operations Model

USBR U.S. Bureau of Reclamation

USDA U.S. Department of Agriculture

USGS U.S. Geological Survey

V&V Verification and Validation

VNIR Visible and Near Infrared

WaRSMP Watershed and River Systems Management Program

WMA NASA's Water Management Applications Team

WSR-88D Weather Surveillance Radar-1988 Doppler