Flood-Hazard Mapping in Honduras

in Response to Hurricane Mitch

Prepared in cooperation with the U.S Agency for International Development

U.S. Department of the Interior

U.S. Geological Survey

Water-Resources Investigations Report 01-4277
U.S. GEOLOGICAL SURVEY

Water-Resources Investigations Report 01-4277

Flood-Hazard Mapping in Honduras in 

Response to Hurricane Mitch

Prepared in cooperation with

U.S. AGENCY FOR INTERNATIONAL DEVELOPMENT

By Mark C. Mastin

Tacoma, Washington

2002
U.S. DEPARTMENT OF THE INTERIOR

GALE A. NORTON, Secretary

U.S. GEOLOGICAL SURVEY

Charles G. Groat, Director

For additional information write to:

District Chief

U.S. Geological Survey

1201 Pacific Avenue – Suite 600

Tacoma, Washington 98402

http://wa.water.usgs.gov

Copies of this report can be purchased

from:

U.S. Geological Survey

Information Services

Building 810

Box 25286, Federal Center

Denver, CO 80225-0286

Any use of trade, product, or firm names in this publication is for descriptive purposes only and does not imply 

endorsement by the U.S. Government.

District Chief

U.S. Geological Survey

1201 Pacific Avenue – Suite 600

Tacoma, Washington 98402

http://wa.water.usgs.gov
Contents iii

CONTENTS

Abstract ................................................................................................................................................................ 1

Introduction .......................................................................................................................................................... 1

Purpose and Scope ...................................................................................................................................... 3

Description of the Study Area..................................................................................................................... 3

Methods....................................................................................................................................................... 5

Acknowledgments....................................................................................................................................... 7

Regional Hydrology of Honduras ........................................................................................................................ 7

River Discharge........................................................................................................................................... 7

Precipitation ................................................................................................................................................ 9

Data Sources......................................................................................................................................................... 10

Annual Peak Discharge............................................................................................................................... 10

Precipitation ................................................................................................................................................ 12

Topography ................................................................................................................................................. 12

Frequency Analysis of Precipitation and Peak Flows.......................................................................................... 17

Precipitation Frequency .............................................................................................................................. 18

Peak-Flow Frequency at Gaged Sites ......................................................................................................... 18

Peak-Flow Frequency at Ungaged Sites ..................................................................................................... 23

A GIS to Estimate 50-Year Flood Discharges................................................................................... 31

Estimated 50-Year Flood Discharges at Selected Municipalities............................................................... 31

50-Year Flood Discharges Reported by Others .......................................................................................... 31

Flood-Hazard Mapping Method........................................................................................................................... 33

Pre- and Post-Processing GIS Data With HEC-GeoRAS........................................................................... 33

Hydraulic Modeling With HEC-RAS ......................................................................................................... 34

Summary .............................................................................................................................................................. 37

References Cited .................................................................................................................................................. 38
iv Contents

FIGURES

Figure 1. Map showing location of the study area, the general topography, and the three 

geographic regions............................................................................................................................. 4

Figure 2. Map showing flood-hazard areas that were mapped by airborne topographic surveys in 

this study, and extents of drainage basins that contribute streamflow discharge to the 

flood-hazard areas.............................................................................................................................. 6

Figure 3. Map showing the extent of the airborne topographic survey at Santa Rosa de Aguán, 

Honduras, and the area of inundation for the 25-year flood.............................................................. 7

Figure 4. Graphs showing mean monthly streamflow discharge at three streamgaging stations in 

Honduras for their periods of record.................................................................................................. 8

Figure 5. Graph showing average monthly distribution of annual maximum instantaneous 

streamflow discharges (peak flows) for 424 peak flows at 27 streamgaging 

stations in Honduras........................................................................................................................... 9

Figure 6. Map showing locations of streamflow gaging stations with 10 years or more of annual 

peak-flow records, lengths of records, locations of flood-hazard areas that were mapped 

by airborne topographic surveys, and extents of drainage basins that contribute streamflow 

discharge to the flood-hazard areas.................................................................................................... 11

Figure 7. Diagram showing comparison of river cross sections 55 meters downstream of the 

Highway Bridge on Río Humuya in Comayagua, Honduras, using elevations from a 

ground survey and an airborne LIDAR survey.................................................................................. 15

Figure 8. Shaded-relief images of LIDAR-derived digital elevation models with cross-section 

locations for the Tocoa hydraulic model (A) with vegetation, and (B) with vegetation 

removed through filtering .................................................................................................................. 16

Figure 9. Graph showing original and edited cross sections of Río Tocoa at station 2.098.72 of the 

Tocoa hydraulic model, Tocoa, Honduras......................................................................................... 17

Figure 10. Map showing lines of equal 50-year, daily precipitation totals and the locations of 

precipitation stations at which 50-year, daily precipitation totals were estimated ............................ 22

Figure 11. Graph showing comparison of annual peak-flow discharge and annual exceedance 

probability for Choluteca en Puente Choluteca, Honduras, using exceedance

probabilities based on the recorded (unadjusted) record and based on local, historical 

information (adjusted)........................................................................................................................ 28

Figure 12. Graph showing comparison of predicted and observed 50-year peak flows at 34 

streamgaging stations in Honduras .................................................................................................... 30

Figure 13. Map showing shaded-relief image of the Río Tocoa, Honduras, study site based on the 

LIDAR-derived digital elevation model, and the locations of the stream thalweg, river banks, 

approximate centerlines of overbank areas, and cross-sectional lines............................................... 35
Contents v

TABLES

Table 1. Characteristics of 15 municipalities selected to demonstrate the flood-hazards mapping 

methodology developed for Honduras .............................................................................................. 2

Table 2. Maximum 3-day precipitation totals for selected precipitation stations in Honduras 

for several tropical cyclones in recent history .................................................................................. 10

Table 3. Multipliers for the 3-day daily discharge method used to estimate annual maximum 

instantaneous discharge (peak flow) ................................................................................................. 12

Table 4. Comparison of root mean square errors for predicting the annual maximum 

instantaneous discharge (peak flow) at three test sites using the peak-day daily 

discharge linear regression and the 3-day daily discharge methods ................................................. 13

Table 5. Statistical analysis of elevation differences obtained from Global Positioning System 

(GPS) ground surveys and LIDAR airborne surveys ....................................................................... 14

Table 6. Mean, standard deviation, and 50-year return period of annual maximum daily 

precipitation at 39 precipitation stations in Honduras with 15 years or more of record, 

and maximum daily precipitation during Hurricane Mitch .............................................................. 19

Table 7. Streamflow stations in Honduras with 10 years or more of annual peak-flow data 

from 1954 through 1998 and water years for which data are available ............................................ 20

Table 8. Estimated flood discharges, 95-percent confidence intervals, and weighted estimates 

at selected exceedance probabilities for 34 streamflow stations in Honduras and the 

maximum peak recorded at each station ........................................................................................... 24

Table 9. Streamflow stations at which the peak discharge during Hurricane Mitch was estimated 

using indirect measurements near the station and comparisons of different peak flows .................. 27

Table 10. Basin characteristics and 50-year flood discharge at 34 long-term streamflow stations 

in Honduras ....................................................................................................................................... 29

Table 11. Comparisons of 50-year flood discharges estimated by different studies and estimates 

of peak flows during Hurricane Mitch at four municipalities in Honduras ...................................... 32

Table 12. Annual maximum instantaneous streamflow discharge (peak flow) for streamflow 

discharge stations in Honduras with 10 years or more of annual peak-flow records ....................... 41
vi Contents

CONVERSION FACTORS AND VERTICAL DATUM

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=1.8 °C+32

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8

Sea level: In this report, "sea level" refers to the National Geodetic Vertical Datum of 1929 (NGVD

of 1929)--a geodetic datum derived from a general adjustment of the first-order level nets of both the

United States and Canada, formerly called Sea Level Datum of 1929.

Multiply By To obtain

Length

millimeter (mm) 0.03937 inch

meter (m) 3.281 foot 

kilometer (km) 0.6214 mile 

Area

square meter (m2) 10.76 square foot 

square kilometer (km2) 0.3861 square mile

Flow rate

cubic meter per second (m3/s) 70.07 acre-foot per day 
Introduction 1

Flood-Hazard Mapping in Honduras in Response to 

Hurricane Mitch

By Mark C. Mastin

ABSTRACT

The devastation in Honduras due to 

flooding from Hurricane Mitch in 1998 

prompted the U.S. Agency for International 

Development, through the U.S. Geological 

Survey, to develop a country-wide systematic 

approach of flood-hazard mapping and a 

demonstration of the method at selected sites 

as part of a reconstruction effort. The design 

discharge chosen for flood-hazard mapping 

was the flood with an average return interval 

of 50 years, and this selection was based on 

discussions with the U.S. Agency for 

International Development and the Honduran 

Public Works and Transportation Ministry. A 

regression equation for estimating the 50-year 

flood discharge using drainage area and annual 

precipitation as the explanatory variables was 

developed, based on data from 34 long-term 

gaging sites. This equation, which has a 

standard error of prediction of 71.3 percent, 

was used in a geographic information system 

to estimate the 50-year flood discharge at any 

location for any river in the country. The 

flood-hazard mapping method was 

demonstrated at 15 selected municipalities. 

High-resolution digital-elevation models of the 

floodplain were obtained using an airborne 

laser-terrain mapping system. Field 

verification of the digital elevation models 

showed that the digital-elevation models had 

mean absolute errors ranging from -0.57 to 

0.14 meter in the vertical dimension. From 

these models, water-surface elevation cross 

sections were obtained and used in a 

numerical, one-dimensional, steady-flow stepbackwater model to estimate water-surface 

profiles corresponding to the 50-year flood 

discharge. From these water-surface profiles, 

maps of area and depth of inundation were 

created at the 13 of the 15 selected 

municipalities. At La Lima only, the area and 

depth of inundation of the channel capacity in 

the city was mapped. At Santa Rose de 

Aguán, no numerical model was created. The 

50-year flood and the maps of area and depth 

of inundation are based on the estimated 

50-year storm tide.

INTRODUCTION

In late October 1998, Hurricane Mitch, a 

category 5 hurricane, struck Honduras and other 

countries in Central America. Several days of intense 

rain from this tropical cyclone caused devastating 

floods and landslides throughout the affected area. 

In Honduras, 7,000 people died, 33,000 homes and 

95 bridges were destroyed, and 70 percent of the road 

network was damaged. 

In response to this horrific natural disaster, the 

U.S. Agency for International Development (USAID) 

developed a program to aid Central America in 

rebuilding itself. A top priority identified by USAID 

was the need for reliable maps of areas of flood hazard 

in Honduras to help plan the rebuilding of housing and 

infrastructure. USAID requested that the U.S. 

Geological Survey (USGS) develop these maps and 

also document the method used to produce them. It was 

recognized that a systematic method of defining areas 

of flood hazard was required that eventually can be 

applied to the country as a whole. However, to guide 

the rebuilding that is currently underway, rapid 

determination of flood hazard is needed for selected 

municipalities. Therefore, the flood-hazard mapping 

method would be applied in these municipalities first.
2 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

USAID considered 41 municipalities in 

Honduras for hazard mitigation, but not all of them 

sustained flood damage during Hurricane Mitch. After 

visits to a number of the municipalities, 15 of the 41 

were selected as most in need of flood hazard mapping: 

Catacamas, Choloma, Choluteca, Comayagua, El 

Progreso, Juticalpa, La Ceiba, La Lima, Nacaome, 

Olanchito, Santa Rose de Aguán, Siquatepeque, 

Sonaguera, Tegucigalpa, and Tocoa (table 1).

The flood design criterion selected for the 

program’s flood mapping effort was the 50-year flood 

recurrence interval, or 50-year flood discharge—the 

discharge that is equaled or exceeded on average once 

every 50 years and has a 2-percent probability of 

occurring in any one year. This selection was based on 

discussions with staff of USAID and the Honduran 

Public Works and Transportation Ministry. The 

50-year flood discharge is the most common discharge 

used for flood-design purposes by domestic and foreign 

agencies working on the recovery effort in Honduras 

(Jeff V. Phillips, U.S. Geological Survey, written 

commun., 2001).

Table 1. Characteristics of 15 municipalities selected to demonstrate the flood-hazards 

mapping methodology developed for Honduras

Municipality River

Area of

topographic 

survey

(square

kilometers)

Area of

contributing

drainage

(square

kilometers)

1 Catacamas Catacamas 8.4 45.4

2 Choloma Choloma 7.2 89.5

3 Choluteca Choluteca, Iztoca 37.1 7,080

4 Comayagua Humuya 20.9 1,542

5 El Progreso Pelo 14.7 47.4

6 Juticalpa Juticalpa 6.4 431

7 La Ceiba Cangrejal 10.9 498

8 La Lima Chamelecón 33.6 3,757 

9 Nacaome Nacaome, Guacirope, 

Grande

10.4 2,478

10 Olanchito Uchapa 5.2 97.1 

11 Santa Rosa de Aguán Aguán 6.4 10,579

12 Siguatepeque Selguapa, Celán, Guique, 

Chalantuma, Calán

12.1 139

13 Sonaguera Sonaguera 4.9 72.7

14 Tegucigalpa Choluteca, Guacerique, 

Chiquito, Grande

54.2 804

15 Tocoa Tocoa 7.4 204
Introduction 3

The methodology for determining and mapping 

flood-hazard areas in Honduras involved three steps. 

(1) A regional regression equation was developed to 

estimate the 50-year flood discharge in a river as a 

function of drainage area and annual precipitation in 

the basin, and a geographic information system (GIS) 

was used to estimate the 50-year flood discharge for 

any location on the river. (2) An airborne laser terrainmapping system was used to obtain high-resolution 

digital-elevation models (DEMs) of the river 

floodplain, from which elevation cross sections were 

determined along the river profile. The cross-section 

data were applied in a numerical, one-dimensional, 

steady-flow step-backwater model to estimate the 

corresponding water-surface profile of the 50-year 

flood discharge. (3) The water-surface profiles and 

floodplain DEMs were used in a GIS to produce maps 

of the area and depth of inundation of the 50-year flood 

for that area.

Purpose and Scope

The purpose of this report is to describe the 

methodology developed to estimate the 50-year flood 

discharge for areas throughout Honduras and map the 

extent and depth of flooding. The report (1) provides 

regional data to facilitate flood-hazard mapping in 

Honduras, (2) documents the development of regional 

relations for estimating the 50-year flood discharges for 

rivers throughout Honduras, and (3) describes the 

methodology used to create flood-hazard maps for 15 

municipalities in Honduras, which are considered most 

in need of flood-hazard mapping. 

Flood-hazard maps for the municipalities, along 

with graphs of water-level profiles, are published in 

15 separate reports that refer to this report for 

documentation of the flood-hazard mapping methods 

that were used.

Data presented in this report, collected or 

assembled to produce flood maps for the 15 

municipalities, include available annual peak flows for 

the rivers of Honduras, an annual precipitation map for 

Honduras, and topography. Specifically, data presented 

in this report include estimated annual maximum daily 

precipitation with a 50-year return period and flood 

discharges for the streamflow gages with 2-, 10-, 25-, 

50-, and 100-year return periods.

Description of the Study Area

The study area is located in Honduras, a country 

in Central America bordered by the Caribbean Sea in 

the north, Nicaragua on the east and south, the Pacific 

Ocean (Gulf of Fonseca) and El Salvador on the south, 

and Guatemala on the west (fig. 1). It covers about 

112,100 square kilometers (km2) and is slightly larger 

than the State of Tennessee in the United States. The 

country is largely mountainous with narrow coastal 

lowlands in the north and south. More extensive 

coastal lowlands are present in the northeast. Altitudes 

range from sea level near the Caribbean and Pacific 

coasts to 2,849 meters above sea level at Cerro Las 

Minas in the southwest.

Honduras is incised by rivers that flow from the 

interior of the country to the Caribbean Sea in the north 

and the Pacific Ocean in the south. The rivers flow 

year-round and are fed by springs, distributed groundwater discharge, and surface runoff after storms. 

The climate in Honduras ranges from subtropical 

in the lowlands to temperate in the mountains. The 

mean annual precipitation ranges from less than 

800 millimeters per year (mm/yr) in parts of the 

interior to more than 3,400 mm/yr along the 

northeastern coast (Modesto Canales, 1998). In 

general, precipitation is greater along the coasts than in 

the central interior, and precipitation along the north 

coast is greater than along the south coast. The rainy 

season usually lasts from May through October and the 

dry season from November through April. During the 

rainy season, Honduras is subject to tropical cyclones, 

which may range in strength from tropical depressions 

(sustained surface winds of less than 17 meters per 

second - m/s), to tropical storms (sustained surface 

winds from 17 m/s to 33 m/s), to hurricanes (sustained 

surface winds greater than or equal to 33 m/s) 

(Landsea, 1996). The mean annual temperature is 

about 21 degrees Celsius (°C) in the interior of 

Honduras and 27°C in low-lying coastal regions (U.S. 

Department of State, 2001).

In 1993, approximately 54 percent of the study 

area was covered by forests and woodland, 18 percent 

by crops, and 14 percent by pastures (Central 

Intelligence Agency, 2001). The remaining 14 percent 

includes land use not already listed, such as bare rock, 

roads, and urban areas. In July 2000, the population of 

Honduras was estimated to be about 6.4 million, with a 

population growth rate estimated to be 2.43 percent in 

2001 (Central Intelligence Agency, 2001). 
4

Flood-HazardMappinginHondurasinResponsetoHurricaneMitch

Tegucigalpa

San Pedro 

Sula

X

NICARAGUA

 

 

CARIBBEAN SEA

NICARAGU E A L SALVADOR

Gulf of Honduras

Gulf of Fonseca

Cerro Las Minas

GUATEMALA

PACIFIC OCEAN

BELIZE

GUATEMALA

EL

SALVADOR

HONDURAS

NICARAGUA

HONDURAS

PACIFIC LOWLANDS

CARIBBEAN LOWLANDS

INTERIOR HIGHLANDS

Figure 1. Location of the study area, the general topography, and the three geographic regions.(Modified from Modesto Canales, 1998.)
Introduction 5

The population density is generally greatest in western 

Honduras, where the capital Tegucigalpa is the largest 

city and San Pedro Sula the second largest city (fig. 1).

Methods

Flood-hazard maps for individual municipalities 

were developed by (1) estimating the 50-year flood 

discharge for each major river in the selected 

municipality, (2) constructing a hydraulic model of the 

river reaches within the municipality based on cross 

sections from topographic information, and (3) plotting 

water-level profiles, simulated with the hydraulic 

model, and area- and depth-of-inundation maps over 

topographic maps. 

At municipalities where long-term records exist 

from nearby streamgaging stations, the 50-year flood 

discharge is estimated from the streamflow record 

using statistical procedures established for the United 

States (U.S. Water Resources Council, 1981). At 

municipalities with no long-term streamflow records, 

the 50-year flood discharge was estimated on the basis 

of a regression equation developed for the entire 

country by analysis of all the available long-term, 

annual peak-discharge records for Honduras and 

drainage basin characteristics. 

A GIS program, HEC-GeoRAS (U.S. Army 

Corps of Engineers, 2000), was used to create cross 

sections of floodplain elevations from a DEM of the 

selected municipality acquired from a high-resolution, 

airborne laser terrain-mapping system survey 

conducted as part of this project. A hydraulic model 

embedded in the HEC-RAS software program (U.S. 

Army Corps of Engineers, 1998a,b) performed the 

hydraulic calculations to estimate water levels at the 

cross-section locations. HEC-GeoRAS was used again 

to process the hydraulic model results to create maps of 

the areas and depths of inundation for the 

municipalities. 

The high cost of the airborne topographic 

surveys limited the study to flood-prone areas with a 

high population and(or) densely spaced structures. The 

surveyed areas were generally adjacent to river reaches 

within or near cities. Many of the municipalities that 

were visited were subjected to local flooding of small 

creeks or failed and(or) undersized drainage networks 

during Hurricane Mitch. This localized flooding was 

outside the scope of the project. The extents of the 

study areas at the select municipality were defined by 

the extents of the airborne topographic surveys and 

varied in size from 4.9 square kilometers (km2) at 

Sonaguera to 54.2 km2 at Tegucigalpa (fig. 2 and 

table 1). The contributing drainage basins to the 

downstream end of the study areas vary from 45.4 km2

at Catacamas to 10,579 km2 at Santa Rosa de Aguán. 

The area of the topographic survey at 

Tegucigalpa extended away from the river into the 

foothills because data from the survey also were used 

for a concurrent landslide study. 

It was discovered after conducting the airborne 

topographic surveys that the surveyed areas in the 

municipalities of Santa Rosa de Aguán and La Lima 

did not include the entire areas that would be inundated 

by a 50-year flood. A map of the 25-year flood 

inundation for Santa Rosa de Aguán by Sir William 

Halcrow and Partners (1985) shows that even the area 

of inundation for the 25-year flood is not entirely 

covered by the topographic survey (fig. 3). The area of 

possible inundation is large because Río Aguán and the 

city of Santa Rosa de Aguán are located on a relatively 

flat delta. The river dramatically changed its course 

between site visits in April 2000 and January 2001 and 

built up a large sand bar at its mouth where it flows into 

the Caribbean Sea. Because of the unstable channel 

conditions and limited topographic coverage, no stepbackwater hydraulic model was constructed for Santa 

Rosa de Aguán as was done for the other 

municipalities. The area- and depth-of-inundation 

maps in the site report for Santa Rosa de Aguán are 

based on the elevation of the estimated 50-year storm 

tide.

For La Lima, the site report describes the 

maximum streamflow discharge that the main channel 

can convey without overtopping levees and natural 

river banks in the city, as computed from trial-and-error 

model simulations. However, the report does not 

include a map of the extent of inundation for the 

50-year flood. 
6

Flood-HazardMappinginHondurasinResponsetoHurricaneMitch

0 20 40 60 0 20 40 60 80 100 KIL

16°15°14°13°

90° 89° 88° 87° 86° 85° 84°

HONDURAS

Choluteca

Nacaome

Tegucigalpa

Comayagua

Siguatepeque

La Lima El Progreso

Choloma

La Cieba

Tocoa

Santa Rosade Aguan

Sonaguera

Olanchito

Juticalpa

Catacamas

Rio Choluteca

Pacific Ocean

Caribbean Sea

EL SALVADOR

NICARAGUA

GUATEMALA

Rio Ulua

Rio Aguan

EXPLANATION

Gulf of Honduras

Gulf of Fonseca

EXTENT OF TOPOGRAPHIC SURVEYCONTRIBUTING DRAINAGE BASIN

Digital base from U.S. Geological Survey and ESRIDigital Atlas of Central America, January, 1999Drainage basins from the National Imagery and Mapping Agency93-meter cell resolution Digital Terrain Elevation data, Level 1

Figure 2. Flood-hazard areas that were mapped by airborne topographic surveys in this study, and extents of drainage basinstreamflow discharge to the flood-hazard areas.
Regional Hydrology of Honduras 7

Acknowledgments

The author acknowledges the support of Mr. 

Jeff V. Phillips, U.S. Geological Survey, and the staff of 

USAID in Honduras for providing the primary data 

upon which this report is based. I also thank Sr. 

Humberto Calderón of the Comisión Ejecutiva Valle 

del Sula (CEVS) for information and insights into the 

hydrology of the Sula Valley, and the leaders and staff 

of the municipalities for cordially providing us with 

information about their towns and giving us guided 

tours of nearby rivers.

REGIONAL HYDROLOGY OF HONDURAS

River Discharge

The seasonal pattern in river discharge is seen in 

graphs of mean monthly discharge for representative 

rivers from the three geographic regions of Honduras: 

Río Aguán in the Caribbean Lowlands in the north, Río 

Humuya in the Interior Highlands, and Río Choluteca 

in the Pacific Lowlands in the south (figs. 1, 4). 

Tocoa

Trujillo

Limon

Santa Rosa

de Aguan

Bonito Oriental

Rio

Aguan

Trujillo Bay

Caribbean Sea

E 610,000 E 620,000 E 630,000 E 640,000 E 650,000 E 660,000

N 1,760,000

N 1,750,000

N 1,740,000

N 1,730,000

0 1 2 3 4 5 6 MILES

0 1 2 3 4 5 6 KILOMETERS Base map digitized and modified from figure H.4.1, Sir William Halcrow 

and Partners,1985, Hydraulic Master Plan for the Aguan River Basin, 

Final Report, volume 4

EXPLANATION

EXTENT OF TOPOGRAPHIC SURVEY

AREA OF INUNDATION, 25-YEAR FLOOD

ROADS

Figure 3. The extent of the airborne topographic survey at Santa Rosa de Aguán, Honduras, and the area of inundation 

for the 25-year flood.

From Sir William Halcrow and Partners, 1985.
8 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

0

20

40

60

80

100

120

140

160

0

5

10

15

20

25

30

0

5

10

15

20

25

30

Aguan en Sabana Larga,

Latitude: 15°23'48", Longitude: 89°59'23"

Elevation: 350 meters

Period of record: August 1, 1972 - April 31, 1996 

Humuya en Las Higueras,

Latitude: 14°20'06", Longitude: 87°38'04"

Elevation: 580 meters

Period of record: May 1, 1966 - April 30, 1988 

Choluteca en Puente Choluteca

Latitude: 13°18'35", Longitude: 87°11'30"

Elevation: 27 meters

Period of record: May 1, 1979 - April 30, 1997 

JAN FEB MAR APR MAY JUNE JUL AUG SEPT OCT NOV DEC

JAN FEB MAR APR MAY JUNE JUL AUG SEPT OCT NOV DEC

JAN FEB MAR APR MAY JUNE JUL AUG SEPT OCT NOV DEC

Figure 4. Mean monthly streamflow discharge at three streamgaging stations in Honduras for their 

periods of record.
Regional Hydrology of Honduras 9

An analysis of the dates for 424 annual peaks for 

27 stations located throughout the country shows a 

similar seasonal pattern. About two-thirds of the peaks 

occur in the months of August through October (fig. 5)

Precipitation

The largest annual peak flows are usually 

associated with tropical cyclones. Topical cyclone is a 

general term for any weather system over tropical 

waters, with subcategories of tropical depressions 

(sustained winds of less than 17 m/s), tropical storms 

(sustained winds of 17 m/s to 33 m/s) and hurricanes 

(sustained winds of 33 m/s or greater). During 

Hurricane Mitch in October 1998, precipitation in 

some areas of Honduras exceed 450 millimeters (mm) 

in 24 hours and more than 800 mm in 3 days. This 

caused record peak flows in many rivers. 

Although Hurricane Mitch is listed as the most 

deadly hurricane in the Western Hemisphere since the 

“Great Hurricane” of 1780, other destructive tropical 

cyclones have hit Honduras in recent history. For 

example, Hurricane Fifi hit Honduras in 

September 1974 and caused 8,000 deaths, and tropical 

storm Gert hit in September 1993 and caused 76 deaths 

(Rappaport and Fernández-Partagas, 1995). The 

Hurricane Research Division of the National Oceanic 

and Atmospheric Administration (NOAA) has 

produced a map showing that in any year, there is a 10- 

to 40-percent chance that a tropical storm or hurricane 

will hit within 165 km of Honduras from June to 

November (chances are greatest near the north coast of 

Honduras), and a 1- to 2-percent chance that the north 

coast will be hit by a major (category 3-5) hurricane 

(Kimberlain, 2001a, 2001b).

Although the largest recorded precipitation and 

associated flooding are caused by tropical cyclones, the 

intensity of precipitation during individual storms 

varies throughout the country (table 2). Generally, 

Hurricane Mitch generated the largest 3-day 

precipitation totals for the stations that were compared 

and it also seemed to generate the most widespread 

precipitation. Whereas the Sula Valley, represented by 

the La Mesa station, seems to be vulnerable to all the 

tropical cyclones that were considered, precipitation at 

some of the inland stations, such as Catacamas and 

Santa Rosa, seem little affected.

0

5

10

15

20

25

30

35

40

JAN FEB MAR APR MAY JUNE JUL AUG SEPT OCT NOV DEC

PERCENTAGE OF TOTAL

Figure 5. Average monthly distribution of annual maximum instantaneous streamflow discharges 

(peak flows) for 424 peak flows at 27 streamgaging stations in Honduras.

Data are from the Secretaría de Recursos Naturales y Ambiente, Dirección General de Recursos 

Hídricos, Departamento de Servicios Hidrológicos y Climatológicos.
10 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

DATA SOURCES

The analyses in this report relied on three types 

of data: annual peak flow, annual precipitation totals, 

and topography. This section describes the sources of 

the data and, for the topographic data, estimates of data 

accuracy. Annual peak flows and annual precipitation 

totals were obtained from published data or estimated 

from published data, and the accuracies are mostly 

unknown. The topographic information that was 

acquired under contract specifically for this project was 

field verified in selected locations to assess the data 

accuracy.

The analyses in this report utilized all streamflow 

discharge and precipitation data that were available to 

the author. Most of the data came from a compact disc 

with precipitation and hydrologic data from the 

Servicio Autónomo Nacional de Acueductos y 

Alcantarillados (SANAA), the Secretaría de Recursos 

Naturales (SERNA), Servicio Meteorolópgico 

Nacional (SMN), and the CEVS. These data were 

assembled by Jeff V. Phillips of the USGS while 

working in Honduras at the USAID office in 

Tegucigalpa. Additional peak-flow data came from a 

flood-protection feasibility study on Río Chamelecón 

conducted by Consorcio Lahmeyer International 

(1998) for CEVS. This study was provided by Sr. 

Humberto Calderón. 

Annual Peak Discharge

Annual maximum instantaneous discharges 

(henceforth referred to as peak flows in this report), 

shown in table 12 at the end of the report, were taken 

from records provided by SERNA and from a floodprotection feasibility study on Río Chamelecón 

(Consorcio Lahmeyer International, 1998). Only 

streamflow stations with 10 years or more of annual 

peak-flow data were used in the analyses for this report 

(fig. 6). A total of 34 stations were used, with a total of 

annual 833 peak-flow values. A water year, as defined 

in this report and by SERNA, is defined as being from 

May through April. For example, the 1990 water year 

begins May 1, 1990, and ends April 30, 1991. 

Annual peak-flow data from SERNA were 

obtained from tables of daily discharges that also 

included the monthly and annual peak flows. In some 

cases, however, either the exact date or month of the 

annual peak-flow value was missing or the value was 

actually the maximum daily mean flow for the year. 

Table 2. Maximum 3-day precipitation totals for selected precipitation stations in Honduras for several tropical cyclones in recent 

history

Precipitation stations 3-day precipitation (millimeters)

Name

Latitude

(North)

Longitude

(West)

Hurricane Fifi

Sept. 17–20,

1974

Tropical

Depression

Nov. 28–30,

1990

Tropical 

Storm

Gert

Sept. 16–17,

1993

Tropical

Depression

Nov. 17–19,

1996

Hurricane 

Mitch

Oct. 26–31,

1998

Catacamas 14o50’22" 85o52’32” 74.4 35.7 35.8 13.1 204.2

Choluteca 13o24’29" 87o09’32” 249.5 2.6 269.4 217.5 830.6

La Esperanza 14o17’28" 88o10’20” no data 16.6 42.0 6.9 115

La Mesa 15o26’46" 87o56’18” 383.1 114.1 240.8 74.2 232.2

Puerto Lempira 15o12’30" 83o48’00” 66.0 77.5 53.6 24.6 130.4

Quimistán 15o20’34" 88o24’25” 172.2 172.4 106.9 207.2 no data

Santa Rosa 14o47’30" 88o48’00” 83.7 0.0 81.3 59.3 56.1

Tegucigalpa 14o03’31" 87o13’10” 97.1 3.3 52 4.3 254.1

Tela 15o46’28" 87o31’36” 345.6 75.2 254.8 208 350.4
Data Sources 11

16°15°14°13°

90° 89° 88° 87° 86° 85° 84°

0 20 40 60 0 20 40 60 80 100 K

HONDURAS

Pacific Ocean

Caribbean Sea

EL SALVADOR

NICARAGUA

GUATEMALA

Gulf of Honduras

Gulf of Fonseca

Digital base from U.S. Geological Survey and ESRIDigital Atlas of Central America, January, 1999Drainage basins from the National Imagery and Mapping Agency93-meter cell resolution Digital Terrain Elevation data, Level 1Long-term streamflow gaging station data from Secretaria de Recursos Naturales, Honduras

EXTENT OF TOPOGRAPHIC SURVEYCONTRIBUTING DRAINAGE BASINLONG-TERM STREAMFLOW GAGING STATIO

Number in upper left is the identification number 

 shown in Table 10. Number in the lower right is the  number of years of annual peak-flow record at the sit

EXPLANATION

27

21 19 25

25

14

17

27

28

28

28 38 37

34

33

33

30

30

21

24

21

11

11

10

13 16

16

15

35

36

27

27

16

24

24

4

7

6

8 9

3

2

2

22

21

24

17

11

12

18 14

13

19

10

15

26

23

25

16

27 29

5

20

34

1

32

33 31

30

28

Figure 6. Locations of streamflow gaging stations with 10 years or more of annual peak-flow records, lengths of records, lochazard areas that were mapped by airborne topographic surveys, and extents of drainage basins that contribute streamflow dis

flood-hazard areas.
12 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

In a case where the instantaneous peak discharge was 

unknown, but the daily discharge during the peak was 

known (33 cases), the peak discharge was estimated 

using a 3-day daily discharge method established by a 

USGS Division of Water Utilization report 

(information provided by J.J. Vaccaro, U.S. Geological 

Survey, written commun., 2000; other publication 

information is unknown). This method uses the daily 

mean discharge on the days before, on, and after the 

peak discharge occurred to estimate the instantaneous 

peak discharge. A table of multipliers used to estimate 

the peak discharge by this method is given in table 3. 

The 3-day daily discharge method was tested with data 

from two Honduran sites and one site in Washington 

State (USA) by comparing its results with results of a 

linear regression relation between the peak discharge 

and the daily mean discharge on the peak date (table 4). 

The 3-day daily discharge method works about as well 

as the linear regression method and is easier to apply, 

so it was selected to fill in missing peak-flow data.

Precipitation

Station precipitation data were provided on the 

compact disc mentioned at the beginning of this 

section. Most of the station data contained daily or 

monthly precipitation totals, and only limited data that 

were sampled more frequently. Thirty-four stations in 

Honduras with more than 15 years of maximum daily 

precipitation records were available for analysis.

Topography

An airborne Light Detection and Ranging 

(LIDAR) system, also known as an Airborne Laser 

Terrain Mapping (ALTM) system, was used to acquire 

high-resolution elevation data at the 15 municipalities 

selected for flood-hazard mapping. This work was 

done by the Bureau of Economic Geology, Coastal 

Studies, at the University of Texas (UT). 

Table 3. Multipliers for the 3-day daily discharge method used to estimate annual maximum instantaneous 

discharge (peak flow)

[To estimate the instantaneous peak discharge, multiply the daily mean discharge on the maximum day (defined as the day that the maximum daily discharge occurred) by the appropriate value from the matrix below. In this study, linear interpolation between the listed ratios 

was used to estimate the multiplier.]

Ratio of succeeding day to maximum day

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Ratio of preceding day to maximum day

0.0 2.50 2.50 2.50 2.40 2.30 2.20 2.10 2.10 2.00 2.00

0.1 2.50 2.43 2.03 1.88 1.79 1.72 1.68 1.65 1.62 1.62

0.2 2.50 2.12 1.77 1.62 1.53 1.48 1.46 1.45 1.44 1.43

0.3 2.50 2.00 1.64 1.45 1.36 1.33 1.32 1.31 1.31 1.31

0.4 2.50 2.00 1.55 1.36 1.25 1.19 1.19 1.20 1.21 1.23

0.5 2.50 2.04 1.53 1.33 1.21 1.16 1.14 1.15 1.16 1.17

0.6 2.50 2.12 1.59 1.34 1.21 1.14 1.09 1.09 1.11 1.12

0.7 2.50 2.25 1.69 1.38 1.24 1.15 1.07 1.05 1.05 1.05

0.8 2.50 2.47 1.81 1.46 1.29 1.18 1.08 1.03 1.02 1.02

0.9 2.50 2.50 1.95 1.54 1.38 1.23 1.10 1.02 1.01 1.00

1.0 2.50 2.50 2.50 1.80 1.49 1.30 1.15 1.01 1.00 1.00
Data Sources 13

They used an Optech ALTM 1225 module mounted in 

a fixed-winged airplane and flown over the selected 

municipality during February and March 2000. Data 

were first acquired along densely spaced parallel flight 

paths and then again along flight paths orthogonal to 

the original flight paths. Reported vertical accuracy is 

0.15 meter at a 1,200-meter operating altitude. Precise 

global positioning systems (GPS) operated on the 

aircraft during LIDAR operation and on the ground at 

survey control benchmarks. Final Digital Elevation 

Models (DEM) derived from the irregularly positioned 

LIDAR data were resampled to a regular grid with a 

cell (horizontal) resolution of 1.5 meters in a Arc/Info 

Grid format using TopoGrid software, and then 

converted to a Triangular Irregular Network (TIN) 

format, the format needed for input to the Geographic 

Information System (GIS) software program used to 

pre- and post-process the hydraulic model input and 

output.

The data accuracy of the LIDAR was assessed 

with two sets of independent field surveys. One set 

was conducted by the University of Texas personnel in 

February and March of 2000 with a survey-grade GPS 

collecting point data on ground-control features such as 

roads, soccer fields, bridges, and buildings. The other 

set of surveys was made by USGS personnel during 

field surveys of the bridges with a total station tied into 

benchmarks. The benchmarks were established by UT 

personnel. Results of the point surveys by University 

of Texas personnel shows vertical errors as high as 

0.78 meter, but the standard deviation of errors are 

within 0.12 meter for all the sites (table 5). In many of 

the comparisons (11 of 17), the mean absolute error is 

greater than the reported accuracy of 0.15 meter. To 

assess horizontal accuracies, GPS ground points on 

ground-control features were overlaid on a 1- to 

2-square kilometer LIDAR-derived DEM with a 

1-meter cell resolution at each of the selected 

municipalities. UT compared the positions of groundcontrol features with the DEM for any discrepancies in 

horizontal positions. In all the LIDAR surveys, 

horizontal agreement between the GPS-derived points 

and the LIDAR data was within the 1-meter cell 

resolution of the DEM.

An example comparison of the field-surveyed 

cross section (fig. 7) shows reasonably close agreement 

between LIDAR-derived data and the field survey data 

above the water surface. LIDAR does not penetrate the 

water surface; therefore, the LIDAR-derived data do 

not compare well with the field data below the water 

surface. The LIDAR was conducted during the lowflow portion of the water year when the area of the 

underwater portion of the cross section was small 

compared to the area of wetted cross section during 

peak flows. 

Table 4. Comparison of root mean square errors for predicting the annual 

maximum instantaneous discharge (peak flow) at three test sites using the peakday daily discharge linear regression and the 3-day daily discharge methods

[RMSE = root mean square error = , 

where Ei is the estimated value of peak i; Oi is the observed value of peak i; and n is the total number of 

peaks.]

RMSE for indicated method

Streamflow station

Number

of peaks

in the

analysis

Linear

regression

method

3-day

daily

discharge

method

Juticalpa en El Torito, Honduras 14 41.0 46.1

Chamelecón en La Vegona, Honduras 19 46.0 54.5

South Prairie Creek at South Prairie, 

Washington, USA

32 607.0 613.8

Ei Oi ( ) –

n ---------------------2

i = 1

n

∑
14 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

The comparison also shows that there is some error in 

the conversion of the LIDAR data from the Arc/Info 

grid format to the TIN, as much as 0.47 meter. During 

the conversion from the grid format to the TIN a 

z_tolerance of 1.0 was used. The z_tolerance is a 

measure of how well the TIN surface follows the 

original grid. It sets the maximum allowable vertical 

error between the grid and the TIN (Environmental 

Systems Research Incorporated, 2000). Using smaller 

z_tolerance values resulted in large TIN files and long 

computation times to produce the TIN. In the example 

cross section (fig. 7), the area and hydraulic radius 

(cross section area divided by wetted perimeter) below 

an arbitrary elevation of 557.0 m for the two LIDARderived cross sections can be compared with the fieldsurveyed cross section with a cross section area of 

209.5 m2 and a hydraulic radius of 3.16 m. The actual 

50-year flood elevation is about 599.8 m at this site, 

which inundates an area beyond the area of the field 

survey. The area is 192.8 m2 for the cross section 

derived from the Arc/Info Grid DEM, or 92.0 percent 

of the field-surveyed cross sectional area, and the 

hydraulic radius is 2.99 m. The area is 183.0 m2 for the 

cross section derived from the TIN DEM, or 

87.4 percent of the field-surveyed cross sectional area, 

and the hydraulic radius is 2.95 m.

Input to step-backwater, hydraulic models is 

usually land-surface or river-bottom elevation, ignoring 

the vegetation but including permanent structures. 

(Vegetation effects on water-surface profiles are 

accounted for by roughness coefficients). Although the 

laser pulses from the LIDAR instrument reflect from 

the first object they hit, such as tree tops, some pulses 

will hit the ground surface if it is not completely 

obscured by vegetation. Optech proprietary software 

allows the user to filter data and remove data points 

believed to represent vegetation, creating a bare-earth 

representation of the topography. 

Table 5. Statistical analysis of elevation differences obtained from Global Positioning System (GPS) ground 

surveys and LIDAR airborne surveys

Municipality

Mean

elevation

difference

(meters,

ground - 

LIDAR)

Standard

deviation of

elevation

differences

(meters)

Range of

elevation

differences

(meters) Ground feature

Number

of

elevation

differences

Tegucigalpa -0.134 0.097 0.10 to 0.45 Building roof 89

Tegucigalpa -0.152 0.071 0.03 to -0.30 Soccer field 142 

Choluteca -0.195 0.097 0.07 to -0.48 Bridge 862

Choluteca -0.222 0.090 0.12 to -0.47 Bridge 742

Nacaome -0.573 0.068 -0.39 to -0.78 Unpaved bridge 312

El Progreso 0.100 0.112 0.42 to -0.26 Highway 539

La Lima -0.125 0.092 0.24 to -0.35 Airport road 1,185

Catacamas -0.356 0.110 -0.16 to -0.53 Low-water crossing 21

Choloma -0.103 0.076 0.19 to -0.35 Highway 647

Juticalpa -0.169 0.088 0.03 to -0.51 Soccer field 417

La Ceiba -0.302 0.077 -0.06 to -0.51 Wooden pier 245

Olanchito -0.318 0.098 -0.03 to -0.67 Unpaved road 1,708

Olanchito -0.304 0.066 -0.14 to -0.50 Soccer field 903

Comayagua 0.143 0.089 0.50 to -0.10 Unpaved road 1,091

Siguatepeque -0.154 0.098 0.13 to -0.45 Soccer field 1,252

Sonaguera 0.029 0.110 0.35 to -0.32 Unpaved road 1,285

Tocoa -0.182 0.093 0.09 to -0.47 Unpaved levee 341

Santa Rosa de Aguán 0.092 0.068 -0.07 to 0.26 House foundations 25
Data Sources 15

The UT contractors made several iterations of filtering 

the data with different sets of parameters to maximize 

the vegetation removal while at the same time 

minimizing the building removal. 

For the most part, the vegetation-removal 

process worked well; however, the process was not 

perfect, and sometimes some manual editing of crosssection data was required. An example from a cross 

section on the Tocoa floodplain shows some errors in 

the vegetation-removal process that were corrected 

manually after the cross-section data were processed 

for the hydraulic model. The vegetation-removal 

algorithm removed the dense natural vegetation 

efficiently, but failed to completely remove the trees in 

the regular patterned orange grove (fig. 8). This 

resulted in a cross section with many large "peaks" in 

the overbank area, not accurately representing the bare 

ground surface. 

The Tocoa example also shows a unique study 

site where the underwater portion of the cross section 

was field surveyed downstream of the highway bridge. 

These data were used to estimate the underwater 

portion of all cross sections in the Tocoa study area. 

The channel at the highway bridge in Tocoa was filled 

with sediment during the Hurricane Mitch flood, and it 

is a major constriction that influences the water-surface 

elevations upstream of the bridge. The cross section 

was field surveyed and included the underwater 

portion. The data were added to the hydraulic model 

along with the LIDAR-derived cross sections. The 

resulting profile of the channel thalweg showed a 

prominent downward dip at the bridge site where the 

underwater portion of the cross section was included. It 

was felt that the underwater portion was needed 

throughout the Tocoa reach study in order to make a 

more realistic profile of the channel bottom, especially 

in the vicinity of the bridge. The field-surveyed 

underwater portion of the channel 36.5 meters 

downstream of the bridge was 19.7 m2, which was used 

as representative of the underwater portion for all the 

cross sections on the main river in the Tocoa model. 

The cross-section area and shape of the underwater 

portion was held constant and fitted into the other cross 

sections at what was determined to be the edges of 

water in the main channel from the LIDAR-derived 

cross section (fig. 9).

551

552

553

554

555

556

557

558

559

560

STATIONING FROM LEFT BANK, IN METERS

LIDAR-derived cross section at 2-meter intervals

 (Arc/Info Grid DEM)

LIDAR-derived cross section at 2-meter intervals

 (TIN DEM)

Field-surveyed cross section

Arbitrary elevation

for area computation

Water surface at 

time of field survey

Left 

bank

ELEVATION, IN METERS

0 10 20 30 40 50 60 70 80

Figure 7. Comparison of river cross sections 55 meters downstream of the Highway Bridge on Río Humuya in 

Comayagua, Honduras, using elevations from a ground survey and an airborne LIDAR survey.

LIDAR survey results are shown in Arc/Info GRID and TIN formats.
16 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

B

A

Cross Section 2098.72

Cross Section 2098.72

Figure 8. Shaded-relief images of LIDAR-derived digital elevation models with cross-section 

locations for the Tocoa hydraulic model (A) with vegetation, and (B) with vegetation removed 

through filtering.

Note that filtering removed randomly distributed natural vegetation (left side of images) but not 

regularly spaced trees in orange groves (top center of images).
Frequency Analysis of Precipitation and Peak Flows 17

FREQUENCY ANALYSIS OF 

PRECIPITATION AND PEAK FLOWS

Design discharge is one of the major inputs to 

the hydraulic model that is used to estimate watersurface profiles, and hence, the boundaries of a flood 

inundation map. If there is a long-term streamflow 

station within the stream reach of interest, the gage data 

can be analyzed to estimate a design discharge of a 

specified average recurrence interval or exceedance 

probability (in this study, a 50-year recurrence interval, 

or a 2-percent probability of occurrence per year). In 

most cases, a gage does not exist at the stream reach of 

interest and other methods must be employed to 

estimate the discharge. 

In this study, where long-term station data were 

not available for a study site, the method used and 

described in this chapter was a regional regression 

equation developed using basin characteristics and 

computed discharges with a 50-year recurrence interval 

at 34 long-term streamflow gages in Honduras. The 

basin characteristics that were investigated include the 

contributing drainage area, stream length, stream slope, 

basin average annual precipitation, percentage of the 

basin as forest, and maximum daily precipitation with a 

50-year return interval. Contributing drainage area and 

basin average annual precipitation proved to be the 

most significant variables in the regression equation 

and only those characteristics were used to estimate the 

50-year flood discharge.

One approach used to determine a design 

discharge on an ungaged basin is to develop a design 

storm and the unit-hydrograph method or other more 

complex precipitation-runoff model to estimate the 

discharge. This approach was not used in the estimate 

of discharges for the 15 selected municipalities. The 

approach may be appropriate on smaller basins (basins 

less than 100 km2 or about the smallest basin used in 

the regression analysis) for a quick, reasonably 

accurate peak-flow estimation. Results from the 

precipitation frequency analysis described in this 

chapter may be useful to engineers when applying the 

unit-hydrograph approach. The results were also used 

as one of the basin characteristics in the regression 

equation to estimate the 50-year flood discharge.

37

38

39

40

41

42

43

44

0 100 200 300 400 500 600

STATIONING, IN METERS

ELEVATION, IN METERS

Final, edited data used in hydraulic model

Original LIDAR-derived data removed 

from final cross section

Rio Tocoa 

main channel 

Left overbank

Figure 9. Original and edited cross sections of Río Tocoa at station 2.098.72 of the Tocoa hydraulic model, Tocoa, 

Honduras.
18 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

Precipitation Frequency

Annual maximum daily precipitation data from 

39 stations in Honduras with 15 years or more of 

record were available for the analysis. Although hourly 

precipitation data would have been preferred, little 

were available. The analysis was limited to 

determining the maximum daily precipitation totals for 

an average return interval of 50 years (0.02 exceedance 

probability). The frequency distribution used for this 

calculation was an extreme value Type I distribution 

(Linsley and others, 1982) given by:

, (1)

where in this study

The estimated daily precipitations with a 50-year 

return period (daily, 50-year totals) ranged from 94 mm 

at Las Limas to 586 mm at La Ceiba (table 6). Where 

precipitation data for Hurricane Mitch were available, 

they were used in the analysis. In some areas there 

were closely spaced stations, some of which had 

precipitation data from Hurricane Mitch and others did 

not. In some of these areas, there was a significant 

difference in the calculated daily, 50-year total for the 

stations with and without data for Hurricane Mitch. 

This was especially true in the southern portion of 

Honduras (fig. 10). Five sites without Hurricane Mitch 

data showed significant differences to nearby sites, and 

they were dropped from the analysis so that a regular 

pattern of equal precipitation totals could be drawn.

These station values were put into a GIS, and 

estimates were calculated for all of Honduras using an 

inverse-distance weighting scheme between station 

values. The inverse-distance weighting procedure 

involved interpolating values for a grid of regularly 

spaced cells using a linearly weighted combination of 

50-year return period values at known points. 

The weights are a function of inverse distance, so 

that the points that are closest to the grid cell are given 

the most weight. After the grid of estimates was 

created, contour lines of equal precipitation depths 

were drawn by the GIS software (fig. 10). 

Peak-Flow Frequency at Gaged Sites

Thirty-four stations with at least 10 years of 

annual peak-flow data totaling 833 peak flow values 

during the period 1954–98 were used for this analysis 

(table 7). The discharge at none of these stations is 

known to have been regulated such that the peak flow 

would be significantly affected. Discharges for five 

recurrence intervals (table 8) were computed for all 34 

stations using an interactive version of USGS computer 

program J407 (Kirby, 1981) that follows the guidelines 

established by the U.S. Water Resources Council 

(1981). The program automatically identifies low and 

high outliers and uses a conditional probability 

adjustment according to the established guidelines 

when outliers are detected. Of the 833 peak-flow 

values, eight low outliers and two high outliers were 

not used. 

Per the guidelines of the U.S. Water Resources 

Council (1981), a log-Pearson Type III distribution was 

fitted to the data for each station. The base 10 

logarithms of the discharge, Q, at selected exceedance 

probabilities was computed using the following 

equation:

, (2)

where

= the maximum daily precipitation for a given 

return period, in mm;

= the mean annual maximum daily 

precipitation, in mm;

= a reduced variate as a function of probability: 

3.902 for a 50-year return period; and

= the standard deviation of the annual maximum 

daily precipitation. 

X

ˆ X ( )σ 0.7797γ – 0.45 x = +

X

ˆ

X

γ

σx

= mean of the logarithms of peak flows;

= factor that is a function of the skew 

coefficient and the selected 

exceedance probability; and

= standard deviation of the logarithms 

of peak flows.

Q

ˆ log ( ) logQ mean K Q ( ) log sd = +

( ) logQ mean

K

( ) logQ sd
Frequency Analysis of Precipitation and Peak Flows 19

Table 6. Mean, standard deviation, and 50-year return period of annual maximum daily precipitation at 39 precipitation 

stations in Honduras with 15 years or more of record, and maximum daily precipitation during Hurricane Mitch

[Latitude and longitude are in degrees, minutes, and seconds]

Annual maximum daily precipitation, 

in millimeters

Maximum 

daily

precipitation

 during 

Hurricane 

Mitch

(millimeters)

Precipitation

station

name

Latitude 

(North)

Longitude

(West)

Years

of

data Mean

Standard

deviation

50-year

return period

Agua Caliente 14°40’39” 87°17’25” 30 71.09 20.70 125 70

Amapala 13°17’45” 87°39’40” 42 114.59 52.32 250 260

Campamento 14°33’18” 86°40’07” 30 85.32 22.91 145 56

Catacamas 14°50’22” 85°52’32” 48 66.66 22.24 124 100

Choluteca 13°24’29” 87°09’32” 35 119.01 70.80 303 467

El Coyolar 14°19’00” 87°30’39” 33 68.78 27.57 140 173

El Modelo 15°23’50” 87°59’30” 20 80.91 33.93 169 82

El Piyonal 14°04’23” 86°20’29” 19 62.18 20.10 114 no data

El Zamorano 14°00’45” 87°00’08” 24 75.23 21.51 131 no data

Flores 14°17’30” 87°34’06” 24 55.87 15.94 97 no data

Guayabilis 14°35’08” 86°17’30” 32 66.16 20.23 119 80

La Ceiba 15°44’24” 86°51’36” 34 286.59 115.52 586 284

La Conce 14°38’48” 86°11’34” 16 75.49 28.09 148 126

La Entrada 15°04’55” 88°44’00” 26 73.15 17.70 119 100

La Ermita 14°28’00” 87°04’05” 30 75.84 24.87 140 170

La Gloria 14°26’59” 87°58’31” 30 55.88 15.59 96 no data

La Lujosa 13°19’00” 87°17’15” 20 119.47 60.34 276 120

La Mesa 15°26’46” 87°56’18” 55 81.91 36.18 176 149

La Venta 14°18’32” 87°10’15” 32 81.05 39.88 184 184

Las Limas 15°06’06” 85°47’48” 23 56.67 14.45 94 no data

Los Encuentros 13°28’08” 87°05’25” 19 107.96 43.01 219 no data

Marcala 14°09’32” 88°02’25” 28 65.98 11.28 95 no data

Morazán 15°19’19” 87°35’50” 24 80.58 60.90 238 no data

Nacaome 13°31’32” 87°29’55” 23 88.93 22.28 147 no data

Olanchito 15°29’00” 86°33’52” 17 87.66 53.45 226 no data

Pespire 13°35’40” 87°21’55” 20 110.39 42.91 222 no data

Playitas 14°25’25” 87°42’06” 27 70.20 22.24 128 123

Puerto Lempira 15°12’30” 83°48’00” 43 137.85 54.83 280 106

Quimistán 15°20’34” 88°24’25” 27 82.91 27.44 154 110

San Fransisco 15°40’52” 87°01’56” 19 221.69 81.05 432 257

Santa Clara 14°26’38” 87°17’00” 24 72.92 20.24 125 no data

Santa Rosa 14°47’30” 88°48’00” 54 78.58 20.90 133 80

Sensentí 14°29’40” 88°56’12” 16 88.93 41.20 196 no data

Siguatepeque 14°34’53” 87°50’25” 20 65.58 22.04 123 no data

Tegucigalpa 14°03’31” 87°13’10” 49 62.76 19.88 114 119

Tela 15°46’28” 87°31’36” 41 187.96 62.59 350 171

Victoria 14°56’07” 87°23’22” 20 72.39 21.79 129 no data

Villa Ahumada 14°00’15” 86°34’18” 24 67.73 17.70 114 87

Yoro 15°08’50” 87°08’20” 18 80.76 47.56 204 237
20 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

Table 7. Streamflow stations in Honduras with 10 years or more of annual peak-flow data from 1954 through 1998 and water 

years for which data are available

River Basin/Station name 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972

AGUÁN

Aguán en La Isleña

Aguán en Sabana Larga X X X

Manguille en La Enyeda

PATUCA

San Antonio en Los Almendros X

Juticalpa en El Torito X X X X X X X X X X X

Guayape en Guayabillis X X X X X X X X X X X X X

Telica en Puente Telica X X X X X X X

Jalán en El Delirio X X X X X X X X X X X

Jalán en La Isleta X X X X X X

San Francisco en Paso Guayambre X

SICO

Palos Blanco en Puente X X X X X

Tonjagua en Tonjagua X X X X X X X

NACAOME

Nacaome en Las Mercedes X X X X X X X X

CHOLUTECA

Choluteca en Puente Choluteca

Choluteca en Paso La Ceiba X X X X X X X X X

Choluteca en Hernando López X X X X X X X X X X X X X X

CHAMELECÓN

Tapalapa en Chumbagua X X X

Chiquila en Carretera X X

Chamelecón en Puente X X X X X X X X X X X X

Chamelecón en La Vergona X

Chamelecón en La Florida X X X X X X

ULUA

Funez en San Nicolás X X X X X

Grande Otoro en La Gloria X X X X X X X X X X X X

Jicatuyo en Ulapa X X

Ulua en Chinda X X X X X X X X X X X X X

Ulua Puente Pimienta X X X X X X X X X X X X

Ulua en Remolino X X

HUMUYA

Jacagua en Las Vegas X X X X X X

Sulaco en El Sarro X X

Agua Caliente X X X X X

Tascalape en El Desmonte X X X X X X

Humuya en Guacamaya X X X X X

Humuya en La Encantada X X X X X X X X X X X X

Humuya en Las Higueras X X X X X X X X X X X X X X X
Frequency Analysis of Precipitation and Peak Flows 21

Table 7. Streamflow stations in Honduras with 10 years or more of annual peak-flow data from 1954 through 1998 and water 

years for which data are available—Continued

1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997

AGUÁN

X X X X X X X X X X X

X X X X X X X X X X X X X X X X X

X X X X X X X X X X

PATUCA

X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X

SICO

X X X X X X X X X

X X X X X X X X X X

NACAOME

X X X X X X X

CHOLUTECA

X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X

CHAMELECÓN

X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X

ULUA

X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X

HUMUYA

X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X

X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X
22 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch 16° 15° 14°

13°

90° 89° 88° 87° 86° 85° 84

Digital base from U.S. Geological Survey and ESRIDigital Atlas of Central America, January, 1999Station data from Servicio Meteorologico Nacional,Departmento de Climatologica, Honduras

0 20 40 60 0 20 40 60 80 10

HONDURAS

Pacific Ocean

Caribbean Sea

EL SALVADOR

NICARAGUA

GUATEMALA

Gulf of Honduras

Gulf of Fonseca

E

X

P

L

A

N

A

225

200

175

150

150

150

175

200

225

250

25

100

150

250

300

350

400

450

175

275

375

500

325

125

125

125

225

125

100

125

125

150

175

250

275

300

175

200

575

PRECIPITATION STATION

Data not used

 Does not include Hurricane M Includes Hurricane Mitch dat

CONTOURS—show 50-year, 24

 totals, in millimeters

Note: Several data points were excludenot include data from Hurricane Mitch aclose to points where the Hurricane Mitcimpact on the value.

125

Figure 10. Lines of equal 50-year, daily precipitation totals and the locations of precipitation stations at which 50-year, daily prwere estimated.
Frequency Analysis of Precipitation and Peak Flows 23

For this study, the average of the station skews 

calculated for each set of station data with more than 

20 years of record defined a generalized skew 

coefficient for the country (average = 0.166; standard 

error = 0.523). Regional patterns of skew coefficients 

were investigated by plotting the station skew 

coefficients on a map, but no discernible pattern was 

detected. The skew coefficients used to obtain values 

of K in equation (2) were calculated by weighting the 

station skew coefficients and the generalized skew 

coefficient according to the U.S. Water Resources 

Council guidelines. Peak flows for exceedance 

probabilities of 0.5, 0.1, 0.04, 0.02 and 0.01 and their 

95-percent confidence intervals are given in table 8 for 

all 34 stations. There is a 95-percent probability that 

the true peak flow for a particular exceedance 

probability lies within the 95-percent confidence 

interval.

Weighted estimates of peak flow in table 8 were 

obtained using the weighting procedures detailed in 

appendix 8 of the guideline of the U.S. Water 

Resources Council (1981). Estimates of peak flow 

obtained from frequency analysis and from generalized 

least-squares regression as discussed in the next section 

are weighted inversely proportional to their variance. 

The weighted estimate generally provides better 

estimates of the true flood discharges than those 

determined from frequency or regression analysis 

alone.

Six of the station records included the peak 

discharge caused by Hurricane Mitch. Only one of the 

gaging stations, Humuya en La Encantada, recorded a 

peak discharge for Hurricane Mitch, and the other five 

stations used nearby indirect peak flow measurements 

made by the USGS. Many gaging stations were 

destroyed and many did not report peak flows, 

presumably because of malfunctions at the gage. The 

ratio of the drainage area at the indirect site to the 

drainage area at the gage site was used to estimate the 

Hurricane Mitch peak flow at the gaging station from 

the computed indirect peak flow. The Hurricane Mitch 

floods computed by the indirects were in all cases the 

largest peak flow recorded at the station by a significant 

margin (table 9), however the Hurricane Mitch flood at 

the Humuya en La Encantada was only the fifth largest 

annual peak out of 38 recorded peaks. The frequency 

analysis of the precipitation during Hurricane Mitch as 

discussed previously suggests that the Hurricane Mitch 

peak flow is probably an event with a frequency larger 

than the period of peak-flow record at stations in some 

regions of the country and a less significant event in 

other regions of the country. When it is known that no 

other peak discharges have exceeded a high outlier 

peak such as the Hurricane Mitch peak for a period 

longer than the period of record at a station, a historical 

adjustment can be made to the frequency curve to take 

into account the historical period or the effective 

increase in the number of peak flows. In the case of the 

Hurricane Mitch peak flows, local information (Jeff V. 

Phillips, U.S. Geological Survey, written commun., 

September 2000) was used to establish a historical 

period. In Pespire on Río Nacaome, it was reported 

that 100-year-old houses never experienced flooding 

until Hurricane Mitch; thus, 100 years was used as the 

historical period for the Río Nacaome station. In 

Choluteca on the Río Choluteca, local residents 

reported that the Hurricane Mitch flood was 1 meter 

higher than the large flood in 1935 flood. In this case, 

65 years was used as the historical period for all the 

Río Choluteca stations (table 9 and fig. 11). No reports 

were available for the Río Ulua; therefore, the 

historical period was set to 44 years, or the period of 

record for all the stream gages in the basin. 

Peak-Flow Frequency at Ungaged Sites

If a site is located near and on the same river as 

one of the 34 long-term streamflow stations, then the 

peak flow data and frequency information are readily 

available. However, most of the selected municipalities 

are not located near a long-term streamflow station. To 

make estimates at ungaged sites, a regression analysis 

was performed to obtain a relation between peak flows 

and other basin characteristics. At each of the 34 longterm streamflow sites, a series of basin characteristics 

was compiled (table 10). A stepwise linear regression, 

stepping both ways from a simple model to the most 

complex model with all the variables, identified the 

best model as one using drainage area and annual 

precipitation as the explanatory variables to estimate 

the 50-year flood discharge. 
24 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

Table 8. Estimated flood discharges, 95-percent confidence intervals, and weighted estimates at selected exceedance 

probabilities for 34 streamflow stations in Honduras and the maximum peak recorded at each station

[All values are in cubic meters per second.]

Exceedance

probability

Maximum

peak

Station name recorded

0.5

(2-year

flood)

0.1

(10-year

flood)

0.04

(25-year

flood)

0.02

(50-year

flood)

0.01

(100-year

flood)

Flood Discharge1

Agua Caliente 494 904 1,130 1,310 1,490 1,010

Aguán en La Isleña 169 848 1,480 2,100 2,860 610

Aguán en Sabana Larga 162 444 654 844 1l,070 750

Chamelecón en La Florida 108 559 1,090 1,720 2,620 2,030

Chamelecón en La Vergona 189 384 490 571 654 522

Chamelecón en Puente 452 928 1,190 1,400 1,610 1,271

Chiqula en Carretera 28.3 131 247 381 571 636

Choluteca en Hernando López 237 830 1390 1980 2740 6,310

Choluteca en Paso La Ceiba 277 822 1,280 1,740 2,310 7,500

Choluteca en Puente Choluteca 1,010 2,580 3,790 4,910 6,250 15,500

95-Percent Confidence Interval1

Agua Caliente 426-574 760-1,150 925-1,510 1,050-1,810 1,170-2,140

Aguán en La Isleña 84.3-343 407-2,970 647-6,760 858-11,500 1,100-18,300

Aguán en Sabana Larga 122-215 322-706 449-1,160 557-1,620 677-2,200

Chamelecón en La Florida 73.0-158 355-1,040 637-2,400 937-4,230 1,340-7,210

Chamelecón en La Vergona 157-229 308-519 382-702 436-851 489-1,010

Chamelecón en Puente 376-544 748-1,240 933-1,690 1,070-2,060 1,210-2,460

Chiqula en Carretera 19.1-41.5 83.6-248 145-554 208-968 292-1,640

Choluteca en Hernando López 183-305 612-1,240 966-2,310 1,310-3,540 1,740-5,280

Choluteca en Paso La Ceiba 216-353 616-1,220 910-2,110 1,180-3,070 1,500-4,380

Choluteca en Puente Choluteca 756-1,340 1,880-4,190 2,600-7,000 3,220-9,960 3,920-13,860

Weighted Estimate2

Agua Caliente 480 894 1,130 1,320 1,520

Aguán en La Isleña 177 727 1,170 1,590 2,100

Aguán en Sabana Larga 179 499 735 945 1,190

Chamelecón en La Florida 102 469 864 1,310 1,920

Chamelecón en La Vergona 194 410 536 636 739

Chamelecón en Puente 465 968 1,250 1,480 1,710

Chiqula en Carretera 31.9 143 261 389 565

Choluteca en Hernando López 241 817 1,340 1,880 2,570

Choluteca en Paso La Ceiba 282 816 1,260 1,680 2,200

Choluteca en Puente Choluteca 1,010 2,480 3,550 4,530 5,680
Frequency Analysis of Precipitation and Peak Flows 25

Table 8. Estimated flood discharges, 95-percent confidence intervals, and weighted estimates at selected exceedance 

probabilities for 34 streamflow stations in Honduras and the maximum peak recorded at each station—Continued

Exceedance

probability

Maximum

peak

Station name recorded

0.5

(2-year

flood)

0.1

(10-year

flood)

0.04

(25-year

flood)

0.02

(50-year

flood)

0.01

(100-year

flood)

Flood Discharge1

Funez en San Nicolás 96.5 428 759 1,110 1,570 746

Guayape en Guayabilis 375 942 1,330 1,670 2,050 1,947

Grande Otoro en la Gloria 204 510 739 949 1,200 999

Humuya en Guacamaya 601 1,400 1,930 2,390 2,890 1,860

Humuya en La Encantada 360 671 816 918 1,020 726

Humuya en Las Higueras 178 404 533 632 735 472

Jacagua en Las Vegas 40.2 112 165 212 267 163

Jalán en El Delirio 284 619 824 991 1,170 1,042

Jalán en La Isleta 330 610 784 930 1,090 1,100

Jicatuyo en Ulapa 1,070 1,900 2,400 2,810 3,260 3,460

95-Percent Confidence Interval1

Funez en San Nicolás 66.9-139 279-768 461-1,560 638-2,510 855-3,880

Guayape en Guayabilis 309-454 749-1,270 1,020-1,910 1,240-2,510 1,480-3,210

Grande Otoro en la Gloria 167-247 404-695 560-1,090 696-1,480 848-1,960

Humuya en Guacamaya 473-763 1,070-2,080 1,410-3,140 1,680-4,130 1,970-5,310

Humuya en La Encantada 311-418 565-838 673-1,060 747-1,220 816-1,370

Humuya en Las Higueras 144-220 317-560 404-783 470-967 534-1,160

Jacagua en Las Vegas 30.8-52.4 82.4-172 115-279 143-384 174-514

Jalán en El Delirio 234-345 494-842 635-1,200 744-1,500 858-1,850

Jalán en La Isleta 288-378 519-757 647-1,030 750-1,270 858-1,550

Jicatuyo en Ulapa 927-1,230 1,610-2,390 1,970-3,210 2,250-3,940 2,550-4,760

Weighted Estimate2

Funez en San Nicolás 93.0 387 668 957 1,330

Guayape en Guayabilis 377 939 1,320 1,650 2,020

Grande Otoro en la Gloria 202 501 724 928 1,170

Humuya en Guacamaya 596 1,370 1,880 2,320 2,800

Humuya en La Encantada 363 687 848 963 1,070

Humuya en Las Higueras 183 427 571 685 803

Jacagua en Las Vegas 42.7 126 189 247 315

Jalán en El Delirio 291 635 845 1,020 1,200

Jalán en La Isleta 319 594 768 915 1,080

Jicatuyo en Ulapa 1,040 1,860 2,360 2,770 3,220
26 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

Table 8. Estimated flood discharges, 95-percent confidence intervals, and weighted estimates at selected exceedance 

probabilities for 34 streamflow stations in Honduras and the maximum peak recorded at each station—Continued

Exceedance

probability

Maximum

peak

Station name recorded

0.5

(2-year

flood)

0.1

(10-year

flood)

0.04

(25-year

flood)

0.02

(50-year

flood)

0.01

(100-year

flood)

Flood Discharge1

Juticalpa en El Torito 153 606 1,060 1,550 2,200 1,920

Manguilile en La Enyeda 282 983 1,630 2,300 3,160 1,500

Nacaome en Las Mercedes 1,080 2,580 3,630 4,550 5,600 9,300

Palos Blanco en Puente 187 511 748 960 1200 759

San Antonio en Los Almendros 107 334 511 675 868 512

San Francisco en Paso Guayambre 35.7 60.5 74.3 85.1 96.4 72.2

Sulaco en El Sarro 832 1,380 1,650 1,840 2,030 1,480

Tapalape en Chumbagua 69.1 118 143 161 180 128

Tascalape en El Desmonte 53.0 227 401 587 832 524

Telica en Puente Telica 277 570 752 902 1,060 924

95-Percent Confidence Interval1

Juticalpa en El Torito 114-204 428-964 701-1,900 973-3,020 1,320-4,650

Manguilile en La Enyeda 167-465 576-2,560 871-5,580 1,140-9,550 1,460-15,790

Nacaome en Las Mercedes 814-1,420 1,890-4,160 2,520-6,600 3,040-9,010 3,600-12,000

Palos Blanco en Puente 131-266 347-947 478-1,610 585-2,290 703-3,170

San Antonio en Los Almendros 73.4-156 220-634 316-1,130 397-1,650 487-2,340

San Francisco en Paso Guayambre 29.5-43.2 49.2-84.8 58.4-113 65.2-138 72.0-166

Sulaco en El Sarro 732-959 1,170-1,730 1,370-2,160 1,510-2,490 1,640-2830

Tapalape en Chumbagua 57.6-83.0 96.3-161 113-208 125-245 137-285

Tascalape en El Desmonte 34.6-80.6 140-461 229-972 314-1,610 418-2,570

Telica en Puente Telica 230-333 60-769 586-1,090 684-1,370 786-1,690

Weighted Estimate2

Juticalpa en El Torito 145 541 918 1,310 1,840

Manguilile en La Enyeda 239 737 1,150 1,560 2,080

Nacaome en Las Mercedes 956 2,190 3,030 3,770 4,620

Palos Blanco en Puente 209 573 834 1,060 1,320

San Antonio en Los Almendros 109 329 498 653 835

San Francisco en Paso Guayambre 41.6 86.2 116 139 165

Sulaco en El Sarro 822 1,380 1,670 1,880 2,080

Tapalape en Chumbagua 70.9 151 204 247 293

Tascalape en El Desmonte 49.9 201 346 496 693

Telica en Puente Telica 281 589 783 945 1,120
Frequency Analysis of Precipitation and Peak Flows 27

Table 8. Estimated flood discharges, 95-percent confidence intervals, and weighted estimates at selected exceedance 

probabilities for 34 streamflow stations in Honduras and the maximum peak recorded at each station—Continued

Exceedance

probability

Maximum

peak

Station name recorded

0.5

(2-year

flood)

0.1

(10-year

flood)

0.04

(25-year

flood)

0.02

(50-year

flood)

0.01

(100-year

flood)

Flood Discharge1

Tonjagua en Tonjagua 40.9 106 152 192 238 148

Ulua en Chinda 2,000 3,690 4,810 5,790 6,890 11,000

Ulua Puente Pimienta 1,720 2,690 3,160 3,500 3,840 3,070

Ulua en Remolino 1,070 2,470 3,400 4,190 5,070 3,780

95-Percent Confidence Interval1

Tonjagua en Tonjagua 29.9-55.9 74.9-181 102-294 123-406 147-546

Ulua en Chinda 1,770-2,250 3,190-4,460 4,040-6,140 4,740-7,690 5,500-9,520

Ulua Puente Pimienta 1,560-1,900 2,400-3,140 2,760-3,800 3,020-4,300 3,270-4,800

Ulua en Remolino 841-1,350 1,880-3,640 2,480-5,490 2,960-7,210 3,470-9,270

Weighted Estimate2

Tonjagua en Tonjagua 38.1 106 158 207 263

Ulua en Chinda 1,980 3,630 4,710 5,660 6,730

Ulua Puente Pimienta 1,720 2,700 3,180 3,530 3,870

Ulua en Remolino 1,040 2,340 3,180 3,900 4,700

1Obtained by frequency analysis of station records.

2Obtained from frequency and generalized least-squares regression analysis weighted according to procedures outlined in appendix 8 of the U.S. Water 

Resources Council (1981).

Table 9. Streamflow stations at which the peak discharge during Hurricane Mitch was estimated using indirect measurements 

near the station and comparisons of different peak flows

[m3/s, cubic meters per second]

50-year flood discharge

(m3/s)

Gaging station name

Period of

station

record

Length of

period

based

on local,

historical

information

(years)

Peak discharge

during

Hurricane Mitch

estimated from

indirect

measurements

(m3/s)

Next highest

peak discharge

on record

(m3/s)

Estimated

using the

length

of period

based on

local,

historical

information

Estimated

using

the

period of

station

record

Choluteca en Hernando López 1954–98 65 6,310 962 1,980 2,950

Choluteca en Paso La Ceiba 1956–98 65 7,500 730 1,740 3,280

Choluteca en Puente Choluteca 1979–98 65 15,500 2,130 4,910 12,500

Nacaome en Las Mercedes 1965–98 100 9,300 3,590 4,550 9,210

Ulua en Chinda 1955–98 44 11,000 3,670 5,790 6,950
28 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

Final frequency curve with 65-year historical period

Frequency curve without historical adjustment

Unadjusted peaks

Historical adjusted peaks

10 3

104 

10 5 

ANNUAL PEAK DISCHARGE, 

IN CUBIC METERS PER SECOND

99.5 99 98 95 90 80 70 50 30 20 10 5 2 1 0.5 0.2

ANNUAL EXCEEDANCE PROBABILITY, IN PERCENT 

Figure 11. Comparison of annual peak-flow discharge and annual exceedance probability 

for Choluteca en Puente Choluteca, Honduras, using exceedance probabilities based on the 

recorded (unadjusted) record and based on local, historical information (adjusted).
Frequency Analysis of Precipitation and Peak Flows 29

Table 10. Basin characteristics and 50-year flood discharge at 34 long-term streamflow stations in Honduras

[m3/s, cubic meters per second; km2, square kilometers; mm, millimeters]

Identification

number Gaging station name

50-year

flood

discharge

(m3/s)

Area of

contributing

drainage

(km2)

River

length

(meters)

River

slope

Annual

precipitation

(mm)

Percentage

of basin

as forest

50-year

maximum

daily

precipitation

(mm)

1 Agua Caliente 1,310 1,545.2 76,117 0.005255 1,519 56.2 134

2 Aguán en La Isleña 2,100 797.1 40,140 0.013187 1,600 51.0 204

3 Aguán en Sabana Larga 844 1,908.3 92,812 0.007337 1,647 68.0 234

4 Chamelecón en La Florida 1,720 236.6 28,106 0.019071 1,524 29.4 132

5 Chamelecón en La Vergona 571 970.9 76,932 0.007782 1,580 29.7 128

6 Chamelecón en Puente 1,400 3,233.6 1,5639 0.003913 1,573 35.2 147

7 Chiquila en Carretera 381 124.2 23,838 0.021478 1,928 44.2 141

8 Choluteca en Hernando López 1,980 1465.1 82,550 0.010063 1,305 37.6 131

9 Choluteca en Paso La Ceiba 1,740 1,741.0 99,807 0.008750 1,260 37.7 137

10 Choluteca en Puente Choluteca 4,910 6,942.0 285,177 0.004128 1,139 34.9 159

11 Funez en San Nicolás 1,110 217.7 28,974 0.023055 1,832 80.2 131

12 Guayape en Guayabilis 1,670 2,223.7 127,257 0.006580 1,224 51.0 143

13 Grande Otoro en La Gloria 949 927.9 60,243 0.018857 978 26.4 106

14 Humuya en Guacamaya 2,390 2,621.2 106,027 0.005822 1,542 43.3 122

15 Humuya en La Encantada 918 2,058.4 73,264 0.008827 1,448 43.0 121

16 Humuya en Las Higueras 632 1,117.4 45,749 0.020459 1,522 50.9 120

17 Jacagua en Las Vegas 212 202.3 29,202 0.041321 1,455 19.0 165

18 Jalán en El Delirio 991 2,480.0 146,684 0.002809 1,028 60.6 133

19 Jalán en La Isleta 930 1,167.4 68,629 0.005284 903 78.9 139

20 Jicatuyo en Ulapa 2,810 3,620.0 141,059 0.004745 1,744 51.0 145

21 Juticalpa en El Torito 1,550 414.2 40,754 0.003435 1,000 20.6 133

22 Mangulile en La Eneyda 2,300 573.0 37,981 0.005804 1,537 86.0 185

23 Nacaome en Las Mercedes 4,550 1,852.0 87,038 0.018352 1,982 36.0 171

24 Palos Blanco en Puente 960 1,841.2 87,523 0.005180 1,431 51.1 139

25 San Antonio en Los Almendros 675 583.1 53,743 0.010891 992 67.1 119

26 San Francisco en Paso Guayambre 85.1 320.3 45,015 0.013151 1,110 31.2 125

27 Sulaco en El Sarro 1840 3,758.4 134,294 0.003674 1,402 53.5 140

28 Tapalapa en Chumbagua 161 243.5 37,849 0.026069 1,658 24.6 146

29 Tascalape en El Desmonte 587 114.6 25,015 0.025851 1,570 33.7 161

30 Telica en Puente Telica 902 1,607.6 73,215 0.006829 1,262 51.7 145

31 Tonjagua en Tonjagua 192 102.6 19,997 0.030405 1,118 84.8 111

32 Ulua en Chinda 5,790 8,590.0 205,597 0.005214 1,618 41.8 131

33 Ulua Puente Pimienta 3,500 9,065.0 243,974 0.004662 1,632 40.8 134

34 Ulua en Remolino 4,190 3,813.0 141,448 0.009172 1,488 37.4 118
30 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

A generalized least-squares regression technique 

(Tasker and Stedinger, 1989) was used to determine an 

equation to estimate the 50-year flood discharge at a 

site, based on drainage basin area and annual 

precipitation. The method weights each station used in 

the analysis on the number of years of peak flow record 

and the distance between stations. Logarithmic 

transformations were made on the variable so that 

linear regression techniques could be used (fig. 12). 

The resulting equation for estimating the 50-year flood 

discharge, Q50, converted to a linear form for the entire 

country, is:

, (3)

where 

The comparison of predicted values calculated 

from equation (3) and observed values used in the 

analysis shows a linear relation in log units with a 

r-square value of 0.56 (fig. 12). The standard error of 

estimate is 0.260 log unit or 65.6 percent, and the 

standard error of prediction equals 0.278 log unit or 

71.3 percent. The last two values are a measure of how 

well the regression equation predicts the 50-year flood 

discharge from the data used in the analysis, and it 

includes the error in the regression equation as well as 

the scatter about the equation (Hardison,1971).

Q50 0.0788 × ( ) DA 0.5664× ( ) P

0.7693 =

= drainage area, in km2; and

= mean annual precipitation on the basin, in 

mm.

DA

P

1.5

2

2.5

3

3.5

4

1.5 2 2.5 3 3.5 4

PREDICTED 50-YEAR PEAK FLOW, IN LOG UNITS

 OF CUBIC METERS PER SECOND

OBSERVED 50-YEAR PEAK FLOW, IN LOG UNIT 

OF CUBIC METERS PER SECOND

Figure 12. Comparison of predicted and observed 50-year 

peak flows at 34 streamgaging stations in Honduras.

The solid diagonal line represents a line of equivalence between 

predicted and observed values and the dashed lines are 

standard error of estimate about the equivalence line.
Frequency Analysis of Precipitation and Peak Flows 31

A GIS to Estimate 50-Year Flood Discharges

A GIS was created for utilizing the regression 

equation (equation 3) to estimate the 50-year flood 

discharge anywhere on a stream network created for 

the country. A user with the GIS software ArcView on 

a personal computer may access the GIS by (1) opening 

the ArcView project file, (2) highlighting the 50-year 

flood discharge theme in the table of contents of the 

map view of Honduras, (3) zooming to the area of 

interest, and (4) clicking with the mouse on the stream 

network using the identify tool. A window will appear 

with the 50-year flood discharge estimate. The 

ArcView project and shape files are available from the 

USGS Hurricane Mitch Program Clearinghouse web 

site at <http://mitchnts1.cr.usgs.gov/projects/ 

floodhazard.html>. 

Stream networks and basin areas were defined 

using a 93-meter cell resolution Digital Terrain 

Elevation Data (DTED) level 1 of the country provided 

by the National Imagery and Mapping Agency with a 

missing 12,000 km2 portion of the central part of the 

country filled in with GTOPO-30 1-km cell resolution 

DEM data. Comparisons with hand-drawn basin areas 

on topographic maps show excellent duplication by the 

GIS in steep terrain and some errors in flat terrain. A 

stream network of basin-average precipitation was 

created using GIS to first digitize an isohyetal map of 

the mean annual precipitation for the country from a 

1:2,500,000-scale map (Modesto Canales, 1998, p. 15) 

and then convert it to a raster format of regularly 

spaced cells.

Estimated 50-Year Flood Discharges at 

Selected Municipalities 

The 50-year flood discharges for the selected 

municipalities were obtained by one of two methods. 

At four of the municipalities, the 50-year flood 

discharge for one or more rivers was estimated from the 

weighted 50-year flood discharge determined from a 

nearby gaging station record and the regression 

equation (equation 3). The weighted estimate followed 

procedures presented in appendix 8 of the guidelines of 

the U.S. Water Resources Council (1981). The result 

was adjusted by multiplying the weighted result by the 

ratio of the drainage area at the study site to the 

drainage area at the gage site. At the remainder of the 

sites, the regression equation (equation 3) was used 

directly to determine the design discharge. 

At three of the selected municipalities, the 

50-year flood discharge from the regression equation 

was used as the design discharge, despite having one or 

more long-term gaging station on the same river. For 

the Tegucigalpa municipality, there are two 

downstream gaging stations on the Río Choluteca with 

approximately twice the drainage area of the Río 

Choluteca at Tegucigalpa. Their weighted discharges, 

when adjusted by the drainage area ratios, averaged 

about the same as the study area’s 50-year flood 

discharge by regression; therefore, the design discharge 

is simply the 50-year flood discharge determined by 

regression. For the Comayagua municipality, there are 

three long-term gages near Comayagua. The weighted 

discharges adjusted by the drainage area ratio at the 

two closest sites upstream and downstream of 

Comayagua are significantly less than the discharge 

computed by regression, but at the gage further 

downstream, the weighted discharges adjusted by the 

drainage area ratio is approximately the same as the 

discharge computed by regression. The discharge 

computed by regression was used at this municipality. 

And finally, for the La Lima municipality, the flood 

protection feasibility study on Río Chamelecón 

(Consorcio Lahmeyer International, 1998, p.3-35) 

reports the Río Chamelecón en Puente gage tends to 

under-report peak discharges because stage 

observations are made at insufficient frequency, often 

missing the instantaneous peaks, and the gage has a 

history of missing recordings during floods. The design 

discharge for this municipality is based on the 

discharge given by the regression equation.

50-Year Flood Discharges Reported by 

Others

Several independent studies estimated 50-year 

flood discharge at the selected municipalities 

(table 11). These include La Lima, Tegucigalpa,

El Progreso, and Santa Rosa de Aguán. 

The flood protection feasibility study for La 

Lima compared station records in the region to develop 

a relation based on drainage area to estimate the 

50-year flood discharge of the Río Chamelecón. 
32 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

At the Río Chamelecón en Puente gage that is located 

just upstream of the La Lima study site, the relation 

estimated a 50-year flood discharge of 2,485 m3/s and 

verified this figure with an application of a unit 

hydrograph model using SCS (Soil Conservation 

Service, now called the Natural Resources 

Conservation Service) loss rate parameters to compute 

a 50-year flood discharge of 2,473 m3/s (Consorcio 

Lahmeyer International, 1998, p.3-78). These figures 

agree closely with the discharge computed by 

regression for the 50-year flood discharge at the 

La Lima site, 2,400 m3/s. 

In Tegucigalpa, the Japan International 

Cooperation Agency (JICA) is conducting a concurrent 

project on flood control that has made estimates of the 

50-year flood discharge on the Río Choluteca river 

system. They used a storage function method to 

estimate runoff that was calibrated to the Hurricane 

Mitch peak flow (827 m3/s) at Concepción Dam on the 

Río Grande with a drainage area of 139.5 km2 and 

precipitation recorded at Toncontín Airport in 

Tegucigalpa. An unsteady flow-routing model was 

used to route flows estimated with the storage function 

model for the subbasins through the stream network. 

Estimated 2-day maximum precipitation with a 50-year 

return interval for the Toncontín precipitation record, 

distributed hourly using the pattern of observed 

precipitation during Hurricane Mitch, is input to their 

model that estimates the 50-year flood discharge of 

2,600 m3/s at Río Choluteca at the downstream end of 

Tegucigalpa (Dr. Chaisak Sripadungtham, JICA, 

written commun., July 2001), where 922 m3/s was 

estimate by the regression method.

The Spanish government did a flood and erosion 

control study of the Santa Rita-El Progreso corridor in 

the eastern portion of Departamento de Yoro in 

response to Hurricane Mitch. This included a study of 

flooding in the Río Pelo watershed. A modified rational 

method was used to compute peak flows for various 

return intervals. The 50-year flood discharge for the 

Río Pelo was estimated to be 316 m3/s (Centro de 

Estudios Hidrográficos del CEDEX, 1999, p. 33). The 

design discharge for the site model is 235 m3/s as 

computed by regression, and the Hurricane Mitch peak 

flow is estimated at 309 m3/s by a three-section slopearea method. (Mark Smith, U.S. Geological Survey, 

written commun., April 2001). 

Sir William Halcrow and Partners (1985) 

estimated a combined discharge of 1,750 m3/s in the 

Río Aguán above Puente Durango (600 m3/s) and a 

tributary Río Chapagua (1,150 m3/s) with a combined 

drainage area of 9,850 km2, for the 1974 Hurricane Fifi 

flood. They believe this approximates the 25-year peak 

flow. This estimated discharge is less than half the 

50-year flood discharge (3,980 m3/s) estimated for the 

same location in the current study using the regression 

method. 

Table 11. Comparisons of 50-year flood discharges estimated by different studies and estimates of peak 

flows during Hurricane Mitch at four municipalities in Honduras

[m3/s, cubic meters per second]

Municipality—river

Hurricane1

Mitch

peak-flow

estimate

(m3/s)

50-year flood discharge

(m3/s)

Method used 

to estimate

50-year flood

discharge

by others

Estimated by

this study

Estimated by

others

La Lima—

Río Chamelecón en Puente

No data 2,400 2,473 Drainage area relation for 

Río Chamelecón

Tegucigalpa—

Río Choluteca

4,360 922 2,600 Storage function, unsteady 

flow-routing

El Progreso—

Río Pelo

309 235 316 Modified rational method

Santa Rosa de Aguán—

Río Aguán en Puente Saba

19,700 3,310 4,700 SOGREAH model

1Estimated by three-section slope-area indirect measurement.
Flood-Hazard Mapping Method 33

Upstream of this site at Río Aguán at Puente Saba 

(drainage area of 7,722 km2), a report by Sir William 

Halcrow and Partners (1985, p. H.194) includes a 

figure with a 50-year flood discharge estimate of 

4,700 m3/s using a model created by SOGREAH. The 

50-year flood discharge estimated for this site in the 

current study by regression is 3,310 m3/s. Upstream of 

Puente Saba on Río Aguán, a three-section slope-area 

estimate of the peak flow on the Río Aguán during 

Hurricane Mitch is 19,700 m3/s near Clifton, with a 

drainage area of 7,463 km2 (Mark Smith, U.S. 

Geological Survey, written commun., April 2001).

FLOOD-HAZARD MAPPING METHOD

This section describes the procedures and 

methods used to construct flood-hazard maps of the 15 

selected sites based on the 50-year flood discharge 

values and topographic information previously 

described. The estimates of the water-surface profiles 

and the construction of the inundation maps were 

compiled with the aid of two software packages 

developed and distributed by the U.S. Army Corps of 

Engineers, HEC-GeoRAS and HEC-RAS. The general 

approach is to (1) pre-process the GIS data to define 

stream thalweg, banks, approximate overbank 

centerlines, and cross section lines in HEC-GeoRAS, 

(2) export the GIS pre-processed data into HEC-RAS 

and run the hydraulic model to simulate water-surface 

elevations, and (3) post-process the hydraulic 

simulation results in HEC-GeoRAS to display the 

results as maps. 

HEC-GeoRAS is a pre- and post-processing 

GIS software package that runs in conjunction with 

Arc/Info or ArcView GIS software distributed by 

ESRI. Both ArcInfo and ArcView GIS, which run in a 

similar manner and require similar inputs, were used in 

this project. The version described in this report relates 

directly to the ArcView extension of HEC-GeoRAS 

version 3.0 that was developed by the U.S. Army Corps 

of Engineers, Hydrologic Engineering Center (HEC) 

and ESRI. The reader is referred to the user’s manual 

(U.S. Army Corps of Engineers, 2000) for more detail 

on how this software works. 

HEC-RAS (River Analysis System) software is a 

one-dimensional steady-flow modeling system 

developed by HEC (Hydraulic Engineering Center). 

The version described in this report is version 2.2, 

designed to perform hydraulic step-backwater 

calculations for estimating water-surface profiles in a 

full network of channels. The calculations start with a 

user-specific boundary condition at one end of the 

study reach and proceed one cross section at a time to 

the other end. For subcritical flow conditions, 

calculations start at the downstream end and proceed 

upstream. For supercritical flow conditions, 

calculations start at the upstream end and proceed 

downstream. The reader is referred to the user’s manual 

(U.S. Army Corps of Engineers, 1998a) and the 

hydraulic reference manual (U.S. Army Corps of 

Engineers, 1998b) for more details on this software, 

hydraulic theory, and equations used by the modeling 

system. 

The conceptual model for the cross-section 

geometry used in this project is the default method 

used in HEC-GeoRAS and HEC-RAS, which is to 

divide the cross section into three subsections, the main 

channel, a left overbank area, and a right overbank 

area. Each subsection has a reach length to the next 

downstream cross section and a composite roughness 

coefficient associated with it. In most cases, the main 

channel, which defines the inside boundaries for the 

overbank areas, is fairly easy to define on cross 

sections. The main channel generally carries all of the 

low to medium-high flows and has steep side slopes. 

The outside boundaries of the overflow channels define 

the extent of the modeled area and generally extend 

beyond the expected width of the 50-year flood. In 

some instances, the slope of the overbank continues 

downward from the main channel banks, and, 

consequently, any flood water that escapes the main 

channel will continue to flow outward. Where this is a 

minor overflow of unknown amounts, the area beyond 

the end of the overbank area is labeled as an area of 

shallow flooding or an area of undetermined depth and 

extent on the final maps. 

Pre- and Post-Processing GIS Data With 

HEC-GeoRAS

Input to the GIS pre- and post-processing 

software package, HEC-GeoRAS, was a triangular 

irregular network (TIN) topographic model that was 

created from the LIDAR DEM. The user digitized the 

main channel thalweg, bank lines, approximate center 

lines of both overbank areas, and cross-section lines 

beginning at the upstream end of the study area and 

working downstream. 
34 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

Often, a shaded relief of the LIDAR-derived DEM was 

used as a background image to help locate the various 

lines (fig.13). The bank lines define the division 

between the overbank areas and the main channel and 

are important in establishing those areas where the 

main channel roughness coefficient should be applied 

and where the overbank roughness coefficient should 

be applied. The approximate centerlines of the 

overbank areas are used to determine the reach lengths 

for the overbank sections. The cross-section lines 

define the positioning of the cross-sectional data in the 

stream network and the stationing of the elevation data 

beginning on the left bank of the channel (looking 

downstream). These lines are used to extract elevation 

data from the TIN DEM, producing station-elevation 

data pairs that will be entered into the HEC-RAS 

hydraulic model for each cross section. All the crosssection data are exported as a single file formatted for 

reading by the HEC-RAS model.

After the pre-processed data from HEC-GeoRAS 

are imported into HEC-RAS, the step-backwater model 

is run and adjustments (described in the following 

section) are made. The results are exported from HECRAS as a single file containing 50-year flood watersurface elevations at each cross section and coordinates 

of vertices of a bounding polygon that defines the 

extent of flooding. This file is imported into HECGeoRAS, and a water-surface TIN DEM of the water 

surface is created. Next, the area-of-inundation 

polygon coverage, which shows only areas within the 

bounding polygon that will be under water during the 

50-year flood, is created by intersecting the watersurface TIN with the topographic TIN. A water-depth 

grid at a 2-meter cell resolution (sometimes a 2.5- or 

3-meter cell resolution was used on a large coverage 

because of file-size limitations) is also created by 

subtracting the topographic elevation from the watersurface elevation at every cell.

Outside of the HEC-GeoRAS, some final GIS 

steps are made to make the final two inundation maps 

for the site reports. The water-depth grid is converted 

into a polygon coverage with three to four depth ranges 

and shaded from light blue (shallow) to dark blue 

(deep). This coverage is combined with a coverage of 

the cross-section locations to make the depth-ofinundation map. The polygon coverage of the area of 

flood inundation is underlaid by a digital raster graphic 

of the existing 1:50,000-scale topographic maps for the 

study site to make the area-of-inundation map. 

Hydraulic Modeling With HEC-RAS

After the GIS pre-processing phase with the 

HEC-GeoRAS software, the cross section or 

“geometry” data is imported into the HEC-RAS 

modeling system. Generally, the main channel bank 

locations need to be refined from the locations 

estimated in HEC-GeoRAS in the cross-section data 

editor with the aid of cross-section plots. The crosssection data editor also allows the user to edit reach 

lengths, roughness coefficients, and contraction and 

expansion coefficients. Reach lengths are already 

calculated and generally were not changed except when 

bridge cross sections from field surveys were added. 

The default contraction coefficient (0.1) and expansion 

coefficient (0.3) generally were used, except where a 

contraction or expansion was abrupt. At such a reach, 

the contraction or expansion coefficient was increased 

to as much as 0.6 or 0.8, respectively, as suggested by 

the reference manual (U.S. Army Corps of Engineers, 

1998b, p. 3-20).

Roughness coefficients, Manning’s n, were 

estimated by a hydrologist at many of the bridge 

locations where field surveys were conducted. These 

estimates were somewhat subjective, but followed the 

guidelines provided by Benson and Dalrymple (1967, 

p. 20-23). At other locations, the n-values were 

estimated on the basis of photos and recollections of 

the site if it had been visited, and by reviewing a 

shaded-relief image of the LIDAR-derived DEM prior 

to the vegetation-removal filtering. The image gave a 

good view of the density of vegetation--higher 

densities were given higher Manning’s n value. On 

some occasions, a video of the site that was taken from 

the airplane at the same time that the LIDAR data were 

collected was reviewed to determine the type of 

vegetation at the site. Main-channel n-values typically 

ranged from a low of 0.026 in straight, sand channels 

with few irregularities to a high of around 0.045 in 

cobble and boulder channels with cross-section 

irregularities. Overbank values typically ranged from 

0.045 in pastures without much brush or trees to 0.090 

in dense natural forests. No observed high-water marks 

were available to calibrate the n-values. 

In the Catacamas study site, the average slope of 

the bed along the study-area reach was 0.019 and is as 

steep as 0.03 in the upper portion. In the El Progreso 

study site, the slope of the bed of the upper reaches was 

about 0.02. These study sites were much steeper than 

the other sites. 
Flood-Hazard Mapping Method 35

EXPLANATION

EXPLANATION

STREAM THALWEG

RIVER BANK

APPROXIMATE CENTERLINE OF OVERBANK AREAS

CROSS-SECTION LINE

Tocoa

Rio Tocoa

Figure 13. Shaded-relief image of the Río Tocoa, Honduras, study site based on the LIDAR-derived 

digital elevation model, and the locations of the stream thalweg, river banks, approximate centerlines 

of overbank areas, and cross-sectional lines.
36 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

For these sites and these sites only, Manning’s n

for the main channel was estimated by the equation 

Jarrett (1985) developed for high-gradient streams:

where

The values of Manning’s n determined from this 

equation ranged from 0.0452 to 0.0834 for the 

Catacamas study site and from 0.0643 to 0.1456 for the 

upper El Progreso study site.

HEC-RAS provides two options in the crosssection editor that can dramatically alter the simulated 

extent of flooding, and they were used extensively in 

the models for Honduras. The options are the 

placement of levees and designation of areas in the 

overbank subsections as being ineffective for 

conveying floods. Levees will not allow simulated 

discharges to extend outside of their locations as long 

as the water surface does not exceed user-supplied 

elevations. Without the levee option, HEC-RAS will 

inundate everything in the cross section below the 

simulated water surface. It is common to have areas on 

the landward side of a natural or constructed levee be 

lower than the water surface in the main channel during 

a flood, but be protected from flooding by the levee. To 

simulate these conditions, simulated levees were 

located on cross sections where areas below the 

simulated water surface were surrounded by high 

ground that was continuous along a reach. Where high 

ground is not continuous, flood waters may be 

separated from the main channel along a reach and not 

be actively conveyed by the stream. These wet portions 

of the cross section will have zero or near-zero water 

velocities. By using the ineffective flow option, 

inundated areas separated from the main body of the 

river are shown as areas of inundation, but they are not 

included in the hydraulic computations.

The first hydraulic model computations for a 

study site were always made assuming subcritical flow. 

These calculations started with a user-specified 

boundary condition at the downstream end and 

proceeded upstream. In this study the downstream 

boundary condition was calculated as normal depth 

using the average channel slope near the boundary as 

an approximation of the energy slope. At some cross 

sections the model could not obtain a solution and 

consequently defaulted to a critical-depth solution. 

When this occurred, the model was rerun using the 

mixed-flow-regime option in HEC-RAS with a usersupplied upstream boundary condition. The mixedflow-regime option performs both subcritical and 

supercritical calculations. At cross sections with valid 

subcritical and supercritical solutions, the solution with 

the highest specific force is considered the correct 

solution (U.S. Army Corps of Engineers, 1998b,

p. 4-6 to 4-8).

Modeling flow through bridges requires the user 

to supply four cross sections. Two are located adjacent 

to the upstream and downstream bridge openings, 

generally at the toe of the road embankment. Upstream 

of the upstream bridge-opening cross section, another 

cross section is located where the cross section is fully 

effective and the flow lines begin to contract towards 

the bridge opening. The fourth cross section is located 

downstream of the downstream bridge-opening cross 

section where the flow has fully expanded after 

becoming contracted through the bridge opening. In 

addition to the four user-supplied cross sections, two 

internal bridge cross sections are created automatically 

by the HEC-RAS program. Most bridge sites were field 

surveyed to provide station-elevation data for defining 

the bridge openings, piers, and bridge-deck elevations. 

Measurements were usually made on only one face of a 

bridge and assumed to be the same at the other face 

unless it was apparent that the geometries of the two 

faces were different. Sometimes the most upstream or 

most downstream cross sections were field surveyed 

and entered into the hydraulic model. Otherwise, the 

cross-section data obtained from the LIDAR DEM was 

used. Hydraulic computations through the bridge used 

the standard energy equation when the water surface 

was below the low-chord elevation at the bridge deck 

or above the low-chord and the tailwater was 95 

percent or more submerged. If the water surface was 

above the low-chord elevation and the tailwater was 

less than 95 percent submerged, pressure-flow 

equations were used. Weir flow computations were 

used to calculate flow over the bridge. 

= Manning’s ;

= the frictional slope; and.

= the hydraulic radius.

n 0.39Sf

0.38R–0.16 =

n n

Sf

R
Summary 37

SUMMARY

A review of the surface-water hydrology for 

Honduras shows runoff and flooding fluctuating with 

the wet season, May through October, and the dry 

season, November through April. Two-thirds of the 

annual peak flows occur during August through 

October, with most of the largest floods resulting from 

hurricanes and tropical depressions. Typically, the 

influence of individual storms varies throughout the 

different regions of the country. However, the floods 

caused by Hurricane Mitch in October 1998 caused 

widespread damage, and in most cases, where the 

Hurricane Mitch peak flow was estimated near a longterm gage, it was much larger than any previously 

recorded peak flow. The devastation caused by the 

Hurricane Mitch floods underscored a need for a 

national program of flood-hazard mapping. The design 

discharge selected for this national program is the peak 

flow with an average return interval of 50 years (a 0.02 

probability of being equaled or exceeded in any year). 

The selection was based on conversations with USAID 

and the Honduran Public Works and Transportation 

Ministry. This report describes the statistics used for 

estimating the 50-year flood discharge and describes a 

flood-hazard mapping methodology that was used to 

create flood-hazard maps of 15 selected municipalities. 

Annual peak-flow data, annual maximum daily 

and mean annual precipitation, and a country-wide 

digital elevation model (DEM) was the primary data 

for hydrologic analysis. The estimated peak flow for 

various exceedance probabilities were calculated for 

34 sites with long-term annual peak-flow data. Results 

from statistical analysis of the daily maximum rainfall 

provided the data to create a contour map of the daily, 

50-year precipitation for Honduras. Basin 

characteristics for the 34 long-term stream-gaging 

stations were generated from a DEM, the daily, 50-year 

precipitation map, and an existing map of mean annual 

precipitation. A step-wise regression analysis found 

drainage basin area and mean annual precipitation to be 

the most significant variables to estimate the 50-year 

flood discharge. A regression equation using these 

explanatory variables was formulated to estimate the 

50-year flood discharge with a standard error of 

prediction of 71.3 percent. A Geographic Information 

System (GIS) was constructed to facilitate the use of 

the regression equation for all streams in the country.

Topographic information for the floodplains at 

the 15 municipalities was gathered in February and 

March 2000 using an airborne Light Detection and 

Ranging (LIDAR) system to create a high-resolution 

DEM of each site. The DEMs were processed with 

vegetation-removal filters to created a bare-earth 

representation of the floodplain while retaining 

buildings. The filter was mostly successful, although 

some regular crop patterns (like orchards) were not 

entirely removed. Triangular Irregular Networks (TIN) 

were created from the DEMs so that the HEC-GeoRAS 

GIS software package could process the topographic 

data to obtain station elevation data along cross 

sections for input to a hydraulic model. Field surveys 

verified the accuracy of the LIDAR and supplemented 

the topographic information with the bridge-opening 

geometry needed for the hydraulic models. Field 

verification of the DEMs had mean absolute errors 

ranging from -0.57 to 0.14 meter in the vertical 

dimension. Output from the hydraulic models was used 

as input to HEC-GeoRAS to create area- and depth-ofinundation maps.

Surface-water profiles for the design flood 

discharge were simulated with a one-dimensional, 

steady-flow step-backwater hydraulic model embedded 

in the HEC-RAS software package developed by the 

U.S. Corp of Engineers. After the stream thalweg, 

banks, approximate overbank centerlines, and crosssection data are imported into HEC-RAS from HECGeoRAS, several parameters are added or edited to 

construct the final model. Default expansion and 

contraction coefficients were used except at abrupt 

changes where larger coefficients were used to estimate 

the energy losses due to expansion or contraction. The 

models required the placement of “levees” and 

“ineffective flow area” boundaries in the individual 

cross sections to prohibit simulated flooding at low 

areas not in the channel that are protected by high 

banks or levees (“levees”) or to remove areas of 

inundation from the flow calculations that are separated 

from the main channel, but still depict these areas as 

flooded (ineffective flow areas). Bridges are included 

in the model by incorporating field-survey data of the 

bridge opening and dimensions into bridge cross 

sections and selecting whether the energy equation or 

pressure-flow and weir-flow computations should be 

used. 
38 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

Roughness coefficients are estimated for the main 

channel and overbank areas of each cross section from 

site visits, photos, and the LIDAR-derived shadedrelief images that provided a relative comparison of 

vegetation densities. No observed high-water marks 

were available to calibrate the roughness coefficients. 

At two selected municipalities, Santa Rosa de 

Aguán and La Lima, the full extent of the 50-year 

flooding extended well beyond the area of the 

topographic survey. At Santa Rosa de Aguán the 

alluvial channel is constantly shifting its course, and 

combined with the fact that the surveyed area was too 

small, no model of this site was constructed. Maps of 

area and depth of inundation were generated from the 

elevation of the estimated 50-year storm tide. In the 

case of La Lima, the capacity of the main channel in 

town was determined by trial and error using the model 

and maps of the area and depth of inundation of this 

flow were made.

REFERENCES CITED

Benson, M.A., and Dalrymple, Tate, 1967, General field and 

office procedures for indirect discharge measurements: 

U.S. Geological Survey Techniques of Water-Resources 

Investigations, Book 3, Chap. A1, 30 p.

Central Intelligence Agency, 2001, The World Factbook 

2001, accessed October 1, 2001, at URL 

<http://www.cia.gov/cia/publications/ 

factbook/geos/ho.html>.

Centro de Estudios Hidrográficos del CEDEX, 1999, 

Convenio para la realización de trabajos y actividades 

de cooperación técnica, en materia de medio ambiente e 

infraestructuras, con los paises de Centroamérica 

afectados por el Huracán Mitch, II. Informe de los 

proyectos del convenio, Proyecto Honduras 6, 

Elaboración de términos de referencia para la 

formulación de un programa de control de erosión e 

inundaciones para el corredor Santa Rita-El Progreso 

(Cordillera de Mico-Quemado), vol. 1: Madrid, Spain. 

Report prepared for Ministerio de Asuntos Exteriores, 

Secretaría de Estado de Cooperación Internacional y 

para Iberoamérica Agencia Española de Cooperación 

Internacional (AECI).

Consorcio Lahmeyer International, 1998, Estudio de 

factibilidad y diseño final proyecto obras prioritarias en 

zonas de alto riesgo, Chamelecón Pueblo-Choloma: 

Report prepared for Gobierno de Honduras, Comisión 

Ejecutiva Valle de Sula.

Environmental Systems Research Incorporated, 2000, 

ArcDoc Version 8.0.2: Redlands, California, 

Environmental Systems Research Incorporated, On-line 

Help distributed with Arc/Info software.

Hardison, C.H., 1971, Prediction error of regression 

estimates of streamflow characteristics at ungaged sites: 

U.S. Geological Survey Professional Paper 750-C, 

p. C228-236.

Jarrett, Robert D., 1985, Determination of roughness 

coefficients for streams in Colorado: U.S. Geological 

Survey Water-Resources Investigations Report 85-

4004, 54 p.

Kimberlain, Todd, 2001a, Probability of a named storm: 

United States Department of Commerce, National 

Oceanic and Atmospheric Administration, Atlantic 

Oceanographic and Meteorological Laboratory, 

Hurricane Research Division, Map on-line on the World 

Wide Web, accessed October 1, 2001, at URL 

<http://www.aoml.noaa.gov/hrd/tcfaq/ 

tcfaqG.html#G12>.

———2001b, Probability of an intense hurricane: United 

States Department of Commerce, National Oceanic and 

Atmospheric Administration, Atlantic Oceanographic 

and Meteorological Laboratory, Hurricane Research 

Division, Map on-line on the World Wide Web, 

accessed October 1, 2001, at URL 

<http://www.aoml.noaa.gov/hrd/tcfaq/ih_prob.gif>.

Kirby, William, 1981, Annual flood frequency analysis using 

U.S. Water Resources Council guidelines (Program 

J407), Chapter I, Section C of WATSTORE user’s 

guide: U.S. Geological Survey Open-File Report 

76-435, vol. 4, p. C-1 to C-57.

Landsea, C.W., 1996, FAQ: Hurricanes, Typhoons, and 

Tropical Cyclones — Part I: Definitions, basic 

questions, and basin information, accessed October 1, 

2001, at URL <.http://cirrus.sprl.umich.edu/ 

wxnet/hurricane/TCfaq.html#1

Linsley, R.K., Jr., Kohler, M.A., and Paulhus, J.L.H., 1982, 

Hydrology for engineers (3rd ed.): New York, 

McGraw-Hill, 508 p.

Modesto Canales, J., ed., 1998, Átlas Geográfico de 

Honduras, edición 1997-1998: Edificio Torres Fiallos, 

Tegucigalpa, Honduras, 48 p.

Rappaport, Edward N., and Fernandez-Partagas, Jose, 2001, 

The deadliest Atlantic tropical cyclones, 1492-present: 

NOAA Technical Memorandum, National Hurricane 

Center, Tropical Prediction Center home page, on-line 

on the World Wide Web, accessed March 16, 2001, at 

URL< http://www.nhc.noaa.gov/pastdeadly.html>, 

HTML format.

Sir William Halcrow and Partners, 1985, Hydraulic master 

plan for the Aguán River Basin, Final Report, vol. 4,

various pagination.
References Cited 39

Tasker, G.D., and Stedinger, J.R., 1989, An operational GLS 

model for hydrologic regression: Journal of Hydrology, 

vol. 3, Nos. 1-4, p. 361-375.

U.S. Army Corps of Engineers, 1998a, HEC-RAS, River 

Analysis System user’s manual version 2.2: Hydrologic 

Engineering Center, Davis, California, 320 p.

———1998b, HEC-RAS, River Analysis System hydraulic 

reference manual version 2.2: Hydrologic Engineering 

Center, Davis, California, 237 p.

———2000, HEC-GeoRAS, An extension for support of 

HEC-RAS using ArcView user’s manual: Hydrologic 

Engineering Center, Davis, California, 96 p.

U.S. Department of Agriculture, 1986, Urban hydrology for 

small watersheds, Technical Release 55: Soil 

Conservation Service, Washington, D.C.

U.S. Department of State, 2001, Climate information as 

reported in Airman magazine, accessed October 3, 2001 

at <http://www.af.mil/news/airman/0800/hondusb.htm.

U.S. Water Resources Council, 1981, Guidelines for 

determining flood flow frequency: U.S. Water 

Resources Council Bulletin 17B, 28p., 14 appendixes.
TABLE 12
Table 12 41

Table 12. Annual maximum instantaneous streamflow discharge (peak flow) for streamflow discharge stations in Honduras 

with 10 years or more of annual peak-flow records

[Discharge in cubic meters per second; --, no data]

Río Aguán Basin Río Choluteca Basin

Río Nacaome 

Basin

Year

Aguán en

La Isleña

Aguán en

Sabana

Larga

Manguille en

La Enyeda

Choluteca en

Puente

Choluteca

Choluteca en

Paso

La Ceiba

Choluteca en

Hernando

Lopez

Nacaome en

Las

Mercedes

1954 -- -- -- -- -- 652 --

1955 -- -- -- -- -- 247 --

1956 -- -- -- -- 88.6 155 --

1957 -- 100 -- -- 179 116 --

1958 -- 156 -- -- 730 482 --

1959 -- -- -- -- 282 105 --

1960 -- -- -- -- -- -- --

1961 -- -- -- -- -- -- --

1962 -- -- -- -- -- -- --

1963 -- -- -- -- -- -- --

1964 -- -- -- -- 200 149 --

1965 -- -- -- -- 426 962 2,089

1966 -- -- -- -- 323 120 693

1967 -- -- -- -- 75.6 60.5 384

1968 -- -- -- -- 503 543 1,167

1969 -- -- -- -- -- 654 1,490

1970 -- -- -- -- -- 750 1,378

1971 -- -- -- -- -- 498 1,900

1972 -- 563 -- -- -- -- 865

1973 -- 70.4 -- -- -- 395 1,496

1974 -- -- -- -- -- 578 3591

1975 -- -- -- -- -- 212 904

1976 -- -- -- -- 677 275 404

1977 -- 107 -- -- 493 363 695

1978 -- 160 -- -- 168 109 610

1979 -- 207 -- 1,097 301 169 1,850

1980 339 598 780 1,686 481 494 --

1981 552 185 916 1,607 258 -- --

1982 584 156 191 1,218 121 101 --

1983 197 220 199 391 277 169 --

1984 434 251 221 807 -- 353 --

1985 11.9 47.0 1,504 2,132 60.0 65.2 --

1986 30.2 135 -- 1,041 429 254 --

1987 144 173 -- 457 410 246 --

1988 119 193 -- 1,912 592 941 --

1989 30.1 750 -- 1,855 529 392 --

1990 -- -- -- -- -- -- --

1991 -- -- 102 -- 120 62.8 --

1992 57.6 117.8 -- 498 371 101 --

1993 610 292 267 1,470 424 229 --

1994 -- 51.6 173 346 148 86.0 --

1995 -- 138 131 16,20 414 -- --

1996 -- -- -- 721 323 -- --

1997 -- -- -- -- -- -- --

1998 -- -- -- 15,500 7,500 6,310 9,300
42 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

Table 12. Annual maximum instantaneous streamflow discharge (peak flow) for streamflow discharge stations in Honduras 

with 10 years or more of annual peak-flow records—Continued

Río Sico Basin

Río Chamelecón

Basin

Year

Palos

Blanco

en Puente

Tonjagua

en Tonjagua

Tapalapa

en

Chumbagua

Chiquila

en Carretera

Chamelecón

en Puente

Chamelecón

en La Vergona

Chamelecón

en La Florida

1954 -- -- -- -- -- -- --

1955 -- -- -- -- 585 -- --

1956 -- -- -- -- 487 -- --

1957 -- 28.0 -- -- 317 -- --

1958 -- 23.0 -- -- 427 -- --

1959 -- -- -- -- -- -- --

1960 -- -- -- -- -- -- --

1961 -- -- -- -- -- -- --

1962 -- -- -- -- -- -- --

1963 -- -- -- -- -- -- --

1964 -- -- -- -- -- -- --

1965 -- 105 -- -- 392 -- --

1966 -- 29.2 -- -- 341 -- 35.2

1967 201 36.1 -- -- 561 -- 11.3

1968 166 60.4 -- -- 552 -- 70.1

1969 209 29.7 -- -- 833 -- 78.9

1970 86.0 -- 96.5 -- 465 -- 85.4

1971 143 -- 89.3 19.2 322 54.7 90.1

1972 -- -- 114.9 5.96 162.7 -- --

1973 -- -- 41.5 7.73 -- 71.6 42.1

1974 -- -- 120 18.0 -- 152 74.3

1975 -- -- 55.5 21.7 -- 57.0 36.9

1976 112 41.8 71.3 145 -- 219 57.6

1977 455 34.7 44.5 -- -- 97.0 32.2

1978 235 46.1 86.8 -- -- 236 576

1979 444 148 106 -- 106.9 298 2,032

1980 373 29.1 72.1 49.8 483 162 507

1981 76.4 -- 127 33.5 903 190 75.7

1982 -- 133 91.0 9.22 702 190 68.0

1983 759 71.0 -- 28.2 822 192 67.2

1984 166 8.51 -- 48.8 429 200 198

1985 49.6 -- 33.3 63.8 206 200 908

1986 -- 25.6 59.3 10.8 349 398 129

1987 -- -- 54.6 34.2 218 113 229

1988 -- -- -- 1636 479 283 39.0

1989 -- -- -- 21.7 476 189 261

1990 -- -- -- 117 1,000 119 88.4

1991 -- -- -- 45.7 243 189 624

1992 -- -- -- 11.8 271 225 341

1993 -- -- -- 41.2 1,060 228 87.3

1994 -- -- -- 7.83 -- 386 --

1995 -- -- -- 33.2 -- 439 --

1996 -- -- -- 80.2 1,271 522 --

1997 -- -- -- -- -- 185 --

1998 -- -- -- -- -- -- --
Table 12 43

Table 12. Annual maximum instantaneous streamflow discharge (peak flow) for streamflow discharge stations in Honduras 

with 10 years or more of annual peak-flow records—Continued

Río Patuca

Basin

Year

San Antonio

en

Los Almendros

Juticalpa

en

El Torito

Guyape

en

Guyabilis

Telica en

Puente Telica

Jalán en

El Delirio

Jalán en

La Isleta

San Francisco

en

Paso Guyambre

1954 -- -- -- -- -- -- --

1955 -- -- 296 128 130 -- --

1956 -- -- 377 246 344 -- --

1957 -- 46.6 728 225 299 -- --

1958 -- 106 512 254 86.1 -- --

1959 -- 21.4 -- 143.6 -- -- --

1960 -- -- -- -- -- -- --

1961 -- -- -- -- -- -- --

1962 -- -- -- -- -- -- --

1963 -- -- -- -- -- -- --

1964 -- -- 145 -- -- -- --

1965 -- 91.7 142 168 408 -- --

1966 -- 642 1,947 340 135 -- --

1967 103 764 628 -- 472 199 --

1968 -- 1,060 1,338 -- 345 388 --

1969 -- 1,920 174 -- 330 368 33.5

1970 -- 351 374 -- 719 196 --

1971 -- 152 108 -- 103 398 --

1972 -- 598 138 -- 268 184.0 --

1973 -- 83.9 133 -- 269 398 --

1974 34.9 480 869 -- 490 185 --

1975 76.5 149 313 809 520 265 --

1976 512 50.8 373 190 396 268 --

1977 193 289 360 458 234 404 20.7

1978 206 72.8 360 246 512 558 33.5

1979 104 245 1,034 -- 1,042 715 60.8

1980 149 88.8 454 337 280 314 --

1981 374 106 672 436 136 697 --

1982 132 105 389 288 188 332 21.2

1983 43.0 54.3 381 414 201 1,101 72.2

1984 268 89.9 467 251 128 340 46.8

1985 45.4 60.5 321 309 588 268 28.2

1986 67.2 126 94.3 258 217 333 27.1

1987 21.9 88.0 278 521 310 198 30.8

1988 108 182 295 -- -- 357 50.6

1989 -- -- 416 -- -- 357 51.3

1990 -- -- 707 -- -- 245 --

1991 -- 252 516 924 -- 475 --

1992 -- -- 665 207 311 279 30.1

1993 -- 135 238 315 -- 564 --

1994 -- 82.3 167 161 -- -- --

1995 -- 193 1,130 419 -- 505 --

1996 -- 144 428 92.7 -- 222 --

1997 -- 435 373 -- -- 221 --

1998 -- -- -- -- -- -- --
44 Flood-Hazard Mapping in Honduras in Response to Hurricane Mitch

Table 12. Annual maximum instantaneous streamflow discharge (peak flow) for streamflow discharge stations in Honduras 

with 10 years or more of annual peak-flow records—Continued

Río Humuya

Basin

Year

Jacagua

en

Las Vegas

Sulaco 

en

El Sarro

Agua

Caliente

Tascalape

en

El Desmonte

Humuya

en

Guacamaya

Humuya

en

La Encantada

Humuya

en

Las Higueras

1954 -- -- -- -- -- -- 372

1955 -- -- -- -- -- -- 320

1956 -- -- -- -- -- 487 78.1

1957 -- -- -- -- -- 285 155

1958 -- -- -- -- -- 726 354

1959 -- -- -- -- -- -- 472

1960 -- -- -- -- -- -- --

1961 -- -- -- -- -- -- --

1962 -- -- -- -- -- -- --

1963 -- -- -- -- -- -- --

1964 -- -- -- -- -- 407 30.9

1965 -- -- -- -- -- 397 86.1

1966 -- -- -- -- -- 279 112

1967 16.3 -- -- 9.16 695 156 84.7

1968 28.7 -- 489 75.0 867 566 187

1969 50.3 -- 598 45.2 1,662 726 184

1970 60.4 -- 477 83.6 506 512 366

1971 75.5 765 857 14.2 287 346 182

1972 20.7 380 550 14.2 297 143 70.5

1973 23.5 486 950 13.5 918 256 137

1974 84.2 879 883 133 1,860 515 313

1975 79.5 1,180 1,010 -- 822 632 287

1976 70.8 1,460 594 71.3 871 636 313

1977 51.9 744 828 65.7 489 527 287

1978 19.5 418 253 49.8 413 233 86.0

1979 127 640 386 184 1,043 273 184

1980 95.3 1,320 467 26.6 727 581 278

1981 22.7 890 431 52.8 371 475 260

1982 55.2 750 244 52.8 401 362 297

1983 19.8 497 328 43.9 616 398 123

1984 27.4 925 301 384 319 320 336

1985 22.1 1,420 273 51.4 172 90.4 62.9

1986 121 635 266 524 364 92.9 72.0

1987 163 -- 918 -- 864 244 183

1988 -- 1,210 850 -- -- 526 --

1989 20.5 882 329 -- -- 321 --

1990 -- 1,040 845 -- -- 473 --

1991 10.4 1,480 459 -- -- 381 --

1992 12.8 1,190 485 -- -- 154.8 --

1993 70.9 750 408 -- -- 426 --

1994 -- 1184 240 -- -- 196 --

1995 -- 882 666 -- -- 441 --

1996 -- -- -- -- -- 390 --

1997 -- -- -- -- -- 206 --

1998 -- -- -- -- -- 615 --
Table 12 45

Table 12. Annual maximum instantaneous streamflow discharge (peak flow) for streamflow discharge 

stations in Honduras with 10 years or more of annual peak-flow records—Continued

Río Ulua

Basin

Year

Funez

en

San Nicolás

Grande

Otoro en

La Gloria

Jicatuyo

en

Ulapa

Ulua

en

Chinda

Ulua

Puente

Pimienta

Ulua

en

Remolino

1954 -- -- -- -- -- --

1955 -- 174 -- 1,466 2,050 --

1956 -- 132 -- 1,074 1,390 --

1957 -- 237 -- 1,870 2,590 --

1958 -- 183 -- 2,280 3,020 --

1959 -- -- -- 2,508 -- --

1960 -- -- -- -- -- --

1961 -- -- -- -- -- --

1962 -- -- -- -- -- --

1963 -- -- -- -- -- --

1964 -- -- -- -- -- --

1965 -- 270 -- 1,743 1,270 --

1966 -- 181 -- 1,922 1,040 --

1967 -- 149 -- 1,564 1,720 --

1968 50.6 999 -- 2,330 1,200 --

1969 66.3 239 -- 2,171 2,750 --

1970 82.2 154 -- 1,910 998 --

1971 124 154 685 1,275 943 579

1972 45.9 158 584 1,245 845 425

1973 17.7 176 1,006 2,185 1,370 840

1974 54.9 141 1,092 3,670 2,170 1,500

1975 30.3 804 1,030 3,260 1,550 2,060

1976 38.1 764 1,476 2,506 2,270 2,040

1977 57.6 414 494 1,630 1,400 1,340

1978 22.6 183 1,099 2,181 2,100 1,000

1979 746 192 1,460 2,678 1,760 890

1980 436 115 -- 2,615 2,680 928

1981 75.4 379 -- 1,115 1,690 644

1982 137 654 1,374 -- 1,550 1141

1983 39.1 364 953 2,245 1,830 2,480

1984 203 356 1,075 -- 1,650 1,512

1985 13.3 173 911 3,175 1,040 419

1986 572 170 768 1,515 983 788

1987 325 164 999 1,152 1,495 590

1988 519 267 1,600 3,460 2,774 2,640

1989 47.4 151 2,115 3,287 1,903 1,124

1990 192 -- 13,463 -- 2,480 3,780

1991 -- -- 915 1,504 1,570 1,490

1992 127 52.6 951 2,117 2,270 --

1993 512 55.7 1,215 3,083 3,069 --

1994 107 140 897 1,569 1,660 --

1995 188 140 1,056 2,420 2,389 --

1996 -- -- 1,716 1,912 2,009 --

1997 -- -- -- -- -- --

1998 -- -- -- 11,000 -- --

1Low or high outlier.
P

rintedonrecycledpaper

FLOOD-HAZARD MAPPING IN HONDURAS IN RESPONSE TO HURRICANE MITCH WRIR 01-4277 Mark C. Mastin