Natural Hazards

, Volume 43, Issue 2, pp 167–185 | Cite as

Adequacy of satellite derived rainfall data for stream flow modeling

  • Guleid Artan
  • Hussein Gadain
  • Jodie L. Smith
  • Kwabena Asante
  • Christina J. Bandaragoda
  • James P. Verdin
Original Paper

Abstract

Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated.

Keywords

Flood forecasting Satellite-based rainfall estimates Remotely sensed rainfall Hydrologic modeling Calibration Validation Nile River Mekong River 

Abbreviations

AMSU-B

Advanced Microwave Sounding Unit-B

CCD

Cold cloud duration

CN

Soil Conservation Service Curve Number

CPC

Climate Prediction Center

DEM

Digital elevation model

EROS

Center for Earth Resources Observation and Science

FAO

Food and Agriculture Organizations of the United Nations

FEWS

Famine Early Warning System

GDAS

Global Data Assimilation System

GeoSFM

Geospatial Stream Flow Model

GIS

Geographical Information System

GORE

Gauge-observed rainfall estimates

GTS

Global Telecommunications System

IDW

Inverse distance weighted interpolation method

IR

Geostationary thermal infrared

ITCZ

Inter-Tropical Convergence Zone

MOSCEM-UA

Multiobjective Shuffled Complex Evolution Metropolis algorithm

MRC

Mekong River Commission

NSCE

Nash-Sutcliffe Coefficient of Efficiency

NOAA

National Oceanic and Atmospheric Administration

OCHA

United Nations Office for the Coordination of Humanitarian Affairs

PET

Potential evapotranspiration

PM

Passive microwave

RMSE

Root mean square error

SBRE

Satellite-based rainfall estimates

SSM/I

Special Sensor Microwave/Imager

USGS

U.S. Geological Survey

USAID

U.S. Agency for International Development

WMO

World Meteorological Organization

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Copyright information

© Springer Science+Business Media, Inc. 2007

Authors and Affiliations

  • Guleid Artan
    • 1
  • Hussein Gadain
    • 2
  • Jodie L. Smith
    • 1
  • Kwabena Asante
    • 1
  • Christina J. Bandaragoda
    • 3
  • James P. Verdin
    • 4
  1. 1.Early Warning and Environmental MonitoringSAIC Contractor to U.S. Geological Survey (USGS) Center for Earth Resources Observation and ScienceSioux FallsUSA
  2. 2.Regional Centre for Mapping of Resources for Development (RCMRD)NairobiKenya
  3. 3.Utah Water Research LaboratoryUtah State UniversityLoganUSA
  4. 4.Early Warning and Environmental MonitoringU.S. Geological Survey (USGS) Center for Earth Resources Observation and ScienceSioux FallsUSA

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