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Oct 12, 2010 Hydrologic Early Warning System for East Africa Ashutosh Limaye, John Gitau, Eric Kabuchanga CRAM Workshop September 26, 2011.

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Presentation on theme: "Oct 12, 2010 Hydrologic Early Warning System for East Africa Ashutosh Limaye, John Gitau, Eric Kabuchanga CRAM Workshop September 26, 2011."— Presentation transcript:

1 Oct 12, 2010 Hydrologic Early Warning System for East Africa Ashutosh Limaye, John Gitau, Eric Kabuchanga CRAM Workshop September 26, 2011

2 Data and Models Online Maps Visualizations Decision Support Training Partnerships Mapping Fires in Guatemala Mexico Training and Capacity Building Flood Forecasting in Africa SERVIR Strengthen the capacity of governments and other key stakeholders to integrate Earth observations into development decision-making

3 SERVIR Network

4 SERVIR @ CATHALAC City of Knowledge, Panama Inaugurated on February 3, 2005

5 SERVIR-Africa @ RCMRD Nairobi, Kenya Inaugurated on November 21, 2008

6 SERVIR-Himalaya @ ICIMOD Kathmandu, Nepal Inaugurated on October 5, 2010

7 SERVIR Applications have several dependencies: NASA Applied Science Program Agriculture, air quality, climate, disasters, biodiversity, public health, water resources GEO Agriculture, biodiversity, climate, disaster, ecosystems, and human health USAID Climate change adaptation, carbon tracking and GEO focus areas Regional Needs Assessment SERVIR Applications

8 Spatially distributed hydrologic model CREST, developed by University of Oklahoma (based on Variable Infiltration Capacity (VIC) model) Uses near real-time satellite rainfall estimates from TRMM and forecasts from Kenya Meteorological Department (KMD) to produce soil moisture, evapotranspiration & streamflow CREST model SERVIR Hydrologic Modeling KMD East African Domain

9 Spatial extent of CREST runs match the KMD domain (~2800 x 3000 km) Spatial resolution: 1km KMD temperature and rainfall forecasts (QPF), available hourly at 14km spatial resolution, to provide boundary conditions. Forecasted soil moisture, evapotranspiration and streamflow will enable KMD to issue early flood warning, especially in the flood prone watersheds in western Kenya. KMD intends to use the modeled fields to initialize the next model run SERVIR Hydrologic Forecasting 48-hr KMD QPF Sept 20, 2011 18z

10 Last week, we completed the 10-year CREST model run with the available TRMM data. We are calibrating CREST model using observations at Nzoia River in Kenya. We plan to use that calibration for the entire region. Needless to say, we welcome additional observational data to make the model results more robust. Using the 10-yr CREST model run, we have generated a streamflow history for each 1km pixel. We are using that historic data to assess 5 th, 20 th, 80 th and 95 th percentiles for each pixel Based on the four quantiles, we can assess whether the near real time model output falls within one of five categories: Five Quantile Categories Very Wet Wet Normal Dry Very Dry Providing Historic Data Perspective in Near Real Time CREST Model Outputs

11 Additionally, we have made Land Information System (LIS) reanalysis runs with Princeton land surface forcings. The Princeton forcings go back to 1949. In next two months, we plan to use the 10 years of TRMM data to bias-correct the resampled dataset form 1949. It will extend our historic range to over 60 years. Together, the 10-years of TRMM data, and 60-years of Princeton data will provide the historic perspective to contextualize the near real time model estimates and to quantify hydrologic extremes including floods and drought.

12 Incorporating Seasonal Outlook from ICPAC or IRI Ensembles of seasonal forecasts need to be factored in the hydrologic predictions. Historic reanalysis allows us to assess the “normal”, “above” and “below” conditions. Expect to produce the hydrologic forecasts with the seasonal forecasts (target: March 2012).

13 SERVIR-East Africa Products Near Real Time Hydrologic Datasets –Streamflow –Soil moisture –Quantiles of Streamflow, Soil Moisture Short Term Forecasts using KMD QPF –Rainfall –Streamflow –Soil moisture 48-hr Streamflow based on KMD QPF Sept 20, 2011 18z

14 SERVIR Web Portal

15 CREST User Tool Enables time querying of maps Enables time querying of time series Users can download time series data Users can extract time series data for specific sites Supports OGC standards (WMS, WMS-T) Enables extraction of pixel values based on date Continuous enhancements and updates being carried out

16 SERVIR One-Stop Web Portal Geospatial Catalog Interactive Web Maps

17 SERVIR Web Portal

18 Hydrologic Modeling for KMD, Kenya Dept. of Water Resources and Beyond KMD has indicated that this hydrologic modeling information will be useful for their monthly Weather Outlook bulletin. Kenya Department of Water Resources would like to tailor our hydrologic modeling tools to their specific interests of producing three-monthly forecasts. We are seeking additional government and non- governmental groups, including FEWS NET, in sharing our near real time, short term as well as seasonal forecasts.

19 In a Nutshell… SERVIR-East Africa is running an operational hydrologic model using near real time NASA satellite data sets and Kenya Meteorological Department forecasts. In next few months, we plan to include seasonal forecasts in our hydrologic modeling. We anticipate those products to become available on our website ( by the beginning of next We are committed to making our products useful to governmental and non-governmental agencies for their decision making.

20 Thank you Ashutosh Limaye SERVIR Science Applications Lead

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