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Narrowing Gaps in Water Resources Management: Satellite Rainfall Data Study in Bangladesh

This study aims to develop a flood forecasting model using remotely sensed data in order to mitigate the impact of annual flooding in Bangladesh. The study analyzes satellite rainfall data, examines its accuracy, and compares it with measured discharge. The results show promise for flood forecasting and highlight the need for further improvements in model performance and data validation.

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Narrowing Gaps in Water Resources Management: Satellite Rainfall Data Study in Bangladesh

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  1. A Step Towards Narrowing the Gaps in the field of Water Resources Management by Satellite Estimated Rainfall Data Mohammad Khaled Akhtar Bangladesh

  2. Outline: • Introduction & background • Objective • Methodology • Data collection & processing • Model development • Result analysis • Summary

  3. Introduction & Background: • Flooding is an annual recurrent event in Bangladesh • Total protection against flood is neither possible nor feasible • A basin model with reasonable accuracy could alleviate the problem to some extent by flood forecasting and disaster preparation application

  4. Introduction & Background: • Area affected by flood – 38 districts • Crop Damage: • fully-793,140 hectares • partly- 656,187 hectares • Affected People –10 million; • People taking refuge – 373,939 in 1601 shelters; • Housing units destroyed – 89,048 • Deaths – 192. (Year: August 2007) Flood Damage:

  5. Introduction & Background Study Area: Area: 583x103 km2 Length: 2,900km Area: 65 x 103 km2 Length: 930km Area: 907x103 km2 Length: 2,500km Bangladesh (145,000 km2)

  6. Introduction & Background Causes of flood: • Low topography of the country with excessive runoff from the drainage basins (92% of its located outside Bangladesh) • Coast line is conical in shape • Backwater effect and poor drainage facilities

  7. Objectives: To develop the GBM basin model using remotely sensed data, which can provide enough flood information few days ahead Specific objectives: • To develop a simulation model of the GBM basin with remotely sensed data • To compare the measured discharge with the total amount of rainfall • To simulate basin discharge under climate change scenarios

  8. Catchment parameter Rainfall TRMM RR model Temperature Internet Evaporation Model output Field observation (BWDB) Result comparison Discharge Methodology:

  9. Data Collection & Processing: Data sources: • Rainfall (TRMM- 3B42RT) • Discharge (BWDB, IWM) • DEM (IWM, USGS) • Evaporation (NASA) • Soil Type (FAO, ISRIC) • Land-use (USGS)

  10. Data Collection & Processing:

  11. Model Development:

  12. Model Development:

  13. Model Result: Area: 583x103 km2 Length: 2,900km Area: 65 x 103 km2 Length: 930km Area: 907x103 km2 Length: 2,500km Bahadurabad Hardinge bridge

  14. Result analysis:

  15. Result analysis:

  16. Result analysis:

  17. Model Result: Area: 583x103 km2 Length: 2,900km Area: 65 x 103 km2 Length: 930km Area: 907x103 km2 Length: 2,500km Bahadurabad Hardinge bridge

  18. Result analysis:

  19. Result analysis:

  20. Result analysis:

  21. Result analysis: Sensitivity test: In this study sensitivity analysis is carried out to have some idea, how model will perform if present time data is used as future data when rainfall forecast data is not available.

  22. Result analysis: Sensitivity test:

  23. Result analysis: Sensitivity test: Performance of 3 to4-day forecast is quit acceptable for this case

  24. Result analysis: • Impact of climate change: Few simple model simulations were carried out to see the impact of climate change on the basis of changing rainfall volume even though the model is not well calibrated. A very crude estimation is applied by increasing rainfall by 20% and 40% and a decrease of rainfall by 20% for Ganges basin.

  25. Result analysis: • Impact of climate change:

  26. Summary: • The satellite derived rainfall data is very promising • Yearly accumulated volume of rainfall over the Ganges basin and generated runoff at the outlet varies within acceptable range. • On the other hand, the accuracy of satellite measured rainfall over Brahmaputra basin is beyond the acceptable range • Sensitivity analysis gives some indication about the forecasting condition, if no rainfall forecast is available, which is very encouraging in the field of flood forecasting • Further efforts are needed to improve the model performance to make it operational

  27. Summary: • Consistency and accuracy of the satellite data needed to be checked before further calibration especially for the Brahmaputra basin area • More detailed analysis should be carried out to say anything concrete on the generated runoff of GBM basin considering the climate change scenario • It is hoped that there will be significant improvement in the model performance if validated rainfall data can be used

  28. Thank You

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