Mohammad Khaled Akhtar Bangladesh 23/11/2018 A Step Towards Narrowing the Gaps in the field of Water Resources Management by Satellite Estimated Rainfall Data Mohammad Khaled Akhtar Bangladesh

Outline: Introduction & background Objective Methodology 23/11/2018 Introduction & background Objective Methodology Data collection & processing Model development Result analysis Summary

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

Introduction & Background: Flood Damage: 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) November 23, 2018

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) November 23, 2018

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 November 23, 2018

Objectives: Specific objectives: 23/11/2018 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 Climate change and how it affects the sustainability of the current socio-economic system Providing an analysis tool for decision makers to view outcomes of policies and programs Approaches to system modelling that are based on feedbacks between different components of social-economic-climatic system The Overall Point: Through modelling global change, we gain a better understanding of the entire system  We hope, of course, that better understanding translates to better policies

Field observation (BWDB) Methodology: Result comparison TRMM Internet Catchment parameter Rainfall Temperature Evaporation Field observation (BWDB) Discharge RR model Model output November 23, 2018

Data Collection & Processing: Data sources: Rainfall (TRMM- 3B42RT) Discharge (BWDB, IWM) DEM (IWM, USGS) Evaporation (NASA) Soil Type (FAO, ISRIC) Land-use (USGS) November 23, 2018

Data Collection & Processing: November 23, 2018

Model Development: November 23, 2018

Model Development: November 23, 2018

Model Result: Area: 583x103 km2 Length: 2,900km Area: 907x103 km2 Bahadurabad Hardinge bridge November 23, 2018

Result analysis: November 23, 2018

Result analysis: November 23, 2018

Result analysis: November 23, 2018

Model Result: Area: 583x103 km2 Length: 2,900km Area: 907x103 km2 Bahadurabad Hardinge bridge November 23, 2018

Result analysis: November 23, 2018

Result analysis: November 23, 2018

Result analysis: November 23, 2018

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. November 23, 2018

Result analysis: Sensitivity test: November 23, 2018

Performance of 3 to4-day forecast is quit acceptable for this case Result analysis: Sensitivity test: Performance of 3 to4-day forecast is quit acceptable for this case November 23, 2018

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. November 23, 2018

Result analysis: Impact of climate change: November 23, 2018

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 November 23, 2018

Summary: 23/11/2018 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

23/11/2018 Thank You