Assimilation of remotely sensed soil moisture into hydrological modeling : a case study in the Mahanadi Basin, India | |
| Author | Behara, Soumya Sucharita |
| Call Number | AIT Thesis no.WM-17-12 |
| Subject(s) | Hydrologic models--India--Mahanadi Basin Hydrologic models--Remote sensing |
| Note | A thesis submitted in partial fulfilment of the requirements for the degree of Master of Engineering in Water Engineering and Management |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. WM-17-12 |
| Abstract | Hydrologic data assimilation technique provides the best analysis estimators by merging the strengths of modelled state (forecast) and the satellite derived observations to achieve higher accuracy and continuous improvement in hydrological estimates/forecasts. This research performs Kalman filtering in macroscale semi distributed hydrological model Variable Infiltration Capacity (VIC) model for Mahanadi Basin in India. In the present study it has been envisaged to set up a fully calibrated and validated distributed physical based hydrological model for the Mahanadi River Basin, to estimate runoff, evapotranspiration, baseflow and soil moisture on daily time scale for the entire basin. The model is parameterized using traditionally observed and remote sensing data. Primarily parameter sensitivity analysis is done for the meteorological forcing parameters of VIC considering four different scenarios. VIC requires at least four parameters in forcing namely, Tmax, Tmin, Prec and wind speed. The Water balance component deviation observed in runoff and evapotranspiration are +7.8% and +2.1% respectively and change in discharge is +1.25% with and without forcing wind speed parameter. Cloud cover factor has no influence on the water budget components and discharge of the basin. The calibration of VIC model is done using observed discharge data at Tikarapara gauging station (main outlet), soil parameters determined after calibration are binfilt =0.4, Ds=0.001 and Ws=0.9; validation of the calibrated model is done by comparing model simulated discharge with observed long-term river discharge data at Jhondra, Kantamal, Kotni and Rajim gauging stations in the sub basin and the performance indices have also been determined. The present study gives 0.95 coefficient of determination, 0.99 Nash-Sutcliffe model efficiency coefficient and -0.039 relative error between model simulated discharge and observed discharge. Soil moisture is very important variable for both the water and energy balance modes of the model; small-scale soil moisture conditions have a great impact on agriculture, ecology and hydrology; hence this crucial variable has been chosen for the assimilation study. Kalman Filtering has been used to assimilate satellite observed soil moisture data in the VIC model for The Mahanadi Basin. Assimilated variable (soil moisture) is used to generate multilayer soil moisture regime. Kalman gain has been calculated for 208 grids covering the entire basin. Analysis is generated for the calculated Kalman gain matrix and compared with rainfall events in which assimilated soil moisture behaviour is studied and compared to without assimilation case. Soil Moisture is assimilated for the entire month of August in 2010. Water balance for assimilated case draws attention on the importance of hydrologic data assimilation. The impact of data assimilation on the accuracy of hydrological parameter estimation is also evaluated. An improved data set (maps) for different hydrological parameters has been developed on a daily basis which can be used as an important initialization variable for large-scale weather forecasts and climatic predictions in the basin. |
| Year | 2017 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. WM-17-12 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Water Engineering and Management (WM) |
| Chairperson(s) | Babel, Mukand Singh |
| Examination Committee(s) | Shrestha, Sangam;Andriyas, Sanyogita;Nikam, Bhaskar Ramchandra |
| Scholarship Donor(s) | AIT Fellowship |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2017 |