Integrating remote sensing-derived evapotranspiration and ground-monitored discharge data for improvement of hydrologic modeling : a case study of the Sekong River Basin | |
| Author | Raksmey Ang |
| Call Number | AIT Thesis no.WM-19-07 |
| Subject(s) | Evapotranspiration--Cambodia--Sekong River Basin--Remote sensing Hydrologic models--Data processing |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Water Engineering and Management |
| Publisher | Asian Institute of Technology |
| Abstract | Hydrologic modeling knowledge is greatly beneficial for sustainable water resources development. Hydrologists use hydrological models for their water resources studies including both quantity and quality of water in the river basins. However, the ability of perfromance of those hydrlogical models – especially those used for streamflow simulation, is constrained by the accessible observed flow data both quality and quantity of data used to calibrate hydrologic model. Nowadays most of the hydrological models are calibrated using only ground-monitored streamflow. Consequently, the vast part of hydrlogical process particularly in unsaturated zone might not be calibrated. This study is to analyze the benefit of integrating remotely sensed evapotranspiration into process of hydrlogical model calibration. A joint-calibration approach employing both remote sensing-derived evapotranspiration and ground-monitored streamflow data will be compared with a conventional ground-monitored streamflow-only calibration approach through physical-based hydrological, Soil and Water Assessement Tool (SWAT), model setups. SWAT model calibration and validation were performed by integrating remote sensing-derived actual evapotranspiration data (Global Land Evaporation Amsterdam Model (GLEAM)) and observed streamflow for the Sekong River Basin (28,816 km2). Model joint-calibration performed well compared to the conventional technique, particularly monthly time steps. There were increase in NSE and R2 on average of 3% compared with streamflow-only calibration models. There was much improvement at the upstream part compared with downstream area. It might be the result of necessary of evapotranspiration information is needed to include in model calibration approach at the unsaturated zone. Temporally, multi-variable models can improve much in high flow compared to low flow simulation. According to the student t tests, it was found that applying remote sensing-derived evapotranspiration data along together with the ground-monitored streamflow to do SWAT model calibration brought statistically significant improvement of model perfromance leading to better streamflow simulation. Next, the impacts of satellite-based evapotranspiration on model perfromance at both gauged and ungauged locations were also defined. The model perfromance improvement at “ungauged” was more noticeable than “gauged” locations. This can be the limitation of streamflow gauges; thus, the spatially distributed evapotranspiration information becomes the only information for internal sub-catchments. The p-values of the student t test for ‘‘ungauged” locations were 0.014 for NSE and 0.00001 for R2. The p-values for gauged locations were 0.008 for NSE and 0.009 for R2, which denote that the model perfromance was significant increase with a significance level of both 0.05 and 0.01. Eventually, satellite-based evapotranspiration was evaluated its suitability for streamflow simulation. For “gauged” location, evapotranspiration calibration model is good enough to use for streamflow simulation study, where the gauged streamflow data is not available. However, streamflow simulation at ‘‘ungauged” locations were found to be unsatisfactory. All statistic values indicate that the streamflow simulations are not good. Therefore, the additional evapotranspiration data into batch calibration substantially can minimize equifinality and prediction uncertainty in a physical-based hydrologic, SWAT, model. |
| Year | 2019 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Water Engineering and Management (WM) |
| Chairperson(s) | Shrestha, Sangam; |
| Examination Committee(s) | Babel, Mukand Singh;Virdis, Salvatore G.P. |
| Scholarship Donor(s) | Kurita Water and Environment Foundation, Japan; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2019 |