Leveraging WRF-Hydro to improve Thailand’s streamflow forecasting capabilities | |
| Author | Nur, Ridwan Mohammed |
| Call Number | AIT Thesis no.WM-24-02 |
| Subject(s) | Streamflow--Thailand-- Forecasting Hydrologic models |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Water Engineering and Management, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis; no. WM-24-02 |
| Abstract | This study evaluates the applicability of the Weather Research and Forecasting Hydrological model (WRF-Hydro) for streamflow simulation in the lower Chao Phraya River Basin (CPRB) of Thailand. In the face of increasing climatic variability and the critical need for accurate streamflow forecasting and water resource management, a distributed hydrological approach was adopted. The study used the standalone (uncoupled) WRF-Hydro Noah-MP LSM to simulate river discharge with GFS 6- hourly analysis cycle forcing for the first time in this tropical region. It utilized datasets from four in-situ stations to develop a model for estimating river discharge. The study primarily focused on evaluating the effectiveness of the WRF-Hydro model in the context of water resources management for the study area. In the default simulation, Stations C.3 and C.13 showed reasonably good model performance (KGE of 0.77 and 0.73, respectively), while Stations C.2 and C.29 highlighted significant areas for improvement (KGE of 0.28 and 0.42, respectively), particularly in accurately capturing peak discharge events and managing frequent fluctuations. The underestimations at Stations C.2 and C.29 can be attributed to the inadequate representation of unaccounted human activities and reservoir operations. GFS forecasts perform well at shorter lead times (95-96% accuracy for up to 24 hours) and degrade at longer ones (85% to 95% accuracy for three days, and 65-80% for subsequent days); the overall performance is commendable. The GFS forcing correlated better with the timing of observed data but tended to be underestimated, while the IMERG model showed less correlation in timing. The Dynamically Dimensioned Search (DDS) algorithm was applied for calibration. Validation allowed the dynamics of the lower CPRB to be studied and compared. Good results in terms of KGE were achieved at all stations (0.43 to 0.79) using default simulation. During the calibration, it improved (0.39 to 0.86). The model demonstrates strong foundational accuracy, capturing the general trends and timing of peak discharges effectively. |
| Year | 2024 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis; no. WM-24-02 |
| 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) | Natthachet Tangdamrongsub; |
| Examination Committee(s) | Shrestha, Sangam;Shanmugam, Mohana Sundaram; |
| Scholarship Donor(s) | AIT Scholarships; |
| Degree | Thesis (M. Sc.) - Asian Institute of Technology, 2024 |