Climate change projections and impacts assessment on streamflows : a case study of the Sunkoshi River Basin, Nepal | |
| Author | Shrestha, Kiran |
| Call Number | AIT Thesis no.WM-24-09 |
| Subject(s) | Climatic changes--Nepal--Forecasting Climatology--Data processing Climatology--Technique Streamflow--Nepal--Forecasting |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Water Engineering and Management, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis; no. WM-24-09 |
| Abstract | Sunkoshi basin, subbasin of Koshi basin, is one of the most vulnerable basins to climate change. This basin has already been subjected to hydroclimatic extremes. The hydrological regime of the river is expected to undergo significant alterations due to climate change, leading to potential water scarcity and flood hazards in the region. This study was aimed to introduce machine learning in future climate projection and investigating the potential impact of climate change on the streamflow in the basin. Augmented Convolutional LSTM was used in the downscaling and future climate projection. Two CMIP6 climate models namely NOR-ESM-MM and MPI-ESM-HR under SSP2-4.5 and SSP5-8.5 scenarios were selected downscaling. The downscaling from the ML was compared with the downscaled results by quantile mapping. The result showed better downscaling with machine learning (augmented ConvLSTM) as compared with the quantile mapping. The climate projection indicated that the future would have more precipitation during the monsoon and in case of temperature it is expected to increase in the future with minimum temperatures with higher rate. Hydrological modeling was carried out with HEC-HMS to assess the future discharge in the basin under the climate change scenarios. Results showed that river flow is expected to increase during monsoon while decrease in flow during the dry season. Indicators of Hydrological Alteration (IHA) based on SSP2-4.5 and SSP5-8.5 downscaled, indicated there will be significant change (decrease) in the low flows compared to high flows in the future. |
| Year | 2024 |
| Corresponding Series Added Entry | sian Institute of Technology. Thesis; no. WM-24-09 |
| 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) | Shanmugam, Mohana Sundaram;Babel, Mukand S. (Co-Chairperson); |
| Examination Committee(s) | Shrestha, Sangam;Natthachet Tangdamrongsub; |
| Scholarship Donor(s) | Thai Pipe Scholarship;AIT Scholarships; |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2024 |