Climate change and land use transition are the main drivers of watershed hydrological processes. The main objective of this study was to assess the hydrometeorological responses to climate and land use changes in the Jhelum River Basin (JRB), Pakistan. The development of proper climate information is a challenging task. To date, Global Climate Models (GCMs) are used for climate projections. However, these models have a coarse spatial resolution, which is not suitable for regional/local impact studies such as water resources management in the JRB. Therefore, different downscaling methods and techniques have been developed as means of bridging the gap between the coarse resolution global models projection and the spatial resolution required for hydrological impact studies. Statistical Downscaling Model (SDSM) and Long Ashton Research Station Weather Generator (LARS-WG) are selected in this study for downscaling of temperature and precipitation. Both downscaling approaches consider three climate models and two emission scenarios (i.e., RCP4.5 and RCP8.5) in order to sample the widest range of uncertainties in climate projections. Current land use and land cover (LULC) maps are generated from Landsat imagery to analyze the pattern and dynamic of land use change. Both climate projections and LULC are fed into SWAT (Soil and Water Assessment Tool) hydrological model to investigate the streamflow dynamics. The results indicate good applicability of SDSM and LARS-WG for downscaling of temperature and precipitation in three future periods (2020s, 2050s and 2080s). Both models show an increase mean annual max temperature, min temperature and precipitation as 0.4-4.2°C, 0.3-4.2°C and 4.4-32.2% under both RCPs scenarios. Similarly, results of SWAT model suggest an increase in mean annual discharge about 3.6 to 28.8% under RCP4.5 and RCP8.5. The study also revealed that water yield and evapotranspiration in the eastern part of the basin (sub-basins at high elevation) would be most affected by climate change. The results of LULC change detection show that forest exhibited maximum positive change while agriculture showed maximum negative change during 2001-2018. SWAT model simulations suggested that implementation of afforestation in the watershed would reduce surface runoff and water yield while enhancing the evapotranspiration. It is recommended that authorities should pay attention to both climate change and land use transition for proper water resources management.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:74212 |
| Date | 22 March 2021 |
| Creators | Saddique, Naeem |
| Contributors | Bernhofer, Christian, Liedl, Rudolf, Shahid, Muhammad Adnan, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 10.1007/s13143-019-00111-2, 10.1007/s00477-020-01829-6, 10.3390/w11102141, 10.1007/s12665-020-09206-w |
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