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- Karan, Kunal, et al.
(författare)
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Implications of future climate change on crop and irrigation water requirements in a semi-arid river basin using CMIP6 GCMs
- 2022
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Ingår i: Journal of Arid Land. - : Springer Science and Business Media LLC. - 1674-6767 .- 2194-7783. ; 14:11, s. 1234-1257
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Tidskriftsartikel (refereegranskat)abstract
- Agriculture faces risks due to increasing stress from climate change, particularly in semi-arid regions. Lack of understanding of crop water requirement (CWR) and irrigation water requirement (IWR) in a changing climate may result in crop failure and socioeconomic problems that can become detrimental to agriculture-based economies in emerging nations worldwide. Previous research in CWR and IWR has largely focused on large river basins and scenarios from the Coupled Model Intercomparison Project Phase 3 (CMIP3) and Coupled Model Intercomparison Project Phase 5 (CMIP5) to account for the impacts of climate change on crops. Smaller basins, however, are more susceptible to regional climate change, with more significant impacts on crops. This study estimates CWRs and IWRs for five crops (sugarcane, wheat, cotton, sorghum, and soybean) in the Pravara River Basin (area of 6537 km2) of India using outputs from the most recent Coupled Model Intercomparison Project Phase 6 (CMIP6) General Circulation Models (GCMs) under Shared Socio-economic Pathway (SSP)245 and SSP585 scenarios. An increase in mean annual rainfall is projected under both scenarios in the 2050s and 2080s using ten selected CMIP6 GCMs. CWRs for all crops may decline in almost all of the CMIP6 GCMs in the 2050s and 2080s (with the exceptions of ACCESS-CM-2 and ACCESS-ESM-1.5) under SSP245 and SSP585 scenarios. The availability of increasing soil moisture in the root zone due to increasing rainfall and a decrease in the projected maximum temperature may be responsible for this decline in CWR. Similarly, except for soybean and cotton, the projected IWRs for all other three crops under SSP245 and SSP585 scenarios show a decrease or a small increase in the 2050s and 2080s in most CMIP6 GCMs. These findings are important for agricultural researchers and water resource managers to implement long-term crop planning techniques and to reduce the negative impacts of climate change and associated rainfall variability to avert crop failure and agricultural losses.
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2. |
- Singh, Dharmaveer, et al.
(författare)
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Fusing morphometric characteristics with extreme precipitation indices for identifying the most vulnerable sub-basin at risk of flooding
- 2023
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Ingår i: Journal of Hydro-Environment Research. - 1570-6443. ; 50, s. 44-56
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Tidskriftsartikel (refereegranskat)abstract
- Fluvial floods are commonly studied as an occurrence at the level of a specific basin and are speculated to be closely related to the basin's morphometry. It is possible to identify and rank sub-basins based on how susceptible they are to fluvial flooding events using morphometric criteria. However, one of the key causes that triggers fluvial flooding is the increase in precipitation extremes and changes to their patterns. In this study, influence of morphometric factors and extreme precipitation events on the hydrological responses of the Brahmani River, India as well as their sensitivity to fluvial flooding, are investigated to identify the most vulnerable sub-basin in a catchment. The morphometric parameters were calculated from a digital elevation model (DEM), and the change in trend of extreme precipitation indices was detected using precipitation data of period 1991 to 2021. Furthermore, the Standardized Precipitation Index (SPI) was used to determine the frequency of wet cycles on time scale of 1, 3, 12, and 24 months, as well as their link to fluvial flooding. The two sub-basins of the catchment that are most vulnerable to river flooding are recognised as Noamundi and Gomlai based on morphometric criteria. However, analysis of SPI and extreme precipitation indices showed that the Jenapur sub-basin is the most vulnerable to flooding. It is also corroborated with analytic hierarchy process (AHP) based weighted overlay analysis and historical flood records. The outcomes will assist researchers in better understanding the mechanisms causing flooding in the Brahamni River Basin and in developing flood mitigation practices for the most vulnerable Jenapur sub-basin.
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