{"title":"Modeling projected impacts of climate and land use/land cover changes on streamflow in Gelana Catchment, Southern Ethiopia","authors":"Alemu Osore Aga, Muse Wldmchel Shomre","doi":"10.1016/j.wsee.2024.09.003","DOIUrl":null,"url":null,"abstract":"<div><div>Effective watershed management is extremely critical because changes in the global and local distribution of climate have a direct impact on ecosystems. The primary goal of the current study was to evaluate current and projected climate and land use land cover (LULC) change on streamflow in Gelana catchment. LULC prepared via supervised classification algorithm by using ERDAS (Earth Resources and Development Systems) software, ArcGIS 10.4 (for satellite image processing and map preparation), and the Cellular Automata (CA)-Markov model revealed significant gains in agricultural and built-up over forest and pasture land classes. A coordinated regional climate downscaling experiment under the Africa domain for three regional climate data for two future scenarios (RCP 4.5 and RCP 8.5) showed a significant reduction in rainfall from 48.64 % to 4.6 %, while minimum and maximum temperatures increased from 0.58 to 3.35 °C and 0.5 to 2.93 °C, respectively. The Soil and Water Assessment Tool (SWAT) model was applied to analyze the impact of LULC and climate change on streamflow. The model calibration and validation were carried out by using monthly observed streamflow for the most sensitive parameters by using Sequential Uncertainty Fitting (SUFI-2) within the SWAT Calibration of Uncertainty Program (SWAT-CUP). The model performed well between observed and simulated streamflow, with R<sup>2</sup>, NSE, PBIAS, P, and r-factors of 0.84, 0.77, −15.9, 0.68, and 0.56 for calibration and 0.88, 0.8, −14, 0.63, and 0.65 for validation, respectively. The results of the study implied the simulated mean annual streamflow increased from 3.22 % to 23.82 % in the case of LULC change alone, while it decreased from 38.2 % to 23.27 % for climate change alone for the near-term of RCP 4.5 and from 45.3 % to 24.6 % for RCP 8.5. Further substantial decline was observed in the combined simulation, from 55.38 % to 42.45 % and 62.15 % to 59.36 % for the near and far future of RCP 4.5 and RCP 8.5, respectively. In order to address the constraints, current findings are valuable to scale up sustainable natural resource management.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"6 ","pages":"Pages 195-208"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Watershed Ecology and the Environment","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2589471424000160","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Effective watershed management is extremely critical because changes in the global and local distribution of climate have a direct impact on ecosystems. The primary goal of the current study was to evaluate current and projected climate and land use land cover (LULC) change on streamflow in Gelana catchment. LULC prepared via supervised classification algorithm by using ERDAS (Earth Resources and Development Systems) software, ArcGIS 10.4 (for satellite image processing and map preparation), and the Cellular Automata (CA)-Markov model revealed significant gains in agricultural and built-up over forest and pasture land classes. A coordinated regional climate downscaling experiment under the Africa domain for three regional climate data for two future scenarios (RCP 4.5 and RCP 8.5) showed a significant reduction in rainfall from 48.64 % to 4.6 %, while minimum and maximum temperatures increased from 0.58 to 3.35 °C and 0.5 to 2.93 °C, respectively. The Soil and Water Assessment Tool (SWAT) model was applied to analyze the impact of LULC and climate change on streamflow. The model calibration and validation were carried out by using monthly observed streamflow for the most sensitive parameters by using Sequential Uncertainty Fitting (SUFI-2) within the SWAT Calibration of Uncertainty Program (SWAT-CUP). The model performed well between observed and simulated streamflow, with R2, NSE, PBIAS, P, and r-factors of 0.84, 0.77, −15.9, 0.68, and 0.56 for calibration and 0.88, 0.8, −14, 0.63, and 0.65 for validation, respectively. The results of the study implied the simulated mean annual streamflow increased from 3.22 % to 23.82 % in the case of LULC change alone, while it decreased from 38.2 % to 23.27 % for climate change alone for the near-term of RCP 4.5 and from 45.3 % to 24.6 % for RCP 8.5. Further substantial decline was observed in the combined simulation, from 55.38 % to 42.45 % and 62.15 % to 59.36 % for the near and far future of RCP 4.5 and RCP 8.5, respectively. In order to address the constraints, current findings are valuable to scale up sustainable natural resource management.