Simulation of the Potential Impacts of Projected Climate and Land Use Change on Runoff under CMIP6 Scenarios
Saif HaiderMuhammad Umer MasoodMuhammad RashidFahad AlshehriChaitanya B. PandeOkan Mert KatipoğluRomulus Costache
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Assessing the impacts of climate change and land use/land cover changes on water resources within a catchment is essential because it helps us understand how these dynamic factors affect the quantity, quality, and availability of freshwater. This knowledge is crucial for making informed decisions about water management, conservation, and adaptation strategies, especially in regions facing increasing environmental uncertainties and challenges to water resource sustainability. In Pakistan’s Kunhar River Basin (KRB), this investigation explores the potential effects of shifting land use/land cover (LULC), and climate on stream flows. The SWAT (Soil and Water Assessment Tool), a semi-distributed hydrological model, and the most recent Coupled Model Intercomparison Project phase 6 (CMIP6) dataset from multiple global climate models (GCMs) were used to evaluate these effects. The temperature and precipitation data were downscaled using the CMhyd software; for both shared socioeconomic pathways (SSP2 and SSP5), the top-performing GCM out of four was required to produce downscaled precipitation and temperature predictions while taking future land use characteristics into account. The output from the chosen GCM indicated that by the conclusion of the 21st century, relative to the reference period (1985–2014), the study area’s average monthly precipitation, highest temperature, and lowest temperature will be increasing. Precipitation is anticipated to increase between 2015 and 2100 by 20.5% and 29.1% according to the SSP2 and SSP5 scenarios, respectively. This study’s findings, which emphasize the need for project planners and managers taking into account the effects of climate and land cover changes in their management techniques, show that climate change can have a significant impact on the changing seasons of flows in the Kunhar River basin.Keywords:
Land Cover
Water cycle
Abstract The SWAT model was used to investigate the impact of land-cover changes on the runoff of the River Nzoia catchment, Kenya. The model was calibrated against measured daily discharge, and land-cover changes were examined through classification of satellite images. Land-cover change scenarios were generated, namely the worst- and best-case scenarios. Historical land-cover change results showed that agricultural area increased from 39.6 to 64.3% between 1973 and 2001, while forest cover decreased from 12.3 to 7.0%. A comparison between 1970–1975 and 1980–1985 showed that land-cover changes accounted for a difference in surface runoff ranging from 55 to 68% between the two time periods. The land-cover scenarios used showed the magnitude of changes in runoff due to changes in the land covers considered. Compared to the 1980–1985 runoff, the land-cover scenarios generated changes in runoff of about −16% and 30% for the best and worst case scenarios respectively.
Land Cover
SWAT model
Agricultural land
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Agricultural land
SWAT model
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Lake Chad lost more than 80% of its surface area over the past decades as a result of environmental change and climate variability. It is not yet known how climate change will affect water resources availability in the basin over the coming decades. In this study, the reliability ensemble averaging (REA) technique was used to evaluate the performance of Coupled Model Intercomparison Project phase 5 (CMIP5) models in simulating present‐day precipitation and temperature (1980–2005), and to quantify the uncertainties in future projections (2050–2075) under two representative concentration pathways (RCPs) in the Lake Chad basin (LCB). Analyses were carried out at both annual and seasonal timescales. Overall, the CMIP5 models simulated precipitation better than temperature in the study area. Although the models were able to simulate the annual precipitation cycle in the basin, most models overestimated precipitation during the dry season and underestimated it during the monsoon season. Future annual basin precipitation is projected to increase by 2.5 and 5%, respectively, under RCP4.5 and RCP8.5 scenario by the middle of the century by most of the models and most of the model projections are within the REA uncertainty range. Despite the increase in projected annual precipitation in the basin, most models project a decrease in monsoon precipitation under both RCPs. Although the uncertainty range for future precipitation projections for most models lie within the range of natural climate variability, additional analysis is needed for results to be useful for any future planning in the study area.
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Annual cycle
Water cycle
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