Abstract

Water resources are highly dependent on climatic variations. The quantification of climate change impacts on surface water availability is critical for agriculture production and flood management. The current study focuses on the projected streamflow variations in the transboundary Mangla Dam watershed. Precipitation and temperature changes combined with future water assessment in the watershed are projected by applying multiple downscaling techniques for three periods (2021–2039, 2040–2069, and 2070–2099). Streamflows are simulated by using the Soil and Water Assessment Tool (SWAT) for the outputs of five global circulation models (GCMs) and their ensembles under two representative concentration pathways (RCPs). Spatial and temporal changes in defined future flow indexes, such as base streamflow, average flow, and high streamflow have been investigated in this study. Results depicted an overall increase in average annual flows under RCP 4.5 and RCP 8.5 up until 2099. The maximum values of low flow, median flow, and high flows under RCP 4.5 were found to be 55.96 m3/s, 856.94 m3/s, and 7506.2 m3/s and under RCP 8.5, 63.29 m3/s, 945.26 m3/s, 7569.8 m3/s, respectively, for these ensembles GCMs till 2099. Under RCP 4.5, the maximum increases in maximum temperature (Tmax), minimum temperature (Tmin), precipitation (Pr), and average annual streamflow were estimated as 5.3 °C, 2.0 °C, 128.4%, and 155.52%, respectively, up until 2099. In the case of RCP 8.5, the maximum increase in these hydro-metrological variables was up to 8.9 °C, 8.2 °C, 180.3%, and 181.56%, respectively, up until 2099. The increases in Tmax, Tmin, and Pr using ensemble GCMs under RCP 4.5 were found to be 1.95 °C, 1.68 °C and 93.28% (2021–2039), 1.84 °C, 1.34 °C, and 75.88%(2040–2069), 1.57 °C, 1.27 °C and 72.7% (2070–2099), respectively. Under RCP 8.5, the projected increases in Tmax, Tmin, and Pr using ensemble GCMs were found as 2.26 °C, 2.23 °C and 78.65% (2021–2039), 2.73 °C, 2.53 °C, and 83.79% (2040–2069), 2.80 °C, 2.63 °C and 67.89% (2070–2099), respectively. Three seasons (spring, winter, and autumn) showed a remarkable increase in streamflow, while the summer season showed a decrease in inflows. Based on modeling results, it is expected that the Mangla Watershed will experience more frequent extreme flow events in the future, due to climate change. These results indicate that the study of climate change’s impact on the water resources under a suitable downscaling technique is imperative for proper planning and management of the water resources.

Highlights

  • Most of the countries in South Asia are observing water stress due to global atmospheric changes.The rising population in urban areas, agriculture, and mismanagement of water resources and climate change has included Pakistan in the countries that are worst affected by climate change [1]

  • Atmosphere 2020, 11, 1071 future, due to climate change. These results indicate that the study of climate change’s impact on the water resources under a suitable downscaling technique is imperative for proper planning and management of the water resources

  • Pakistan stands among one of the countries with significant and more prominent water stress, and its existing water resources are extremely vulnerable to climate change

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Summary

Introduction

Most of the countries in South Asia are observing water stress due to global atmospheric changes. The rising population in urban areas, agriculture, and mismanagement of water resources and climate change has included Pakistan in the countries that are worst affected by climate change [1]. According to a report by the International Monetary Fund (IMF), Pakistan positioned third in the world among the countries prone to severe water scarcity [2]. Reported a 0.72 ◦ C increase in the total temperature from 1951 to 2012. The severe temperature changes affect the land cover and change the streamflow patterns [3]. River flows are associated with long-term fluctuations in rainfall and temperature, especially in areas where snowmelt is the principal component of the total runoff [5,6]

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