Assessing the impact of climate change on surface water resources (Case study: Babolrood watershed)

Arekhi, Saleh; Emadodin, Somayeh; Roshun, Sayed Hussein

Assessing the impact of climate change on surface water resources (Case study: Babolrood watershed)

Document Type : Extract article from research project

Authors

Saleh Arekhi ¹ ^¶

Somayeh Emadodin ²

Sayed Hussein Roshun ³

¹ Associate Professor, Department of Geography and GIS, Faculty of Human Sciences, Golestan University, Gorgan, Iran, Iran

² Associate Professor, Department of Geography and GIS, Faculty of Human Sciences, Golestan University, Gorgan, Iran

³ Ph.D. Graduated in Watershed Management, Department of Watershed Management, Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.

Abstract

Background and Objective: In recent years, climate change and human activities have increasingly intensified the global water scarcity crisis. These changes have disrupted the hydrological cycle, placing surface water resources under serious threat in terms of accessibility, quality, and sustainability.
Methodology: To assess the impact of climate change on surface water resources in the Babolrood watershed, meteorological and hydrometric data were initially collected. After addressing statistical deficiencies, removing outliers, and selecting a common temporal baseline, future climate variables (precipitation, minimum temperature, and maximum temperature) were projected for the period 2020–2100 using the CanESM5 climate model under IPCC AR6 scenarios SSP1-2.6, SSP2-4.5, and SSP5-8.5 within the SDSM framework. Streamflow simulation for the future period was conducted using downscaled data processed through an Artificial Neural Network (ANN). Finally, to identify trends in the projected data, non-parametric Mann–Kendall and Sen’s slope estimator tests were applied using the R software environment.
Results and Findings: Trend analysis of streamflow using the Mann–Kendall test, Sen’s slope estimator, and the ANN model over the period 2021–2100 revealed a weak and statistically insignificant decreasing trend across all SSP climate scenarios. The most pronounced decline was observed under the SSP5-8.5 scenario. Minimum temperature exhibited a non-significant increasing trend, potentially indicating nighttime or cold-season warming, while precipitation showed no discernible trend. The ANN model results were consistent with the statistical tests, confirming a gradual reduction in streamflow, thereby underscoring the need for sustainable water resource management in the face of climate change. These findings not only confirm the direct impact of climate change on surface water resources but also highlight the importance of employing intelligent models for long-term analysis and sustainable water resource management. Moreover, they underscore the necessity of integrated approaches and region-specific analyses in future studies.

Keywords

Artificial Neural Network (ANN)

Babolrood watershed

Hydrological modeling

Mann-Kendall test

SSP emission scenarios

Subjects

Physical geogeaphy

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