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2025 Vol. 13, No. 4
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Article navigation > Journal of Groundwater Science and Engineering > 2025 > 13(4): 352-370
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Sulistiani, Lubis Rachmat Fajar, Santikayasa I Putu, Taufik Muh., Nugraha Gumilar Utamas. 2025. Groundwater recharge modeling with integration of land use/land cover and climate change projections in Surakarta City, Indonesia. Journal of Groundwater Science and Engineering, 13(4): 352-370. doi: 10.26599/JGSE.2025.9280059
Citation: Sulistiani, Lubis Rachmat Fajar, Santikayasa I Putu, Taufik Muh., Nugraha Gumilar Utamas. 2025. Groundwater recharge modeling with integration of land use/land cover and climate change projections in Surakarta City, Indonesia. Journal of Groundwater Science and Engineering, 13(4): 352-370. doi: 10.26599/JGSE.2025.9280059
shu

Groundwater recharge modeling with integration of land use/land cover and climate change projections in Surakarta City, Indonesia

  • 1.

    Department of Geophysics and Meteorology, Faculty of Mathematics and Natural Sciences, IPB University, Bogor, West Java, Indonesia

  • 2.

    Research Center for Limnology and Water Resources, National Research and Innovation Agency, Bandung, West Java, Indonesia

More Information
Received Date:  26 July 2024
Accepted Date:  21 July 2025
Available Online:  10 October 2025
Publish Date:  15 December 2025
    Abstract

  • Increased population mobility in urban areas drives higher water demand and significant changes in Land Use and Land Cover (LULC), which directly impact groundwater recharge capacity. This study aims to predict LULC changes in 2030 and 2040, analyse groundwater recharge quantities for historical, current, and projected conditions, and evaluate the combined impacts of LULC and climate change. The Cellular Automata-Artificial Neural Network (CA-ANN) method was employed to predict LULC changes, using classified and interpreted land use data from Landsat 7 ETM+ (2000 and 2010) and Landsat 8 OLI (2020) imagery. The Soil and Water Assessment Tool (SWAT) model was used to simulate groundwater recharge. Input data for the SWAT model included Digital Elevation Model (DEM), soil type, LULC, slope, and climate data. Climate projections were based on five Regional Climate Models (RCMs) for two time periods, 2021–2030 and 2031–2040, under Shared Socioeconomic Pathways (SSP) scenarios 2–45 and 5–85. The results indicate a significant increase in built-up areas, accounting for 71.08% in 2030 and 71.83% in 2040. Groundwater recharge projections show a decline, with average monthly recharge decreasing from 83.85 mm/month under SSP2-45 to 78.25 mm/month under SSP5-85 in 2030, and further declining to 82.10 mm/month (SSP2-45) and 77.44 mm/month (SSP5-85) in 2040. The expansion of impervious surfaces due to urbanization is the primary factor driving this decline. This study highlights the innovative integration of CA-ANN-based LULC predictions with climate projections from RCMs, offering a robust framework for analysing urban groundwater dynamics. The findings underscore the need for sustainable urban planning and water resource management to mitigate the adverse effects of urbanization and climate change. Additionally, the methodological framework and insights gained from this research can be applied to other urban areas facing similar challenges, thus contributing to broader efforts in groundwater conservation.

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