A GIS-BASED DECISION SUPPORT SYSTEM FOR SUSTAINABLE LAND USE PLANNING AND CLIMATE CHANGE ADAPTATION IN THE BRANTAS RIVER WATERSHED
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GIS, Decision Support System (DSS), Land Use Planning, Climate Change Adaptation, Watershed Management
Abstract
The Brantas River Watershed, a vital socio-economic region in East Java, Indonesia, faces escalating environmental pressures from unplanned urbanization and intensive agriculture. These challenges are exacerbated by climate change, leading to increased land degradation, soil erosion, and severe flood events, which threaten the watershed’s long-term sustainability and the livelihoods of millions. This study aimed to develop and validate a Geographic Information System (GIS)-based Decision Support System (DSS) to aid policymakers in formulating integrated, evidence-based strategies for sustainable land use planning and climate change adaptation within this critical watershed. The DSS was constructed by integrating a multi-criteria evaluation (MCE) framework within a GIS environment. Key geospatial datasets (land cover, soil type, slope, rainfall projections) were weighted using the Analytical Hierarchy Process (AHP). The system models land suitability and vulnerability to environmental hazards under various climate change scenarios. The developed DSS successfully generated high-resolution maps identifying priority zones for conservation, reforestation, and sustainable development. The model revealed that 22% of the upper watershed area is at high risk of landslides under projected rainfall patterns. The optimized land use plan proposed by the DSS demonstrated a potential to reduce surface runoff by up to 35%, significantly mitigating flood risk. The GIS-based DSS is a powerful and effective tool for integrated watershed management. It provides a dynamic, scientifically-grounded platform for strategic planning, enabling policymakers to balance ecological protection with socio-economic needs and enhance the climate resilience of the Brantas River Watershed.
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Copyright (c) 2025 Dani Hakim, Luis Santos, Maria Clara Reyes
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