Pipeline Route Optimization: An Integrated GIS–MCDA–LCP Approach to Address Water Scarcity in Rio de Janeiro, Brazil

Abstract The Eastern Metropolitan Region of Rio de Janeiro faces significant water insecurity, as current supply ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="5.5 normal m cubed divided by normal s" display="inline" overflow="scroll"> <mml:mn>5.5</mml:mn> <mml:mtext> </mml:mtext> <mml:msup> <mml:mi mathvariant="normal">m</mml:mi> <mml:mn>3</mml:mn> </mml:msup> <mml:mo stretchy="false">/</mml:mo> <mml:mi mathvariant="normal">s</mml:mi> </mml:math> ) falls short of the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="12.5 normal m cubed divided by normal s" display="inline" overflow="scroll"> <mml:mn>12.5</mml:mn> <mml:mtext> </mml:mtext> <mml:msup> <mml:mi mathvariant="normal">m</mml:mi> <mml:mn>3</mml:mn> </mml:msup> <mml:mo stretchy="false">/</mml:mo> <mml:mi mathvariant="normal">s</mml:mi> </mml:math> demand projected for 2030. A new water intake at the Juturnaíba Lagoon, located approximately 80 km from the existing system, represents a viable complementary solution, though routing such a pipeline presents complex geographic challenges, including heterogeneous terrain, environmental constraints, and conflicting land uses. This study presents an integrated geographic information system (GIS)-based methodology combining multicriteria decision analysis (equal weights, analytic hierarchy process, and rank reciprocal weights) with Dijkstra’s least-cost path algorithm to optimize routing. Six spatial criteria—elevation, slope, proximity to roadways and watercourses, land use, and soil type—were integrated through expert consultation and weighted overlay to generate cost surfaces, applied to two study areas in Rio de Janeiro. Results show route convergence in rural landscapes and significant divergence in urbanized areas where spatial heterogeneity is highest. The Kruskal–Wallis test confirmed statistically distinguishable cost distributions among routes in both study areas. Among the weighting schemes, the analytic hierarchy process (AHP) produced the most favorable cost distributions and spatially coherent alignments. Rather than prescribing a single optimal route—an outcome inherently conditioned by weighting assumptions, data quality, and planning priorities—the framework generates comparable alternatives that broaden the basis for informed spatial decision-making. The approach provides a transferable decision-support tool for planning water supply infrastructure.