Abstract Flooding in low-lying deltaic regions such as Kuttanad, India, has intensified due to rapid land use and land cover (LULC) changes and inadequate water management. To address this challenge, this study poses the research question of whether spatially adaptive rainwater harvesting (RH) strategies mitigate flood risk and enhance water resilience in such vulnerable landscapes. It is hypothesised that site-specific interventions such as rooftop rainwater harvesting (RTRH), surface runoff harvesting (SRH), and infiltration enhancement zones (IEZ) can significantly reduce surface runoff when guided by basin-scale spatial analysis. To test this hypothesis, this study aims to delineate and prioritise suitable zones for RH interventions using the Fuzzy Analytical Hierarchy Process (F-AHP). LULC was classified into six categories using Landsat 8 OLI imagery 2023, achieving an overall accuracy of 89.33% and a Kappa coefficient of 0.87. By integrating LULC, rainfall, slope, and soil type, the study evaluates how each of the six LULC categories can be effectively targeted for RH strategies. F-AHP was used to assign weights based on the relative importance of each criterion, and the resulting scores were rescaled from 1 to 4 using the Natural Breaks method. These scores were categorised into four classes: very low, low, high, and very high, with values ≥3 indicating high to very high suitability. Based on this classification, 59.64% of the area was identified as highly suitable for RTRH, 64.99% for SRH, and 71.71% for IEZ. These zoning maps offer actionable guidance for local planners and policymakers to implement decentralised, data-driven flood mitigation strategies. Research highlights <UnorderedList Mark="Bullet"> <ItemContent> The study demonstrates how spatially adaptive rainwater harvesting (RH) zones can reduce flood risk in deltaic landscapes. </ItemContent> <ItemContent> Land use and Land cover (LULC) based RH zoning supports data-driven flood and water resilience planning in Kuttanad. </ItemContent> <ItemContent> Over 59–72% of the area identified as highly suitable for rooftop rainwater harvesting (RTRH) zone, surface runoff harvesting (SRH) zone, and infiltration enhancement zone (IEZ). SRH and IEZ mapping reveals priority areas that significantly reduce runoff. </ItemContent> <ItemContent> The framework enables scalable, data-driven flood management for other deltaic regions. </ItemContent> </UnorderedList>

Enhancing flood resilience through sustainable water management strategies in the deltaic region, Kuttanad, India

期刊论文
发表日期：

2026年2月9日

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Neethu Lukose,
N Sunilkumar

摘要

Abstract

Flooding in low-lying deltaic regions such as Kuttanad, India, has intensified due to rapid land use and land cover (LULC) changes and inadequate water management. To address this challenge, this study poses the research question of whether spatially adaptive rainwater harvesting (RH) strategies mitigate flood risk and enhance water resilience in such vulnerable landscapes. It is hypothesised that site-specific interventions such as rooftop rainwater harvesting (RTRH), surface runoff harvesting (SRH), and infiltration enhancement zones (IEZ) can significantly reduce surface runoff when guided by basin-scale spatial analysis. To test this hypothesis, this study aims to delineate and prioritise suitable zones for RH interventions using the Fuzzy Analytical Hierarchy Process (F-AHP). LULC was classified into six categories using Landsat 8 OLI imagery 2023, achieving an overall accuracy of 89.33% and a Kappa coefficient of 0.87. By integrating LULC, rainfall, slope, and soil type, the study evaluates how each of the six LULC categories can be effectively targeted for RH strategies. F-AHP was used to assign weights based on the relative importance of each criterion, and the resulting scores were rescaled from 1 to 4 using the Natural Breaks method. These scores were categorised into four classes: very low, low, high, and very high, with values ≥3 indicating high to very high suitability. Based on this classification, 59.64% of the area was identified as highly suitable for RTRH, 64.99% for SRH, and 71.71% for IEZ. These zoning maps offer actionable guidance for local planners and policymakers to implement decentralised, data-driven flood mitigation strategies.

Research highlights

The study demonstrates how spatially adaptive rainwater harvesting (RH) zones can reduce flood risk in deltaic landscapes.

Land use and Land cover (LULC) based RH zoning supports data-driven flood and water resilience planning in Kuttanad.

Over 59–72% of the area identified as highly suitable for rooftop rainwater harvesting (RTRH) zone, surface runoff harvesting (SRH) zone, and infiltration enhancement zone (IEZ).

SRH and IEZ mapping reveals priority areas that significantly reduce runoff.

The framework enables scalable, data-driven flood management for other deltaic regions.