4.6 Article

Scaling Up Indigenous Rainwater Harvesting: A Preliminary Assessment in Rajasthan, India

期刊

WATER
卷 15, 期 11, 页码 -

出版社

MDPI
DOI: 10.3390/w15112042

关键词

Indigenous rainwater harvesting; Site suitability; Multicriteria decision analysis

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Rainwater harvesting has the potential to enhance water sustainability, especially in arid and semi-arid regions. However, selecting suitable sites for rainwater harvesting is challenging due to the lack of necessary data. This study applied GIS modeling and remote sensing techniques to identify potential rainwater harvesting sites in Rajasthan, India by considering various criteria. The results showed that a small percentage of the study area was highly suitable for rainwater harvesting, and sensitivity analysis revealed the influence of different parameters on the outcome. Overall, this study demonstrates the applicability of the GIS-based multicriteria decision analysis approach in scaling up traditional rainwater harvesting systems and its potential for other regions with similar conditions.
Rainwater harvesting (RWH) has the potential to enhance the sustainability of ground and surface water to meet increasing water demands and constrained supplies, even under a changing climate. Since arid and semi-arid regions frequently experience highly variable spatiotemporal rainfall patterns, rural communities have developed indigenous RWH techniques to capture and store rainwater for multiple uses. However, selecting appropriate sites for RWH, especially across large regions, remains challenging since the data required to evaluate suitability using critical criteria are often lacking. This study aimed to identify the essential criteria and develop a methodology to select potential RWH sites in Rajasthan (India). We combined GIS modeling (multicriteria decision analysis) with applied remote sensing techniques as it has the potential to assess land suitability for RWH. As assessment criteria, spatial datasets relating to land use/cover, rainfall, slope, soil texture, NDVI, and drainage density were considered. Later, weights were assigned to each criterion based on their relative importance to the RWH system, evidence from published literature, local expert advice, and field visits. GIS analyses were used to create RWH suitability maps (high, moderate, and unsuited maps). The sensitivity analysis was also carried out for identified weights to check the inadequacy and inconsistency among preferences. It was estimated that 3.6%, 8.2%, and 27.3% of the study area were highly, moderately, and unsuitable, respectively, for Chauka implementation. Further, sensitivity analysis results show that LULC is highly sensitive and NDVI is the least sensitive parameter in the selected study region, which suggests that changing the weight of these parameters is more likely to decide the outcome. Overall, this study shows the applicability of the GIS-based MCDA approach for up-scaling the traditional RWH systems and its suitability in other regions with similar field conditions, where RWH offers the potential to increase water resource availability and reliability to support rural communities and livelihoods.

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