Rainwater harvesting planning using geospatial techniques and multicriteria decision analysis

• Published in: Resources, conservation and recycling conservation and recycling, 2014-02, Vol.83, p.96-111
• Main Authors: Jha, Madan K., Chowdary, V.M., Kulkarni, Y., Mal, B.C.
• Format: Article
• Language: English
• Subjects: Applied sciences; Distributed CN method; Exact sciences and technology; Geospatial techniques; Multicriteria analysis; Natural water pollution; Pollution; Rainwater conservation; Rainwaters, run off water and others; RWH planning; Water scarcity; Water treatment and pollution
• ISSN: 0921-3449; 1879-0658
• DOI: 10.1016/j.resconrec.2013.12.003

•A robust methodology is presented for assessing rainwater harvesting (RWH) potential and identifying suitable sites/zones for RWH structures.•The novel and scientifically sound approach adopted in this study is likely to reduce the bias involved in GIS-based multicriteria analysis.•Findings of this study are very useful to the decision makers for ensuring sustainable water supply and improved sanitation in the study area.•Integrated geospatial and MCDA techniques offer a powerful tool for the planning of rainwater harvesting at a basin or sub-basin scale. Growing water scarcity and global climate change call for more efficient alternatives of water conservation; rainwater harvesting (RWH) is the most promising alternative among others. However, the assessment of RWH potential and the selection of suitable sites for RWH structures are very challenging for the water managers, especially on larger scales. This study addresses this challenge by presenting a fairly robust methodology for evaluating RWH potential and identifying sites/zones for different RWH structures using geospatial and multicriteria decision analysis (MCDA) techniques. The proposed methodology is demonstrated using a case study. The remote sensing data and conventional field data were used to prepare desired thematic layers using ArcGIS© software. Distributed Curve Number method was used to calculate event-based runoffs, based on which annual runoff potential and runoff coefficient maps were generated in the GIS (geographic information system) environment. Thematic layers such as slope, drainage density, and runoff coefficient and their features were assigned suitable weights and then they were integrated in a GIS to generate a RWH potential map of the study area. Zones suitable for different RWH structures were also identified, together with suitable sites for constructing recharge structures (check dams and percolation tanks along the streams). It was found that the study area can be classified into three RWH potential zones: (a) ‘good’ (241km2), (b) ‘moderate’ (476km2), and (c) ‘poor’ (287km2). About 3% of the study area (30km2) is suitable for constructing farm ponds, while percolation tanks (on the ground) can be constructed in about 2.7% of the area (27km2). Of the 83 sites identified for the recharge structures, 32 recharge sites are specially suited to the inhabitants because of their proximity. It is concluded that the integrated geospatial and MCDA techniques offer a useful and po