Identification of Potential Rainwater-Harvesting Sites for the Sustainable Management of a Semi-Arid Watershed

Abstract

In the present study, the potential locations for constructing different water‐harvesting structures in a semi‐arid watershed located at Goparajpalli, in southern India, were derived using GIS in three stages. The locations were first identified based on land use land cover, land slope, rainfall characteristics, soil texture and soil depth. Then a number of structures and suitable semi‐arid rainfed regions have limitations in their runoff potential availability; these locations were further optimized based on the runoff available after in situ water conservation and storage in existing water‐harvesting structures. The surplus runoff volume available in a normal year after storage was estimated to be 870 000 m3. Suitable locations for 25 rock fill dams (RFD), 74 farm ponds and 5 check dams were identified. These derived sites were validated by exporting to Google Earth and investigated for their suitability with ground truth information. At present, the number of structures existing is more than the optimum number of structures derived, but they have less storage capacity. Hence those structures such as farm ponds located at potential sites are recommended for desiltation and renovation by increasing their size along with lining so that they can be utilized for rainwater harvesting and supplementary irrigation. This methodology for identification of potential locations for water‐harvesting structures is less time‐consuming, more precise and can be utilized for the planning of large catchments to improve the water availability and productivity. Copyright © 2017 John Wiley & Sons, Ltd.

GIS-Based Modeling for Selection of Dam Sites in the Kurdistan Region, Iraq

“…Although the CN grid is not indicative of runoff, several studies on dam site selection have used it as a predictive factor [9,23,[25][26][27][28]30,31]. Al-Ruzouq [31] and Mugo [9] used the drainage density as an expression of runoff and considered the CN grid as a predictive factor.…”

“…More than 70% of these papers have used land cover [14,[23][24][25][26][27][28][29][30], soil type [14,[23][24][25][26][27][28][29][30], slope gradient [14,23,24,26,[28][29][30][31], precipitation [14,23,24,26,[28][29][30][31], and CN grid [23,[25][26][27][28]30,31] as significant predictive factors for dam site selection. Fifty percent of the papers used different factors to calculate stream order [23][24][25]30], and between 40% and 20% of the papers used elevation [25,27,30,31], lithology…”

Estimation of Soil Loss Under Changing Climatic Scenarios in Semi-Arid Watersheds

“…The mean annual rainfall of the Goparajpalli watershed is around 735 mm with 80% of its contribution during southwest monsoon (June to September). The area is characterized by moderate to very deep soil with clayey and cracking clayey texture with major portion having slopes below 5% (Rejani et al, 2016b).…”

Identifying important ecological areas for potential rainwater harvesting in the semi-arid area of Chifeng, China

“…Water shortage can be minimized by careful planning and operation. Water stress can be managed by harvesting runoff during rainy days, and this harvested water can be used for social development during dry spells [ 10 ]. Identifying potential sites for rainwater harvesting (RWH) is therefore an important step toward maximizing water availability and land productivity in the arid and semi-arid areas of China.…”

“…Rainfall, terrain, soil type, land use, runoff characteristics and other indicators have been used to identify potential RWH sites in semi-arid areas [ 11 – 14 ]. Runoff is one of the most important parameters for predicting potential RWH sites [ 10 , 14 ]. The Soil Conservation Service curve number (SCS-CN) method, one of the commonest models for simulating rainfall and runoff due to its simple structure, few parameters and low requirement for empirical data, accounts for many factors, including rainfall, soil properties and land-use type [ 11 ].…”