Abstract
The exponential rise in population and adverse climatic conditions adversely affects safe water availability and has become a substantial issue in most countries. To combat this, Rainwater harvesting (RWH) can be a viable alternative source. This study proposes a framework for ranking potential sites to construct centralised RWH structures by integrating Geographical Information System (GIS) and multiple Multi-criteria decision-making (MCDM) approaches. In a study, the identified sites are compared for various predefined criteria using two objective weight methods, Criteria Importance Through Intercriteria Correlation (CRITIC) and Entropy. Furthermore, to rank the identified sites, four MCDM techniques: Weighted Aggregated Sum Product Assessment (WASPAS); Technique for Order of Preference by Similarity to an Ideal Solution (TOPSIS); VIšekriterijumsko Kompromisno Rangiranje (VIKOR); and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE-II) are applied for both objective weightage methods. In addition, Sensitivity Analysis is also performed to confirm the robustness of this methodology. The results from the analysis on real-time data of the municipality ward of Jaipur city, Rajasthan, India, show that the criteria evaluated by all the applied methods provide consistent rankings for all the potential sites.
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References
Abdulla, F. A., Amayreh, J. A., & Hossain, A. H. (2002). Single Event Watershed Model for Simulating Runoff Hydrograph in Desert Regions. Water Resources Management 2002 16:3, 16(3), 221–238. https://doi.org/10.1023/A:1020258808869
Adham, A., Wesseling, J. G., Abed, R., Riksen, M., Ouessar, M., & Ritsema, C. J. (2019). Assessing the impact of climate change on rainwater harvesting in the Oum Zessar watershed in Southeastern Tunisia. Agricultural Water Management, 221, 131–140. https://doi.org/10.1016/J.AGWAT.2019.05.006
Al-Adamat, R., Diabat, A., & Shatnawi, G. (2010). Combining GIS with multicriteria decision making for siting water harvesting ponds in Northern Jordan. Journal of Arid Environments, 74(11), 1471–1477. https://doi.org/10.1016/J.JARIDENV.2010.07.001
Al-Adamat, R., AlAyyash, S., Al-Amoush, H., Al-Meshan, O., Rawajfih, Z., Shdeifat, A., Al-Harahsheh, A., & Al-Farajat, M. (2012). The Combination of Indigenous Knowledge and Geo-Informatics for Water Harvesting Siting in the Jordanian Badia. Journal of Geographic Information System, 2012(04), 366–376. https://doi.org/10.4236/JGIS.2012.44042
Al-Adamat, R. (2012). Gis as a decision support system for siting water harvesting ponds in the basalt aquifer/ne Jordan. https://doi.org/10.1142/S1464333208003020, 10(2), 189–206.
Carver, S. J. (2007). Integrating multi-criteria evaluation with geographical information systems. 5(3), 321–339. https://doi.org/10.1080/02693799108927858
Chakhar, S., & Mousseau, V. (2010). GIS‐based multicriteria spatial modeling generic framework. 22(11–12), 1159–1196. https://doi.org/10.1080/13658810801949827
Dadhich, P. N., & Hanaoka, S. (2011). Spatio-temporal Urban Growth Modeling of Jaipur, India. 18(3), 45–65. https://doi.org/10.1080/10630732.2011.615567
de Winnaar, G., Jewitt, G. P. W., & Horan, M. (2007). A GIS-based approach for identifying potential runoff harvesting sites in the Thukela River basin, South Africa. Physics and Chemistry of the Earth, Parts a/b/c, 32(15–18), 1058–1067. https://doi.org/10.1016/J.PCE.2007.07.009
Dhakate, R., Rao, V. V. S. G., Raju, B. A., Mahesh, J., Rao, S. T. M., & Sankaran, S. (2013). Integrated approach for identifying suitable sites for rainwater harvesting structures for groundwater augmentation in Basaltic Terrain. Water Resources Management, 27(5), 1279–1299. https://doi.org/10.1007/S11269-012-0238-3/FIGURES/13
Gevrey, M., Dimopoulos, I., & Lek, S. (2003). Review and comparison of methods to study the contribution of variables in artificial neural network models. Ecological Modelling, 160(3), 249–264. https://doi.org/10.1016/S0304-3800(02)00257-0
Greco, S., Ehrgott, M., & Figueira, J. R. (Eds.). (2016). Multiple Criteria Decision Analysis. 233. https://doi.org/10.1007/978-1-4939-3094-4
Hwang, C. L. (Ching-L., & Masud, A. S. M. (1979). Multiple Objective Decision Making—Methods and Applications : a State-of-the-Art Survey.
Jayasooriya, V. M., Muthukumaran, S., Ng, A. W. M., & Perera, B. J. C. (2018). Multi Criteria Decision Making in Selecting Stormwater Management Green Infrastructure for Industrial areas Part 2: A Case Study with TOPSIS. Water Resources Management, 32(13), 4297–4312. https://doi.org/10.1007/S11269-018-2052-Z/FIGURES/3
Khosravi, K., Daggupati, P., Alami, M. T., Awadh, S. M., Ghareb, M. I., Panahi, M., Pham, B. T., Rezaie, F., Qi, C., & Yaseen, Z. M. (2019). Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: a case study in Iraq. Computers and Electronics in Agriculture, 167, 105041. https://doi.org/10.1016/J.COMPAG.2019.105041
Krois, J., & Schulte, A. (2014). GIS-based multi-criteria evaluation to identify potential sites for soil and water conservation techniques in the Ronquillo watershed, northern Peru. Applied Geography, 51, 131–142. https://doi.org/10.1016/J.APGEOG.2014.04.006
Kumar, T., & Jhariya, D. C. (2016). Identification of rainwater harvesting sites using SCS-CN methodology, remote sensing and Geographical Information System techniques. 32(12), 1367–1388. https://doi.org/10.1080/10106049.2016.1213772
Kumari, R., Kumar, S., Poonia, R. C., Singh, V., Raja, L., Bhatnagar, V., & Agarwal, P. (2021). Analysis and predictions of spread, recovery, and death caused by COVID-19 in India. Big Data Mining and Analytics, 4(2), 65–75. https://doi.org/10.26599/BDMA.2020.9020013
Mukhametzyanov, I., & Pamucar, D. (2018). A sensitivity analysis in MCDM problems: A statistical approach. Decision Making: Applications in Management and Engineering, 1(2), 51–80. https://doi.org/10.31181/DMAME1802050M
Munier, N., & Hontoria, E. (2021). Shortcomings of the AHP Method. 41–90. https://doi.org/10.1007/978-3-030-60392-2_5
Musayev, S., Burgess, E., & Mellor, J. (2018). A global performance assessment of rainwater harvesting under climate change. Resources, Conservation and Recycling, 132, 62–70. https://doi.org/10.1016/J.RESCONREC.2018.01.023
Patil, D., Kumar, G., Kumar, A., & Gupta, R. (2022). A systematic basin-wide approach for locating and assessing volumetric potential of rainwater harvesting sites in the urban area. Environmental Science and Pollution Research, 1–15. https://doi.org/10.1007/s11356-022-23039-z
Rikalovic, A., Cosic, I., & Lazarevic, D. (2014). GIS Based Multi-criteria Analysis for Industrial Site Selection. Procedia Engineering, 69, 1054–1063. https://doi.org/10.1016/J.PROENG.2014.03.090
Saraf, A. K., & Choudhury, P. R. (2010). Integrated remote sensing and GIS for groundwater exploration and identification of artificial recharge sites. 19(10), 1825–1841. https://doi.org/10.1080/014311698215018
Saraf, A. K., & Jain, S. K. (1996). Integrated use of remote sensing and GIS methods for ground water exploration in parts of Lalitpur district, U.P. 251–259. https://doi.org/10.1007/978-94-011-0391-6_19
Sayl, K. N., Muhammad, N. S., Yaseen, Z. M., & El-shafie, A. (2016). Estimation the physical variables of rainwater harvesting system using integrated gis-based remote sensing approach. Water Resources Management, 30(9), 3299–3313. https://doi.org/10.1007/S11269-016-1350-6/FIGURES/8
Sayl, K. N., Muhammad, N. S., & El-Shafie, A. (2017). Robust approach for optimal positioning and ranking potential rainwater harvesting structure (RWH): a case study of Iraq. Arabian Journal of Geosciences, 10(18), 1–12. https://doi.org/10.1007/S12517-017-3193-8/FIGURES/8
Sayl, K. N., Mohammed, A. S., & Ahmed, A. D. (2020b). GIS-based approach for rainwater harvesting site selection. IOP Conference Series: Materials Science and Engineering, 737(1), 012246. https://doi.org/10.1088/1757-899X/737/1/012246
Sayl, K. N., Mohammed, A. S., & Ahmed, A. D. (2020a). GIS-based approach for rainwater harvesting site selection. IOP Conference Series: Materials Science and Engineering, 737(1). https://doi.org/10.1088/1757-899X/737/1/012246
Sayl, K. G. multicriteria analysis in modeling optimum sites for rainwater harvesting, Adham, A., & Ritsema, C. J. (2020). A GIS-based multicriteria analysis in modeling optimum sites for rainwater harvesting. Hydrology, 7(3). https://doi.org/10.3390/HYDROLOGY7030051
Singh, J. P., Singh, D., & Litoria, P. K. (2009). Selection of suitable sites for water harvesting structures in Soankhad watershed, Punjab using remote sensing and geographical information system (RS&GIS) approach— A case study. Journal of the Indian Society of Remote Sensing 2009 37:1, 37(1), 21–35. https://doi.org/10.1007/S12524-009-0009-7
Vassoney, E., Mammoliti Mochet, A., Desiderio, E., Negro, G., Pilloni, M. G., & Comoglio, C. (2021). Comparing multi-criteria decision-making methods for the assessment of flow release scenarios from small hydropower plants in the Alpine Area. Frontiers in Environmental Science, 9, 104. https://doi.org/10.3389/FENVS.2021.635100/BIBTEX
Vujičić, M. D., & Blagojević, M. D. (2017). Comparative Analysis of Objective Techniques for Criteria Weighing in Two MCDM Methods on Example of an Air Conditioner Selection. https://doi.org/10.5937/tehnika1703422V
Waseem Ghani, M., Arshad, M., Shabbir, A., Shakoor, A., Mehmood, N., & Ahmad, I. (2013). Investigation of potential water harvesting sites at potohar using modeling approach. Pakistan Journal of Agricultural Sciences, 50(4), 723–729.
Yaseen, Z. M., Ali, Z. H., Salih, S. Q., & Al-Ansari, N. (2020). Prediction of risk delay in construction projects using a hybrid artificial intelligence model. Sustainability (switzerland), 12(4), 1–14. https://doi.org/10.3390/su12041514
Zamani, R., Ali, A. M. A., & Roozbahani, A. (2020). Evaluation of adaptation scenarios for climate change impacts on agricultural water allocation using fuzzy MCDM methods. Water Resources Management, 34(3), 1093–1110. https://doi.org/10.1007/S11269-020-02486-8/TABLES/6
Zavadskas, E. K., & Podvezko, V. (2016). Integrated Determination of Objective Criteria Weights in MCDM. 15(2), 267–283. https://doi.org/10.1142/S0219622016500036
Funding
The authors are grateful to the Department of Science & Technology, New Delhi, for providing financial assistance under the project vide grant no. DST/TMD/EWO/WTI/2K19/UWS-04(C1) titled Structured Dialogues for Sustainable Urban Water Management (SDSUWM). The authors have no relevant financial or non-financial interests to disclose.
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1. DP: Conceptualization; Methodology; Formal analysis; Visualization; Writing original draft; and Paper administration. 2. RG: Conceptualization; Guidance; Supervision; and Motivation.
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Appendix
Appendix
Site | Latitude | Longitude | Landmark |
---|---|---|---|
Site A | 26°51′36.18″N | 75°45′30.83″E | Heera path (Behind Indian Post Office) |
Site B | 26°51′32.76″N | 75°45′33.65″E | Abhimanyu Park (Sector 6) |
Site C | 26°51′32.68″N | 75°45′41.30″E | VT Road (Near VT Market) |
Site D | 26°51′39.77″N | 75°45′42.77″E | Baba Ramdev Mandir (Open Space) |
Site E | 26°51′41.86″N | 75°45′42.79″E | Agrasen Garden-Heera Path |
Site F | 26°51′44.03″N | 75°45′36.52″E | Mahrshi Dadhichi Bhawan Heera Path (Open Space) |
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Patil, D., Gupta, R. GIS-based multi-criteria decision-making for ranking potential sites for centralized rainwater harvesting. Asian J Civ Eng 24, 497–506 (2023). https://doi.org/10.1007/s42107-022-00514-z
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DOI: https://doi.org/10.1007/s42107-022-00514-z