Spatiotemporal Analysis of Water Resources in the Haridwar Region of Uttarakhand, India

Shray Pathak, Chandra Shekhar Prasad Ojha, Rahul Dev Garg, Min Liu, Daniel Jato-Espino and Rajendra Prasad Singh
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Shray Pathak: Key Laboratory of Geographical Information Sciences, Ministry of Education, and School of Geographic Sciences, Institute of Eco-Chongming, East China Normal University, Shanghai 200241, China
Chandra Shekhar Prasad Ojha: Department of Civil Engineering, Indian Institute of Technology Roorkee, Uttarakhand 247667, India
Rahul Dev Garg: Department of Civil Engineering, Indian Institute of Technology Roorkee, Uttarakhand 247667, India
Min Liu: Key Laboratory of Geographical Information Sciences, Ministry of Education, and School of Geographic Sciences, Institute of Eco-Chongming, East China Normal University, Shanghai 200241, China
Daniel Jato-Espino: Department of Transport and Projects and Processes Technology, Universidad de Cantabria, Av. de los Castros 46, 39005 Santander, Spain
Rajendra Prasad Singh: School of Civil Engineering, Southeast University, Nanjing 210096, China

Sustainability, 2020, vol. 12, issue 20, 1-17

Abstract: Watershed management plays a dynamic role in water resource engineering. Estimating surface runoff is an essential process of hydrology, since understanding the fundamental relationship between rainfall and runoff is useful for sustainable water resource management. To facilitate the assessment of this process, the Natural Resource Conservation Service-Curve Number (NRCS-CN) and Geographic Information Systems (GIS) were integrated. Furthermore, land use and soil maps were incorporated to estimate the temporal variability in surface runoff potential. The present study was performed on the Haridwar city, Uttarakhand, India for the years 1995, 2010 and 2018. In a context of climate change, the spatiotemporal analysis of hydro meteorological parameters is essential for estimating water availability. The study suggested that runoff increased approximately 48% from 1995 to 2010 and decreased nearly 71% from 2010 to 2018. In turn, the weighted curve number was found to be 69.24, 70.96 and 71.24 for 1995, 2010 and 2018, respectively. Additionally, a validation process with an annual water yield model was carried out to understand spatiotemporal variations and similarities. The study recommends adopting water harvesting techniques and strategies to fulfill regional water demands, since effective and sustainable approaches like these may assist in the simultaneous mitigation of disasters such as floods and droughts.

Keywords: water resources management; urban sprawl; rainfall-runoff modeling; spatiotemporal variation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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