Authors:
Ruhina Karani
1
;
Anant Joshi
2
;
Miloni Joshi
2
;
Sarmishta Velury
2
and
Saumya Shah
2
Affiliations:
1
Computers Department, Dwarkadas J. Sanghvi College of Engineering, University of Mumbai, Mumbai and India
;
2
Keyword(s):
Rainwater Harvesting, DEM, India, Drought.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Health Engineering and Technology Applications
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
Water scarcity is hitting new peaks every day and is exacerbated by the current rapid climatic change. Demand for clean water in India is very high, especially for agriculture and consumption. One way to cater to these needs is through rainwater harvesting. Through this paper, we propose a framework that optimizes the site selection for reservoirs by intersecting various data points. Our framework uses a three-step approach to combine stream networks, digital elevation, and soil quality to produce the most viable reservoir sites. Our framework is easy to implement and highly scalable. For the purpose of this paper and a proof of concept, we restrict our focus to the arid Beed district in the state of Maharashtra, India. Our approach provides consistent results that are corroborated by the manual inferences that can be drawn from the data under consideration.