Earth, Atmosphere & Environment Sciences
Title : | Climate variability and human influence on depth-dependent groundwater recharge in semi-arid western parts of West Bengal using chemical, physical, and AI-based modeling |
Area of research : | Earth, Atmosphere & Environment Sciences |
Principal Investigator : | Dr. Pragnaditya Malakar, Jadavpur University, West Bengal |
Timeline Start Year : | 2023 |
Timeline End Year : | 2026 |
Contact info : | pragnadityamalakar@gmail.com |
Equipments : | Desktop Computer
Groundwater Level logger and Barologger |
Details
Executive Summary : | Global Groundwater depletion significantly affects the water availability for food production and domestic needs. Rapid agricultural expansion and unplanned urbanization have further aggravated this problem. India's water availability per capita is projected to reduce from 1,800 m³/yr in 2001 to 1,100 m³/yr in 2050. The water shortage is expected to impact food security, particularly in semi-arid areas of India, hosting more than 300 million people in India. The pervasive use of groundwater damages the trade-off between groundwater abstraction and groundwater restoration. Recharge indicates replenishment of groundwater resources and is a dominant control on human water-food nexus and ecosystem sustainability. An increase in temperature increases evaporative demand and decreases soil moisture, which leads to a reduction in recharge (and aquifer replenishment), resulting in groundwater depletion. Numerous climate models suggest future alterations in both precipitation characteristics and temperature, negatively impacting the hydrologic cycle and potentially reducing groundwater recharge. Thus, studies providing verifiable recharge estimates and linking groundwater recharge to climate variations and human influence merit further consideration. However, evaluating groundwater recharge is challenging due to the lack of detail on subsurface properties, irrigation, and pumping. While impacts of potential multipart drivers on water availability in reservoirs and rivers continue to receive much attention, understanding their effects on groundwater aquifers at fine spatiotemporal resolutions is still lacking, especially in the semi-arid regions with deeper groundwater levels. By harnessing the unsaturated zone tracer profile, a swath of big hydrologic datasets using novel methods and AI-based models, the overreaching goal of this study is to develop high-resolution groundwater recharge and storage (and level) estimates in the laterite and hard rock-dominated water-scarce western part of West Bengal, India. Novel contributions from this effort will include the development of multi-depth groundwater recharge estimates and new machine (and deep) learning algorithms, such as convolutional and long-short term memory networks with conservation principles. The proposed integrated framework will help answer several important science and management questions, including 1) How well can we estimate groundwater recharge at fine spatio-temporal resolution? 2) How different is the efficacy of physical, AI-based models w.r.t. the tracer-based models for obtaining groundwater recharge estimates, and does a hybrid approach render advantages? and 3) What are the physical controls of human influence, climate variability, and change on groundwater recharge patterns? The outcome of this integrated approach could provide a blueprint for assessing the emerging threats to food and water security in the region. |
Total Budget (INR): | 34,58,840 |
Organizations involved