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Nihar Ranjan Sahoo Nihar Ranjan Sahoo Written by Nihar Ranjan Sahoo, Senior Principal Architect & Head - Geospatial Technologies
on 22 May 2023

Resource depletion has made industries rethink their strategies and restructure their production and manufacturing techniques. With several renewable resources playing an imperative role in human progress and sustainability, leveraging digital technologies to optimally utilize these resources has gained exponential momentum. Water is one of the key natural resources for human survival, and its role in hydrology is vast.

In March 2022, the UN released the 2022 edition of the UN World Water Development Report (WWDR), which stated that 99% of the earth’s running freshwater is groundwater. Despite its inestimable worth, it tends to be poorly monitored and managed. Though groundwater has immense potential for social, economic, and environmental benefits, pollution and overuse pose a significant threat to this valuable resource. Once poisoned, aquifer zones or groundwater remain polluted, and it is nearly impossible to reverse this.

In several countries, groundwater is the primary source of water for everyday use. According to a study by the International Association of Hydrogeologists, “Over a third of the world’s population is supplied with drinking water from groundwater and, of the 700 million people worldwide who don’t have an adequate water supply at present, most will have to be supplied from groundwater in the future. Groundwater also meets over 40% of irrigation water demand, providing about a quarter of all industrial supplies.”

Real-time data and analytics

Effective groundwater management is becoming increasingly important as many regions worldwide face water scarcity and depletion of groundwater resources. It is critical to ensure that groundwater is used sustainably to meet society's needs while preserving the natural systems that support it. Groundwater management covers a range of activities, including monitoring groundwater levels, assessing groundwater quality, regulating groundwater use, and implementing strategies to recharge depleted aquifers. It ensures sustainable use of this valuable resource, considering the needs of present and future generations. It also involves coordinating efforts among stakeholders, such as water users, policymakers, scientists, and local communities.

Digital technology can play a crucial role in groundwater management by providing real-time data and analytics, improving efficiency, and promoting stakeholder transparency and collaboration. Here are some examples of how digital technology can be used for groundwater management:

Groundwater monitoring systems: Digital monitoring systems can provide real-time data on groundwater levels, quality, and other parameters, helping identify potential issues early on. This information can be used to adjust groundwater extraction rates and identify areas that require additional monitoring and management.

Spatial decision support systems: Digital tools such as decision support systems can help groundwater managers make informed decisions by analyzing data and providing recommendations based on specific parameters and constraints. These systems can also provide simulations of different management scenarios, helping to evaluate the potential impact of different management strategies.

Earth observation: Remote sensing technologies such as satellite imagery can be used to monitor groundwater resources over large areas, helping to identify trends and patterns in groundwater use and availability.

Groundwater modeling: Digital models can simulate how groundwater resources respond to different management scenarios and can help predict the impact of future development and climate change.

Making the invisible, visible

Groundwater hydrology is highly interdisciplinary, covering several earth and atmospheric sciences themes such as geomorphology, geology, geochemistry, and hydraulics. Advances in earth observation with high temporal and spectral resolution, machine learning algorithms, and computing have been effective in hydrological and hydraulic modeling, hydrological optimizations, water quality modeling, and aquifer mapping. Spatial machine learning algorithms help locate and delineate aquifers precisely, monitor water level, assess water quality, identify areas with over-extraction, and others using collation and synthesis of diverse and disparate datasets—geological, hydrological, geomorphological, topographical, water table depth—and several secondary data sources including ground truth and help in developing strategies to manage groundwater more sustainably.  Various machine learning algorithms, including those of Bayes, Fuzzy, Dempster-Shafer theory, logistic regression analysis in predictive modeling, and classification models—Logistic Regression, Support Vector Machines, K-Nearest Neighbors, Naïve Bayes, Support Vector Machine, Random Forest, Decision Tree—have been found effective in handling spatial data and carrying out an integrated analysis for targeting groundwater potential or pollution-vulnerable areas.

Several groundwater models—1D and 2D flow models—use data from wells and other sources to simulate groundwater flows through an aquifer. A geospatial decision support system helps create maps of the aquifer, identify recharge areas, and track the movement of groundwater over time. This information helps develop strategies for managing the groundwater resource, such as determining the optimal locations for pumping wells or identifying areas where recharge efforts would be most effective.  The system can be used to identify areas where groundwater is contaminated. Typically, groundwater resources around mines are negatively impacted through hazardous tailings, mine drainage, infiltration of polluted liquid effluents into the underground, and water quality degradation, affecting the ecological environment and vegetal and animal biodiversity.

Planning for sustainability

As the world's population continues to grow and the demand for water increases, geospatial technology will play an increasingly important role in managing our precious groundwater resources. A GIS-based spatial decision support system with diverse factors leading to groundwater exploration, exploitation, and water quality assessment can effectively and efficiently help strategies for managing and remediating contaminated groundwater.

GeoAI, with high-resolution EO data, will effectively manage groundwater resources—delineating aquifers, monitoring water levels, assessing water quality, and strategizing for effective and sustainable usage of resources. To formulate effective, sustainable management strategies, knowledge about the behavior of groundwater systems and their interaction with the environment is critical.

Cyient’s megatrend report that covers the sustainability theme has enabled conceptualizing solutions around sustainable groundwater resource development. It deliberates on efficient management of existing groundwater resources to meet the needs of the present and on a long-term basis in an equitable manner, sustaining its quality without negotiating the risks associated with damage to aquifer physical characteristics and storage capacity.


About the Author

Nihar R Sahoo is a PhD in Earth Sciences with specializations in GIS, Remote Sensing, Applied Statistics and has over 23 years of industry experience. His interest areas lie in building end-to-end development, deployment and operationalization of Geospatial Machine Learning Solutions with Earth Observation Data.

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