Smart Aquifer Monitoring Using Remote Sensing and Deep Learning for Groundwater Sustainability
Main Article Content
Abstract
Groundwater constitutes one of the most critical freshwater resources supporting domestic consumption, agriculture, industrial production, and ecosystem sustainability. However, increasing groundwater extraction, climate variability, urbanization, and land-use changes have intensified aquifer depletion and degradation across many regions of the world. Conventional groundwater monitoring techniques, which primarily rely on field-based observations and piezometric measurements, often suffer from limited spatial coverage, high operational costs, and delayed decision-making. Recent advances in remote sensing technologies and deep learning algorithms provide unprecedented opportunities for large-scale, real-time, and data-driven aquifer monitoring. This study proposes a smart aquifer monitoring framework that integrates multisource remote sensing data, geospatial analytics, and deep learning models to enhance groundwater assessment and sustainability management. Satellite-derived indicators related to land surface temperature, vegetation dynamics, precipitation, evapotranspiration, soil moisture, and groundwater storage are combined with historical hydrogeological observations to develop predictive and monitoring capabilities. The framework aims to improve groundwater level forecasting, identify depletion hotspots, detect recharge patterns, and support sustainable groundwater governance. The integration of artificial intelligence with earth observation technologies offers a scalable, accurate, and cost-effective solution for long-term aquifer resilience and water resource sustainability under changing environmental conditions.
Article Details
Section
How to Cite
References
[1] S. Mohanty, A. Yadav, M. K. Jha, and P. K. Singh, “Groundwater science in the age of AI: Emerging paradigms and challenges,” Advances in Space Research, vol. 77, no. 4, pp. 4184–4207, Feb. 2026.
[2] Abdul Gaffar Sheik, Arvind Kumar, Anandan Govindan Sharanya, and Seshagiri Rao Amabati, “Machine learning-based monitoring and design of managed aquifer rechargers for sustainable groundwater management: Scope and challenges,” Environmental Science and Pollution Research, vol. 32, pp. 31572–31605, 2025.
[3] Ndubuisi Igwebuike, Moyinoluwa Ajayi, Chukwuma Okolie, Thokozani Kanyerere, and Todd Halihan, “Application of machine learning and deep learning for predicting groundwater levels in the West Coast Aquifer System, South Africa,” Earth Science Informatics, vol. 18, no. 6, pp. 1–24, 2025.
[4] Jayabrabu Ramakrishnan, John Rajan, Dinesh Mavaluru, Ravula Sahithya Ravali, and Karthik Srinivasan, “Transforming groundwater sustainability, management and development through deep learning,” Groundwater for Sustainable Development, vol. 27, Art. no. 101366, Nov. 2024.
[5] Bommi Rammohan, Pachaivannan Partheeban, Ranihemamalini Ranganathan, and Sundarambal Balaraman, “Groundwater quality prediction and analysis using machine learning models and geospatial technology,” Sustainability, vol. 16, no. 22, Art. no. 9848, 2024.
[6] Saeid Pourmorad, Mostafa Kabolizade, and Luca Antonio Dimuccio, “Artificial intelligence advancements for accurate groundwater level modelling: An updated synthesis and review,” Applied Sciences, vol. 14, no. 16, Art. no. 7358, 2024.
[7] Fabian J. Zowam and Adam M. Milewski, “Groundwater level prediction using machine learning and geostatistical interpolation models,” Water, vol. 16, no. 19, Art. no. 2771, 2024.
[8] Fan Feng, Hamzeh Ghorbani, and Ahmed E. Radwan, “Predicting groundwater level using traditional and deep machine learning algorithms,” Frontiers in Environmental Science, vol. 12, Art. no. 1291327, 2024.
[9] Mohamed Hamdy Eid, Ali Shebl, and Mustafa Eissa, “Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems,” Heliyon, vol. 10, no. 12, Art. no. e32992, Jun. 2024.
[10] Zahra Jamshidzadeh, Sarmad Dashti Latif, Mohammad Ehteram, Zohreh Sheikh Khozani, Ali Najah Ahmed, and Mohsen Sherif, “An advanced hybrid deep learning model for predicting total dissolved solids and electrical conductivity in coastal aquifers,” Environmental Sciences Europe, vol. 36, no. 20, pp. 1–22, 2024.
[11] Sandeep Gupta, S.V.N. Sreenivasu, Kuldeep Chouhan, Anurag Shrivastava, Bharti Sahu, Ravindra Manohar Potdar, Novel Face Mask Detection Technique using Machine Learning to control COVID’19 pandemic, Materials Today: Proceedings, Volume 80, Part 3, 2023, Pages 3714-3718, ISSN 2214-7853, https://doi.org/10.1016/j.matpr.2021.07.368.
[12] K. Chouhan, A. Singh, A. Shrivastava, S. Agrawal, B. D. Shukla and P. S. Tomar, "Structural Support Vector Machine for Speech Recognition Classification with CNN Approach," 2021 9th International Conference on Cyber and IT Service Management (CITSM), Bengkulu, Indonesia, 2021, pp. 1-7, doi: 10.1109/CITSM52892.2021.9588918.
[13] S. Gupta, S. V. M. Seeswami, K. Chauhan, B. Shin, and R. Manohar Pekkar, "Novel Face Mask Detection Technique using Machine Learning to Control COVID-19 Pandemic," Materials Today: Proceedings, vol. 86, pp. 3714–3718, 2023.
[14] H. Douman, M. Soni, L. Kumar, N. Deb, and A. Shrivastava, "Supervised Machine Learning Method for Ontology-based Financial Decisions in the Stock Market," ACM Transactions on Asian and Low Resource Language Information Processing, vol. 22, no. 5, p. 139, 2023.
[15] Singh, C., Basha, S. A., Bhushan, A. V., Venkatesan, M., Chaturvedi, A., & Shrivastava, A. (2025). A Secure IoT Based Wireless Sensor Network Data Aggregation and Dissemination System. Cybernetics and Systems, 56(6), 784–796. https://doi.org/10.1080/01969722.2023.2176653
[16] L. Chawla, A. Shrivastava, M. I. Habelalmateen, H. Shekhar, P. Mittal and S. Sharma, "Federated Foundation Models for Healthcare Diagnostics," 2025 2nd International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI), Raipur, India, 2025, pp. 1-6, doi: 10.1109/ICAIIHI67124.2025.11403022.
[17] V. Nimbalkar, L. Chawla, M. M. Adnan, A. Bhansali, M. Gupta and R. Kalra, "A Human-Centered Approach to Interpretable Machine Learning in Clinical Decision Support Systems," 2025 2nd International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI), Raipur, India, 2025, pp. 1-5, doi: 10.1109/ICAIIHI67124.2025.11403473.
[18] D. Chawla, D. Chawla, A. Shrivastava, M. I. Habelalmateen, M. Dixit and S. P. Dwivedi, "Explainable AI for Mental Health Diagnosis: Enhancing Transparency, Trust, and Clinical Decision-Making," 2025 2nd International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI), Raipur, India, 2025, pp. 1-6, doi: 10.1109/ICAIIHI67124.2025.11403514
[19] D. Chawla, D. Chawla, A. Shrivastava, M. M. Adnan, B. Sireesha and I. Khan, "Blockchain and Federated Learning Integration for Secure IoT and Cyber-Physical Systems," 2025 IEEE 5th International Conference on ICT in Business Industry & Government (ICTBIG), Indore, Madhya Pradesh, India, India, 2025, pp. 1-7, doi: 10.1109/ICTBIG68706.2025.11323990.
[20] Chawla, D. Chawla, A. Shrivastava, M. M. Adnan, B. Sireesha and I. Khan, "AI-Driven Predictive Infrastructure for Smart and Sustainable Cities," 2025 IEEE 5th International Conference on ICT in Business Industry & Government (ICTBIG), Indore, Madhya Pradesh, India, India, 2025, pp. 1-7, doi: 10.1109/ICTBIG68706.2025.11324009.
[21] Saxena, P., and Saxena, V. (2022). “Comparative Study of White Gaussian Noise Reduction for Different Signals Using Wavelet”. International Journal of Research -GRANTHAALAYAH, 10(7), 112–123. https://doi.org/10.29121/granthaalayah.v10.i7.2022.4711
[22] Saxena Parul, Umang Saini, and Vinay Saxena. "Design and implementation of sound signal reconstruction algorithm for blue hearing system using wavelet." Automation and Computation. CRC Press, 2023. 405-411.
[23] K. Himabindu, V. Saxena, S. P, K. K, E. Sathish and D. Suganthi, "IoT–Fuzzy Logic Hybrid Framework for Crop Monitoring and Yield Prediction in Smart Agriculture," 2025 2nd International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS), Hassan, India, 2025, pp. 1-6, doi: 10.1109/IACIS65746.2025.11211067.
[24] Saxena Vinay. (2012) “Fourier Descriptors under Rotation, Scaling, Translation and Various Distortion for Hand Drawn Planar Curves”. Journal of Experimental Sciences, vol. 3, no. 1, 05-07. https://updatepublishing.com/journal/index.php/jes/article/view/1905.
[25] Saxena Vinay, and Kapoor V.V., (2011), “Behavior of Normalized Moments under Distortion and Optimization, Recent Research in Science and Technology”, 3(7),73-76. https://updatepublishing.com/journal/index.php/rrst/article/view/743
[26] Vinay Saxena, (2014), “International Journal of Emerging Technologies in Computational and Applied Sciences”, 9(2), 170-175. https://iasir.net/files/ijetcaspapers/ijetcas14-567.pdf
[27] Saxena, P., Saxena, V., Basvant, M. S. Lohumi, Y.Saraswat, M. Sankhyan, A. Deepak, A. and Shrivastava, A.. (2024) “Fuzzy-Based Medical Image Processing and Analysis”, International Journal of Intelligent Systems and Applications in Engineering, 12(16s), pp. 320–327.
[28] Saxena, V.,Singh, M., Saxena, P., Singh, M., Srivastava, A. P., Kumar, N., Deepak, A.& Shrivastava, A.. (2024). “Utilizing Support Vector Machines for Early Detection of Crop Diseases in Precision Agriculture a Data Mining Perspective”. International Journal of Intelligent Systems and Applications in Engineering, 12(16s), 281–288.
[28] P. Bagane, S. G. Joseph, A. Singh, A. Shrivastava, B. Prabha and A. Shrivastava, "Classification of Malware using Deep Learning Techniques," 2021 9th International Conference on Cyber and IT Service Management (CITSM), Bengkulu, Indonesia, 2021, pp. 1-7, doi: 10.1109/CITSM52892.2021.9588795.
[29] Attar T. V., & Momin S. (2025). Nanotechnology in drug delivery: Challenges and future prospects. Advances in Bioresearch, 16(2), 63–69.
[30] Das B., Attar T. V., Sharma N., Sharma R., Anandhan A., & Acharya S. (2025). Biochemistry to solve environmental degradation and sustainable future. International Journal of Environmental Sciences, 11(20s), 2527–2545. https://doi.org/10.64252/bz71eq58 80. Dhanke J., Attar T. V. & Zode, P. (2025). Optimal transport theory in machine learning: Applications to generative modelling and domain adaptation. International Journal of Environmental Sciences, 11(21s), 2613–2630.
[31] Divate S., Attar T. V., Patil M. A., Yadav T. P., & Wagh G. D. (2025). Synthesis and characterization applications of nanoparticles for photocatalytic degradation of organic dyes. International Journal of Environmental Sciences, 11(23s), 695–712. https://doi.org/10.64252/n0shfg48
[32] Attar T. V. (2022). Investigations on enhanced DC conductivity and dielectric properties by rare earth doping of lanthanum fluoride. Shodhasamhita, 9(2), 180–184.
[33] Attar T. V. (2022). Studies on cytotoxicity of LaF3: Pr, Ho nanoparticles for possible biomedical applications. Shodhasamhita, 9(2/1), 254–257.
[34] Dr. Mohd. Talib Ather Ansari, (2025). “One Nation One Subscription' Digital Library Resources to Enrich Teacher Educators for Practical Knowledge and Foster an Engaging Teaching-Learning Ecosystem” South eastern European Journal of Public Health, ISSN: 2197-5248, Volume XXVI, S1, 2025, P. 7166-7181, Published by- Uphill’s Publishers LLC, Sheridan, Wyoming, United States. DOI: https://doi.org/10.5281/zenodo.16325646 Available at https://seejph.com/index.php/seejph/article/view/6671/4424
[35] Dr. Hina Hasan, & Dr. Mohd. Talib Ather Ansari, (2025). “Techno-Pedagogical Practices in Inclusive Education: Comparing Approaches for Slow Learners across Teacher Education Programme” TPM - Testing, Psychometrics, Methodology in Applied Psychology, (Scopus Q3 journal), ISSN- 1972-6325, Impact Factor- 0.505, Vol-32, Page from 222-235-2025, Published by Cises DOI: https://doi.org/10.5281/zenodo.17746118 Available at https://tpmap.org/submission/index.php/tpm/article/view/3162/2364
[36] Dr. Mohd. Talib Ather Ansari, & Dr. Hina Hasan. (2024). “Need And Importance of Translation of Indian Languages Vice Versa to Promote Indian Educational Scenario”. Educational Administration: Theory and Practice, 30(1), ISSN:1300-4832E-
[37] S. N. Siri, H. B. Divyashree, and S. P. Mala, "The Memorable Assistant: An IoT-Based Smart Wearable Alzheimer's Assisting Device," in Proc. 5th Int. Conf. Comput. Syst. Inf. Technol. Sustain. Solut. (CSITSS), 2021. DOI: 10.1109/CSITSS54238.2021.9682788
[38] D. H. Balachandra, P. C. Gowda, and N. P. K. Shivaprasad, "Secure Cluster-Based Routing Using Multi Objective-Trust Centric Artificial Algae Algorithm for Wireless Sensor Network," Int. J. Electr. Comput. Eng., vol. 13, no. 2, pp. 1618–1628, 2023, DOI: https://doi.org/10.11591/ijece.v13i2.pp1618-1628
[39] H. B. Divyashree, C. Puttamadappa, and K. S. Nandini Prasad, "Performance Analysis and Enhancement of QoS Parameters for Real-Time Applications in MANETs-Comparative Study," in Proc. 5th IEEE Int. Conf. Recent Trends Electron. Inf. Commun. Technol. (RTEICT), 2020, pp. 256–260, DOI: 10.1109/RTEICT49044.2020.9315547
[40] V. H. Patil, A. Shrivastava, D. Verma, A. L. N. Rao, P. Chaturvedi and S. V. Akram, "Smart Agricultural System Based on Machine Learning and IoT Algorithm," 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), Tashkent, Uzbekistan, 2022, pp. 740-746, doi: 10.1109/ICTACS56270.2022.9988530.
[41] S. Chakaborty, Y. D. Borole, A. S. Nanoty, A. Shrivastava, S. K. Jain and M. L. Rinawa, "Smart Remote Solar Panel Cleaning Robot with Wireless Communication," 2021 9th International Conference on Cyber and IT Service Management (CITSM), Bengkulu, Indonesia, 2021, pp. 1-5, doi: 10.1109/CITSM52892.2021.9588917.
[42] A. Rana, V. Khurana, A. Shrivastava, D. Gangodkar, D. Arora and A. Kumar Dixit, "A ZEBRA Optimization Algorithm Search for Improving Localization in Wireless Sensor Network," 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), Tashkent, Uzbekistan, 2022, pp. 817-824, doi: 10.1109/ICTACS56270.2022.9988278.
[43] P. Bogane, S. G. Joseph, A. Singh, B. Proble, and A. Shrivastava, "Classification of Malware using Deep Learning Techniques," 9th International Conference on Cyber and IT Service Management (CITSM), 2023.