Emerging Trends and Technologies for Conservation and Sustainable Approach in Groundwater Management DOI

Lisha Borgohain,

Mayurakshi Gogoi,

Jayashri Dutta

et al.

Advances in environmental engineering and green technologies book series, Journal Year: 2024, Volume and Issue: unknown, P. 175 - 202

Published: Dec. 6, 2024

Groundwater is a natural renewable resource vital for any life on Earth. management of emerging concern the conservation and protection this resource. With advent innovative technologies, managing such resources become easier to some extent. This chapter illustrates advanced their contribution, challenges future prospects sustainable groundwater. AI methods have widespread in decision-making recent years are accepted globally due cost-effectiveness, time-saving, efficient nature. AI-driven models provide precise analytical modelling, real-time monitoring, data integration groundwater management. Innovative can detect vulnerable regions that prone pollution depletion level draw attention scientists, local people policymakers prompt intervention.

Language: Английский

Enhancing the accuracy of groundwater level prediction at different scales using spatio-temporal graph convolutional model DOI
Long Chen, Dezheng Zhang, Jianwei Xu

et al.

Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(2)

Published: Feb. 1, 2025

Language: Английский

Citations

1
Hydrogeological Insights: Assessing Groundwater in Trans-Yamuna Using Decision Making Method, Prayagraj, India DOI
Swapnil Sharma, H. K. Pandey, Rakesh Singh

et al.

Iranian Journal of Science and Technology Transactions of Civil Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Language: Английский

Citations

0
Multi-Frequency SAR Polarimetry and Ground Penetrating Radar for Paleochannel Identification in the Thar Desert, India DOI
Sashikanta Sahoo, Ajanta Goswami, Shubham Awasthi

et al.

Remote Sensing Applications Society and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 101533 - 101533

Published: April 1, 2025

Language: Английский

Citations

0
Projection of groundwater level fluctuations using deep learning and dynamic system response models in a drought affected area DOI
Dilip Roy,

Chitra Rani Paul,

Md. Panjarul Haque

et al.

Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(1)

Published: Jan. 1, 2025

Language: Английский

Citations

0
Hybrid Drought Forecasting Framework for Water‐Scarce Regions Based on Support Vector Machine and Precipitation Index DOI
Abdullah A. Alsumaiei

Hydrological Processes, Journal Year: 2024, Volume and Issue: 38(12)

Published: Dec. 1, 2024

ABSTRACT Drought is a natural event that slowly deteriorates water reserves. This study aims to develop machine learning–based computational framework for monitoring drought status in water‐scarce regions. The proposed integrates the precipitation index (PI) with support vector models forecast occurrences based on an autoregressive modelling scheme. Due suitability of PI analysis arid climates, developed hybrid model appropriate regions limited rainfall. used historical dataset from 1958 2020 at Kuwait International Airport, City. area characterised by scarce rainfall and vulnerable severe shortages owing resources. Initially, time‐series datasets were examined stationarity validate utility model. autocorrelation function test was significantly associated time series 12‐ 24‐month drought‐monitoring scales. Predictive forecasting constructed predict up 3 months advance. Statistical evaluation metrics assess performance results showed strong association between observed predicted events, coefficients determination ( R 2 ) ranging 0.865 0.925 provide managers efficient reliable tools assist preparing management plans. provides guidance improving resource resilience under shortage scenarios other climatic applying suitable indices conjunction robust data‐driven models. baseline policymakers worldwide establish sustainable conservation strategies crucial insights disaster preparation.

Language: Английский

Citations

1
An improved equation for potential discharge estimation in groundwater basin delineated watershed DOI Creative Commons

Christine Mayavani,

Indratmo Soekarno,

Mohammad Farid

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 103238 - 103238

Published: Oct. 1, 2024

Language: Английский

Citations

1
Uncertainty Assessment of Ensemble Base Machine Learning Modeling for Multi-step Ahead Forecasting of Dam Reservoir Inflows DOI
Vahid Nourani,

Bagher Nikoufar,

Nardin Jabbarian Paknezhad

et al.

Iranian Journal of Science and Technology Transactions of Civil Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 26, 2024

Language: Английский

Citations

1
Emerging Trends and Technologies for Conservation and Sustainable Approach in Groundwater Management DOI

Lisha Borgohain,

Mayurakshi Gogoi,

Jayashri Dutta

et al.

Advances in environmental engineering and green technologies book series, Journal Year: 2024, Volume and Issue: unknown, P. 175 - 202

Published: Dec. 6, 2024

Groundwater is a natural renewable resource vital for any life on Earth. management of emerging concern the conservation and protection this resource. With advent innovative technologies, managing such resources become easier to some extent. This chapter illustrates advanced their contribution, challenges future prospects sustainable groundwater. AI methods have widespread in decision-making recent years are accepted globally due cost-effectiveness, time-saving, efficient nature. AI-driven models provide precise analytical modelling, real-time monitoring, data integration groundwater management. Innovative can detect vulnerable regions that prone pollution depletion level draw attention scientists, local people policymakers prompt intervention.

Language: Английский

Citations

0