The Experts below are selected from a list of 4512 Experts worldwide ranked by ideXlab platform
Bithin Datta - One of the best experts on this subject based on the ideXlab platform.
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Saltwater Intrusion prediction in coastal aquifers utilizing a weighted average heterogeneous ensemble of prediction models based on dempster shafer theory of evidence
Hydrological Sciences Journal-journal Des Sciences Hydrologiques, 2020Co-Authors: Dilip Kumar Roy, Bithin DattaAbstract:Accurate and meaningful prediction of Saltwater Intrusion in coastal aquifers requires appropriate prediction tools. Artificial intelligence-based prediction models and their ensembles have been a ...
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modelling Saltwater Intrusion processes and development of a multi objective strategy for management of coastal aquifers utilizing planned artificial freshwater recharge
Modeling Earth Systems and Environment, 2018Co-Authors: Alvin Lal, Bithin DattaAbstract:The need for freshwater is emerging as the utmost critical resource issue facing humanity. In several arid and semi-arid parts of the world, groundwater resources are being used as an alternative source of freshwater. Excessive and/or unplanned groundwater withdrawals have a negative impact on the aquifer. Groundwater withdrawn from coastal aquifers are susceptible to contamination by Saltwater Intrusion. This study investigates the efficiency and viability of using artificial freshwater recharge (AFR) to increase fresh groundwater pumping from production wells for beneficial use. A three dimensional (3D), transient, density dependent, finite element based flow and transport model of an illustrative coastal aquifer is implemented using FEMWATER code. First, the effect of AFR on inland encroachment of saline water is quantified for existing scenarios. Specifically, groundwater head and salinity concentration differences at monitoring locations before and after artificial recharge is presented. Second, a multi-objective management model incorporating groundwater pumping and AFR is implemented to control groundwater salinization in an illustrative coastal aquifer system. To avoid computational burden and ensure computational feasibility, the numerical flow and transport simulation model is substituted by the new support vector regression (SVR) predictive models as approximate simulators in the simulation–optimization framework for developing optimal management strategies. The performance evaluation results indicated that the SVR models were adequately trained and were capable of approximating Saltwater Intrusion processes in the aquifer. Multi-objective genetic algorithm (MOGA) is used to solve the multi-objective optimization problem. The Pareto-optimal front obtained as solution from the SVR–MOGA optimization model presented a set of optimal solutions needed for the sustainable management of the coastal aquifer. The pumping strategies obtained as Pareto optimal solutions with and without freshwater recharge wells showed that Saltwater Intrusion is sensitive to the AFR. Also, the hydraulic head lenses created by AFR can be used as one practical option to control Saltwater Intrusion in coastal aquifers. The developed 3D Saltwater Intrusion model, predictive capability of the developed SVR models and the feasibility of using the proposed linked multi-objective SVR–MOGA optimization model makes the proposed methodology potentially attractive in solving large scale regional Saltwater Intrusion management problems.
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genetic algorithm tuned fuzzy inference system to evolve optimal groundwater extraction strategies to control Saltwater Intrusion in multi layered coastal aquifers under parameter uncertainty
Modeling Earth Systems and Environment, 2017Co-Authors: Bithin DattaAbstract:Excessive withdrawal of groundwater resources poses significant challenges to the management of Saltwater Intrusion processes in coastal aquifers. Optimization of groundwater withdrawal rates plays a vital role in sustainable management of coastal aquifers. This study proposes a genetic algorithm (GA) tuned Fuzzy Inference System (FIS) hybrid model (GA-FIS) for developing a regional scale Saltwater Intrusion management strategy. GA is used to tune the FIS parameters in order to obtain the optimal FIS structure. The GA-FIS models thus obtained are linked externally to the Controlled Elitist Multi-objective Genetic Algorithm (CEMGA) in order to derive optimal pumping management strategies using a linked simulation–optimization approach. The performance of the hybrid GA-FIS-CEMGA based Saltwater Intrusion management model is compared with that of a basic adaptive neuro fuzzy inference system (ANFIS) based management model (ANFIS-CEMGA). The parameters of the ANFIS model are tuned using hybrid algorithm. To achieve computational efficiency, the proposed optimization routine is run in a parallel processing platform. An illustrative multi-layered coastal aquifer system is used to evaluate the performances of both management models. The illustrative aquifer system considers uncertainties associated with the hydrogeological parameters e.g. hydraulic conductivity, compressibility, bulk density, and aquifer recharge. The evaluation results show that the proposed Saltwater Intrusion management models are able to evolve reliable optimal groundwater extraction strategies to control Saltwater Intrusion for the illustrative multi-layered coastal aquifer system. However, a closer look at the performance evaluation results demonstrate the superiority of the GA-FIS-CEMGA based management model over ANFIS-CEMGA based Saltwater Intrusion management model.
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multi objective management of Saltwater Intrusion in coastal aquifers using genetic programming and modular neural network based surrogate models
Journal of Hydrology, 2010Co-Authors: J Sreekanth, Bithin DattaAbstract:Surrogate model based methodologies are developed for evolving multi-objective management strategies for Saltwater Intrusion in coastal aquifers. Two different surrogate models based on genetic programming (GP) and modular neural network (MNN) are developed and linked to a multi-objective genetic algorithm (MOGA) to derive the optimal pumping strategies for coastal aquifer management, considering two objectives. Trained and tested surrogate models are used to predict the salinity concentrations at different locations resulting due to groundwater extraction. A two-stage training strategy is implemented for training the surrogate models. Surrogate models are initially trained with input patterns selected uniformly from the entire search space and optimal management strategies based on the model predictions are derived from the management model. A search space adaptation and model retraining is performed by identifying a modified search space near the initial optimal solutions based on the relative importance of the variables in salinity prediction. Retraining of the surrogate models is performed using input–output samples generated in the modified search space. Performance of the methodologies using GP and MNN based surrogate models are compared for an illustrative study area. The capability of GP to identify the impact of input variables and the resulting parsimony of the input variables helps in developing efficient surrogate models. The developed GP models have lesser uncertainty compared to MNN models as the number of parameters used in GP is much lesser than that in MNN models. Also GP based model was found to be better suited for optimization using adaptive search space.
Rafael Munozcarpena - One of the best experts on this subject based on the ideXlab platform.
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groundwater salinity in a floodplain forest impacted by Saltwater Intrusion
Journal of Contaminant Hydrology, 2014Co-Authors: David Kaplan, Rafael MunozcarpenaAbstract:Coastal wetlands occupy a delicate position at the intersection of fresh and saline waters. Changing climate and watershed hydrology can lead to Saltwater Intrusion into historically freshwater systems, causing plant mortality and loss of freshwater habitat. Understanding the hydrological functioning of tidally influenced floodplain forests is essential for advancing ecosystem protection and restoration goals, however finding direct relationships between hydrological inputs and floodplain hydrology is complicated by interactions between surface water, groundwater, and atmospheric fluxes in variably saturated soils with heterogeneous vegetation and topography. Thus, an alternative method for identifying common trends and causal factors is required. Dynamic factor analysis (DFA), a time series dimension reduction technique, models temporal variation in observed data as linear combinations of common trends, which represent unexplained common variability, and explanatory variables. DFA was applied to model shallow groundwater salinity in the forested floodplain wetlands of the Loxahatchee River (Florida, USA), where altered watershed hydrology has led to changing hydroperiod and salinity regimes and undesired vegetative changes. Long-term, high-resolution groundwater salinity datasets revealed dynamics over seasonal and yearly time periods as well as over tidal cycles and storm events. DFA identified shared trends among salinity time series and a full dynamic factor model simulated observed series well (overall coefficient of efficiency, Ceff=0.85; 0.52≤Ceff≤0.99). A reduced multilinear model based solely on explanatory variables identified in the DFA had fair to good results (Ceff=0.58; 0.38≤Ceff≤0.75) and may be used to assess the effects of restoration and management scenarios on shallow groundwater salinity in the Loxahatchee River floodplain.
David Kaplan - One of the best experts on this subject based on the ideXlab platform.
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restore or retreat Saltwater Intrusion and water management in coastal wetlands
Ecosystem Health and Sustainability, 2017Co-Authors: Elliott White, David KaplanAbstract:Coastal wetlands perform a unique set of physical, chemical, and biological functions, which provide billions of dollars of ecosystem services annually. These wetlands also face myriad environmenta...
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groundwater salinity in a floodplain forest impacted by Saltwater Intrusion
Journal of Contaminant Hydrology, 2014Co-Authors: David Kaplan, Rafael MunozcarpenaAbstract:Coastal wetlands occupy a delicate position at the intersection of fresh and saline waters. Changing climate and watershed hydrology can lead to Saltwater Intrusion into historically freshwater systems, causing plant mortality and loss of freshwater habitat. Understanding the hydrological functioning of tidally influenced floodplain forests is essential for advancing ecosystem protection and restoration goals, however finding direct relationships between hydrological inputs and floodplain hydrology is complicated by interactions between surface water, groundwater, and atmospheric fluxes in variably saturated soils with heterogeneous vegetation and topography. Thus, an alternative method for identifying common trends and causal factors is required. Dynamic factor analysis (DFA), a time series dimension reduction technique, models temporal variation in observed data as linear combinations of common trends, which represent unexplained common variability, and explanatory variables. DFA was applied to model shallow groundwater salinity in the forested floodplain wetlands of the Loxahatchee River (Florida, USA), where altered watershed hydrology has led to changing hydroperiod and salinity regimes and undesired vegetative changes. Long-term, high-resolution groundwater salinity datasets revealed dynamics over seasonal and yearly time periods as well as over tidal cycles and storm events. DFA identified shared trends among salinity time series and a full dynamic factor model simulated observed series well (overall coefficient of efficiency, Ceff=0.85; 0.52≤Ceff≤0.99). A reduced multilinear model based solely on explanatory variables identified in the DFA had fair to good results (Ceff=0.58; 0.38≤Ceff≤0.75) and may be used to assess the effects of restoration and management scenarios on shallow groundwater salinity in the Loxahatchee River floodplain.
Tom Gleeson - One of the best experts on this subject based on the ideXlab platform.
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vulnerability of coastal aquifers to groundwater use and climate change
Nature Climate Change, 2012Co-Authors: Grant Ferguson, Tom GleesonAbstract:There are concerns that sea-level rise resulting from climate change could lead to Saltwater Intrusion into coastal aquifers. However, a study shows that groundwater extraction is the main driver of Saltwater Intrusion in the United States, highlighting the importance of sustainable water management.
Mutasem El-fadel - One of the best experts on this subject based on the ideXlab platform.
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Social Perception of Public Water Supply Network and Groundwater Quality in an Urban Setting Facing Saltwater Intrusion and Water Shortages
Environmental management, 2016Co-Authors: Ibrahim Alameddine, Gheeda Jawhari, Mutasem El-fadelAbstract:Perceptions developed by consumers regarding the quality of water reaching their household can affect the ultimate use of the water. This study identified key factors influencing consumers’ perception of water quality in a highly urbanized coastal city, experiencing chronic water shortages, overexploitation of groundwater, and accelerated Saltwater Intrusion. Household surveys were administered to residents to capture views and perceptions of consumed water. Concomitantly, groundwater and tap water samples were collected and analyzed at each residence for comparison with perceptions. People’s rating of groundwater quality was found to correlate to the measured water quality both in the dry and wet seasons. In contrast, perceptions regarding the water quality of the public water supply network did not show any correlation with the measured tap water quality indicators. Logistic regression models developed to predict perception based on salient variables indicated that age, apartment ownership, and levels of total dissolved solids play a significant role in shaping perceptions regarding groundwater quality. Perceptions concerning the water quality of the public water supply network appeared to be independent of the measured total dissolved solids levels at the tap but correlated to those measured in the wells. The study highlights misconceptions that can arise as a result of uncontrolled cross-connections of groundwater to the public supply network water and the development of misaligned perceptions based on prior consumption patterns, water shortages, and a rapidly salinizing groundwater aquifer.
