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A robust Simulation–Optimization (SO) framework is proposed for the cost-effective design of groundwater remediation schemes in contaminated aquifers. The simulation involves the solution of coupled groundwater flow and transport phenomena using the Meshless Local Petrov Galerkin (MLPG) method, selected due to its high stability, truly meshless nature and independence from complex meshing process. The MLPG simulator is integrated with four metaheuristic optimization techniques: the emerging nature-inspired Whale Optimization Algorithm (WOA), Aquila Optimization (AO), Golden Jackal Optimization (GJO) and the widely used Differential Evolution (DE), forming MLPG-WOA, MLPG-AO, MLPG-GJO and MLPG-DE models. These SO models advance existing approaches by minimizing remediation costs while simultaneously optimizing extraction rates and remediation well locations in Pump and Treat (PAT) remediation schemes. Additionally, the proposed models have several advantages including minimal sensitivity to initial estimates, simplified fine tuning, rapid convergence and reliable designs. The performance of the metaheuristic algorithms is investigated through two case studies of hypothetical and field-type aquifers. All the models effectively design remediation strategies that reduce contamination within permissible limits within the remediation period. In the hypothetical case, a single well extracting 1368 m 3 /day for 1000 days is identified by MLPG-WOA as the least-cost solution of INR 4,115,238. For the field-type aquifer, nine-well strategy with the lowest cost of INR 145,072,081 is identified by MLPG-DE. Optimal well placement zones are identified in both the case studies. The proposed SO models are thus found to be efficient in providing reliable remediation designs and can serve as alternative to the existing PAT remediation models.

Coastal cities contrive to spread their transformative influence both into the hinterland, along the coastline, and into the coastal waters themselves. These effects will be intensified in urban agglomerations as the concentration of population and allied activities are more pronounced there compared to the inland regions. Indian coastal cities are no exception, and it is high time to delineate these hazard-prone regions and implement proper mitigation and adaptation strategies at city scale. This review article provides an assessment regarding quantification, management and climate change impacts of flood risks in Surat, Mumbai, Chennai and Kolkata, which are the most populated coastal cities in India. The flood impacts considered in the existing or prevailing analyses are associated with adverse effects on population, land use of cities, transportation and economy caused by different types of riverine and urban flooding, though coastal flooding, tsunami and storm surge effects are less studied. Mumbai and Kolkata are relatively progressive in the assessment of flood risks and adaptation. The present article also suggests strategies to evaluate the relative progress in the assessment of past and future risks and adaptation. We also discuss the mitigation and adaptation strategies considering the historical importance of these cities. We propose that the strategies should be implemented considering public opinion and should be initialized at the grass root level. Though it is technically difficult to re-plan the city structures in the current scenario, it is possible to adapt to and mitigate the effects of natural hazards through suitable planning and management with the integrated cooperation and involvement of citizens and government as well.

In this study, the impacts of land use/land cover (LULC) and climate change on the streamflow and sediment yield were investigated for the Payaswani River Basin, Western Ghats, India. The LULC was determined using Landsat images, and climate data were procured from five general circulation models for representative concentration pathway (RCP) 4.5 (moderate emission) and 8.5 (high emission). The land change modeler was used to derive the future LULC and its changes from 1988 (historical) to 2030 (future) by using the transition matrix method. The SWAT model was used to assess the impacts of LULC and climate change for the streamflow and sediment yield. The results showed that decrease in forests and grasslands and increase in plantation, agricultural, and urban areas from 1988 to 2030 would lead to an increase in the mean streamflow (11.23%) and sediment yield (17.41%). Under RCP 4.5, climate change would decrease the streamflow by 2.38% in 2030. However, under RCP 8.5, climate change would increase the streamflow by 0.12% in 2030. The sediment yield under RCP 4.5 and 8.5 would increase by 1.23% and 3.33%, respectively. In comparison with the baseline condition, by 2030 future changes in the LULC and climate would increase the streamflow by 7.05% and 11.71% under RCP 4.5 and 8.5, respectively. The sediment yield would increase by 7.92% and 27.11% under RCP 4.5 and 8.5, respectively. The streamflow and sediment yield were predicted to increase in the summer and winter but decrease in the monsoon season.

The general circulation models (GCMs) and emission scenarios (RCP 4.5 and 8.5) have proven to be significantly functional in evaluating the impacts of climate change (CC) on hydrology, although their performance and accuracy varies on a regional scale. The objective of the present study is to evaluate the performance of five CMIP5 GCMs (CanESM2, BNU-ESM, CNRM-CM5, MPI-ESM-LR and MPI-ESM-MR) on a regional scale in the West Flowing River Basins-2 (WFRB-2) in India to model the impact of CC and its scenario uncertainty using reliability ensemble average (REA) method. For quantifying the results, the upper, middle and lower regions of WFRB-2 are separately analysed. The MPIMR and MPILR GCM model shows highest reliability factor range (0.3–0.6) in predicting the annual mean and annual maximum rainfall for most of the grids in the region. The GCM-simulated runoff using VIC (variable infiltration capacity) model is evaluated using statistical parameters such as root mean square error (RMSE), percentage bias (Pbias) and standard deviation (Std). The annual mean (maximum) runoff obtained using REA ensemble shows least RMSE, Pbias and Std values, i.e. 21.08%, 9.10 mm and 8.9 mm (6%, 39.1 mm, 39.1 mm), respectively for the middle region, which demonstrates higher reliability of GCM outputs in the flood-prone regions of WFRB-2. Furthermore, the future projection of annual maximum rainfall/runoff shows an increase of 50 mm/15 mm in the near future (2011–2040) for lower and 20 mm/6 mm for middle regions, which may cause flooding activities in the lower and middle region of WFRB-2.

The West Flowing River Basins from Tadri to Kanyakumari (WFRB-2), India, is a highly complex hydrological system witnessing hydrological extremes frequently. In this study, the impacts of climate/Land Use Land Cover (LULC) changes on hydrology in WFRB-2 are investigated on a 0.25° spatial scale for a historic (1979–2018) time period. Six major river basins are chosen in the upper, middle and lower regions of WFRB-2 and the variable infiltration capacity (VIC) model is calibrated using SCE-UA (Shuffle Complex Evolution) algorithm. The linear trend analysis showed a significant increase in premonsoon/monsoon rainfall in the lower region and a 13% increase in the percentage of very wet years, while dry years completely disappeared in the recent past. Sensitivity analysis shows that annual mean surface runoff (SR) increases by 125 mm and evapotranspiration (ET) decreases by 562 mm when a fully forested grid was transformed into a fully built-up grid. Similarly, sensitivity towards rainfall alone is showing an increase of SR and ET by 54 mm (6%) and 64 mm (6%) respectively. Overall impact results in a reduction in the annual mean total runoff by 48 mm in the upper and 100 mm in the middle and a rise of 53 mm in the lower regions. This shows that in the lower region, with an increase in precipitation coupled with increasing urbanization, there is a possibility of greater magnitude flood peaks. This study is useful to understand the complex hydrological impacts due to climate/LULC changes for management decisions on a regional scale.

An understanding of natural degradation of multiple reactive contaminants in the aquifers is essential before designing the monitoring or remediation programs for polluted aquifers. Since such reactive contaminants are ubiquitous, a number of research works has been performed in the past three decades for the modelling of multi-species reactive transport (MSRT) phenomenon. The widely used finite difference method (FDM) and finite element method (FEM)–based models suffer a drawback of relying on a grid/mesh, which makes the solution unstable. Addressing such difficulties, the latest research on the MSRT models is directed towards the meshless methods. In this study, the meshless local Petrov Galerkin (MLPG) method–based multi-species reactive transport model (MLPG-MSRT) is presented, with an objective to create a robust simulation tool for the prediction of fate of multiple contaminants of the first-order reaction network. The developed model is validated for reversible as well as irreversible reaction networks with the available analytical solutions. Also, the MLPG model for unconfined aquifer flow (UF) is developed, validated, and coupled with the MLPG-MSRT model. The MLPG-UF-MSRT model results are further compared with the established FDM-based MODFLOW-RT3D model solutions for a rectangular and a real field type study. The results showed that the proposed model can simulate MSRT as accurately as the FDM-based models with an additional advantage of simplicity and stability, and thus, is more efficient for complex field problems.

Land use–land cover (LULC) change in space and time is the main cause behind the changing hydrological processes, ecosystem and environment in urban catchments. In the present study, the main focus was on evaluation of spatial and temporal variation of land use and land cover change in a major coastal urban catchment of Mumbai City, India, called Mithi River catchment. The LULC is derived from the topographic map surveyed in the year 1966 and satellite image for the year 2009. The analysis from toposheet and remote sensing data showed that there is a rise in the built-up area of Mithi River catchment, Mumbai by 59.66 % between 1966 and 2009. It also showed adverse human-induced influences on the Mithi River course and its catchment. Flood hydrographs for different land use conditions were derived by using Soil Conservation Service-Curve Number hydrological model and kinematic wave model, for routing available within the HEC-HMS software. Flood plain maps as well as flood hazard maps for the different land use scenarios have been developed by integrating the models HEC-HMS and HEC-RAS with HEC-GeoHMS and HEC-GeoRAS as well as with GIS and remote sensing. Results obtained from the present study revealed marginal increases in the runoff peak discharges and volumes within the catchment. Even though the runoff change is marginal, combined with tidal influence, it may cause major flooding problem. The integrated modeling approach has been found to be very effective for flood estimation, flood plain and flood hazard mapping. The flood plain and flood hazard maps derived can be used as effective tool to minimize the damages within the flood-prone areas of the river basin for the Mumbai City.

It is widely known that land use/land cover (LULC) changes significantly alter watershed hydrology and sediment yields. The impact, especially on erosion and sedimentation, is likely to be exacerbated in regions dominated by high rainfall patterns such as monsoons. This study analyzed the hydrological responses of LULC changes in terms of streamflow (SF) and sediment yield (SY) in a monsoon-dominated tropical watershed, the Periyar River Watershed (PRW) in Kerala, India. This watershed drains an area of 4793 km2 characterized by an average monsoon rainfall of 2900 mm from June to November. The watershed hydrology and sediment dynamics were simulated using the Soil and Water Assessment Tool (SWAT) model for the impact assessment at the watershed outlet and the sub-watershed level. Historical LULC data were analyzed for 1988, 1992, 2002, and 2016 using the maximum likelihood method, and future LULC changes were projected for 2030, 2050, 2075, and 2100 using the Markov chain–cellular automata technique. Between 1988 and 2016, the urban area increased by 4.13 percent, while plantation and forest coverage decreased by 1.5 percent. At this rate, by 2100, the urban area is expected to grow by 16.45% while plantations and forest area will shrink by 13.7% compared to 1988. The effects of these changes on SF and SY were found to be minimal at the watershed outlet; however, at the spatial scale of sub-watersheds, the changes varied up to 70% for surface runoff and 200% for SY. These findings highlight the potential impacts of LULC changes in a monsoon-dominated watershed and may contribute to the development of successful LULC-based watershed management strategies for prevention of flooding and sediment loss.

Sustainability in hydrology aims at maintaining a high likelihood of meeting future water demands without compromising hydrologic, environmental, or physical integrity. Therefore, understanding the local-scale impact of global climate change on hydrology and water balance is crucial. This study focuses on assessing the impact of climate change on water balance components (precipitation, surface runoff, groundwater flow, percolation, etc.) at the river basin scale in a humid tropical region. The Periyar river basin (PRB) in Kerala in India is considered as a case study and the SWAT hydrological model is adopted to obtain the water balance components. Three general circulation models are considered under two shared socioeconomic pathways (SSP 245 and SSP 585) emission scenarios assess the impact of climate change until 2100. For the PRB, the results demonstrate a significant increase in streamflow (>65%) and runoff (>40%) in the mid (2041–2070) and far (2071–2100) future under both the SSP scenarios, indicating a potential vulnerability to future floods. Conversely, in the near future under SSP 585, a decrease in runoff (−15%) and nominal changes in streamflow (−5%) are observed. Spatially, the eastern sub-basins and the west coast of the Periyar river basin are projected to experience higher precipitation events, while the central region faces reduced precipitation and low flow rates. The findings emphasize the need for proactive and sustainable management of water resources, considering irrigation requirements, groundwater discharge, and flood control measures, to mitigate the negative effects of climate change and prevent water stress/surplus situations in specific sub-basins. This study enhances our understanding of climate change impacts on water balance and emphasizes the significance of sustainable water resource management for an effective response. By integrating scientific knowledge into policy and management decisions, we can strive towards a resilient water future within a changing climate.

This study proposed a novel combination of a meshfree simulator with the covariance matrix adaptation evolution strategy (Mfree-CMA-ES) to construct a simulation-optimization (SO) model for accurate estimation of aquifer parameters. In most regional aquifer systems, minimal temporal fluctuations are observed throughout the year. Therefore, the widely used approaches of least squares error minimization with metaheuristics (MH) optimization, such as differential evolution (DE), particle swarm optimization (PSO), and their hybrid versions, are often prone to premature convergence and lead to incorrect estimations of aquifer parameters. In the proposed model, the Mfree simulator was used, which produces accurate values of groundwater head, particularly when compared to the popularly used grid or mesh-based finite difference method (FDM) or finite element method (FEM). Furthermore, CMA-ES, with its auto-updated-strategy parameters, provided a competitive resultant population in each generation, leading to fast convergence and excellent matches with observed head data. The developed SO model was applied to both a synthetic regional aquifer and a real field case, i.e., the Mahi Right Bank Canal aquifer in India. Results showed that Mfree-CMA-ES requires less computational time and has a greater accuracy of estimated parameter values in comparison to various other models, i.e., FEM-DE, Mfree-DE, FEM-PSO, Mfree-PSO, FEM-DE-PSO, Mfree-DE-PSO, and FEM-CMA-ES. A sensitivity analysis showed the relative composite scaled sensitivity (RCSS) values of all the hydraulic conductivity zones that are within the range of 1–0.1. These obtained RCSS values validated the ability of the proposed model to estimate zonal hydraulic conductivity values using the Mfree-CMA-ES model.