Depletion Of Groundwater Level Research Articles

Exploring groundwater depletion and land subsidence dynamics in Taiwan’s Choushui river alluvial fan: insights from integrated GNSS and hydrogeological data analysis

The Choushui River Alluvial Fan (CRAF) is a major agricultural area in Taiwan with heavy groundwater usage. The extraction of groundwater here has caused land subsidence, which is now a significant global environmental issue. This study analyzes land subsidence in the CRAF by integrating hydrogeological data from 233 groundwater monitoring stations across four aquifers (CRAF Groundwater_NET) and data from 50 continuous GNSS stations (CRAF GNSS_NET). We developed an automated processing flow for GNSS static surveying within CRAF GNSS_NET, and further employed a time-series fitting method to examine the long-term trends and annual changes for both GNSS and groundwater level data. Our analysis of the time-series data from the past decade identifies areas of significant groundwater level depletion and subsidence hotspots. We explore the relationship between groundwater level variations and surface displacements within CRAF, utilizing GNSS data to analyze horizontal and vertical displacement trends, as well as annual changes. We integrate these findings with hydrogeological data to understand regional subsidence patterns. Our results indicate that CRAF is characterized by distinct hydrogeological features. The study finds that the amplitudes of annual changes in both groundwater level and vertical displacement generally increase from northeast to southwest in the analyzed region. One particular area shows significant groundwater level decline, with the most severe rate recorded at 0.54 m/year. Similarly, GNSS analysis indicates pronounced subsidence trends in the same area, with rates ranging from 4.2 to 5.2 cm/year. These findings highlight the critical need for the development of effective groundwater management strategies to ensure sustainable use of groundwater resources and to implement mitigation measures against land subsidence in similar multiple-aquifer settings.

Quantitative and qualitative assessment of groundwater resources for drinking water supply in the peri-urban area of Dhaka, Bangladesh

Groundwater is the primary source of freshwater for drinking, industrial, and agricultural water in many nations worldwide. This vital resource is deteriorating due to rapidly growing urbanization, pollution, overexploitation, and climate change. However, it is unclear how much this specific resource deteriorates over time. Therefore, this study aimed to investigate groundwater resources qualitatively and quantitatively in the peri-urban area of Dhaka, Bangladesh. The study used the modified Mann-Kendall trend test, hotspot analysis, groundwater recharge estimation, multivariate statistical analysis, and the water quality index (WQI) mapping. The trend analysis of groundwater levels indicates that in the most recent year, groundwater levels close to industrial areas have declined at a maximum rate of 1.18 m/year. The estimated groundwater recharge reveals that it is highest (480 mm/year) on rural agricultural land and lowest (220 mm/year) in urban areas. With a 99% confidence level, the groundwater water trend cluster analysis indicates the hotspots of groundwater level depletion near the industrial area. The results showed that Mn, Fe, and As exceeded the World Health Organization's (WHO) recommended limit for drinking water by 76.92%, 61.53%, and 23.07%, respectively. The principal component analysis and hierarchical clustering results indicate that groundwater quality is influenced by rock-water interaction and human interventions. The WQI results suggest that 47.05% of the samples were excellent, 7.69% were good, 9.96% were poor, 17.65% were very poor, and the remaining 17.65% were unfit for drinking purposes. The depletion of groundwater hotspots was identified in northeast region of the study area. Overall, an integrated framework was proposed that offers a holistic approach to sustainable groundwater resource management amid urbanization and industrialization. These findings will provide an essential guideline for groundwater resource management in the peri-urban area of Dhaka city.

Groundwater Abstraction has Caused Extensive Ecological Damage to the Doñana World Heritage Site, Spain

Acreman et al. (Wetlands 42:63, 2022) reviewed evidence for ecological damage to the Doñana wetlands (UNESCO World Heritage Site [WHS] and Ramsar site), Spain, associated with intensification of groundwater use, particularly for agriculture. Acreman et al. presented a multistep methodology for evidence-based risk assessment that involves identification of conservation issues, and a systematic review of scientific evidence for ecological damage and its causes. However, they involved few local scientists, used a questionable methodology in stakeholder selection and involvement, used a flawed conceptual framework, and an incomplete literature review. We propose improvements to their methodology. They overlooked or misinterpreted key evidence, and underestimated the impacts that abstraction for irrigation for red fruits (mainly strawberries), rice and other crops has had on Doñana and its biodiversity. They reported groundwater level depletion of up to 10 m in the deep aquifer, but wrongly concluded that there is no evidence for impacts on the natural marsh ecosystem, the dune ponds or the ecotone. Groundwater drawdowns are actually up to 20 m, and have inverted the formerly ascending vertical hydraulic gradient in discharge areas. Phreatic levels have been lowered from 0.5 to 2 m in some areas. Groundwater abstraction has caused multiple ecological impacts to temporary ponds and marshes in the WHS, as well as to terrestrial vegetation, and should be urgently reduced. Furthermore, Acreman et al. focused on groundwater quantity while overlooking the importance of severe impacts on quality of both surface and groundwater, intimately connected to the use of agrochemicals for irrigated crops.

Evaluating the Mechanical Performance of Waste Glass Powder as a Fine Aggregate Substitute to Enhance Sustainability in Concrete Production

The concrete industry poses a significant challenge to sustainability since it ranks among the foremost users of natural resources. The utilization of river sand as a fine aggregate result in the degradation of natural resources, depletion of groundwater levels, subsidence of bridge piers, and degradation of riverbeds. By substituting fine aggregate with waste glass in a specified proportion and gradation, the requirement for river sand may be reduced, therefore mitigating the adverse impacts of river dredging. This substitution has the potential to contribute to the sustainability of the concrete building sector. The main objective of this study is to examine the use of waste glass powder (WGP) in concrete and evaluate its influence on the strength characteristics and the overall cost of the concrete. The chemical composition of natural sand and WGP exhibits similarities, hence enabling the potential for partial substitution of sand with WGP in concrete. This project involves the use of WGP as a partial substitute for sand in the production of M20 grade concrete. Concrete specimens were casted using different percentages of glass powder as a replacement for sand, namely 0% (Control Mix), 10%, 20%, 30%, and 40%. These specimens were then subjected to testing to evaluate their compressive, split tensile, and flexural strengths. The test results obtained for concrete mixed with WGP are compared to those of regular concrete. The findings of the study revealed that WGP has the potential to serve as a viable substitute for fine aggregate in certain applications.

Road Drains, An Efficient Tool for Groundwater Recharge – A Remote Sensing and GIS-Based Study on Visakhapatnam, Andhra Pradesh, India

Abstract Depletion of groundwater levels has become a significant concern worldwide, particularly during dry seasons. The study proposes an innovative and effective method to increase recharge by proposing road drains with the help of geospatial technologies. The study recommends pervious concrete, which allows water to pass through it and recharge the groundwater table. Experiments are carried out with pervious concrete on four different soil types, and the results were analysed using Geographical Information System (GIS) to provide an effective solution for managing water resources in Visakhapatnam. The derived results provide valuable insights into the sustainable management of water resources and improve the overall water utilization efficiency of urban areas. The outcomes of this study drive attention towards the necessity of road drains for groundwater recharge. GIS analysis of the results suggests that in Visakhapatnam alone, a total length of 1,559.94 km of road drains along residential, primary and highway roads can be planned to recharge and conserve a total volume of 3,79,08,762.3 m3/hrs. of groundwater by using the pervious concrete as road drains.

Investigating groundwater recharge using hydrogen and oxygen stable isotopes in Kabul city, a semi-arid region

There are significant concerns about the sustainability of groundwater, and the inhabitants that depend on it, due to rapid groundwater depletion from the alluvium aquifers in Kabul city. Sustainable groundwater management in Kabul requires an understanding of the sources and rates of groundwater recharge, however, both these parameters are poorly quantified. In this study, we examined the stable isotopic composition (δ18O and δ2H) of groundwater and surface water from the Upper Kabul River and Logar River. Utilizing the hydrograph separation approach, we assessed the percentage contribution of river water to groundwater, including the uncertainty analysis of its estimation. Our results, based on isotopic analysis, demonstrated that precipitation was the primary source of groundwater recharge in the Central Kabul sub-basin. Mixed recharge from the river, precipitation and irrigation return flow governed groundwater recharge in the Logar sub-basin. In Paghman and Lower Kabul, and Upper Kabul sub-basins, more rainfall input was observed besides the river contribution to groundwater recharge. We have noted substantial spatial and depth-related variation in the contribution of the river water to groundwater recharge. In the study area, the river water contribution (fraction contribution) to groundwater recharge has changed from over 60 ± 5 % (on average) in 2007 to less than 50 ± 5 % (on average) in 2020. We documented significant groundwater level depletion in the Central Kabul sub-basin and western parts of Kabul city (Paghman and Upper Kabul sub-basins). The present study provides important insights into the local water cycle in Kabul City, which is critical for developing sustainable management strategies for groundwater sources in this semi-arid region.

Influence assessment of urban expansion on groundwater level fluctuations in Gandhinagar, Gujarat, India.

Being the state capital of Gujarat, Gandhinagar is snowballing urban population, resulting in overexploitation of groundwater resources and consequent decline in local groundwater level. The key objective of the current research is to understand the impact of urban expansion on the groundwater level of Gandhinagar district for the last 3 decades. Long-term land use/land cover (LULC) alterations using Landsat images (1991-2021) reveal a 234% increase in overall built-up area and it is more prominent in western and southern parts than the eastern part of study area till 2021 due to urban sprawl of adjacent Ahmedabad City. Spatial distribution of groundwater levels exhibits the same pattern of groundwater level drop as that of the urban expansion and the drop of maximum depth of the groundwater level has also observed during study tenure. Rapid population growth indicates inevitable urban densification which may lead to increase in groundwater abstraction and consequent groundwater level depletion of Gandhinagar City in near future. The scenario may be worsened due to the reduction in groundwater recharge area owing to enhancement of impervious surfaces. A negative correlation is established between groundwater level and respective built-up areas from 1991 to 2011. After 2001, groundwater levels in some areas showed a rising trend and the number of those locations have increased from 2001 to 2021, indicating a sufficient supply of surface water, meeting the escalating water demand and subsequent reduction in groundwater abstraction. High fluoride content was found in many groundwater samples collected from Gandhinagar's shallow unconfined aquifer. In lieu of almost unperturbed natural groundwater recharge, built-up expansion, rising population, and over-exploitation result in groundwater level depletion in both shallow and deeper aquifers. To replenish the already depleted groundwater level and for sustainable water supply, an integration of rainwater-surface water-groundwater management plan and sustainable urban management plan is highly required. The future sustainable urban-groundwater management plan of Gandhinagar City must emphasized on the expansion of green and permeable spaces for groundwater recharge, mandatory rainwater harvesting system in every building possible, suitable area demarcation for artificial recharge, and identification of areas which are less prone to groundwater level depletion for city expansion. The outcomes of the present study will help the decision-makers to prepare inclusive and resilient urban management plan to accomplish the 6th and 11th Sustainable Development Goals of United Nations by 2030.

Groundwater Level Depletion Assessment of Dhaka City Using MODFLOW

Groundwater Level Depletion Assessment of Dhaka City Using MODFLOW

Predicting Groundwater Levels in Ogallala Aquifer Wells Using Hierarchical Cluster Analysis and Artificial Neural Networks

The Ogallala Aquifer, located in the Central Plains of the United States, is essential for agricultural irrigation and public water supply. Indiscriminate pumping from the aquifer has caused several negative impacts, such as deterioration of water quality and depletion of groundwater levels, which urgently demand better management. This paper applies hierarchical cluster analysis (HCA) and artificial neural networks (ANNs) for predicting annual groundwater levels in 403 wells of the Ogallala Aquifer. First, the methodology employed HCA to cluster homogeneous wells based on the time series of groundwater levels. Then, the study calibrated an ANN model for each cluster (composed of one or more wells) using previous annual values of groundwater levels as input. The HCA results showed a particular pattern in the spatial distribution of the 30 found clusters, revealing that the Ogallala Aquifer holds higher groundwater levels in the western part, which gradually decrease, advancing to the east. The ANN models provided proper predictions even for wells outside of the calibration data set. This investigation concludes that the integration of HCA and ANN enabled single models to accurately forecast annual groundwater levels for sets of wells in the Ogallala Aquifer.

Forecasting the human and climate impacts on groundwater resources in the irrigated agricultural region of North China Plain

AbstractClimate change has caused significant impacts on water resource redistribution around the world and posed a great threat in the last several decades due to intensive human activities. The impacts of human water use and management on regional water resources remain unclear as they are intertwined with the impacts of climate change. In this study, we disentangled the impact of climate‐induced human activities on groundwater resources in a typical region of the semi‐arid North China Plain based on a process‐oriented groundwater modelling approach accounting for climate‐human‐groundwater interactions. We found that the climate‐induced human effect is amplified in water resources management (‘amplifying effect’) for our study region under future climate scenarios. We specifically derived a tipping point for annual precipitation of 350 mm, below which the climate‐induced human activities on groundwater withdrawal will cause significant ‘amplifying effect’ on groundwater depletion. Furthermore, we explored the different pumping scenarios under various climate conditions and investigated the pumping thresholds, which the pumping amount should not exceed (4 × 107 m3) in order to control future groundwater level depletion. Our results highlight that it is critical to implement adaptive water use practices, such as water‐saving irrigation technologies in the semi‐arid regions, in order to mitigate the negative impacts of groundwater overexploitation, particularly when annual precipitation is anomalously low.

Achieving sustainability through improvement in the textile wet process using particle swarm optimization and the tabu search algorithm

As far as cloth production is concerned, the dyeing process in textiles forms a bottleneck procedure, as this process consumes a great deal of time and high volumes of water per unit of fabric for processing, which causes depletion of groundwater levels at a high rate. Besides, textile effluents are discharged into rivers or wetlands without proper treatment in many cases. Untreated textile effluent can contaminate groundwater and water bodies, reduce dissolved oxygen in the water, and affect aquatic ecosystems, which may indirectly cause climate change. The waste generated in dyeing is mainly due to the cleaning process. Thus, the dyeing process needs to be improved and optimized to solve the problem and reduce delay. To take effective measures for future improvement, it is essential to develop a nature-inspired tracking system. The amount of emission and the performance can be improved by utilizing scheduling as a tool. In this view, the dyeing process is formulated as a bi-objective optimization model to reduce the tardiness cost and minimize the emission of wastewater during the cleaning process of the dyeing vat. The current problem is of a difficult nature; thus, multi-objective particle swarm optimization in collaboration with the tabu search algorithm has been used to attain good and nondominant results. The tabu search algorithm is used along with ejection chains to focus on the objectives of emission reduction and increase the number of desired solutions. It was found that the total processing time was reduced by 4–5 hours and water was reduced by 500 liters for dyeing 200 kg of yarn daily.

An Assessment of Energy and Groundwater Consumption of Textile Dyeing Mills in Bangladesh and Minimization of Environmental Impacts via Long-Term Key Performance Indicators (KPI) Baseline

Bangladesh’s ready-made garment sectors have evolved to increase market share in the global textile supply chain. Textile sectors heavily rely on energy and groundwater consumption during production; mainly, textile dyeing mills contribute to the carbon footprint and water footprint impact to the environment. Textile dyeing mills have become one of the major industries responsible for the continuous depletion of groundwater levels and severe water pollution to the environment. Reduction of long-term key performance indicators (KPI) can be set to a baseline by reducing energy and groundwater consumption in textile dyeing mills. This study has analyzed the energy and groundwater consumption trend based on 15 textile dyeing mills in Bangladesh in 2019. The average dyed fabric production of 15 textile dyeing mills in 2019 was 7602.88 tons by consuming electricity and groundwater, and discharging treated effluent wastewater to the environment, in the amounts of 17,689.43 MWh, 961.26 million liters, and 640.24 million liters, respectively. The average KPI of treated effluent discharged wastewater was 97.27 L/kg, and energy consumption was 2.58 kWh/kg. Considering yearly 5% reduction strategies of groundwater and energy consumption for each factory could save around 355.43 million liters of water and 6540.68 MWh of electricity in 10 years (equivalent to 4167.08-ton CO2 emission).

Prediction of future groundwater levels under representative concentration pathway scenarios using an inclusive multiple model coupled with artificial neural networks

Abstract Groundwater (GW) plays a key role in water supply in basins. As global warming and climate change affect groundwater level (GWL), it is important to predict it for planning and managing water resources. This study investigates the GWL of the Yazd-Ardakan Plain basin in Iran for the base period of 1979–2005 and predicts for periods of 2020–2059 and 2060–2099. Lagged temperature and rainfall are used as inputs to hybrid and standalone artificial neural network (ANN) models. In this study, the rat swarm algorithm (RSA), particle swarm optimisation (PSO), salp swarm algorithm (SSA), and genetic algorithm (GA) are used to adjust ANN models. The outcomes of these models are then entered into an inclusive multiple model (IMM) as an ensemble model. In this study, the output of climate models is also inserted into the IMM model to improve the estimation accuracy of temperature, rainfall, and GWL. The monthly average temperature for the base period is 12.9 °C, while average temperatures for 2020–2059 under RCP 4.5 and RCP 8.5 scenarios are 14.5 and 15.1 °C, and for 2060–2099 they are 16.41 and 18.5 °C under the same scenarios, respectively. In future periods, rainfall is low in comparison with the base period. Lagged rainfall and temperature of the base period are inserted into ANN-RSA, ANN-SSA, ANN-PSO, ANN-GA, and ANN models to predict GWL for the base period. Outputs of IMM, ANN, and the five hybrid models (ANN-RSA, ANN-SSA, ANN-PSO, and ANN-GA) indicate that root mean square errors (RMSE) are 2.12, 3.2, 4.58, 6.12, 6.98, and 7.89 m, respectively, in the testing level. It is found that GWL depletion in 2020–2059 under RCP 4.5 and RCP 8.5 scenarios are 0.60–0.88 m and 0.80–1.16 m, and in 2060–2099 under the same scenarios they are 1.49–1.97 m and 1.75–1.98 m, respectively. The results highlight the need to prevent overexploitation of GW in the Ardakan-Yazd Plain to avoid water shortages in the future.

Low Cost Smart Ground System for Rainwater Harvesting for Indian Houses using IoT Technology

Water conservation is critical because it is one of the most significant factors for all species' survival. According to the Central Ground Water Board's estimates, underground water will be scarce in 15 Indian states by 2025 (Firstpost. Two-third of the world, much of India to face water scarcity, stress by 2025: Expert, 2018). However, as per the report from Ministry of Environment and Forest, only 10 to 20% rainwater is harvested. In urban areas, it is seen that nowadays concrete structures are constructed everywhere, so it is not possible to recharge the water table by natural process of raining. All the rainwater which is one of the sources for fresh water goes to drain. This causes the depletion of groundwater level which may be fatal in the future. Therefore, a rainwater harvesting system is required in Indian household to conserve water. On the other hand, the urban cities are having high pollutant levels which in turn affecting the quality of water. The government has defined certain parameters for quality checking of water. With the aid of the suitable sensors and IoT boards, quality checking, monitoring and water segregation can be easily achieved. In this work, an efficient and cost effective technique of rainwater harvesting has been presented. Some real case studies have been done at Indian houses in order to validate the effectiveness of system in terms of its implementation and cost analysis. As a result, the proposed system becomes one of the smart solutions to address the modern problem of rainwater harvesting with water quality management in low cost.

Analysing Effects on Ground Water Levels Due to Conversion of Rural to Urban Landscapes

Abstract Greater NOIDA evolved from 1991 with 101 villages to 2020 with 293 villages. This is an ideal case of rural to urban transformation in the immediate past. This transformation led to a decrease in recharging natural surfaces and an increase in impermeable surfaces. Along with the reduction in recharge areas, an increase in population has necessitated more and more extraction of groundwater resulting in an imbalance of water extraction and recharge. The result is depletion of groundwater levels in this area. The area is part of the wide Indo-Gangetic alluvium with sand, silt and clay layers resting on quartzite’s of Delhi Super Group. Geomorphological map prepared using digital elevation models of the area shows older and younger alluvial plains and active flood plains of the river Hindan. Time series analysis of key land use land cover classes shows that recharge areas were reduced from 77 % to 30 % from 2005 to 2019 and impervious surfaces have increased from 19 % to 65 % for the same period. Aquifers of the area are both phreatic and semi-confined. The aquifer parameters estimated through step drawdown test and long duration aquifer performance test indicates that the average coefficient of transmissivity of the area is 1752 m2/day and the average coefficient of storage is 4.84 x 10-4. Discharge of the wells shows a yield of 8 to 16 lps for a drawdown of 3 to 6 m. An attempt has been made to know the behaviour of groundwater levels during the same period as that of land use land cover. The results indicate a 74 % depletion in groundwater levels with an average annual depletion of 21 %. An interrelationship between urban growth and groundwater levels has been established in this study. This analysis indicates that as agriculture declined water levels also depleted and have a positive correlation of 0.852. On the contrary, as the built-up increased water level has depleted hence have a negative relationship with a correlation coefficient of -0.851. To make it a sustainable resource, these overexploited aquifers need careful participatory management by communities, Scientists, and policymakers.

Sustainability of Boro rice cultivation in the canal irrigated command area of India

Abstract A comprehensive assessment and monitoring of rice intensification in canal irrigated command areas and its consequences on groundwater dynamics have enormous importance for the water–food–energy nexus. This study analyzed the spatiotemporal transition of Boro rice cultivation, canal irrigation practices during the cultivation season, and its effect on groundwater of a pioneering multipurpose water resource project in India. The rice maps from 1989 to 2018 were generated from Landsat and Sentinel-2A images using the Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA), the normalized difference vegetation index (NDVI), and the enhanced vegetation index (EVI) to understand the historical distribution of rice cultivation. The ISODATA clustering algorithm performed well compared to the NDVI and the EVI with medium-resolution satellite images. The impact of Boro rice cultivation on groundwater resources was investigated by considering GLDAS NOAH model-based crop evapotranspiration, rainfall, and canal water supply. The area under rice cultivation increased from 33 to 66% during 1989–2018 due to its higher stress tolerance ability and productivity. However, during the cultivation period, the canal water supply was limited to the upstream and middle section of the command area, irrigating only 19% of the rice-cultivated area on average. The unavailability of the canal water supply during the cultivation season has led to 31 m of groundwater level depletion, which, if unchecked, may lead to overexploitation of groundwater in the middle and lower sections of the command area. The results of this study can be used to identify vulnerable areas that require urgent attention and accurate implementation of any agricultural or hydrological policy.

The impact of irrigation return flow on seasonal groundwater recharge in northwestern Bangladesh

Irrigation is vital in Bangladesh in order to meet the growing food demand as a result of the increasing population. During the dry season, groundwater irrigation is the main source of water for agriculture. However, excessive abstraction of groundwater for irrigation causes groundwater level depletion. At the same time, the loss from excessive irrigation could end up contributing to aquifer recharge as return flow. Therefore, investigating the influence of irrigation on groundwater is important for the sustainable management of this resource. This study aims to assess the impact of irrigation on groundwater recharge in the northwest Rajshahi district in Bangladesh. A semi-physically based water balance model was used to simulate spatially distributed groundwater recharge with two scenarios (with and without irrigation). To evaluate the effect of irrigation, groundwater recharges from these two scenarios were compared. The result showed that the use of groundwater for irrigation increased over the study period whereas, there was a persistent trend of decrease in groundwater level during the study period. Groundwater provides 91% of overall irrigation in the study area. However, on average, about 33% of the total irrigation becomes return flow and contributes to groundwater recharge in the dry season. Irrigation return flow is around 98% of the total recharge during the dry season in this region. The spatially distributed seasonal return flow varies from 305 to 401 mm. In brief, irrigation has a significant role in groundwater recharge in the study area during the dry season. Hence, proper irrigation water measurement and management are necessary for sustainable groundwater resource management in this region.

Assessment of Groundwater Flow Dynamics Using MODFLOW in Shallow Aquifer System of Mahanadi Delta (East Coast), India

Despite being a biodiversity hotspot, the Mahanadi delta is facing groundwater salinization as one of the main environmental threats in the recent past. Hence, this study attempts to understand the dynamics of groundwater and its sustainable management options through numerical simulation in the Jagatsinghpur deltaic region. The result shows that groundwater in the study area is extensively abstracted for agricultural activities, which also causes the depletion of groundwater levels. The hydraulic head value varies from 0.7 to 15 m above mean sea level (MSL) with an average head of 6 m in this low-lying coastal region. The horizontal hydraulic conductivity and the specific yield values in the area are found to vary from 40 to 45 m/day and 0.05 to 0.07, respectively. The study area has been calibrated for two years (2004–2005) by using these parameters, followed by the validation of four years (2006–2009). The calibrated numerical model is used to evaluate the net recharge and groundwater balance in this study area. The interaction between the river and coastal unconfined aquifer system responds differently in different seasons. The net groundwater recharge to the coastal aquifer has been estimated and varies from 247.89 to 262.63 million cubic meters (MCM) in the year 2006–2007. The model further indicates a net outflow of 8.92–9.64 MCM of groundwater into the Bay of Bengal. Further, the outflow to the sea is preventing the seawater ingress into the shallow coastal aquifer system.

Aquifer Storage and Recovery Feasibility Study With Flowing Fluid Electrical Conductivity Logging in Shallow Aquifers of South Bihar, India

Growing dependence on groundwater to fulfill the water demands has led to continuous depletion of groundwater levels and, consequently, poses the maintenance of optimum groundwater and management challenge. The region of South Bihar faces regular drought and flood situations, and due to the excessive pumping, the groundwater resources are declining. Rainwater harvesting has been recommended for the region; however, there are no hydrogeological studies concerning groundwater recharge. Aquifer storage and recovery (ASR) is a managed aquifer recharge technique to store excess water in the aquifer through borewells to meet the high-water demand in the dry season. Therefore, this paper presents the hydrogeological feasibility for possible ASR installations in shallow aquifers of South Bihar with the help of flowing fluid electrical conductivity (FFEC) logging. For modeling, the well logging data of two shallow borewells (16- and 47-m depth) at Rajgir, Nalanda, were used to obtain the transmissivity and thickness of the aquifers. The estimated transmissivities were 804 m2/day with an aquifer thickness of 5 m (in between 11 and 16 m) at Ajatshatru Residential Hall (ARH) well. They were 353 and 1,154 m2/day with the aquifer thicknesses of 6 m (in between 16 and 22 m) and 2 m (in between 45 and 47 m), respectively, at Nalanda University Campus (NUC) well. Despite the acceptable transmissivities at these sites, those aquifers may not be fruitful for the medium- to large-scale (more than 100-m3/day injection rate) ASR as the thickness of the aquifers is relatively small and may not efficiently store and withdraw a large amount of water. However, these aquifers can be adequate for small (up to 20-m3/day injection rate) ASR, for example, groundwater recharge using rooftop water. For medium- to large-scale ASR, deeper aquifers need to be further explored on these sites or aquifers with similar characteristics.

Assessment of groundwater drought vulnerability and delineation of sites for artificial recharge – a case study

Drought impacts both surface water and groundwater, which leads to reduced supply. Groundwater drought indicates continuous depletion of groundwater level, storage and discharge. Assessment of groundwater drought conditions is necessary for effective planning of drought management strategies. In this study, the drought vulnerability of Chittur Block in Palakkad, Kerala is assessed by the occurrence of groundwater drought and is mapped using geographic information system (GIS). A strategy for the effective implementation of artificial recharge schemes is proposed to combat future drought conditions. A combination of GIS and weighted parameter approach (WPA) is employed to delineate safe, suitable locations for artificial groundwater recharge. Site specific recharging structures such as check dams, infiltration pits, injection wells and percolation ponds are recommended within the 65% area which was identified as most conducive for artificial recharge.