Appraisal of the groundwater balance components from multi-remote sensing datasets in a semi-arid region

Semi-arid regions across the globe are fronting water crises, signaling a challenge to ensure future water security. Given the high inter-seasonal rainfall variability and unrestrained groundwater extraction, the precise quantification of groundwater flow components in an aquifer system is a priority. To address this challenge, we used high-resolution remote sensing (RS) data (Landsat and IRS) and GIS modeling (SEBAL, ArcCN) to spatially quantify major groundwater balance (GWB) components, viz., evapotranspiration (ET), rainfall recharge (R), surface runoff (Q), groundwater extraction (PG), irrigation return flow (IRF), and ultimately changes in groundwater storage (ΔS) in a small semi-arid crystalline representative watershed. Results show that a total of ~?230 mm of groundwater is extracted during 2008–2009, creating a negative impact on the groundwater resource, which is further enhanced by limited recharge and high ET. A decrease of approximately 65 mm in groundwater storage is observed in a single hydrological year, and given a very low specific yield, this decrease will introduce large water level decline. The study establishes that declining groundwater level in the watershed is a direct result of over-extraction, and owing to this scenario, efficient irrigation and land use policies are suggested as potential approaches to minimize extraction specifically in the dry season. Our methodology provides a systematic assessment of vital GWB components at a high spatial resolution and an insight on various sustainable mitigation methods. This methodology is useful in the planning and management of groundwater resources, particularly in water-stressed areas.     

Spatial variability of depth and salinity of groundwater under irrigated ustifluvents in the Middle Black Sea Region of Turkey

Information on the potential risk for soil salinity buildup can be very helpful for soil salinity management in irrigated areas. We evaluated the spatial and temporal variability of groundwater salinity (GWS) and groundwater depth (GWD), which are two of the most important indicators of soil salinity, by indicator kriging technique in a large irrigated area in northern Turkey. GWS and GWD were measured on a monthly basis from irrigation season (August 2003) to rainy season (April 2004) at 60 observation wells in the 8,187-ha irrigated area. Five indicator thresholds were used for GWS and GWD. The semivariogram for each of the thresholds for both variables was analyzed then used together with experimental data to interpolate and map the corresponding conditional cumulative distribution functions (CCDF). Risk for soil salinity buildup was greater in the irrigation season compared to that in the rainy season. The greatest risk for soil salinity buildup occurred in the eastern part of the study area, suffering from poor drainage problem due to malfunctioning drainage infrastructure, as indicated by the CCDF of GWS and GWD obtained in both seasons. It was concluded that a combination of mechanical and cultural measures should be taken in high-risk locations to avoid further salinity problems.     

Composite use of numerical groundwater flow modeling and geoinformatics techniques for monitoring Indus Basin aquifer, Pakistan

The integration of the Geographic Information System (GIS) with groundwater modeling and satellite remote sensing capabilities has provided an efficient way of analyzing and monitoring groundwater behavior and its associated land conditions. A 3-dimensional finite element model (Feflow) has been used for regional groundwater flow modeling of Upper Chaj Doab in Indus Basin, Pakistan. The approach of using GIS techniques that partially fulfill the data requirements and define the parameters of existing hydrologic models was adopted. The numerical groundwater flow model is developed to configure the groundwater equipotential surface, hydraulic head gradient, and estimation of the groundwater budget of the aquifer. GIS is used for spatial database development, integration with a remote sensing, and numerical groundwater flow modeling capabilities. The thematic layers of soils, land use, hydrology, infrastructure, and climate were developed using GIS. The Arcview GIS software is used as additive tool to develop supportive data for numerical groundwater flow modeling and integration and presentation of image processing and modeling results. The groundwater flow model was calibrated to simulate future changes in piezometric heads from the period 2006 to 2020. Different scenarios were developed to study the impact of extreme climatic conditions (drought/flood) and variable groundwater abstraction on the regional groundwater system. The model results indicated a significant response in watertable due to external influential factors. The developed model provides an effective tool for evaluating better management options for monitoring future groundwater development in the study area.     

Mapping of groundwater potential zones across Ghana using remote sensing, geographic information systems, and spatial modeling

Groundwater development across much of sub-Saharan Africa is constrained by a lack of knowledge on the suitability of aquifers for borehole construction. The main objective of this study was to map groundwater potential at the country-scale for Ghana to identify locations for developing new supplies that could be used for a range of purposes. Groundwater potential zones were delineated using remote sensing and geographical information system (GIS) techniques drawing from a database that includes climate, geology, and satellite data. Subjective scores and weights were assigned to each of seven key spatial data layers and integrated to identify groundwater potential according to five categories ranging from very good to very poor derived from the total percentage score. From this analysis, areas of very good groundwater potential are estimated to cover 689,680 ha (2.9 % of the country), good potential 5,158,955 ha (21.6 %), moderate potential 10,898,140 ha (45.6 %), and poor/very poor potential 7,167,713 ha (30 %). The results were independently tested against borehole yield data (2,650 measurements) which conformed to the anticipated trend between groundwater potential and borehole yield. The satisfactory delineation of groundwater potential zones through spatial modeling suggests that groundwater development should first focus on areas of the highest potential. This study demonstrates the importance of remote sensing and GIS techniques in mapping groundwater potential at the country-scale and suggests that similar methods could be applied across other African countries and regions.     

Implications of depletion of groundwater levels in three layered aquifers and its management to optimize the supply demand in the urban settlement near Kahota Industrial Triangle area, Islamabad, Pakistan

This study deals with the implications of depletion of groundwater levels in three layered aquifers and its management to optimize the supply demand in the urban settlement near Kahota Industrial Triangle area, located adjacent to the Soan River, Islamabad Pakistan. Initially, a groundwater 3-D steady-state flow model has been developed, calibrated to the known observed heads of 24 water wells, verified, and confirmed that convergence has actually arrived and hydraulic heads are no more changing. Later, the transient simulation was carried out with the constant discharge rates of groundwater by means of pumping wells, storage factor, porosity, and observed drawdown matched with the simulated drawdown that appears to fall in close agreement with a difference of 0.25 m. As such, the developed groundwater model has facilitated to understand, evaluate, and to predict regional trends of groundwater flow regimes and their ultimate utilization at a maximum rate of 4.5 million gallons/day for the growing urban settlement. The calibrated and verified model was then used to simulate the depletion of groundwater level, annual water balance, discharge versus time drawdown, and a temporal behavior of the system over an extended period of pumping. The modeling results indicate that, due to the pumping, the direction of flow has changed: first from groundwater regimes to the Soan River and then it is entirely reversed from the Soan River to the groundwater regimes as the drawdown started to deepen.     

Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters

A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82–90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.     

Groundwater modeling of Saq Aquifer Buraydah Al Qassim for better water management strategies

Saudi Arabia is an arid country. It has limited water supplies. About 80?C90% of water supplies come from groundwater, which is depleting day by day. It needs appropriate management. This paper has investigated groundwater modeling of Saq Aquifer in Buraydah Al Qassim to estimate the impact of its excessive use on depletion of Saq Aquifer. MODFLOW model has been used in this study. Data regarding the aquifer parameters was measured by pumping tests. Groundwater levels and discharge of wells in the area for the year 2008 and previous record of year 1999 have been collected from Municipal Authority of Buraydah. Location of wells was determined by Garmin. The model has been run for different sets of pumping rates to recommend an optimal use of groundwater resources and get prolonged life of aquifer. Simulations have been made for a long future period of 27?years (2008?C2035). Model results concluded that pumping from the Saq Aquifer in Buraydah area will result into significant cones of depression if the existing excessive pumping rates prevail. A drawdown up to 28?m was encountered for model run for 27?years for existing rates of pumping. Aquifer withdrawals and drawdowns will be optimal with the conservation alternative. The management scheme has been recommended to be adopted for the future protection of groundwater resources in Kingdom of Saudi Arabia.     

Urban water resource management for sustainable environment planning using artificial intelligence techniques

In the current era, water is a significant resource for socio-economic growth and the protection of healthy environments. Properly controlled water resources are considered a vital part of development, which reduces poverty and equity. Conventional Water system Management maximizes the existing water flows available to satisfy all competing demands, including on-site water and groundwater. Therefore, Climatic change would intensify the specific challenges in water resource management by contributing to uncertainty. Sustainable water resources management is an essential process for ensuring the earth's life and the future. Nonlinear effects, stochastic dynamics, and hydraulic constraints are challenging in ecological planning for sustainable water development. In this paper, Adaptive Intelligent Dynamic Water Resource Planning (AIDWRP) has been proposed to sustain the urban areas' water environment. Here, an adaptive intelligent approach is a subset of the Artificial Intelligence (AI) technique in which environmental planning for sustainable water development has been modeled effectively. Artificial intelligence modeling improves water efficiency by transforming information into a leaner process, improving decision-making based on data-driven by combining numeric AI tools and human intellectual skills. In AIDWRP, Markov Decision Process (MDP) discusses the dynamic water resource management issue with annual use and released locational constraints that develop sensitivity-driven methods to optimize several efficient environmental planning and management policies. Consequently, there is a specific relief from the engagement of supply and demand for water resources, and substantial improvements in local economic efficiency have been simulated with numerical outcomes.     

Deciphering groundwater potential zones in hard rock terrain using geospatial technology

Remote sensing and geographical information system (GIS) has become one of the leading tools in the field of groundwater research, which helps in assessing, monitoring, and conserving groundwater resources. This paper mainly deals with the integrated approach of remote sensing and GIS to delineate groundwater potential zones in hard rock terrain. Digitized vector maps pertaining to chosen parameters, viz. geomorphology, geology, land use/land cover, lineament, relief, and drainage, were converted to raster data using 23 m × 23 m grid cell size. Moreover, curvature of the study area was also considered while manipulating the spatial data. The raster maps of these parameters were assigned to their respective theme weight and class weights. The individual theme weight was multiplied by its respective class weight and then all the raster thematic layers were aggregated in a linear combination equation in Arc Map GIS Raster Calculator module. Moreover, the weighted layers were statistically modeled to get the areal extent of groundwater prospects with respect to each thematic layer. The final result depicts the favorable prospective zones in the study area and can be helpful in better planning and management of groundwater resources especially in hard rock terrains.     

Performance of semipermeable membrane devices for sampling of organic contaminants in groundwater

Lipid-filled semipermeable membrane devices (SPMDs) are receiving increasing attention as passive, in situ samplers for the assessment of environmental pollutant exposure. Although SPMDs have been successfully used in a variety of field studies in surface waters, only a few studies have addressed their characteristics as groundwater samplers. In this study, the performance of the SPMDs for monitoring organic contaminants in groundwater was evaluated in a pilot field application in an area severely contaminated by chemical waste, especially by chlorinated hydrocarbons. The spatial distribution of hydrophobic groundwater contaminants was assessed using a combination of passive sampling with SPMDs and non-target semiquantitative GC-MS analysis. More than 100 contaminants were identified and semiquantitatively determined in SPMD samples. Along the 6 field sites under investigation, a large concentration gradient was observed, which confirms a very limited mobility of hydrophobic substances in dissolved form in the aquifer. The in situ extraction potential of the SPMD is limited by groundwater flow, when the exchange volume of well water during an exposure is lower than the SPMD clearance volume for the analytes. This study demonstrates that SPMDs present a useful tool for sampling and analyzing of groundwater polluted with complex mixtures of hydrophobic chemicals and provides guidance for further development of passive sampling technology for groundwater.     

Land cover change of watersheds in Southern Guam from 1973 to 2001

Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.     

Evaluation of groundwater quality in and around Peenya industrial area of Bangalore, South India using GIS techniques

Groundwater resource forms a significant component of the urban water supply. Declining groundwater levels in Bangalore Urban District is generally due to continuous overexploitation during the last two decades or more. There is a tremendous increase in demand in the city for good quality groundwater resource. The present study monitors the groundwater quality using geographic information system (GIS) techniques for a part of Bangalore metropolis. Thematic maps for the study area are prepared by visual interpretation of SOI toposheets on 1:50,000 scale using MapInfo software. Physicochemical analysis data of the groundwater samples collected at predetermined locations form the attribute database for the study, based on which spatial distribution maps of major water quality parameters are prepared using MapInfo GIS software. Water quality index was then calculated by considering the following water quality parameters--pH, total dissolved solids, total hardness, calcium hardness, magnesium hardness, alkalinity, chloride, nitrate and sulphate to find the suitability of water for drinking purpose. The water quality index for these samples ranged from 49 to 502. The high value of water quality index reveals that most of the study area is highly contaminated due to excessive concentration of one or more water quality parameters and that the groundwater needs pretreatment before consumption.     

广东省地下水环境监测井现状及管理对策

在广东省范围内开展了地下水环境监测井资料收集和现场排查,统计可用监测井3 620个,分析监测井的数量、分布、功能和监测情况。结果表明,尚存在环评井建设与监测任务落实不到位、地下水环境监测井管理体制不够健全、监测井信息化管理水平低、监测网络布局不完善等问题。结合地下水污染防治管理需求,针对性提出了完善监测井管理法规标准体系、加强地下水环境监测井建设与维护、推进监测井信息化建设与数据共享、完善地下水环境监测网络等对策。     

面向水源保护与污染监控的广东地下水环境监测网研究

通过系统整理分析自然资源、水利、生态环境等部门已有地下水监测网,针对广东地下水监测存在的问题和未来地下水环境管理需求,提出较大空间尺度和水质监控的地下水环境监测网建设框架及广东省"三层七级"共237个网点的层级化地下水环境监测网建设方案,并与水文地质单元、浅层地下水功能区划进行了空间叠加分析。结果表明,广东省三大部门监测网在空间上分布总体较为分散,相互补充性好,提出的监测网方案总体上与广东省地下水本底条件、地下水资源开发利用现状、地下水环境功能分区、重点污染源空间分布特征等相匹配,契合地下水饮用水源保护和重点污染源监控两大管理需求,构建的地下水环境监测网框架可为其他地区提供参考,提出的地下水环境监测网建设方案可为广东省地下水环境管理和污染防控提供决策支持。     

Time Series Analysis to Monitor and Assess Water Resources: A Moving Average Approach

An understanding of the behavior of the groundwater body and its long-term trends are essential for making any management decision in a given watershed. Geostatistical methods can effectively be used to derive the long-term trends of the groundwater body. Here an attempt has been made to find out the long-term trends of the water table fluctuations of a river basin through a time series approach. The method was found to be useful for demarcating the zones of discharge and of recharge of an aquifer. The recharge of the aquifer is attributed to the return flow from applied irrigation. In the study area, farmers mainly depend on borewells for water and water is pumped from the deep aquifer indiscriminately. The recharge of the shallow aquifer implies excessive pumping of the deep aquifer. Necessary steps have to be taken immediately at appropriate levels to control the irrational pumping of deep aquifer groundwater, which is needed as a future water source. The study emphasizes the use of geostatistics for the better management of water resources and sustainable development of the area.     

Geostatistical Analysis of Spatial and Temporal Variations of Groundwater Level

Groundwater and water resources management plays a key role in conserving the sustainable conditions in arid and semi-arid regions. Applying management tools which can reveal the critical and hot conditions seems necessary due to some limitations such as labor and funding. In this study, spatial and temporal analysis of monthly groundwater level fluctuations of 39 piezometric wells monitored during 12 years was carried out. Geostatistics which has been introduced as a management and decision tool by many researchers has been applied to reveal the spatial and temporal structure of groundwater level fluctuation. Results showed that a strong spatial and temporal structure existed for groundwater level fluctuations due to very low nugget effects. Spatial analysis showed a strong structure of groundwater level drop across the study area and temporal analysis showed that groundwater level fluctuations have temporal structure. On average, the range of variograms for spatial and temporal analysis was about 9.7 km and 7.2 months, respectively. Ordinary and universal kriging methods with cross-validation were applied to assess the accuracy of the chosen variograms in estimation of the groundwater level drop and groundwater level fluctuations for spatial and temporal scales, respectively. Results of ordinary and universal krigings revealed that groundwater level drop and groundwater level fluctuations were underestimated by 3% and 6% for spatial and temporal analysis, respectively, which are very low and acceptable errors and support the unbiasedness hypothesis of kriging. Although, our results demonstrated that spatial structure was a little bit stronger than temporal structure, however, estimation of groundwater level drop and groundwater level fluctuations could be performed with low uncertainty in both space and time scales. Moreover, the results showed that kriging is a beneficial and capable tool for detecting those critical regions where need more attentions for sustainable use of groundwater. Regions in which were detected as critical areas need to be much more managed for using the current water resources efficiently. Conducting water harvesting systems especially in critical and hot areas in order to recharge the groundwater, and altering the current cropping pattern to another one that need less water requirement and applying modern irrigation techniques are highly recommended; otherwise, it is most likely that in a few years no more crop would be cultivated.     

Predicting saltwater intrusion into aquifers in vicinity of deserts using spatio-temporal kriging

The primary objective of this study was to provide a detailed framework to use the spatio-temporal kriging to model the spatio-temporal variations of salinity data and predict saltwater intrusion into freshwater aquifers in the vicinity of deserts. EC data, measured in extraction wells in the Mahvelat plain located in the Northeastern part of Iran, available from 2007 to 2013, were used to demonstrate the developed framework. The source of data was not a well-designed measurement network. Therefore, to homogenize the data, spatial analysis was used to find EC distribution in the area in each year of study. To conduct the spatial analysis, a guideline and a systematic process were developed to select an appropriate kriging method and optimize its parameters. This process can be applied to different variables. After spatial analysis of EC data for all the years of the analysis period using empirical Bayesian kriging (EBK) method with manually optimized parameters, spatio-temporal and corresponding variogram analysis was conducted using R software. This process was based on a separable product-sum model applied to the data from 2007 to 2012. The data of 2013 and the data available for the years 1999 and 2006 were used for evaluating the performance of the spatio-temporal model. The EC distribution maps, developed for different years until 2021, show a high level of EC in the north, south, and west of the study area and growing saltwater intrusion into the central freshwater aquifer. This result can be attributed to the over-exploitation of the aquifer and hydraulic head and gradient distribution in the area. The framework provided in this study for spatio-temporal analysis of unstructured EC data is useful for groundwater managers in making proper decisions.     

Promoting corporate sustainability through sustainable resource management: A hybrid decision-making approach incorporating social media data

Previous studies revealed triple bottom line cannot entirely cover the concept of corporate sustainability. This study thus uses sustainable resource management (SRM) to improve corporate sustainability (CS) performance considering the socio-environmental, socio-economical, and eco-efficiency aspects. In this study, the vague set (VS) theory and the technique for order preference by similarity to ideal solution (TOPSIS) method are integrated as a hybrid decision-making tool by which social media data can be transformed into entropy weights. The results indicate eco-efficiency and society should be prioritized to improve the corporate sustainability performance. Specifically, the aspects should be promoted through encouraging environmental innovation, redesigning consumers' offer, raising support of the institutions and policy measures, and organizing synergetic involvement. The contributions of this study are three-fold: (i) establishing a comprehensive framework for guiding firms make effective improvements; (ii) developing a hybrid VS-TOPSIS method to process the assessment data and social media information and address the interrelationships; (3) identifying the decisive SRM criteria to precisely guide the Chinese automobile industry towards CS under severe resource constraints.     

Geospatial Analysis of Climatic and Geomorphic Interactions Influencing Stream Discharge, Appalachian Mountains, USA

Streamflow values are commonly synthesized for locations where flow measurement stations are lacking or where only intermittent measurements are available. In an Appalachian Mountains dataset comprised of 29 watersheds, the most appropriate among geomorphic, geologic, and hydrogeologic datasets were selected for use in prediction of streamflow at watershed scale. A statistical model was developed using principal components analysis (PCA) and cluster analysis (CA) for. Using CA on variables derived from the PCA, an optimum set of variables was derived for predicting streamflow. Results indicate there are two categories of watersheds in the study area. The first is strongly correlated with climatic variables (precipitation, temperature, elevation, and groundwater recharge). The second is strongly correlated with two geomorphic variables (watershed slope and percentage of forested area). The spatial distribution of cluster classifications shows that watersheds dominated by the climatic component are located along the Allegheny Front while watersheds dominated by the geomorphic component are located in the Allegheny Plateau and Valley and Ridge physiographic provinces. These variations between the Allegheny Plateau and Valley and Ridge physiographic provinces suggest that, to accurately model streamflow, modeling needs be done based on natural physiographic boundaries rather than political boundaries. In this physiographic setting, elevation seems to be a major control.