Indian agriculture is trapped in a complex nexus of groundwater depletion and energy subsidies. This nexus is the product of past public policy choices that initially offered opportunities to India’s small-holder-based irrigation economy but has now generated in its wake myriad economic, social, and environmental distortions. Conventional ‘getting-the-price-right’ solutions to reduce these distortions have consistently been undermined by the invidious political economy that the nexus has created. The historical evolution of the nexus is outlined, the nature and scale of the distortions it has created are explored, and alternative approaches which Indian policy makers can use to limit, if not eliminate, the damaging impacts of the distortions, are analysed.

Local groundwater management in Yemen and the means by which stakeholders can work together to improve water governance are discussed. In the last few decades the discourse on groundwater management in Yemen has increasingly been cast in terms of crisis, triggered by rapidly declining water tables around cities and in the main agricultural areas. However, in some places in Yemen, communities have responded by implementing local rules that have reduced conflict and provided more reliable and equitable access to water. This trend towards development of local groundwater governance is described, and could make a major contribution in realizing the goals of national water-sector policies and strategies. Twenty-four cases have been identified from different parts of the country and five cases are presented in detail. The article discusses how the process of local management could be nurtured and how it could contribute to rebalancing water use in several parts of Yemen.

Jinci Spring in Shanxi, north China, is a major local water source. It dried up in April 1994 due to groundwater overexploitation. The groundwater system is complex, involving many nonlinear and uncertain factors. Artificial neural network (ANN) models are statistical techniques to study parameter nonlinear relationships of groundwater systems. However, ANN models offer little explanatory insight into the mechanisms of prediction models. Sensitivity analysis can overcome this shortcoming. In this study, a back-propagation neural network model was built based on the relationship between groundwater level and its sensitivity factors in Jinci Spring Basin; these sensitivity factors included precipitation, river seepage, mining drainage, groundwater withdrawals and lateral discharge to the associated Quaternary aquifer. All the sensitivity factors were analyzed with Garson’s algorithm based on the connection weights of the neural network model. The concept of “sensitivity range” was proposed to describe the value range of the input variables to which the output variables are most sensitive. The sensitivity ranges were analyzed by a local sensitivity approach. The results showed that coal mining drainage is the most sensitive anthropogenic factor, having a large effect on groundwater level of the Jinci Spring Basin.

In an urban regional groundwater flow field, the presence of thousands of channels between impervious structures makes the field difficult to simulate using the finite-element method (FEM), because the scale of the field is usually several orders of magnitude larger than that of the channels. To overcome this problem, a simple element for the simulation of potential channel flows has been developed. This element works with linear triangular elements and can be easily implemented in a finite-element code to simulate the channel flows with a sparse mesh without a loss of global accuracy. The transmissivity matrix of this element is deduced from the analytical solution for channel flow. The application of the element is discussed, and the accuracy of the element is assessed. The element makes it easy to merge small structures that are close to each other into a larger one that can be modeled with a sparse mesh.

Extensive hydrogeological investigations followed by three-dimensional groundwater flow and contaminant transport modelling were carried out around a proposed uranium tailings pond at Seripalli in Andhra Pradesh, India, to estimate its radiological impact. The hydrogeological parameters and measured groundwater level were used to model the groundwater flow and contaminant transport from the uranium tailings pond using a finite-element-based model. The simulated groundwater level compares reasonably with the observed groundwater level. Subsequently, the transport of long-lived radionuclides such as 238U, 234U, 230Th and 226Ra from the proposed tailings pond was modelled. The ingrowths of progenies were also considered in the modelling. It was observed that these radionuclides move very little from the tailings pond, even at the end of 10,000 y, due to their high distribution coefficients and low groundwater velocities. These concentrations were translated into committed effective dose rates at different distances in the vicinity of the uranium tailings pond. The results indicated that the highest effective dose rate to members of the public along the groundwater flow pathway is 2.5 times lower than the drinking water guideline of 0.1 mSv/y, even after a long time period of 10,000 y.

The Sultansazligi Wetland, an internationally important aquatic site in Turkey, has suffered from a severe contraction since the early 1990s. To determine the factors affecting contraction, temporal variations of climatic and hydrogeologic variables have been investigated. Both the long-term climate change and the increasing surface and groundwater use are found to be responsible. Hydrologic analyses reveal an apparent correlation between increasing use of water resources and contraction in the wetland. Particularly, increasing use of groundwater and complete capture of springs and effluent streams once feeding the wetland are found to be the prime factors. Furthermore, a strong coherence is found between the temporal trend of the North Atlantic Oscillation and local precipitation, which is the main source of the basin’s water excess and supplies the wetland. Future existence of the wetland depends on the application of thrifty water-use polices in irrigation.

An artificial neural network model (ANN) and a geographic information system (GIS) are applied to the mapping of regional groundwater productivity potential (GPP) for the area around Pohang City, Republic of Korea. The model is based on the relationship between groundwater productivity data, including specific capacity (SPC) and its related hydrogeological factors. The related factors, including topography, lineaments, geology, and forest and soil data, are collected and input into a spatial database. In addition, SPC data are collected from 44 well locations. The SPC data are randomly divided into a training set, to analyse the GPP using the ANN, and a test set, to validate the predicted potential map. Each factor’s relative importance and weight are determined by the back-propagation training algorithms and applied to the input factor. The GPP value is then calculated using the weights, and GPP maps are created. The map is validated using area under the curve analysis with the SPC data that have not been used for training the model. The validation shows prediction accuracies between 73.54 and 80.09 %. Such information and the maps generated from it could serve as a scientific basis for groundwater management and exploration.

A drilling project was carried out in Syria to assess the potential of the deep groundwater resources of the Cretaceous aquifer, composed of Cenomanian-Turonian limestones and dolomites. In this context, isotope (14C, 3H, δ13C, δ18O, δ2H) and hydrochemical analyses were performed on wells in and around the Aleppo and Steppe basins. The interpretation includes complementary results from published and unpublished literature. The results provide evidence that many new wells pump mixed groundwater from the Cretaceous aquifer and the overlying Paleogene aquifer. Radiocarbon measurements confirmed dominating Pleistocene groundwater in the Cretaceous aquifer and mainly Holocene groundwater in the Paleogene aquifer. Most groundwater in the Cretaceous aquifer seems to be recharged in the western limestone ridges, stretching from Jebel az Zawiyah (south of Idlep) via Jebel Samane (south of Afrin and A’zaz) to the region north of Aleppo, and in the Northern Palmyrides mountain belt. Some recharge also occurs around the basalt plateau of the Jebel al Hass, south east of Aleppo. It is concluded that the Taurus Mountains and the Euphrates River do not recharge the Cretaceous aquifer. The sources of recharge seem to be occasionally occurring intensive winter storms that approach from Siberia.

Anthropogenic sources of carbon from landfill or waste leachate can promote reductive dissolution of in situ arsenic (As) and enhance the mobility of As in groundwater. Groundwater from residential-supply wells in a fractured crystalline-rock aquifer adjacent to a Superfund site in Raymond, New Hampshire, USA, showed evidence of locally enhanced As mobilization in relatively reducing (mixed oxic-anoxic to anoxic) conditions as determined by redox classification and other lines of evidence. Redox classification was determined from geochemical indicators based on threshold concentrations of dissolved oxygen (DO), nitrate (NO 3 – ), iron (Fe2+), manganese (Mn2+), and sulfate (SO 4 2– ). Redox conditions were evaluated also based on methane (CH4), excess nitrogen gas (N2) from denitrification, the oxidation state of dissolved As speciation (As(III) and As(V)), and several stable isotope ratios. Samples from the residential-supply wells primarily exhibit mixed redox conditions, as most have long open boreholes (typically 50–100 m) that receive water from multiple discrete fractures with contrasting groundwater chemistry and redox conditions. The methods employed in this study can be used at other sites to gauge redox conditions and the potential for As mobilization in complex fractured crystalline-rock aquifers where multiple lines of evidence are likely needed to understand As occurrence, mobility, and transport.

The development and implementation of a hybrid discrete fracture network/equivalent porous medium (DFN/EPM) approach to groundwater flow at the Gyeong-Ju low- and intermediate-level radioactive waste (LILW) disposal site in the Republic of Korea is reported. The geometrical and hydrogeological properties of fractured zones, background fractures and rock matrix were derived from site characterization data and implemented as a DFN. Several DFN realizations, including the deterministic fractured zones and the stochastic background fractures, whose statistical properties were verified by comparison with in-situ fracture and hydraulic test data, were suggested, and they were then upscaled to continuums using a fracture tensor approach for site-scale flow simulations. The upscaled models were evaluated by comparison to in-situ pressure monitoring data, and then used to simulate post-closure hydrogeology for the LILW facility. Simulation results demonstrate the importance of careful characterization and implementation of fractured zones. The study highlighted the importance of reducing uncertainty regarding the properties and variability of natural background fractures, particularly in the immediate vicinity of repository emplacement.