Aquifers provide water, nutrients and energy with various patterns for many aquatic and terrestrial ecosystems. Groundwater-dependent ecosystems (GDEs) are increasingly recognized for their ecological and socio-economic values. The current knowledge of the processes governing the ecohydrological functioning of inland GDEs is reviewed, in order to assess the key drivers constraining their viability. These processes occur both at the watershed and emergence scale. Recharge patterns, geomorphology, internal geometry and geochemistry of aquifers control water availability and nutritive status of groundwater. The interface structure between the groundwater system and the biocenoses may modify the groundwater features by physicochemical or biological processes, for which biocenoses need to adapt. Four major types of aquifer-GDE interface have been described: springs, surface waters, peatlands and terrestrial ecosystems. The ecological roles of groundwater are conditioned by morphological characteristics for spring GDEs, by the hyporheic zone structure for surface waters, by the organic soil structure and volume for peatland GDEs, and by water-table fluctuation and surface floods in terrestrial GDEs. Based on these considerations, an ecohydrological classification system for GDEs is proposed and applied to Central and Western-Central Europe, as a basis for modeling approaches for GDEs and as a tool for groundwater and landscape management.

Understanding groundwater-pumpage sources is essential for assessing impacts on water resources and sustainability. The objective of this study was to quantify pumping impacts and sources in dipping, unconfined/confined aquifers in the Gulf Coast (USA) using the Texas Carrizo-Wilcox aquifer. Potentiometric-surface and streamflow data and groundwater modeling were used to evaluate sources and impacts of pumpage. Estimated groundwater storage is much greater in the confined aquifer (2,200 km3) than in the unconfined aquifer (170 km3); however, feasibility of abstraction depends on pumpage impacts on the flow system. Simulated pre-development recharge (0.96 km3/yr) discharged through evapotranspiration (ET, ∼37%), baseflow to streams (∼57%), and to the confined aquifer (∼6%). Transient simulations (1980–1999) show that pumpage changed three out of ten streams from gaining to losing in the semiarid south and reversed regional vertical flow gradients in ∼40% of the entire aquifer area. Simulations of predictive pumpage to 2050 indicate continued storage depletion (41% from storage, 32% from local discharge, and 25% from regional discharge capture). It takes ∼100 yrs to recover 40% of storage after pumpage ceases in the south. This study underscores the importance of considering capture mechanism and long-term system response in developing water-management strategies.

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.

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.

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.

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.