La evaluación de la productividad de los recursos naturales es primordial para su uso óptimo y garantizar su sustentabilidad. El objetivo del presente trabajo fue determinar la pertinencia del uso de indicadores de eficiencia de uso del agua para evaluar la vulnerabilidad de los sistemas agrícolas bajo riego. Se evaluó de la productividad de los patrones de cultivo para dos ciclos agrícolas (primavera-verano 2003 y otoño-invierno 2003-2004) de dos Distritos de Riego del Norte Centro de México; así como la operatividad para cuatro Distritos de Riego. En la evaluación se aplicó el índice propuesto por el Instituto Internacional del Manejo del Agua. Se concluye la utilidad del uso de indicadores para la adecuada toma de decisiones para el uso efi ciente del agua de riego en la producción agrícola de los Distritos de Riego. | The evaluation of productivity of the natural resources is an essential task for promoting its sustainability and optimal use. The overall objective of this study was to expose the relevance of the use of efficiency and vulnerability indexes for the use of water in agricultural systems under irrigation. A study case is presented regarding the evaluation of crop patterns for the agricultural year 2003 during the spring-summer season and fall-winter 2003-2004 of two irrigation districts in the central-north region of Mexico. Also, the evaluation of the operation of four irrigation districts is presented. In both cases, indexes developed for the International Water Management Institute were used. We concluded on the utility of these indexes for satisfactory decision taking processes and for clasifing farmers according to their capacity to cope with climatic uncertainty.

Nonlinear complex behavior of pore-water pressure responses to rainfall was modelled using support vector regression (SVR). Pore-water pressure can rise to disturbing levels that may result in slope failure during or after rainfall. Traditionally, monitoring slope pore-water pressure responses to rainfall is tedious and expensive, in that the slope must be instrumented with necessary monitors. Data on rainfall and corresponding responses of pore-water pressure were collected from such a monitoring program at a slope site in Malaysia and used to develop SVR models to predict pore-water pressure fluctuations. Three models, based on their different input configurations, were developed. SVR optimum meta-parameters were obtained using k-fold cross validation and a grid search. Model type 3 was adjudged the best among the models and was used to predict three other points on the slope. For each point, lag intervals of 30 min, 1 h and 2 h were used to make the predictions. The SVR model predictions were compared with predictions made by an artificial neural network model; overall, the SVR model showed slightly better results. Uncertainty quantification analysis was also performed for further model assessment. The uncertainty components were found to be low and tolerable, with d-factor of 0.14 and 74 % of observed data falling within the 95 % confidence bound. The study demonstrated that the SVR model is effective in providing an accurate and quick means of obtaining pore-water pressure response, which may be vital in systems where response information is urgently needed.

The quantification of groundwater flow near the freshwater–saltwater transition zone at the coast is difficult because of variable-density effects and tidal dynamics. Head measurements were collected along a transect perpendicular to the shoreline at a site south of the city of Adelaide, South Australia, to determine the transient flow pattern. This paper presents a detailed overview of the measurement procedure, data post-processing methods and uncertainty analysis in order to assess how measurement errors affect the accuracy of the inferred flow patterns. A particular difficulty encountered was that some of the piezometers were leaky, which necessitated regular measurements of the electrical conductivity and temperature of the water inside the wells to correct for density effects. Other difficulties included failure of pressure transducers, data logger clock drift and operator error. The data obtained were sufficiently accurate to show that there is net seaward horizontal flow of freshwater in the top part of the aquifer, and a net landward flow of saltwater in the lower part. The vertical flow direction alternated with the tide, but due to the large uncertainty of the head gradients and density terms, no net flow could be established with any degree of confidence. While the measurement problems were amplified under the prevailing conditions at the site, similar errors can lead to large uncertainties everywhere. The methodology outlined acknowledges the inherent uncertainty involved in measuring groundwater flow. It can also assist to establish the accuracy requirements of the experimental setup.

Complex hydrogeological systems require detailed knowledge of aquifer dynamics to ensure appropriate and sustainable management of the groundwater resource. The Riardo Plain aquifer, southern Italy, is a strategic resource for conjunctive uses; nevertheless, the conceptual model still suffers some uncertainties due to the presence of a deep lateral inflow through the carbonate basement. Therefore, the realisation of a 3D numerical model at catchment scale needs preliminary tests to constrain the possible additional inflow rate, which is at the moment only estimated through the results of the groundwater budget calculation. A 2D section of the mixing area was modelled using FEFLOW in order to test the hypothesis of a combined recharge. Seven versions of the same model were calibrated over an increasing number of adjustable parameters according to their sensitivity. The most efficient model version was identified according to the calculated information criteria and the sum of squared-weighted residuals. In the second phase of the work, nine model scenarios characterised by different deep inflow rates were calibrated and validated according to the same procedure of the first model, in order to identify the range of possible acceptable solutions. The most likely deep inflow rate is 34 ± 4% of the total recharge, corresponding to an estimated deep inflow of 415 ± 50 L/s in the Riardo Plain aquifer through the carbonate basement. This methodological approach will be the basis of following numerical 3D numerical models of the Riardo Plain and can be a valuable tool in conceptualising similar mineral water areas.

Coastal groundwater flow is driven by an interplay between terrestrial and marine forcings. One of the distinguishing features in these settings is the formation of a freshwater lens due to the density difference between fresh and saline groundwater. The present study uses data collected on Sable Island, Canada—a remote sand island in the northwest Atlantic Ocean—to highlight the potential of exploiting freshwater lens geometry for calibration of numerical groundwater flow models in coastal settings. Three numerical three-dimensional variable-density groundwater flow models were constructed for different segments of the island, with only one model calibrated using the freshwater–saltwater interface derived from an electromagnetic geophysical survey. The other two (uncalibrated) models with the same parameterisation as the calibrated model successfully reproduced the interpreted interface depth and location of freshwater ponds at different parts of the island. The successful numerical model calibration, based solely on the geophysically derived interface depth, is enabled by the interface acting as an amplified version of the water table, which reduces the relative impact of the interpreted depth uncertainty. Furthermore, the freshwater–saltwater interface is far more inertial than the water table, making it less sensitive to short-term forcings. Such “noise-filtering” behaviour enables the use of the freshwater–saltwater interface for calibration even in dynamic settings where selection of representative groundwater heads is challenging. The completed models provide insights into island freshwater lens behaviour and highlight the role of periodic beach inundation and wave overheight in driving short-term water-table variability, despite their limited impact on the interface depth.

In the numerical simulation of groundwater flow, uncertainties often affect the precision of the simulation results. Stochastic and statistical approaches such as the Monte Carlo method, the Neumann expansion method and the Taylor series expansion, are commonly employed to estimate uncertainty in the final output. Based on the first-order interval perturbation method, a combination of the interval and perturbation methods is proposed as a viable alternative and compared to the well-known equal interval continuous sampling method (EICSM). The approach was realized using the GFModel (an unsaturated-saturated groundwater flow simulation model) program. This study exemplifies scenarios of three distinct interval parameters, namely, the hydraulic conductivities of six equal parts of the aquifer, their boundary head conditions, and several hydrogeological parameters (e.g. specific storativity and extraction rate of wells). The results show that the relative errors of deviation of the groundwater head extremums (RDGE) in the late stage of simulation are controlled within approximately ±5% when the changing rate of the hydrogeological parameter is no more than 0.2. From the viewpoint of the groundwater head extremums, the relative errors can be controlled within ±1.5%. The relative errors of the groundwater head variation are within approximately ±5% when the changing rate is no more than 0.2. The proposed method of this study is applicable to unsteady-state confined water flow systems.

This study aims to assess the sensitivity of river level estimations to the stream–aquifer exchanges within a hydrogeological model of the Upper Rhine alluvial aquifer (France/Germany), characterized as a large shallow aquifer with numerous hydropower dams. Two specific points are addressed: errors associated with digital elevation models (DEMs) and errors associated with the estimation of river level. The fine-resolution raw Shuttle Radar Topographic Mission dataset is used to assess the impact of the DEM uncertainties. Specific corrections are used to overcome these uncertainties: a simple moving average is applied to the topography along the rivers and additional data are used along the Rhine River to account for the numerous dams. Then, the impact of the river-level temporal variations is assessed through two different methods based on observed rating curves and on the Manning formula. Results are evaluated against observation data from 37 river-level points located over the aquifer, 190 piezometers, and a spatial database of wetlands. DEM uncertainties affect the spatial variability of the stream–aquifer exchanges by inducing strong noise and unrealistic peaks. The corrected DEM reduces the biases between observations and simulations by 22 and 51% for the river levels and the river discharges, respectively. It also improves the agreement between simulated groundwater overflows and observed wetlands. Introducing river-level time variability increases the stream–aquifer exchange range and reduces the piezometric head variability. These results confirm the need to better assess river levels in regional hydrogeological modeling, especially for applications in which stream–aquifer exchanges are important.

Sustainable management of groundwater resources is vital for development of areas at risk from water-resource over-exploitation. In northeast Thailand, the Phu Thok aquifer is an important water source, particularly in the Thaphra area, where increased groundwater withdrawals may result in water-level decline and saline-water upconing. Three-dimensional finite-difference flow models were developed with MODFLOW to predict the impacts of future pumping on hydraulic heads. Four scenarios of pumping and recharge were defined to evaluate the system response to future usage and climate conditions. Primary model simulations show that groundwater heads will continue to decrease by 4–12 m by the year 2040 at the center of the highly exploited area, under conditions of both increasing pumping and drought. To quantify predictive uncertainty in these estimates, in addition to the primary conceptual model, three alternative conceptual models were used in the simulation of sustainable yields. These alternative models show that, for this case study, a reasonable degree of uncertainty in hydrostratigraphic interpretation is more impactful than uncertainty in recharge distribution or boundary conditions. The uncertainty-analysis results strongly support addressing conceptual-model uncertainty in the practice of groundwater-management modeling. Doing so will better assist decision makers in selecting and implementing robust sustainable strategies.

In most arid areas, due to scarce hydrogeological data, it is a challenge to locate groundwater sources and to meet water demand for residential, irrigation, and mining uses. In this study, an innovative method is presented, using magnetic resonance sounding (MRS), to detect areas suitable as groundwater sources on the Mongolian Plateau. First, a target investigation area was identified with a small number of MRS surveys of potential areas by determining whether aquifers exist, whether the aquifers have relatively large water contents and relaxation times, and whether there are hydraulic connections among the aquifers. Next, an intensive MRS survey (158 points in total) was conducted in the target investigation area, and eight boreholes were drilled. A comparison of the borehole data and MRS data showed that when the MRS data had a high signal-to-noise ratio, the aquifer depth and transmissivity estimated by MRS were associated with a deviation of only 4.85 m from the measured depth, and an uncertainty in transmissivity of 15.53%, respectively. These values indicated that the proposed method is highly accurate. Finally, a kriging interpolation method was used to construct distribution maps of groundwater levels, aquifer thickness, transmissivity, and water yield, based on the borehole and MRS data. The reliability of the results was assessed from several perspectives. The findings showed that this step-by-step approach is an effective method of groundwater source detection in arid areas with scarce hydrogeological data.

The classical aquitard-drainage model COMPAC has been modified to simulate the compaction process of a heterogeneous aquitard consisting of multiple sub-units (Multi-COMPAC). By coupling Multi-COMPAC with the parameter estimation code PEST++, the vertical hydraulic conductivity (K ᵥ) and elastic (S ₛₖₑ) and inelastic (S ₛₖₚ) skeletal specific-storage values of each sub-unit can be estimated using observed long-term multi-extensometer and groundwater level data. The approach was first tested through a synthetic case with known parameters. Results of the synthetic case revealed that it was possible to accurately estimate the three parameters for each sub-unit. Next, the methodology was applied to a field site located in Changzhou city, China. Based on the detailed stratigraphic information and extensometer data, the aquitard of interest was subdivided into three sub-units. Parameters K ᵥ, S ₛₖₑ and S ₛₖₚ of each sub-unit were estimated simultaneously and then were compared with laboratory results and with bulk values and geologic data from previous studies, demonstrating the reliability of parameter estimates. Estimated S ₛₖₚ values ranged within the magnitude of 10⁻⁴ m⁻¹, while K ᵥ ranged over 10⁻¹⁰–10⁻⁸ m/s, suggesting moderately high heterogeneity of the aquitard. However, the elastic deformation of the third sub-unit, consisting of soft plastic silty clay, is masked by delayed drainage, and the inverse procedure leads to large uncertainty in the S ₛₖₑ estimate for this sub-unit.