The widely used groundwater flow model MODFLOW offers a range of software packages to simulate the interaction between streams and groundwater in aquifer systems. However, these existing packages lack a general method to address the chaotic simulation sequences of stream segments and require these segments to be ordered by modelers as input to the code. Therefore, it is challenging to simulate a stream network divided into a large number of segments such as a canal irrigation system. In this study, the Streamflow Automatic Routing (SAR) package was developed, and an effective method is proposed to automatically determine the segment simulation sequence. The stream segment order in the SAR input file is arbitrary, which allows modifications of the stream network by removing segments directly and adding segments at the end of the segment group. This mainly includes two processes: scanning all the outlet channels of the water system and calling the recursive algorithm for each outlet channel of the water system. The SAR package was tested using a hypothetical stream–aquifer system and applied to a complex flow field in Aiding Lake of Turpan Basin, China. In the results, a close fitting between the simulation and observations shows that the SAR package precisely simulated the exchange flux between the steams and aquifer. The SAR package can significantly improve the efficiency of simulations in a complex stream network, and it can be widely used as a subroutine package of MODFLOW in agricultural irrigation areas where rivers and canals are interlaced.

A combined simulation-optimization model was developed to minimize the freshwater footprint at multi-well hydraulic fracturing sites. The model seeks to reduce freshwater use by blending it with brackish groundwater and recovered water. Time-varying water quality and quantity mass balance expressions and drawdown calculations using the Theis solution along with the superposition principle were embedded into the optimization model and solved using genetic algorithms. The model was parameterized for representative conditions in the Permian Basin oil and gas play region with the Dockum Formation serving as the brackish water source (Texas, USA). The results indicate that freshwater use can be reduced by 25–30 % by blending. Recovered water accounted for 2–3 % of the total blend or 10–15 % of total water recovered on-site. The concentration requirements of sulfate and magnesium limited blending. The evaporation in the frac pit constrained the amount blended during summer, while well yield of the brackish (Dockum) aquifer constrained the blending during winter. The Edwards-Trinity aquifer provided the best quality water compared to the Ogallala and Pecos Valley aquifers. However, the aquifer has low diffusivity causing the drawdown impacts to be felt over large areas. Speciation calculations carried out using PHREEQC indicated that precipitation of barium and strontium minerals is unlikely in the blended water. Conversely, the potential for precipitation of iron minerals is high. The developed simulation-optimization modeling framework is flexible and easily adapted for water management at other fracturing sites.

The Central-West region of Argentina was seriously affected by a series of convective summer storms on January–February of 2013 generating many debris flows and rockfall in the Central Andes mountain regions. In particular, the unreported 8th February event caused the sad death of a 10-year-old child being completely ignored by society and local authorities. Despite this, meteorological conditions associated with this event and further episodes were rarely measured and determined mainly due to scarce meteorological stations in Andean mountain areas. In this paper, meteorological data from CMORPH algorithm and measurements of surrounding gauges were analyzed for estimating the triggering precipitation value of this event. As well, the particular debris flow channeled into the main branch of the Amarilla gully in the Agua Negra valley was geomorphologically described. The amount of precipitation associated with this debris flow was 5.5 and 13.2 mm accumulated previous to the event. This violent debris flow was generated in a talus zone in a periglacial environment located just below a covered rock glacier. However, the influence of the permafrost thawing in this process is not feasible. The altitude of the 0 °C isotherm was lower during the previous days of the event, and no monitoring on permafrost is available for this area. The volume of removed mass was estimated in 5 × 10⁴ m³, and the mean velocity was 35 km/h. Boulders of 4 m diameter were found in the source area, while the deposit is up to 75% sandy with clasts that hardly exceed 10 cm in the alluvial fan distal part. Herein the main objective is to advice about the probable catastrophic impact of similar events in the future. These findings could be useful for hazard remediation, mitigation, and prevention plans for the Agua Negra international pass under construction.

The application of statistical classification methods is investigated—in comparison also to spatial interpolation methods—for predicting the acceptability of well-water quality in a situation where an effective quantitative model of the hydrogeological system under consideration cannot be developed. In the example area in northern Italy, in particular, the aquifer is locally affected by saline water and the concentration of chloride is the main indicator of both saltwater occurrence and groundwater quality. The goal is to predict if the chloride concentration in a water well will exceed the allowable concentration so that the water is unfit for the intended use. A statistical classification algorithm achieved the best predictive performances and the results of the study show that statistical classification methods provide further tools for dealing with groundwater quality problems concerning hydrogeological systems that are too difficult to describe analytically or to simulate effectively.

Freshwater scarcity is an ever-increasing problem throughout the arid and semi-arid countries, and it often results in poverty. Thus, it is necessary to enhance understanding of freshwater resources availability, particularly for groundwater, and to be able to implement functional water resources plans. This study introduces a novel statistical approach combined with a data-mining ensemble model, through implementing evidential belief function and boosted regression tree (EBF-BRT) algorithms for groundwater potential mapping of the Lordegan aquifer in central Iran. To do so, spring locations are determined and partitioned into two groups for training and validating the individual and ensemble methods. In the next step, 12 groundwater-conditioning factors (GCFs), including topographical and hydrogeological factors, are prepared for the modeling process. The mentioned factors are employed in the application of the EBF model. Then, the EBF values of the GCFs are implemented as input to the BRT algorithm. The results of the modeling process are plotted to produce spring (groundwater) potential maps. To verify the results, the receiver operating characteristics (ROC) test is applied to the model’s output. The findings of the test indicated that the areas under the ROC curves are 75 and 82% for the EBF and EBF-BRT models, respectively. Therefore, it can be inferred that the combination of the two techniques could increase the efficacy of these methods in groundwater potential mapping.

The Henry saltwater intrusion problem provides a semi-analytical solution that is largely used for benchmarking density-dependent groundwater flow models. The major drawback of this problem arises from the high dispersion value used by Henry (represented by the dimensionless parameter b = 0.1). Finding a stable semi-analytical solution for small values of b is challenging due to the low convergence of the corresponding nonlinear system. In this work, an accurate semi-analytical solution is developed in the case of a very narrow transition zone corresponding to b = 0.005. About 6,330 terms are used in the Fourier series to accurately represent the solution. The resolution of the corresponding highly nonlinear system is made possible by the modified Powell hybrid algorithm due to the analytical evaluation of the Jacobian, which drastically reduces the computational time. The new test problem is also investigated numerically using different numerical methods and different mesh sizes to show its high worthiness, compared to the standard Henry problem, for benchmarking density driven flow codes.

Coal-floor water-inrush incidents account for a large proportion of coal mine disasters in northern China, and accurate risk assessment is crucial for safe coal production. A novel and promising assessment model for water inrush is proposed based on random forest (RF), which is a powerful intelligent machine-learning algorithm. RF has considerable advantages, including high classification accuracy and the capability to evaluate the importance of variables; in particularly, it is robust in dealing with the complicated and non-linear problems inherent in risk assessment. In this study, the proposed model is applied to Panjiayao Coal Mine, northern China. Eight factors were selected as evaluation indices according to systematic analysis of the geological conditions and a field survey of the study area. Risk assessment maps were generated based on RF, and the probabilistic neural network (PNN) model was also used for risk assessment as a comparison. The results demonstrate that the two methods are consistent in the risk assessment of water inrush at the mine, and RF shows a better performance compared to PNN with an overall accuracy higher by 6.67%. It is concluded that RF is more practicable to assess the water-inrush risk than PNN. The presented method will be helpful in avoiding water inrush and also can be extended to various engineering applications.

In numerical modeling of groundwater flow, the result of a given solution method is affected by the way in which transient flow conditions and geologic heterogeneity are simulated. An algorithm is demonstrated that simulates breakthrough curves at a pumping well by convolution-based particle tracking in a transient flow field for several synthetic basin-scale aquifers. In comparison to grid-based (Eulerian) methods, the particle (Lagrangian) method is better able to capture multimodal breakthrough caused by changes in pumping at the well, although the particle method may be apparently nonlinear because of the discrete nature of particle arrival times. Trial-and-error choice of number of particles and release times can perhaps overcome the apparent nonlinearity. Heterogeneous aquifer properties tend to smooth the effects of transient pumping, making it difficult to separate their effects in parameter estimation. Porosity, a new parameter added for advective transport, can be accurately estimated using both grid-based and particle-based methods, but predictions can be highly uncertain, even in the simple, nonreactive case.

Optimization methods have been used in groundwater modeling as well as for the planning and management of groundwater systems. This paper reviews and evaluates the various optimization methods that have been used for solving the inverse problem of parameter identification (estimation), experimental design, and groundwater planning and management. Various model selection criteria are discussed, as well as criteria used for model discrimination. The inverse problem of parameter identification concerns the optimal determination of model parameters using water-level observations. In general, the optimal experimental design seeks to find sampling strategies for the purpose of estimating the unknown model parameters. A typical objective of optimal conjunctive-use planning of surface water and groundwater is to minimize the operational costs of meeting water demand. The optimization methods include mathematical programming techniques such as linear programming, quadratic programming, dynamic programming, stochastic programming, nonlinear programming, and the global search algorithms such as genetic algorithms, simulated annealing, and tabu search. Emphasis is placed on groundwater flow problems as opposed to contaminant transport problems. A typical two-dimensional groundwater flow problem is used to explain the basic formulations and algorithms that have been used to solve the formulated optimization problems.

River impoundment is an alternative to artificial groundwater recharge in coastal aquifers, while mitigating seawater intrusion caused by anthropogenic activities. This study implements a new multiobjective optimization framework for management of the existing engineering measures of river multidamming impoundment and strategies for groundwater abstraction in Dagu River Basin, a water-scarce basin in north China. The optimization framework integrates a calibrated numerical model with a conceptualized river package to simulate the interaction between the Dagu River and groundwater due to river impoundment, and it focuses on the tradeoff among minimizing the seawater intrusion extent, minimizing the river seepage, and maximizing the allowable groundwater abstraction. Then the elitist nondominated sorting genetic algorithm (NSGA-II) is used to search for the Pareto-optimal solutions affected by different climate conditions. Results show that the river water level and groundwater abstraction schemes can be regulated to achieve the optimal tradeoffs among different objectives. To mitigate seawater intrusion, the impoundment river water level behind the dam adjacent to the seawater intrusion associated with years of insufficient precipitation should be raised by at least 0.5–1.5 m, while the river level behind the remaining dams should be reduced by at least 1 m. Moreover, under the constraint of restricting groundwater abstraction, the annual groundwater abstraction in the four county-level administrative subdomains should be adjusted by 1.2–1.5 million m³ or more in years with less precipitation compared to that in years with more precipitation. The implications might also be applied to other coastal aquifers with intense human activities.