Groundwater travel time computation for two-layer islands

A closed-form analytical computation of groundwater travel time (GWTT) for two-layer oceanic small island aquifers is developed assuming steady-state and sharp-interface conditions. The two-layer geology impacts on the GWTT are investigated using the developed analytical solution to achieve a greater transparency of such conceptualizations. The results demonstrate that the inclusion of geologic layering leads to large changes in the GWTT. Sensitivity analyses, using specified dimensionless parameters, are employed to assess the influences of hydraulic conductivity, recharge rate, upper layer thickness, and seawater/freshwater density difference parameters, which influence the GWTT. These evaluations reveal that the GWTT is mainly influenced by the recharge rate and the upper layer thickness compared to the other influential parameters when the typical parameter ranges are considered.     

Compounding effects of human activities and climatic changes on surface water availability in Iran

Climatic Change - By combining long-term ground-based data on water withdrawal with climate model projections, this study quantifies the compounding effects of human activities and climate change...     

An efficient tool for accelerating the numerical solution of the stochastic subsurface flow problem using neural networks

 An efficient numerical solution for the two-dimensional groundwater flow problem using artificial neural networks (ANNs) is presented. Under stationary velocity conditions with unidirectional mean flow, the conductivity realizations and the head gradients, obtained by a traditional finite difference solution to the flow equation, are given as input-output pairs to train a neural network. The ANN is trained successfully and a certain level of recognition of the relationship between input conductivity patterns and output head gradients is achieved. The trained network produced velocity realizations that are physically plausible without solving the flow equation for each of the conductivity realizations. This is achieved in a small fraction of the time necessary for solving the flow equations. The prediction accuracy of the ANN reaches 97.5% for the longitudinal head gradient and 94.7% for the transverse gradient. Head-gradient and velocity statistics in terms of the first two moments are obtained with a very high accuracy. The cross covariances between head gradients and the fluctuating log-conductivity (log-K) and between velocity and log-K obtained with the ANN approach match very closely those obtained by a traditional numerical solution. The same is true for the velocity components auto-covariances. The results are also extended to transport simulations with very good accuracy. Spatial moments (up to the fourth) of mean-concentration plumes obtained using ANNs are in very good agreement with the traditional Monte Carlo simulations. Furthermore, the concentration second moment (concentration variance) is very close between the two approaches. Considering the fact that higher moments of concentration need more computational effort in numerical simulations, the advantage of the presented approach in saving long computational times is evident. Another advantage of the ANNs approach is the ability to generalize a trained network to conductivity distributions different from those used in training. However, the accuracy of the approach in cases with higher conductivity variances is being investigated.     

Groundwater origins and mixing pattern in the multilayer aquifer system of the Gafsa-south mining district: a chemical and isotopic approach

Major ion geochemistry and environmental isotopes were used to identify the origins and the mineralisation processes of groundwater flowing within the three aquifer levels of the multilayer system of the Gafsa-south mining district (Southwestern Tunisia). It has been demonstrated that groundwaters are characterised by a Ca–Mg–SO₄ water type. Geochemical pattern is mainly controlled by the dissolution of halite, gypsum and/or anhydrite as well as by the incongruent dissolution of dolomite. δ¹⁸O and δ²H values are much lower than the isotopic signature of regional precipitation and fall close to the meteoric water lines, indicating that groundwaters have not been significantly affected by evaporation or mineral–water reactions. The distribution of stable and radiogenic isotopes (δ¹⁸O, δ²H, δ¹³C and ¹⁴C) within the aquifer levels suggests that the deep confined aquifer receives a significant modern recharge at higher altitudes, while, the shallow unconfined aquifer has been mainly recharged under cooler paleoclimatic condition, likely during Late Pleistocene and Early Holocene humid periods. However, waters from the intermediate confined/unconfined aquifer have composite isotopic signatures, highlighting that they are derived from a mixture of the two first end-members.     

Investigation of RS and GIS techniques on MPSIAC model to estimate soil erosion

Soil erosion due to surface water is a standout among the serious threat land degradation problem and an hazard environmental destruction. The first stage for every kind of soil conservation planning is recognition of soil erosion status. In this research, the usability of two new techniques remote sensing and geographical information system was assessed to estimate the average annual specific sediments production and the intensity erosion map at two sub-basins of DEZ watershed, southwest of Lorestan Province, Iran, namely Absorkh and Keshvar sub-basins with 19,920 ha, using Modified Pacific Southwest Inter-Agency Committee (MPSIAC) soil erosion model. At the stage of imagery data processing of IRS-P6 satellite, the result showed that an overall accuracy and kappa coefficient were 90.3% and 0.901, respectively, which were considered acceptable or good for imagery data. According to our investigation, the study area can be categorized into three level of severity of erosion: moderate, high, and very high erosion zones. The amount of specific sediments and soil erosion predicted by MPSIAC model was 1374.656 and 2396.574 m³ km^?2 year^?1, respectively. The areas situated at the center and south parts of the watershed were subjected to significant erosion because of the geology formation and ground cover, while the area at the north parts was relatively less eroded due to intensive land cover. Based on effective of nine factors, the driving factors from high to low impact included: Topography > Land use > Upland erosion > Channel erosion > Climate > Ground cover > Soil > Runoff > Surface geology. The measured sediment yield of the watershed in the hydrometric station (Keshvar station) was approximately 2223.178 m³ km^?2 year^?1 and comparison of the amount of total sediment yield predicted by model with the measured sediment yield indicated that the MPSIAC model 38% underestimated the observed value of the watershed.