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.

Construction of a conveyance tunnel through rock often induces the ingress of groundwater into the tunnel, a flow that changes both the hydrogeological regime of the tunnel and its environment. To explore this key interaction, a novel modeling approach using the conduit flow process (CFP) is developed that considers both the hydraulic head and the ingress of water from the rock matrix during excavation. The resulting flow values are predicted through an adapted MODFLOW numerical model into which the tunnel is introduced with the aid of the new CFP approach. The CFP approach can simulate both laminar and turbulent flow in the tunnel whether the flow is free surface or pressurized. Several simulations, including one for which the permeability of the tunnel perimeter is assumed to be identical to the hydraulic conductivity of the surrounding rock matrix, are then used to explore the sensitivity of the predicted head and flow conditions to the permeability of the tunnel perimeter. Comparisons of the numerical results with field data from the Kerman Water Conveyance Tunnel in Iran show that the proposed approach accurately predicts the spatial variation of both groundwater ingress and hydraulic head.

An accurate estimate of the groundwater inflow to a tunnel is one of the most challenging but essential tasks in tunnel design and construction. Most of the numerical or analytical solutions that have been developed ignore tunnel seepage conditions, material properties and hydraulic-head changes along the tunnel route during the excavation process, leading to inaccurate prediction of inflow rates. A method is introduced that uses MODFLOW code of GMS software to predict inflow rate as the tunnel boring machine (TBM) gradually advances. In this method, the tunnel boundary condition is conceptualized and defined using Drain package, which is simulated by dividing the drilling process into a series of successive intervals based on the tunnel excavation rates. In addition, the drain elevations are specified as the respective tunnel elevations, and the conductance parameters are assigned to intervals, depending on the TBM type and the tunnel seepage condition. The Qomroud water conveyance tunnel, located in Lorestan province of Iran, is 36 km in length. Since the Qomroud tunnel involved groundwater inrush during excavating, it is considered as a good case study to evaluate the presented method. The groundwater inflow to this tunnel during the TBM advance is simulated using the proposed method and the predicted rates are compared with observed rates. The results show that the presented method can satisfactorily predict the inflow rates as the TBM advances.

‘Blue water’ is the portion of freshwater flowing through rivers and the subsurface (groundwater) that is available for human consumption. ‘Green water’ is the portion stored in the unsaturated soil and vegetation canopy that is available only indirectly. Security of blue and green water resources is assessed over the Dorudzan Dam watershed in southern Iran. Precipitation and temperature data from 22 models of the Coupled Model Intercomparison Project Phase 5 are transiently downscaled at five climatic stations under three Representative Concentration Pathway (RCP) scenarios. The Soil and Water Assessment Tool (SWAT) is used to simulate and quantify blue and green water components over the region at the present time and under climate-change conditions. Climate-change study indicates that precipitation decreases (13–17%) and temperature increases (1.7–3. 3 °C) under the three RCPs, leading to substantial dam-inflow reduction. Evapotranspiration will increase while soil-water content will decrease, further intensifying green-water scarcity and vulnerability. Water use from the Kor River is sustainable at present, but future climate change will raise some ecological hotspots. Groundwater exploitation is currently unsustainable in all aquifers of the study area and climate change will further decrease the available groundwater, leading to intensification of the water crisis. Assessment of inter-annual security under climate change indicates that maximum scarcities of green water and surface blue water occur during spring and summer, and subsurface blue water (groundwater) maxima occur throughout the year. Thus, climate change threatens the future security of water resources in this arid watershed, requiring different management strategies for sustainability.

Many environmental problems are rooted in human behavior. This study aimed to explore the causal effect of cultural environmental bias on ‘sustainable behavior’ among agricultural groundwater users in Fars province, Iran, according to Klockner’s comprehensive model. A survey-based research project was conducted to gathering data on the paradigm of environmental psychology. The sample included agricultural groundwater users (n = 296) who were selected at random within a structured sampling regime involving study areas that represent three (higher, medium and lower) bounds of the agricultural-groundwater-vulnerability spectrum. Results showed that the “environment as ductile (EnAD)” variable was a strong determinant of sustainable behavior as it related to groundwater use, and that EnAE had the highest causal effect on the behavior of agricultural groundwater users. The adjusted model explained 41% variance of “groundwater sustainable behavior”. Based on the results, the groundwater sustainable behaviors of agricultural groundwater users were found to be affected by personal and subjective norm variables and that they are influenced by casual effects of the “environment as ductile (EnAD)” variable. The conclusions reflect the Fars agricultural groundwater users’ attitude or worldview on groundwater as an unrecoverable resource; thus, it is necessary that scientific disciplines like hydrogeology and psycho-sociology be considered together in a comprehensive approach for every groundwater study.

In southern Iran’s Gareh Bygone Plain, water-supply qanats in four mixed farming communities were desiccated by over-pumping of illegal dug wells throughout the area. Emergency situations developed, resulting in city-ward migration. Since 1983, 193 million m³ of water has been supplied to those communities by floodwater spreading (FWS) to facilitate spate irrigation of sandy rangeland (2,034 ha) and artificial recharge of groundwater (ARG), of which 76 % has recharged the aquifer. This resulted in a reverse migration of the population. The irrigated area in the 2010–2011 growing season increased 13.2 fold when compared to the pre-FWS period, and year-round forage for about 700 sheep has been provided since 1991. The ARG is a logical alternative to building large dams in Iran; 420,000 km² of coarse-grained alluvium provides capacity to store 5,000 km³ of water, representing more than ten times the annual precipitation of the whole country. As the equivalent cost for building dams to accommodate that volume is estimated at US$12.5 × 10¹², the potential value of the alluvium may be realized. ARG on the recharge areas of 33,000 of the desiccated qanats eventually could rejuvenate them. As agricultural commodities absorb 19 % of the monetary value of Iran’s imports, and ARG activities could supply the water to produce them, alluvium is even more valuable than oil, which provides foreign exchange. More importantly, ARG on 140,000 km² of the alluvium could strengthen the capacity to adapt to droughts and reduce the number and impact of water-related emergency situations.

Temporal changes in the quantity and chemical status of groundwater resources must be accurately quantified to aid sustainable management of aquifers. Monitoring data show that the groundwater level in Shahrood alluvial aquifer, northeastern Iran, continuously declined from 1993 to 2009, falling 11.4 m in 16 years. This constitutes a loss of 216 million m³from the aquifer’s stored groundwater reserve. Overexploitation and reduction in rainfall intensified the declining trend. In contrast, the reduced abstraction rate, the result of reduced borehole productivity (related to the reduction in saturated-zone thickness over time), slowed down the declining trend. Groundwater salinity varied substantially showing a minor rising trend. For the same 16-year period, increases were recorded in the order of 24% for electrical conductivity, 12.4% for major ions, and 9.9% for pH. This research shows that the groundwater-level declining trend was not interrupted by fluctuation in rainfall and it does not necessarily lead to water-quality deterioration. Water-level drop is greater near the aquifer’s recharging boundary, while greater rates of salinity rise occur around the end of groundwater flow lines. Also, fresher groundwater experiences a greater rate of salinity increase. These findings are of significance for predicting the groundwater level and salinity of exhausted aquifers.

Assessing the groundwater recharge potential zone and differentiation of the spring catchment area are extremely important to effective management of groundwater systems and protection of water quality. The study area is located in the Saldoran karstic region, western Iran. It is characterized by a high rate of precipitation and recharge via highly permeable fractured karstic formations. Pire-Ghar, Sarabe-Babaheydar and Baghe-rostam are three major karstic springs which drain the Saldoran anticline. The mean discharge rate and electrical conductivity values for these springs were 3, 1.9 and 0.98 m³/s, and 475, 438 and 347 μS/cm, respectively. Geology, hydrogeology and geographical information system (GIS) methods were used to define the catchment areas of the major karstic springs and to map recharge zones in the Saldoran anticline. Seven major influencing factors on groundwater recharge rates (lithology, slope value and aspect, drainage, precipitation, fracture density and karstic domains) were integrated using GIS. Geology maps and field verification were used to determine the weights of factors. The final map was produced to reveal major zones of recharge potential. More than 80 % of the study area is terrain that has a recharge rate of 55–70 % (average 63 %). Evaluating the water budget of Saldoran Mountain showed that the total volume of karst water emerging from the Saldoran karst springs is equal to the total annual recharge on the anticline. Therefore, based on the geological and hydrogeological investigations, the catchment area of the mentioned karst springs includes the whole Saldoran anticline.

One important tool for water resources management in arid and semi-arid areas is groundwater potential mapping. In this study, four data-mining models including K-nearest neighbor (KNN), linear discriminant analysis (LDA), multivariate adaptive regression splines (MARS), and quadric discriminant analysis (QDA) were used for groundwater potential mapping to get better and more accurate groundwater potential maps (GPMs). For this purpose, 14 groundwater influence factors were considered, such as altitude, slope angle, slope aspect, plan curvature, profile curvature, slope length, topographic wetness index (TWI), stream power index, distance from rivers, river density, distance from faults, fault density, land use, and lithology. From 842 springs in the study area, in the Khalkhal region of Iran, 70 % (589 springs) were considered for training and 30 % (253 springs) were used as a validation dataset. Then, KNN, LDA, MARS, and QDA models were applied in the R statistical software and the results were mapped as GPMs. Finally, the receiver operating characteristics (ROC) curve was implemented to evaluate the performance of the models. According to the results, the area under the curve of ROCs were calculated as 81.4, 80.5, 79.6, and 79.2 % for MARS, QDA, KNN, and LDA, respectively. So, it can be concluded that the performances of KNN and LDA were acceptable and the performances of MARS and QDA were excellent. Also, the results depicted high contribution of altitude, TWI, slope angle, and fault density, while plan curvature and land use were seen to be the least important factors.

Increased irrigation in the Neishaboor watershed, Iran, during the last few decades has caused serious groundwater depletion, making the development of comprehensive mitigation strategies and tools increasingly important. In this study, SWAT and MODFLOW were employed to integratively simulate surface-water and groundwater flows. SWAT and MODFLOW were iteratively executed to compute spatial and temporal distributions of hydrologic components. The combined SWAT-MODFLOW model was calibrated (2000–2010) and validated (2010–2012) based on streamflow, wheat yield, groundwater extraction, and groundwater-level data. This multi-criteria calibration procedure provided greater confidence for the partitioning of water between soil storage, actual evapotranspiration, and aquifer recharge. The SWAT model provided satisfactory predictions of the hydrologic budget for the watershed outlet. It also provided good predictions of irrigated wheat yield and groundwater extraction. The 10-year mean annual recharge rate estimated using the combined model varied greatly, ranging from 0 to 960 mm, with an average of 176 mm. This result showed good agreement with the independently estimated annual recharge rate from an earlier study. The combined model provides a robust tool for the sustainable planning and management of water resources for areas with stressed aquifers where interaction between groundwater and surface water cannot be easily assessed.