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The overall aim of the MEWAC-FEMAR project (Middle East Regional Water Research Cooperation Program – Feasibility of Managed Aquifer Recharge), funded by the German Federal Ministry of Education and Research (BMBF), is to support and enhance a safe and sustainable water supply in the Middle East by Managed Aquifer Recharge (MAR). One target region is Syria, which is facing water insecurity regarding water availability, water supply, and agricultural water needs. In addition, the region is severely affected by war which results in extreme destruction of infrastructure and other resources. The project's objective is to provide a model-based framework for integrated water resources management (IWRM) to identify suitable sites for MAR and to predict their impact on the regional water balance and the local situation. The proposed framework incorporates different methods and model techniques with applications ranging from global to local scales. The model workflow is completely based on open-source tools to ensure sustainable use of the project efforts. Modeling on the global scale is mainly done by data-driven methods like GIS Multi-Criteria Decision Analysis (GIS-MCDA) to answer questions like where are suitable and feasible areas for MAR. Regional scale models aim to describe the hydrological cycle by distributed numerical methods (e.g., MODFLOW-OWHM) to predict and manage MAR under consideration of the regional groundwater situation. Local-scale numerical models can provide detailed and site-specific insights into the flow and transport processes of the unsaturated zone and the underlying aquifer. Specific activities in Syria include e.g., evaluation of wastewater reuse for irrigation. Finally, the current process understanding with regard to MAR methods is critically evaluated and expanded.

Managed aquifer recharge (MAR) is a powerful approach to counteracting the negative impacts of overexploited groundwater resources and enhancing groundwater availability in water-scarce regions. One common MAR strategy is aquifer storage and recovery (ASR). Theoretically, the ASR techniques can be adopted for karst systems to store and recover water within the system or to increase the subsurface inflow into the alluvial system from the adjacent upland karst system. However, karst systems present a particular challenge for the application and technical implementation of ASR, due to the associated strong anisotropy and heterogeneity, high runoff dynamics, as well as the underlying uncertainties regarding the available data.This research is oriented to provide a regional scale model of a karst-alluvial system in Lebanon, analyzing the impact of MAR scenarios as well as quantifying boundary inflow to adjacent alluvial systems. For this reason, several model conceptualizations (considering multi-model concepts) and ASR application scenarios are adopted and tested. For transferability, real-world case studies and idealized yet generalizable systems are considered and assessed. The model pre- and postprocessing is entirely script-based and uses open-source tools to ensure sustainable useAn anisotropic fast-marching algorithm is used to create spatially distributed karst channel networks through the Python package pyKasso. In addition, a discrete continuum model is developed (e.g., CfPy), where the stochastic conduit networks are implemented as a large ensemble of the plausible and representative karstic system. The regional karst alluvial model results are also used to make general recommendations for MAR site selection in the karstic study site.

Characterization of karst systems and forecast of their state variables are essential for groundwater management and engineering in karst regions. These objectives can be met by the use of process-based discrete-continuum models (DCMs). However, results of DCMs may suffer from inversion nonuniqueness. It has been demonstrated that the joint inversion of observations regulated by different natural processes can tackle the nonuniqueness issue in groundwater modeling. However, this has not been tested for DCMs thus far. This research proposes a methodology for the joint inversion of hydro-thermo-chemo-graphs, applying to two small-scale sink-to-spring experiments at Freiheit Spring, Minnesota, USA. In order to address conceptual uncertainty, a multimodel approach was implemented, featuring seven mutually exclusive variants. Spring hydro-thermo-chemo-graphs, for all the variants simulated by MODFLOW-CFPv2, were jointly inverted using a weighted least squares algorithm. Subsequently, models were compared in terms of inversion and forecast performances, as well as parameter uncertainties. Results reveal the suitability of the DCM approach for simultaneous inversion and forecast of hydro-physico-chemical behavior of karst systems, even at a scale of meters and seconds. The estimated volume of the tracer conduit passage ranges from approximately 46–51 m3, which is comparable to the estimate from the flood-pulse method. Moreover, it was demonstrated that the thermograph and hydrograph contain more information about aquifer characteristics than the chemograph. However, this finding can be site-specific and should depend on the analysis scale, the considered conceptual models, and the hydrological state, which are potentially affected by minor unaccountable processes and features.

This upload contains the PEST Model files used for the inverse calibration of the first application of MODFLOW CFPV2 to a Hawaiian aquifer contributing to a potentially pseudo-karstic spring.

Karst aquifers are important sources of fresh water on a global scale. The hydrological modelling of karst spring discharge, however, still poses a challenge. In this study we apply a transfer function noise (TFN) model in combination with a bucket-type recharge model to simulate and predict karst spring discharge. The application of the noise model for the residual series has the advantage that it is more consistent with assumptions for optimization such as homoscedasticity and independence. In an earlier hydrological modeling study, named Karst Modeling Challenge (KMC; Jeannin et al (2021)), several modelling approaches were compared for the Milandre Karst System in Switzerland. This serves as a benchmark and we apply the TFN model to KMC data, subsequently comparing the results to other models. Using different data-model combinations, the most promising data-model combination is identified in a three-step least-squares calibration. To quantify uncertainty, the Bayesian approach of Markov-chain Monte Carlo (MCMC) sampling is subsequently used with uniform priors for the previously identified best data-model combination. The MCMC maximum likelihood solution is used to predict spring discharge for the evaluation period, indicating a superior performance compared to all other models in the KMC. It is found that the model gives a physically feasible representation of the system, which is supported by field measurements. While the TFN model simulated rising limbs and flood recession especially well, medium and baseflow conditions were not represented as accurately. The TFN approach poses a well-performing data-driven grey-box alternative to other approaches that should be considered in future studies.

Despite substantial drought conditions in the karst critical zone (KCZ), the KCZ landscapes are often covered with forest woody plants. However, it is not well understood how these plants balance water supply and demand to survive in such a water-limited environment. This study investigated the water uptake and transpiration relationships of four coexisting woody species in a subtropical karst forest ecosystem using measurements of microclimate, soil moisture, stable isotopes (δ

International audience; The complexity of karst groundwater flow modelling is reflected by the amount of simulation approaches. The goal of the Karst Modelling Challenge (KMC) is comparing different approaches on one single system using the same data set. Thirteen teams with different computational models for simulating discharge variations at karst springs have applied their respective models on one single data set coming from the Milandre Karst Hydrogeological System (MKHS). The approaches include neural networks, reservoir models, semi-distributed models and fully distributed groundwater models. Four and a half years of hourly or daily meteorological input and hourly discharge data were provided for model calibration. The validation comprised forecasting one year of discharge, without the observed discharge data. The model performance was evaluated using the volume conservation, Nash-Sutcliffe efficiency (NSE) and the Kling-Gupta efficiency (KGE) applied on the total discharge and individual flow components. As a result, the comparison of model performances is a challenging task due to the differences in the model architecture but also required time steps: some of the models require aggregated daily steps while others could be run using hourly data, which provided some interesting differences depending on how the data was transformed. The use of instantaneous data (e.g. value at noon) produces less bias that averaging hourly data over one day. The transformation of hourly into daily data produces a decrease of Nash and KGE of 0.05 to 0.08 (i.e. from 1 to ~0.93). The resulting simulations (forecasted values for year 2016) produced KGEs ranging between 0.83 and 0.37 (0.83 to −0.24 for NSE). Although the simulations matched the monitored flows reasonably well, most models struggled to simulate baseflow conditions accurately. In general, the models that performed the best for this exercise were the global ones (Gardenia and Varkarst), with a limited number of parameters, which can be calibrated using automatic calibration procedures. The neural network models also showed a fair potential, with one providing reasonable results despite the relatively short dataset available for warming-up (4.5 years). Semi-and fully distributed models also suggested that with some more effort they could perform well. The accuracy of model predictions does not seem to increase by using models with more than 9–12 calibration parameters. An evaluation of the relative errors between the forecasted and the observed values revealed that for most models, 50% of the forecasted values contained more than 50% of difference against the observed discharge rate, with 25% having a difference larger than 100%. A significant part of the poorly forecasted values corresponded to base-flow which was surprising given that as base-flow is generally much easier to predict than peak flow. Hence, this shows that modelling approaches and criteria for the calibration are too oriented towards peak-flow sections of the hydrographs, and that improvements could be gained by more focus on the base-flow.

Vulnerability assessment is one of the most effective tools for the quality protection of karst aquifers. In the COP method, three essential factors, i.e., karstification process (K), atmospheric conditions (A), and tectonic (T) of the KARSTLOP method, are not considered despite being important factors in karstic aquifer vulnerability. This study aims to develop a new method to obtain the vulnerability map for karst aquifers based on the COP method and the factors used in the KARSTLOP method. The new method, namely COP*KAT, considers K, A, and T factors in the COP method using fuzzy logic. A comparison of microbial and nitrate contamination indices for livestock and agriculture land use, respectively, to the distribution of vulnerability classes for three springs in the study area (Dorfak region, Iran) reveals the more efficient performance of COP*KAT compared to COP in vulnerability analysis.

The locally focused dissolution of the rock material (e.g., below dolines and dry valleys) in karst systems and in general percolating clusters of fractures in consolidated aquifer systems trigger the development of preferential flow paths in the vadose zone. Rainfall events may initiate rapid mass fluxes via macropores and fractures (e.g., as gravitationally-driven films) that lead to source-responsive water table fluctuations and comparably short residence times within the vadose zone. The degree of partitioning into a slow diffuse infiltration component and a rapid localized part depends, amongst others, on the hydraulic interaction of porous matrix and fracture domain as well as the geometrical characteristics of the fracture systems (e.g., persistence, connectivity) that are often difficult to obtain or unknown under most field conditions. Given their importance in water-resource management, specifically in arid and semi-arid regions (e.g., Mediterranean), it is desirable to recover such infiltration dynamics in porous-fractured systems with physically-based yet not overparameterized models. Here, we simulate water table fluctuations in a karst catchment in southwest Germany (Gallusquelle) using a source-responsive film flow model based on borehole and precipitation data. The model takes into account interfacial connectivity between slow and fast domain as well as phreatic zone discharge via classical recession analysis. This case study shows the potential importance of preferential flows while modeling water table responses in karst systems and recognizes the need for formulations other than those applied for a diffuse bulk fractured domain where infiltration patterns are assumed to be homogeneous without formation of infiltration instabilities along preferential pathways.

Voting is one of the important aspects of a democratic society in which people can express their opinions in a formal and legitimate way. In recent years, there has been an increasing interest in electronic voting (e-voting) systems. E-voting is a modern method of vote casting which is based on cryptographic tools. In many proposed scheme, it is a need to have a trusted entity to manage to take the votes and properly counting them. Recently and in the light of pivotal features of blockchain technology including immutability, transparency, and decentralization, blockchain based schemes have received considerable attention. In 2017, J. P. Cruz and Y. Kaji presented a blockchain based e-voting scheme with the help of some cryptographic concepts like bit-commitment and blind signatures. The vital property of their scheme was that it did not use any kind of anonymous channel which is a common and of course hard to implement tool in many e-voting protocols. In this paper, we address some security issues in the mentioned scheme and propose an improved version that has the edge on the prior one in terms of preserving privacy of voters and efficiency when it comes to large scale elections. We show how to use private blockchain instead of a public blockchain to provide more efficiency and privacy. Also, by utilizing proper entities, some security breaches like double voting are nrevented.

The study investigates how topographic and hydrogeological properties influence groundwater dynamics. Using the concept of the fundamental hydrologic landscape (FHL; Winter, 2001), the impact of slope angle, wavelength and amplitude, as well as boundary conditions and hydraulic conductivity on groundwater dynamics is systematically assessed. This type of global sensitivity study has been done for stream flow (e.g. Carlier et al., 2019) or within groundwater focusing solely on groundwater flow and fractions of regional versus local recharge at steady state (e.g. Gleeson and Manning, 2008). In contrast, we study the influence of controls on groundwater level dynamics by using transient models. The coupled, physically based Groundwater and Surface-Water Flow simulator GSFLOW (Markstrom et al., 2008) is employed, to run a set of simulations for a FHL, where topographic and hydrogeological properties are varied across a range of possible value. The model is run at a daily time-step with climate data obtained from a measuring station in Southern Germany. Subsequently, groundwater level time series are read from the model domain across the set of simulations. These time series are decomposed into amplitude, magnitude, timing, flashiness and inter-annual variability by using dynamics indices (Heudorfer et al., 2019). Sensitivity of groundwater dynamics to the different topographic and hydrogeological controls is discussed and contrasted with the results from a prior empirical study (Haaf et al., under review). This type of global sensitivity study may aid understanding hypothesis testing of climate change impacts on groundwater level dynamics. Carlier C, Wirth SB, Cochand F, Hunkeler D, Brunner P. 2019. Exploring Geological and Topographical Controls on Low Flows with Hydrogeological Models. Groundwater, 57: 48-62. DOI: 10.1111/gwat.12845.Gleeson T, Manning AH. 2008. Regional groundwater flow in mountainous terrain: Three-dimensional simulations of topographic and hydrogeologic controls. Water Resources Research, 44. DOI:10.1029/2008wr006848.Haaf E, Giese M, Heudorfer B, Stahl K, Barthel R. Physiographic and climatic controls on groundwater dynamics on the regional scale. (under review).Heudorfer B, Haaf E, Stahl K, Barthel R. 2019. Index-Based Characterization and Quantification of Groundwater Dynamics. Water Resources Research, 55: 5575-5592. DOI: 10.1029/2018wr024418.Markstrom SL, Niswonger RG, Regan RS, Prudic DE, Barlow, PM. 2008. GSFLOW-Coupled Ground-water and Surface-water FLOW model based on the integration of the Precipitation-Runoff Modeling System (PRMS) and the Modular Ground-Water Flow Model (MODFLOW-2005): U.S. Geological Survey Techniques and Methods 6-D1, 240 p.Winter TC. 2001. The concept of hydrologic landscapes. Journal of the American Water Resources Association, 37: 335-349. DOI: DOI 10.1111/j.1752-1688.2001.tb00973.x.

Determination of recharge from precipitation and its distribution in karst areas is of great importance in water budget calculations. Several multi-parameter weighting-rating methods have been proposed to determine the recharge into karst aquifers; one of the most precise methods used in this field is the KARSTLOP. It is always necessary that the weight of recharge estimation method becomes calibrated by new techniques due to the diversity conditions of each area. Therefore, in this study, the analytical hierarchy process (AHP) technique has been used as a powerful decision-helping subjective tool. Using this method, the weights of the original KARSTLOP method were modified and improved based on the comments from water experts in the area. The mean annual recharge in the study area was 27.5% and 34.5% for the KARSTLOP-AHO and KARSTLOP methods, respectively. The results of KARSTLOP–AHP method are in accordance with the discharge of selected springs in the study area and budget reports.

This research presents the first application of a distributed discrete-continuum numerical model for simultaneous inversion of long-term spring flow in conjunction with solute- and heat-transport signatures, in a large-scale karst system. The MODFLOW-2005 CFPv2 code was adopted for this reason, utilizing PEST for automated inversion. Taking the principal of model parsimony into account, simulations were performed at two stages, testing likely conceptual models based on the hydro-geological understandings. At the first stage, simple yet realistic conceptual models were setup considering different probable variants of conduit geometries. Results of this stage highlights the importance of sinkhole-spring dynamics, in the recorded spring signatures; such that, successful simultaneous calibration of all spring signatures could not be obtained unless high linkage of conduits to the sinkholes all over the catchment was adopted. Subsequently, some additional rational complexity was added in order to achieve a more demonstrable model of the karst system, as the second stage. Model selection criteria, fitting statistics and reasonableness of calibrated parameters were assessed, at this stage. Although one of the model variants could statistically represent all observations with reasonable parameter values and high agreement with catchment hydrogeological perspective, it still cannot be approved as a predictive tool, unless field measurements on conduit system characteristics and matrix hydraulic parameters, as well as long-term observation of aquifer physicochemical signatures be collected for further validation/improvement of conceptual and numerical model. Achieved simultaneous inversion results can serve as a proof of concept for applicability of physically based discrete-continuum modeling approach for flow and transport modeling in karst.

Groundwater is inevitable for agricultural production in the Indus Basin of Pakistan. Its management on sustainable basis is only possible by careful appraisal of its recharge potential and dynamics. This study aimed at exploring pixel-based groundwater recharge at 1 km2 spatial resolution using remote sensing data through water balance method. Moreover, spatially distributed groundwater abstractions are estimated by new approach with the aid of remote sensing data and results are compared with the conventional utilization factor method. Groundwater abstraction estimation from conventional utilization factor method overstates results both for kharif and rabi cropping seasons. Recharge results obtained from water balance method and water table fluctuation approach are comparable both at irrigation subdivision and 1 km2 spatial scales. During the kharif cropping seasons, rainfall is the main source of recharge followed by field percolation losses while for rabi cropping seasons, canal seepage remains the major source. Net groundwater recharge is mainly positive during all kharif seasons. A gradual increase in groundwater level is observed in major parts of the study area. Improvement in results from water table fluctuation method is possible by better distribution and increased intensity of piezometers while for water balance approach, it is possible by adopting alternative buffer zones for canal seepage. Detailed sensitivity and uncertainty analyses of input/output variables are needed to present the results with confidence interval and hence to support sustainable and economical operation of irrigation system.

Dissolution of evaporite formations, emergence of salty water springs, and intrusion of deep saline waters are important causes in changing the quality of surface water. The study area is part of the reservoir and downstream of Chamshir Dam, which is located in watershed of the Zohreh River 20 km southeast of Gachsaran City (southwest Iran). To construct powerhouse and related structures for supplying water to agricultural lands located in downstream of dam, water quality of Zohreh River was studied by eight sampling stations in the study area. Early studies showed that water quality of the Zohreh River decreases severely downstream of the Chamshir Dam. Spatial variations diagram of major ions, Piper and composition diagrams of water samples in selected stations mark the presence of two slight and major contaminating zones at sampling station R4 and R5. In these zones, concentration of Ca, SO4 and Na, Cl ions increase suddenly. Results of hydrogeological, hydrochemical, lithological and tectonics studies showed that even though there are several low discharges springs in the contaminated zone they cannot be related to surface dissolution of evaporate layers by Zohreh River. There is an important fault zone including Chamshir faults I and II in the contamination zones through which intrusion of sulfate brackish and chloride brine waters occur along the fault zone and then enter Zohreh River below its base level. In the absence of any surface evidence, the fault zone is the main cause of salinity. Evaluation of water balance salinity in contaminated zones shows that the discharge rate of saline waters to the river is not low and cannot be separated. These findings show that there are serious restrictions upon the purposes of the project.