Integrated Hydrological Modeling of Climate Change Impacts in a Snow-Influenced Catchment

The potential impact of climate change on water resources has been intensively studied for different regions and climates across the world. In regions where winter processes such as snowfall and melting play a significant role, anticipated changes in temperature might significantly affect hydrological systems. To address this impact, modifications have been made to the fully integrated surface-subsurface flow model HydroGeoSphere (HGS) to allow the simulation of snow accumulation and melting. The modified HGS model was used to assess the potential impact of climate change on surface and subsurface flow in the Saint-Charles River catchment, Quebec (Canada) for the period 2070 to 2100. The model was first developed and calibrated to reproduce observed streamflow and hydraulic heads for current climate conditions. The calibrated model was then used with three different climate scenarios to simulate surface flow and groundwater dynamics for the 2070 to 2100 period. Winter stream discharges are predicted to increase by about 80, 120, and 150% for the three scenarios due to warmer winters, leading to more liquid precipitation and more snowmelt. Conversely, the summer stream discharges are predicted to fall by about 10, 15, and 20% due to an increase in evapotranspiration. However, the annual mean stream discharge should remain stable (±0.1 m³/s). The predicted increase in hydraulic heads in winter may reach 15 m and the maximum decrease in summer may reach 3 m. Simulations show that winter processes play a key role in the seasonal modifications anticipated for surface and subsurface flow dynamics.     

A COMSOL-PHREEQC Coupled Python Framework for Reactive Transport Modeling in Soil and Groundwater

The CPqPy framework coupling COMSOL and PHREEQC based on Python was developed. This framework can achieve the simulation of diversified situations including multi-physics coupling and geochemical reactions of soil and groundwater. The multi-physics coupling models are calculated in COMSOL, whereas PHREEQC was applied to calculate the geochemical models through the Phreeqpy library in Python. Feasibility and accuracy of CPqPy were verified and applied to two cases, including a solute transport model considering equilibrium reaction and ion exchange as well as a reactive transport model of a variable saturation soil considering kinetic reaction. The results show a high degree of credibility of CPqPy. The framework has the advantages of strong portability, and it can be further used in conjunction with multiple Python calculation libraries, which greatly extends the application of the reactive transport model.     

Indications of Changing Solar Activity and North Atlantic Sea Surface Temperature in Fennoscandian Climate

Geomagnetism and Aeronomy - Solar-climatic correlations were examined over the timescales, corresponding to solar cycles of Schwabe, Hale and Gleissberg, during the last 3–4 centuries using...     

On the Forecast of Long-Term Changes in the Hydrological Regime of Rivers Using the Results of Climate Modeling

Water Resources - A method is proposed for probabilistic forecasting of river flow under non-stationary conditions based on the Bayesian approach and using the results of climatic system modeling....     

Groundwater Quality Modeling with a Small Data Set

Seventeen groundwater quality variables collected during an 8‐year period (2006 to 2013) in Andimeshk, Iran, were used to implement an artificial neural network (NN) with the purpose of constructing a water quality index (WQI). The method leading to the WQI avoids instabilities and overparameterization, two problems common when working with relatively small data sets. The groundwater quality variables used to construct the WQI were selected based on principal component analysis (PCA) by which the number of variables were decreased to six. To fulfill the goals of this study, the performance of three methods (1) bootstrap aggregation with early stopping; (2) noise injection; and (3) ensemble averaging with early stopping was compared. The criteria used for performance analysis was based on mean squared error (MSE) and coefficient of determination (R²) of the test data set and the correlation coefficients between WQI targets and NN predictions. This study confirmed the importance of PCA for variable selection and dimensionality reduction to reduce the risk of overfitting. Ensemble averaging with early stopping proved to be the best performed method. Owing to its high coefficient of determination (R² = 0.80) and correlation coefficient (r=0.91), we recommended ensemble averaging with early stopping as an accurate NN modeling procedure for water quality prediction in similar studies.     

Effects of Density and Viscosity in Modeling Heat as a Groundwater Tracer

Decoupled simulation of groundwater flow and heat transport assuming constant fluid density and viscosity is computationally efficient and simple. However, by neglecting the effects of variable density and viscosity, numerical solution of heat transport may be inaccurate. This study investigates the conditions under which the density and viscosity effects on heat transport modeling can be neglected without any significant loss of computational accuracy. A cross-section model of aquifer-river interactions at the Hanford 300 Area in Washington State was employed as the reference frame to quantify the role of fluid density and viscosity in heat transport modeling. This was achieved by comparing the differences in simulated temperature distributions with and without considering variable density and viscosity, respectively. The differences between the two sets of simulations were found to be minor under the complex field conditions at the Hanford 300A site. Based on the same model setup but under different prescribed temperature gradients across the simulation domain, a series of heat transport scenarios were further examined. When the maximum temperature difference across the simulation domain is within 15°C, the mean discrepancy between the simulated temperature distributions with and without considering the effects of variable density and viscosity is approximately 2.5% with a correlation coefficient of above 0.8. Meanwhile, the speedup in runtime is roughly 225% when the maximum temperature difference is at 15°C. This work provides some quantitative guidelines for when heat transport may be simulated by assuming constant density and viscosity as a reasonable compromise between accuracy and efficiency.     

A Coupled Groundwater–Surface Water Modeling Framework for Simulating Transition Zone Processes

There is an identified need for fully representing groundwater–surface water transition zone (i.e., the sediment zone that connects groundwater and surface water) processes in modeling fate and transport of contaminants to assist with management of contaminated sediments. Most existing groundwater and surface water fate and transport models are not dynamically linked and do not consider transition zone processes such as bioturbation and deposition and erosion of sediments. An interface module is developed herein to holistically simulate the fate and transport by coupling two commonly used models, Environmental Fluid Dynamics Code (EFDC) and SEAWAT, to simulate surface water and groundwater hydrodynamics, while providing an enhanced representation of the processes in the transition zone. Transition zone and surface water contaminant processes were represented through an enhanced version of the EFDC model, AQFATE. AQFATE also includes SEDZLJ, a state‐of‐the‐science surface water sediment transport model. The modeling framework was tested on a published test problem and applied to evaluate field‐scale two‐ and three‐dimensional contaminant transport. The model accurately simulated concentrations of salinity from a published test case. For the field‐scale applications, the model showed excellent mass balance closure for the transition zone and provided accurate simulations of all transition zone processes represented in the modeling framework. The model predictions for the two‐dimensional field case were consistent with site‐specific observations of contaminant migration. This modeling framework represents advancement in the simulation of transition zone processes and can help inform risk assessment at sites where contaminant sources from upland areas have the potential to impact sediments and surface water.     

Using a Cloud to Replenish Parched Groundwater Modeling Efforts

Groundwater models can be improved by introduction of additional parameter flexibility and simultaneous use of soft-knowledge. However, these sophisticated approaches have high computational requirements. Cloud computing provides unprecedented access to computing power via the Internet to facilitate the use of these techniques. A modeler can create, launch, and terminate “virtual” computers as needed, paying by the hour, and save machine images for future use. Such cost-effective and flexible computing power empowers groundwater modelers to routinely perform model calibration and uncertainty analysis in ways not previously possible.     

Simulating the Effect of Climate Extremes on Groundwater Flow Through a Lakebed

Groundwater exchanges with lakes resulting from cyclical wet and dry climate extremes maintain lake levels in the environment in ways that are not well understood, in part because they remain difficult to simulate. To better understand the atypical groundwater interactions with lakes caused by climatic extremes, an original conceptual approach is introduced using MODFLOW‐2005 and a kinematic‐wave approximation to variably saturated flow that allows lake size and position in the basin to change while accurately representing the daily lake volume and three‐dimensional variably saturated groundwater flow responses in the basin. Daily groundwater interactions are simulated for a calibrated lake basin in Florida over a decade that included historic wet and dry departures from the average rainfall. The divergent climate extremes subjected nearly 70% of the maximum lakebed area and 75% of the maximum shoreline perimeter to both groundwater inflow and lake leakage. About half of the lakebed area subject to flow reversals also went dry. A flow‐through pattern present for 73% of the decade caused net leakage from the lake 80% of the time. Runoff from the saturated lake margin offset the groundwater deficit only about half of that time. A centripetal flow pattern present for 6% of the decade was important for maintaining the lake stage and generated 30% of all net groundwater inflow. Pumping effects superimposed on dry climate extremes induced the least frequent but most cautionary flow pattern with leakage from over 90% of the actual lakebed area.     

The Value of Groundwater Modeling to Support a Pump and Treat Design

A wide range of rules, algorithms, and models are available to design an effective pump and treat remediation system. Often, one refers to the effectiveness of the developed pump and treat system to demonstrate how valuable the use of a groundwater model can be. An economic valuation of the groundwater model is usually missing. This study provides a framework that puts the discussion concerning the use of groundwater models in an economic perspective. It is not only demonstrated that a more effective pump and treat system can be designed using a groundwater model, but also the economic implications of using a groundwater model are calculated. A set of economic decision rules is applied to determine the economic value of a groundwater model. It is shown that investing in a groundwater model can be economically worthwhile. The remediation time is reduced, remediation costs are saved and the property can be sold more early. These benefits outweigh the costs of developing a groundwater model, and hence a positive net benefit (NB) is determined.     

Importance of Spatial Resolution in Global Groundwater Modeling

Global-scale gradient-based groundwater models are a new endeavor for hydrologists who wish to improve global hydrological models (GHMs). In particular, the integration of such groundwater models into GHMs improves the simulation of water flows between surface water and groundwater and of capillary rise and thus evapotranspiration. Currently, these models are not able to simulate water table depth adequately over the entire globe. Unsatisfactory model performance compared to well observations suggests that a higher spatial resolution is required to better represent the high spatial variability of land surface and groundwater elevations. In this study, we use New Zealand as a testbed and analyze the impacts of spatial resolution on the results of global groundwater models. Steady-state hydraulic heads simulated by two versions of the global groundwater model G³M, at spatial resolutions of 5 arc-minutes (9 km) and 30 arc-seconds (900 m), are compared with observations from the Canterbury region. The output of three other groundwater models with different spatial resolutions is analyzed as well. Considering the spatial distribution of residuals, general patterns of unsatisfactory model performance remain at the higher resolutions, suggesting that an increase in model resolution alone does not fix problems such as the systematic overestimation of hydraulic head. We conclude that (1) a new understanding of how low-resolution global groundwater models can be evaluated is required, and (2) merely increasing the spatial resolution of global-scale groundwater models will not improve the simulation of the global freshwater system.     

Enhancing Groundwater Remediation in Air Sparging by Changing the Pulse Duration

An important operation parameter in the design of a pulsed air sparging (PAS) system is the pulse duration (PD). To study the effect of the PD on the remediation process, a series of laboratory experiments and numerical simulations were performed. The experimental apparatus was a cylindrical tank, packed with fine sand and partially filled by water contaminated with toluene. Toluene concentrations in water and in effluent air were measured over time during the application of PAS, which was applied with three different PD. Next, the T2VOC model, an extension of the TOUGH2 simulation program, was used to simulate the two-phase flow and transport processes for these cases. The simulation model was calibrated to the experimental results, and then run with a range of PD values. Results showed that there exists an optimal PD which yields the highest remediation efficiency. Next, it was shown that this PD may be obtained by performing a PAS pilot test and measuring the groundwater pressure response in a monitoring well. The characteristic time which describes the exponential decay of the pressure response was shown to provide an adequate estimate for the optimal PD. The estimation improved by taking a number of injection cycles.     

Stochastic Modeling of Groundwater Extractions over a Data-Sparse Region of Australia

Setting limit on groundwater extractions is important to ensure sustainable groundwater management. Lack of extraction data can affect interpretations of historical pressure changes, predictions of future impacts, accuracy of groundwater model calibration, and identification of sustainable management options. Yet, many groundwater extractions are unmetered. Therefore, there is a need for models that estimate extraction rates and quantify model outputs uncertainties arising due to a lack of data. This paper develops such a model within the Generalized Linear Modeling (GLM) framework, using a case study of stock and domestic (SD) extractions in the Surat Cumulative Management Area, a predominantly cattle farming region in eastern Australia. Various types of extraction observations were used, ranging from metering to analytically-derived estimates. GLMs were developed and applied to estimate the property-level extraction amounts, where observation types were weighted by perceived relative accuracy, and well usage status. The primary variables found to affect property-level extraction rates were: yearly average temperature and rainfall, pasture, property area, and number of active wells; while variables most affecting well usage were well water electrical conductivity, spatial coordinates, and well age. Results were compared with analytical estimates of property-level extraction, illustrating uncertainties and potential biases across 20 hydrogeological units. Spatial patterns of mean extraction rates (and standard deviations) are presented. It is concluded that GLMs are well suited to the problem of extraction rate estimation and uncertainty analysis, and are ideal when model verification is supported by measurement of a random sample of properties.     

Transient and Transition Factors in Modeling Permafrost Thaw and Groundwater Flow

Permafrost covers approximately 24% of the Northern Hemisphere, and much of it is degrading, which causes infrastructure failures and ecosystem transitions. Understanding groundwater and heat flow processes in permafrost environments is challenging due to spatially and temporarily varying hydraulic connections between water above and below the near-surface discontinuous frozen zone. To characterize the transitional period of permafrost degradation, a three-dimensional model of a permafrost plateau that includes the supra-permafrost zone and surrounding wetlands was developed. The model is based on the Scotty Creek basin in the Northwest Territories, Canada. FEFLOW groundwater flow and heat transport modeling software is used in conjunction with the piFreeze plug-in, to account for phase changes between ice and water. The Simultaneous Heat and Water (SHAW) flow model is used to calculate ground temperatures and surface water balance, which are then used as FEFLOW boundary conditions. As simulating actual permafrost evolution would require hundreds of years of climate variations over an evolving landscape, whose geomorphic features are unknown, methodologies for developing permafrost initial conditions for transient simulations were investigated. It was found that a model initialized with a transient spin-up methodology, that includes an unfrozen layer between the permafrost table and ground surface, yields better results than with steady-state permafrost initial conditions. This study also demonstrates the critical role that variations in land surface and permafrost table microtopography, along with talik development, play in permafrost degradation. Modeling permafrost dynamics will allow for the testing of remedial measures to stabilize permafrost in high value infrastructure environments.     

Effects of the Land Use and Check Dams on Flood in Upper Catchment of Fuping Hydrological Station by Hydrological Modeling

Flood peaks and volumes had been detected a downward trend in Fuping hydrological station. To quantify the effects of check dams on flood peaks and volumes, a hydrological model integrating land use was established. The model performed well in flood processes simulation, and the Nash efficiency of the model was 0.72. Then the model was used to identify the comprehensive effects of land use and land cover change on flood processes by comparing the simulation results of the selected flood events under 1980 and 2000 land use and land cover conditions. 24.5, 37.7 and 51.3% decrease in flood peaks for flood events of greater than 10 years, 5~10 years and less than 5 years return periods, respectively, and 16.3, 27.9 and 28.5% decrease in flood volumes for the three groups flood events of different return periods. Contributions of land use change and check dams to decrease in flood peak and volume were simulated, and it was found that peak discharge and volume for each flood event responded differently to the two factors. The results in this study can provide valuable information on design flood calculation in the basin under land use and land cover change.     

Distributed Parallel Computing in Stochastic Modeling of Groundwater Systems

Stochastic modeling is a rapidly evolving, popular approach to the study of the uncertainty and heterogeneity of groundwater systems. However, the use of Monte Carlo‐type simulations to solve practical groundwater problems often encounters computational bottlenecks that hinder the acquisition of meaningful results. To improve the computational efficiency, a system that combines stochastic model generation with MODFLOW‐related programs and distributed parallel processing is investigated. The distributed computing framework, called the Java Parallel Processing Framework, is integrated into the system to allow the batch processing of stochastic models in distributed and parallel systems. As an example, the system is applied to the stochastic delineation of well capture zones in the Pinggu Basin in Beijing. Through the use of 50 processing threads on a cluster with 10 multicore nodes, the execution times of 500 realizations are reduced to 3% compared with those of a serial execution. Through this application, the system demonstrates its potential in solving difficult computational problems in practical stochastic modeling.     

Accelerating Streamline Tracking in Groundwater Flow Modeling on GPUs

Streamline simulation in groundwater flow modeling is a time-consuming process when a large number of streamlines are analyzed. We develop a parallelization method on graphics processing units (GPUs) for the semi-analytical particle tracking algorithm developed by Pollock (1988). Compute Unified Device Architecture was used to implement the parallel method. Forward and backward tracking of a streamline is handled by an individual thread. A GPU includes a grid of blocks where a block handles 32 threads. We use multi-GPUs to accelerate streamline tracking in a flow model with millions of particles. The method was examined to simulate streamlines for identifying three-dimensional (3D) flow systems in a Tóthian basin. The speedup exceeds 1000 when 8 NVIDIA GPUs are used to simulate 5 million or more streamlines.     

Modeling the Factors Impacting Pesticide Concentrations in Groundwater Wells

This study examines the effect of pumping, hydrogeology, and pesticide characteristics on pesticide concentrations in production wells using a reactive transport model in two conceptual hydrogeologic systems; a layered aquifer with and without a stream present. The pumping rate can significantly affect the pesticide breakthrough time and maximum concentration at the well. The effect of the pumping rate on the pesticide concentration depends on the hydrogeology of the aquifer; in a layered aquifer, a high pumping rate resulted in a considerably different breakthrough than a low pumping rate, while in an aquifer with a stream the effect of the pumping rate was insignificant. Pesticide application history and properties have also a great impact on the effect of the pumping rate on the concentration at the well. The findings of the study show that variable pumping rates can generate temporal variability in the concentration at the well, which helps understanding the results of groundwater monitoring programs. The results are used to provide guidance on the design of pumping and regulatory changes for the long‐term supply of safe groundwater. The fate of selected pesticides is examined, for example, if the application of bentazone in a region with a layered aquifer stops today, the concentration at the well can continue to increase for 20 years if a low pumping rate is applied. This study concludes that because of the rapid response of the pesticide concentration at the drinking water well due to changes in pumping, wellhead management is important for managing pesticide concentrations.     

东亚季风的气候变化及其时间序列模型

本文运用统计方法分析了东亚季风指数的观测序列;同时还揭示了不同时期的东亚季风变化趋势和年代际变化.自1873年以来,东亚季风逐渐减少,同时年代际的变化也十分明显.在1891-1900年间和1971-1980年间,夏季季风指数的十年平均达到极大,另外还出现两个极小值,它们分别出现在1921-1930年和1991-2000年.为了对东亚季风变化进行模拟,我们首先简要地介绍了动力系统的自忆性原理,然后叙述了一个新的时间序列分析方法——基于数据的机制自记忆模型(DAMSM).DAMSM被应用于东亚季风指数研究并且证明了它对东亚季风的拟合及预报能力.