Stochastic Approach In Groundwater Modeling: A Case Study Of The Buffalo Creek Watershed

Simulation and prediction of groundwater flow and solute (contaminant) transport highly depends upon aquifer parameters and their spatial distribution. Since this variability in space is in fact random, solutions for groundwater flow and contaminants transport are better defined through a statistical approach. This study acknowledges and considers spatial variability of horizontal hydraulic conductivity values and compares calibrated steady-state condition groundwater flow both in deterministic and stochastic approach using MODFLOW model. Based upon the discretized model, for each model run 10, 495 different horizontal hydraulic conductivity values (set) were generated using Kriging statistical distribution method and results of groundwater depth was compared with measured depth, R2 value equal to 0.7471. Seven of the eight (87 %) sets of hydraulic conductivity values ranging from 10-3 m/second to 10-7 m/second generated less error than the deterministic approach. Similarly, using the calibrated parameter, contaminant plume path has also been defined using MT3D model, with five of the eight (62 %) sets of spatially varied hydraulic conductivity values generating less error than the deterministic value for solute mass balance. Potential groundwater paths were also determined and indicated using velocity vectors calculated by MODPATH model. Moreover, contaminant plume propagation in flat slope regions of the watershed showed little advance towards the predefined exits. Rather, higher concentration contours were observed in a limited area, indicating potentially polluted regions of the watershed in shallow aquifer zones that include South Buffalo wetland. Out of the total annual base flow, about 3 %, with expected rise during dry seasons, is contributed by impaired streams through groundwater-stream flow exchange

Stochastic Approach In Groundwater Modeling: A Case Study Of The Buffalo Creek Watershed

Simulation and prediction of groundwater flow and solute (contaminant) transport highly depends upon aquifer parameters and their spatial distribution. Since this variability in space is in fact random, solutions for groundwater flow and contaminants transport are better defined through a statistical approach. This study acknowledges and considers spatial variability of horizontal hydraulic conductivity values and compares calibrated steady-state condition groundwater flow both in deterministic and stochastic approach using MODFLOW model. Based upon the discretized model, for each model run 10, 495 different horizontal hydraulic conductivity values (set) were generated using Kriging statistical distribution method and results of groundwater depth was compared with measured depth, R2 value equal to 0.7471. Seven of the eight (87 %) sets of hydraulic conductivity values ranging from 10-3 m/second to 10-7 m/second generated less error than the deterministic approach. Similarly, using the calibrated parameter, contaminant plume path has also been defined using MT3D model, with five of the eight (62 %) sets of spatially varied hydraulic conductivity values generating less error than the deterministic value for solute mass balance. Potential groundwater paths were also determined and indicated using velocity vectors calculated by MODPATH model. Moreover, contaminant plume propagation in flat slope regions of the watershed showed little advance towards the predefined exits. Rather, higher concentration contours were observed in a limited area, indicating potentially polluted regions of the watershed in shallow aquifer zones that include South Buffalo wetland. Out of the total annual base flow, about 3 %, with expected rise during dry seasons, is contributed by impaired streams through groundwater-stream flow exchange

Uncertainty Assessment of Hydrogeological Models Based on Information Theory

There is a great deal of uncertainty in hydrogeological modeling. Overparametrized models increase uncertainty since the information of the observations is distributed through all of the parameters. The present study proposes a new option to reduce this uncertainty. A way to achieve this goal is to select a model which provides good performance with as few calibrated parameters as possible (parsimonious model) and to calibrate it using many sources of information. Akaike’s Information Criterion (AIC), proposed by Hirotugu Akaike in 1973, is a statistic-probabilistic criterion based on the Information Theory, which allows us to select a parsimonious model. AIC formulates the problem of parsimonious model selection as an optimization problem across a set of proposed conceptual models. The AIC assessment is relatively new in groundwater modeling and it presents a challenge to apply it with different sources of observations. In this dissertation, important findings in the application of AIC in hydrogeological modeling using different sources of observations are discussed. AIC is tested on ground-water models using three sets of synthetic data: hydraulic pressure, horizontal hydraulic conductivity, and tracer concentration. In the present study, the impact of the following factors is analyzed: number of observations, types of observations and order of calibrated parameters. These analyses reveal not only that the number of observations determine how complex a model can be but also that its diversity allows for further complexity in the parsimonious model. However, a truly parsimonious model was only achieved when the order of calibrated parameters was properly considered. This means that parameters which provide bigger improvements in model fit should be considered first. The approach to obtain a parsimonious model applying AIC with different types of information was successfully applied to an unbiased lysimeter model using two different types of real data: evapotranspiration and seepage water. With this additional independent model assessment it was possible to underpin the general validity of this AIC approach.Hydrogeologische Modellierung ist von erheblicher Unsicherheit geprägt. Überparametrisierte Modelle erhöhen die Unsicherheit, da gemessene Informationen auf alle Parameter verteilt sind. Die vorliegende Arbeit schlägt einen neuen Ansatz vor, um diese Unsicherheit zu reduzieren. Eine Möglichkeit, um dieses Ziel zu erreichen, besteht darin, ein Modell auszuwählen, das ein gutes Ergebnis mit möglichst wenigen Parametern liefert („parsimonious model“), und es zu kalibrieren, indem viele Informationsquellen genutzt werden. Das 1973 von Hirotugu Akaike vorgeschlagene Informationskriterium, bekannt als Akaike-Informationskriterium (engl. Akaike’s Information Criterion; AIC), ist ein statistisches Wahrscheinlichkeitskriterium basierend auf der Informationstheorie, welches die Auswahl eines Modells mit möglichst wenigen Parametern erlaubt. AIC formuliert das Problem der Entscheidung für ein gering parametrisiertes Modell als ein modellübergreifendes Optimierungsproblem. Die Anwendung von AIC in der Grundwassermodellierung ist relativ neu und stellt eine Herausforderung in der Anwendung verschiedener Messquellen dar. In der vorliegenden Dissertation werden maßgebliche Forschungsergebnisse in der Anwendung des AIC in hydrogeologischer Modellierung unter Anwendung unterschiedlicher Messquellen diskutiert. AIC wird an Grundwassermodellen getestet, bei denen drei synthetische Datensätze angewendet werden: Wasserstand, horizontale hydraulische Leitfähigkeit und Tracer-Konzentration. Die vorliegende Arbeit analysiert den Einfluss folgender Faktoren: Anzahl der Messungen, Arten der Messungen und Reihenfolge der kalibrierten Parameter. Diese Analysen machen nicht nur deutlich, dass die Anzahl der gemessenen Parameter die Komplexität eines Modells bestimmt, sondern auch, dass seine Diversität weitere Komplexität für gering parametrisierte Modelle erlaubt. Allerdings konnte ein solches Modell nur erreicht werden, wenn eine bestimmte Reihenfolge der kalibrierten Parameter berücksichtigt wurde. Folglich sollten zuerst jene Parameter in Betracht gezogen werden, die deutliche Verbesserungen in der Modellanpassung liefern. Der Ansatz, ein gering parametrisiertes Modell durch die Anwendung des AIC mit unterschiedlichen Informationsarten zu erhalten, wurde erfolgreich auf einen Lysimeterstandort übertragen. Dabei wurden zwei unterschiedliche reale Messwertarten genutzt: Evapotranspiration und Sickerwasser. Mit Hilfe dieser weiteren, unabhängigen Modellbewertung konnte die Gültigkeit dieses AIC-Ansatzes gezeigt werden

2D finite volume model for groundwater flow simulations : integrating non-orthogonal grid capability into modflow

The modular finite-difference groundwater flow model MODFLOW is one of the most widely used groundwater modelling programs, and is applicable to most types of flow problems in its field. However, its finite difference formulation decreases its ability to simulate accurately natural aquifer geometries. To enhance its capability in simulating such boundaries, a finite volume scheme has been developed for inclusion in MODFLOW. In this study, the two-dimensional formulation has been considered. Three discretisations of the two-dimensional diffusion equation, governing groundwater flow and for use with structured quadrilateral meshes, have been developed. The three methods rely on a cell-centred finite volume approach, but show distinct differences in the choice of: gradient approximation, head interpolations and control volume. A time implicit formulation has been used in each model. The sparse system of linear equations that result from the implicit formulation has been solved by using an iterative solver, based on the strongly implicit procedure. Five test examples have been undertaken to compare the performance of the newly developed methods against MODFLOW predictions and analytical results. The accuracy of the results obtained was found to depend on the spatial and temporal discretisations. One of the three developed methods proved its robustness, with regard to mesh non-orthogonality and skewness, and was called the GWFV method. In a second step of studies, a field case study was used to test the preferred model. A mesh generator using a structured quadrilateral grid was used to produce the finite volume mesh of the simulated area. The results of MODFLOW and the GWFV model simulations were compared against field observations. A discussion about the performance of the new developed model has been included and the model has been shown to perform well in comparison with MODFLOW. Keywords: numerical models, finite volume discretisations, groundwater flow models, MODFLOW, non-orthogonal grid

Nitrogen transformation and retention in riparian buffer zones

Diffuse pollution of nutrients and pesticides from agricultural areas is increasingly recognised as a major problem in water management. Ecotechnological measures as constructed wetlands and riparian buffer zones clearly have an important role in the reduction of diffuse pollution by removing and modifying pollutants from agricultural runoff. However the processes that account for the pollution retention capacity are diverse and the performance of buffer zones along climatic gradients and under varying hydrological regimes is largely unknown. This study was conducted to determine the influence of N-loading rate, vegetation and hydrologic regime on the mechanisms of nitrogen removal in riparian zones along a climatic gradient.The research was performed in several locations across Europe within the framework of a joint research project (NItrogen COntrol by LAndscape Structures in agricultural environments). Partners in this project were researchers from The Netherlands, France, England, Spain, Switserland, Romania and Poland. In the European buffer zones, denitrification was identified as the dominant process of N removal, denitrification is however also considered as a major source of the greenhouse gas nitrous oxide (N2O). Higher rates of N2O emissions found in the Dutch forested buffer zone were associated with higher nitrate concentrations in the groundwater. We conclude that N transformation by N-loaded buffer zones results in a significant increase of greenhouse gas emission. Until now, only the beneficial function of wetlands on water quality improvement has received a lot of attention. To perform a full assessment, however, we have to evaluate the precise consequences of both forms of environmental pollution to determine the environmental risks. Overall, no significant effect of climate has been observed in measurements of N removal efficiency in a range of European sites. However, N transformation proceses rates were strongly related to water table level. Three consistent water table thresholds were identified. When water table levels are within -10 cm of the soil surface, ammonification prevailed and ammonium accumulated in the topsoil. Average groundwater tables between -10 and -30 cm favor denitrification and therefore reduce the nitrogen availability in soils. At sites with water table levels below -30 cm, nitrate is the main end product as a result of high net nitrification. Tracing the groundwater flow paths in the Dutch riparian zones revealed that dilution of agricultural runoff with groundwater from a deeper aquifer caused a significant decrease in nitrate concentrations which could cause an over-estimation of the N-removal capacity of upto 60%. Besides the dilution both Dutch riparian zones were capable of reducing nitrate in subsurface runoff by biological N removal, the grassland riparian zone as a whole removed about 63% of the incoming nitrate load whereas in the more heavily loaded forested zone clear symptoms of saturation were visible and only 38% of the incoming nitrate load was removed. Riparian zones are highly valuable landscape elements from the perspective of water quality improvement and landscape connectivity, however in N-loaded systems a certain risk of N2O emission remains inevitable, still we support the general belief that riparian buffer need to be protected, restored or re-established

World Multidisciplinary Civil Engineering- Architecture- Urban Planning symposium

We would like to express our sincere gratitude to all 900+ submissions by 600+ participants of WMCAUS 2018 from 60+ different countries all over the world for their interests and contributions in WMCAUS 2018. We wish you enjoy the World Multidisciplinary Civil Engineering-Architecture-Urban Planning Symposium – WMCAUS 2018 and have a pleasant stay in the city of romance Prague. We hope to see you again during next event WMCAUS 2019 which will be held in Prague (Czech Republic) approximately in the similar period