George Kourakos

Agriculture's Contribution to Nitrate Contamination of Californian Groundwater (1945-2005).

Nitrogen (N) use in intensive agriculture can degrade groundwater resources. However, considerable time lags between groundwater recharge and extraction complicate source attribution and remedial responses. We construct a historic N mass balance of two agricultural regions of California to understand trends and drivers of past and present N loading to groundwater (1945-2005). Changes in groundwater N loading result from historic changes in three factors: the extent of agriculture (cropland area and livestock herd increased 120 and 800%, respectively), the intensity of agriculture (synthetic and manure waste effluent N input rates increased by 525 and 1500%, respectively), and the efficiency of agriculture (crop and milk production per unit of N input increased by 25 and 19%, respectively). The net consequence has been a greater-than-order-of-magnitude increase in nitrate (NO) loading over the time period, with 163 Gg N yr now being leached to groundwater from approximately 1.3 million ha of farmland (not including alfalfa [ L.]). Meeting safe drinking water standards would require NO leaching reductions of over 70% from current levels through reductions in excess manure applications, which accounts for nearly half of all groundwater N loading, and through synthetic N management improvements. This represents a broad challenge given current economic and technical conditions of California farming if farm productivity is to be maintained. The findings illustrate the growing tension-characteristic of agricultural regions globally-between intensifying food, feed, fiber, and biofuel production and preserving clean water.

A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA

Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50ppb and probability of dissolved oxygen concentration to be below 0.5ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971-2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative impact on nitrate predictions. Three-dimensional visualization indicates that nitrate predictions depend on the probability of anoxic conditions and other factors, and that nitrate predictions generally decreased with increasing groundwater age.

Preface: Optimization for groundwater characterization and management

[Extract]: Introduction: Anthropogenic activities conducted in an unplanned manner, and often without a regional-scale view, have led to over-exploitation and wide spread deterioration of groundwater quality. In order to address all the associated groundwater management issues on a larger regional scale, it is necessary to (1) obtain adequate and reliable information regarding the complex geology of the aquifer; (2) develop suitable mathematical simulation models incorporating reliable estimates of hydrogeologic and geochemical parameters, to describe the likely impacts of human interventions; and (3) utilize a suitably formulated decision model capable of prescribing as a solution a set of strategies for optimal management of aquifers, or capable of optimally solving the inverse problem with unknown hydrogeologic or geochemical characteristics. These components are often interrelated. This theme issue, Optimization for Groundwater Characterization and Management, provides a glimpse of the present state of the art, and points towards some of the future prospects in this area.

Parallel simulation of groundwater non-point source pollution using algebraic multigrid preconditioners

The simulation of non-point source pollution in agricultural basins is a computationally demanding process due to the large number of individual sources and potential pollution receptors (e.g., drinking water wells). In this study, we present an efficient computational framework for parallel simulation of diffuse pollution in such groundwater basins. To derive a highly detailed velocity field, we employed algebraic multigrid (AMG) preconditioners to solve the groundwater flow equation. We compare two variants of AMG implementations, the multilevel preconditioning provided by Trilinos and the BoomerAMG provided by HYPRE. We also perform a sensitivity analysis on the configuration of AMG methods to evaluate the application of these libraries to groundwater flow problems. For the transport simulation of diffuse contamination, we use the streamline approach, which decomposes the 3D transport problem into a large number of 1D problems that can be executed in parallel. The proposed framework is applied to a 2,600-km2 groundwater basin in California discretized into a grid with over 11 million degrees of freedom. Using a Monte Carlo approach with 200 nitrate loading realizations at the aquifer surface, we perform a stochastic analysis to quantify nitrate breakthrough prediction uncertainty at over 1,500 wells due to random, temporally distributed nitrate loading. The results show that there is a significant time lag between loading and aquifer response at production wells. Generally, typical production wells respond after 5–50 years depending on well depth and screen length, while the prediction uncertainty for nitrate in individual wells is very large—approximately twice the drinking water limit for nitrate.

An efficient simulation-optimization coupling for management of coastal aquifers

Seawater intrusion in coastal aquifers is a major environmental problem and efficient tools are needed to assist decision making. Decision tools are often simulation models (which evaluate probable actions) combined with optimization algorithms (which search for optimum management decisions). A coupling between simulation models and optimization algorithms for management of coastal aquifers is presented. The simulation models are based on the sharp-interface approximation where the decision variables do not affect the discretized system matrix. For such problems, a transformation of the system matrix prior to optimization is proposed which supports rapid solution of the linear system of equations during the optimization stage, for different values of decision variables. The method is applied to a hypothetical simulation of a coastal aquifer on the Greek island of Santorini, where the proposed simulation-optimization coupling method is employed to maximize pumping rates subject to environmental constraints that protect the aquifer from seawater intrusion. Various packages were tested in order to investigate their efficiency in solving the linear system pertinent to the case study. The proposed method, based on coupling of equations, is found to be very efficient in terms of computational cost. In particular, for the problem examined, it is at least 50 times faster than standard methods, depending on the grid size.RésuméL’intrusion d’eau salée dans les aquifères côtiers est un problème environnemental majeur et des outils efficaces sont nécessaires pour aider à la prise de décision. Les outils d’aide à la décision sont souvent des modèles de simulation (qui évaluent les actions probables) associés à des algorithmes d’optimisation (qui recherchent des décisions de gestion optimales). Un couplage de modèles de simulation à des algorithmes d’optimisation pour la gestion des aquifères côtiers est présenté. Les modèles de simulation sont basés sur l’approximation de l’interface abrupte entre eaux douces et eaux salées pour lequel les variables utiles pour la décision n’affectent par la matrice du système discrétisé. Pour de tels problèmes, une transformation de la matrice du système avant optimisation est proposée, qui permet une solution rapide du système linéaire des équations lors de la phase d’optimisation, pour différentes valeurs de variables utiles pour la décision. La méthode est appliquée à la simulation hypothétique d’un aquifère côtier de l’île grecque de Santorin, pour lequel la méthode proposée de couplage simulation-optimisation est employée pour maximiser les débits de pompage sujets aux contraintes environnementales qui protègent l’aquifère d’une intrusion d’eau de mer. Différentes combinaisons ont été testées afin d’étudier leur efficacité dans la résolution du système linéaire pertinent pour le cas d’étude. La méthode proposée, basée sur le couplage des équations, est très efficace en termes de temps de calcul. En particulier, pour le problème examine, il est au moins 50 fois plus rapide que les méthodes classiques, fonction de la taille de la grille considérée.ResumenLa intrusión marina en los acuíferos costeros es un problema ambiental importante y se necesitan herramientas eficientes para ayudar a la toma de decisiones. Las herramientas de decisión son a menudo modelos de simulación (que evalúan las probables acciones) combinados con algoritmos de optimización (que buscan las decisiones de óptimas de gestión). Se presenta un acoplamiento entre los modelos de simulación y algoritmos de optimización para la gestión de los acuíferos costeros. Los modelos de simulación se basan en la aproximación de una interfaz marcada donde las variables de decisión no afectan a la matriz del sistema discretizado. Para este tipo de problemas, se propone una transformación de la matriz del sistema antes de la optimización, que apoya una solución rápida del sistema lineal de ecuaciones durante la etapa de optimización, para diferentes valores de variables de decisión. El método se aplica a una simulación hipotética de un acuífero costero en la isla griega de Santorini, donde se emplea el método de acoplamiento de simulación y de optimización propuesto para maximizar las tasas de bombeo con limitaciones medioambientales que protegen el acuífero de la intrusión de agua de mar. Se ensayaron varios paquetes para investigar su eficiencia en la resolución del sistema lineal pertinente para el caso de estudio. Se encuentra que el método propuesto, sobre la base del acoplamiento de ecuaciones, es muy eficiente en términos de costo computacional. En particular, el problema examinado, es al menos 50 veces más rápido que los métodos estándar, dependiendo del tamaño de cuadrícula.摘要沿海含水层的海水入侵是一个主要的环境问题,需要有效率的工具来支持决策。决策工具通常是模拟模型(评价可能的行为)结合最优化算法(寻找最优化管理决策)。本文展示了沿海含水层管理模拟模型和最优化算法之间的耦合。模拟模型基于截面近似值,在截面上,决策变量不影响离散系统基质。针对这样的问题,提出了最优化前系统基质的转化,转化对不同的决策变量值在最优化阶段支撑公式线性系统的快速解决。方法应用于希腊圣托里尼岛一个沿海含水层的假定模拟中,在这个地方,采用所述的模拟-最优化耦合方法提出了确保含水层免受海水入侵情况下的最大抽水量。实验了各种方案以调查每个方案在解决与实例研究有关的线性系统中的效率。所述的方法基于公式的耦合,发现在计算费用上非常有效率。尤其是对于检查的问题,至少比标准方法快50倍,这取决于网格的大小。ResumoIntrusão de água marinha em aquíferos costeiros é um importante problema ambiental e ferramentas eficientes para assessorar a tomada de decisão são necessários. Ferramentas de decisão são geralmente modelos de simulação (que avaliam ações prováveis) combinados com algoritmos de otimização (que procuram por decisões de gerenciamento ótimas). Um acoplamento entre modelos de simulação e algoritmos de otimização para o gerenciamento de aquíferos costeiros é apresentado. Os modelos de simulação são baseados na aproximação da interface abrupta onde as variáveis de decisão não afetam o sistema matricial discretizado. Para tais problemas, uma transformação no sistema matricial antes da otimização é proposta, a qual suporta soluções rápidas do sistema de equações lineares durante o estágio de otimização, para diferentes valores das variáveis de decisão. O método é aplicado a uma simulação hipotética de um aquífero costeiro na ilha Grega de Santorini, onde o método de acoplamento simulação-otimização é empregado para maximizar a taxas de bombeamento sujeitas a restrições ambientais que protegem o aquífero da intrusão de água do mar. Vários pacotes foram testados com o propósito de investigar suas eficiências em solucionar o sistema linear pertinente à cada estudo de caso. O método proposto, baseado no acoplamento de equações, é considerado muito eficiente em termos de custos computacionais. Em particular, para o problema examinado, isso é ao menos 50 vezes mais rápido do que métodos padrões, dependendo do tamanho da malha.