Hydrogeology Journal

, Volume 20, Issue 7, pp 1239–1249 | Cite as

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

  • Rodrigo L. Manzione
  • Edson Wendland
  • Diego H. Tanikawa
Paper

Abstract

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Keywords

Groundwater monitoring Geostatistics Statistical modeling Brazil 

Modèles de simulation stochastique de séries chronologiques combinées avec la géostatistique pour prédire des scénarios piézométriques dans une région d’affleurement du système aquifère du Guarani au Brésil

Résumé

Les méthodes stochastiques basées sur une combinaison de modèles de chroniques piézométriques et de géostatistique peuvent être des outils utiles pour décrire la variabilité spatiale et temporelle des niveaux piézométriques et pour prendre en compte les incertitudes. Les réseaux piézométriques peuvent fournir une information sur l’hydrodynamique du domaine aquifère dans les deux dimensions. La modélisation de chroniques piézométriques est une manière élégante de traiter des données piézométriques sans la complexité des modèles physiques mécanistes. Les prévisions de chroniques piézométriques peuvent être interpolées dans l’espace en considérant les différences spatiales de la dynamique piézométrique déterminée par la variation spatiale des propriétés du système et la variation temporelle contrainte par la dynamique des données d’entrée. Une intégration des méthodes stochastiques est présentée, basée sur la modélisation de chroniques piézométriques et la géostatistique en tant que cadre pour prédire les niveaux piézométriques nécessaires à la prise de décision pour la gestion de la ressource en eaux souterraines et pour la planification de l'occupation du sol. La méthodologie est appliquée à un cas d’étude dans une région d’affleurement du système aquifère du Guarani (SAG), localisé dans le Sud-Est du Brésil. La présentation des résultats sous une forme claire et compréhensible, par des scénarios simulés, est discutée comme une alternative de traduction des connaissances scientifiques dans des applications d’hydrogéologie stochastique pour des grands aquifères pour lesquels le réseau piézométrique occupe une couverture restreinte comme c’est le cas pour le SAG.

Simulación estocástica de modelos de series temporales combinados con geoestadística para predecir escenarios de niveles freáticos en un área aflorante del Sistema Acuífero Guaraní, Brasil

Resumen

Los métodos estocásticos basados en modelos de series temporales combinados con geoestadística pueden ser herramientas útiles para describir la variabilidad de los niveles freáticos en tiempo y espacio y para dar cuenta de la incertidumbre. Las redes de monitoreo de niveles de agua puede dar información acerca de la dinámica de un dominio del acuífero en ambas dimensiones. El modelado de series temporales es una forma elegante de tratar los datos de monitoreo sin la complejidad de modelos físicos mecanicistas. Las predicciones de los modelos de series temporales pueden ser interpoladas espacialmente, con las diferencias espaciales en la dinámica de los niveles freáticos determinada por la variación espacial en las propiedades del sistema y la variación temporal conducida por la dinámica de la entrada en el sistema. Se presenta una integración de métodos estocásticos, basados en modelos de series temporales y geostadística como un marco para predecir niveles de agua para la toma de decisiones en el manejo del agua subterránea y en la planificación del uso de la tierra. La metodología se aplica en un caso de estudio en un área aflorante del Sistema Acuífero Guaraní, situada en la parte sudeste de Brasil. Se discute la comunicación de resultados en una forma clara y entendible, a través de los escenarios simulados, como una alternativa, cuando el conocimiento científico se traduce a las aplicaciones de la hidrogeología estocástica a grandes acuíferos con una red de monitoreo de cobertura limitada como la del SAG.

利用与地质统计学相结合的时间序列随机模型来预测水位的变化:以巴西Guarani含水层系统出露地区为例

摘要

以与地质统计学相结合的时间序列模型为基础的随机方法在描述地下水水位的时空变化和解释不确定性方面是非常有效的手段。地下水水位监测网可以提供含水层在时间和空间上的动态资料。时间序列模型是一种避免了复杂的物理机械模型的处理水位监测数据的有效方法。当水位的动态在空间上存在着由系统特征的空间变化和输入项的动态驱使的时间变化导致的差异时,时间序列模型的预测结果可以在空间上进行插值。在时间序列模型和地质统计学的基础上,本文提出了一种综合性的随机方法,基于时间序列的建模和地质统计学为框架预测地下水水位,为地下水管理决策和土体利用规划提供依据。在本文中,这种方法被应用到了位于巴西东南部的Guarani含水层系统(GAS)出露地区的实例当中。当遇到像GAS一样含水层规模很大并且地下水监测网络的覆盖有限的情况时,为了将理论用于随机水文地质学的应用中,作为一种可选择的方案,可以利用模拟方案,将模拟结果的表达用一种清楚的、容易理解的方式呈现出来。

Simulação estocástica de modelos de séries temporais combinados com geoestatística para prever cenários de níveis freáticos numa área de afloramento do Sistema Aquífero do Guarani, Brasil

Resumo

Os métodos estocásticos baseados na modelação de séries temporais combinados com a geoestatística podem ser ferramentas úteis para descrever a variabilidade dos níveis freáticos no tempo e no espaço e para considerar a incerteza. As redes de monitorização de níveis piezométricos podem dar informação acerca da dinâmica do domínio aquífero nas duas dimensões. A modelação de séries temporais é uma forma elegante de tratar dados de monitorização sem a complexidade de modelos mecanicistas físicos. As previsões de modelos de séries temporais podem ser interpoladas espacialmente, com as diferenças espaciais da dinâmica do nível freático determinadas pela variação espacial das propriedades do sistema e a variação temporal guiada pela dinâmica das entradas no sistema. Apresenta-se uma integração de métodos estocásticos, baseada na modelação de séries temporais e na geoestatística, como um quadro para prever os níveis piezométricos em processos de decisão para gestão de águas subterrâneas e ordenamento do uso do solo. Aplica-se a metodologia num caso de estudo de uma área de afloramento do Sistema Aquífero do Guarani (SAG) localizado na parte sudeste do Brasil. A comunicação dos resultados de uma forma clara e compreensível, através de cenários simulados, é discutida como uma alternativa, quando se faz a tradução do conhecimento científico para aplicações de hidrogeologia estocástica em grandes aquíferos com uma cobertura de rede de monitorização limitada, como é o caso do SAG.

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Rodrigo L. Manzione
    • 1
  • Edson Wendland
    • 2
  • Diego H. Tanikawa
    • 3
  1. 1.UNESP/São Paulo State UniversityOurinhosBrazil
  2. 2.EESC/Department of Hydraulics and Sanitary EngineeringUSP/University of São PauloSão CarlosBrazil
  3. 3.UNESP/São Paulo State UniversityOurinhosBrazil

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