Applied Stochastic Hydrogeology

Stochastic hydrogeology has matured into a distinct branch or discipline within hydrogeology. Stochastic hydrogeology is an area of research that developed considerably over the last 20 years. Applied Stochastic Hydrogeology is a book that allows newcomers to the field an easy introduction. The book covers the fundamentals and practical aspects of geostatistics and stochastic hydrogeology, coupling theoretical and practical aspects, with examples, case studies and guidelines for applications, and provides a summary and review of the major developments in these areas. The first part of the book discusses fully stochastic distributed methodology for flood frequency analysis and an analysis of the occurrence probabilities of wet and dry periods using stochastic monthly rainfall model. Then we present an indirect simulation-optimization model for determining optimal TMDL allocation under uncertainty and stochastic urban pluvial flood hazard maps based upon a spatial-temporal rainfall generator. Stochastic flocculation model for cohesive sediment suspended in water and seismic-reliability-based optimal layout of a water distribution network are also discussed. In the middle part of the book, we focus on analysis of urban drainage networks using Gibbs model in South Korea and quantitative estimation of the impact of precipitation and behavior of a fully-looped drainage network and the corresponding dendritic networks. Land surface change on hydrological processes through statistical modeling and the influence of statistical uncertainty in the hydraulic boundary conditions are also discussed. We also try to find out optimizing water allocation under uncertain system conditions for water and agriculture future scenarios in Alfeios River Basin (Greece) and assessment of groundwater chemistry and status in a heavily used semi-arid region with multivariate statistical analysis. The last chapters of the book describe uncertainty analysis of multiple hydrologic models using the bayesian model and modeling the projected changes of river flow in central Vietnam under different climate change scenarios. We also present modelling hydrology of a single bioretention system with HYDRUS-1D and saltwater intrusion in coastal aquifers within a Probabilistic Framework. At the end of the book, we also discuss forecasting daily precipitation using hybrid model and the effect of training image and secondary data integration with multiple-point geostatistics in groundwater modelling.