The suggested book illustrates a geospatial and geostatistical approach to data analysis, modelling, risk assessment, and visualization, as well as surface and subsurface hydrological condition management solutions in many elements of water-induced hazards. This book investigates cutting-edge methodologies based on open source software and R statistical programming and modelling in current decision-making procedures, with a particular emphasis on recent advances in data mining techniques and robust modelling in water-induced hydrological hazard.

This proposed book would assemble a collection of contemporary breakthroughs and rigorous uses of geospatial and geostatistical techniques, as well as their application in the field of surface and subsurface water-induced hazards. Soil conservation service-curve number (SCS-CN), machine learning algorithms (MLA), analytic hierarchy process (AHP), multi-criteria decision making (MCDM), multi influencing factor (MIF), principal component analysis (PCA), mann-kendall non parametric test, artificial neural networks (ANN), autoregressive integrated moving average (ARIMA), supervised and unsupervised classification algorithms, and others are among the techniques covered.

Its covers major topics such as: surface runoff and storage, Aquifer forms, aquifer size, and aquifer components, and their connection to the geological sequence, flow direction, storage, and hydraulic conductivity, present yield of the groundwater. Spatio-temporal variation of groundwater depth and its association with numerous physical parameter like Rainfall, NDVI, NDWI, Drainage density, Drainage frequency, Land use and land cover, numerous hydro-chemical facies such as Wilcox diagram, Donne's diagram, Gibb's mechanism will be incorporated to validate the different features of groundwater, present and potential groundwater conservation condition also be discussed on the basis of its continuous number of applications, groundwater quality, potential refilling experiments will be implemented utilizing different decision-making strategies and, eventually, potential maps for the efficient use of groundwater supplies will be planned etc. The topics of this book will be of value to earth and environmental scientists, experts, and authorities.

This book will look at geospatial modelling and the management of surface and subsurface water resources. The world is rapidly running out of fresh water; severe water shortages have been reported in many parts of the world in recent years. The total amount of groundwater extracted has been gradually increasing globally, and unsustainable water stress has resulted in severe declines in groundwater levels in many locations. Groundwater resource exploitation has occurred at a rate that prevents the water table from recovering its losses. As a result, shallower aquifers dried up, river water levels dropped, and wells were dug continuously. Population participation in natural soil distribution and management is vital for future existence. Water is a critical common service, not a governmental asset. Recent and expected trends indicate that future water challenges will become more complex. The decline in the groundwater table has now become a critical issue in maintaining India's economic prosperity. As a result, assessing the danger of groundwater and effectively managing it in this critical situation is critical. A link between three technologies, including remote sensing (RS), GIS, and the R programming environment, is recognized to be particularly useful in this respect. However, this book will serve as a viable guidance to identify the most recent advancements in geospatial, geostatistical techniques and their application in the field of surface and subsurface water-induced hazards throughout the world.