Despite significant recent developments in computational power and distributed hydrologic
modeling, the issue of how to adequately address the uncertainty associated with …

Data assimilation is a term that is most closely associated with the atmospheric sciences. It
arises from the meteorological custom of constructing daily weather maps which show how …

Integrated, process‐based numerical models in hydrology are rapidly evolving, spurred by
novel theories in mathematical physics, advances in computational methods, insights from …

" Four pedometricians have written this new book on sampling. They are often consulted by
colleagues who need to plan sampling schemes for monitoring, but have not felt able to …

GIS users and professionals are aware that the accuracy of GIS results cannot be naively
based on the quality of the graphical output. Data stored in a GIS will have been collected or …

Groundwater monitoring is fundamental to understanding system dynamics, trends in
storage, and the long‐term sustainability of an aquifer. Water‐level data are the key source …

The literature on the application of simulation-optimization approaches for management and
monitoring of coastal aquifers is reviewed. Both sharp-and dispersive-interface modeling …

Effective groundwater management and allocation are essential from economic and social
points of view due to increasing high-quality water demands. This study presents a review …

A sequential data assimilation procedure based on the ensemble Kalman filter (EnKF) is
introduced and tested for a process‐based numerical model of coupled surface and …

While satellite‐based remote sensing has provided hydrologists with valuable new data
sets, integration of such data sets in operational modeling systems is usually not …