Hillslope and Watershed Hydrology
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".
Deadline for manuscript submissions: closed (31 March 2017) | Viewed by 95529
Special Issue Editors
Interests: hillslope hydrology; stochastic hydrology; isotope hydrology; computational modeling; critical zone science
Special Issue Information
Dear Colleagues,
Current hillslope and catchment hydrologic research requires frequent and intensive interactions between field observations and numerical models. Hillslope hydrologists and ecohydrologists focus on the micro- to macroscale processes, while catchment river basin hydrologists pursue dominant processes affecting the river network and larger macro-scale soil and hydrogeologic distributions. In order to bridge these scales, researchers have pursued a number of physics-based models that capture the effects of spatial heterogeneity in hillslope and watershed properties (e.g., land cover, vegetation, topography, soil, geology). From a modeling aspect, we want to find optimal principles to represent the important heterogeneity and process complexity across multiple scales. From the experimental point of view, recent field campaigns have built a series of experimental catchment observing systems (e.g., Critical Zone Observatories) to provide fundamental information across multiple scales. Through these field experiments and model developments, the broad research community hopes to generalize fundamental theories, and guide model applications. The reconciliation of field data and mathematical models should improve our understanding and capacity to bridge fundamental processes from hillslope to catchments and river basin scales, and to allow watershed forecasting and uncertainty analysis to become a basic tool for decision-making.
This Special Issue aims to assemble contributions on hillslope and watershed scale model developments linked to applications and field experiments. We seek contributions that use model simulation and field observations to understand the heterogeneity and process complexity and uncertainty across scales, and the prospect for prediction in watershed ecohydrologic systems. We welcome generalized findings where experiment and computation leads to systematic learning and the science-based models necessary to manage our future water supply and ecohydrologic services.
Prof. Christopher J. Duffy
Dr. Xuan Yu
Guest Editors
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Keywords
- scale
- hillslope
- watershed
- modeling
- computation
- ecohydrology
- hydrologic observatory
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