This leads to regions of state-space where some processes and their parameters play no role. Hydrologic responses commonly exhibit threshold behaviors in terms of process sensitivity as a function of system state, both in space and time. This gives rise to what is called in hydrology the uniqueness of place ( Beven, 2000). 1) is global in nature, the local response to frequent large-scale meteorological forcing results from global phenomena acting at local scales in response to local conditions. Therefore, a wide variety of different hydrologic models exist, which are inadequate and falsifiable in all but the most simple situations. The practice of hydrologic modeling is greatly hampered by uncertainties in process and the overwhelming influence of heterogeneities ( Troch et al., 2009) and other poorly understood and ill-described natural phenomena. Typically, model selection tends to be more a function of familiarity than appropriateness ( Addor and Melsen, 2019). For this reason and others, the practice of hydrologic modeling has, in general, included too much reliance on mathematics at the expense of true knowledge, and suffers from a need for more rigorous evaluation of appropriateness ( Klemeš, 1997). Rather, there are many plausible solutions, depending on purpose and needed complexity. Because of the nature of environmental predictions, there is no single best model. Hydrologic modeling is used to answer environmental transport questions where water excess, scarcity, or dissolved or solid content is of primary importance ( Burges, 1986). Ogden, in Encyclopedia of Geology (Second Edition), 2021 Introduction The proposed approach thus reduces the 3D watershed model to a two-variable conceptual model that constitutes a basis for developing an improved LSM hydrology.Fred L. Moreover, the model is able to capture the water balance of the reference simulation with reasonable accuracy. Results show a good capacity of this model to capture the water balance of hillslopes having different lengths and slopes. The two variables are then implemented in a conceptual model. The physical analysis of the water balance in the different hillslope compartments leads to the identification of two driving variables: seepage face extension and water table slope. An equivalent hillslope model is then able to capture both 3D simulated water balance and local water table dynamics with reasonable accuracy. A physically based 3D model built with HydroGeoSphere first produces a reference simulation. The approach is developed on the Little Washita Watershed (OK, USA) using 20-year hydrology (1993–2013). This article presents an upscaling (or bottom-up) approach to identify the basin-scale driving variables that need to be exported into LSMs. Bringing the dominant physical processes from the local scale up to the LSMs presents a significant challenge for improving the models. However, these models either neglect or oversimplify basin-scale hydrological processes that produce the land surface water balance. Land Surface Models (LSMs) are key components of Earth System Models, which the Intergovernmental Panel on Climate Change relies on in many of their studies.
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