mHM (Mesoscale Hydrologic Model)

The mHM is a spatially distributed, grid-based mesoscale hydrologic model that accounts for the following main hydrologic processes: canopy interception, snow accumulation and melt, root zone soil moisture and evapotranspiration, infiltration, surface and subsurface runoff, percolation, baseflow and flood routing.

spatially distributedgrid-basedmesoscalehydrologic
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contributed at 2019-12-29

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Model Description

English {{currentDetailLanguage}} English

Quoted from: https://www.ufz.de/index.php?en=40114 

The mesoscale hydrologic model (mHM) developed by our group is a spatially explicit distributed hydrologic model that uses grid cells as a primary hydrologic unit, and accounts for the following processes: canopy interception, snow accumulation and melting, soil moisture dynamics, infiltration and surface runoff, evapotranspiration, subsurface storage and discharge generation, deep percolation and baseflow and discharge attenuation and flood routing.

Schematic Representation of the Mesoscale Hydrologic Model
Fig. 1: Schematic of resolution levels, data, processes and states in mHM.

The model is driven by hourly or daily meteorological forcings (e.g., precipitation, temperature), and it utilizes observable basin physical characteristics (e.g., soil textural, vegetation, and geological properties) to infer the spatial variability of the required parameters.

The main feature of mHM is the approach to estimate parameters at the target resolution based on high resolution physiographic land surface descriptors (e.g., DEM, slope, aspect, root depth based on land cover class or plant functional types, LAI, soil texture, geological formation type) . The technique was proposed in Samaniego et al WRR 2010 and is called multiscale parameter regionalization (MPR). The MPR technique is crucial to reach flux-matching across scales and to derive seamless parameter fields (Samaniego et al HESS 2017).

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How to Cite

mHM team (2019). mHM (Mesoscale Hydrologic Model), Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/7cb9aff4-9b9d-4de4-a71e-b5d035293ede
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Initial contribute: 2019-12-29

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