3.8 Article

A distributed water-heat coupled model for mountainous watershed of an inland river basin of Northwest China (I) model structure and equations

Journal

ENVIRONMENTAL GEOLOGY
Volume 53, Issue 6, Pages 1299-1309

Publisher

SPRINGER
DOI: 10.1007/s00254-007-0738-2

Keywords

frozen soil; soil temperature; soil water content; soil water tension

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It is absolutely necessary to quantify the hydrological processes in earth surface by numerical models in the cold regions where although most Chinese large rivers acquire their headstreams, due to global warming, its glacier, permafrost and snow cover have degraded seriously in the recent 50 years. Especially in an arid inland river basin, where the main water resources come from mountainous watershed, it becomes an urgent case. However, frozen ground's impact to water cycle is little considered in the distributed hydrological models for a watershed. Took Heihe mountainous watershed with an area of 10,009 km(2), as an example, the authors designed a distributed heat-water coupled (DWHC) model by referring to SHAW and COUP. The DWHC model includes meteorological variable interception model, vegetation interception model, snow and glacier melting model, soil water-heat coupled model, evapotransporation model, runoff generation model, infiltration model and flow concentration model. With 1 km DTM grids in daily scale, the DWHC model describes the basic hydrological processes in the research watershed, with 3 similar to 5 soil layers for each of the 18 soil types, 9 vegetation types and 11 landuse types, according to the field measurements, remote sensing data and some previous research results. The model can compute the continuous equation of heat and water flow in the soil and can estimate them continuously, by numerical methods or by some empirical formula, which depends on freezing soil status. However, the model still has some conceptual parameters, and need to be improved in the future. This paper describes only the model structure and basic equations, whereas in the next papers, the model calibration results using the data measured at meteorological stations, together with Mesoscale Model version 5 (MM5) outputs, will be further introduced.

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