3D hydrological simulation of a forested headwater catchment: spatio-temporal validation and scale dependent parameterization
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Soil moisture plays a key role in the water and energy balance in soil, vegetation and atmosphere systems. There is a grand need to increase global-scale hyper-resolution waterenergy- biogeochemistry land surface modelling capabilities. High reliability simulation of soil water content using various kinds of numerical modeling tools has been studied in recent years. Multiple methods have been applied for more accurate parameterizations. In distributed hydrological modelling one often faces the problem that input data need to be aggregated to match the model resolution. However, aggregated data may be too coarse for the parametrization of the processes represented. This dilemma can be circumvented by the adjustment of certain model parameters. Unfortunately, it is not clear how to parameterize hydrological processes as a function of scale, and how to test deterministic models with regard to epistemic uncertainties.
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3D hydrological simulation of a forested headwater catchment: spatio-temporal validation and scale dependent parameterization, Zhufeng Fang
- Language
- Released
- 2016
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- Title
- 3D hydrological simulation of a forested headwater catchment: spatio-temporal validation and scale dependent parameterization
- Language
- English
- Authors
- Zhufeng Fang
- Publisher
- Forschungszentrum Jülich GmbH
- Released
- 2016
- ISBN10
- 3958061745
- ISBN13
- 9783958061743
- Series
- Schriften des Forschungszentrums Jülich : [...], Reihe Energie & Umwelt
- Category
- University and college textbooks
- Description
- Soil moisture plays a key role in the water and energy balance in soil, vegetation and atmosphere systems. There is a grand need to increase global-scale hyper-resolution waterenergy- biogeochemistry land surface modelling capabilities. High reliability simulation of soil water content using various kinds of numerical modeling tools has been studied in recent years. Multiple methods have been applied for more accurate parameterizations. In distributed hydrological modelling one often faces the problem that input data need to be aggregated to match the model resolution. However, aggregated data may be too coarse for the parametrization of the processes represented. This dilemma can be circumvented by the adjustment of certain model parameters. Unfortunately, it is not clear how to parameterize hydrological processes as a function of scale, and how to test deterministic models with regard to epistemic uncertainties.