کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6962202 | 1452249 | 2018 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
What can we learn from multi-data calibration of a process-based ecohydrological model?
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزار
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
We assessed whether a complex, process-based ecohydrological model can be appropriately parameterized to reproduce the key water flux and storage dynamics at a long-term research catchment in the Scottish Highlands. We used the fully-distributed ecohydrological model EcH2O, calibrated against long-term datasets that encompass hydrologic and energy exchanges, and ecological measurements. Applying diverse combinations of these constraints revealed that calibration against virtually all datasets enabled the model to reproduce streamflow reasonably well. However, parameterizing the model to adequately capture local flux and storage dynamics, such as soil moisture or transpiration, required calibration with specific observations. This indicates that the footprint of the information contained in observations varies for each type of dataset, and that a diverse database informing about the different compartments of the domain, is critical to identify consistent model parameterizations. These results foster confidence in using EcH2O to contribute to understanding current and future ecohydrological couplings in Northern catchments.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Environmental Modelling & Software - Volume 101, March 2018, Pages 301-316
Journal: Environmental Modelling & Software - Volume 101, March 2018, Pages 301-316
نویسندگان
Sylvain Kuppel, Doerthe Tetzlaff, Marco P. Maneta, Chris Soulsby,