کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6409625 1629914 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Evaluating uncertainties in multi-layer soil moisture estimation with support vector machines and ensemble Kalman filtering
ترجمه فارسی عنوان
ارزیابی عدم اطمینان در برآورد رطوبت چند لایه خاک با استفاده از دستگاه های بردار پشتیبانی و فیلتر کلمن گروه
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
چکیده انگلیسی


- The SVM performance decreases for the deeper soil moisture estimation.
- Coupled dual EnKF-SVM model improves soil moisture estimation in deep root zone layers.
- Soil moisture estimation is influenced by the rainfall magnitude.

SummaryThis paper examines the combination of support vector machines (SVM) and the dual ensemble Kalman filter (EnKF) technique to estimate root zone soil moisture at different soil layers up to 100 cm depth. Multiple experiments are conducted in a data rich environment to construct and validate the SVM model and to explore the effectiveness and robustness of the EnKF technique. It was observed that the performance of SVM relies more on the initial length of training set than other factors (e.g., cost function, regularization parameter, and kernel parameters). The dual EnKF technique proved to be efficient to improve SVM with observed data either at each time step or at a flexible time steps. The EnKF technique can reach its maximum efficiency when the updating ensemble size approaches a certain threshold. It was observed that the SVM model performance for the multi-layer soil moisture estimation can be influenced by the rainfall magnitude (e.g., dry and wet spells).

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Hydrology - Volume 538, July 2016, Pages 243-255
نویسندگان
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