کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8883400 | 1625600 | 2018 | 65 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
فرآیندهای سطح زمین
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation](/preview/png/8883400.png)
چکیده انگلیسی
Assimilation of remotely sensed surface soil moisture (SSM) data into hydrological catchment models has been identified as a means to improve streamflow simulations, but reported results vary markedly depending on the particular model, catchment and assimilation procedure used. In this study, the influence of key aspects, such as the type of model, re-scaling technique and SSM observation error considered, were evaluated. For this aim, Advanced SCATterometer ASCAT-SSM observations were assimilated through the ensemble Kalman filter into two hydrological models of different complexity (namely MISDc and TOPLATS) run on two Mediterranean catchments of similar size (750 km2). Three different re-scaling techniques were evaluated (linear re-scaling, variance matching and cumulative distribution function matching), and SSM observation error values ranging from 0.01% to 20% were considered. Four different efficiency measures were used for evaluating the results. Increases in Nash-Sutcliffe efficiency (0.03-0.15) and efficiency indices (10-45%) were obtained, especially when linear re-scaling and observation errors within 4-6% were considered. This study found out that there is a potential to improve streamflow prediction through data assimilation of remotely sensed SSM in catchments of different characteristics and with hydrological models of different conceptualizations schemes, but for that, a careful evaluation of the observation error and re-scaling technique set-up utilized is required.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Water Resources - Volume 111, January 2018, Pages 86-104
Journal: Advances in Water Resources - Volume 111, January 2018, Pages 86-104
نویسندگان
Javier Loizu, Christian Massari, Jesús Álvarez-Mozos, Angelica Tarpanelli, Luca Brocca, Javier CasalÃ,