کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6410696 1332885 2015 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A comparative analysis of 9 multi-model averaging approaches in hydrological continuous streamflow simulation
ترجمه فارسی عنوان
تجزیه و تحلیل تطبیقی ​​9 روش میانگین محاسباتی چند مدل در شبیه سازی جریان هیدرولوژیکی جریان
کلمات کلیدی
مدل میانگین توابع هدف، مقیاس میانگین مقایسه، کاهش خطای مدل،
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
چکیده انگلیسی


- Multi-model averaging improves hydrological modeling performance substantially.
- Models with similar structures can be combined efficiently to improve upon single-model simulations.
- The GRC model averaging scheme performs the best and is the quickest to execute.
- Even low scoring models contribute to the ensemble average and improve performance.

SummaryThis study aims to test whether a weighted combination of several hydrological models can simulate flows more accurately than the models taken individually. In addition, the project attempts to identify the most efficient model averaging method and the optimal number of models to include in the weighting scheme. In order to address the first objective, streamflow was simulated using four lumped hydrological models (HSAMI, HMETS, MOHYSE and GR4J-6), each of which were calibrated with three different objective functions on 429 watersheds. The resulting 12 hydrographs (4 models × 3 metrics) were weighted and combined with the help of 9 averaging methods which are the simple arithmetic mean (SAM), Akaike information criterion (AICA), Bates-Granger (BGA), Bayes information criterion (BICA), Bayesian model averaging (BMA), Granger-Ramanathan average variant A, B and C (GRA, GRB and GRC) and the average by SCE-UA optimization (SCA). The same weights were then applied to the hydrographs in validation mode, and the Nash-Sutcliffe Efficiency metric was measured between the averaged and observed hydrographs. Statistical analyses were performed to compare the accuracy of weighted methods to that of individual models. A Kruskal-Wallis test and a multi-objective optimization algorithm were then used to identify the most efficient weighted method and the optimal number of models to integrate. Results suggest that the GRA, GRB, GRC and SCA weighted methods perform better than the individual members. Model averaging from these four methods were superior to the best of the individual members in 76% of the cases. Optimal combinations on all watersheds included at least one of each of the four hydrological models. None of the optimal combinations included all members of the ensemble of 12 hydrographs. The Granger-Ramanathan average variant C (GRC) is recommended as the best compromise between accuracy, speed of execution, and simplicity.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Hydrology - Volume 529, Part 3, October 2015, Pages 754-767
نویسندگان
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