کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8894858 | 1629893 | 2018 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Reference evapotranspiration forecasting based on local meteorological and global climate information screened by partial mutual information
ترجمه فارسی عنوان
پیش بینی تبخیر تعرق مرجع بر اساس اطلاعات هواشناسی محلی و اطلاعات مربوط به آب و هوا بر اساس اطلاعات جزئی متقابل
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کلمات کلیدی
تبخیر تعرق، جزئی اطلاعات متقابل، شاخص های آب و هوا، اتصال مخابرات،
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
فرآیندهای سطح زمین
چکیده انگلیسی
In this study, reference evapotranspiration (ET0) forecasting models are developed for the least economically developed regions subject to meteorological data scarcity. Firstly, the partial mutual information (PMI) capable of capturing the linear and nonlinear dependence is investigated regarding its utility to identify relevant predictors and exclude those that are redundant through the comparison with partial linear correlation. An efficient input selection technique is crucial for decreasing model data requirements. Then, the interconnection between global climate indices and regional ET0 is identified. Relevant climatic indices are introduced as additional predictors to comprise information regarding ET0, which ought to be provided by meteorological data unavailable. The case study in the Jing River and Beiluo River basins, China, reveals that PMI outperforms the partial linear correlation in excluding the redundant information, favouring the yield of smaller predictor sets. The teleconnection analysis identifies the correlation between Nino 1â¯+â¯2 and regional ET0, indicating influences of ENSO events on the evapotranspiration process in the study area. Furthermore, introducing Nino 1â¯+â¯2 as predictors helps to yield more accurate ET0 forecasts. A model performance comparison also shows that non-linear stochastic models (SVR or RF with input selection through PMI) do not always outperform linear models (MLR with inputs screen by linear correlation). However, the former can offer quite comparable performance depending on smaller predictor sets. Therefore, efforts such as screening model inputs through PMI and incorporating global climatic indices interconnected with ET0 can benefit the development of ET0 forecasting models suitable for data-scarce regions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Hydrology - Volume 561, June 2018, Pages 764-779
Journal: Journal of Hydrology - Volume 561, June 2018, Pages 764-779
نویسندگان
Wei Fang, Shengzhi Huang, Qiang Huang, Guohe Huang, Erhao Meng, Jinkai Luan,