Reference evapotranspiration forecasting based on local meteorological and global climate information screened by partial mutual information
By Wei Fang, Shengzhi Huang, Qiang Huang, Guohe Huang, Erhao Meng, J. Luan. Journal of Hydrology, 2018
70 citations recorded by the source corpus.
Abstract 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 1 + 2 and regional ET0, indicating influences of ENSO events on the evapotranspiration process in the study area. Furthermore, introducing Nino 1 + 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.
Subfields: Environmental Engineering, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/4a13ebee18743b2047178e2752b4aa23d7b3eff3
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In Environmental Engineering
In Global and Planetary Change
Citations in the corpus
- Copulas‐based risk analysis for inter‐seasonal combinations of wet and dry conditions under a changing climate (2018, background): “…Society 2005 One striking variation of precipitation frequency distributions is the shift towards extremes across almost the entire globe, largely due to the accelerated rate of the water cycle (Alexander et al., 2006; Sun et al., 2007; Wang et al., 2011; Westra et al., 2013; Fang et al., 2019).”