%0 Journal Article
%T 基于转移熵的长江流域土壤湿度对降水反馈研究<br>Soil Moisture Feedbacks on Precipitation in the Yangtze River Catchment Based on Transfer Entropy
%A 娄巍
%A 刘攀
%A 程磊
%A 邹铠杰
%A 夏倩
%J Journal of Water Resources Research
%P 21-32
%@ 2166-5982
%D 2021
%I Hans Publishing
%R 10.12677/JWRR.2021.101003
%X <div style=\"text-align:justify;\">
	<span style=\"font-size:14px;line-height:1.5;\">陆气耦合过程复杂，研究土壤湿度对降水的影响机制，对气候预测和天气预报具有重要意义。目前土壤湿度对降水的反馈机制尚不明确，采用物理模型存在较大的不确定性，而通过数据直接反映非线性统计相关性的转移熵，是一种可解释水文系统的新范式，为研究此类问题提供了可能。本文提出并验证了归一化转移熵，使量纲不同的耦合强度具备可比性；使用长江流域2002~2018年168个气象站点观测的降水和蒸散发数据、全球陆面参数数据LPDR V2.0中的土壤湿度数据、以及MODIS中的植被指数NDVI数据，采用显著滞时、不同滞时的相对预测度和归一化信息熵3个信息指标识别土壤湿度对降水的反馈特征，并应用偏相关方法验证了长江流域土壤湿度对降水正反馈的合理性。结果表明：1) 土壤湿度对降水的平均显著滞时为4.3 d，与降水对土壤湿度的1.8 d相比滞时更长，说明土壤湿度对降水的反馈过程存在滞时，即土壤湿度响应前期降水后，延迟较长时段影响降水过程；2) 降水对土壤湿度的归一化转移熵为0.51，与土壤湿度对降水的0.13相比耦合强度更高，说明土壤湿度对降水的反馈显著弱于降水对土壤湿度的影响；3) 金沙江下游和洞庭湖、鄱阳湖、太湖水系等近湖区域由于水量交换频繁，土壤湿度对降水反馈较快且强度更高。<br />
The land surface and atmosphere interact as a complexly linked system. The soil moisture-precipitation feedback mechanism is of great significance to weather forecast and climate prediction; however, it is uncertain in physical-based numerical simulation. Transfer entropy, which reflects non-linear statistical correlation directly through data, has been considered as a new paradigm to explain hydrological system and provides possibility to study the land-atmosphere coupling. Normalized transfer entropy was proposed in this study, and was verified to measure comparable coupling strength. Observation data on 168 weather stations during 2002~2018, MODIS-NDVI (MOD13A2) and soil moisture data from the global land parameters data record LPDR V2.0 were used. Characteristics of the feedback were explored by three information indexes. A positive soil moisture-precipitation feedback was also valid by the partial correlation. The results showed: 1) the average significant lag time of soil moisture-precipitation coupling was 4.3 d, which was longer than 1.8 d of precipitation-soil moisture coupling. It indicated that there was a delay effect during the feedback process. The soil moisture in response to precipitation affected the precipitation process after a longer period of time; 2) the normalized transfer entropy of precipitation-soil moisture coupling was 0.51, which was stronger than 0.13 of soil moisture -precipitation coupling; and 3) due to the frequent water exchange in the lower reaches of the Jinsha River, the Dongting Lake, the Poyang Lake and the Taihu Lake systems, soil moisture had a faster and stronger feedback on precipitation.</span> 
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%K 土壤湿度对降水反馈，长江流域，转移熵<br>Soil Moisture-Precipitation Feedback
%K The Yangtze River
%K Transfer Entropy
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=40465