Variability Identification and Uncertainty Evolution Characteristic Analysis of Hydrological Variables in Anhui Province, China
Variability identification and uncertainty characteristic analysis, under the impacts of climate change and human activities, is beneficial for accurately predicting the future evolution trend of hydrological variables. In this study, based on the evolution trend and characteristic analyses of histo...
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MDPI AG
2025-03-01
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| author | Xia Bai Jinhuang Yu Yule Li Juliang Jin Chengguo Wu Rongxing Zhou |
| author_facet | Xia Bai Jinhuang Yu Yule Li Juliang Jin Chengguo Wu Rongxing Zhou |
| author_sort | Xia Bai |
| collection | DOAJ |
| description | Variability identification and uncertainty characteristic analysis, under the impacts of climate change and human activities, is beneficial for accurately predicting the future evolution trend of hydrological variables. In this study, based on the evolution trend and characteristic analyses of historical precipitation and temperature sequences from monthly, annual, and interannual scales through the Linear Tendency Rate (LTR) index, as well as its variability point identification using the M–K trend test method, we further utilized three cloud characteristic parameters comprising the average <i>Ex</i>, entropy <i>En</i>, and hyper-entropy <i>He</i> of the Cloud Model (CM) method to quantitatively reveal the uncertainty features corresponding to the diverse cloud distribution of precipitation and temperature sample scatters. And then, through an application analysis of the proposed research framework in Anhui Province, China, the following can be summarized from the application results: (1) The annual precipitation of Anhui Province presented a remarkable decreasing trend from south to north and an annual increasing trend from 1960 to 2020, especially in the southern area, with the LTR index equaling 55.87 mm/10a, and the annual average temperature of the entire provincial area also presented an obvious increasing trend from 1960 to 2020, with LTR equaling about 0.226 °C/10a. (2) The uncertainty characteristic of the precipitation series was evidently intensified after the variability points in 2013 and 2014 in the southern and provincial areas, respectively, according to the derived values of entropy <i>En</i> and hyper-entropy <i>He</i>, which are basically to the contrary for the historical annual average temperature series in southern Anhui Province. (3) The obtained result was basically consistent with the practical statistics of historical hydrological and disaster data, indicating that the proposed research methodologies can be further applied in related variability diagnosis analyses of non-stationary hydrological variables. |
| format | Article |
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| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-bd914848c66d42c8bbadbc4e56cac1912025-08-20T02:11:14ZengMDPI AGEntropy1099-43002025-03-0127330510.3390/e27030305Variability Identification and Uncertainty Evolution Characteristic Analysis of Hydrological Variables in Anhui Province, ChinaXia Bai0Jinhuang Yu1Yule Li2Juliang Jin3Chengguo Wu4Rongxing Zhou5College of Civil Engineering, Anhui Jianzhu University, Hefei 230601, ChinaCollege of Civil Engineering, Anhui Jianzhu University, Hefei 230601, ChinaCollege of Civil Engineering, Anhui Jianzhu University, Hefei 230601, ChinaCollege of Civil Engineering, Hefei University of Technology, Hefei 230009, ChinaCollege of Civil Engineering, Hefei University of Technology, Hefei 230009, ChinaSchool of Environment and Energy Engineering, Anhui Jianzhu University, Hefei 230601, ChinaVariability identification and uncertainty characteristic analysis, under the impacts of climate change and human activities, is beneficial for accurately predicting the future evolution trend of hydrological variables. In this study, based on the evolution trend and characteristic analyses of historical precipitation and temperature sequences from monthly, annual, and interannual scales through the Linear Tendency Rate (LTR) index, as well as its variability point identification using the M–K trend test method, we further utilized three cloud characteristic parameters comprising the average <i>Ex</i>, entropy <i>En</i>, and hyper-entropy <i>He</i> of the Cloud Model (CM) method to quantitatively reveal the uncertainty features corresponding to the diverse cloud distribution of precipitation and temperature sample scatters. And then, through an application analysis of the proposed research framework in Anhui Province, China, the following can be summarized from the application results: (1) The annual precipitation of Anhui Province presented a remarkable decreasing trend from south to north and an annual increasing trend from 1960 to 2020, especially in the southern area, with the LTR index equaling 55.87 mm/10a, and the annual average temperature of the entire provincial area also presented an obvious increasing trend from 1960 to 2020, with LTR equaling about 0.226 °C/10a. (2) The uncertainty characteristic of the precipitation series was evidently intensified after the variability points in 2013 and 2014 in the southern and provincial areas, respectively, according to the derived values of entropy <i>En</i> and hyper-entropy <i>He</i>, which are basically to the contrary for the historical annual average temperature series in southern Anhui Province. (3) The obtained result was basically consistent with the practical statistics of historical hydrological and disaster data, indicating that the proposed research methodologies can be further applied in related variability diagnosis analyses of non-stationary hydrological variables.https://www.mdpi.com/1099-4300/27/3/305variability identificationuncertaintyentropyLTRCMAnhui Province |
| spellingShingle | Xia Bai Jinhuang Yu Yule Li Juliang Jin Chengguo Wu Rongxing Zhou Variability Identification and Uncertainty Evolution Characteristic Analysis of Hydrological Variables in Anhui Province, China Entropy variability identification uncertainty entropy LTR CM Anhui Province |
| title | Variability Identification and Uncertainty Evolution Characteristic Analysis of Hydrological Variables in Anhui Province, China |
| title_full | Variability Identification and Uncertainty Evolution Characteristic Analysis of Hydrological Variables in Anhui Province, China |
| title_fullStr | Variability Identification and Uncertainty Evolution Characteristic Analysis of Hydrological Variables in Anhui Province, China |
| title_full_unstemmed | Variability Identification and Uncertainty Evolution Characteristic Analysis of Hydrological Variables in Anhui Province, China |
| title_short | Variability Identification and Uncertainty Evolution Characteristic Analysis of Hydrological Variables in Anhui Province, China |
| title_sort | variability identification and uncertainty evolution characteristic analysis of hydrological variables in anhui province china |
| topic | variability identification uncertainty entropy LTR CM Anhui Province |
| url | https://www.mdpi.com/1099-4300/27/3/305 |
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