Variability Identification and Uncertainty Evolution Characteristic Analysis of Hydrological Variables in Anhui...

Area of Science:

• Hydrology
• Climate Science
• Data Analysis

Background:

• Accurate prediction of hydrological variables is crucial for understanding climate change and human impacts.
• Identifying variability and uncertainty is key to improving hydrological forecasting models.

Purpose of the Study:

• To analyze historical precipitation and temperature trends and their uncertainty characteristics in Anhui Province.
• To apply a novel framework combining trend analysis and cloud model uncertainty quantification.

Main Methods:

• Linear Tendency Rate (LTR) index for trend analysis.
• Mann-Kendall (M-K) trend test for variability point identification.
• Cloud Model (CM) with parameters Ex, En, and He for uncertainty analysis.

Main Results:

• Anhui's annual precipitation shows a south-to-north decrease and an overall increase (1960-2020).
• Annual average temperature increased significantly across Anhui (1960-2020).
• Precipitation uncertainty intensified post-2013/2014, contrasting with temperature trends.

Conclusions:

• The proposed methodology effectively diagnoses variability and uncertainty in hydrological data.
• Findings align with historical hydrological and disaster data, validating the approach.
• This framework can be applied to analyze non-stationary hydrological variables under climate change.