Climate Impact on Irrigation Water Use in Jiangsu Province, China: An Analysis Using Empirical Mode Decomposition (EMD)

Abstract

In this paper, the quantitative effects of climatic factor changes on irrigation water use were analyzed in Jiangsu Province from 2004 to 2020 using the Empirical Mode Decomposition (EMD) time-series analysis method. In general, the irrigation water use, precipitation (P), air temperature (T), wind speed (Ws), relative humidity (Rh) and water vapor pressure (Vp) annual means ± standard deviation were 25.44 ± 1.28 billion m3, 1034.4 ± 156.6 mm, 16.1 ± 0.4 °C, 2.7 ± 0.2 m·s−1, 74 ± 2%, and 15.5 ± 0.6 hPa, respectively. The analysis results of the irrigation water use sequence using EMD indicate three main change frequencies for irrigation water use. The first major change frequency (MCF1) was a 2-to-3-year period varied over a ±1.00 billion m3 range and showed a strong correlation with precipitation (the Pearson correlation was 0.68, p < 0.05). The second major change frequency (MCF2) was varied over a ±2.00 billion m3 range throughout 10 years. The third major change frequency (MCF3) was a strong correlation with air temperature, wind speed, relative humidity, and water vapor pressure (the Pearson correlations were 0.56, 0.75, 0.71, and 0.69, respectively, p < 0.05). In other words, MCF1 and MCF3 represent the irrigation water use changes influenced by climate factors. Furthermore, we developed the Climate–Irrigation–Water Model based on farmland irrigation theory to accurately assess the direct effects of climate factor changes on irrigation water use. The model effectively simulated irrigation water use changes with a root mean square error (RMSE) of 0.06 billion m3, representing 2.24% of the total. The findings from the model indicate that climate factors have an average impact of 6.40 billion m3 on irrigation water use, accounting for 25.14% of the total. Specifically, precipitation accounted for 3.04 billion m3 of the impact, while the combined impact of other climatic factors was 3.36 billion m3.