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| DOI：10.13522/j.cnki.ggps.2023223 |
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| Spatiotemporal temperature variation in soil in Wudaogou area and its modelling using the SARIMA model |
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JIANG Xinping, WANG Qimeng, LIU Meng, WANG Faxin,
LYU Haishen, CHEN Yu, LI Jie, WANG Zhenlong
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1. Hohai University, Nanjing 210098, China; 2. Huaihe River Water Conservancy Commission, Ministry of Water Resources,
Bengbu 233000, China; 3. Anhui Province (Huaihe Commission, Ministry of Water Resources)
Institute of Water Resources Science, Hefei 230088, China
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| Abstract: |
| 【Objective】Soil temperature is not only important for hydrological processes but also plays an imperative role in crop growth and soil biochemical reactions. Understanding its spatiotemporal variation is crucial to improving soil and hydrological management. The purpose of this paper is to investigate the applicability of the SARIMA model to model spatiotemporal change in temperature across the entire soil profile.【Method】The study is based on temperatures measured from 1964 to 2022 across a 0-320 cm profile located at the Wudaogou Hydrological Experimental Station, in Anhui province, China. Linear regression, Sen's slope estimation, MK test and other methods are used to analyze the seasonal change in temperature in different soil layers, and to establish the SARIMA model.【Result】① In spring and winter, the temperature in 0-160 cm soil layer had been in increase from 1964 to 2022 at significant levels. Except in the 0-10 cm soil, summer temperature in other soil layers had been in decrease from 1964 to 2022 at significant levels. In the fall, the temperature had been increasing in the 0 and 20 cm soil layer, but decreasing in other soil layers. ② The temperature in depths of 0, 10, 20, 40, and 160 cm had endured sudden drops in spring in 2006, 2013, 2012, 2015 and 2018, followed by significant increases. Since 1984, temperature in the 320 cm soil layer had begun to decrease significantly. ③ The correlation between measured and predicted temperature was >0.95. With the increase in soil depth, the correlation increases, MAE decreases from 1.666 to 0.390, and the RMSE decreases from 2.139 to 0.525.【Conclusion】The SARMA model is accurate to model spatiotemporal change in soil temperature across the entire 0-320 cm soil profile in Huaibei Plain area. |
| Key words: soil temperature; characteristics of change; time series; SARIMA model |
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