Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over Southwest China during 1960–2013

Zhao, Yifei; Zou, Xinqing; Cao, Liguo; Yao, Yulong; Fu, Guanghe

doi:10.1007/s00704-017-2216-4

Cited by 21 publications

(8 citation statements)

References 36 publications

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“…Province. Similar to some previous studies in China [6,21,32,33,48,64,65]. We found that the climate of Jiangsu province also exhibited different dry-wet trends in different seasons and annually during 1960-2019 (Figure 3).…”

Section: Dry and Wet Trends In Jiangsusupporting

confidence: 89%

“…e HI was most sensitive to Pre in Jiangsu province for the period 1960-2019 (Figure 4(e)). is is consistent with results for both the entire northwestern and southwestern parts of China [34,65]. Wang et al [6] also found that dry-wet conditions were most sensitive to Pre in the humid regions of China that had annual precipitation >800 mm.…”

Section: Sensitivity Of Humidity Index (Hi) To Meteorologicalsupporting

confidence: 86%

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Spatiotemporal Climate Variation and Analysis of Dry-Wet Trends for 1960–2019 in Jiangsu Province, Southeastern China

Qin

Zhang

Wan

et al. 2022

Advances in Meteorology

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The spatiotemporal characteristics of dry-wet trends were identified and assessed, and the dominant meteorological factors were identified for the climate of Jiangsu province in humid southeastern China for the period 1960–2019. We conducted the research using data for the entire Jiangsu province as well as three major regions in Jiangsu (Huaibei, Jianghuai, and Sunan) with different regional climates. The results showed that decreased precipitation and relative humidity in spring and autumn over the study period were mainly responsible for the dry trends of the climates of all three regions and the entire province. Precipitation had a greater influence in spring and relative humidity in autumn. Decreases in sunshine hours and wind speed were responsible for the summer wet trends of the climates of Huaibei and Jianghuai and the entire province. However, precipitation increased significantly in the summer and was responsible for the increasing wet trend in Sunan. Significantly increased precipitation in winter was primarily responsible for the increasing wetness in Jianghuai and Sunan and the entire province in that season. However, the wet trend in northern Huaibei in winter was mainly caused by the decrease in wind speed over the study period. For the growing season and annually, the positive effects of changes in wind speed, sunshine hours, and precipitation led to increased humidity index in Jianghuai, Sunan, and the entire province. Precipitation showed a decreasing trend that countered the positive effects of decreases in wind speed and sunshine hours, which resulted in a slight decrease in the humidity index in Huaibei for both the growing season and annually. Sensitivity analysis indicated that the humidity index was positively sensitive to precipitation and relative humidity and negatively sensitive to air temperature, wind speed, and sunshine hours in Jiangsu province during 1960–2019. Overall, the humidity index in this region of southeastern China was most sensitive to changes in precipitation followed, in order of sensitivity, by sunshine hours, air temperature, wind speed, and relative humidity. Our findings provide a theoretical basis for adjusting irrigation programs and efficient utilization of water resources at the regional scale in humid southeastern China.

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Section: Dry and Wet Trends In Jiangsusupporting

confidence: 89%

Section: Sensitivity Of Humidity Index (Hi) To Meteorologicalsupporting

confidence: 86%

Spatiotemporal Climate Variation and Analysis of Dry-Wet Trends for 1960–2019 in Jiangsu Province, Southeastern China

Qin

Zhang

Wan

et al. 2022

Advances in Meteorology

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“…A similar area of northwest China showed similar findings [38]. In addition, the AI calculated with the same formula in the Loess Plateau [60], Tibetan Plateau [61], Yellow River Basin [32], and southwest China [62] and with the ratio between ET 0 and Pre in Northwest China [38] showed a declining trend, which indicated that these regions became wetter in the past 50 years. Considering the correlation coefficient between AI and climate factors, the dominant factor of the AI trend in the Yellow River basin was determined to be RH, followed by Pre [32].…”

Section: Discussionsupporting

confidence: 54%

Attribution Analysis of Long-Term Trends of Aridity Index in the Huai River Basin, Eastern China

Chu

Islam

et al. 2020

Sustainability

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This paper aims to combinedly investigate the spatiotemporal trends of precipitation (Pre), reference evapotranspiration (ET0), and aridity index (AI) by employing nonparametric methods based on daily datasets from 137 meteorological stations during 1961–2014 in the Huai River Basin (HRB). The dominant factors influencing ET0 and AI trends were also explored using the detrended and differential equation methods. Results show that (1) Pre, ET0, and AI were much larger in summer than in other seasons, and AI had a nonsignificant increasing trend in annual time scale, while Pre and ET0 exhibited decreasing trends, but AI showed a downward trend in spring and autumn (becoming drier) and an upward trend during summer and winter due to increased Pre (becoming wetter); (2) lower AI values were identified in north and higher in south, and lower ET0 was identified in south and higher in north in annual time scale, growing season and spring, while ET0 decreased from west to east in summer and winter, the spatial distribution of Pre was similar to that of AI; (3) for ET0 trends, in general, wind speed at two-meter height (u2) was the dominant factor in spring, autumn, winter, and annual time scale, while in other seasons, solar radiation (Rs) played a dominant role; (4) for AI trends, AI was mostly contributed by Pre in spring, autumn, and winter, the Rs contributed the most to AI trend in growing season and summer, then in annual time scale, u2 was the dominant factor; (5) overall, the contribution of Pre to AI trends was much larger than that of ET0 in spring, autumn, and winter, while AI was mostly contributed by ET0 in annual time scale, growing season and summer. The outcomes of the study may improve our scientific understanding of recent climate change effects on dry–wet variations in the HRB; moreover, this information may be utilized in other climatic regions for comparison analyses.

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“…Climate change has also had a profound impact on global glacial permafrost (Svoboda and Fuchs, 2017). In the Siberian permafrost region, its southern boundary has retreated substantially in the past decades, and the permafrost that has been silent for many years shows increasingly active signs, leading to the deepening of the active layer, the lengthening of the ablation period, and even complete ablation (Zhao et al, 2018). Also, permafrost ablation affects groundwater supply and water resources (Dai et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Characteristics of Seasonal Frozen Soil in Hetao Irrigation District under Climate Change

Duan

Wang²,

Li³

2021

J ENVIRON INFORM LET

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Seasonal freezing and thawing is a major cause of serious soil salinization in Hetao irrigation area under climate change. In this paper, the Hetao irrigation area has been selected as an example and field monitoring experiments were used to analyze and study the dynamics of soil water, salt, and heat during freezing and thawing periods. The research results show that the unfrozen water presents a "concave" shape change, and as the degree of freezing deepens, the total water content continues to increase; the salt content also shows an increasing trend, with the 0 ~ 100 cm soil layer salt rate being 43.73%, of which 0 ~ 10 cm soil layer is 91.56%, followed by the 10 ~ 20 cm soil layer, which is 41.78%. The surface aggregation effect is obvious. The temperature data obtained by analysis shows that the freezing process is one-way freezing and the melting process is two-way melting. The above analysis results can provide a scientific basis for scientific planting and soil salinization prevention and control in irrigation areas.

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Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over Southwest China during 1960–2013

Cited by 21 publications

References 36 publications

Spatiotemporal Climate Variation and Analysis of Dry-Wet Trends for 1960–2019 in Jiangsu Province, Southeastern China

Spatiotemporal Climate Variation and Analysis of Dry-Wet Trends for 1960–2019 in Jiangsu Province, Southeastern China

Attribution Analysis of Long-Term Trends of Aridity Index in the Huai River Basin, Eastern China

Characteristics of Seasonal Frozen Soil in Hetao Irrigation District under Climate Change

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