Dominant Impacting Factors on Water-Use Efficiency Variation in Inner Mongolia from 2001 to 2018: Vegetation or Climate?
Water-use efficiency (WUE) is not only an important indicator to connect the carbon and water cycles of a terrestrial ecosystem, but also a key parameter for an ecosystem to respond to climate change. It is crucial for understanding the mechanism of regional ecosystem response to environmental chang...
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MDPI AG
2022-09-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/18/4541 |
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| author | Hao Luo Xiaojuan Bie Guihua Yi Xiaobing Zhou Tingbin Zhang Jingji Li Pingqing Lai |
| author_facet | Hao Luo Xiaojuan Bie Guihua Yi Xiaobing Zhou Tingbin Zhang Jingji Li Pingqing Lai |
| author_sort | Hao Luo |
| collection | DOAJ |
| description | Water-use efficiency (WUE) is not only an important indicator to connect the carbon and water cycles of a terrestrial ecosystem, but also a key parameter for an ecosystem to respond to climate change. It is crucial for understanding the mechanism of regional ecosystem response to environmental change by researching the influences of vegetation and climate change on WUE variation and revealing its drivers. Based on trend analysis, grey relational analysis, and ridge-regression analysis, this study analyzed the spatiotemporal variation characteristics of WUE in Inner Mongolia (IM) from 2001 to 2018 and determined the dominant influencing factors of WUE variation. The results showed that the annual mean WUE in IM was 1.39 g C m<sup>−2</sup> mm<sup>−1</sup> and it generally presented a rising trend, with an increasing rate of 0.0071 g C m<sup>−2</sup> mm<sup>−1</sup> yr<sup>−1</sup>. Leaf-area index (LAI) and precipitation were the most important factors influencing WUE in IM, followed by relative humidity and wind speed. Temperature, water vapor pressure and sunshine duration slightly influenced WUE and they were relatively less important. According to the ridge-regression analysis, LAI, precipitation and relative humidity had a positive contribution to WUE variation, while the wind speed had a negative contribution. Regionally, LAI was the dominant cause of WUE variation. The contribution and relative contribution rate of LAI to WUE variation were 0.008 g C m<sup>−2</sup> mm<sup>−1</sup> yr<sup>−1</sup> and 44.57%, which were significantly higher than those of precipitation, relative humidity, and sunshine duration. Thus, vegetation primarily dominated WUE variability during the study period. The relative contribution rate of LAI varied across the different vegetation types and ranged from 25.26% in swamps to 51.29% in meadows. Our results improve the understanding of the effects of driving factors on WUE, which can help policymakers with water resource management and ecological restoration. |
| first_indexed | 2024-03-09T22:38:50Z |
| format | Article |
| id | doaj.art-8c61cd1196c94a17b461156f9d7ba623 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T22:38:50Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-8c61cd1196c94a17b461156f9d7ba6232023-11-23T18:44:21ZengMDPI AGRemote Sensing2072-42922022-09-011418454110.3390/rs14184541Dominant Impacting Factors on Water-Use Efficiency Variation in Inner Mongolia from 2001 to 2018: Vegetation or Climate?Hao Luo0Xiaojuan Bie1Guihua Yi2Xiaobing Zhou3Tingbin Zhang4Jingji Li5Pingqing Lai6College of Earth Science, Chengdu University of Technology, Chengdu 610059, ChinaCollege of Tourism and Urban-Rural Planning, Chengdu University of Technology, Chengdu 610059, ChinaCollege of Tourism and Urban-Rural Planning, Chengdu University of Technology, Chengdu 610059, ChinaGeological Engineering Department, Montana Technological University, Butte, MT 59701, USACollege of Earth Science, Chengdu University of Technology, Chengdu 610059, ChinaState Environmental Protection Key Laboratory of Synergetic Control and Joint Remediation for Soil & Water Pollution, Chengdu University of Technology, Chengdu 610059, ChinaCollege of Earth Science, Chengdu University of Technology, Chengdu 610059, ChinaWater-use efficiency (WUE) is not only an important indicator to connect the carbon and water cycles of a terrestrial ecosystem, but also a key parameter for an ecosystem to respond to climate change. It is crucial for understanding the mechanism of regional ecosystem response to environmental change by researching the influences of vegetation and climate change on WUE variation and revealing its drivers. Based on trend analysis, grey relational analysis, and ridge-regression analysis, this study analyzed the spatiotemporal variation characteristics of WUE in Inner Mongolia (IM) from 2001 to 2018 and determined the dominant influencing factors of WUE variation. The results showed that the annual mean WUE in IM was 1.39 g C m<sup>−2</sup> mm<sup>−1</sup> and it generally presented a rising trend, with an increasing rate of 0.0071 g C m<sup>−2</sup> mm<sup>−1</sup> yr<sup>−1</sup>. Leaf-area index (LAI) and precipitation were the most important factors influencing WUE in IM, followed by relative humidity and wind speed. Temperature, water vapor pressure and sunshine duration slightly influenced WUE and they were relatively less important. According to the ridge-regression analysis, LAI, precipitation and relative humidity had a positive contribution to WUE variation, while the wind speed had a negative contribution. Regionally, LAI was the dominant cause of WUE variation. The contribution and relative contribution rate of LAI to WUE variation were 0.008 g C m<sup>−2</sup> mm<sup>−1</sup> yr<sup>−1</sup> and 44.57%, which were significantly higher than those of precipitation, relative humidity, and sunshine duration. Thus, vegetation primarily dominated WUE variability during the study period. The relative contribution rate of LAI varied across the different vegetation types and ranged from 25.26% in swamps to 51.29% in meadows. Our results improve the understanding of the effects of driving factors on WUE, which can help policymakers with water resource management and ecological restoration.https://www.mdpi.com/2072-4292/14/18/4541WUELAIgrey relational analysisridge regressionInner Mongolia |
| spellingShingle | Hao Luo Xiaojuan Bie Guihua Yi Xiaobing Zhou Tingbin Zhang Jingji Li Pingqing Lai Dominant Impacting Factors on Water-Use Efficiency Variation in Inner Mongolia from 2001 to 2018: Vegetation or Climate? Remote Sensing WUE LAI grey relational analysis ridge regression Inner Mongolia |
| title | Dominant Impacting Factors on Water-Use Efficiency Variation in Inner Mongolia from 2001 to 2018: Vegetation or Climate? |
| title_full | Dominant Impacting Factors on Water-Use Efficiency Variation in Inner Mongolia from 2001 to 2018: Vegetation or Climate? |
| title_fullStr | Dominant Impacting Factors on Water-Use Efficiency Variation in Inner Mongolia from 2001 to 2018: Vegetation or Climate? |
| title_full_unstemmed | Dominant Impacting Factors on Water-Use Efficiency Variation in Inner Mongolia from 2001 to 2018: Vegetation or Climate? |
| title_short | Dominant Impacting Factors on Water-Use Efficiency Variation in Inner Mongolia from 2001 to 2018: Vegetation or Climate? |
| title_sort | dominant impacting factors on water use efficiency variation in inner mongolia from 2001 to 2018 vegetation or climate |
| topic | WUE LAI grey relational analysis ridge regression Inner Mongolia |
| url | https://www.mdpi.com/2072-4292/14/18/4541 |
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