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中国水资源的未来趋势及其对农业的影响。

Future trends of water resources and influences on agriculture in China.

机构信息

School of Business, Henan Normal University, Xinxiang, Henan, China.

Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, China.

出版信息

PLoS One. 2020 Apr 17;15(4):e0231671. doi: 10.1371/journal.pone.0231671. eCollection 2020.

DOI:10.1371/journal.pone.0231671
PMID:32302331
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7164664/
Abstract

Water resources are indispensable for all social-economic activities and ecosystem functions. In addition, changes in water resources have great significance for agricultural production. This paper uses five global climate models from CMIP5 to evaluate the future spatiotemporal variation in water resources in China under four RCP scenarios. The results show that the available precipitation significantly decreases due to evapotranspiration. Comparing the four RCP scenarios, the national average of the available precipitation is the highest under the RCP 2.6 and 4.5 scenarios, followed by that under the RCP 8.5 scenario. In terms of spatial distribution, the amount of available precipitation shows a decreasing trend from southeast to northwest. Regarding temporal changes, the available precipitation under RCP 8.5 exhibits a trend of first increasing and then decreasing, while the available precipitation under the RCP 6.0 scenario exhibits a trend of first decreasing and then increasing. Under the RCP 2.6 and 4.5 scenarios, the available precipitation increases, and the RCP 4.5 scenario has a higher rate of increase than that of RCP 2.6. In the context of climate change, changes in water resources and temperature cause widespread increases in potential agricultural productivity around Hu's line, especially in southwestern China. However, the potential agricultural productivity decreases in a large area of southeastern China. Hu's line has a partial breakthrough in the locking of agriculture, mainly in eastern Tibet, western Sichuan, northern Yunnan and northwestern Inner Mongolia. The results provide a reference for the management and deployment of future water resources and can aid in agricultural production in China.

摘要

水资源是所有社会经济活动和生态系统功能不可或缺的。此外,水资源的变化对农业生产具有重要意义。本文利用 CMIP5 中的五个全球气候模型,评估了在四种 RCP 情景下中国未来水资源的时空变化。结果表明,由于蒸散作用,可用降水量显著减少。在比较四种 RCP 情景时,RCP2.6 和 4.5 情景下的全国平均可用降水量最高,其次是 RCP8.5 情景。在空间分布方面,可用降水量呈东南向西北递减的趋势。关于时间变化,RCP8.5 下的可用降水量呈先增加后减少的趋势,而 RCP6.0 情景下的可用降水量呈先减少后增加的趋势。在 RCP2.6 和 4.5 情景下,可用降水量增加,RCP4.5 情景下的增长率高于 RCP2.6。在气候变化背景下,水资源和温度的变化导致胡焕庸线周围的潜在农业生产力普遍增加,特别是在中国西南部。然而,中国东南部大面积的潜在农业生产力下降。胡焕庸线在农业方面的锁定出现部分突破,主要在西藏东部、四川西部、云南北部和内蒙古西北部。研究结果为未来水资源的管理和部署提供了参考,并有助于中国的农业生产。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/64ec19b71411/pone.0231671.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/269fa423822b/pone.0231671.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/09d9ee7685a1/pone.0231671.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/af3bcc9b4d1e/pone.0231671.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/72dcf166c4f2/pone.0231671.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/d3b7fdd6b4bf/pone.0231671.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/045a2d371d42/pone.0231671.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/5b953938fdb9/pone.0231671.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/062342f8c4cc/pone.0231671.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/64ec19b71411/pone.0231671.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/269fa423822b/pone.0231671.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/09d9ee7685a1/pone.0231671.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/af3bcc9b4d1e/pone.0231671.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/72dcf166c4f2/pone.0231671.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/d3b7fdd6b4bf/pone.0231671.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/045a2d371d42/pone.0231671.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/5b953938fdb9/pone.0231671.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/062342f8c4cc/pone.0231671.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/585c/7164664/64ec19b71411/pone.0231671.g009.jpg

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