苏晨芳1, 2
1.中国科学院地理科学与资源研究所陆地水循环及地表过程重点实验室 北京 100101
2.中国科学院大学 北京 101408
基金项目: 中国科学院战略性先导科技专项XDA20040302
国家自然科学基金面上项目41671354
详细信息
作者简介:田静, 研究方向为遥感水文。E-mail: tianj.04b@igsnrr.ac.cn
中图分类号:P967计量
文章访问数:320
HTML全文浏览量:15
PDF下载量:82
被引次数:0
出版历程
收稿日期:2020-06-01
录用日期:2020-10-06
刊出日期:2021-02-01
Variations in and predictions of irrigation water requirements of cotton and winter wheat in Central Asia
TIAN Jing1,,,SU Chenfang1, 2
1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2. University of Chinese Academy of Sciences, Beijing 101408, China
Funds: the Strategic Priority Research Program of Chinese Academy of SciencesXDA20040302
the National Natural Science Foundation of China41671354
More Information
Corresponding author:TIAN Jing, E-mail: tianj.04b@igsnrr.ac.cn
摘要
HTML全文
图
参考文献
相关文章
施引文献
资源附件
访问统计
摘要
摘要:农业灌溉用水是中亚地区最主要的水资源利用方式，灌溉用水量的变化直接影响中亚地区水资源消耗量，进而影响水资源管理和配置。作物需水量是衡量农业灌溉用水量的直接指标，为此本文以中亚主要作物棉花和冬小麦为研究对象，分析了2006-2015年中亚地区灌溉农业用地，以及棉花和冬小麦的需水量变化，并利用CA_Markov方法预测了2030年灌溉农地的变化，进而分析了未来中亚地区农业需水量的状况。研究表明，2006-2015年，中亚地区灌溉农田面积总体增加492 km2，其中哈萨克斯坦、吉尔吉斯斯坦和土库曼斯坦均有所增加，但塔吉克斯坦和乌兹别克斯坦有所减少。2006-2015年，棉花需水量只在土库曼斯坦和哈萨克斯坦东部地区显著增加（2.5~4.3 mm·a-1），在吉尔吉斯斯坦显著减少，并且是唯一呈现总体减少趋势的国家。冬小麦需水量在土库曼斯坦明显增加（10.0 mm·a-1）。至2015年，土库曼斯坦的棉花总灌溉水量增幅最大（3.44%），其他4个国家变化较小。中亚五国冬小麦的总灌溉水量均呈上升趋势；2030年，土库曼斯坦是唯一灌溉农业用地增加的国家，棉花和冬小麦的总灌溉水量均明显增加，棉花灌溉水量增加约28 km3，冬小麦增加约17 km3。
关键词:中亚五国/
灌溉农地/
作物需水量/
棉花和冬小麦
Abstract:Agricultural irrigation consumes most of the fresh water in Central Asia (CA). Therefore, changes in irrigation water use have direct effects on water resources, water management, and water resource allocation. The crop water requirement (CWR) is a direct indicator of agricultural irrigation; the CWR of cotton and winter wheat (the two main crops of CA) was investigated in this study. Based on the CWR method proposed by the Food and Agriculture Organization (FAO), the CWR and total irrigation water of cotton and winter wheat in irrigated croplands in CA were calculated from 2006 to 2015. Changes in the irrigation cropland area and cotton and winter wheat CWR from 2006 to 2015 were also analyzed. To assess the near-future status of agricultural water resources in CA, the irrigated cropland area in 2030 was predicted via the CA_Markov method, and the CWR of the two crops in 2030 was explored. Land cover data from the European Space Agency Climate Change Initiative (ESA CCI) was used to identify the irrigation cropland. Digital Elevation Model (DEM) data from the Shuttle Radar Topography Mission (SRTM), population density data from the Socioeconomic Data and Applications Center, and river vector data from Natural Earth were used to predict the irrigated cropland area in 2030. The results showed that irrigated cropland in CA increased by 492 km2 from 2006 to 2015, with increases in Kazakhstan, Kyrgyzstan, and Turkmenistan, and decreases in Tajikistan and Uzbekistan. The CWR of cotton and winter wheat tended to increase in most areas. The CWR of cotton increased rapidly from 2006 to 2015 (2.5-4.3 mm·a-1) in Turkmenistan and eastern Kazakhstan but decreased in Kyrgyzstan. For winter wheat, the largest CWR increase (10 mm·a-1) was in Turkmenistan, and no changes were observed in the other four CA countries. In 2030, the irrigated cropland in Turkmenistan was predicted to increase by 30.5% compared with 2015, and Turkmenistan is the only country to increase irrigated croplands in the near future. This will lead to a notable increase in the CWR of cotton and winter wheat. The results showed that there will be an increase of 28 km3 for the total irrigation water of cotton and 17 km3 for winter wheat in Turkmenistan in 2030. The other four countries were predicted to have decreased irrigation cropland compared with 2015, with decreases of 7.4%, 5.8%, 3.4%, and 0.9% for Uzbekistan, Tajikistan, Kazakhstan, and Kyrgyzstan, respectively. Although Uzbekistan is predicted to decrease irrigation cropland in 2030, the increase in winter wheat CWR will increase the total irrigation water by 10-14 km3. Therefore, Uzbekistan and Turkmenistan will face severe shortages in irrigation water resources in the near future.
Key words:Five Central Asian Countries/
Irrigated cropland/
Crop water requirement/
Cotton and winter wheat
HTML全文
图12015年中亚五国灌溉农业用地空间分布图(数据来源: CCI土地利用数据)
Figure1.Irrigated cropland over Central Asia in 2015 (CCI land cover product)
下载: 全尺寸图片幻灯片
图22006-2015年中亚五国及各国灌溉耕地面积的年际变化
Figure2.Variations of irrigated cropland areas over Central Asia and the five countries from 2006 to 2015
下载: 全尺寸图片幻灯片
图3中亚地区2006年(a)和2015年(b)棉花作物需水量的空间分布及其2006-2015年变化趋势(c)和变化率(d)的空间分布
Figure3.Spatial distributions of cotton water requirements in 2006 (a) and 2015 (b), and its trend slope (c) and relative change (d) from 2006 to 2015 in Central Asia
下载: 全尺寸图片幻灯片
图4中亚地区2006年(a)和2015年(b)冬小麦作物需水量的空间分布及其2006-2015年变化趋势(c)和变化率(d)的空间分布
Figure4.Spatial distributions of winter wheat water requirements in 2006 (a) and 2015 (b), and its trend slope (c) and relative change (d) from 2006 to 2015 in Central Asia
下载: 全尺寸图片幻灯片
图5中亚五国2006-2015年棉花(a)和冬小麦(b)需水量年际变化趋势图
Figure5.Annual variations of water requirements of cotton (a) and winter wheat (b) for the five Central Asian countries from 2006 to 2015
下载: 全尺寸图片幻灯片
图6中亚五国2015年和2030年RCP2.6和RCP4.5情景下棉花和冬小麦需水量和总灌溉需水量
Figure6.Crop water requirements and total irrigation water of winter wheat and cotton for the five Central Asian countries under RCP2.6 and RCP4.5 in 2015 and 2030
下载: 全尺寸图片幻灯片表1中亚地区冬小麦和棉花在4个生长阶段的作物系数(Kc)值
Table1.Crop coefficient (Kc) values for cotton and winter wheat at four growth stages in Central Asia
| 作物 Crop | 种植期 Planting time | 发育期 Development stage | 生长中期 Mid-growth-season | 收获期 Harvest stage | |
| 时间 Time | 棉花 Cotton | 4月初 Early Apri | 10月初 Early October | ||
| 冬小麦 Winter wheat | 10月中 Mid October | 6月初 Early June | |||
| 天数 Duration (d) | 棉花 Cotton | 30 | 50 | 55 | 45 |
| 冬小麦 Winter wheat | 30 | 140 | 40 | 30 | |
| Kc | 棉花 Cotton | 0.55 | 0.55 | 0.95~1.15 | 0.65 |
| 冬小麦 Winter wheat | 0.65 | 0.65 | 1.15 | 0.65 |
下载: 导出CSV表22006-2015年中亚五国种植棉花、冬小麦总灌溉需水量
Table2.Irrigation water requirements of cotton and winter wheat for the five Central Asian countries from 2006 to 2015?
| 作物 Crop | 国家 Country | 2006 | 2008 | 2010 | 2012 | 2015 | 变化率 Change rate (%) |
| 棉花 Cotton | 哈萨克斯坦 Kazakhstan | 127.7 | 130.4 | 131.1 | 132.4 | 128.8 | 0.82 |
| 吉尔吉斯斯坦 Kyrghyzstan | 33.6 | 35.4 | 35.9 | 35.6 | 33.7 | 0.17 | |
| 塔吉克斯坦 Tajikistan | 21.8 | 22.8 | 22.9 | 22.6 | 22.1 | 1.30 | |
| 土库曼斯坦 Turkmenistan | 78.8 | 82.1 | 81.9 | 82.8 | 81.6 | 3.44 | |
| 乌兹别克斯坦 Uzbekistan | 144.1 | 149.1 | 148.6 | 148.0 | 143.5 | -0.38 | |
| 冬小麦 Winter wheat | 哈萨克斯坦 Kazakhstan | 54.1 | 56.6 | 57.5 | 56.6 | 58.3 | 3.69 |
| 吉尔吉斯斯坦 Kyrghyzstan | 9.5 | 10.3 | 10.9 | 10.5 | 11.7 | 9.88 | |
| 塔吉克斯坦 Tajikistan | 5.0 | 6.2 | 6.4 | 6.1 | 7.0 | 21.79 | |
| 土库曼斯坦 Turkmenistan | 45.6 | 50.7 | 49.8 | 49.9 | 51.3 | 11.17 | |
| 乌兹别克斯坦 Uzbekistan | 65.6 | 69.7 | 71.0 | 68.8 | 72.6 | 3.99 | |
| 合计 Total | 哈萨克斯坦 Kazakhstan | 181.8 | 187.0 | 188.6 | 189.0 | 187.1 | |
| 吉尔吉斯斯坦 Kyrghyzstan | 43.1 | 45.7 | 46.8 | 46.1 | 45.4 | ||
| 塔吉克斯坦 Tajikistan | 26.8 | 29.0 | 29.3 | 28.7 | 29.1 | ||
| 土库曼斯坦 Turkmenistan | 124.4 | 132.8 | 131.7 | 132.7 | 132.9 | ||
| 乌兹别克斯坦 Uzbekistan | 209.7 | 218.8 | 219.6 | 216.8 | 216.1 |
下载: 导出CSV表32015年和2030年中亚五国农业用地灌溉面积对比
Table3.Comparisons of irrigated cropland areas between 2015 and 2030 for the five Central Asian countries
| 国家 Country | 灌溉农地面积 Irrigated cropland area | ||
| 2015 (km2) | 2030 (km2) | 变化率 Change rate (%) | |
| 哈萨克斯坦 Kazakhstan | 86 269 | 83 363 | -3.4 |
| 吉尔吉斯斯坦 Kyrghyzstan | 32 178 | 31 902 | -0.9 |
| 塔吉克斯坦 Tajikistan | 14 283 | 13 456 | -5.8 |
| 土库曼斯坦 Turkmenistan | 40 233 | 52 516 | 30.5 |
| 乌兹别克斯坦 Uzbekistan | 81 198 | 75 229 | -7.4 |
下载: 导出CSV参考文献
| [1] | 杨胜天, 于心怡, 丁建丽, 等. 中亚地区水问题研究综述[J]. 地理学报, 2017, 72(1): 79-93 https://www.cnki.com.cn/Article/CJFDTOTAL-DLXB201701008.htm YANG S T, YU X Y, DING J L, et al. A review of water issues research in Central Asia[J]. Acta Geographica Sinica, 2017, 72(1): 79-93 https://www.cnki.com.cn/Article/CJFDTOTAL-DLXB201701008.htm |
| [2] | TIAN J, ZHANG Y Q. Detecting changes in irrigation water requirement in Central Asia under CO2 fertilization and land use changes[J]. Journal of Hydrology, 2020, 583: 124315 doi: 10.1016/j.jhydrol.2019.124315 |
| [3] | RUAN H W, YU J J, WANG P, et al. Increased crop water requirements have exacerbated water stress in the arid transboundary rivers of Central Asia[J]. Science of The Total Environment, 2020, 713: 136585 doi: 10.1016/j.scitotenv.2020.136585 |
| [4] | 邓铭江, 龙爱华, 章毅, 等. 中亚五国水资源及其开发利用评价[J]. 地球科学进展, 2010, 25(12): 1347-1356 https://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ201012007.htm DENG M J, LONG A H, ZHANG Y, et al. Assessment of water resources development and utilization in the five Central Asia countries[J]. Advances in Earth Science, 2010, 25(12): 1347-1356 https://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ201012007.htm |
| [5] | YULDASHEVA G, HASHIMOVA U, CALLAHAN J. Current trends in water management in Central Asia[J]. Peace and Conflict Review, 2010, 5(1): 1-5 http://www.review.upeace.org/pdf.cfm?articulo=105&ejemplar=20 |
| [6] | CONRAD C, RAHMANN M, MACHWITZ M, et al. Satellite based calculation of spatially distributed crop water requirements for cotton and wheat cultivation in Fergana Valley, Uzbekistan[J]. Global and Planetary Change, 2013, 110: 88-98 doi: 10.1016/j.gloplacha.2013.08.002 |
| [7] | ALLEN R G, PEREIRA L S, RAES D, et al. FAO irrigation and drainage paper No. 56: Crop evapotranspiration[R]. Rome: FAO, 2006 |
| [8] | YANG Y T, RODERICK M L, ZHANG S L, et al. Hydrologic implications of vegetation response to elevated CO2 in climate projections[J]. Nature Climate Change, 2019, 9(1): 44-48 doi: 10.1038/s41558-018-0361-0 |
| [9] | 阮宏威, 于静洁. 1992-2015年中亚五国土地覆盖与蒸散发变化[J]. 地理学报, 2019, 74(7): 1292-1304 https://www.cnki.com.cn/Article/CJFDTOTAL-DLXB201907003.htm RUAN H W, YU J J. Changes in land cover and evapotranspiration in the five Central Asian countries from 1992 to 2015[J]. Acta Geographica Sinica, 2019, 74(7): 1292-1304 https://www.cnki.com.cn/Article/CJFDTOTAL-DLXB201907003.htm |
| [10] | 岳东霞, 杨超, 江宝骅, 等. 基于CA-Markov模型的石羊河流域生态承载力时空格局预测[J]. 生态学报, 2019, 39(6): 1993-2003 https://www.cnki.com.cn/Article/CJFDTOTAL-STXB201906013.htm YUE D X, YANG C, JIANG B H, et al. Spatio-temporal pattern prediction of the biocapacity in the Shiyang River Basin on the basis of the CA-Markov model[J]. Acta Ecologica Sinica, 2019, 39(6): 1993-2003 https://www.cnki.com.cn/Article/CJFDTOTAL-STXB201906013.htm |
| [11] | 李丽, 刘普幸, 姚玉龙. 近28年金昌市土地利用动态变化及模拟预测[J]. 生态学杂志, 2015, 34(4): 1097-1104 https://www.cnki.com.cn/Article/CJFDTOTAL-STXZ201504030.htm LI L, LIU P X, YAO Y L. Land-use dynamic change of Jinchang City in the last 28 years and simulation prediction[J]. Chinese Journal of Ecology, 2015, 34(4): 1097-1104 https://www.cnki.com.cn/Article/CJFDTOTAL-STXZ201504030.htm |
| [12] | STULINA G. Recommendations on Hydromodule Zoning and Crop Irrigation Rate[R]. Tashkent: SIC ICWC, 2010 |
| [13] | ROST S, GERTEN D, BONDEAU A, et al. Agricultural green and blue water consumption and its influence on the global water system[J]. Water Resources Research, 2008, 44(9): W09405 doi: 10.1029/2007WR006331/full |
| [14] | 井云清, 张飞, 张月. 基于CA-Markov模型的艾比湖湿地自然保护区土地利用/覆被变化及预测[J]. 应用生态学报, 2016, 27(11): 3649-3658 https://www.cnki.com.cn/Article/CJFDTOTAL-YYSB201611030.htm JING Y Q, ZHANG F, ZHANG Y. Change and prediction of the land use/cover in Ebinur Lake Wetland Nature Reserve based on CA-Markov model[J]. Chinese Journal of Applied Ecology, 2016, 27(11): 3649-3658 https://www.cnki.com.cn/Article/CJFDTOTAL-YYSB201611030.htm |
| [15] | HAMAD R, BALZTER H, KOLO K. Predicting land use/land cover changes using a CA-Markov model under two different scenarios[J]. Sustainability, 2018, 10(10): 1-23 http://www.researchgate.net/publication/327868238_Predicting_Land_UseLand_Cover_Changes_Using_a_CA-Markov_Model_under_Two_Different_Scenarios |
| [16] | 韩其飞, 罗格平, 白洁, 等. 基于多期数据集的中亚五国土地利用/覆盖变化分析[J]. 干旱区地理, 2012, 35(6): 909-918 https://www.cnki.com.cn/Article/CJFDTOTAL-GHDL201206009.htm HAN Q F, LUO G P, BAI J, et al. Characteristics of land use and cover change in Central Asia in recent 30 years[J]. Arid Land Geography, 2012, 35(6): 909-918 https://www.cnki.com.cn/Article/CJFDTOTAL-GHDL201206009.htm |
| [17] | YU Y, PI Y Y, YU X, et al. Climate change, water resources and sustainable development in the arid and semi-arid lands of Central Asia in the past 30 years[J]. Journal of Arid Land, 2019, 11(1): 1-14 doi: 10.1007/s40333-018-0073-3 |
| [18] | 邓铭江, 龙爱华, 李湘权, 等. 中亚五国跨界水资源开发利用与合作及其问题分析[J]. 地球科学进展, 2010, 25(12): 1337-1346 https://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ201012006.htm DENG M J, LONG A H, LI X Q, et al. An analysis of the exploitation, cooperation and problems of trans-boundary water resources in the Five Central Asian Countries[J]. Advances in Earth Science, 2010, 25(12): 1337-1346 https://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ201012006.htm |
| [19] | 李嫱, 年雁云, 李新. 2000—2009年中亚阿姆河流域土地覆被时空变化分析[J]. 遥感技术与应用, 2017, 32(2): 218-227 https://www.cnki.com.cn/Article/CJFDTOTAL-YGJS201702004.htm LI Q, NIAN Y Y, LI X. The analysis of spatial and temporal change in the Amu Darya Basin, Central Asia, from 2000 to 2009[J]. Remote Sensing Technology and Application, 2017, 32(2): 218-227 https://www.cnki.com.cn/Article/CJFDTOTAL-YGJS201702004.htm |
| [20] | KLEIN I, GESSNER U, KUENZER C. Regional land cover mapping and change detection in Central Asia using MODIS time-series[J]. Applied Geography, 2012, 35(1/2): 219-234 http://www.sciencedirect.com/science/article/pii/S0143622812000720 |
| [21] | HAJ-AMOR Z, ACHARJEE T K, DHAOUADI L, et al. Impacts of climate change on irrigation water requirement of date palms under future salinity trend in coastal aquifer of Tunisian oasis[J]. Agricultural Water Management, 2020, 228: 105843 doi: 10.1016/j.agwat.2019.105843 |
| [22] | YANG W T, LONG D, BAI P. Impacts of future land cover and climate changes on runoff in the mostly afforested river basin in North China[J]. Journal of Hydrology, 2019, 570: 201-219 doi: 10.1016/j.jhydrol.2018.12.055 |
| [23] | FU X, WANG X H, YANG Y J. Deriving suitability factors for CA-Markov land use simulation model based on local historical data[J]. Journal of Environmental Management, 2018, 206: 10-19 http://www.sciencedirect.com/science/article/pii/S0301479717309908 |
