干旱区研究

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2018 , Vol. 35 >Issue 01: 1 - 11

DOI: https://doi.org/10.13866/j.azr.2018.01.01

水土资源

用经验径流系数推算全球径流深度分布场

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  • 中国农业科学院农业经济与发展研究所，北京 100081
梁书民（1966-），男，研究员，博士，主要从事水资源和农业经济学研究，E-mail: liangshumin@caas.cn

收稿日期: 2017-04-07

  网络出版日期: 2018-02-06

基金资助

中国农业科学院科技创新工程（ASTIP-IAED-2017-07）农业资源环境经济与政策研究项目资助

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Global runoff field calculated by empirical runoff coefficient

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  • Institute of Agricultural Economics and Development Chinese Academy of Agricultural Sciences, Beijing, 100081

Received date: 2017-04-07

  Online published: 2018-02-06

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摘要

摘要：通过回顾110 a的全球径流量估算历史,以中国为样本区域,通过求算样本区域的径流系数，利用最小二乘法回归得出了径流系数经验公式。基于径流系数经验公式和高分辨率降水深度图，利用地理信息系统绘制了全球水资源的高分辨率空间分布场，计算得出全球（不含南极洲）径流量为47 884 km3，平均径流深度为359 mm；内流区径流量为1 663 km3，平均径流深度为58.4 mm。将31个内流区径流量的计算结果与有关文献进行比较，发现下垫面蒸发和人类利用耗散对地下径流及地下水增量变化在水资源核算中的重要性，计算得出的内流区径流量与实际值较为接近。

关键词： 全球; 水资源; 经验公式; 径流系数; 空间分布场; 高分辨率; 地理信息系统

本文引用格式

梁书民, 于智媛 . 用经验径流系数推算全球径流深度分布场[J]. 干旱区研究, 2018 , 35(01) : 1 -11 . DOI: 10.13866/j.azr.2018.01.01

Abstract

Abstract: This paper reviews 110 years’ history of global runoff estimation. By taking land slope and aridity index as independent variable, and employing the method of Ordinary Least Squares (OLS) regression on sample region’s runoff coefficient, the empirical formula of runoff coefficient is calculated for China. Based on the empirical formula and high-resolution precipitation grid data, by applying Grid and Spatial Analysis module in Geographic Information System(GIS), the high resolution spatial distribution field of global water resources are calculated. Main calculation results are that the total runoff volume in the world(not including Antarctic Continent) is 47,884 cubic kilometers, the average runoff depth is 359 mm, the average runoff coefficient is 0.462; the runoff depth in African is 230mm, its runoff coefficient is 0.345, both are the lowest in the 6 continents; the runoff depth in South America is 770mm, the runoff coefficient is 0.507, both are the highest; Asia’s runoff depth is 313mm, which is below the world’s average, while it’s runoff coefficient is 0.495, which is higher than the world’s average. The results are compared with relevant literatures. This study emphasis on the importance of groundwater runoff and groundwater increment in arid and semi-arid regions, and significantly increases the estimation value of runoff depth in these regions. The calculated runoff volume of Africa and Australia are 6944 cubic kilometers and 3026 cubic kilometers respectively, which is obviously higher than the average of 24 estimations between 1973 and 2014 by literatures. Moreover, the authors also calculated the detail runoff pattern of all the 31 inner flow areas in the world. The total area of the world’s inner flowing regions is 28.47 million square Km, the total runoff volume is 1,663 cubic kilometers, the average runoff depth is 58.4 mm, and the average runoff coefficient is 0.252. The runoff depth of Oceania’s inner flowing region is 35mm, and its runoff coefficient is 0.129, both are the lowest in the world. Case studies of inner flow area show that the runoff depth field calculated by the empirical formula is in accordance with the actual runoff distribution pattern in Africa, Oceania, and 4 regions of Asia, including Nura River in Kazakhstan, Hexi Corridor and western Inner Mongolia Plateau in China, Southeastern Mongolia and China’s central and eastern Inner Mongolia Plateau, and Arabian Peninsula’s inner flow region. The theoretical hypothesis is confirmed for the inner flow sub-regions, the higher is the spatial resolution; the larger is the calculated runoff values. Main conclusions of this study are as follows: the spatial resolution of this study is 0.1667 degrees, which is 3 times as much as the majority resolution used in the runoff calculation; the runoff volume is calculated from the high spatial resolution runoff field in this study, which includes the runoff in inner flow watersheds and the runoff consumed in the outflow watersheds before it inflows to the oceans; the difference between the runoff of this study and the actual measured runoff at river mouth to the oceans or inland lakes should be the intermit consumption of the evaporation of on natural water surface, wetlands, the net water consumption of agricultural irrigation, and the net dissipation of artificial water usage at urban and industrial regions in the watershed; the underground runoff, the increment of groundwater, and the increment of soil available water are the main forms of runoff in arid and semi-arid climate zones. Current literature’s underestimation on water resources mainly lies in ignoring the evaporation of natural water body and wetland, the net dissipation of artificial water usage.

Key words： global water resources; empirical formula; runoff coefficient; spatial distribution field; high resolution; geographic information system

参考文献

[1] Korzoun V I, Sokolov A A, Budyko M I, et al. Atlas of World Water Balance - Maps and Explanatory Text[M]. Paris, France: The UNESCO Press，1977:1-36.
[2] Wilkinson K, von Zabern M, Scherzer J. Report No.44, GRDC Report Series, Global Freshwater Fluxes into the World Oceans [M]. Koblenz, Germany: Global Runoff Data Centre, Federal Institute of Hydrology(BfG), 2014:1-9.
[3] Food and Agriculture Organization of the United Nations (FAO). AQUASTAT Main Database[M]. Rome, Italy:Website accessed on [28/03/2016 9:50], 2016:1-10.
[4] Lvovitch M I. The Global Water Balance, US IHD Bulletin No. 23[M]. Washington D C, USA: US National Committee for the International Hydrological Decade, 1973: 28-53.
[5] Grabs W, De Couet T, Pauler J. Report No.10, GRDC Report Series, Freshwater Fluxes from Continents into the World Oceans [M]. Koblenz, Germany: Global Runoff Data Centre, Federal Institute of Hydrology(BfG), 1996: 22.
[6] Widen-Nilsson E, Halldin S, Xu C Y. Global water-balance modeling with WASMOD-M: Parameter estimation and regionalization[J]. Journal of Hydrology, 2007, 340 (1, 2):105-118.
[7] Fekete B M, Voeroesmarty Ch J, Grabs W. High-resolution composite runoff fields[J] Global Biogeochemical Cycles，2002, 16(3): 1-10.
[8] GRDC. Comparisons with other Estimations, Global Freshwater Fluxes into the World Oceans[M]. Koblenz, Germany: Global Runoff Data Centre, Federal Institute of Hydrology(BfG), 2014:1.
[9] Shiklomanov Igor A. Appraisal and assessment of world water resources[J]. Water International, 2000, 25(1): 11-32, DOI: 10.1080/02508060008686794, http://dx.doi.org/10. 1080 /02508060008686794.
[10] Sirajul Islam Md, Oki Taikan, Kanae Shinjiro, et al. A grid-based assessment of global water scarcity including virtual water trading[J]. Water Resource Manage, 2007，(21):19-33.
[11] Couet Thomas de, Thomas Maurer. Surface Freshwater Fluxes into the World Oceans[M]. Koblenz, Germany: Global Runoff Data Centre, Federal Institute of Hydrology (BfG), 2004:1.
[12] Couet Thomas de, Thomas Maurer. Surface Freshwater Fluxes into the World Oceans[M]. Koblenz, Germany: Global Runoff Data Centre, Federal Institute of Hydrology (BfG), 2009:1.
[13] Fekete B M, Voeroesmarty Ch J, Grabs W. UNH/GRDC Composite Runoff Fields V1.0[M]. Durham, USA and Koblenz, Germany: Complex Systems Research Center, University of New Hampshire, Durham, NH, USA, Global Runoff Data Center, Koblenz, Germany, http://www.compositerunoff.sr.unh.edu/, 2000a:1.
[14] Fekete B M, Voeroesmarty Ch J, Grabs W. Global Composite Runoff Fields Based on Observed River Discharge And Simulated Water Balances. Technical Report No. 22[M]. Koblenz, Germany: Global Runoff Data Center, 2000b, 115.
[15] Gassert F, Matt Landis, Matt Luck, et al. Aqueduct global maps 2.1, World Resource Institute working paper [M]. Washington D.C., USA: World Resource Institute, 2014: 6-7.
[16] Jarvis A, Reuter H I, Nelson A, et al. Hole-filled SRTM for the globe Version 4 [M]. Washington D.C., USA: available from the CGIAR-CSI SRTM 90m Database, 2008:1.
[17] Hijmans R J, Cameron S E, Parra J L, et al. Very high resolution interpolated climate surfaces for global land areas [J]. International Journal of Climatology, 2005, 25: 1965-1978.
[18] Hijmans Robert J, Susan Cameron, Juan Parra. WorldClim version 1 [M]. Berkeley, CA, USA: developed by at the Museum of Vertebrate Zoology, University of California, Berkeley, in collaboration with Peter Jones and Andrew Jarvis (CIAT), and with Karen Richardson (Rainforest CRC) , Accessed at Jan. 15, 2016, http://www.worldclim.org/, CA, USA, 2005:1.
[19] Trabucco A, Zomer R J. Global Aridity Index (Global-Aridity) and Global Potential Evapo-Transpiration (Global-PET) Geospatial Database [M]. Washington D C, USA:CGIAR Consortium for Spatial Information. http://www.csi.cgiar.org/, 2009.
[20] 焦北辰. 中国自然地理图集[M]. 北京：中国地图出版社，1984:103，115-116，129-130，143-144，157-158，167-168，179-180，191-192. [Jiao Beichen. Physical Geographical Atlas of China [M]. Beijing: Sinomap Press, 1984:103，115-116，129-130，143-144，157-158，167-168，179-180，191-192.] 
[21] 范正一. 中国自然保护地图集[M]. 北京：科学出版社, 1989:88, 195-196. [Fan Zhengyi. Natural Conservancy Atlas of China [M]. Beijing: Science Press,1989:88，195-196.]
[22] Lehner B, Verdin K, Jarvis A. New global hydrography derived from space borne elevation data [J]. Eos Transactions American Geophysical Union, 2008, 89(10): 93-94.
[23] Patterson T, Nathaniel Vaughn Kelso. Natural Earth [M]. Tallahassee, FL, USA: NACIS (North American Cartographic Information Society), 2016:1.
[24] 瑞木杰. 非洲地图集[M]. 北京：中国地图出版社, 1985:15-16. [Rui Mujie. Atlas of Africa [M]. Beijing: Sinomap Press, 1985:15-16.]
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