为探究北江流域的水资源状况及其在不同程度干旱下的变化特征,利用SWAT模型模拟北江流域径流过程,并在此基础上评估北江流域的蓝绿水资源时空变化及其对干旱的响应特征。研究表明:北江流域水资源以蓝水为主,多年平均蓝水量为1 149.08 mm,绿水量为981.08 mm,绿水系数为0.48; 1966—2010年间,北江流域蓝绿水无显著变化趋势,空间分布上蓝水表现为南多北少,而绿水则与之相反;蓝水对干旱的响应更敏感,重度干旱下,北江流域的蓝水量较多年平均值分别减少16.94%,流域内的水资源分配模式由以蓝水为主转变为以绿水为主,绿水系数达0.53。从蓝水和绿水的角度研究北江流域的水资源状况及其干旱响应特征,可以为流域水资源管理提供依据,增强应对干旱风险、保障流域水安全的能力。
Abstract
The aim of this study is to explore the status of water resources and its variation characteristics in Beijiang river basin in the presence of different degrees of drought. The streamflow in Beijiang river basin was simulated using SWAT model, and on this basis, the temporal and spatial variation characteristics of blue water and green water and their responses to droughts were evaluated. Results unraveled that: (1) Blue water accounted for the main part in the water resources in Beijiang river basin, with the average annual blue water reaching 1 149.08 mm, green water 981.08 mm, and green water coefficient 0.48. (2) From 1966 to 2010, blue water and green water experienced no significant changes, whereas in spatial scale, blue water distributed more in the south than that in the north, and the opposite for green water. (3) Blue water was more sensitive to drought than green water. Under severe droughts, the blue water in Beijiang river basin dropped by 16.94% from annual average, and the pattern of water resource distribution changed from blue water dominated to green water taking a lead, with the green water coefficient of 0.53. The research findings will be beneficial for the formulation of water resources management strategies, the designation of drought risk response measures and the guarantee of water security in the basin.
关键词
水资源 /
蓝水 /
绿水 /
干旱响应 /
SWAT模型 /
北江流域
Key words
water resources /
blue water /
green water /
drought response /
SWAT model /
Beijiang river basin
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 左其亭, 胡德胜, 窦 明, 等. 基于人水和谐理念的最严格水资源管理制度研究框架及核心体系[J]. 资源科学, 2014, 36(5): 906-912.
[2] 吴洪涛, 武春友, 郝芳华, 等. “绿水”的多角度评估及其管理研究[J]. 中国人口·资源与环境, 2008, 18(6): 61-67.
[3] FALKENMARK M.Land-Water Linkages: A Synopsis[M]//Land and Water Bulletin: Land and Water Integration and River Basin Management. Rome: Food and Agriculture Organization(FAO) of the United Nations, 1995: 15-16.
[4] 吕乐婷, 王晓蕊, 孙才志, 等. 基于SWAT模型的细河流域蓝水绿水资源量时空分布研究[J]. 长江流域资源与环境, 2019, 28(1): 39-47.
[5] SCHUOL J, ABBASPOUR KC, YANG Hong, et al. Modeling Blue and Green Water Availability in Africa[J]. Water Resource Research,2008,44(7):W07406.
[6] SERURA B. Modeling Blue and Green Water Resources Availability at the Basin and Sub-basin Level under Changing Climate in the Weyb River Basin in Ethiopia[J]. Scientific African, 2020, 7: e00299.
[7] VEETTIL A V, MISHRA A K.Water Security Assessment Using Blue and Green Water Footprint Concepts[J]. Journal of Hydrology, 2016, 542: 589-602.
[8] HOEKSTRA A Y. Green-blue Water Accounting in a Soil Water Balance[J]. Advances in Water Resources, 2019, 129: 112-117.
[9] GENG Qing-ling, REN Qing-fu, NOLAN R H,et al. Assessing China’s Agricultural Water Use Efficiency in a Green-blue Water Perspective: A Study Based on Data Envelopment Analysis[J]. Ecological Indicators, 2019, 96: 329-335.
[10] 张为彬, 查小春, 马玉改. 1961—2010年黄河源区蓝绿水资源时空变化[J]. 水土保持通报, 2014, 34(6): 338-343.
[11] 张云英, 袁 喆, 许继军,等. 金沙江流域蓝水绿水时空变化特征分析[J]. 人民长江, 2017, 48(20): 45-51,57.
[12] 赵安周, 赵玉玲, 刘宪锋, 等.气候变化和人类活动对渭河流域蓝水绿水影响研究[J]. 地理科学, 2016, 36(4): 571-579.
[13] 庞靖鹏, 徐宗学, 刘昌明. SWAT模型中天气发生器与数据库构建及其验证[J]. 水文, 2007(5): 25-30.
[14] BRIGHENTI T M, BONUMÁ N B,SRINIVASAN R, et al. Simulating Sub-Daily Hydrological Process with SWAT: A Review[J]. Hydrological Sciences Journal, 2019, 64(12): 1415-1423.
[15] ILAMPOORANAN I, VAN METER K J, BASU N B. A Race against Time: Modeling Time Lags in Watershed Response[J]. Water Resources Research, 2019, 55(5): 3941-3959.
[16] 胡文慧, 李光永, 孟国霞, 等. 基于SWAT模型的汾河灌区非点源污染负荷评估[J]. 水利学报, 2013, 44(11): 1309-1316.
[17] 周 铮, 吴剑锋, 杨 蕴, 等. 基于SWAT模型的北山水库流域地表径流模拟[J]. 南水北调与水利科技, 2020, 18(1): 66-73.
[18] DE GIROLAMO A M, MISCIOSCIA P, POLITI T, et al. Improving Grey Water Footprint Assessment: Accounting for Uncertainty[J]. Ecological indicators, 2019, 102:822-833.
[19] TAN M L, IBRAHIM A L, YUSOP Z, et al. Impacts of Land-Use and Climate Variability on Hydrological Components in The Johor River Basin, Malaysia[J]. Hydrological Sciences Journal, 2015, 60(5): 1-17.
[20] 王军德,李元红,李赞堂,等.基于SWAT模型的祁连山区最佳水源涵养植被模式研究:以石羊河上游杂木河流域为例[J].生态学报,2010,30(21):5875-5885.
[21] BADOU D F, DIEKKRÜGER B, KAPANGAZIWIRI E, et al. Modelling Blue and Green Water Availability under Climate Change in the Beninese Basin of the Niger River Basin, West Africa[J]. Hydrological Processes, 2018, 32(16): 2526-2542.
[22] 臧传富. 黑河流域蓝绿水时空变化研究[D]. 北京:北京林业大学, 2013.
[23] 张 杰, 贾绍凤. 基于SWAT模型的湟水流域蓝绿水与不同土地利用类型的绿水差异研究[J]. 水资源与水工程学报, 2013, 24(4): 6-10.
[24] 黄晚华, 杨晓光, 李茂松, 等.基于标准化降水指数的中国南方季节性干旱近58 a演变特征[J]. 农业工程学报, 2010, 26(7): 50-59.
[25] SONG Li-rong,ZHANG Jian-yun.Hydrological Response to Climate Change in Beijiang River Basin Based on the SWAT Model[J].Procedia Engineering,2012,28:241-245.
[26] 王兆礼,沈 艳,宋立荣. 基于SWAT模型的北江流域气候变化的水文响应[J]. 安徽农业科学, 2012, 40(34): 16761-16764.
[27] NASH J E, SUTCLIFFE J V. River Flow Forecasting Through Conceptual Models Part 1- A Discussion of Principles[J]. Journal of Hydrology, 1970, 10(3): 282-290.
[28] 吕乐婷, 王晓蕊, 江 源, 等. 基于SWAT模型的东江流域蓝水、绿水时空分布特征研究[J]. 水资源保护, 2017, 33(5): 53-60.
[29] 荣 琨, 陈兴伟. 用SWAT模拟土地利用对绿水蓝水的影响:以晋江西溪流域为例[J]. 环境科学与技术, 2016, 39(1): 205-210.
[30] WU Chuan-hao, XIAN Zhuo-yan, HUANG Guo-ru. Meteorological Drought in the Beijiang River Basin, South China: Current Observations and Future Projections[J]. Stochastic Environmental Research and Risk Assessment, 2016, 30(7):1821-1834.
基金
广东省“珠江人才计划”引进创新创业青年团队项目(2019ZT08G090);广东省教育厅普通高校青年创新人才项目(2020KQNCX125);中山大学新华学院校级科研基金项目(2019KYYB08)
PDF(4088 KB)
