宁夏典型粮食作物生产水足迹时空演变及节水潜力评价

doi:10.12118/j.issn.1000-6060.2024.114

Abstract

Abstract:

In recent years, the grain and vegetable production capacity of Ningxia Hui Autonomous Region (Ningxia) has increased significantly. However, as one of the most water-scarce provinces in China, evaluating the water footprint of agricultural production and its water-saving potential is crucial for promoting the sustainable use of agricultural water resources. Focusing on the production water footprint of five typical food crops, this study explored the spatiotemporal evolution trends of the production water footprint in the region from 2006 to 2020 using the Mann-Kendall trend test. Additionally, a water-saving potential model was employed to further analyze the water-saving potential of these crops. The results indicated that: (1) The production water footprint of typical grain crops in Ningxia exhibited a decreasing trend over the past 15 years, with the production water footprint in Guyuan City decreasing by 42.97%. (2) The blue water and gray water footprints of each crop showed a consistent downward trend, while the green water footprint of the same crop varied significantly across cities, with soybean contributing the most to the green water footprint. (3) The water-saving potential of crop engineering, true water-saving potential of blue water and true water-saving potential of green water could reach 44.81%, 46.43% and 45.10%, respectively, in typical year crop production projects. These findings provide a theoretical foundation for the sustainable development of water-saving agriculture in Ningxia.

Key words: crop production water footprint, spatiotemporal evolution, water saving potential, Ningxia

GAO Yamiao, CHEN Haonan, WANG Fang, NAN Xiongxiong, CHEN Hongxiang, LI Wenhui. Spatio-temporal evolution of water footprint of typical grain crops and evaluation of water-saving potential in Ningxia[J].Arid Land Geography, 2024, 47(12): 2005-2016.

Figures/Tables 12

Fig. 1

Tab. 1

Calculation process of water footprint of typical grain crops in Ningxia"

名称	计算方法	解释	意义
作物蒸散量^[22]	$E T 0 = 0.408 Δ (R n - G) + γ 900 T + 273 (e a - e b) Δ + γ (1 + 0.34 U 2)$	$E T 0$ 为作物蒸发量； $Δ$ 为温度曲线斜率；R_n为净辐射；G为土壤热通量； $γ$ 为干湿度常数；T为日平均气温； $e a$ 为饱和水汽压； $e b$ 为实际水汽压； $U 2$ 为风速	评估区域内作物耗水和水资源的供求关系是不可或缺
粮食作物蒸散量^[23]	$E T c = K c × E T 0$	$E T c$ 为不同作物蒸散量； $K c$ 为作物系数	作物各生长阶段的需水比例
作物生长中有效降水量^[24]	$P e = P (125 - 0.2 P) / 125, P ≤ 250 125 + 0.1 P, P > 250$	$P e$ 为有效降水量；P为月降水量	作物生长期有效降水量
作物蓝、绿水蒸散发量	$E T g = m i n (E T c, P e)$ $E T b = m a x (E T c - P e, 0)$	$E T g$ 、 $E T b$ 分别为作物绿、蓝水蒸散发量	作物的蒸散发量直接影响其生产水足迹
粮食生产水足迹^[25]	$W F g = 10 E T g Y$ $W F b = 10 E T b + L Y$ $L = 10 α E T b (1 - η) / η$	$W F b$ 、 $W F g$ 分别为蓝水足迹、绿水足迹；Y为作物单产；L为灌溉水输配过程中的水面蒸发损失；η为利用系数；α取5%	某一时段作物生产所需水的总消耗量
粮食生产灰水足迹^[21]	$W F g r e y = (β A R) / (C m a x - C n a t) Y$	WF_grey为作物生产灰水足迹；β为淋失率；AR为作物氮肥折纯量； $C m a x$ 为水体中氮（0.002 kg·m^-3）最大容许浓度； $C n a t$ 为污染物的自然本底浓度（假设其数值为0）	氮肥是农业生产用水中最主要的污染物

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References 42

[1]	Hussain M I, Farooq M, Muscolo A, et al. Crop diversification and saline water irrigation as potential strategies to save freshwater resources and reclamation of marginal soils: A review[J]. Environmental Science and Pollution Research International, 2020, 27(23): 28695-28729.
[2]	宁夏回族自治区水利厅. 宁夏水资源公报[EB/OL]. [2023-07-24]. http://slt.nx.gov.cn/xxgk_281/fdzdgknr/gbxx/szygb/202307/t20230724_4190036.html.
	[Ningxia Water Conservancy. Ningxia Water Resources Bulletin[EB/OL]. [2023-07-24]. http://slt.nx.gov.cn/xxgk_281/fdzdgknr/gbxx/szygb/202307/t20230724_4190036.html.]
[3]	邓铭江, 王全九, 陶汪海, 等. 西北旱区现代农业提质增效发展模式探究[J]. 中国工程科学, 2023, 25(4): 59-72. doi: 10.15302/J-SSCAE-2023.07.016
	[Deng Mingjiang, Wang Quanjiu, Tao Wanghai, et al. Development model for improving the quality and efficiency of modern agriculture in the arid region of northwest China[J]. Strategic Study of CAE, 2023, 25(4): 59-72.] doi: 10.15302/J-SSCAE-2023.07.016
[4]	Falkenmark M, Kijne J M, Taron B, et al. Meeting water requirements of an expanding world population[J]. Philosophical Transactions: Biological Sciences, 1997, 352(1356): 929-936.
[5]	高洁, 吴普特, 谢朋轩, 等. 灌区蓝绿水资源与作物生产水足迹多时空分布量化分析[J]. 农业工程学报, 2021, 37(5): 105-112.
	[Gao Jie, Wu Pute, Xie Pengxuan, et al. Distributed quantification of blue and green water resources and water footprint of crop production in an irrigation district at multiple temporal scales[J]. Transactions of the Chinese Society of Agricultural Engineering, 2021, 37(5): 105-112.]
[6]	吴普特, 卓拉, 刘艺琳, 等. 区域主要作物生产实体水-虚拟水耦合流动过程解析与评价[J]. 科学通报, 2019, 64(18): 1953-1966.
	[Wu Pute, Zhuo La, Liu Yilin, et al. Assessment of regional crop-related physical-virtual water coupling flows[J]. Chinese Science Bulletin, 2019, 64(18): 1953-1966.]
[7]	Hoekstra A Y, Mekonnen M M. The water footprint of humanity[J]. Proceedings of the National Academy of Sciences of the United States of America, 2012, 109(9): 3232-3237. doi: 10.1073/pnas.1109936109 pmid: 22331890
[8]	翟家齐, 赵勇, 刘宽, 等. 干旱区灌溉绿洲农业节水潜力形成机制与评估方法[J]. 水利学报, 2023, 54(12): 1440-1451.
	[Zhai Jiaqi, Zhao Yong, Liu Kuan, et al. Formation mechanism and evaluation method of agriculture water-saving potential in irrigated oasis in arid regions[J]. Jurnal of Hydraulic Engineering, 2023, 54(12): 1440-1451.]
[9]	曹连海. 基于水足迹理论的灌区农业节水潜力研究[D]. 咸阳: 西北农林科技大学, 2014.
	[Cao Lianhai. Study on agriculture water-saving potential of irrigation district based on water footprint theory[D]. Xianyang: Northwest Agriculture & Forestry University, 2014.]
[10]	周雯晶. 中国主要农作物的理论灌溉效率及其节水潜力研究[D]. 郑州: 华北水利水电大学, 2018.
	[Zhou Wenjing. Theoretical irrigation efficiency and water saving potential of main crops in China[D]. Zhengzhou: North China University of Water Resources and Electric Power, 2018.]
[11]	闫晨健, 栗萌, 卓拉, 等. 1989—2019年陕西省作物生产水足迹时空演变与节水潜力评价[J]. 资源科学, 2023, 45(1): 158-173. doi: 10.18402/resci.2023.01.12
	[Yan Chenjian, Li Meng, Zhuo La, et al. Spatiotemporal evolution of water footprint and water-saving potentials of crop production in Shaanxi Province during 1989—2019[J]. Resources Science, 2023, 45(1): 158-173.] doi: 10.18402/resci.2023.01.12
[12]	杨静, 周冬梅, 马静, 等. 疏勒河流域农业水土资源时空匹配特征分析[J]. 干旱区地理, 2023, 46(6): 982-992. doi: 10.12118/j.issn.1000-6060.2022.474
	[Yang Jing, Zhou Dongmei, Ma Jing, et al. Spatial and temporal matching characteristics of agricultural land and water resources in the Shule River Basin[J]. Arid Land Geography, 2023, 46(6): 982-992.] doi: 10.12118/j.issn.1000-6060.2022.474
[13]	陶汪海, 邓铭江, 王全九, 等. 西北旱区农业高质量发展体系的生态农业内涵与路径[J]. 农业工程学报, 2023, 39(20): 221-232.
	[Tao Wanghai, Deng Mingjiang, Wang Quanjiu, et al. Ecological agriculture connotation and pathway of high-quality agricultural development system in northwest arid region[J]. Transactions of the Chinese Society for Agricultural Machinery, 2023, 39(20): 221-232.]
[14]	Li Y, Conway D, Wu Y, et al. Rural livelihoods and climate variability in Ningxia, northwest China[J]. Climatic Change, 2013, 119(3-4): 891-904.
[15]	国家气象信息中心. 中国地面气候资料日值数据集(V3.0)[EB/OL]. [2024-02-02]. http://data.cma.cn/data/cdc-detail/dataCode/SURF_CLI_CHN_MUL_DAY_V3.0.html.
	[National Meteorological Information Center. Daily ground climate (V3.0)[EB/OL]. [2024-02-02]. http://data.cma.cn/data/cdc-detail/dataCode/SURF_CLI_CHN_MUL_DAY_V3.0.html.]
[16]	宁夏回族自治区人民政府. 宁夏统计年鉴[DB/OL]. [2023-10-27]. https://www.nx.gov.cn/zwgk/zfxxgk/fdzdgknr/tjxx_40901/tjnj/.
	[Ningxia Hui Autonomous Region People’s Government. Ningxia statistical yearbook[DB/OL]. [2023-10-27]. https://www.nx.gov.cn/zwgk/zfxxgk/fdzdgknr/tjxx_40901/tjnj/.]
[17]	罗静怡, 东梅. 水足迹视角下宁夏粮食生产用水绿色效率研究-基于非期望产出的三阶段SBM-Malmquist指数[J/OL]. [2024-08-05]. 中国农业资源与区划. http://kns.cnki.net/kcms/detail/11.3513.S.20221031.1336.028.html.
	[Luo Jingyi, Dong Mei. Research on the green efficiency of water use for grain production in Ningxia from the perspective of water footprint-three-stage SBM-Malmquist index based on unexpected output[J/OL]. [2024-08-05]. Chinese Journal of Agricultural Resources and Regional Planning. http://kns.cnki.net/kcms/detail/11.3513.S.20221031.1336.028.html.]
[18]	姬小敏. 宁夏灌溉水利用系数影响因素研究[D]. 银川: 宁夏大学, 2021.
	[Ji Xiaomin. Study on the influencing factors of irrigation water utilization coefficient in Ningxia[D]. Yinchuan: Ningxia University, 2021.]
[19]	Gao J, Zhuo L, Liu Y, et al. Efficiency and sustainability of inter-provincial crop-related virtual water transfers in China[J]. Advances in Water Resources, 2020, 138: 103560, doi: 10.1016/j.advwatres.2020.103560.
[20]	中华人民共和国生态环境部. 中华人民共和国地表水环境质量标准[EB/OL]. [2022-11-06]. https://www.mee.gov.cn/ywgz/fgbz/bz/bzwb/shjbh/shjzlbz/200206/t20020601_66497.shtml.
	[Ministry of Ecology and Environment of the People’s Republic of China. Environmental quality standards for surface water of the People’s Republic of China[EB/OL]. [2022-11-06]. https://www.mee.gov.cn/ywgz/fgbz/bz/bzwb/shjbh/shjzlbz/200206/t20020601_66497.shtml.]
[21]	Hoekstra A, Chapagain A, Aldaya M, et al. The water footprint assessment manual: Setting the global standard[M]. Washington: Earthscan, 2011: 7-68.
[22]	陈绍民, 李晓丽, 杨启良, 等. 基于机器学习的遮荫设施内参考作物蒸散量估算[J]. 农业工程学报, 2022, 38(11): 108-116.
	[Chen Shaomin, Li Xiaoli, Yang Qiliang, et al. Estimation of reference evapotranspiration in shading facility using machine learning[J]. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(11): 108-116.]
[23]	史利洁, 吴普特, 王玉宝, 等. 基于作物生产水足迹的陕西省水资源压力评价[J]. 中国生态农业学报, 2015, 23(5): 650-658.
	[Shi Lijie, Wu Pute, Wang Yubao, et al. Assessment of water stress in Shaanxi Province based on crop water footprint[J]. Chinese Journal of Eco-Agriculture, 2015, 23(5): 650-658.]
[24]	Döll P, Siebert S. Global modeling of irrigation water requirements[J]. Water Resources Research, 2002, 38(4): 1037, doi: 10.1029/2001WR000355.
[25]	Allen R G, Pereira L S, Raes D, et al. Crop evapotranspiration: Guidelines for computing crop water requirements: FAO irrigation and drainage 56[M]. Rome: FAO, 1998: 7-207.
[26]	玉苏甫·买买提, 阿热孜古丽·图尔荪, 艾萨迪拉·玉苏甫. 渭-库河三角洲绿洲农作物需水量分析[J]. 节水灌溉, 2015(11): 85-88.
	[Mamat Yusup, Tursun Arzigul, Yusup Asadilla. Analysis of crop water requirement in Weigan-Kuqa River Delta Oasis of Xinjiang[J]. Water Saving Irrigation, 2015(11): 85-88.]
[27]	赵丹. 黑龙江省农业水土资源系统脆弱性测度及种植结构调控优化[D]. 哈尔滨: 东北林业大学, 2022.
	[Zhao Dan. Vulnerability evaluation and planting structure regulation and optimization of agricultural soil and water resources system in Heilongjiang Province[D]. Harbin: Northeast Forestry University, 2022.]
[28]	范星, 陈彬. 三江平原粮食作物生产水足迹时空特征及影响因素[J]. 生态学报, 2022, 42(15): 6368-6380.
	[Fan Xing, Chen Bin. Spatio-temporal patterns and influencing factors of the water footprint of grain crop production in the Sanjiang Plain[J]. Acta Ecologica Sinica, 2022, 42(15): 6368-6380.]
[29]	Mann H B. Non-parametric tests against trend[J]. Econometrica, 1945, 13(3): 245-259.
[30]	甘容, 徐孟莎, 左其亭. 伊洛河流域基流分割及其时空变化特征[J]. 资源科学, 2022, 44(9): 1824-1834. doi: 10.18402/resci.2022.09.07
	[Gan Rong, Xu Mengsha, Zuo Qiting. Baseflow separation and spatiotemporal variation characteristics in the Yiluo River Basin[J]. Resources Science, 2022, 44(9): 1824-1834.] doi: 10.18402/resci.2022.09.07
[31]	李慧娟, 师长兴, 马小晴, 等. 黄河中游窟野河流域水沙变化影响因素定量评估[J]. 资源科学, 2020, 42(3): 499-507. doi: 10.18402/resci.2020.03.08
	[Li Huijuan, Shi Changxing, Ma Xiaoqing, et al. Quantification of the influencing factors of runoff and sediment discharge changes of the Kuye River catchment in the middle reaches of the Yellow River[J]. Resources Science, 2020, 42(3): 499-507.] doi: 10.18402/resci.2020.03.08
[32]	李晓菲, 徐长春, 李路, 等. CMIP5模式对西北干旱区典型流域气温模拟能力评估——以开都-孔雀河为例[J]. 资源科学, 2019, 41(6): 1141-1153. doi: 10.18402/resci.2019.06.13
	[Li Xiaofei, Xu Changchun, Li Lu, et al. Evaluation of air temperature of the typical river basin in desert area of northwest China by the CMIP5 models: A case of the Kaidu-Kongqi River Basin[J]. Resources Science, 2019, 41(6): 1141-1153.] doi: 10.18402/resci.2019.06.13
[33]	杨凌示范区市场监督管理局. 基于作物生产水足迹调控的农业节水潜力评价通则: DB6111/T183-2021[EB/OL]. [2022-08-23]. https://www.eiacloud.com.
	[Market Supervision and Administration Bureau of Yangling Demonstration Zone. General rules for agricultural water saving potential evaluation based on water footprint regulation of crop production: DB6111/T183-2021[EB/OL]. [2022-08-23]. https://www.eiacloud.com.]
[34]	刘路广, 崔远来, 王建鹏. 基于水量平衡的农业节水潜力计算新方法[J]. 水科学进展, 2011, 22(5): 696-702.
	[Liu Luguang, Cui Yuanlai, Wang Jianpeng. New calculation method for water-saving potential in agriculture based on water balance principle[J]. Advances in Water Science, 2011, 22(5): 696-702.]
[35]	Zhuo L, Mekonnen M M, Hoekstra Y A. Benchmark levels for the consumptive water footprint of crop production for different environmental conditions: A case study for winter wheat in China[J]. Hydrology and Earth System Sciences, 2016, 20(11): 4547-4559.
[36]	刘鑫钰. 基于水-碳足迹的叶尔羌河灌区作物可持续生产研究[D]. 北京: 华北电力大学(北京), 2023.
	[Liu Xinyu. Research on sustainable crop production in Yarkant River Basin irrigated district based on water footprint and carbon footprint[D]. Beijing: North China Electric Power University (Beijing), 2023.]
[37]	聂汉林, 樊良新, 郭琎, 等. 县域尺度下关中地区农作物水足迹时空特征及影响因素[J]. 干旱区研究, 2024, 41(2): 339-352. doi: 10.13866/j.azr.2024.02.16
	[Nie Hanlin, Fan Liangxin, Guo Jin, et al. Spatial and temporal characteristics of crop water footprint and influencing factors in Guanzhong region at the county scale[J]. Arid Zone Research, 2024, 41(2): 339-352.] doi: 10.13866/j.azr.2024.02.16
[38]	高海燕, 李王成, 李晨, 等. 宁夏主要农作物生产水足迹及其变化趋势研究[J]. 灌溉排水学报, 2020, 39(3): 110-118.
	[Gao Haiyan, Li Wangcheng, Li Chen, et al. Water footprints of main crops and their change in Ningxia[J]. Journal of Irrigation and Drainage, 2020, 39(3): 110-118.]
[39]	齐娅荣, 张嗣曌, 唐莲, 等. 宁夏固原市主要农作物生产水足迹分析[J]. 水资源与水工程学报, 2020, 31(1): 91-96, 103.
	[Qiao Yarong, Zhang Sizhao, Tang Lian, et al. Analysis of water footprint of main crop production in Guyuan, Ningxia[J]. Journal of Water Resources & Water Engineering, 2020, 31(1): 91-96, 103.]
[40]	郭相平, 高爽, 吴梦洋, 等. 中国农作物水足迹时空分布与影响因素分析[J]. 农业机械学报, 2018, 49(5): 295-302.
	[Guo Xiangping, Gao Shuang, Wu Mengyang, et al. Analysis of temporal-spatial distribution and influencing factors of water footprint in crop production system of China[J]. Transactions of the CSAM, 2018, 49(5): 295-302.]
[41]	张家欣, 邓铭江, 李鹏, 等. 虚拟水流视角下西北地区农业水资源安全格局与调控[J]. 中国工程科学, 2022, 24(1): 131-140. doi: 10.15302/J-SSCAE-2022.01.014
	[Zhang Jiaxin, Deng Mingjiang, Li Peng, et al. Security pattern and regulation of agricultural water resources in northwest China from the perspective of virtual water flow[J]. Strategic Study of CAE, 2022, 24(1): 131-140.] doi: 10.15302/J-SSCAE-2022.01.014
[42]	褚家琦, 蒋志辉. 新疆农业水资源绿色效率时空演变及影响因素研究[J]. 干旱区地理, 2024, 47(7): 1231-1241. doi: 10.12118/j.issn.1000-6060.2023.577
	[Chu Jiaqi, Jiang Zhihui. Spatiotemporal evolution and influencing factors of green efficiency of agricultural water resources in Xinjiang[J]. Arid Land Geography, 2024, 47(7): 1231-1241.] doi: 10.12118/j.issn.1000-6060.2023.577

作物类型	4月	5月	6月	7月	8月	9月
小麦	0.40	1.15	1.15	1.15	1.15	0.40
玉米	0.60	0.47	0.95	1.15	1.10	0.57
水稻	0.90	0.85	1.33	1.48	1.36	0.95
大豆	-	0.45	0.89	1.11	0.92	0.55
薯类	0.32	1.11	1.11	1.11	0.74	0.74

年份	银川市	石嘴山市	吴忠市	固原市	中卫市
2006	0.416	0.393	0.594	0.580	0.379
2007	0.417	0.400	0.595	0.582	0.377
2008	0.410	0.370	0.578	0.567	0.370
2009	0.420	0.410	0.610	0.590	0.390
2010	0.420	0.420	0.598	0.588	0.370
2011	0.430	0.430	0.600	0.592	0.380
2012	0.440	0.440	0.602	0.612	0.388
2013	0.440	0.440	0.609	0.615	0.400
2014	0.450	0.440	0.610	0.618	0.410
2015	0.480	0.500	0.640	0.625	0.420
2016	0.520	0.500	0.618	0.632	0.440
2017	0.530	0.520	0.630	0.633	0.450
2018	0.540	0.540	0.638	0.634	0.470
2019	0.550	0.540	0.640	0.637	0.470
2020	0.560	0.560	0.648	0.640	0.480

作物类型	干旱区	湿润区
小麦	0.625	0.981
玉米	0.573	0.655
水稻	0.263	0.369
薯类	0.208	0.131
豆类	0.900	1.512

作物类型	工程节水潜力			绿水节水潜力			蓝水节水潜力
作物类型	丰水年	平水年	枯水年	丰水年	平水年	枯水年	丰水年	平水年	枯水年
大豆	0.242	0.313	0.189	0.317	0.472	0.253	0.831	1.440	0.929
薯类	0.947	1.025	1.437	1.469	2.415	2.530	4.456	8.107	12.363
小麦	4.082	6.362	4.072	1.041	1.068	1.275	3.509	5.730	6.268
玉米	18.030	18.017	17.816	1.423	1.061	0.522	3.745	3.930	2.639
水稻	3.355	3.296	2.655	2.155	1.714	1.626	5.589	5.251	4.703
合计	26.657	29.013	26.170	6.405	6.730	6.207	18.131	24.458	26.900

Spatio-temporal evolution of water footprint of typical grain crops and evaluation of water-saving potential in Ningxia

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