Abstract
There is an urgent need to ensure regional food security and increase irrigation water productivity in response to water shortages in arid and semi-arid regions. Previous studies of the optimal allocation of irrigation water did not consider simultaneously optimizing across multiple crops or at different growth stages. This paper describes the development of an irrigation water optimization model that uses a crop water allocation priority (CWAP) model. The CWAP value was determined by quantifying the changes in three indicators: yield, economic benefits, and irrigation water productivity. Maximum yield, maximum economic benefits, and minimum irrigation shortage (at the critical crop and growth stage) were used as the objective functions of a non-linear multi-objective optimization model. The largest irrigation district in the northern arid area of China, Hetao Irrigation District (HID), was chosen to prototype this model. The optimization results, using CWAP, showed that yield, economic benefits, irrigation water productivity, and water productivity could be increased, respectively, by up to 13.38%, 13.40%, 2.30%, and 6.29%, for most crops when compared with optimization results without CWAP. Comparison of the optimized net irrigation quantities with the actual net irrigation quantities showed that optimization reduced water usage by up to 60.77% for wheat, 51.24% for corn, and 63.59% for sunflower. Blue water utilization under optimal irrigation conditions decreased by 1.12% for wheat, 2.91% for corn, and 9.91% for sunflower, compared with those in actual irrigation scenario. This method of optimizing irrigation water allocation in arid areas using CWAP provides decision-makers with accurate water-saving irrigation protocols that will reduce demand for water resources and promote sustainable agriculture.
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References
Allen RG, Pereia LS, Raes D, Smith M (1998) Crop evapotranspiration-guidelines for computing crop water requirements–FAO irrigation and drainage Paper 56. FAO Rome 300:D05109
Bessembinder JJE, Leffelaar PA, Dhindwal AS, Ponsioen TC (2005) Which crop and which drop, and the scope for improvement of water productivity. Agric Water Manag 73(2):113–130. https://doi.org/10.1016/j.agwat.2004.10.004
Deepa R, Anandhi A, Alhashim R (2021) Volumetric and impact-oriented water footprint of agricultural crops: a review. Ecol Indic. https://doi.org/10.1016/j.ecolind.2021.108093
Doorenbos J, Kassam A H, Bentvelsen CIM (1979) Yield response to water. Food and Agriculture Organization of the United Nations, Rome
Doulgeris C, Georgiou P, Papadimos D, Papamichail D (2015) Water allocation under deficit irrigation using MIKE BASIN model for the mitigation of climate change. Irrig Sci 33(6):469–482. https://doi.org/10.1007/s00271-015-0482-4
Evett SR, Stone KC, Schwartz RC, O’Shaughnessy SA, Colaizzi PD, Anderson SK, Anderson DJ (2019) Resolving discrepancies between laboratory-determined field capacity values and field water content observations: implications for irrigation management. Irrig Sci 37(6):751–759. https://doi.org/10.1007/s00271-019-00644-4
FAO (2013) Climate-smart agriculture sourcebook. Food and Agriculture Organization of the United Nations, Rome. https://www.fao.org/3/i3325e/i3325e.pdf
FAO, IFAD, UNICEF, WFP, WHO (2019) The State of Food Security and Nutrition in the World 2019. Safeguarding against economic slowdowns and downturns. Food and Agriculture Organization of the United Nations, Rome. https://www.fao.org/3/ca5162en/ca5162en.pdf
Gao X, Huo Z, Xu X, Qu Z, Huang G, Tang P, Bai Y (2018) Shallow groundwater plays an important role in enhancing irrigation water productivity in an arid area: The perspective from a regional agricultural hydrology simulation. Agric Water Manag 208:43–58. https://doi.org/10.1016/j.agwat.2018.06.009
García-López J, Lorite IJ, García-Ruiz R, Ordoñez R, Dominguez J (2016) Yield response of sunflower to irrigation and fertilization under semi-arid conditions. Agric Water Manag 176:151–162. https://doi.org/10.1016/j.agwat.2016.05.020
Gómez-Limón JA, Gutiérrez-Martín C, Montilla-López NM (2020) Agricultural water allocation under cyclical scarcity: the role of priority water rights. Water 12(6):1835. https://doi.org/10.3390/w12061835
He X, Yang P, Ren S, Li Y, Jiang G, Li L (2016) Quantitative response of oil sunflower yield to evapotranspiration and soil salinity with saline water irrigation. Int J Agric Biol Eng 9(2):63–73. https://doi.org/10.3965/j.ijabe.20160902.1683
Henry EI, Andrew KPRT, Baanda AS, Henry FM (2007) Evaluation of selected crop water production functions for an irrigated maize crop. Agric Water Manag 94(1–3):1–10. https://doi.org/10.1016/j.agwat.2007.07.006
Jensen ME (1968) Water consumption by agricultural plants. In: Kozlowski TT (ed) Water deficit and plant growth. Academic Press, New York, Vol II, pp 1–22
Junaid NC, Allah B, Ragab R, Abdul K, Bernard AE, Muhammad R, Muhammad AS, Qamar N (2020) Modeling corn growth and root zone salinity dynamics to improve irrigation and fertigation management under semi-arid conditions. Agric Water Manag 230. https://doi.org/10.1016/j.agwat.2019.105952
Karatayev M, Kapsalyamova Z, Spankulova L, Skakova A, Movkebayeva G, Kongyrbay A (2017) Priorities and challenges for a sustainable management of water resources in Kazakhstan. Sustain Water Qual Ecol 9–10:115–139. https://doi.org/10.1016/j.swaqe.2017.09.002
Li M, Guo P, Singh VP (2016) An efficient irrigation water allocation model under uncertainty. Agric Syst 144:46–57. https://doi.org/10.1016/j.agsy.2016.02.003
Li C, Xiong Y, Cui Z, Huang Q, Xu X, Han W, Huang G (2020) Effect of irrigation and fertilization regimes on grain yield, water and nitrogen productivity of mulching cultivated maize (Zea mays L.) in the Hetao Irrigation District of China. Agric Water Manag. https://doi.org/10.1016/j.agwat.2020.106065
Li M, Bi D, Yang D (2020) The impact of climate change on country’s fragility assessment. J Appl Math Phys 8(11):2447–2462. https://doi.org/10.4236/jamp.2020.811181
Li X, Zhang C, Huo Z (2020) Optimizing irrigation and drainage by considering agricultural hydrological process in arid farmland with shallow groundwater. J Hydrol. https://doi.org/10.1016/j.jhydrol.2020.124785
Li X, Zhang C, Huo Z, Adeloye AJ (2020) A sustainable irrigation water management framework coupling water-salt processes simulation and uncertain optimization in an arid area. Agric Water Manag. https://doi.org/10.1016/j.agwat.2019.105994
Liu J, Li Y, Huang G, Zeng X (2014) A dual-interval fixed-mix stochastic programming method for water resources management under uncertainty. Resour Conserv Recy 88:50–66. https://doi.org/10.1016/j.resconrec.2014.04.010
Luan X, Wu P, Sun S, Wang Y, Gao X (2018) Quantitative study of the crop production water footprint using the SWAT model. Ecol Indic 89:1–10. https://doi.org/10.1016/j.ecolind.2018.01.046
Luo B, Liu X, Zhang F, Guo P (2021) Optimal management of cultivated land coupling remote sensing-based expected irrigation water forecasting. J Clean Prod. https://doi.org/10.1016/j.jclepro.2021.127370
Luo B, Zhang F, Liu X, Pan Q, Guo P (2021) Managing agricultural water considering water allocation priority based on remote sensing data. Remote Sens 13:1536. https://doi.org/10.3390/rs13081536
Mandal S, Vema VK, Kurian C, Sudheer KP (2020) Improving the crop productivity in rainfed areas with water harvesting structures and deficit irrigation strategies. J Hydrol. https://doi.org/10.1016/j.jhydrol.2020.124818
Mello KD, Valente RA, Randhir TO, Vettorazzi CA (2018) Impacts of tropical forest cover on water quality in agricultural watersheds in southeastern Brazil. Ecol Indic 93:1293–1301. https://doi.org/10.1016/j.ecolind.2018.06.030
Miao Q, Rosa RD, Shi H, Paredes P, Zhu L, Dai J, Gonçalves JM, Pereira LS (2016) Modeling water use, transpiration and soil evaporation of spring wheat-maize and spring wheat-sunflower relay intercropping using the dual crop coefficient approach. Agric Water Manag 165:211–229. https://doi.org/10.1016/j.agwat.2015.10.024
Mishra V, Cherkauer KA (2010) Retrospective droughts in the crop growing season: implications to corn and soybean yield in the Midwestern United States. Agric For Meteorol 150(7–8):1030–1045. https://doi.org/10.1016/j.agrformet.2010.04.002
Moeinaddini M, Khorasani N, Danehkar A, Darvishsefat AA, Zienalyan M (2010) Siting MSW landfill using weighted linear combination and analytical hierarchy process (AHP) methodology in GIS environment (case study: karaj). Waste Manag 30(5):912–920. https://doi.org/10.1016/j.wasman.2010.01.015
Moldero D, López-Bernal Á, Testi L, Lorite IJ, Fereres E, Orgaz F (2021) Long-term almond yield response to deficit irrigation. Irrig Sci 39(4):409–420. https://doi.org/10.1007/s00271-021-00720-8
Naghdi S, Bozorg-Haddad O, Khorsandi M, Chu X (2021) Multi-objective optimization for allocation of surface water and groundwater resources. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2021.146026
Niu G, Li Y, Huang G, Liu J, Fan Y (2016) Crop planning and water resource allocation for sustainable development of an irrigation region in China under multiple uncertainties. Agric Water Manag 166:53–69. https://doi.org/10.1016/j.agwat.2015.12.011
O’Shaughnessy SA, Andrade MA, Evett SR (2017) Using an integrated crop water stress index for irrigation scheduling of two corn hybrids in a semi-arid region. Irrig Sci 35(5):451–467. https://doi.org/10.1007/s00271-017-0552-x
Omer A, Ma Z, Zheng Z, Saleem F (2020) Natural and anthropogenic influences on the recent droughts in Yellow River Basin, China. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2019.135428
Omer A, Ma Z, Yuan X, Zheng Z, Saleem F (2021) A hydrological perspective on drought risk-assessment in the Yellow River Basin under future anthropogenic activities. J Environ Manag. https://doi.org/10.1016/j.jenvman.2021.112429
Qi Z, Feng H, Zhao Y, Zhang T, Yang A, Zhang Z (2018) Spatial distribution and simulation of soil moisture and salinity under mulched drip irrigation combined with tillage in an arid saline irrigation district, northwest China. Agric Water Manag 201:219–231. https://doi.org/10.1016/j.agwat.2017.12.032
Qu Z, Yang X, Huang Y, Du B, Yang J (2015) Analysis of efficiency of water utilization in canal system in Hetao irrigation district based on Horton fractal. Trans CSAE 31(13):120–127. https://doi.org/10.11975/j.issn.1002-6819.2015.13.017 (In Chinese)
Ren D, Xu X, Hao Y, Huang G (2016) Modeling and assessing field irrigation water use in a canal system of Hetao, upper Yellow River basin: application to maize, sunflower and watermelon. J Hydrol 532:122–139. https://doi.org/10.1016/j.jhydrol.2015.11.040
Ren D, Xu X, Engel B, Huang G (2018) Growth responses of crops and natural vegetation to irrigation and water table changes in an agro ecosystem of Hetao, upper Yellow River basin: scenario analysis on maize, sunflower, watermelon and tamarisk. Agric Water Manag 199:93–104. https://doi.org/10.1016/j.agwat.2017.12.021
Shang S (2013) Downscaling crop water sensitivity index using monotone piecewise cubic interpolation. Pedosphere 23(5):662–667. https://doi.org/10.1016/S1002-0160(13)60058-2
Shi J, Wu X, Zhang M, Wang X, Zuo Q, Wu X, Zhang H, Ben-Gal A (2021) Numerically scheduling plant water deficit index-based smart irrigation to optimize crop yield and water use efficiency. Agric Water Manag. https://doi.org/10.1016/j.agwat.2021.106774
Song Z, Guo J, Zhang Z, Kou T, Deng A, Zheng C, Ren J, Zhang W (2013) Impacts of planting systems on soil moisture, soil temperature and corn yield in rainfed area of Northeast China. Eur J Agron 50:66–74. https://doi.org/10.1016/j.eja.2013.05.008
Sonkar I, Kotnoor HP, Sen S (2019) Estimation of root water uptake and soil hydraulic parameters from root zone soil moisture and deep percolation. Agric Water Manag 222:38–47. https://doi.org/10.1016/j.agwat.2019.05.037
Stetson L E, Mecham B Q (2011) Irrigation (6th ed). Irrigation Association, Falls Church, Virginia.
Sun S, Liu J, Wu P, Wang Y, Zhao X, Zhang X (2016) Comprehensive evaluation of water use in agricultural production: a case study in Hetao Irrigation District, China. J Clean Prod 112(5):4569–4575. https://doi.org/10.1016/j.jclepro.2015.06.123
Surendran U, Jayakumar M, Marimuthu S (2016) Low cost drip irrigation: impact on sugarcane yield, water and energy saving in semiarid tropical agro ecosystem in India. Sci Total Environ 573:1430–1440. https://doi.org/10.1016/j.scitotenv.2016.07.144
Tang Q, Oki T, Kanae S, Hu H (2008) Hydrological cycles change in the Yellow River Basin during the Last Half of the Twentieth Century. J Climate 21(8):1790–1806. https://doi.org/10.1175/2007JCLI1854.1
Tang Y, Zhang F, Wang S, Zhang X, Guo S, Guo P (2019) A distributed interval nonlinear multiobjective programming approach for optimal irrigation water management in an arid area. Agric Water Manag 220:13–26. https://doi.org/10.1016/j.agwat.2019.03.052
Tian D, Guo K, Lu H, Ye Z (2015) Optimizal irrigation systems of the main crops under wellcanal irrigation mode in Hetao Irrigation District. J Irrig Drain 34(1):48–52. https://doi.org/10.13522/j.cnki.ggps.2015.01.011 (In Chinese)
Tong W, Chen X, Wen X, Chen F, Zhang H, Chu Q, Dikgwatlhe SB (2015) Applying a salinity response function and zoning saline land for three field crops: a case study in the Hetao Irrigation District, Inner Mongolia, China. J Integr Agr 144(1):178–189. https://doi.org/10.1016/S2095-3119(14)60761-9
Wang Y (2017) Calculation of irrigation water utilization coefficient and analysis of total agricultural water consumption in Hetao irrigation District. Dissertation, Yangzhou University (in Chinese)
Wang L (2018) Area ratio of canal to well irrigation areas for combined use of groundwater and surface water in Hetao Irrigation District. Dissertation, Wuhan University (in Chinese)
White I, Xu T, Zeng J, Yu J, Ma X, Yang J, Huo Z, Chen H (2020) Changing climate and implications for water use in the Hetao Basin, Yellow River, China. Proc IAHS 383:51–59. https://doi.org/10.5194/piahs-383-51-2020
Xue J, Huo Z, Wang S, Wang C, White I, Kisekka I, Sheng Z, Huang G, Xu X (2020) A novel regional irrigation water productivity model coupling irrigation and drainage-driven soil hydrology and salinity dynamics and shallow groundwater movement in arid regions in China. Hydrol Earth Syst Sci 24(5):2399–2418. https://doi.org/10.5194/hess-24-2399-2020
Yu B, Shang S (2020) Estimating growing season evapotranspiration and transpiration of major crops over a large irrigation district from HJ–1A/1B data using a remote sensing-based dual source evapotranspiration model. Remote Sens 12(5):865. https://doi.org/10.3390/rs12050865
Yun W, Hou Q, Li J, Miao B, Feng X (2015) Yield prediction of sunflower based on crop coefficient and water production function. J Appl Meteor Sci 26(6):705–713. https://doi.org/10.11898/1001-7313.20150607 (In Chinese)
Zeng W, Wu J, Hoffmann MP, Xu C, Ma T, Huang J (2016) Testing the APSIM sunflower model on saline soils of Inner Mongolia, China. Field Crops Res 192:42–54. https://doi.org/10.1016/j.fcr.2016.04.013
Zeng W, Xu C, Wu J, Huang J (2016) Sunflower seed yield estimation under the interaction of soil salinity and nitrogen application. Field Crops Res 198:1–15. https://doi.org/10.1016/j.fcr.2016.08.007
Zhang F, Guo P, Engel BA, Guo S, Zhang C (2019) Planning seasonal irrigation water allocation based on an interval multiobjective multi-stage stochastic programming approach. Agric Water Manag. https://doi.org/10.1016/j.agwat.2019a.105692
Zhang F, Yue Q, Engel BA, Guo S, Guo P, Li X (2019) A bi-level multiobjective stochastic approach for supporting environment-friendly agricultural planting strategy formulation. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2019.133593
Zhang T, Ji X, Zhan X, Ding Y, Zou Y, Kisekka I, Chau H, Feng H (2021) Maize is stressed by salt rather than water under drip irrigation with soil matric potential higher than – 50 kPa in an arid saline area. J Agron Crop Sci 207(4):654–668. https://doi.org/10.1111/jac.12497
Zhang X, Guo P, Guo W, Gong J, Luo B (2021) Optimization toward sustainable development in shallow groundwater area and risk analysis. Agric Water Manag. https://doi.org/10.1016/j.agwat.2021.107225
Zhang X, Guo P, Zhang F, Liu X, Yue Q, Wang Y (2021) Optimal irrigation water allocation in Hetao Irrigation District considering decision makers’ preference under uncertainties. Agric Water Manag. https://doi.org/10.1016/j.agwat.2020.106670
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This research was supported by the National Key Research and Development Program of China (No. 2018YFC1508705). We are extremely grateful to the anonymous reviewers and editors for their thoughtful suggestions and valuable comments, which helped us to improve the manuscript.
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CRediT taxonomy JG: conceptualization, methodology, original draft paper, formal analysis, and investigation; LH: conceptualization, paper review, and editing, supervision; XL: data review and paper review; SW: conceptualization, funding acquisition, project administration, paper review, and editing.
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Gong, J., He, L., Liu, X. et al. Optimizing the allocation of irrigation water for multiple crops based on the crop water allocation priority. Irrig Sci 41, 49–68 (2023). https://doi.org/10.1007/s00271-022-00792-0
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DOI: https://doi.org/10.1007/s00271-022-00792-0