Temporal-Spatial Distribution Characteristics and Influencing Factors of Regional Agricultural Water Requirement Indicators
Publication: Journal of Irrigation and Drainage Engineering
Volume 145, Issue 9
Abstract
The temporal-spatial distribution of agricultural water requirements constitutes an important basis for the optimal allocation of regional irrigation water resources. The primary crops (rice, maize, and soybeans) of 12 cities in Heilongjiang Province, China, were used as a case study, and reference evapotranspiration, crop water requirement, effective rainfall, irrigation requirement, and irrigation requirement index for these crops were calculated for a period of 10 years (2006–2015). The indexes of homogeneity and stability were used to reveal the characteristics of the temporal and spatial distributions based on a cloud model, i.e., a mathematical representation of qualitative concept—including expectation, Ex, entropy, En, and hyperentropy, He—that integrates the homogeneity and stability of the explored water use terms. Path analysis was used to determine the most pertinent factors influencing the irrigation requirement. The results showed a wide range in annual effective rainfall. The trends of the annual irrigation requirement and irrigation requirement index were similar, with the maximum irrigation requirement occurring in 2007. The distribution of the annual irrigation requirement was widely dispersed and that of the annual effective rainfall displayed the lowest degree of cohesion. The ranges of the various agricultural water requirement indicators between crops except for the effective rainfall were greater in the southwest than in the northeast. The distributions of the annual reference evapotranspiration, effective rainfall, irrigation requirement, and irrigation requirement index were most discrete and unstable in the Xiaoxing’anling Mountains, whereas the distributions of the annual crop water requirement, effective rainfall, and irrigation requirement index in the Sanjiang Plain were uniform and stable. Compared with the temporal distribution, the spatial distribution of each indicator was discrete and nonhomogeneous. Temperature and precipitation were the primary factors that influenced the irrigation requirement.
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Acknowledgments
This research was supported by funds from the National Natural Science Foundation of China (51479032 and 51709044), the National Key R&D Plan (2017YFC0406002), the National Science Fund for Distinguished Young Scholars (51825901), and the Northeast Agricultural University Youth Talent Fund Project (18QC28).
References
Allen, R. G., L. S. Pereira, D. Raes, and M. Smith. 1998. “Crop evapotranspiration: Guidelines for computing crop water requirements.” FAO Irrigation and Drainage Paper 56. Rome: Food and Agriculture Organization of the United Nations.
Beyazgül, M., Y. Kayam, and F. Engelsman. 2000. “Estimation methods for crop water requirements in the Gediz Basin of western Turkey.” J. Hydrol. 229 (1): 19–26.
Carr, J. Z., A. M. Schmidt, J. K. Ford, and R. P. Deshon. 2003. “Climate perceptions matter: a meta-analytic path analysis relating molar climate, cognitive and affective states, and individual level work outcomes.” J Appl. Phys. 88 (4): 605–619.
China Meteorological Data Sharing Service. n.d. “Monthly data set of surface climate data in China.” Accessed October 12, 2017. http://data.cma.cn.
Díaz, J. A. R., E. K. Weatherhead, J. W. Knox, and E. Camacho. 2007. “Climate change impacts on irrigation water requirements in the Guadalquivir river basin in spain.” Reg. Environ. Change 7 (3): 149–159.
Dofing, S. M., and C. W. Knight. 1992. “Alternative model for path analysis of small-grain yield.” Crop Sci. 32 (2): 487–489.
Döll, P., and S. Siebert. 2002. “Global modeling of irrigation water requirements.” Water Resour. Res. 38 (4): 1–8. https://doi.org/10.1029/2001WR000355.
Fu, Q., L. Li, M. Li, T. Li, D. Liu, R. Hou, and Z. Zhou. 2018. “An interval parameter conditional value-at-risk two-stage stochastic programming model for sustainable regional water allocation under different representative concentration pathways scenarios.” J Hydrol. 564 (Sep): 115–124. https://doi.org/10.1016/j.jhydrol.2018.07.008.
Huang, S., B. Hou, J. Chang, Q. Huang, and Y. Chen. 2015. “Spatial-temporal change in precipitation patterns based on the cloud model across the wei river basin, china.” Theor. Appl. Climatol. 120 (1–2): 391–401.
Katerji, N., P. Campi, and M. Mastrorilli. 2013. “Productivity, evapotranspiration, and water use efficiency of corn and tomato crops simulated by AquaCrop under contrasting water stress conditions in the Mediterranean region.” Agric. Water Manage. 130 (4): 14–26. https://doi.org/10.1016/j.agwat.2013.08.005.
Li, D. Y., H. J. Meng, and X. M. Shi. 1995. “Membership clouds and membership cloud generators.” [In Chinese.] J. Comput. Res. Dev. 32 (6): 16–18.
Liu, X. Y., and E. D. Lin. 2004. “Impact of climate change on water requirement of main crops in North China.” J. Hydraul. Eng. 35 (2): 77–82.
McVicar, T. R., T. G. V. Niel, L. T. Li, M. F. Hutchinson, X. M. Mu, and Z. H. Liu. 2007. “Spatially distributing monthly reference evapotranspiration and pan evaporation considering topographic influences.” J. Hydrol. 338 (3–4): 196–220. https://doi.org/10.1016/j.jhydrol.2007.02.018.
Mehta, V. K., V. R. Haden, B. A. Joyce, D. R. Purkey, and L. E. Jackson. 2013. “Irrigation demand and supply, given projections of climate and land-use change, in Yolo County, California.” Agric. Water Manage. 117 (1): 70–82. https://doi.org/10.1016/j.agwat.2012.10.021.
Mo, X. G., S. X. Liu, Z. H. Lin, and R. P. Guo. 2009. “Regional crop yield, water consumption and water use efficiency and their responses to climate change in the North China Plain.” Agric. Ecosyst. Environ. 134 (1–2): 67–78. https://doi.org/10.1016/j.agee.2009.05.017.
Ojekunle, Z. O., Z. Lin, T. Xin, G. Harrer, A. O. Martins, and H. Bangura. 2009. “Global climate change: The empirical study of sensitivity model in china’s sustainable development.” Energy Source 31 (19): 1777–1789. https://doi.org/10.1080/15567030902937143.
Rossi, S., A. Rampini, S. Bocchi, and M. Boschetti. 2010. “Operational monitoring of daily crop water requirements at the regional scale with time series of satellite data.” J. Irrig. Drain. Eng. 136 (4): 225–231. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000161.
Saadi, S., M. Todorovic, L. Tanasijevic, L. S. Pereira, C. Pizzigalli, and P. Lionello. 2015. “Climate change and Mediterranean agriculture: Impacts on winter wheat and tomato crop evapotranspiration, irrigation requirements and yield.” Agric. Water Manage. 147 (2): 103–115. https://doi.org/10.1016/j.agwat.2014.05.008.
Shen, Y., S. Li, Y. Chen, Y. Qi, and S. Zhang. 2013. “Estimation of regional irrigation water requirement and water supply risk in the arid region of northwestern china 1989–2010.” Agric. Water Manage. 128 (1): 55–64.
Smith, M. 1992. “CROPWAT: A computer program for irrigation planning and management.” FAO Irrigation and Drainage Paper 46. Rome: Food and Agriculture Organization of the United Nations.
Tabari, H., O. Kisi, A. Ezani, and P. H. Talaee. 2012. “SVM, ANFIS, regression and climate based models for reference evapotranspiration modeling using limited climatic data in a semi-arid highland environment.” J. Hydrol. 444–445 (10): 78–89.
Tong, L., S. Kang, and L. Zhang. 2007. “Temporal and spatial variations of evapotranspiration for spring wheat in the Shiyang river basin in northwest China.” Agric. Water Manage. 87 (3): 241–250. https://doi.org/10.1016/j.agwat.2006.07.013.
Wriedt, G., M. V. D. Velde, A. Aloe, and F. Bouraoui. 2009. “Estimating irrigation water requirements in Europe.” J. Hydrol. 373 (3): 527–544.
Wright, S. 1934. “The method of path coefficients.” Ann. Stat. 5 (3): 161–215. https://doi.org/10.1214/aoms/1177732676.
Xu, C. Y., L. Gong, T. Jiang, D. Chen, and V. P. Singh. 2006. “Analysis of spatial distribution and temporal trend of reference evapotranspiration and pan evaporation in Changjiang (Yangtze River) catchment.” J. Hydrol. 327 (1–2): 81–93. https://doi.org/10.1016/j.jhydrol.2005.11.029.
Yang, Y. M., Y. H. Yang, and J. P. Moiwo. 2010. “Estimation of irrigation requirement for sustainable water resources reallocation in North China.” Agric. Water Manage. 97 (11): 1711–1721.
Zhang, C., X. Chen, Y. Li, W. Ding, and G. Fu. 2018. “Water-energy-food nexus: Concepts, questions and methodologies.” J. Cleaner Prod. 195 (10): 625–639. https://doi.org/10.1016/j.jclepro.2018.05.194.
Zhu, Y., S. Huang, J. Chang, and G. Leng. 2017. “Spatial–temporal changes in potential evaporation patterns based on the cloud model and their possible causes.” Stochastic Environ. Res. Risk A. 31 (8): 2147–2158.
Zwart, S. J., and W. G. M. Bastiaanssen. 2004. “Review of measured crop water productivity values for irrigated wheat, rice, cotton and maize.” Agric. Water Manage. 69 (2): 115–133. https://doi.org/10.1016/j.agwat.2004.04.007.
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Published In
Journal of Irrigation and Drainage Engineering
Volume 145 • Issue 9 • September 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: May 10, 2018
Accepted: Mar 21, 2019
Published online: Jul 8, 2019
Published in print: Sep 1, 2019
Discussion open until: Dec 8, 2019
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