Estimation of irrigation requirements for drip-irrigated maize in a subhumid climate
LIU Yang1, 2, 3, YANG Hai-shun3, LI Jiu-sheng2, LI Yan-feng2, YAN Hai-jun1
1 College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, P.R.China 2 State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100048, P.R.China 3 Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln 68503, United States
Abstract Drip-irrigation is increasingly applied in maize (Zea mays L.) production in sub-humid region. It is critical to quantify irrigation requirements during different growth stages under diverse climatic conditions. In this study, the Hybrid-Maize model was calibrated and applied in a sub-humid Heilongjiang Province in Northeast China to estimate irrigation requirements for drip-irrigated maize during different crop physiological development stages and under diverse agro-climatic conditions. Using dimensionless scales, the whole growing season of maize was divided into diverse development stages from planting to maturity. Drip-irrigation dates and irrigation amounts in each irrigation event were simulated and summarized in 30-year simulation from 1981 to 2010. The maize harvest area of Heilongjiang Province was divided into 10 agro-climatic zones based on growing degree days, arid index, and temperature seasonality. The simulated results indicated that seasonal irrigation requirements and water stress during different growth stages were highly related to initial soil water content and distribution of seasonal precipitation. In the experimental site, the average irrigation amounts and times ranged from 48 to 150 mm with initial soil water content decreasing from 100 to 20% of the maximum soil available water. Additionally, the earliest drip-irrigation event might occur during 3- to 8-leaf stage. The water stress could occur at any growth stages of maize, even in wet years with abundant total seasonal rainfall but poor distribution. And over 50% of grain yield loss could be caused by extended water stress during the kernel setting window and grain filling period. It is estimated that more than 94% of the maize harvested area in Heilongjiang Province needs to be irrigated although the yield increase varied (0 to 109%) in diverse agro-climatic zones. Consequently, at least 14% of more maize production could be achieved through drip-irrigation systems in Heilongjiang Province compared to rainfed conditions.
This study was financially supported by the Key Technology R&D Program of China during the 12th Five-year Plan period (2014BAD12B05), the National Natural Science Foundation of China (51479211, 51621061) and the Chinese Scholarship Council (201506350059).
Corresponding Authors: Correspondence LI Jiu-sheng, Tel: +86-10-68786545, E-mail: email@example.com; YAN Hai-jun, Tel: +86-10-62737196, E-mail: firstname.lastname@example.org
About author: LIU Yang,E-mail: email@example.com;
Cite this article:
LIU Yang, YANG Hai-shun, LI Jiu-sheng, LI Yan-feng, YAN Hai-jun. Estimation of irrigation requirements for drip-irrigated maize in a subhumid climate[J]. Journal of Integrative Agriculture,
2018, 17(03): 677-692.
Allen R G, Jensen M E, Wright J L, Burman R D. 1989. Operational estimates of reference evapotranspiration. Agronomy Journal, 81, 650-662.
Allen R G, Pereira L S, Raes D, Smith M. 1998. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. Irrigation and Drainage Paper No. 56. vol. 300. FAO, Rome. p. 6541.
Abedinpour M, Sarangi A, Rajput T B S, Singh M, Pathak H, Ahmad T. 2012. Performance of evaluation of AquaCrop model for maize crop in a semi-arid environment. Agricultural Water Management, 110, 55-66.
Amarasingha R P R K, Suriyagoda L D B, Marambe B, Gaydon D S, Galagedara L W, Punyawardena R, Silva G L L P, Nidumolu U, Howden M. 2015. Simulation of crop and water productivity for rice (Oryza sativa L.) using APSIM under diverse agro-climatic conditions and water management technique in Sri Lanka. Agricultural Water Management, 160, 132-143.
Bar-Yosef B. 1999. Advances in fertigation. Advances in Agronomy, 65, 1-75.
Boogaard H L, De Wit A J W, te Roller J A, Van Diepen C A. 2014. WOFOST CONTROL CENTRE 2.1; User’s guide for the WOFOST CONTROL CENTRE 2.1 and the crop growth simulation model WOFOST 7.1.7. Wageningen University and Research Centre, Wageningen, The Netherlands.
Boote K J, Jones J W, Pickering N B. 1996. Potential uses and limitations of crop models. Agronomy Journal, 88, 704-716.
Bu L D, Chen X P, Li S Q, Liu J L, Zhu L, Luo S S, Hill R L, Zhao Y. 2015. The effects of adapting cultivars on the water use efficiency of dryland maize (Zea mays L.) in northwest China. Agricultural Water Management, 148, 1-9.
van Bussel L G J, Grassini P, van Wart J, Wolf J, Claessens L, Yang H S, Boogaard H, de Groot H, Saito K, Cassman K G, van Ittersum M K. 2015. From field to atlas: Upscaling of location-specific yield gap estimates. Field Crops Research, 177, 98-108.
Claassen M M, Shaw R H. 1970. Water deficit effects on corn. II. Grain Components. Agronomy Journal, 62, 652-655.
Girardin P, Tollennaar M. 1994. Effects of intraspecific interactions on maize leaf azimuth. Crop Science, 34, 151-155.
Goudriaan J. 1986. A simple and fast numerical method for the computation of daily totals of crop photosynthesis. Agricultural and Forest Meteorology, 38, 249-254.
Grassini P, van Bussel L G J, van Wart J, Wolf J, Glaessens L, Yang H S, Boogarrd H, de Groot H, van Ittersum M K, Cassman K G. 2015. How good is enough? Data requirements for reliable crop yield simulations and yield-gap analysis. Field Crops Research, 177, 49-63.
Grassini P, Yang H S, Cassman K G. 2009. Limits to maize productivity in Western Corn-Belt: A simulation analysis for fully irrigated and rainfed conditions. Agricultural and Forest Meteorology, 149, 1254-1265.
Grassini P, Yang H S, Irmak S, Thorburn J, Burr C, Cassman K G. 2011. High-yield irrigated maize in the Western U.S. Corn Belt: II. Irrigation management and crop water productivity. Field Crops Research, 120, 133-141.
Guan H J, Li J S, Li Y F. 2013. Effects of drip system uniformity and irrigation amount on water and salt distributions in soil under arid conditions. Journal of Integrative Agriculture, 12, 924-939.
He J Q, Dukes M D, Hochmuth G J, Jones J W, Graham W D. 2012. Identifying irrigation and nitrogen best management practices for sweet corn production on sandy soils using CERES-Maize model. Agricultural Water Management, 109, 61-70.
He Y B, Cai W M. 2016. Linking a farmer crop selection model (FCS) with an agronomic model (EPIC) to simulate cropping pattern in Northeast China. Journal of Integrative Agriculture, 15, 2417-2525.
Hou P, Cui Z L, Bu L D, Yang H S, Zhang F S, Li S K. 2014a. Evaluation of a modified Hybrid-Maize model incorporating a newly developed module of plastic film mulching. Crop Science, 54, 2796-2804.
Hou P, Liu Y, Xie R Z, Ming B, Ma D L, Li S K, Mei X R. 2014b. Temporal and spatial variation in accumulated temperature requirements of maize. Field Crops Research, 158, 55-64.
ISS (Institute of Soil Science, Chinese Academy of Sciences). 1986. The Soil Atlas of China. Cartographic Publishing House, Beijing. (in Chinese)
Irmak S, Djaman K, Rudnick D R. 2016. Effects of full and limited irrigation amount and frequency on subsurface drip-irrigated maize evapotranspiration, yield, water use efficiency and yield response factors. Irrigation Science, 34, 271-286.
Jackson R D, Idso S B, Reginato R J. 1981. Canopy temperature as a crop water-stress indicator. Water Resources Research, 17, 1133-1138.
Jones C A, Kiniry J R. 1986. CERES-Maize: A Simulation Model of Maize Growth and Development. Texas A&M University Press, College Station, TX.
Jones H G. 1992. Plant and Mocroclimate: Aquantitative Approach to Environment Plant Physiology. 2nd ed. Cambridge University Press, Cambridge.
Jiang Y W, Zhang L H, Zhang B Q, He C S, Jin X, Bai X. 2016. Modeling irrigation management for water conservation by DSSAT-maize model in arid northeast China. Agricultural Water Management, 177, 37-45.
Kozak J A, Ma L W, Ahuja L R, Flerchinger G, Nielsen D C. 2005. Evaluating various water stress calculations in RZWQM and RZ-SHAW for corn and soybean production. Agronomy Journal, 98, 1146-1155.
Lamm F R, Trooien T P. 2003. Subsurface drip irrigation for corn production: A review of 10 years of research in Kansas. Irrigation Science, 22, 195-200.
Leib B G, Jabro J D, Matthews G R. 2003. Field evaluation and performance comparison of soil moisture sensors. Soil Science, 168, 396-408.
Li J R, Liu B H. 2006. The change characters of monsoon rainband over Heilongjiang Province for the past 40 years. Journal of Forestry Research, 17, 71-74.
Lindquist J L, Arkebauer T J, Walters D T, Cassman K G, Dobermann A. 2005. Maize radiation use efficiency under optimal growth conditions. Agronomy Journal, 97, 72-78.
Liu C, Sun B C, Tang H J, Wang T Y, Li Y, Zhang D F, Xie X Q, Shi Y S, Song Y C, Yang X H, Li J S. 2017. Simple nonlinear model for the relationship between maize yield and cumulative water amount. Journal of Integrative Agriculture, 16, 858-866.
Liu S, Yang J Y, Zhang X Y, Drury C F, Reynolds W D, Hoogenboom G. 2013. Modeling crop yield, soil water content and soil temperature for a soybean-maize rotation under conventional and conservation tillage systems in Northeast China. Agricultural Water Management, 123, 32-44.
Liu Y, Li J, Li Y. 2015. Effects of split fertigation rates on the dynamics of nitrate in soil and the yield of mulched drip-irrigated maize in the sub-humid region. Applied Engineering in Agriculture, 31, 103-117.
Liu Y, Yang H S, Li Y, Yan H J, Li J S. 2017. Modeling effects of plastic film mulching on irrigated maize yield and water use efficiency in sub-humid Northeast China. International Journal of Agricultural and Biological Engineering, 10, 69-84.
Liu Y, Yang S J, Li S Q, Chen F. 2012. Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiaird environment. Scientia Agricola, 69, 300-307.
Liu Z J, Yang X G, Hubbard K G, Lin X M. 2012. Maize potential yields and yield gaps in the changing climate of northeast China. Global Change Biology, 18, 3441-3454.
Liu Z J, Yang X G, Lin X M, Hubbard K G, Lv S, Wang J. 2016. Maize yield gaps caused by non-controllable, agronomic, and socioeconomic factors in a changing climate of Northeast China. Science of the Total Environment, 541, 756-764.
Lizaso J I, Batchelor W D, Westgate M E, Echarte L. 2003. Enhancing the ability of CERES-Maize to compute light capture. Agriculture Systems, 76, 293-311.
Maddonni G A, Otegui M E, Cirilo A G. 2001. Plant population density, row spacing and hybrid effects on maize canopy architecture and light attenuation. Field Crops Research, 71, 183-193.
Otegui M E. 1995. Kernel set and flower synchrony within the ear of maize: II. Plant population effects. Crop Science, 37, 448-455.
McMaster G S, Wilhelm W W. 1997. Growing degree-days: One equation, two interpretations. Agricultural and Forest Meteorology, 87, 291-300.
Morell F, Yang H S, Cassman K G, van Wart J, Elmore R W, Licht M, Coulter J A, Ciampitti I A, Pittelkow C M, Brouder S M, Thomison P, Lauer J, Graham C, Massey R, Grassini P. 2016. Can crop simulation models be used to predict local to regional maize yields and total production in the U.S. Corn Belt? Field Crops Research, 192, 1-12.
NBSC (National Bureau of Statistics of China). 2015. China Statistics Yearbook. China Statistics Press, Beijing. (in Chinese)
Ritchie S W, Hanway J J, Benson G O. 1992. How a Corn Plant Develops. Iowa State University, Ames.
Russel G, Marshall B, Jarvis P G. 1989. Plant Canopies: Their Growth, Form and Function. Cambridge University Press, Cambridge.
Shi D Y, Li Y H, Zhang J W, Liu P, Zhao B, Dong S T. 2016. Increased plant density and reduced N rate lead to more grain yield and higher resource utilization in summer maize. Journal of Integrative Agriculture, 15, 2515-2528.
Shi S Q, Cao Q W, Yao Y M, Tang H J, Yang P, Wu W B, Xu H Z, Liu J, Li Z G. 2014. Influence of climate and socio-economic factors on the spatio-temporal variability of soil organic matter: A case study of central Heilongjiang Province, China. Journal of Integrative Agriculture, 13, 1486-1500.
Shirazi M A, Boersma L. 1984. A unifying quantitative analysis of soil texture. Soil Science of American Journal, 48, 142-147.
Song Z W, Guo J R, Zhang Z P, Kou T J, Deng A X, Zheng C Y, Ren J, Zhang W J. 2013. Impacts of planting system on soil moisture, soil temperature, and corn yield in rainfed area of Northeast China. European Journal of Agronomy, 50, 66-74.
Timsina J, Jat M L, Majumdar K. 2010. Rice-maize systems of South Asia: Current status, future prospects and research priorities for nutrient management. Plant and Soil, 335, 65-82.
Veihmeyer F J, Hendrickson A H. 1949. Methods of measuring field capacity and permanent wilting percentage of soils. Soil Science, 68, 75-94.
Wang Z, Li J, Li Y. 2014. Simulation of nitrate leaching under drip system uniformities and precipitation patterns during the growing season of maize in North China Plain. Agricultural Water Management, 142, 19-28.
van Wart J, van Bussel L G J, Wolf J, Licker R, Grassini P, Nelson A, Boogaard H, Gerber J, Mueller N D, Claessens L, van Ittersum M K, Cassman K G. 2013. Use of agro-climatic zones to upscale simulated crop yield potential. Field Crops Research, 143, 44-55.
Xu L, Zhang Q, Zhang J, Zhao L, Sun W, Jin Y X. 2017. Extreme meteorological disasters effects on grain production in Jilin Province, China. Journal of Integrative Agriculture, 16, 486-496.
Yang H S, Dobermann A, Cassman K G, Walters D T. 2006. Features, applications, and limitations of the Hybrid-Maize simulation model. Agronomy Journal, 98, 737-748.
Yang H S, Dobermann A, Lindquist J L, Walters D T, Arkenauer T J, Cassman K G. 2004. Hybrid-maize - a maize simulation model that combines two crop modeling approaches. Field Crops Research, 87, 131-154.
Zhang J J, Li J S, Zhao B Q, Li Y T. 2015. Simulation of water and nitrogen dynamics as affected by drip fertigation strategies. Journal of Integrative Agriculture, 14, 2434-2445.