Estimation of rainfed maize transpiration under various mulching methods using modified Jarvis-Stewart model and hybrid support vector machine model with whale optimization algorithm

Agricultural Water Management - Tập 249 - Trang 106799 - 2021
Jing Zheng1,2,3, Junliang Fan1, Fucang Zhang1, Lifeng Wu4, Yufeng Zou1, Qianlai Zhuang2,3
1Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas of Ministry of Education, Northwest A&F University, Yangling, 712100, China
2Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN 47907, USA
3Department of Agronomy, Purdue University, West Lafayette, IN 47907, USA
4School of Hydraulic and Ecological Engineering, Nanchang Institute of Technology, Nanchang 330099, China

Tài liệu tham khảo

Allen, 1998, Crop evapotranspiration-guidelines for computing crop water requirements, FAO Irrig. Drain., Paper 56 Bastidas-Obando, 2017, Estimation of transpiration fluxes from rainfed and irrigated sugarcane in South Africa using a canopy resistance and crop coefficient model, Agric. Water Manag., 181, 94, 10.1016/j.agwat.2016.11.024 Brito, 2015, Canopy transpiration of a semi arid Pinus canariensis forest at a treeline ecotone in two hydrologically contrasting years, Agric. For. Meteor., 201, 120, 10.1016/j.agrformet.2014.11.008 Campbell, 1998, 286 Chen, 2014, Response of relative sap flow to meteorological factors under different soil moisture conditions in rainfed jujube (Ziziphus jujuba Mill.) plantations in semiarid Northwest China, Agric. Water Manag., 136, 23, 10.1016/j.agwat.2014.01.001 Chen, 2013, Assessing the potential of support vector machine for estimating daily solar radiation using sunshine duration, Energy Convers. Manag., 75, 311, 10.1016/j.enconman.2013.06.034 Chen, 2019, Assessing the effects of plant density and plastic film mulch on maize evaporation and transpiration using dual crop coefficient approach, Agric. Water Manag., 225, 10.1016/j.agwat.2019.105765 Cortes, 1995, Support-vector networks, Mach. Learn., 20, 273, 10.1007/BF00994018 Ding, 2013, Partitioning evapotranspiration into soil evaporation and transpiration using a modified dual crop coefficient model in irrigated maize field with ground-mulching, Agric. Water Manag., 127, 85, 10.1016/j.agwat.2013.05.018 Ding, 2013, Evapotranspiration measurement and estimation using modified Priestley–Taylor model in an irrigated maize field with mulching, Agric. For. Meteorol., 168, 140, 10.1016/j.agrformet.2012.08.003 Er-Raki, 2010, Using the dual approach of FAO-56 for partitioning ET into soil and plant components for olive orchards in a semi-arid region, Agric. Water Manag., 97, 1769, 10.1016/j.agwat.2010.06.009 Fan, 2015, Modeling effects of canopy and roots on soil moisture and deep drainage, Vadose Zone J., 14, 1, 10.2136/vzj2014.09.0131 Fan, 2018, Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates of China, Agric. For. Meteor., 263, 225, 10.1016/j.agrformet.2018.08.019 Fan, 2019, Light gradient boosting machine: an efficient soft computing model for estimating daily reference evapotranspiration with local and external meteorological data, Agric. Water Manag., 225, 10.1016/j.agwat.2019.105758 Fan, 2020, Hybrid support vector machines with heuristic algorithms for prediction of daily diffuse solar radiation in air-polluted regions, Renew. Energy, 145, 2034, 10.1016/j.renene.2019.07.104 Fan, 2021, Estimation of daily maize transpiration using support vector machines, extreme gradient boosting, artificial and deep neural networks models, Agric. Water Manag., 245, 10.1016/j.agwat.2020.106547 Feng, 2017, Energy balance and partitioning in partial plastic mulched and non-mulched maize fields on the loess plateau of china, Agric. Water Manag., 191, 193, 10.1016/j.agwat.2017.06.009 Feng, 2017, Estimation of maize evapotranspiration using extreme learning machine and generalized regression neural network on the China Loess Plateau, Hydrol. Res., 48, 1156, 10.2166/nh.2016.099 Féret, 2019, Estimating leaf mass per area and equivalent water thickness based on leaf optical properties: Potential and limitations of physical modeling and machine learning, Remote Sens. Environ., 231, 10.1016/j.rse.2018.11.002 Fu, 2016, Combining sap flow measurements and modelling to assess water needs in an oasis farmland shelterbelt of Populus simonii Carr in Northwest China, Agric. Water Manag., 177, 172, 10.1016/j.agwat.2016.07.015 Gao, 2019, Exploring optimal soil mulching to enhance yield and water use efficiency in maize cropping in China: a meta-analysis, Agric. Water Manag., 225, 10.1016/j.agwat.2019.105741 Gonzalez-Dugo, 2019, Transpiration from canopy temperature: implications for the assessment of crop yield in almond orchards, Eur. J. Agron., 105, 78, 10.1016/j.eja.2019.01.010 Granier, 2000, Water balance, transpiration and canopy conductance in two beech stands, Agric. For. Meteor., 122, 215 Gu, 2018, Plastic film mulch promotes high alfalfa production with phosphorus-saving and low risk of soil nitrogen loss, Field Crops Res., 229, 44, 10.1016/j.fcr.2018.09.011 Guyot, 2017, Soil-water content characterisation in a modified Jarvis-Stewart model: a case study of a conifer forest on a shallow unconfined aquifer, J. Hydrol., 544, 242, 10.1016/j.jhydrol.2016.11.041 Han, 2019, Characteristics and boundary line analysis of canopy transpiration of Ulmus pumila to environmental driving factors, J. Northeast For. Univ., 47, 22 Hernandez-Santana, 2011, Enhanced transpiration by riparian buffer trees in response to advection in a humid temperate agricultural landscape, For. Ecol. Manag., 261, 1415, 10.1016/j.foreco.2011.01.027 Hu, 2019, Exploring optimal soil mulching for the wheat-maize cropping system in sub-humid drought-prone regions in China, Agric. Water Manag., 219, 59, 10.1016/j.agwat.2019.04.004 Huang, 2011, Rainfed farming systems in the Loess Plateauof China, 643 Jarvis, 1976, The interception of the variations in leaf water potential and stomatal conductance found in canopies in the field, Philos. Trans. Roy. Soc. Lond. B, 273, 593, 10.1098/rstb.1976.0035 Jia, 2018, Effects of planting patterns and sowing densities on grain-filling, radiation use efficiency and yield of maize (Zea mays L.) in semi-arid regions, Agric. Water Manag., 201, 287, 10.1016/j.agwat.2017.11.025 Jiang, 2016, Evapotranspiration partitioning and variation of sap flow in female and male parents of maize for hybrid seed production in arid region, Agric. Water Manag., 176, 132, 10.1016/j.agwat.2016.05.022 Kato, 2004, Estimation of evapotranspiration, transpiration ratio and water-use efficiency from a sparse canopy using a compartment model, Agric. Water Manag., 65, 173, 10.1016/j.agwat.2003.10.001 Kisi, 2015, Pan evaporation modeling using least square support vector machine, multivariate adaptive regression splines and M5 model tree, J. Hydrol., 528, 312, 10.1016/j.jhydrol.2015.06.052 Kool, 2014, A review of approaches for evapotranspiration partitioning, Agric. For. Meteorol., 184, 56, 10.1016/j.agrformet.2013.09.003 Li, 2017, Dynamics and responses of sap flow of Haloxylon ammodendron to environmental variables in the southern edge of the Gurbantünggüt Desert, Arid Land Geogr., 40, 795 Li, 2018, Mulching improves yield and water-use efficiency of potato cropping in China: a meta-analysis, Field Crops Res., 221, 50, 10.1016/j.fcr.2018.02.017 Li, 2013, Measuring and modeling maize evapotranspiration under plastic film-mulching condition, J. Hydrol., 503, 153, 10.1016/j.jhydrol.2013.07.033 Li, 2016, Response of Populus euphratica Oliv. sap flow to environmental variables for a desert riparian forest in the Heihe River Basin, Northwest China J. Arid Land, 8, 591, 10.1007/s40333-016-0045-4 Li, 2016, Applying segmented Jarvis canopy resistance into Penman-Monteithmodel improves the accuracy of estimated evapotranspiration inmaize for seed production with film-mulching in arid area, Agric. Water Manag., 178, 314, 10.1016/j.agwat.2016.09.016 Li, 2017, Spatial distribution of soil water, soil temperature, and plant roots in a drip-irrigated intercropping field with plastic mulch, Eur. J. Agron., 83, 47, 10.1016/j.eja.2016.10.015 Liu, 2014, Maize yield and water balance is affected by nitrogen application in a film-mulching ridge–furrow system in a semiarid region of China, Eur. J. Agron., 52, 103, 10.1016/j.eja.2013.10.001 Liu, 2009, Simulation of artificial neural network model for trunk sap flow of Pyrus pyrifolia and its comparison with multiple-linear regression, Agric. Water Manag., 96, 939, 10.1016/j.agwat.2009.01.003 Matsumoto, 2005, Dependence of stomatal conductance on leaf chlorophyll concentration and meteorological variables, Agric. For. Meteorol., 132, 44, 10.1016/j.agrformet.2005.07.001 Matsumoto, 2008, Responses of surface conductance to forest environments in the Far East, Agric. For. Meteor., 148, 1926, 10.1016/j.agrformet.2008.09.009 Mckee, 1964, A coefficient for computing leaf area in hybrid corn, Agron. J., 56, 240, 10.2134/agronj1964.00021962005600020038x Mirjalili, 2016, The whale optimization algorithm, Adv. Eng. Softw., 95, 51, 10.1016/j.advengsoft.2016.01.008 Mo, 2016, Ridge-furrow mulching system in semiarid Kenya: a promising solution to improve soil water availability and maize productivity, Eur. J. Agron., 80, 124, 10.1016/j.eja.2016.07.005 Monteith, 1965, Evaporation and Environment, Symp. Soc. Exp. Biol., 19, 204 Oren, 2001, Sensitivity of mean canopy stomatal conductance to vapor pressure deficit in a flooded Taxodium distichum L. forest: hydraulic and non-hydraulic effects, Oecologia, 126, 21, 10.1007/s004420000497 Penman, 1948, Natural evaporation from open water, bare soil and grass, Proc. R. Soc. Lond., A193, 120 Qin, 2019, Transpiration of female and male parents of seed maize in northwest China, Agric. Water Manag., 213, 397, 10.1016/j.agwat.2018.10.016 Quej, 2017, ANFIS, SVM and ANN soft-computing techniques to estimate daily global solar radiation in a warm sub-humid environment, J. Atmos. Sol. Terr. Phys., 155, 62, 10.1016/j.jastp.2017.02.002 Ramakrishna, 2006, Effect of mulch on soil temperature, moisture, weed infestation and yield of groundnut in northern Vietnam, Field Crops Res., 95, 115, 10.1016/j.fcr.2005.01.030 Rhebergen, 2020, Closing yield gaps in oil palm production systems in Ghana through best management practices, Eur. J. Agron., 115, 10.1016/j.eja.2020.126011 Sakuratani, 1981, A heat balance method for measuring water flow in the stem of intact plants, J. Agric. Meteorol., 37, 9, 10.2480/agrmet.37.9 Schmidt-Walter, 2014, Transpiration and water use strategies of a young and a full-grown short rotation coppice differing in canopy cover and leaf area, Agric. For. Meteor., 195–196, 165, 10.1016/j.agrformet.2014.05.006 Shrestha, 2015, Support vector machine based modeling of evapotranspiration using hydro-climatic variables in a sub-tropical environment, Agric. For. Meteorol., 200, 172, 10.1016/j.agrformet.2014.09.025 Shuttleworth, 1985, Evaporation from sparse crops-an energy combination theory, Q. J. R. Meteorol. Soc., 111, 839, 10.1002/qj.49711146910 Stewart, 1988, Modelling surface conductance of pine forest, Agric. For. Meteor., 43, 19, 10.1016/0168-1923(88)90003-2 Tang, 2018, Evaluation of artificial intelligence models for actual crop evapotranspiration modeling in mulched and non-mulched maize croplands, Comput. Electron. Agric., 152, 375, 10.1016/j.compag.2018.07.029 Tu, 2019, Improvement of sap flow estimation by including phenological index and time-lag effect in back-propagation neural network models, Agric. For. Meteorol., 276–277 Van der Laan, 2019, Are water footprints accurate enough to be useful? a case study for maize (Zea mays L.), Agric. Water Manag., 213, 512, 10.1016/j.agwat.2018.10.026 Vapnik, V.N., 1999. An overview of statistical learning theory. IEEE Transactions on Neural Networks. Wang, 2017, Pan evaporation modeling using six different heuristic computing methods in different climates of China, J. Hydrol., 544, 407, 10.1016/j.jhydrol.2016.11.059 Wang, 2020, Maize transpiration and water productivity of two irrigated fields with varying groundwater depths in an arid area, Agric. For. Meteorol., 281, 10.1016/j.agrformet.2019.107849 Wang, 2017, An empirical calibration for heat-balance sap-flow sensors in maize, Agronomy, 109, 1122, 10.2134/agronj2016.10.0611 Welde, 2016, Effect of different furrow and plant spacing on yield and water use efficiency of maize, Agric. Water Manag., 177, 215, 10.1016/j.agwat.2016.07.026 Whitley, 2008, A modified Jarvis-Stewart model for predicting stand-scale transpiration of an Australian native forest, Plant Soil, 305, 35, 10.1007/s11104-007-9399-x Whitley, 2009, Comparing the Penman–Monteith equation and a modified Jarvis–Stewart model with an artificial neural network to estimate stand-scale transpiration and canopy conductance, J. Hydrol., 373, 256, 10.1016/j.jhydrol.2009.04.036 Whitley, 2013, Developing an empirical model of canopy water flux describing the common response of transpiration to solar radiation and VPD across five contrasting woodlands and forests, Hydrol. Process., 27, 1133, 10.1002/hyp.9280 Wu, 2019, Daily reference evapotranspiration prediction based on hybridized extreme learning machine model with bio-inspired optimization algorithms: application in contrasting climates of China, J. Hydrol., 577, 10.1016/j.jhydrol.2019.123960 Xu, 2017, Comparing three models to estimate transpiration of desert shrubs, J. Hydrol., 550, 603, 10.1016/j.jhydrol.2017.05.027 Yan, 2017, Estimation of drip irrigated summer maize soil water content and evapotranspiration based on SIMDualKc model, Trans. CSAE, 33, 152 Yan, 2021, A novel hybrid WOA-XGB model for estimating daily reference evapotranspiration using local and external meteorological data: applications in arid and humid regions of China, Agric. Water Manag., 244, 10.1016/j.agwat.2020.106594 Yang, 2020, A physical process and machine learning combined hydrological model for daily streamflow simulations of large watersheds with limited observation data, J. Hydrol., 590, 10.1016/j.jhydrol.2020.125206 Zhang, 2016, Multi-scale evapotranspiration of summer maize and the controllingmeteorological factors in north China, Agric. For. Meteor., 216, 1, 10.1016/j.agrformet.2015.09.015 Zhang, 2011, Evapotranspiration components determined by sap flow and microlysimetry techniques of a vineyard in northwest China: Dynamics and influential factors, Agric. Water Manag., 98, 1207, 10.1016/j.agwat.2011.03.006 Zheng, 2018, Rainfall partitioning into throughfall, stemflow and interception loss by maize canopy on the semi-arid Loess Plateau of China, Agric. Water Manag., 195, 25, 10.1016/j.agwat.2017.09.013 Zheng, 2018, Mulching mode and planting density affect canopy interception loss of rainfall and water use efficiency of dryland maize on the Loess Plateau of China, J. Arid Land, 10, 794, 10.1007/s40333-018-0122-y Zheng, 2020, Ridge-furrow plastic mulching with a suitable planting density enhances rainwater productivity, grain yield and economic benefit of rainfed maize, J. Arid Land, 12, 181, 10.1007/s40333-020-0001-1 Zheng, 2021, Evapotranspiration partitioning and water productivity of rainfed maize under contrasting mulching conditions in Northwest China, Agric. Water Manag., 243, 10.1016/j.agwat.2020.106473