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Xiaotao Hu
Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A & F University, Xianyang 712100, China

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Review
Published: 05 July 2021 in Agronomy
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In order to meet the growing food demand of the global population and maintain sustainable soil fertility, there is an urgent need to optimize fertilizer application amount in agricultural production practices. Most of the existing studies on the optimal K rates for apple orchards were based on case studies and lack information on optimizing K-fertilizer management on a regional scale. Here, we used the method of combining meta-analysis with the K application rate-yield relationship model to quantify and summarize the optimal K rates of the Loess Plateau and Bohai Bay regions in China. We built a dataset based on 159 observations obtained from 18 peer-reviewed literature studies distributed in 15 different research sites and evaluated the regional-scale optimal K rates for apple production. The results showed that the linear plus platform model was more suitable for estimating the regional-scale optimal K rates, which were 208.33 and 176.61 kg K ha−1 for the Loess Plateau and Bohai Bay regions of China, respectively. Compared with high K application rates, the optimal K rates increased K use efficiency by 45.88–68.57%, with almost no yield losses. The optimal K rates also enhanced the yield by 6.30% compared with the low K application rates.

ACS Style

Wenzheng Tang; Wene Wang; Dianyu Chen; Ningbo Cui; HaoSheng Yang; Xiaotao Hu. Evaluation of the Regional-Scale Optimal K Rate Based on Sustainable Apple Yield and High-Efficiency K Use in Loess Plateau and Bohai Bay of China: A Meta-Analysis. Agronomy 2021, 11, 1368 .

AMA Style

Wenzheng Tang, Wene Wang, Dianyu Chen, Ningbo Cui, HaoSheng Yang, Xiaotao Hu. Evaluation of the Regional-Scale Optimal K Rate Based on Sustainable Apple Yield and High-Efficiency K Use in Loess Plateau and Bohai Bay of China: A Meta-Analysis. Agronomy. 2021; 11 (7):1368.

Chicago/Turabian Style

Wenzheng Tang; Wene Wang; Dianyu Chen; Ningbo Cui; HaoSheng Yang; Xiaotao Hu. 2021. "Evaluation of the Regional-Scale Optimal K Rate Based on Sustainable Apple Yield and High-Efficiency K Use in Loess Plateau and Bohai Bay of China: A Meta-Analysis." Agronomy 11, no. 7: 1368.

Journal article
Published: 15 June 2021 in Horticulturae
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Precise irrigation management of grapevines in greenhouses requires a reliable method to easily quantify and monitor the grapevine water status to enable effective manipulation of the water stress of the plants. This study describes a study on stem diameter variations of grapevine planted in a greenhouse in the semi-arid area of Northwest China. In order to determine the applicability of signal intensity of stem diameter variation to evaluate the water status of grapevine and soil. The results showed that the relative variation curve of the grapevine stem diameter from the vegetative stage to the fruit expansion stage showed an overall increasing trend. The correlations of MDS (maximum daily shrinkage) and DI (daily increase) with meteorological factors were significant (p< 0.05), and the correlations with SWP, RWC and soil moisture were weak. Although MDS and DI can diagnose grapevine water status in time, SIMDS and SIDI have the advantages of sensitivity and signal intensity compared with other indicators. Compared with MDS and DI, the R2 values of the regression equations of SIMDS and SIDI with SWP and RWC were high, and the correlation reached a very significant level (p< 0.01). Thus, SIMDS and SIDI are more suitable for the diagnosis of grapevine water status. The SIMDS peaked at the fruit expansion stage, reaching 0.957–1.384. The signal-to-noise ratio of SIDI was higher than that of MDS across the three treatments at the vegetative stage. The value and signal-to-noise ratio of SIDI at the flowering stage were similar to those of SIMDS, while the correlation between SIDI and the soil moisture content was higher than that of SIMDS. It can be concluded that that SIDI is suitable as an indicator of water status of grapevine and soil during the vegetative and flowering stages. In addition, the signal-to-noise ratio of SIMDS during the fruit expansion and mature stages was significantly higher than that of SIDI. Therefore, SIMDS is suitable as an indicator of the moisture status of grapevine and soil during the fruit expansion and mature stages. In general, SIMDS and SIDI were very good predictors of the plant water status during the growth stage and their continuous recording offers the promising possibility of their use in automatic irrigation scheduling in grapevine.

ACS Style

Chen Ru; Xiaotao Hu; Wene Wang; Hui Ran; Tianyuan Song; Yinyin Guo. Signal Intensity of Stem Diameter Variation for the Diagnosis of Drip Irrigation Water Deficit in Grapevine. Horticulturae 2021, 7, 154 .

AMA Style

Chen Ru, Xiaotao Hu, Wene Wang, Hui Ran, Tianyuan Song, Yinyin Guo. Signal Intensity of Stem Diameter Variation for the Diagnosis of Drip Irrigation Water Deficit in Grapevine. Horticulturae. 2021; 7 (6):154.

Chicago/Turabian Style

Chen Ru; Xiaotao Hu; Wene Wang; Hui Ran; Tianyuan Song; Yinyin Guo. 2021. "Signal Intensity of Stem Diameter Variation for the Diagnosis of Drip Irrigation Water Deficit in Grapevine." Horticulturae 7, no. 6: 154.

Journal article
Published: 24 December 2020 in Atmosphere
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Reference crop evapotranspiration (ET0) is an important indicator for precise regulation of crop water content, irrigation forecast formulation, and regional water resources management. The Hargreaves model (HG) is currently recognized as the simplest and most effective ET0 estimation model. To further improve the prediction accuracy of the HG model, this study is based on the data of 98 meteorological stations in southwest China (1961–2019), using artificial bee colony (ABC), differential evolution (DE) and particle swarm optimization (PSO) algorithms to calibrate the HG model globally. The standard ET0 value was calculated by FAO-56 Penman–Monteith (PM) model. We compare the calculation accuracy of 3 calibrated HG models and 4 empirical models commonly used (Hargreaves, Priestley–Taylor, Imark–Allen and Jensen–Hais). The main outcomes demonstrated that on a daily scale, the calibrated HG models (R2 range 0.74–0.98) are more accurate than 4 empirical models (R2 range 0.55–0.84), and ET0-PSO-HG has the best accuracy, followed by ET0-ABC-HG and ET0-DE-HG, with average R2 of 0.83, 0.82 and 0.80, average RRMSE of 0.23 mm/d, 0.25 mm/d and 0.26 mm/d, average MAE of 0.52 mm/d, 0.53 mm/d and 0.57 mm/d, and average GPI of 0.17, 0.05, and 0.04, respectively; on a monthly scale, ET0-PSO-HG also has the highest accuracy, followed by ET0-ABC-HG and ET0-DE-HG, with median R2 of 0.96, 0.95 and 0.94, median RRMSE of 0.16 mm/d, 0.17 mm/d and 0.18 mm/d respectively, median MAE of 0.46 mm/d, 0.50 mm/d, and 0.55 mm/d, median GPI of 1.12, 0.44 and 0.34, respectively. The calibrated HG models (relative error of less than 10.31%) are also better than the four empirical models (relative error greater than 16.60%). Overall, the PSO-HG model has the most accurate ET0 estimation on daily and monthly scales, and it can be suggested as the preferred model to predict ET0 in humid regions in southwest China regions.

ACS Style

Zongjun Wu; Ningbo Cui; Bin Zhu; Long Zhao; Xiukang Wang; Xiaotao Hu; Yaosheng Wang; Shidan Zhu. Improved Hargreaves Model Based on Multiple Intelligent Optimization Algorithms to Estimate Reference Crop Evapotranspiration in Humid Areas of Southwest China. Atmosphere 2020, 12, 15 .

AMA Style

Zongjun Wu, Ningbo Cui, Bin Zhu, Long Zhao, Xiukang Wang, Xiaotao Hu, Yaosheng Wang, Shidan Zhu. Improved Hargreaves Model Based on Multiple Intelligent Optimization Algorithms to Estimate Reference Crop Evapotranspiration in Humid Areas of Southwest China. Atmosphere. 2020; 12 (1):15.

Chicago/Turabian Style

Zongjun Wu; Ningbo Cui; Bin Zhu; Long Zhao; Xiukang Wang; Xiaotao Hu; Yaosheng Wang; Shidan Zhu. 2020. "Improved Hargreaves Model Based on Multiple Intelligent Optimization Algorithms to Estimate Reference Crop Evapotranspiration in Humid Areas of Southwest China." Atmosphere 12, no. 1: 15.

Journal article
Published: 20 November 2020 in Horticulturae
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Precise irrigation management of grapevines in greenhouses requires a reliable method to easily quantify and monitor the grapevine water status to enable effective manipulation of the water stress of the plants. This study evaluated the applicability of crop water stress index (CWSI) based on the leaf temperature for diagnosing the grapevine water status. The experiment was conducted at Yuhe Farm (northwest China), with drip-irrigated grapevines under three irrigation treatments. Meteorological factors, soil moisture contents, leaf temperature, growth indicators including canopy coverage and fruit diameter, and physiological indicators including SPAD (relative chlorophyll content), stem water potential (φs), stomatal conductance (gs), and transpiration rate (E) were studied during the growing season. The results show that the relationship between the leaf-air temperature difference (Tc-Ta) and the plant water status indicators (φs, gs, E) were significant (P < 0.05), and the relationship between gs, E and Tc-Ta was the closest, with R2 values ranging from 0.530–0.604 and from 0.545–0.623, respectively. CWSI values are more easily observed on sunny days, and it was determined that 14:00 BJS is the best observation time for the CWSI value under different non-water-stressed baselines. There is a reliable linear correlation between the CWSI value and the soil moisture at 0–40 cm (P < 0.05), which could provide a reference when using the CWSI to diagnose the water status of plants. Compared with the Tc-Ta value, the CWSI could more accurately monitor the plant water status, and above the considered indictors, gs has the greatest correlation with the CWSI.

ACS Style

Chen Ru; Xiaotao Hu; Wene Wang; Hui Ran; Tianyuan Song; Yinyin Guo. Evaluation of the Crop Water Stress Index as an Indicator for the Diagnosis of Grapevine Water Deficiency in Greenhouses. Horticulturae 2020, 6, 86 .

AMA Style

Chen Ru, Xiaotao Hu, Wene Wang, Hui Ran, Tianyuan Song, Yinyin Guo. Evaluation of the Crop Water Stress Index as an Indicator for the Diagnosis of Grapevine Water Deficiency in Greenhouses. Horticulturae. 2020; 6 (4):86.

Chicago/Turabian Style

Chen Ru; Xiaotao Hu; Wene Wang; Hui Ran; Tianyuan Song; Yinyin Guo. 2020. "Evaluation of the Crop Water Stress Index as an Indicator for the Diagnosis of Grapevine Water Deficiency in Greenhouses." Horticulturae 6, no. 4: 86.

Short communication
Published: 14 August 2020 in National Academy Science Letters
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Among all the factors affecting evapotranspiration (ET) in arid areas, the land use types of underlying surface play a dominant role. Under the effects of climate change and human activities, there was a significant change of land use and land cover change in China, special at loess plateau. Based on satellite remote sensing data and ground observation data, this study analyzed the influences of four land types’ urbanization on ET in arid areas from 2010 to 2015. The results showed that rural residence areas’ urbanization has the most magnificent effect on ET after excluding meteorological effects.

ACS Style

Shanlin Tong; Chenfeng Cui; Xiaotao Hu; Wene Wang; Weiguang Wang; Yifei Yao. Quantitative Research on the Influence of Urbanization of Land Types on Evapotranspiration in Arid Areas. National Academy Science Letters 2020, 44, 419 -421.

AMA Style

Shanlin Tong, Chenfeng Cui, Xiaotao Hu, Wene Wang, Weiguang Wang, Yifei Yao. Quantitative Research on the Influence of Urbanization of Land Types on Evapotranspiration in Arid Areas. National Academy Science Letters. 2020; 44 (5):419-421.

Chicago/Turabian Style

Shanlin Tong; Chenfeng Cui; Xiaotao Hu; Wene Wang; Weiguang Wang; Yifei Yao. 2020. "Quantitative Research on the Influence of Urbanization of Land Types on Evapotranspiration in Arid Areas." National Academy Science Letters 44, no. 5: 419-421.

Journal article
Published: 16 June 2020 in Agricultural Water Management
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Irrigation and nitrogen fertilizer management (INM) are essential for maize production. In northwest China, the conventional INM, in which irrigation of about 90-120 mm is carried out four or five times with large nitrogen (N) fertilizer inputs (approximately 450 kg N ha-1), generally result in low water use efficiency (WUE) and N use efficiency (NUE) with a series of environmental pollution problems. The main objective of this study was to optimize the INM for spring maize using the Root Zone Water Quality Model 2 (RZWQM2). The RZWQM2 was first calibrated and verified based on a two-year experiment. The NRMSEs (normalized root mean square errors) for the simulated grain yield, aboveground biomass, plant N uptake and grain N uptake were 7.02%, 6.75%, 10.73% and 12.40%, respectively, in the calibration period; were 9.73%, 7.96%, 12.00% and 15.34%, respectively, in the validation period. The NRMSEs for the simulated soil water content and soil nitrate N content at different depths ranged from 8.29% to 24.52% and from 13.34% to 32.83% across the calibration and validation period, respectively. The calibrated model was used to investigate grain yield, biomass, plant-level WUE (WUEp) and plant-level NUE (NUEp) under different transpiration and plant N uptake characteristics of maize plants. Simulation results indicated that the maize plants with high WUEp generally have high NUEp, and reducing transpiration is an effective way to improve either WUEp or NUEp. Furthermore, the calibrated model was used to evaluate different INM options including N application rates, split N strategies and irrigation strategies. Based on simulation results, split N application is not necessary if water drainage is effectively controlled. The optimal N fertilizer rate is 200 kg ha-1 N and is encouraged to be applied once as a base fertilizer. The irrigation practice, in which irrigation is adopted to refill the primary root zone (PRZ, 0-60 cm) to available water capacity (AWC) when available water in the PRZ decreases to 15% AWC, achieved the highest WUE (2.23 kg m-3) among all alternative irrigation practice options with a high grain yield (12.6 t ha-1) and so is recommended. Compared with conventional INM, the optimal INM decreased irrigation amount by 14.7%, water drainage by 53.7% and N leaching by 80.5% but increased WUE by 8.9% with a comparable grain yield.

ACS Style

Shiwei Zhou; Xiaotao Hu; Hui Ran; Wenè Wang; Neil Hansen; Ningbo Cui. Optimization of irrigation and nitrogen fertilizer management for spring maize in northwestern China using RZWQM2. Agricultural Water Management 2020, 240, 106276 .

AMA Style

Shiwei Zhou, Xiaotao Hu, Hui Ran, Wenè Wang, Neil Hansen, Ningbo Cui. Optimization of irrigation and nitrogen fertilizer management for spring maize in northwestern China using RZWQM2. Agricultural Water Management. 2020; 240 ():106276.

Chicago/Turabian Style

Shiwei Zhou; Xiaotao Hu; Hui Ran; Wenè Wang; Neil Hansen; Ningbo Cui. 2020. "Optimization of irrigation and nitrogen fertilizer management for spring maize in northwestern China using RZWQM2." Agricultural Water Management 240, no. : 106276.

Journal article
Published: 17 March 2020 in Agricultural and Forest Meteorology
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As water scarcity becomes more acute in many parts of the world, crop modeling tools that effectively simulating crop response to deficit irrigation strategies to help investigate management improvement are needed. Identifying the strengths and weaknesses of the crop models with different growth-engines are therefore of great importance. The objective of this study was to investigate the capability and improvements of the new version of a solar energy-driven crop model (DSSAT-CERES-Maize, v4.7.5.0) in simulating water consumption and yield of hybrid seed maize under different soil water conditions, and its comparison with a water-driven crop model (AquaCrop, v4.0). Data obtained from a 4-year (2012–2015) field trial on maize grown under different irrigation treatments at Wuwei, Northwest China, was used for this assessment. These models were calibrated and validated using measured daily evapotranspiration (ET), leaf area index (LAI), aboveground biomass, yield (Y), harvest index (HI) and soil water content (SWC). Daily ET was measured using a combination of an eddy covariance (EC) system, sap flow sensors, and micro-lysimeter cylinders. The ability of DSSAT-CERES-Maize using the two different ET options, i.e., Priestley-Taylor/Ritchie (PT) and FAO-56 Penman-Monteith (PM) was analyzed. The results showed that DSSAT-CERES-Maize with the PT approach had fair agreement with measured daily ET of maize under non-water stress condition (R2=0.85; NRMSE=26.7%), but poor agreement with ET under water stress conditions (R2=0.51; NRMSE=43.8%). DSSAT-CERES-Maize with the PM approach systematically underestimated ET by up to 13% under non-water stress condition, which was mainly attributed to that the maximum static CERES-Maize crop coefficient (EORATIO) was currently hard coded to 1.0. Using the PT or FAO-56 PM approach as ET input in DSSAT-CERES-Maize showed no different effect on final biomass (B) and Y simulation for full irrigation. But for water stress conditions, DSSAT-CERES-Maize with the FAO-56 PM approach simulated B and Y with higher overestimation to the measured data than those simulated using the PT approach. The simulated LAI, biomass and SWC by DSSAT-CERES-Maize using the PT approach generally well followed the trend of the measured values for most irrigation treatments. The model with the PT approach showed acceptable prediction for B and Y of different irrigation treatments across years, with NRMSE of 15.5% and 26.2%, respectively, but the accuracy decreased with an aggravation of water stress. Furthermore, the strengths and weaknesses of DSSAT-CERES-Maize and AquaCrop, and their different cores of growth-engines, i.e. RUE and normalized water productivity (WP*) were carefully discussed. It was concluded that DSSAT-CERES-Maize was a superior estimate of maize yield than was AquaCrop, especially when the climate varied dramatically between years. But DSSAT-CERES-Maize, for the simulation of maize water consumption in an arid region where drought often occurs, was inferior to AquaCrop. These results contribute to recommend the appropriate crop model for specific modeling goals.

ACS Style

Hui Ran; Shaozhong Kang; Xiaotao Hu; Sien Li; Wene Wang; Fulai Liu. Capability of a solar energy-driven crop model for simulating water consumption and yield of maize and its comparison with a water-driven crop model. Agricultural and Forest Meteorology 2020, 287, 107955 .

AMA Style

Hui Ran, Shaozhong Kang, Xiaotao Hu, Sien Li, Wene Wang, Fulai Liu. Capability of a solar energy-driven crop model for simulating water consumption and yield of maize and its comparison with a water-driven crop model. Agricultural and Forest Meteorology. 2020; 287 ():107955.

Chicago/Turabian Style

Hui Ran; Shaozhong Kang; Xiaotao Hu; Sien Li; Wene Wang; Fulai Liu. 2020. "Capability of a solar energy-driven crop model for simulating water consumption and yield of maize and its comparison with a water-driven crop model." Agricultural and Forest Meteorology 287, no. : 107955.

Journal article
Published: 22 November 2019 in Science of The Total Environment
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Droughts have destructive impacts on agricultural production; thus, drought projections are vital for the development of future drought mitigation strategies. This work aimed to project a standardized precipitation and evapotranspiration index (SPEI) at 3-, 6- and 12-month timescales for the period 2011–2100 under two representative concentration pathway (RCP) scenarios – RCP 4.5 and RCP 8.5 in mainland China and to assess the changes in various drought indices over a baseline period of 1961–2000. The spatiotemporal variations in drought characteristics (e.g., the drought occurrence time, duration, severity, peak, and frequency and the percentage of stations suffering from drought (PSSD) were estimated by the projected SPEI for the periods 2011–2040, 2041–2070 and 2071–2100. The results showed that mainland China would experience more frequent and severe droughts in the future than in the baseline period, as denoted by SPEI and the generated drought variables. In particular, drier areas of northwestern China were likely to suffer from worse drought conditions than those in other areas, with PSSD values of 60% and 81% by 2100 under the RCP4.5 and RCP 8.5 scenarios, respectively. Although the annual precipitation was projected to increase in most regions, drought conditions would still worsen because of increased the minimum and maximum air temperatures. However, the GCMs contributed more uncertainties to the projection of the SPEI than the stations or the RCPs, because the GCMs made a larger contribution to the variance (>40%). The SPEI performed better than the other indices that only accounted for the influence of a single variable. The relationship between crop yields and the three drought indices varied by month, crop (maize and cotton), and timescale (3- and 6-month). The drought projections from our study can provide invaluable information for stakeholders in developing regionally specific drought adaptation strategies in the face of climate change.

ACS Style

Ning Yao; Linchao Li; Puyu Feng; Hao Feng; De Li Liu; Yang Liu; Kongtao Jiang; Xiaotao Hu; Yi Li. Projections of drought characteristics in China based on a standardized precipitation and evapotranspiration index and multiple GCMs. Science of The Total Environment 2019, 704, 135245 .

AMA Style

Ning Yao, Linchao Li, Puyu Feng, Hao Feng, De Li Liu, Yang Liu, Kongtao Jiang, Xiaotao Hu, Yi Li. Projections of drought characteristics in China based on a standardized precipitation and evapotranspiration index and multiple GCMs. Science of The Total Environment. 2019; 704 ():135245.

Chicago/Turabian Style

Ning Yao; Linchao Li; Puyu Feng; Hao Feng; De Li Liu; Yang Liu; Kongtao Jiang; Xiaotao Hu; Yi Li. 2019. "Projections of drought characteristics in China based on a standardized precipitation and evapotranspiration index and multiple GCMs." Science of The Total Environment 704, no. : 135245.

Journal article
Published: 17 April 2019 in Water
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In order to improve the water use efficiency (WUE) of spring maize in northwest China, the irrigation strategy of adopting limited supplemental irrigation following a high quota pre-sowing irrigation was evaluated under field conditions in 2016 and 2018. There were three treatments (W1, W2 and W3) differing in designed wetting depth (Dh) where soil water was replenished. Dh in W1, W2 and W3 were 0–40, 0–50 and 0–60 cm, respectively. The limited supplemental irrigation was adopted to improve soil water content (SWC) within Dh to field capacity (θFC) when SWC within 0–40 cm layer decreased to 60%θFC following a high rate of pre-sowing irrigation. Results showed that the smaller Dh was beneficial for improving root length density and enhance the utilization of water in subsoil. In both seasons, different Dh led to similar grain yields, which were comparable to the typical regional yield (14.3 t ha−1). The highest WUE (2.79 kg m−3) was achieved in W1 and was 13% more than the typical regional level of 2.46 kg m−3, implying it was adequate for achieving high yield and WUE to maintain SWC in 0–40 cm above 60% θFC with not replenishing soil water in 40–100 cm during the growth season after pre-sowing irrigation.

ACS Style

Zhou; Xiaotao Hu; Wen’E Wang; Hui Ran; Hu; Wang; Ran; Shiwei Zhou; Zhenjiang Zhou. Improving Water Use Efficiency of Spring Maize by Adopting Limited Supplemental Irrigation Following Sufficient Pre-Sowing Irrigation in Northwest China. Water 2019, 11, 802 .

AMA Style

Zhou, Xiaotao Hu, Wen’E Wang, Hui Ran, Hu, Wang, Ran, Shiwei Zhou, Zhenjiang Zhou. Improving Water Use Efficiency of Spring Maize by Adopting Limited Supplemental Irrigation Following Sufficient Pre-Sowing Irrigation in Northwest China. Water. 2019; 11 (4):802.

Chicago/Turabian Style

Zhou; Xiaotao Hu; Wen’E Wang; Hui Ran; Hu; Wang; Ran; Shiwei Zhou; Zhenjiang Zhou. 2019. "Improving Water Use Efficiency of Spring Maize by Adopting Limited Supplemental Irrigation Following Sufficient Pre-Sowing Irrigation in Northwest China." Water 11, no. 4: 802.

Journal article
Published: 19 February 2019 in Field Crops Research
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Simulating yield response to different irrigation scenarios is important for agricultural production, especially in the arid region where agriculture depends heavily on irrigation. To better predict yield under different irrigation scenarios, the variation of normalized water productivity (WP*) over the whole growing period of maize for seed production and the effect of different irrigation treatments on harvest index (HI) were investigated using field experiments from 2012 to 2015 in an arid region of northwest China. Two new non-linear dynamic WP* (WP*KR-L and WP*KR-S) models derived from the Logistic and Sigmoid equations, and four new HI (HIKR-J, HIKR-M, HIKR-B and HIKR-S) models developed on the basis of water deficit multiplicative or additive models at different growth stages were compared with the measurements and the WP* (WP*AC) and HI sub-model (HIAC) in the original AquaCrop model (Version 4.0). In addition, the WP*AC and HIAC models in the original AquaCrop model were replaced by the optimal WP* and HI models to build the AquaCrop-KR model. Then the yield simulated by the AquaCrop-KR model was compared with the measured yield and the yield simulated by the original AquaCrop model. The results show that both WP*KR-L and WP*KR-S models improved the simulation of final biomass, especially for the WP*KR-L model. The tested HI sub-models, namely HIKR-J, HIKR-M, HIKR-B and HIKR-S models had good performance to simulate HI under different irrigation scenarios, and the HIKR-M model was the best among all tested sub-models. When both WP*KR-L and HIKR-M sub-models were embedded into Aquacrop, the performance of the AquaCrop model was improved significantly to simulate yield, especially under severe water stress condition, with R2 increased from 0.496 to 0.653, NRMSE decreased from 26.2% to 16.1% and EF increased from 0.055 to 0.642.

ACS Style

Hui Ran; Shaozhong Kang; Xiaotao Hu; Fusheng Li; Taisheng Du; Ling Tong; Sien Li; Risheng Ding; Zhenjiang Zhou; David Parsons. Newly developed water productivity and harvest index models for maize in an arid region. Field Crops Research 2019, 234, 73 -86.

AMA Style

Hui Ran, Shaozhong Kang, Xiaotao Hu, Fusheng Li, Taisheng Du, Ling Tong, Sien Li, Risheng Ding, Zhenjiang Zhou, David Parsons. Newly developed water productivity and harvest index models for maize in an arid region. Field Crops Research. 2019; 234 ():73-86.

Chicago/Turabian Style

Hui Ran; Shaozhong Kang; Xiaotao Hu; Fusheng Li; Taisheng Du; Ling Tong; Sien Li; Risheng Ding; Zhenjiang Zhou; David Parsons. 2019. "Newly developed water productivity and harvest index models for maize in an arid region." Field Crops Research 234, no. : 73-86.