Integrating WOFOST and Noah LSM for modeling maize production and soil moisture with sensitivity analysis, in the east of The Netherlands

Eweys, Omar Ali; Elwan, A.; Borham, Taha I.

doi:10.1016/j.fcr.2017.06.004

Cited by 24 publications

(14 citation statements)

References 43 publications

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“…Nitrogen Temperature √ √ × √ [27] Consequently, Zhou et al [42], Li et al [43], Li et al [44], and Eweys, Elwan and Borham [34] proposed the coupling of crop and hydrologic models to maximize their advantages. This approach appears to be beneficial, and it has been used in some studies.…”

Section: Name Version Water Saltmentioning

confidence: 99%

“…In addition, the present modifications added ESs to reduce CO 2 assimilation in WOFOST before biomass partitioning, assuming that the effects of environmental stress would impact all organs act in the same way; thus, compared with some specific studies, our present strategy was short of mechanism [89][90][91]. Although many previous studies have used similar methods to consider drought stress in WOFOST [34,42], further efforts, especially experimental studies, should focus on the effects of environmental factors on feedback between crop organs, which may also provide more reliable evidence to update the present empirical biomass partitioning coefficients in WOFOST. However, as stated above, the present modifications for WOFOST mainly focused on the balance of the crop growth mechanism and practical applications, which was also the motivation to modify the physical-based WOFOST model with a statistical method.…”

Section: Limitationsmentioning

confidence: 99%

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Testing and Improving the WOFOST Model for Sunflower Simulation on Saline Soils of Inner Mongolia, China

Zhu

Zeng

et al. 2018

Agronomy

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Monitoring and improving environmental stress in crops is vital for the sustainable development of agriculture and food security. Traditional experimental methods are costly and time-consuming, yet crop growth models focus mainly only on water and nutrient stresses. In this study, a new World Food Studies (WOFOST) model, WOFOST-ES, was developed by the addition of a general environmental stress factor (ES). To calibrate and validate WOFOST-ES, two-year micro-plot experiments and one-year field experiments with sunflower were conducted in the Hetao Irrigation District, China. The results of the micro-plot experiments indicated that the WOFOST model failed to simulate sunflower growth correctly but that the WOFOST-ES model was highly accurate in simulating both yield (R2 = 0.99, root mean square error (RMSE) = 56 kg/ha) and leaf area index (LAI) (R2 = 0.86, RMSE = 0.44). A statistical method for estimating ESs based on the dominant stress factor (salt at our study site) was also proposed as a supplemental tool for WOFOST-ES, and micro-plot and field experiments conducted in 2013 and 2017 both proved acceptable accuracy of the statistical method when using WOFOST-ES. Comparison between ESs and the water and salt stress factors of Feddes-type stress reduction functions indicated that ESs failed to reveal actual environmental stresses during the sunflower seeding stage but did reflect other environmental stresses in addition to water and salt during the bud, flowering, and maturity stages. Although the present WOFOST-ES model proved to be accurate, stable, and practical, future studies should be performed, focusing on the physical separation of ESs, their mechanistic quantification, and their evaluation at small time steps using more observations.

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Section: Name Version Water Saltmentioning

confidence: 99%

Section: Limitationsmentioning

confidence: 99%

Testing and Improving the WOFOST Model for Sunflower Simulation on Saline Soils of Inner Mongolia, China

Zhu

Zeng

et al. 2018

Agronomy

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“…Sensitivity analyses are used to evaluate the responses of model outputs to changes in model input parameters and to quantify the relative importance of those responses [35,36]. Many studies have been conducted to evaluate the sensitivity of plant parameters and the management practices of different crops under different models [24,[37][38][39][40][41][42][43]. Although the sensitivity assessment of soil is essential [25], limited attention has been paid to evaluating the sensitivity of soil parameters [42].…”

Section: Introductionmentioning

confidence: 99%

A Functional Analysis of Pedotransfer Functions Developed for Sri Lankan soils: Applicability for Process-Based Crop Models

et al. 2020

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As measurements are expensive and laborious, the estimation of soil hydraulic properties using pedotransfer functions (PTFs) has become popular worldwide. However, the estimation of soil hydraulic properties is not the final aim but an essential input value for other calculations and simulations, mostly in environmental and crop models. This modeling approach is a popular way to assess agricultural and environmental processes. However, it is rarely used in Sri Lanka because soil hydraulic data are rare. We evaluated the functionality of PTFs (developed to estimate field capacity (FC) and the permanent wilting point (PWP) of Sri Lankan soils) for process-based crop models. We used the Agricultural Production Systems sIMulator (APSIM) as the test model. Initially, we confirmed the importance of PWP (LL15) and FC (DUL) by assessing the sensitivity of the soil input parameters on the growth and yield of rice under rainfed conditions. We simulated the growth and yield of rice and the four selected outputs related to the APSIM soil module using the measured and estimated values of FC and PWP. These simulations were conducted for ten years in 16 locations of Sri Lanka, representing wet, intermediate, and dry zones. The simulated total aboveground dry matter and weight of the rough rice, using both input conditions (the measured and PTF-estimated soil hydraulic properties), showed good agreement, with no significant differences between each other. Outputs related to the soil module also showed good agreement, as no significant differences were found between the two input conditions (measured and PTF-estimated soil hydraulic properties). Although the DUL and LL15 are the most influential parameters for the selected outputs of APSIM-Oryza, the estimated FC and PWP values did not change the predictive ability of APSIM. In this way, the functionality of PTFs for APSIM crop modeling is confirmed.Agronomy 2020, 10, 285 2 of 18 world, especially in tropical regions [1]. Pedotransfer functions (PTFs) are predictive functions used to estimate difficult-to-measure soil parameters with easily measurable soil parameters [2]. Point-based PTFs are used to determine soil parameters at specific, conventional values of matric potential [3]. The moisture content at −10 and −33 kPa (representing the field capacity (FC)) and moisture content at -1500 kPa (representing the permanent wilting point (PWP)) are the most common reference values for the soil moisture characteristic curve (SMCC) used for point PTFs [4].Point PTFs were developed [5] for Sri Lankan soil and confirmed the statistical accuracy of these PTFs for Sri Lankan conditions. However, these PTFs cannot perfectly calculate soil hydraulic parameters. In other words, there are always some errors that could be over or underestimated according to soil type. These errors may be different according to the application of the PTFs. Hence, the final estimation of the model quality should be defined by the model's applicability [6] because the estimation of hydraulic properties is not the...

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“…The core of any crop growth model is that a set of equations are employed to estimate biomass production from the captured carbon dioxide, solar radiation, and water, mainly including carbon-driven (WOFOST), radiation-driven (EPIC and STICS), and water-driven (CropSyst and AquaCrop) models [15]. Although the driving mechanism of several models is different, many models can be used to perform growth simulations under water stress conditions by considering water balance components, thereby accomplishing crop growth simulation and yield prediction [26][27][28][29][30], as well as evaluating crop water requirements and implementing irrigation management [31][32][33][34][35]. In addition, the water-driven AquaCrop model has been successfully employed to optimize fertigation strategies for orange production, predict the yield of peach trees under different deficit percentages [36,37], and evaluate the transpiration reductions of mature olive trees [38].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Performance of the WOFOST Model in Simulating Jujube Fruit Tree Growth under Different Irrigation Regimes

et al. 2019

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Cropping system models are widely employed to evaluate plant water requirements and growth situations. However, these models rarely focus on growth studies of perennial fruit trees. The aim of this study was to evaluate the performance of the WOFOST (WOrld FOod STudies) model in simulating jujube fruit tree growth under different irrigation treatments. The model was calibrated on data obtained from full irrigation treatments in 2016 and 2017. The model was validated on four deficit percentages (60%, 70%, 80%, and 90%) and one full irrigation treatment from 2016 to 2018. Calibrated R2 and RMSE values of simulated versus measured soil moisture content, excluding samples on the day of irrigation and first day after irrigation, reached 0.94 and 0.005 cm3 cm−3. The model reproduced growth dynamics of the total biomass and leaf area index, with a validated R2 = 0.967 and RMSE = 0.915 t ha−1, and R2 = 0.962 and RMSE = 0.160 m2 m−2, respectively. The model also showed good global performance, with R2 = 0.86 and RMSE = 0.51 t ha−1, as well as good local agreement (R2 ≥ 0.8 ) and prediction accuracy (RMSE ≤ 0.62 t ha−1) for each growth season. Furthermore, 90% of full irrigation can be recommended to achieve a balance between jujube yields and water savings (average decline ratio of yield ≤ 3.8%).

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Integrating WOFOST and Noah LSM for modeling maize production and soil moisture with sensitivity analysis, in the east of The Netherlands

Cited by 24 publications

References 43 publications

Testing and Improving the WOFOST Model for Sunflower Simulation on Saline Soils of Inner Mongolia, China

Testing and Improving the WOFOST Model for Sunflower Simulation on Saline Soils of Inner Mongolia, China

A Functional Analysis of Pedotransfer Functions Developed for Sri Lankan soils: Applicability for Process-Based Crop Models

Assessing the Performance of the WOFOST Model in Simulating Jujube Fruit Tree Growth under Different Irrigation Regimes

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