Remote sensing based estimation system for winter wheat yield in North China Plain

Liu, Honghui; Yang, Xiaohuan; Wang, Naibin

doi:10.1007/s11769-999-0019-y

Cited by 7 publications

(5 citation statements)

References 5 publications

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“…Ammonium bicarbonate (NH 4 HCO 3 ) was mostly applied as the fertilizer. In the model, the crops were fertilized twice in the growing period, with 86 kg of pure nitrogen per hectare each time, and were irrigated four times, with 60 mm of water each time, during the periods of wintering (12/01), stem elongation (3/29), heading (4/20), and grain filling (5/15) [51,52]. Phosphorus and potassium were not simulated in the model.…”

Section: Data Inputs Calibration and Validation Of The Dssat Modelmentioning

confidence: 99%

“…In the DSSAT model, the infiltration and soil water dynamics were simulated based on the equation provided by the Soil Conservations Service of America (Washington, DC, USA) and the one-dimensional water balance model developed by Ritchie [57] (pp. [41][42][43][44][45][46][47][48][49][50][51][52][53][54]. The evapotranspiration was simulated daily using the Penman-Monteith method in FAO-56.…”

Section: Data Inputs Calibration and Validation Of The Dssat Modelmentioning

confidence: 99%

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Impact of Climate Change on the Yield and Water Footprint of Winter Wheat in the Haihe River Basin, China

et al. 2022

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Climate change can impact the yield and water footprint of crops. Therefore, assessing such impacts carries great significance for regional water and food security. This study validated and verified the variety parameters of winter wheat for the Decision Support System for Agrotechnology Transfer (DSSAT) model, using the long-term (1993–2013) growth and yield data observed from six agricultural experiment stations in the Haihe River Basin (HRB), China. The growth process was simulated under three representative concentration pathways (RCPs), named RCP2.6, RCP4.5, and RCP8.5—climate scenarios driven by the HadGEM2-ES model. The variety parameters of winter wheat showed high accuracy in the simulation of the anthesis and maturity dates, and could be used for long-term prediction of the growth process. The trends of climate change had positive impacts on the water footprint of winter wheat but adverse impacts on the yield. The growing period was shortened by 3.6 days, 4.7 days, and 5.0 days per decade in the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, due to the rapid accumulation of heat. The yield would be increased in lower emissions scenarios (17% in RCP2.6), but decreased in high-emissions scenarios due to high temperatures, which may restrict the growth of wheat. The water footprint was decreased by 10%, 11%, and 13% in the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, indicating that the water-use efficiency could be improved in the future. The results showed broad application prospects of the DSSAT model in simulating the response of crop growth to climate change.

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Section: Data Inputs Calibration and Validation Of The Dssat Modelmentioning

confidence: 99%

Section: Data Inputs Calibration and Validation Of The Dssat Modelmentioning

confidence: 99%

Impact of Climate Change on the Yield and Water Footprint of Winter Wheat in the Haihe River Basin, China

et al. 2022

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“…RMSE measures the average magnitude of the error, providing an absolute measure of fit, while NRMSE provides a normalized measure of these errors, allowing for their comparison across different datasets or variables. Liu et al [37] suggested that the simulated results are very good when the NRMSE is below or equal to 15%. If NRMSE is above 15% but below or equal to 30%, the simulation performance is considered good.…”

Section: Discussionmentioning

confidence: 99%

WheatSM V5.0: A Python-Based Wheat Growth and Development Simulation Model with Cloud Services Integration to Enhance Agricultural Applications

Chen,

Bai,

Xue

et al. 2023

Agronomy

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This project aims to improve the wheat growth and development simulation model (WheatSM) V4.0, a renowned wheat model, by addressing limitations in its structure and modules. The WheatSM V4.0 excelled numerically but lacked modularity, hindering maintenance, improvement, and secondary development. Therefore, the project undertook a software framework redesign, adopting a modular approach and implementing WheatSM V5.0 entirely in Python. Furthermore, the project conducted a sensitivity analysis of model parameters. Additionally, WheatSM V5.0 was seamlessly integrated into AgroStudio, an agricultural model system integration platform, enabling the provision of online cloud services. The Morris analysis indicated that photoperiod parameters significantly impacted the jointing and mature stages. Furthermore, biomass was highly sensitive to pmax (the maximum photosynthetic intensity at light saturation point), while yield was influenced by tr1 (the transfer rate of photosynthate to grain before heading). The simulated results demonstrated favorable performance in soil water storage, soil nitrate nitrogen content, winter wheat nitrogen accumulation, the development period, biomass, and yield. The NRMSE ranged from 1.2% to 15.1% for calibration and 1.0% to 18.7% for validation. The project successfully transformed WheatSM into a cloud-based service on AgroStudio, migrating from a PC-based application. Generally, this enhanced model exhibits potential for climate change assessment, wheat production optimization, and digital design.

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“…The Root Mean Square Error of homogenization NRMSE, and the consistency index D were used to quantify the validation accuracy. The specific calculation formula is as follows [46].…”

Section: Methodsmentioning

confidence: 99%

The Quantitative Inhibition Effects of Meteorological Drought on Sugarcane Growth Using the Decision Support System for Agrotechnology Transfer-CANEGRO Model in Lai-bin, China

Yang,

Wang,

Zhang

et al. 2024

Agriculture

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Sugarcane is the most important cash crop for producing sugar and the most promising high-yield bioenergy crop in China. Lai-bin is a major sugarcane growing and karst area in the Guangxi Province of China. However, frequent droughts over the years have caused huge losses on sugarcane production in this region. Therefore, the daily quantitative response mechanisms of sugarcane growth to multiple meteorological drought scenarios were discovered in Lai-bin using the DSSAT−CANEGRO model. The daily Standardized Precipitation Evapotranspiration Index (SPEI) was developed to detect the possible scenarios of meteorological drought events over the sugarcane growth periods. The results indicate that, in general, the inhibitory effect on sugarcane growth is enhanced by the increase in the intensity and duration of meteorological drought, which involved cane yield (CY), stem height (SH), leaf area index (LAI), and evapotranspiration (ET). Additionally, a light drought at the seedling stage and a light, moderate, and severe drought at the maturity stage give a promotion effect on sugarcane growth, but its overall CY increase rate is less than 5%. The stem elongation stage is the most sensitive period of sugarcane growth to all scenarios of meteorological drought, and the CY reduction rates reached 7.12%, 16.48%, 18.80%, and 29.05%, when the plants suffered from light, moderate, severe, and extreme meteorological droughts, respectively. Alternate drought–flood scenarios presented a facilitating or an inhibiting effect on sugarcane growth during different periods, which cannot be ignored. In conclusion, the quantitative function relationships between meteorological drought and sugarcane growth are revealed by this study.

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Remote sensing based estimation system for winter wheat yield in North China Plain

Cited by 7 publications

References 5 publications

Impact of Climate Change on the Yield and Water Footprint of Winter Wheat in the Haihe River Basin, China

Impact of Climate Change on the Yield and Water Footprint of Winter Wheat in the Haihe River Basin, China

WheatSM V5.0: A Python-Based Wheat Growth and Development Simulation Model with Cloud Services Integration to Enhance Agricultural Applications

The Quantitative Inhibition Effects of Meteorological Drought on Sugarcane Growth Using the Decision Support System for Agrotechnology Transfer-CANEGRO Model in Lai-bin, China

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