Estimating evapotranspiration and yield of wheat and maize croplands through a remote sensing-based model

Wang, Xingwang; Lei, Huimin; Li, Jiadi; Huo, Zailin; Zhang, Yongqiang; Qu, Yanping

doi:10.1016/j.agwat.2023.108294

Cited by 17 publications

(4 citation statements)

References 79 publications

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“…(2019). Such data assimilation applications have included the use of remote sensing data along with crop simulation models to estimate regional evapotranspiration, water‐use efficiency, and primary production of wheat and maize in China (Wang, Lei, Li, Huo, et al., 2023; Wang, Lei, Li, Qu, et al., 2023) and rice in India (Pazhanivelan et al., 2022). Data assimilation methods have been used to update LAI and the Normalized Differential Vegetation Index (NDVI) from satellite data to improve simulation of wheat yields under irrigation (Jin et al., 2022).…”

Section: Crop Models As Tools In Climate Change Assessmentmentioning

confidence: 99%

The role of crop simulation modeling in assessing potential climate change impacts

Timlin,

Paff,

Han

2024

Agrosystems Geosci & Env

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Agriculture is weather dependent, and changes in climate can have a drastic impact on our ability to feed, fuel, and clothe the world's population. Climate change is causing more frequent and unprecedented extreme weather events that are already negatively affecting agriculture. We need to assess the effects of extreme temperatures and rainfall on agriculture. Patterns of short‐term extreme weather events, such as elevated temperatures, flooding, and strong winds, are not predictable enough to design field experiments around. Process‐based crop and soil simulation models allow us to explore new management options and thus provide whole‐system‐based knowledge and management guides for different locations over variable climate conditions. By using crop simulation models, researchers can test different adaptation strategies and assess their effectiveness in reducing the impacts of climate change on agricultural production. In this paper, we discuss the development of crop models and how they have been used to assess the effects of a changing climate on agricultural productivity and propose methods for agriculture to adapt to those changes. We describe potential applications of crop models to assess regional issues such as irrigation demand, greenhouse gas emissions, and policy decisions. Better understanding of how weather and climate forecasts at various scales are provided and the reliability of these forecasts is important for using crop models as a planning tool. Different approaches for simulating long‐term climate change impacts on crop yield and seasonal yield forecasting are discussed. The use of ensemble models to better assess climate change impacts is also discussed.

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Section: Crop Models As Tools In Climate Change Assessmentmentioning

confidence: 99%

The role of crop simulation modeling in assessing potential climate change impacts

Timlin,

Paff,

Han

2024

Agrosystems Geosci & Env

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“…C3 and C4 crops in the water-carbon coupling process have different physiological characteristics [57]. To further deepen the study of ETn from cropland, we modeled C3 and C4 crops individually and also validated them on a daily scale.…”

Section: Simulation Of C3 and C4 Crops By The Rf Modelmentioning

confidence: 99%

Integrating Meteorological and Remote Sensing Data to Simulate Cropland Nocturnal Evapotranspiration Using Machine Learning

Huang,

Zhang,

Zhang

et al. 2024

Sustainability

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Evapotranspiration (ET) represents a significant component of the global water flux cycle, yet nocturnal evapotranspiration (ETn) is often neglected, leading to underestimation of global evapotranspiration. As for cropland, accurate modeling of ETn is essential for rational water management and is important for sustainable agriculture development. We used random forest (RF) to simulate ETn at 16 globally distributed cropland eddy covariance flux sites along with remote sensing and meteorological factors. The recursive feature elimination method was used to remove unimportant variables. We also simulated the ETn of C3 and C4 crops separately. The trained RF resulted in a determination coefficient (R2) (root mean square error (RMSE)) of 0.82 (7.30 W m−2) on the testing dataset. C3 and C4 crops on the testing dataset resulted in an R2 (RMSE) of 0.86 (5.59 W m−2) and 0.55 (4.86 W m−2) for the two types of crops. We also showed that net radiation is the dominant factor in regulating ETn, followed by 2 m horizontal wind speed and vapor pressure deficit (VPD), and these three meteorological factors showed a significant positive correlation with ETn. This research demonstrates that RF can simulate ETn from crops economically and accurately, providing a methodological basis for improving global ETn simulations.

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“…However, most existing remote sensing ET c models were based on satellite data, and there is a need for more in-depth research on models based on UAV data [13,14]. Remote sensing ET c models can be classified into mechanistic models, empirical regression models, and spatial feature method models.…”

Section: Introductionmentioning

confidence: 99%

Multispectral Inversion of Citrus Multi-Slope Evapotranspiration by UAV Based on Modified RSEB Model

Zhu,

Zhang,

Duan

et al. 2024

Water

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Evaptotranspiration (ETc) is a crucial link in the farmland water cycle process. To accurately obtain the citrus ETc in different slope positions, the METRIC, RSEB, and FAO Penman–Monteith (P-M) models were constructed based on unmanned aerial vehicle (UAV) multispectral images to invert the ETc values. The ETc of citrus calculated by the P-M model was used as a reference standard, and the accuracy of the ETc inversion was evaluated by the METRIC model and the RSEB model. The results showed that the R2, RMSE, and SE of the METRIC model and the RSEB model were 0.396 and 0.486, 4.940 and 3.010, and 4.570 and 2.090, respectively, indicating a higher accuracy of the RSEB model for inverting the ETc values. Furthermore, the accuracy of the RSEB model could be improved by introducing the optimal correction coefficient (after correction: RMSE = 1.470, SE = 0.003). Based on the modified RSEB model, the ETc values of the citrus in different slope positions were obtained. We also found that the middle slope ETc > the top slope ETc > the bottom slope ETc, indicating that the slope position indeed affected the citrus ETc. This research provides a favorable framework for the ETc inversion, and the results are of theoretical and practical importance to realize crop water conservation.

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Estimating evapotranspiration and yield of wheat and maize croplands through a remote sensing-based model

Cited by 17 publications

References 79 publications

The role of crop simulation modeling in assessing potential climate change impacts

The role of crop simulation modeling in assessing potential climate change impacts

Integrating Meteorological and Remote Sensing Data to Simulate Cropland Nocturnal Evapotranspiration Using Machine Learning

Multispectral Inversion of Citrus Multi-Slope Evapotranspiration by UAV Based on Modified RSEB Model

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