scholarly journals Corrigendum to ‘Coupling land surface and crop growth models to estimate the effects of changes in the growing season on energy balance and water use of rice paddies’ Agricultural and Forest Meteorology 150 (2010) 919–930

2021 ◽  
pp. 108585
Author(s):  
Atsushi Maruyama ◽  
Tsuneo Kuwagata
Keyword(s):  
Energy Balance ◽  
Water Use ◽  
Land Surface ◽  
Growth Models ◽  
Growing Season ◽  
Crop Growth ◽  
Rice Paddies ◽  
Forest Meteorology ◽  
Crop Growth Models

scholarly journals Coupling land surface and crop growth models for predicting evapotranspiration and carbon exchange in wheat-maize rotation croplands

2010 ◽  
Vol 7 (10) ◽  
pp. 3363-3375 ◽  
Author(s):  
H. Lei ◽  
D. Yang ◽  
E. Lokupitiya ◽  
Y. Shen
Keyword(s):  
Water Resources ◽  
Land Surface ◽  
Crop Production ◽  
Growth Models ◽  
Coupled Model ◽  
Crop Growth ◽  
Crop Phenology ◽  
Area Index ◽  
The North ◽  
Crop Growth Models

Abstract. The North China Plain is one of the key crop-producing regions in China. However, water resources in the area are limited. Accurate modeling of water consumption and crop production in response to the changing environment is important. To describe the two-way interactions among climate, irrigation, and crop growth better, the modified crop phenology and physiology scheme from the SiBcrop model was coupled with the second version of the Simple Biosphere model (SiB2) to simulate crop phenology, crop production, and evapotranspiration of winter wheat and summer maize, which are two of the main crops in the region. In the coupled model, the leaf area index (LAI) produced by the crop phenology and physiology scheme was used in estimating sub-hourly energy and carbon fluxes. Observations obtained from two typical eddy covariance sites located in this region were used to validate the model. The coupled model was able to accurately simulate carbon and energy fluxes, soil water content, biomass carbon, and crop yield, especially for latent heat flux and carbon flux. The LAI was also well simulated by the model. Therefore, the coupled model is capable of assessing the responses of water resources and crop production to the changes of future climate and irrigation schedules of this region.

scholarly journals Coupling land surface and crop growth models for predicting evapotranspiration and carbon exchange in wheat-maize rotation croplands

2010 ◽  
Vol 7 (4) ◽  
pp. 5157-5190
Author(s):  
H. Lei ◽  
D. Yang ◽  
E. Lokupitiya ◽  
Y. Shen
Keyword(s):  
Water Resources ◽  
Land Surface ◽  
Crop Production ◽  
Growth Models ◽  
Coupled Model ◽  
Crop Growth ◽  
Crop Phenology ◽  
Area Index ◽  
The North ◽  
Crop Growth Models

Abstract. The North China Plain is one of the most important crop production regions in China. However, water resources in the area are limited. Accurate modeling of water consumption and crop production in response to the changing environment is important. To better describe the two-way interactions among climate, irrigation, and crop growth, the crop phenology and physiology scheme of the SiBcrop model was coupled with the Simple Biosphere model version 2 (SiB2) for simulating crop phenology, as well as the crop production and evapotranspiration of winter wheat and summer maize, two of the main crops in the region. In the coupled model, the Leaf Area Index (LAI) produced by the crop phenology and physiology scheme was used in estimating the sub-hourly energy and carbon fluxes. Observations obtained from two typical eddy covariance sites located in this region were used to validate the model. The coupled model was able to simulate carbon and energy fluxes, soil water content, biomass carbon, and crop yield with high accuracy, especially for the latent heat flux and carbon flux. The LAI was also well-simulated by the model. Therefore, the coupled model is capable of assessing the responses of water resources and crop production to the changes of future climate and irrigation schedules.

scholarly journals An Agent-Based Crop Model Framework for Heterogeneous Soils

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 85
Author(s):  
Jorge Lopez-Jimenez ◽  
Nicanor Quijano ◽  
Alain Vande Wouwer
Keyword(s):  
Growth Models ◽  
Control Strategies ◽  
Low Cost ◽  
Soil Heterogeneity ◽  
Crop Growth ◽  
Negative Effects ◽  
Model Framework ◽  
Agent Based ◽  
Crop Growth Models ◽  
Definition Of

Climate change and the efficient use of freshwater for irrigation pose a challenge for sustainable agriculture. Traditionally, the prediction of agricultural production is carried out through crop-growth models and historical records of the climatic variables. However, one of the main flaws of these models is that they do not consider the variability of the soil throughout the cultivation area. In addition, with the availability of new information sources (i.e., aerial or satellite images) and low-cost meteorological stations, it is convenient that the models incorporate prediction capabilities to enhance the representation of production scenarios. In this work, an agent-based model (ABM) that considers the soil heterogeneity and water exchanges is proposed. Soil heterogeneity is associated to the combination of individual behaviours of uniform portions of land (agents), while water fluxes are related to the topography. Each agent is characterized by an individual dynamic model, which describes the local crop growth. Moreover, this model considers positive and negative effects of water level, i.e., drought and waterlogging, on the biomass production. The development of the global ABM is oriented to the future use of control strategies and optimal irrigation policies. The model is built bottom-up starting with the definition of agents, and the Python environment Mesa is chosen for the implementation. The validation is carried out using three topographic scenarios in Colombia. Results of potential production cases are discussed, and some practical recommendations on the implementation are presented.

Estimation of Evapotranspiration using Remote Sensing and Surface Energy Balance Algorithm for Land (SEBAL) in Canal Command

2021 ◽  
Vol 58 (03) ◽  
pp. 274-285
Author(s):  
H. V. Parmar ◽  
N. K. Gontia
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Surface Energy ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Crop Growth ◽  
Growth Stages ◽  
Landsat 8 ◽  
Surface Temperatures ◽  
Canal Command

Remote sensing based various land surface and bio-physical variables like Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), surface albedo, transmittance and surface emissivity are useful for the estimation of spatio-temporal variations in evapotranspiration (ET) using Surface Energy Balance Algorithm for Land (SEBAL) method. These variables were estimated under the present study for Ozat-II canal command in Junagadh district, Gujarat, India, using Landsat-7 and Landsat-8 images of summer season of years 2014 and 2015. The derived parameters were used in SEBAL to estimate the Actual Evapotranspiration (AET) of groundnut and sesame crops. The lower values NDVI observed during initial (March) and end (May) stages of crop growth indicated low vegetation cover during these periods. With full canopy coverage of the crops, higher value of NDVI (0.90) was observed during the mid-crop growth stage. The remote sensing-based LST was lower for agricultural areas and the area near banks of the canal and Ozat River, while higher surface temperatures were observed for rural settlements, road and areas with exposed dry soil. The maximum surface temperatures in the cropland were observed as 311.0 K during March 25, 2014 and 315.8 K during May 31, 2015. The AET of summer groundnut increased from 3.75 to 7.38 mm.day-1, and then decreased to 3.99 mm.day-1 towards the end stage of crop growth. The daily AET of summer sesame ranged from 1.06 to 7.72 mm.day-1 over different crop growth stages. The seasonal AET of groundnut and sesame worked out to 358.19 mm and 346.31 mm, respectively. The estimated AET would be helpful to schedule irrigation in the large canal command.

Assessment of Soybeans Crop Management Strategies Using Crop Growth Models for Central Brazil

2020 ◽  
pp. 525-543
Author(s):  
Rafael Battisti ◽  
Derblai Casaroli ◽  
Jéssica Sousa Paixão ◽  
José Alves Júnior ◽  
Adão Wagner Pêgo Evangelista ◽  
...  
Keyword(s):  
Growth Models ◽  
Management Strategies ◽  
Crop Management ◽  
Crop Growth ◽  
Central Brazil ◽  
Crop Growth Models

scholarly journals Crop growth models without hormones.

1983 ◽  
Vol 31 (4) ◽  
pp. 313-323 ◽  
Author(s):  
C.T. de Wit ◽  
F.W.T.P. de Vries
Keyword(s):  
Dynamic Models ◽  
Dynamic Equilibrium ◽  
Growth Models ◽  
Co2 Assimilation ◽  
Crop Growth ◽  
State Variables ◽  
System A ◽  
Similar Information ◽  
Hormonal System ◽  
Crop Growth Models

For the simulation of organ formation and assimilate partitioning, information is required on the current level of activities like CO2 assimilation and the growth of various organs, as well as state variables such as leaf and root wt., N content and carbohydrate reserves and exogenous variables like radiation and temp. This information may be retained in auxiliary state variables by considering the dynamic equilibrium between growth of roots and shoots. Auxiliary state variables are not tangible quantities but mathematical artefacts of the simulation program; it is speculated that in real plants similar information may be retained and transferred by the hormonal system. A hormonal system is a communication system and such systems may be analysed either in terms of means (of the hardware used) or in terms of purpose (of the messages transferred). In dynamic models of crop growth, interest should be focused on the latter. Wheat, maize and ryegrass are used as examples. (Abstract retrieved from CAB Abstracts by CABI’s permission)

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