Simulation of Crop Yields Grown under Agro-Photovoltaic Panels: A Case Study in Chonnam Province, South Korea

Agro-photovoltaic systems are of interest to the agricultural industry because they can produce both electricity and crops in the same farm field. In this study, we aimed to simulate staple crop yields under agro-photovoltaic panels (AVP) based on the calibration of crop models in the decision support system for agricultural technology (DSSAT) 4.6 package. We reproduced yield data of paddy rice, barley, and soybean grown in AVP experimental fields in Bosung and Naju, Chonnam Province, South Korea, using CERES-Rice, CERES-Barley, and CROPGRO-Soybean models. A geospatial crop simulation modeling (GCSM) system, developed using the crop models, was then applied to simulate the regional variations in crop yield according to solar radiation reduction scenarios. Simulated crop yields agreed with the corresponding measured crop yields with root mean squared errors of 0.29-ton ha−1 for paddy rice, 0.46-ton ha−1 for barley, and 0.31-ton ha−1 for soybean, showing no significant differences according to paired sample t-tests. We also demonstrated that the GCSM system could effectively simulate spatiotemporal variations in crop yields due to the solar radiation reduction regimes. An additional advancement in the GCSM design could help prepare a sustainable adaption strategy and understand future food supply insecurity.

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A multi-model analysis of teleconnected crop yield variability in a range of cropping systems

10.5194/esd-2019-8 ◽

2019 ◽

Cited By ~ 1

Author(s):

Matias Heino ◽

Joseph H. A. Guillaume ◽

Christoph Müller ◽

Toshichika Iizumi ◽

Matti Kummu

Keyword(s):

Crop Yield ◽

Crop Production ◽

Food System ◽

Crop Yields ◽

Southern Oscillation ◽

Yield Variability ◽

Management Scenarios ◽

Yield Data ◽

Climate Oscillations ◽

Crop Models

Abstract. Climate oscillations are periodically fluctuating oceanic and atmospheric phenomena, which are related to variations in weather patterns and crop yields worldwide. In terms of crop production, the most widespread impacts have been observed for the El Niño Southern Oscillation (ENSO), which has been found to impact crop yields in all continents that produce crops, while two other climate oscillations – the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) – have been shown to impact crop production especially in Australia and Europe, respectively. In this study, we analyse the impacts of ENSO, IOD and NAO on the growing conditions of maize, rice, soybean and wheat at the global scale, by utilizing crop yield data from an ensemble of global gridded crop models simulated for a range of crop management scenarios. Our results show that simulated crop yield variability is correlated to climate oscillations to a wide extent (up to almost half of all maize and wheat harvested areas for ENSO) and in several important crop producing areas, e.g. in North America (ENSO, wheat), Australia (IOD & ENSO, wheat) and northern South America (ENSO, soybean). Further, our analyses show that higher sensitivity to these oscillations can be observed for rainfed, and fully fertilized scenarios, while the sensitivity tends to be lower if crops are fully irrigated. Since, the development of ENSO, IOD and NAO can be reliably forecasted in advance, a better understanding about the relationship between crop production and these climate oscillations can improve the resilience of the global food system to climate related shocks.

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Simulation of Staple Crop Yields for Determination of Regional Impacts of Climate Change: A Case Study in Chonnam Province, Republic of Korea

Agronomy ◽

10.3390/agronomy11122544 ◽

2021 ◽

Vol 11 (12) ◽

pp. 2544

Author(s):

Jinsil Choi ◽

Jonghan Ko ◽

Kyu-Nam An ◽

Saeed A. Qaisrani ◽

Jong-Oh Ban ◽

...

Keyword(s):

Climate Change ◽

Crop Yields ◽

Food Resource ◽

Paddy Rice ◽

Republic Of Korea ◽

Crop Models ◽

Regional Impacts ◽

Staple Crop ◽

The Impact ◽

Impacts Of Climate Change

This study sought to simulate regional variation in staple crop yields in Chonnam Province, Republic of Korea (ROK), in future environments under climate change based on the calibration of crop models in the Decision Support System for Agricultural Technology Transfer 4.6 package. We reproduced multiple-year yield data for paddy rice (2013–2018), barley (2000–2018), and soybean (2004–2018) grown in experimental fields at Naju, Chonnam Province, using the CERES-Rice, CERES-Barley, and CROPGRO-Soybean models. A geospatial crop simulation modeling (GCSM) system developed using the crop models was then applied to simulate the regional impacts of climate change on the staple crops according to the Representative Concentration Pathway 4.5 and 8.5 scenarios. Simulated crop yields agreed with the corresponding measured crop yields, with root means square deviations of 0.31 ton ha−1 for paddy rice, 0.29 ton ha−1 for barley, and 0.27 ton ha−1 for soybean. We also demonstrated that the GCSM system could effectively simulate spatiotemporal variations in the impact of climate change on staple crop yield. The CERES and CROPGRO models seem to reproduce the effects of climate change on region-wide staple crop production in a monsoonal climate system. Added advancements of the GCSM system could facilitate interpretations of future food resource insecurity and establish a sustainable adaption strategy.

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Climate change impacts on crop water productivity in Africa using a multi-model inter-comparison

10.5194/egusphere-egu2020-14125 ◽

2020 ◽

Author(s):

Imeshi Weerasinghe ◽

Celray James Chawanda ◽

Ann van Griensven

Keyword(s):

Climate Change ◽

Crop Yield ◽

Crop Yields ◽

Water Productivity ◽

Baseline Scenario ◽

Crop Water ◽

Yield Data ◽

Water Vapour Flux ◽

Crop Models ◽

Crop Water Productivity

<p>Evapotranspiration (ET) or the water vapour flux is an important component in the water cycle and is widely studied due to its implications in disciplines ranging from hydrology to agricultural and climate sciences. In the recent past, growing attention has been given to estimating ET fluxes at regional and global scales. However, estimation of ET at large scales has been a difficult task due to direct measurement of ET being possible only at point locations, for example using flux towers. For the African continent, only a limited number of flux tower data are openly available for use, which makes verification of regional and global ET products very difficult. Recent advances in satellite based products provide promising data to fill these observational gaps.</p><p>In this study we propose to investigate the Climate Change (CC) impact on crop water productivity across Africa using ET and crop yield predictions of different crop models for future climate scenarios. Different model outputs are evaluated including models from both the ISI-MIP 2a and 2b protocols. Considering the problem of direct observations of ET being difficult to obtain, especially over Africa, we use ET estimates from several remotely sensed derived products as a references to evaluate the crop models (maize) in terms of magnitude, spatial patterns and variations between models. The crop model results for crop yield are compared to FAO reported crop yields at country scale. The results show a very strong disagreement between the different crop models of the baseline scenario and when compared with ET and crop yield data.&#160; Also, a very large uncertainty is obtained for the climate change predictions. It is hence recommended to improve the crop models for application in Africa.</p>

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A multi-model analysis of teleconnected crop yield variability in a range of cropping systems

Earth System Dynamics ◽

10.5194/esd-11-113-2020 ◽

2020 ◽

Vol 11 (1) ◽

pp. 113-128 ◽

Cited By ~ 1

Author(s):

Matias Heino ◽

Joseph H. A. Guillaume ◽

Christoph Müller ◽

Toshichika Iizumi ◽

Matti Kummu

Keyword(s):

Crop Yield ◽

Crop Production ◽

Food System ◽

Crop Yields ◽

Southern Oscillation ◽

Yield Variability ◽

Management Scenarios ◽

Yield Data ◽

Climate Oscillations ◽

Crop Models

Abstract. Climate oscillations are periodically fluctuating oceanic and atmospheric phenomena, which are related to variations in weather patterns and crop yields worldwide. In terms of crop production, the most widespread impacts have been observed for the El Niño–Southern Oscillation (ENSO), which has been found to impact crop yields on all continents that produce crops, while two other climate oscillations – the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) – have been shown to especially impact crop production in Australia and Europe, respectively. In this study, we analyse the impacts of ENSO, IOD, and NAO on the growing conditions of maize, rice, soybean, and wheat at the global scale by utilising crop yield data from an ensemble of global gridded crop models simulated for a range of crop management scenarios. Our results show that, while accounting for their potential co-variation, climate oscillations are correlated with simulated crop yield variability to a wide extent (half of all maize and wheat harvested areas for ENSO) and in several important crop-producing areas, e.g. in North America (ENSO, wheat), Australia (IOD and ENSO, wheat), and northern South America (ENSO, soybean). Further, our analyses show that higher sensitivity to these oscillations can be observed for rainfed and fully fertilised scenarios, while the sensitivity tends to be lower if crops were to be fully irrigated. Since the development of ENSO, IOD, and NAO can potentially be forecasted well in advance, a better understanding about the relationship between crop production and these climate oscillations can improve the resilience of the global food system to climate-related shocks.

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Sensitivity of vegetation indices to spatial degradation of RapidEye imagery for paddy rice detection: a case study of South Korea

GIScience & Remote Sensing ◽

10.1080/15481603.2014.1001666 ◽

2015 ◽

Vol 52 (1) ◽

pp. 1-17 ◽

Cited By ~ 18

Author(s):

Hyun-Ok Kim ◽

Jong-Min Yeom

Keyword(s):

South Korea ◽

Vegetation Indices ◽

Paddy Rice

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Solar Radiation Reduction Monitoring of Macao World Heritage District Photovoltaic System Using GIS and UHF RFID Obstacle Detection Approach

10.1109/icsmartgrid52357.2021.9551216 ◽

2021 ◽

Author(s):

Rong Wang ◽

Oi Tai Tai ◽

Kam Weng Tam

Keyword(s):

Solar Radiation ◽

World Heritage ◽

Obstacle Detection ◽

Photovoltaic System ◽

Uhf Rfid ◽

Radiation Reduction ◽

Detection Approach

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Geostatistical analysis of crop yield maps in a long term no tillage system

Bragantia ◽

10.1590/s0006-87052010000500003 ◽

2010 ◽

Vol 69 (suppl) ◽

pp. 9-18 ◽

Cited By ~ 3

Author(s):

Osvaldo Guedes Filho ◽

Sidney Rosa Vieira ◽

Marcio Koiti Chiba ◽

Célia Regina Grego

Keyword(s):

Crop Yield ◽

Crop Yields ◽

Spherical Model ◽

Exponential Model ◽

Spatial And Temporal Variability ◽

No Tillage ◽

Yield Data ◽

The North ◽

Tillage System

It is known, for a long time, that crop yields are not uniform at the field. In some places, it is possible to distinguish sites with both low and high yields even within the same area. This work aimed to evaluate the spatial and temporal variability of some crop yields and to identify potential zones for site specific management in an area under no-tillage system for 23 years. Data were analyzed from a 3.42 ha long term experimental area at the Centro Experimental Central of the Instituto Agronômico, located in Campinas, Sao Paulo State, Brazil. The crop yield data evaluated included the following crops: soybean, maize, lablab and triticale, and all of them were cultivated since 1985 and sampled at a regular grid of 302 points. Data were normalized and analyzed using descriptive statistics and geostatistical tools in order to demonstrate and describe the structure of the spatial variability. All crop yields showed high variability. All of them also showed spatial dependence and were fitted to the spherical model, except for the yield of the maize in 1999 productivity which was fitted to the exponential model. The north part of the area presented repeated high values of productivity in some years. There was a positive cross correlation amongst the productivity values, especially for the maize crops.

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Growth and Physiological Characteristics of Lettuce (Lactuca sativa L.) and Rocket (Eruca sativa Mill.) Plants Cultivated under Photovoltaic Panels

Notulae Botanicae Horti Agrobotanici Cluj-Napoca ◽

10.15835/nbha46110846 ◽

2018 ◽

Vol 46 (1) ◽

pp. 206-212 ◽

Cited By ~ 9

Author(s):

Angeliki KAVGA ◽

Georgios TRYPANAGNOSTOPOULOS ◽

George ZERVOUDAKIS ◽

Yiannis TRIPANAGNOSTOPOULOS

Keyword(s):

Solar Radiation ◽

Photosynthetic Rate ◽

Lactuca Sativa ◽

The Other ◽

Physiological Characteristics ◽

Eruca Sativa ◽

Partial Shading ◽

Photovoltaic Panels ◽

Lactuca Sativa L ◽

Other Hand

Energy demand of greenhouses is an important factor for their economics and photovoltaics can be considered an alternative solution to cover their electrical and heating needs. On the other hand, plants cultivated under different solar radiation intensities usually appear different physiological adaptations. The objective of this research was to investigate the effect of photovoltaic panels’ induced partial shading on growth and physiological characteristics of lettuce (Lactuca sativa L.) and rocket (Eruca sativa Mill.) plants. Our results indicate that lettuce productivity and the corresponding photosynthetic rate were not affected under the photovoltaic cultivation in comparison with the reference one. On the other hand, the rocket cultivation was less productive and showed lower photosynthetic rate under photovoltaic panels than in the reference greenhouse. The different physiological response between lettuce and rocket seems to be associated with the effect of environmental factors such as solar radiation intensity, temperature and humidity apart from the possible inherent characteristics of each plant species.

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