Application of CERES-sorghum crop simulation model DSSAT v4.7 for determining crop water stress in crop phenological stages

Gohain, G. B.; Singh, K. K.; Singh, R. S.; Dakhore, K. K.; Ghosh, Kripan

doi:10.1007/s40808-021-01194-5

Cited by 6 publications

(4 citation statements)

References 12 publications

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“…Observed daily gridded precipitation, 23 temperature data 24 (maximum and minimum) available on the Indian Meteorological Department website was retrieved using WEATHER MODULE in the required format, i.e., GRD GitHub users can access the module WEATHER MODULE at Source. 14 The simulated daily baseline and future climatic data were obtained from the (CMIP5). The future climate scenarios were generated by using twenty-nine Global Climate Models (GCMs).…”

Section: Climate Datamentioning

confidence: 99%

“…Studies on the stress on crop water requirement at the GRID level at a spatial resolution of 25km using DSSAT for sorghum crops have been conducted to understand the stress on crop water requirements during drought. 14 The use of the random forest algorithm is applied in this study as a machine learning method to estimate the crop yield of wheat under present and future scenarios. [15][16] developed the RCYES tools in python to estimate the crop yield at the spatial level of 0.25° X 0.25° (25km).…”

Section: Introductionmentioning

confidence: 99%

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Assessment of Future Climate and Kharif Paddy Yields using Ceres-Rice in the State of Andhra Pradesh

Kumar,

Reddy,

Gohain

et al. 2023

Curr. World Environ

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Climate change considerably impacts water needs for agricultural production, particularly in paddy crops (Oryza Sativa). The paddy crop response is uncertain and also heterogeneous due to climate change. Climate variables rainfall and temperature directly impact crop productivity. A precise understanding of crop yields is required for agricultural production management to plan sustainable food demand in the future at the state level. The climate change scenario's impact on rice yield at 0.25° × 0.25° spatial resolution was assessed in Andhra Pradesh and presented in this paper. The use of representative concentration Pathway 8.5 scenario in projections made by the Global Climate Model (GCM) were downscaled for mid-century (2048-2078) using statistical tools. In this study, the Cropping System Model (CSM) and Crop Estimation through Resource and Environment Synthesis (CERES) modules for rice, as part of the Decision Support System for Agro-technology Transfer (DSSAT) package, were utilized. The use of the Regional Crop Yield Estimation System (RCYES) for the Cropping System Model (CSM) within the Decision Support System for Agro-technology Transfer (DSSAT) was facilitated through Python in this study. It is observed that rainfall will decrease during winter and pre-monsoon seasons related to the baseline period (1988–2018) for RCP 8.5. From July to October, there was a significant increase in rainfall. The most considerable change in the rain was 50.7 mm in September. A notable variation between the maximum and minimum temperatures of 2.3 and 2.5 degrees Celsius in June and April respectively. Rainfall is expected to increase in Anantapur, Kurnool and Nellore districts during the mid-century 2040's. The correlation between the baseline and DES mean yield was 0.87, with a maximum yield of 0.86 and a minimum yield of 0.82. Decrease paddy yields by up to 10.7% in West Godavari, Krishna, Guntur, Nellore and Prakasam districts. At the same time, an increase in paddy yields up to 9.8% is anticipated in Srikakulam, Visakhapatnam, Vizianagaram, East Godavari, Anantapur, Chittoor, Kadapa, and Kurnool. In contrast, a maximum decrease of 189.9 mm of rainfall is expected in the Vizianagaram district. These results could assist in devising adaptation measures to reduce the negative effect of climate change on rice crops in Andhra Pradesh.

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Section: Climate Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of Future Climate and Kharif Paddy Yields using Ceres-Rice in the State of Andhra Pradesh

Kumar,

Reddy,

Gohain

et al. 2023

Curr. World Environ

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“…They found the DSSAT-CERES-Sorghum model efficient in determining the water stress effects on growth stages of rainfed sorghum in a tropical climate region in India. In that study, the postponement of sorghum planting to mid-July (6th to 15th) was determined effective in minimizing the adverse impacts of drought conditions on sorghum yield [27].…”

Section: Introductionmentioning

confidence: 99%

Determination of the Most Efficient Forage Sorghum Irrigation Scheduling Strategies in the U.S. Central High Plains Using the AquaCrop Model and Field Experiments

Fazel,

Ansari,

Aguilar

2023

Agronomy

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The current status of water resources in the U.S. Central High Plains necessitates adopting water conservation practices to move toward a sustainable agricultural economy. Identifying proper irrigation scheduling techniques is a conservative practice to maintain the sustainability of the agricultural systems. However, conducting field experiments is time and money consuming. Thus, the utilization of crop models, such as AquaCrop, could be a convenient alternative to field experiments. The FAO AquaCrop model was calibrated and validated for simulating forage sorghum yield response to various deficit irrigation conditions in a semi-arid region. Afterwards, the model was used to investigate the efficiency of the pre-season and in-season irrigation scheduling scenarios. In this study, the soil water status at the planting time was considered as the indicator of the pre-season irrigation level. Therefore, the pre-season irrigation scenarios were arranged as the replenishment of soil water deficiency at the time of planting at up to 30, 50, and 100% of the soil’s total available water for the first 60 cm of soil depth and the same replenishment levels for the entire crop root zone (150 cm soil depth). Then, AquaCrop long-term (37 years) simulations of forage sorghum biomass and irrigation water use efficiency reactions to three levels of maximum allowable depletion (MAD) (40, 55, and 70%) were compared to three fixed irrigation interval (4, 6, and 10 days) scenarios by considering six pre-season irrigation conditions (36 scenarios). The scenarios analysis found the 10-day irrigation interval and the MAD levels of 55% and 70% to be the most efficient irrigation scheduling strategies if combined with pre-season irrigation that brought the crop root zone (0–150 cm soil depth) to field capacity. Moreover, the 40% MAD application was the least efficient strategy. This study’s outputs can be a baseline for establishing forage sorghum irrigation scheduling in the U.S. Central High Plains. However, exploring the interactions of irrigation scheduling strategies with other irrigation and agronomic practices, such as salinity management and fertilizer application, is highly recommended.

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“…Os modelos de simulação de culturas têm sido amplamente utilizados para avaliar a umidade do solo (Ebrahimi-Mollabashi et al, 2019;Masasi et al, 2019) e a interação soloplanta-atmosfera (Gohain et al, 2022;Zizinga et al, 2022). No entanto, é importante comparar diferentes modelos para entender suas semelhanças e diferenças, a fim de identificar possíveis limitações (Battisti et al, 2018).…”

Section: Introductionunclassified

Modelagem de base processual aplicada ao crescimento e produtividade do eucalipto

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O eucalipto é a espécie mais abundante nas plantações florestais do Brasil. A alta produtividade do eucalipto é resultado do uso de materiais genéticos adaptados e melhores práticas de manejo. No entanto, devido à diversidade de condições de sítio em que o eucalipto é cultivado no Brasil, existe uma diferença entre a produtividade alcançada no campo e seu potencial máximo. O objetivo deste estudo foi calibrar e validar os modelos de simulação 3- PG e APSIM Next Generation Eucalyptus para entender as quebras de rendimento bem como avaliar a sensibilidade da produtividade do eucalipto em Minas Gerais, Brasil. Os modelos 3- PG e APSIM foram calibrados e avaliados, utilizando-se dados experimentais de produtividade do eucalipto em diferentes regiões produtoras de Minas Gerais. Ambos os modelos apresentaram bom desempenho na simulação de diferentes condições climáticas, solos e genótipos. O APSIM mostrou-se mais eficaz na simulação de uma cultura genérica e em condições contrastantes. Além disso, a deficiência hídrica foi identificada como o principal fator de perda de produtividade, destacando a necessidade de clones mais tolerantes à seca e ajustes no manejo florestal. Em relação à sensibilidade dos modelos, para simular a produtividade em diferentes regiões, tanto o 3-PG quanto o APSIM responderam positivamente ao aumento da disponibilidade de água no solo. O APSIM demonstrou maior sensibilidade e houve variação na produtividade de acordo com a disponibilidade hídrica do solo. Estes modelos podem ser aprimorados, como por exemplo usando classes de solo no APSIM, ou mesmo uma distribuição vertical do sistema radicular em ambos os modelos, para melhorar a dinâmica de água e absorção pelas plantas. Palavras-chave: Apsim, 3-PG, Simulação, Eucalipto, Modelagem, Agrometeorologia, Quebra de produção, Sensibilidade.

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Application of CERES-sorghum crop simulation model DSSAT v4.7 for determining crop water stress in crop phenological stages

Cited by 6 publications

References 12 publications

Assessment of Future Climate and Kharif Paddy Yields using Ceres-Rice in the State of Andhra Pradesh

Assessment of Future Climate and Kharif Paddy Yields using Ceres-Rice in the State of Andhra Pradesh

Determination of the Most Efficient Forage Sorghum Irrigation Scheduling Strategies in the U.S. Central High Plains Using the AquaCrop Model and Field Experiments

Modelagem de base processual aplicada ao crescimento e produtividade do eucalipto

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