Modeling risk analysis for rice production due to agro-climate change in Taiwan

Wu, Szu-Hsien; Chiueh, Ya-Wen; Lien, Ho-Cheng; Hsu, Chih-Tsung

doi:10.1007/s10333-014-0455-x

Cited by 9 publications

(3 citation statements)

References 17 publications

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“…Wu et al (2015) found out rice production to be sensitive to temperature, precipitation and sunlight in Taiwan. The impacts of temperature and solar radiation on rice yield are poorly understood despite many decades of agronomic research on rice crop (Welch et al 2010).…”

Section: Resultsmentioning

confidence: 99%

Effect of weather on grain yield of direct seeded upland rice varieties in Jharkhand, India

Kumari

Kumar

et al. 2017

IJARe

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The study was conducted at Birsa Agricultural University, Ranchi during the years 2009-2013 for understanding the effect of weather variables on the yield of three direct seeded upland rainfed rice varieties viz., Vandana, BVD-109 and BVD-111 in Jharkhand. Correlation and regression methods were used to estimate the impacts of weather on rice yield. Study indicated that temperature, rainfall and sunshine hours have significant effect on the rice yield. Average minimum temperature during sowing to vegetative stage in cv. Vandana and during flowering in BVD-109 and BVD-111 showed significant negative relationship with yield. Rainfall during vegetative and grain filling stage are significantly and positively related with grain yield in all the three rice varieties. The effect of sunshine hours on grain yield of rice was comparatively higher at milk stage than the other phenological stages in all three varieties. However, the effect of sunshine hours on yield is significant during the milk stage in Vandana and BVD-111 only. Multiple regressions using critical weather parameters in critical stages of the three varieties could explain the variability in yield of Vandana, BVD-109 and BVD-111 by 92, 74 and 91 percent, respectively.

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Section: Resultsmentioning

confidence: 99%

Effect of weather on grain yield of direct seeded upland rice varieties in Jharkhand, India

Kumari

Kumar

et al. 2017

IJARe

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“…In addition to the irrigation water supply reliability carried out via the AFOSM method, to effectively evaluate the reliability Pr[W ID > w IS ] of a specific water demand under the uncertainty factors provided, this study aims to derive an equation calculating the corresponding exceedance probability of the irrigation water supply to the uncertainty factors known. In general, the relationship between the multiple hydrological variables is established using regression analysis [31]; specifically, logistic regression analysis helps derive the relationship among numerous independent variables and a dependent variate which takes only two dichotomous values [11,[33][34][35], such as:…”

Section: Establishment Of the Exceedance Probability Estimation Equationmentioning

confidence: 99%

Modeling Probabilistic-Based Reliability Analysis for Irrigation Water Supply Due to Uncertainties in Hydrological and Irrigation Factors

Mai

Lin

et al. 2022

Sustainability

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This study aims to model a probabilistic-based reliability analysis, named the RA_IWS_Canal model, for calculating the probability of the irrigation water supply exceeding the water demand (i.e., reliability) within a multi-canal irrigation zone due to variations in hydrological and irrigation uncertainty factors. The proposed RA_IWS_Canal model is developed by coupling uncertainty and risk analysis with a logistic regression equation. The Zhudong irrigation zone, located within the Touqian River watershed in northern Taiwan, was selected as the study area, with the inflow from Shanping Weir, water supplies at 15 irrigation canals, and water intakes of two reservoirs (Baoshan and Baoshan II) and a water treatment plant (Yuandon); 1000 simulations of 10-day irrigation water allocations and resulting exceedance probabilities of the water supplies at the 15 canals were achieved using the multivariate Monte Carlo simulation and the uncertainty with the water allocation model (RIBASIM), and employed in the development of the proposed RA_IWS_Canal model. The model development and application results indicate that the uncertainty factors and the inflow from Shanping Weir markedly and positively influence the exceedance probability of the canal-based irrigation water supply to boost the corresponding reliability (about 0.8). The water intake of the Baoshan Reservoir has a lower relationship (by 0.19) than the Yuandon water treatment plant with the reliabilities of the irrigation water supplies at its downstream canals. As a result, the proposed RA_IWS_Canal model can evaluate the effect of not only the canal-based uncertainty factors, but also the regional features on the irrigation water supply reliability. In addition, using the proposed RA_IWS_Canal model, the planned irrigation water demands at various canals within a multi-canal irrigation zone could be accordingly formulated based on acceptable reliability.

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“…Yao & Chen (2009) used crop growth model software to assess the impact of climate change on rice growth and yield, and the results showed that the average yield of rice cultivated in Taiwan would decrease by 4.7% in 2050. Through a risk analysis model, Wu et al (2015) reported that rice yields in Taiwan are particularly sensitive to temperature, precipitation, and sunlight. Wang et al (2023) utilized a multi-criteria assessment and sensitivity analysis approach, considering factors such as soil, rainfall, temperature, irrigation, and soil erosion, and reported that agricultural lands across Taiwan generally have moderate or high suitability for rice cultivation, especially in southwestern Taiwan.…”

Section: Introductionmentioning

confidence: 99%

Temporal variation of the relationships between rice yield and climate variables since 1925

Chen,

Wu,

Teng

2023

PeerJ

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Background Long-term time-series datasets of crop yield and climate variables are necessary to study the temporal variation of climate effects on crops. The aim of this study was to broadly assess assessment of the effects of climate on rice, and the associated temporal variations of the effects during the long-term period. Methods We conducted field experiments in Taiwan from 1925 to 2019 to collect and analyze rice yield data and evaluate the impacts of changes in average temperature, diurnal temperature range (DTR), rainfall, and sunshine duration on rice yield during cool and warm cropping seasons. We then estimated the relationships between annual grain yield and the climate variables using the time series of their first difference values. We also computed the total relative and annual actual yield changes using regression coefficients for each climate variable for the intervals 1925–1944, 1945–1983, and 1996–2019 to reveal the impacts of climate change on yields and the associated temporal variations during the overall experimental period. Results The annual daily average temperature calculated from the trend of the regression lines increased by 0.94–1.03 °C during the 95-year period. The maximum temperature remained steady while the minimum temperature increased, leading to decreased DTR. The total annual rainfall decreased by 237–352 mm and the annual total sunshine duration decreased by 93.9–238.9 h during the experimental period. We observed that during the cool cropping season, yield response to temperature change decreased, while that to DTR and rainfall changes increased. During the warm cropping season, all the yield responses to temperature, DTR, and rainfall changes were negative throughout the experimental period. In recent years (1996–2019) the estimated annual actual rice yield changes during the cool cropping season were negatively affected by climate variables (except for sunshine duration), and slightly positively affected (except for temperature) during the warm cropping season. Compared to the effects of temperature and DTR, those of rainfall and sunshine duration on rice yield changes were weak. This study contributes to provide impacts of climate change on rice yield and associated long-term temporal variations over nearly a century.

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Modeling risk analysis for rice production due to agro-climate change in Taiwan

Cited by 9 publications

References 17 publications

Effect of weather on grain yield of direct seeded upland rice varieties in Jharkhand, India

Effect of weather on grain yield of direct seeded upland rice varieties in Jharkhand, India

Modeling Probabilistic-Based Reliability Analysis for Irrigation Water Supply Due to Uncertainties in Hydrological and Irrigation Factors

Temporal variation of the relationships between rice yield and climate variables since 1925

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