pdf impact of temperature and precipitation variability on crop model predictions

Pdf Impact Of Temperature And Precipitation Variability On Crop Model Predictions

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Published: 22.04.2021

Future climate changes, as well as differences in climates from one location to another, may involve changes in climatic variability as well as changes in means. In this study, a synthetic weather generator is used to systematically change the within-year variability of temperature and precipitation and therefore also the interannual variability , without altering long-term mean values.

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Crop production in the Fanteakwa District is predominantly rainfed, exposing this major livelihood activity to the variability or change in rainfall pattern. The net potential effect of severe changes in rainfall pattern is the disruption in crop production leading to food insecurity, joblessness, and poverty. As a major concern to food production in Ghana, this study seeks to show the relationship between the production of major crops and rainfall distribution pattern in the Worobong Agroecological Area WAA relative to food security in the face of climate change. The study analysed the variability in local rainfall data, examining the interseasonal main and minor rainfall distribution using the precipitation concentration index PCI , and determined the pattern, availability of water, and the strength of correlation with crop production in the WAA. Data from the Ghana Meteorological Agency GMet spanning a year period and grouped into 3 decades of 10 years each was used. Part of the result revealed that rainfall variability within the major seasons in the 3 groups was lower than the minor seasons.

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Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. How mean historical and future climate change affects crop yields has received a great deal of attention 1 , 2 , 3 , 4 , 5. However, how variations in climate impact crop yield, and how they vary over time, has received less attention 6 , 7.

Impact of temperature and precipitation variability on crop model predictions

Metrics details. Climate is a key input of rain-fed agriculture. Climate variability and change has been the most important determinant of crop yields in Kenya and other parts of the world.

Climate change is likely to increase the frequency of drought and more extreme precipitation events. The objectives of this study were i to assess the impact of extended drought followed by heavy precipitation events on yield and soil organic carbon SOC under historical and future climate, and ii to evaluate the effectiveness of climate adaptation strategies no-tillage and new cultivars in mitigating impacts of increased frequencies of extreme events and warming. We used the validated SALUS crop model to simulate long-term maize and wheat yield and SOC changes of maize-soybean-wheat rotation cropping systems in the northern Midwest USA under conventional tillage and no-till for three climate change scenarios one historical and two projected climates under the Representative Concentration Path RCP 4. We found maize grain yield declined under the projected climates, whereas wheat grain yield increased. No-tillage is able to reduce yield loss compared to conventional tillage and increased SOC levels 1.

Increasing global CO 2 emissions have profound consequences for plant biology, not least because of direct influences on carbon gain. However, much remains uncertain regarding how our major crops will respond to a future high CO 2 world. Crop model inter-comparison studies have identified large uncertainties and biases associated with climate change.

Translating large-scale climate variability into crop production forecast in Europe

These three districts are located in high-moisture-stress areas because of crop season rainfall variability.

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Thank you for visiting nature. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Studies show that climate variability drives interannual changes in meteorological variables in Europe, which directly or indirectly impacts crop production.

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Impact of temperature and precipitation variability on crop model predictions

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