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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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.

Impact of temperature and precipitation variability on crop model predictions

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. For precipitation, both the magnitude and the qualitative nature of the variability are manipulated.

The synthetic daily weather series serve as input to four crop simulation models. Crop growth is simulated for two locations and three soil types. Results indicate that average predicted yield decreases with increasing temperature variability where growing-season temperatures are below the optimum specified in the crop model for photosynethsis or biomass accumulation.

However, increasing within-year variability of temperature has little impact on year-to-year variability of yield. The influence of changed precipitation variability on yield was mediated by the nature of the soil. The response on a droughtier soil was greatest when precipitation amounts were altered while keeping occurrence patterns unchanged. When increasing variability of precipitation was achieved through fewer but larger rain events, average yield on a soil with a large plant-available water capacity was more affected.

This second difference is attributed to the manner in which plant water uptake is simulated. Failure to account for within-season changes in temperature and precipitation variability may cause serious errors in predicting crop-yield responses to future climate change when air temperatures deviate from crop optima and when soil water is likely to be depleted at depth.

This is a preview of subscription content, access via your institution. Rent this article via DeepDyve. Austin, M. Berry, J. Plant Phys. Google Scholar. Bonan, G. Buttler, I. Cohen, S. Gordon, H. Hanks, R. Jones, C. Press, College Station, pp. Katz, R. Mearns, L. D95 , — Moen, T. Systems 46 , 79— Neild, R. Nonhebel, S.

Systems 44 , — Priestley, C. Reed, D. Richardson, C. Rind, D. Semenov, M. Forest Meteorol. Sharpley, A. Model Documentation , U. User Manual , U. Research Serv. Simane, B. Stockle, C. Irrigation 3 , — ASAE 32 , 66— Waggoner, P. Wilks, D. Williams, J. Singh ed. Wilson, C. Research Paper Download references.

Susan J. Reprints and Permissions. Riha, S. Impact of temperature and precipitation variability on crop model predictions. Climatic Change 32, — Download citation. Received : 15 November Revised : 11 October Issue Date : March Search SpringerLink Search. Abstract 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.

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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. This study demonstrated the need to consider extreme weather events, particularly drought and extreme precipitation events, in climate impact assessment on crop yield and adaptation through no-tillage and new genetics reduces yield losses. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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.

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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. The need to quantify uncertainty has drawn the fields of plant molecular physiology, crop breeding and biology, and climate change modeling closer together. Comparing data from different models that have been used to assess the potential climate change impacts on soybean and maize production, future yield losses have been predicted for both major crops.

Impact of temperature and precipitation variability on crop model predictions

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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. The study used ordinary least square OLS regression to examine the effect of climate variability. The multinomial logistic regression result reveals that households adopt hybrid crops maize and sorghum and dry-sowing adaptation strategies if there is shortage during the cropping season. Cropland increment has positive and significant effect on employing each adaptation strategy. The probability of adopting techniques such as water harvesting, hybrid seeds and dry sowing significantly reduces if a household has a large livestock.

Higher temperatures associated with decreasing relative humidity conditions can lead to severe drought and affect yield potential and impact crop production. Canadian climate model projection studies indicate a gradual decline in annual precipitation in the prairie province of Saskatchewan Price et al. Given the projected changes in annual precipitation and temperature in Saskatchewan, the aim of this paper is to estimate the effect of precipitation and temperature on crop yield distributions by a full- and partial-moment-based approach.

Перила были невысокими. Как это странно, подумал Стратмор, что насчет вируса Чатрукьян был прав с самого начала. Его падение пронзило Стратмора холодным ужасом - отчаянный крик и потом тишина. Но более страшным стало то, что он увидел в следующее мгновение. Скрытые тенью, на него смотрели глаза Грега Хейла, глаза, полные ужаса.

Introduction

Беккер посмотрел на него с недоумением. Панк сплюнул в проход, явно раздраженный невежеством собеседника. - Табу Иуда. Самый великий панк со времен Злого Сида. Ровно год назад он разбил здесь себе голову.

Слишком уж удобная версия. Стратмор пожал плечами. - Слабое сердце… да к тому же еще испанская жара. Не забывай и о сильнейшем стрессе, связанном с попыткой шантажировать наше агентство… Сьюзан замолчала. Какими бы ни были обстоятельства, она почувствовала боль от потери талантливого коллеги-криптографа. Мрачный голос Стратмора вывел ее из задумчивости. - Единственный луч надежды во всей этой печальной истории - то, что Танкадо путешествовал .

Я жду. Бринкерхофф застонал, сожалея, что попросил ее проверить отчет шифровалки. Он опустил глаза и посмотрел на ее протянутую руку. - Речь идет о засекреченной информации, хранящейся в личном помещении директора. Ты только представь себе, что будет, если об этом станет известно.

Существовал только один разумный путь - выключить. Чатрукьян знал и то, что выключить ТРАНСТЕКСТ можно двумя способами. Первый - с личного терминала коммандера, запертого в его кабинете, и он, конечно, исключался. Второй - с помощью ручного выключателя, расположенного в одном из ярусов под помещением шифровалки. Чатрукьян тяжело сглотнул.

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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.

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Crop growth is simulated for two locations and three soil types. Results indicate that average predicted yield decreases with increasing temperature variability.

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