Impact of Different Methods of Climate Change Scenario Construction on the Yield Distributions of Winter Wheat Using Crop Growth Simulation Models PDF Download
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Author: Theodoros Mavromatis
Publisher:
ISBN:
Category : Climatic changes
Languages : en
Pages :
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Author: Theodoros Mavromatis
Publisher:
ISBN:
Category : Climatic changes
Languages : en
Pages :
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Book Description
Author: Theodoros Mavromatis
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: J.J. Beukema
Publisher: Springer Science & Business Media
ISBN: 9400920032
Category : Science
Languages : en
Pages : 216
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J. J. Beukema, w. J. Wolff & J. J. W. M. Brouns Man is changing the biosphere at an ever increasing Netherlands ministery of Housing, Physical Planning rate. Several of these man-made changes are on a and Health (represented by Dr. G. P. Hekstra), chaired worldwide scale, such as the increase in atmospheric by Dr. w. J. Wolff (Research Institute for Nature concentrations of several gases. In particular the Management) and housed by the Netherlands In ongoing increase of the concentration of at stitute for Sea Research (N. I. O. Z. , represented by Dr. mospheric carbon dioxide, by excessive burning of J. J. Beukema). fossil fuels and forest destruction, is well The written versions of the presentations by 23 par documented. By the year 2050, CO levels will ticipants have been brought together in these pro 2 almost certainly be twice the pre-industrial concen ceedings of the Workshop. trations and this is expected to have far-reaching consequences. Direct effects include higher rates of The first paper, by G. P. HEKSTRA, explains how plant production (also in agriculture). Indirect effects trace gases affect UV-B radiation, alkalinity of the might be less favourable: by the intensified sea, rate of photosynthesis, and greenhouse warm 'greenhouse process' (to which several other gases ing.
Author: J. Grasman
Publisher: Springer Science & Business Media
ISBN: 9401109621
Category : Mathematics
Languages : en
Pages : 662
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Researchers in the natural sciences are faced with problems that require a novel approach to improve the quality of forecasts of processes that are sensitive to environmental conditions. Nonlinearity of a system may significantly complicate the predictability of future states: a small variation of parameters can dramatically change the dynamics, while sensitive dependence of the initial state may severely limit the predictability horizon. Uncertainties also play a role. This volume addresses such problems by using tools from chaos theory and systems theory, adapted for the analysis of problems in the environmental sciences. Sensitive dependence on the initial state (chaos) and the parameters are analyzed using methods such as Lyapunov exponents and Monte Carlo simulation. Uncertainty in the structure and the values of parameters of a model is studied in relation to processes that depend on the environmental conditions. These methods also apply to biology and economics. For research workers at universities and (semi)governmental institutes for the environment, agriculture, ecology, meteorology and water management, and theoretical economists.
Author: Stephen K. Harvey
Publisher:
ISBN:
Category : Wheat
Languages : en
Pages : 160
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Book Description
In the sub-arctic region of Interior Alaska, warmer temperatures and a longer growing season caused by climate change could make spring wheat (Triticum aestivum L.) a more viable crop. In this study, a crop model was utilized to simulate the growth of spring wheat in future climate change scenarios RCP4.5 (medium-low emission) and RCP8.5 (high emission) of Fairbanks, Alaska. In order to fulfill such simulation, in 2018 high quality crop growth datasets were collected at the Fairbanks and Matanuska Valley Experiment Farms and along with historic variety trial data, the crop model was calibrated and validated for simulating days to maturity (emergence to physiological maturity) and yield of spring wheat in Fairbanks. In the Fairbanks 1989-2018 (baseline) climate, growing season (planting to physiological maturity) average temperature and total precipitation are 15.6° C and 122 mm, respectively. In RCP4.5 2020-2049 (2035s), 2050-2079 (2065s), and 2080-2099 (2090s) projected growing season average temperature and total precipitation are 16.7° C, 17.4° C, 17.8° C and 120 mm, 112 mm, 112 mm, respectively. In RCP8.5 2035s, 2065s, and 2090s projected growing season average temperature and total precipitation are 16.8° C, 18.5° C, 19.5° C and 120 mm, 113 mm, 117 mm, respectively. Using Ingal, an Alaskan spring wheat, the model simulated days to maturity and yield in baseline and projected climate scenarios of Fairbanks, Alaska. Baseline days to maturity were 69 and yield was 1991 kg ha-1. In RCP4.5 2035s, 2065s, and 2090s days to maturity decreased to 64, 62, 60 days, respectively, and yield decreased 2%, 6%, 8%, respectively. In RCP8.5 2035s, 2065s, and 2090s days to maturity decreased to 64, 58, 55 days, respectively, and yield decreased 1%, 3%, then increased 1%, respectively. Adaptation by cultivar modification to have a growing degree day requirement of 68 days to maturity in RCP4.5 2035s and RCP8.5 2035s resulted in increased yields of 4% and 5%, respectively. Climatic parameters of temperature and precipitation per growing season day are projected to become more favorable to the growth of spring wheat. However, precipitation deficit, an indicator of water stress was found to stay similar to the baseline climate. Without adaption, days to maturity and yield are projected to decrease. Selection and/or breeding of spring wheat varieties to maintain baseline days to maturity are a priority to materialize yield increases in the area of Fairbanks, Alaska.
Author: Mona Maze
Publisher: Sudwestdeutscher Verlag Fur Hochschulschriften AG
ISBN: 9783838137476
Category :
Languages : en
Pages : 196
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The purpose of this study was to develop a new crop simulation model that simulated the crop biomass and yield of winter wheat from accumulated thermal units and simple partitioning rules under the different water and weather conditions in Bavaria, by using the least required input data from the users, which permits a large section of users to use the model. Therefore, the simulated crop model was designed to be used not only at the research sector, but also at the educational and applied sectors. The developed model estimated also the winter wheat yield under the expected future weather conditions, by using the weather models REMO, CLM and STARII, for estimating the expected crop behavior and distribution of winter wheat till 2100.
Author:
Publisher:
ISBN:
Category : Agricultural estimating and reporting
Languages : en
Pages : 244
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Author: Walter H. Wischmeier
Publisher:
ISBN:
Category : Agricultural conservation
Languages : en
Pages : 70
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Book Description
The Universal Soil Loss Equation (USLE) enables planners to predict the average rate of soil erosion for each feasible alternative combination of crop system and management practices in association with a specified soil type, rainfall pattern, and topography. When these predicted losses are compared with given soil loss tolerances, they provide specific guidelines for effecting erosion control within specified limits. The equation groups the numerous interrelated physical and management parameters that influence erosion rate under six major factors whose site-specific values can be expressed numerically. A half century of erosion research in many States has supplied information from which at least approximate values of the USLE factors can be obtained for specified farm fields or other small erosion prone areas throughout the United States. Tables and charts presented in this handbook make this information readily available for field use. Significant limitations in the available data are identified.
Author: Intergovernmental Panel on Climate Change. Working Group II.
Publisher: Cambridge University Press
ISBN: 9780521634557
Category : Science
Languages : en
Pages : 532
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Cambridge, UK : Cambridge University Press, 1998.
Author: Cori Salinas
Publisher:
ISBN:
Category : Wheat
Languages : en
Pages : 0
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Wheat offers winter forage for cattle grazing and is one of the most valuable cash crops in Texas. Yields averaged 30.5 bushels per acre, with a maximum of 37 bushels and a minimum of 24 bushels in 2007 and 2006, respectively. In 2020, the U.S. ranked fifth for wheat production worldwide, while Texas ranked ninth within the U.S. About 40-45% of the wheat produced in the U.S. is used domestically, and 55-60% is exported overseas. Winter wheat yields can be impacted by the various impacts of climate change, which can eventually impact farmers’ income. Rising temperatures and fluctuating precipitation have been observed globally over several decades. Considering changes in climate, farmers will have to adjust their strategies to keep up with changes in weather patterns and changes in the market. The objective of this research is to evaluate the impacts of climate change on Texas winter wheat yield. The data for this research includes yield, prices, soil, management strategies, and climate factors, including precipitation and temperature, from sixteen wheat-producing counties in Texas. Data collection comes from the National Agricultural Statistical Service (NASS), the United States Department of Agriculture (USDA), and the Parameter-elevation Regressions on Independent Slopes Model (PRSIM). Graphs, correlations, and projection analysis will present how factors have an impact on winter wheat yields. Agricultural Policy Environmental eXtender (APEX) and Coupled Model Intercomparison Project-Phase 5 (CMIP 5) are used in this study to determine the most reasonable future trajectory of Texas winter wheat yields. The APEX model has been successfully calibrated to simulate winter wheat crop yields. This study contributes to the understanding of climate change’s impact on yields and farm incomes by projecting their impacts on wheat yields in Texas. Results indicated that yields are expected to decrease due to the impacts of future climate change. In the RCP4.5 scenario, when temperatures are expected to increase 4 to 6 °F, simulated projections resulted in a 44.44% yield decrease during the 2046-2070 time period compared to the Historical PRISM baseline from 1981 to 2005. Maximum yield increases were 43.48% under the PRISM 1981-2017 and the Historical CMIP5 1956-1980 scenarios under the same baseline. Results compared to the PRISM 1981 to 2017 baseline depicted a maximum wheat yield decrease of 54.55% under the RCP4.5 2046-2070 time period scenario. The maximum yield increase of 20% compared to this baseline came from the Historical PRISM 1981-2005 time period scenario. The projected changes in climate will be detrimental to some winter wheat growing areas but also improve crop growth in other areas. Overall, yields will not be as heavily impacted as projected.
