نتایج جستجو برای: both weather simulations indicated similar annual crop yields nevertheless
تعداد نتایج: 2976080 فیلتر نتایج به سال:
We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scale...
We specify a three-stage production function for rice cultivation which incorporates the sequential nature of both production shocks, including weather, and input choices based on sequentially updated information sets of history of realized shocks and observed changes in crop growth. The production function is CES across stages, thus taking into account substantial complementarities between dif...
A non-homogeneous hidden Markov model (NHMM) is used to make stochastic simulations of March–August daily rainfall at 10 stations over the southeastern United States, 1923–98. Station-average observed daily rainfall is prescribed as an input to the NHMM, which is then used to disaggregate the rainfall in space. These rainfall simulations are then used as inputs to a CERES crop model for maize. ...
In this study, we applied version 4.5 of the Community Land Model (CLM) at a 0.1258 resolution to provide the first county-scale model validation for simulating crop yields over the Conterminous United States (CONUS). Large bias was found in simulating crop yields against U.S. Department of Agriculture (USDA) survey data, with county-level root-mean-square error (RMSE) of 42% and 38% for simula...
Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperat...
Pan-European crop modelling with EPIC: Implementation, up-scaling and regional crop yield validation
Justifiable usage of large-scale crop model simulations requires transparent, comprehensive and spatially extensive evaluations of their performance and associated accuracy. Simulated crop yields of a Pan-European implementation of the Environmental Policy Integrated Climate (EPIC) crop model were satisfactorily evaluated with reported regional yield data from EUROSTAT for four major crops, inc...
Understanding the effects of climate variability and extremes on crop growth and development represents a necessary step to assess the resilience of agricultural systems to changing climate conditions. This study investigates the links between the large-scale atmospheric circulation and crop yields in Europe, providing the basis to develop seasonal crop yield forecasting and thus enabling a mor...
S table and secure food production is essential to civilization. Any methods that improve our understanding of crop yields have the potential to reduce human suffering and help provide the caloric needs of an expanding world population. Similar hopes apply to commodity crops such as cotton and those used to meet energy needs. Given the vast amount of agricultural research and experience, it mig...
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