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塞尔维亚和奥地利夏季作物绿水成分及作物产量的季节预测

Seasonal forecasting of green water components and crop yield of summer crops in Serbia and Austria.

作者信息

Lalić B, Firanj Sremac A, Eitzinger J, Stričević R, Thaler S, Maksimović I, Daničić M, Perišić D, Dekić Lj

机构信息

Faculty of Agriculture, University of Novi Sad, Dositej Obradovic Sq. 8, 21000 Novi Sad, Serbia.

Institute of Meteorology, University of Natural Resources and Life Sciences, Gregor Mendel Str. 33, A-1180 Vienna, Austria.

出版信息

J Agric Sci. 2018 Jul;156(5):658-672. doi: 10.1017/S0021859618000047. Epub 2018 Feb 14.

DOI:10.1017/S0021859618000047
PMID:30369629
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6199546/
Abstract

A probabilistic crop forecast based on ensembles of crop model output estimates, presented here, offers an ensemble of possible realizations and probabilistic forecasts of green water components, crop yield and green water footprints (WFs) on seasonal scales for selected summer crops. The present paper presents results of an ongoing study related to the application of ensemble forecasting concepts in crop production. Seasonal forecasting of crop water use indicators (evapotranspiration (ET), water productivity, green WF) and yield of rainfed summer crops (maize, spring barley and sunflower), was performed using the AquaCrop model and ensemble weather forecast, provided by The European Centre for Medium-range Weather Forecast. The ensemble of estimates obtained was tested with observation-based simulations to assess the ability of seasonal weather forecasts to ensure that accuracy of the simulation results was the same as for those obtained using observed weather data. Best results are obtained for ensemble forecast for yield, ET, water productivity and green WF for sunflower in Novi Sad (Serbia) and maize in Groß-Enzersdorf (Austria) - average root mean square error (2006-2014) was <10% of observation-based values of selected variables. For variables yielding a probability distribution, capacity to reflect the distribution from which their outcomes will be drawn was tested using an Ignorance score. Average Ignorance score, for all locations, crops and variables varied from 1.49 (spring barley ET in Groß-Enzersdorf) to 3.35 (sunflower water productivity in Groß-Enzersdorf).

摘要

本文提出了一种基于作物模型输出估计集合的概率作物预报方法，该方法针对选定的夏季作物，在季节尺度上提供了绿水成分、作物产量和绿水足迹（WFs）的一系列可能实现情况和概率预报。本文展示了一项正在进行的关于集合预报概念在作物生产中应用的研究结果。利用AquaCrop模型和欧洲中期天气预报中心提供的集合天气预报，对雨养夏季作物（玉米、春大麦和向日葵）的作物用水指标（蒸散量（ET）、水分生产率、绿水足迹）和产量进行了季节预报。将获得的估计集合与基于观测的模拟进行测试，以评估季节天气预报确保模拟结果准确性与使用观测天气数据获得的结果相同的能力。在诺维萨德（塞尔维亚）的向日葵和大恩策斯多夫（奥地利）的玉米的产量、ET、水分生产率和绿水足迹的集合预报中获得了最佳结果——平均均方根误差（2006 - 2014年）小于选定变量基于观测值的10%。对于产生概率分布的变量，使用无知得分测试了反映其结果所来自分布的能力。对于所有地点、作物和变量，平均无知得分从1.49（大恩策斯多夫春大麦ET）到3.35（大恩策斯多夫向日葵水分生产率）不等。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bc0/6199546/575ca17d2631/S0021859618000047_fig15.jpg
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