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Assessing seasonal climatic impact on water resources and crop production using CLIGEN and WEPP models

机译:使用CLIGEN和WEPP模型评估季节性气候对水资源和作物生产的影响

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Physically based response models are useful tools for assessing climatic impact on water resources and crop productivity. Most response models require daily weather, which is often synthesized using stochastic daily weather generators. Synthesis of climate scenarios using weather generators provides an effective means for making impact assessments. The objectives were to evaluate the ability of the CLIGEN model to generate various climate scenarios and to assess further the hydrological and crop productivity responses using the WEPP model. The CLIGEN model was evaluated at four Oklahoma weather stations with mean annual precipitation ranging from 420 to 1150 mm and was then used to generate typical climate scenarios that represent wet, dry, and average conditions for Chandler, Oklahoma. The WEPP model was used to simulate hydrologic and grain yield responses to the generated climate scenarios. Results show that CLIGEN simulated daily and monthly precipitation reasonably well. CLIGEN was capable of preserving statistics of monthly precipitation as well as reproducing seasonal precipitation patterns for the dry, average, and wet year conditions. Simulated surface runoff, deep percolation, and plant transpiration increased as precipitation increased, but the rates of the increase varied with initial soil moisture levels and total precipitation. Predicted percent increase of wheat grain yield per 1% increase of growing-season precipitation, which was a function of initial soil moisture and total precipitation, ranged from 0.5% to 0.75%. Overall results indicate that CLIGEN is capable of translating monthly climate forecasts into daily weather series while preserving statistics of the forecasts. This study demonstrates that CLIGEN, when used in conjunction with response models such as WEPP, provides a useful tool for assessing the impact of seasonal climate variations or forecasts on water resources and crop production.
机译:基于物理的响应模型是评估气候对水资源和农作物生产力的有用工具。大多数响应模型都需要每日天气,通常使用随机的每日天气生成器进行综合。使用天气生成器综合气候情景为进行影响评估提供了有效的手段。目的是评估CLIGEN模型生成各种气候情景的能力,并使用WEPP模型进一步评估水文和作物生产力的响应。在四个俄克拉荷马州气象站对CLIGEN模型进行了评估,年平均降水量在420至1150 mm之间,然后被用于生成代表俄克拉荷马州钱德勒的潮湿,干燥和平均状况的典型气候情景。 WEPP模型用于模拟水文和粮食产量对产生的气候情景的响应。结果表明,CLIGEN模拟了每天和每月的降水。 CLIGEN能够保存每月降水的统计数据,并能够再现干旱,平均和潮湿年份的季节性降水模式。随着降水增加,模拟的地表径流,深层渗滤和植物蒸腾作用增加,但增加的速率随初始土壤湿度和总降水量而变化。生长季节降水每增加1%,小麦籽粒增产的预测百分比为0.5%至0.75%,这是初始土壤湿度和总降水量的函数。总体结果表明,CLIGEN能够将每月的气候预报转换为每日的天气序列,同时还能保留天气预报的统计信息。这项研究表明,CLIGEN与WEPP等响应模型结合使用时,为评估季节性气候变化或预测对水资源和农作物的影响提供了有用的工具。

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