首页> 外文OA文献 >Evaluation of Surface Runoff Prediction by AnnAGNPS Model in a Large Mediterranean Watershed Covered by Olive Groves
【2h】

Evaluation of Surface Runoff Prediction by AnnAGNPS Model in a Large Mediterranean Watershed Covered by Olive Groves

机译:橄榄树丛覆盖的地中海大流域中的AnnAGNPS模型评估地表径流预报

摘要

The distributed parameter and continuous simulation Annualized Agricultural Non-Point Source (AnnAGNPS) model was implemented in the watershed Anzur (Spain) covered by olive groves, to assess its prediction capability of surface runoff at the large watershed scale in semi-arid conditions. A 5-year database reporting hydrological, geomorphological and land use characteristics of the watershed allowed model implementation. Almost 180 surface runoff events were modelled by AnnAGNPS and compared with the corresponding observations through statistical indexes and grouping the runoff events in order to evaluate the model at different temporal scales (event, monthly and seasonal). AnnAGNPS evaluation showed that, in general, runoff was estimated by the default model with low accuracy at all the investigated time scales, likely, as a result of a simple representation of spatial variability. Calibration (by reducing initial curve numbers (CN) of the olive groves) provided more accurate and satisfactory predictions of event, monthly and seasonal runoff volumes with a low effort in the parameterisation approach. The best model performance was achieved at the event scale. The runoff prediction reliability may be attributable to the AnnAGNPS inaccuracy in adjusting CN values during the continuous simulation of the soil moisture conditions, because estimations of daily evapotranspiration values are quite realistic. Copyright © 2015 John Wiley & Sons, Ltd.
机译:在橄榄树覆盖的流域安祖尔(西班牙)中实施了分布式参数和连续模拟年度农业面源(AnnAGNPS)模型,以评估其在半干旱条件下大流域尺度上地表径流的预测能力。一个5年的数据库报告了该流域的水文,地貌和土地利用特征,从而允许模型实施。 AnnAGNPS对近180个地表径流事件进行了建模,并通过统计指标和对径流事件进行分组与相应的观测值进行了比较,以便在不同的时间尺度(事件,月度和季节)对模型进行评估。 AnnAGNPS评估显示,一般来说,径流是由默认模型在所有调查的时间尺度上以低精度估算的,这很可能是由于空间变异性的简单表示所致。校准(通过减少橄榄树的初始曲线数(CN))以较少的参数设置方法就可以更准确,令人满意地预测事件,月度和季节径流量。在活动规模上获得了最佳的模型性能。径流预测的可靠性可能归因于在连续模拟土壤湿度条件期间调整CN值时AnnAGNPS的不准确性,因为每日蒸散量的估算非常现实。版权所有©2015 John Wiley&Sons,Ltd.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号