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Evaluation of streamflow predictions by the IHACRES rainfall-runoff model in two South African catchments

机译:通过IHACRES降雨径流模型评估南非两个流域的流量预测

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In many South African catchments, water is an increasingly limited and highly fluctuating resource. Accurate prediction of low flows is especially vital if water resource managers are to successfully balance the growing needs of agriculture, industry and rural and urban populations, while maintaining the ecological health of aquatic and riparian ecosystems. Existing hydrological models in use in South Africa suffer from a number of disadvantages. They are complex, over-parameterised, data demanding and expensive to use. IHACRES, a lumped conceptual model requiring minimal input data, is less limited by these problems, and has the potential to advance our understanding of streamflow patterns and predict how these may be altered by land-use change. The purpose of this paper is to evaluate IHACRES performance for two South African catchments: Lambrechtsbos A (a 31 ha research catchment) and Groot-Nylrivier (74 km~2). IHACRES predicted streamflow at Lambrechtsbos A with useful accuracy (pre-afforestation period, R~2 > 0.81; bias <26 mm/yr; post-afforestation period, R~2 = 0.81, bias = 8.4 mm/yr). With prior knowledge of changes in annual evapotranspiration, predictions of land-use impacts on flow regime may be satisfactorily predicted. Simulations of flows in the Groot-Nylrivier catchment were found to be of useful accuracy for relatively short periods of 2-3 yr, but performance over longer time periods was reduced by poor predictions in certain years. We ascribe this primarily to poor catchment-average rainfall estimation following certain storms in some years. Our simulations highlighted a tendency for IHACRES to underestimate quick flow events, especially at times when the greater part of a catchment is dry. Further model development is required to overcome these problems. IHACRES shows great potential in linking proposed land-use change to altered flow regimes, and efficiently describing the flow characteristics within catchments. However, poor estimation of average rainfall in larger catchments is a limitation that needs to be overcome before long-term flow regimes of non-research catchments may be predicted with confidence.
机译:在许多南非流域,水是一种越来越有限且波动很大的资源。如果水资源管理人员要成功地平衡农业,工业以及农村和城市人口不断增长的需求,同时又要保持水生和河岸生态系统的生态健康,那么准确预测低流量就显得尤为重要。南非使用的现有水文模型有许多缺点。它们是复杂的,过分参数化的,对数据的要求很高且使用成本昂贵。 IHACRES是一个集总的概念模型,需要最少的输入数据,受这些问题的限制较小,并且有可能增进我们对水流模式的理解,并预测土地利用方式的变化如何改变这些模式。本文的目的是评估两个南非流域的IHACRES性能:Lambrechtsbos A(一个31公顷的研究流域)和Groot-Nylrivier(74 km〜2)。 IHACRES预测了Lambrechtsbos A处的径流,其准确性很高(造林前期,R〜2> 0.81;偏差<26 mm / yr;造林后期,R〜2 = 0.81,偏差= 8.4 mm / yr)。有了有关年度蒸散量变化的先验知识,就可以令人满意地预测出土地利用对流量状况的影响。发现在Groot-Nylrivier流域的流动模拟在2-3年的相对短时间内具有很高的准确性,但是由于某些年份的不良预测而降低了较长时间段的性能。我们将此主要归因于某些年份中某些暴风雨造成的集水平均降雨量估算不佳。我们的模拟结果突出显示了IHACRES低估快速流动事件的趋势,尤其是在流域大部分干燥的时候。需要进一步的模型开发来克服这些问题。 IHACRES在将拟议的土地利用变化与变化的流域联系起来并有效描述流域内的流特征方面显示出巨大潜力。但是,在较大的流域,对平均降雨量的估算很差,这是一个局限性,在可以可靠地预测非研究流域的长期流态之前,需要克服这一限制。

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