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首页> 外文期刊>Arabian journal of geosciences >Evaluation and validity of the antecedent moisture condition (AMC) of Natural Resources Conservation Service-Curve Number (NRCS-CN) procedure in undeveloped arid basins
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Evaluation and validity of the antecedent moisture condition (AMC) of Natural Resources Conservation Service-Curve Number (NRCS-CN) procedure in undeveloped arid basins

机译:天然资源保护服务曲线数(NRCS-CN)在未开发的干旱盆地中的前进水分状况(AMC)的评价和有效性

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摘要

The available conversion formulae for AMC-CN are estimated in an environment that is not arid. The validity of these formulae in arid regions is questionable. Therefore, in the current study, a focus is made on studying the validity of the NRCS-CN theory, its AMC, formulas, and derivation of conversion formulae of CN for some arid basins in the southwest Saudi Arabia (SA). One hundred sixty-one rainfall-runoff events have been collected over a period of 4 years on 19 sub-basins in the study area. The results show that in arid regions the AMCI antecedent moisture condition at (dry) conditions is dominant. It has been shown that the abstraction ratio, lambda = 0.01, is the best to fit the NRCS-CN theory when compared with lambda = 0.2 or 0.3. The observed and estimated runoff show that the root mean square error (RMSE) is the lowest for lambda = 0.01 (1.8 mm, 3.69 mm, and 1.36 mm) when compared with lambda = 0.2 (4.21 mm, 12.13 mm, and 3.15 mm) and lambda = 0.3 (5.74 mm, 13.92 mm, and 3.1 mm) for CNI (CN at dry condition), CNII (CN at normal condition), and CNIII (CN at wet condition) respectively. The upper and lower limits of lambda, in SA, are 0.02 (90% probability) and 0.00001 (10% probability) respectively. The runoff coefficient is less than 0.4. This is due to high transmission losses which is typical in arid regions. The study recommends using lambda = 0.01 and the developed AMC-CN formulae for enhanced runoff predictions in SA.
机译:AMC-CN的可用转换公式估计在不干旱的环境中。在干旱地区的这些公式的有效性是值得怀疑的。因此,在目前的研究中,对研究NRCS-CN理论,其AMC,公式和CN转化公式的有效性进行了重点,在沙特阿拉伯西南部(SA)中的一些干旱盆地的转化公式。在研究区的19个次池中收集了一百六十一度的降雨径流事件。结果表明,在干旱地区(干燥)条件下的AMCI前一种水分状况是显性的。已经表明,抽象率Lambda = 0.01是与Lambda = 0.2或0.3相比的最佳拟合NRCS-CN理论。观察到和估计的径流表明,与λ= 0.2(4.21mm,12.13mm和3.15mm)相比,Lambda = 0.01(1.8mm,3.69 mm和1.36 mm)的根均方误差(RMSE)是最低的和λ= 0.3(5.74mm,13.92 mm,3.1mm),用于CNI(干燥条件下的CN),CNII(正常条件下CN)和CNIII(潮湿条件下的CN)。 Lambda的上限和下限分别为0.02(90%)和0.00001(10%)。径流系数小于0.4。这是由于在干旱地区典型的高传输损耗。该研究建议使用Lambda = 0.01和发达的AMC-CN公式,用于增强SA中的径流预测。

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