1) annual average sediment concentration
年均含沙量
1.
The Back Propagation (BP) model of artificial neural networks is applied to predict the annual average sediment concentration in a watershed.
针对小流域的土壤、地质、地貌在一定的时间范围内具有相当稳定的特性 ,选取采伐面积、采伐量、降雨量和年均径流量这四个代表植被、气候的主要因子对流域年均含沙量进行了建模预测 。
2.
In this paper we have improved the BP algorithm in the processes of applying BP algorithm of artificial neural networks for the annual average sediment concentration in a watershed by multi-factors.
本文在用人工神经网络BP模型对流域年均含沙量进行多因素建模过程中 ,对BP算法进行了改进。
2) yearly average sediment concentration
年平均含沙量
3) mean annual sediment content
多年平均含沙量
1.
From the pointview of sediment formation mechanism in basin,the empirical relationship is established for the derivation of mean annual sediment content in rivers without sediment data.
分析四川境内41个水文站(区间)1130站年实测悬移质泥沙资料和相应水文站控制流域内土地利用资料,从流域产沙机理出发,建立了经验关系,以用于无泥沙测验资料地区推求河流多年平均含沙量。
4) mean sediment content
平均含沙量
1.
1 mrn will be delivered into the sea, if the mean sediment contentsare 100~200 kg/m3 and the flood peak discharges are 4 000~5 000 m3/s from the SanmenxiaReservoir in flood periods.
从1973~1990年期间,选取了60个洪峰时段的实测资料,分析了黄河下游河道的泥沙淤积和排沙比,得出结论为,如果洪水期三门峡出库平均含沙量为100~200kg/m3时,出库洪峰流量在4000~5000m3/s之间,可把50%~80%左右0。
5) cross-section mean sediment concentration
断面平均含沙量
1.
Application of the vertical discharge weighting method in determining the cross-section mean sediment concentration
悬移质取样垂线流量权重法测定断面平均含沙量的应用研究
6) distribution of suspended sediment concentrations
泥沙含量年内分配
补充资料:含沙量
指河流每一立方米水中所含泥沙的重量。单位是千克/米3。
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
参考词条