共查询到19条相似文献,搜索用时 250 毫秒
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本文通过对ADCP实测流量随机误差统计数据的分析,建立了最大相对误差与随机不确定度之间的关系,给出了 ADCP流量测验最大相对误差预测模型。利用在美国加利福尼亚州Imperial Irrigation District灌渠试验得到的数据验证了最大相对误差和随机不确定度预测模型的有效性。最大相对误差预测模型和随机不确定度预测模型都可以用于指导ADCP流量测验作业以保证测验精度满足要求。 相似文献
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结合传统流速仪测定方法对比走航式ADCP在辽东地区水文测流的适用性,结果表明:由于辽东山区河流较多,高水流速较大,使得走航式ADCP适用性降低,但在畅流期中低水时,流速较小时,具有一定的适用性。在中低水流速时,通过流量测定精度分析,走航式ADCP流量测定的系统误差和随机不确定度均可满足河流流量测验规范的允许误差要求。研究成果对于辽东地区河流巡测方案的制定具有参考价值。 相似文献
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本文介绍了无线ADCP基本原理、流量计算方法及桥沟站流量测验资料分析,修正设置参数,提高该仪器测验精度,减小流速、流量测验误差。 相似文献
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ADCP河流流量测验及其误差分析 总被引:1,自引:0,他引:1
声学多普勒流速剖面仪(简称ADCP)作为水体流量测验的新仪器,由于该仪器优于传统的流量测验方法,且具有测量快速、不干扰水体、极少受天气影响等优点,是河流流量测验领域的一次革命,具有广阔的发展前景,因而,近年在我国的河流、湖泊、海洋等的水文测验中得到了广泛的应用,特别是在潮汐河段的水文测验中应用较多。通过分析ADCP流量测验原理、方法和与传统方法的对比试验,探讨了ADCP流量测验中存在的几种测量误差成因,并对其误差提出了相应的解决对策,供广大用户参考。 相似文献
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感潮水文站河流自然流态在潮水涨、落的影响下,顺逆变化,给流量测验带来很大影响。传统流速仪测量方法,测次多,误差大,为此采用声学多普勒流速剖面仪(ADCP)进行流速和流量的测量。比较了传统流速仪与ADCP测流的优缺点,介绍了ADCP的测量原理、安装、使用,详细分析了ADCP流速、流量比测和率定,并进行评定,以探索定点式ADCP测法在感潮水文站进行潮流量测验的可行性。黄屋屯水文站使用结果说明ADCP比较适用于感潮水文站的流量测验。 相似文献
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走航式ADCP在河流流量测验中得到广泛运用,但当河床存在走沙现象时,“底跟踪”模式下流量测验受影响显著。该文从ADCP的流量计算原理及误差成因出发,提出用计算航迹偏移量的方法来推算河床走沙影响的流量偏小值,以完成对“底跟踪”流量的修正,为无GPS定位条件下,使用ADCP获得可靠流量数据提供一种新的计算方法。 相似文献
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在珠江三角洲河区测船测流和安装固定H-ADCP测流无法普及使用的情况下,可采用浮标式ADCP自动测量流量。介绍了浮标式ADCP自动流量测验的方法、研究内容,分析了数据比测结果和误差等,阐述了浮标式ADCP测流在珠三角地区的应用情况。此应用特别适合网河区巡测和船只较多的河道断面,运行成本低,解决了三角洲各河道流量资料缺乏的难题。 相似文献
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K Beven 《Water science and technology》2005,52(6):167-175
A consideration of model structural error leads to some particularly interesting tensions in the model calibration/conditioning process. In applying models we can usually only assess the total error on some output variable for which we have observations. This total error may arise due to input and boundary condition errors, model structural errors and error on the output observation itself (not only measurement error but also as a result of differences in meaning between what is modelled and what is measured). Statistical approaches to model uncertainty generally assume that the errors can be treated as an additive term on the (possibly transformed) model output. This allows for compensation of all the sources of error, as if the model predictions are correct and the total error can be treated as "measurement error." Model structural error is not easily evaluated within this framework. An alternative approach to put more emphasis on model evaluation and rejection is suggested. It is recognised that model success or failure within this framework will depend heavily on an assessment of both input data errors (the "perfect" model will not produce acceptable results if driven with poor input data) and effective observation error (including a consideration of the meaning of observed variables relative to those predicted by a model). 相似文献
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Roughness coefficient and its uncertainty in gravel-bed river 总被引:1,自引:0,他引:1
Manning's roughness coefficient was estimated for a gravel-bed river reach using field measurements of water level and discharge,and the applicability of various methods used for estimation of the roughness coefficient was evaluated.Results show that the roughness coefficient tends to decrease with increasing discharge and water depth,and over a certain range it appears to remain constant.Comparison of roughness coefficients calculated by field measurement data with those estimated by other methods shows that,although the field-measured values provide approximate roughness coefficients for relatively large discharge,there seems to be rather high uncertainty due to the difference in resultant values.For this reason,uncertainty related to the roughness coefficient was analyzed in terms of change in computed variables.On average,a 20%increase of the roughness coefficient causes a 7% increase in the water depth and an 8% decrease in velocity,but there may be about a 15% increase in the water depth and an equivalent decrease in velocity for certain cross-sections in the study reach.Finally,the validity of estimated roughness coefficient based on field measurements was examined.A 10% error in discharge measurement may lead to more than 10% uncertainty in roughness coefficient estimation,but corresponding uncertainty in computed water depth and velocity is reduced to approximately 5%.Conversely,the necessity for roughness coefficient estimation by field measurement is confirmed. 相似文献
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基于统计诊断的异常数据划分,并结合大坝监测数据的误差成因,将监测的异常数据划分为随机误差、粗差、系统误差等,并辨识强影响数据。继而基于均值漂移模型,研究不同异常数据的诊断方法,包括以模型扰动值为依据的粗差的t检验法和以模型扰动对拟合参数的影响为依据的强影响数据的Cook距离检验法。以大坝典型位移监测数据为例,采用上述统计诊断方法对原始监测数据进行合理性检验,结果表明可有效辨识误差数据和强影响数据,能提高数据进一步建模分析的准确性。 相似文献