Efficient Method of Discharge Measurements in Rivers and Streams

9415862邱河川的水流是地球上水文循环的主要组成部分。 为了研究和预测水流和各种过程，如河流和溪流中沉积物和污染物的输送，必须测量或估计的一个重要水文变量是流量。 为了确定流量，传统方法需要大量的速度测量，因此对于许多至关重要的情况下的应用来说太耗时、低效和昂贵。 拟议的项目将开发一种有效的流量测量方法，该方法将具有合理的理论基础，并且只需要少量的流速测量。 该方法还可以增强现代的速度剖面测量设备，例如声学多普勒海流剖面仪（ADCP），由于技术原因，该设备会丢失床和水面附近的速度数据。 待开发的方法可以填补缺失的数据，并迅速将设备测量的速度分布转化为横截面平均速度，从而转化为流量。 因此，它甚至应该适用于随时间迅速变化的河流和溪流中的流动，例如在冰、风和潮汐影响下的流动。 它也适用于连接两个湖泊的河流，即使流向也会周期性变化。 该方法的另一个重要应用是确定（卡尔曼）滤波方案的流量，该方案可以被设计为通过使用监测到的流量和水位来顺序地更新流阻，以减少流量预测中的不确定性。 该方法将基于能够表示从河床到水面的各种速度分布模式的速度分布模型，而不管最大速度是出现在水面上还是水面下。 该模型是基于概率和熵的概念，再加上一个几何技术，使用曲线坐标系。

9415862 Chiu The flow in rivers and streams is a major component of the hydrologic cycle on earth. To study and forecast the flow and various processes such as the transport of sediment and pollutants in rivers and streams, an essential hydrologic variable that must be measured or estimated is the discharge. To determine the discharge, conventional methods require a great amount of velocity measurement and are, therefore, too time-consuming, inefficient and costly for applications in many situations of critical importance. The proposed project will develop an efficient method of discharge measurements, which will have a sound, theoretical basis, and will require only a small amount of velocity measurement. The method can also enchance a modern, velocity-profile measuring device, such as an Acoustic Doppler Current Profiler (ADCP) which,for technical reasons, misses velocity data near the bed and water surface. The method to be developed can fill the missed data and quickly translate a velocity profile measured by the device into the cross-sectional mean velocity and, hence, the discharge. Therefore, it should be applicable even to flows in rivers and streams that change rapidly with time, such as flows under the effects of ice, wind, and tides. It is also applicable to rivers connecting two lakes, in which even the flow direction changes periodically. Another important application of the method is to determine the discharge for (Kalman) filtering schemes, that can be designed to sequentially update the flow resistance by using the monitored discharge and water level, to reduce the uncertainty in flow forecasting. The method will be based on a velocity distribution model capable of representing various velocity distribution patterns, from the channel bed to the water surface, regardless of whether the maximum velocity occurs on or below the water surface. The model is based on the probability and entropy concepts, coupled with a geometrical technique using a curvilinear coordinate s ystem.