Specification of channel geometry incorporates a significant impact on hydraulic and hydrologic modeling, flood forecasts, and ecology of any water resources system. Specifically, a large amount of high-resolution data is required for specifying the channel geometry in hydraulic and hydrologic modeling. Moreover, a considerable computational effort is needed to incorporate such big data [4, 5], which is helpful for simplifying assumptions for long river reaches such as rectangular or trapezoidal channels [3]. For example, The National Water Model (NWM) uses a trapezoidal channel representation for 2.7 million river reaches to forecast water discharge for the entire continental United States. This simplification of channel estimation saves the computational effort but has created uncertainties in hydraulic predictions. This issue was addressed by a study done by a group of Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) summer institute, 2018 fellows. The aim of the study was to: (1) evaluate the impact of simplified (NWM trapezoidal) channel geometry representation on hydrological model predictions and (2) suggest an improved representation of channel geometry while maintaining parsimony in model input and runtime [1]. The study has been published in the Journal of the American Water Resources Association, 2020 and can be accessible through the following link: https://onlinelibrary.wiley.com/doi/abs/10.1111/1752-1688.12865

In this study the Hydrologic Engineering Center’s River Analysis System (HEC RAS) model was used to calculate multiple hydrological variables such as stage, discharge, and flood area of three different channels along with three different geometry representations. The channel geometry representations are,

Surveyed channel: Surveyed channels were represented based on lidar. It is the high resolutions representation of channel geometry.

NWM (trapezoidal): NWM assumes the channel as a trapezoidal cross section. In this representation, the channel has infinite depth and a default side slope of 1H:20V which has the simplistic channel representation.

Proposed generalized geometry: The proposed channel geometry is more realistic than the NWM representation and requires less computational cost than surveyed channels. In this representation 5 points should be defined, two bank points and three points at the channel.

As Figure 1(c) shows the channel depths at b, c, and d (h_b, h_c, and h_d, respectively) and the widths (W_ab, W_bc, W_cd, and W_df) between each sequential pair of points are known in this representation. Two assumptions in this representation are possible, one is where all the thalwegs (width between the points) are the same, and the other one is where they are different. The five-point representation assumes level bank elevations, so the seven parameters are sufficient to represent an entire cross section.

After simulating with all the geometry representation, the stages were compared with the U.S. Geological Survey (USGS) stage data of the same locations. Results demonstrated that the simulated stages with the surveyed and the proposed geometry matched with the USGS stage, while the stage for NWM geometry showed much higher value.

An inundation map (Figure 3) of Big Canoe Creek shows the total predicted inundation area using all the geometric representations. Table 1 displays the calculated total inundated area for different geometric representations. Results showed that use of NWM geometry for the channel overpredicts the inundated area compared to other geometric representations. On the other hand, the prediction by using the proposed geometry is more reliable than the NWM approach. Results for the proposed geometry 2 are shown in Figure 3 and Table 1, where all the thalwegs are different; because this approach is more realistic than proposed geometry 1, where all the thalwegs are the same, and the stages from those two approaches are the same (Figure 2).

The results show that proposed channel geometry is a viable one for hydrology and hydraulic modeling and more reliable than the simplistic channel geometry used by NWM. This approach also requires less data and computational effort compared to the surveyed channel geometric representation.

Nowadays, stream stage data is being collected by crowdsourcing, which is gaining popularity as a viable tool for collecting distributed measurements of stream stage. In crowdsourcing, citizen scientists can send hydrologic measurements via text message to a server that stores and displays the data on the web [6]. This way of collecting stage measurement is often easier, especially with the availability of cellphones [2]. In this study, an advanced approach requiring wading of small streams is suggested to test the potential for acquiring channel geometry data of this kind. Local officials or citizen scientists who are involved in collecting channel cross sectional data in a municipality can obtain channel geometry data in the form of the proposed cross sections by simply taking measurements of channel width and depths of the river at a few pre defined points along its width. This will be a straight-forward and easy task that does not require much equipment or intensive training, as only a measuring tape to measure the channel widths and a ruler to measure depths will be sufficient. These methods can be applied by citizen scientists and professionals alike.

For a riverine country like Bangladesh, where surveyed channel geometry data is not readily available for all the rivers, this idea of channel representation and data collection by citizen scientists can be very useful.

Author’s Bio:

Azbina Rahman Oni is a Graduate Research Assistant at the Civil, Environmental, and Infrastructure Engineering of George Mason University.

Acknowledgement:

WRE Forum is thankful to Dr. Md Abul Ehsan Bhuiyan for critically reviewing the article.

References:

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[2] Lowry, C. S., Fienen, M. N., Hall, D. M., & Stepenuck, K. F. (2019). Growing Pains of Crowdsourced Stream Stage Monitoring Using Mobile Phones: The Development of CrowdHydrology. Frontiers in Earth Science, 7, 128. https://doi.org/10.3389/feart.2019.00128

[3] Neal, J. C., Odoni, N. A., Trigg, M. A., Freer, J. E., Garcia-Pintado, J., Mason, D. C., Wood, M., & Bates, P. D. (2015). Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models. Journal of Hydrology, 529, 169–183. https://doi.org/10.1016/j.jhydrol.2015.07.026

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