Calibrating 1D hydrodynamic river models in the absence of cross-section geometry using satellite observations of water surface elevation and river width

Hydrodynamic modeling has been increasingly used to simulate water surface elevation which is important for flood prediction and risk assessment. Scarcity and inaccessibility of in situ bathymetric information have hindered hydrodynamic model development at continental-to-global scales. Therefore, river cross-section geometry is commonly approximated by highly simplified generic shapes. Hydrodynamic river models require both bed geometry and roughness as input parameters. Simultaneous calibration of shape parameters and roughness is difficult, because often there are trade-offs between them. Instead of parameterizing cross-section geometry and hydraulic roughness separately, this study introduces a parameterization of 1D hydrodynamic models by combining cross-section geometry and roughness into one conveyance parameter. Flow area and conveyance are expressed as power laws of flow depth, and they are found to be linearly related in log–log space at reach scale. Data from a wide range of river systems show that the linearity approximation is globally applicable. Because the two are expressed as power laws of flow depth, no further assumptions about channel geometry are needed. Therefore, the hydraulic inversion approach allows for calibrating flow area and conveyance curves in the absence of direct observations of bathymetry and hydraulic roughness. The feasibility and performance of the hydraulic inversion workflow are illustrated using satellite observations of river width and water surface elevation in the Songhua river, China. Results show that this approach is able to reproduce water level dynamics with root-mean-square error values of 0.44 and 0.50 m at two gauging stations, which is comparable to that achieved using a standard calibration approach. In summary, this study puts forward an alternative method to parameterize and calibrate river models using satellite observations of river width and water surface elevation.

Dam break analysis using 1D geometry at Jatigede Dam, Sumedang

Dam breaks can result in flash floods which have enormous destructive power. This destructive force becomes even more significant when the dam break occurs in a dam with a large capacity. An example is the Jatigede Dam, which has a capacity of 1,060 million m3. To determine the flash flood characteristics and potential impact of the collapse of the Jatigede Dam, an analysis of the dam break was carried out using HEC-RAS software. The dam break scenario uses a Probable Maximum Flood (PMF) inflow with the partial opening of two spillway gates in the middle, which causes the dam overtopping. The Froehlich and Von Thun, and Gillette regression methods were used to defining the breach parameters. Based on the dam break analysis, the simulated flash flood of the Von Thun-Gillette method resulted in a higher velocity and lower water surface elevation than the Froehlich method. The difference in the velocity, dimension of the breach shape, water surface elevation, and discharge is caused by the breaching shape and breach formation time.

Transformation of Water Wave Spectra into Time Series of Surface Elevation

Spectral wave modelling is widely used to simulate large-scale wind–wave processes due to its low computation cost and relatively simpler formulation, in comparison to phase-resolving or hydrodynamic models. However, some applications require a time-domain representation of sea waves. This article proposes a methodology to transform the wave spectrum into a time series of water surface elevation for applications that require a time-domain representation of ocean waves. The proposed method uses a generated phase spectrum and the inverse Fourier transform to turn the wave spectrum into a time series of water surface elevation. The consistency of the methodology is then verified. The results show that it is capable of correctly transforming the wave spectrum, and the significant wave height of the resulting time series is within 5% of that of the input spectrum.

Deep visual domain adaptation and semi-supervised segmentation for understanding wave elevation using wave flume video images

Accurate water surface elevation estimation is essential for understanding nearshore processes, but it is still challenging due to limitations in measuring water level using in-situ acoustic sensors. This paper presents a vision-based water surface elevation estimation approach using multi-view datasets. Specifically, we propose a visual domain adaptation method to build a water level estimator in spite of a situation in which ocean wave height cannot be measured directly. We also implemented a semi-supervised approach to extract wave height information from long-term sequences of wave height observations with minimal supervision. We performed wave flume experiments in a hydraulic laboratory with two cameras with side and top viewpoints to validate the effectiveness of our approach. The performance of the proposed models were evaluated by comparing the estimated time series of water elevation with the ground-truth wave gauge data at three locations along the wave flume. The estimated time series were in good agreement within the averaged correlation coefficient of 0.98 and 0.90 on the measurement and 0.95 and 0.85 on the estimation for regular and irregular waves, respectively.

Evaluation of Hydraulic Performance On Lower Areb Small Scale Irrigation Scheme Amhara, Ethiopia

This study was conducted in the Lower Areb small-scale irrigation scheme for one crop season from March to May 2018 to evaluate the hydraulic performance of the scheme by estimating the hydraulic performance indicators, physical performance indicators, and maintenance performance indicators. The primary data including water flow rate, soil physical properties, and water infiltration were collected. The secondary data collected were climatic, crop data, and data from different reports and design documents including the irrigation water users' interviews. The hydraulic performance of the irrigation scheme was evaluated by estimating adequacy, efficiency, dependability, and equity indicators at nine selected offtakes; three each at the head, middle, and tail reaches of the scheme. The physical performance and maintenance indicators were determined using the irrigation ratio, the sustainability of the irrigated area, the effectiveness of infrastructure, and the water surface elevation ratio. The data were analyzed by using CROPWAT 8.0, ARC GIS 10.1 software, and Microsoft Excel 2013. The overall average values of adequacy, efficiency, dependability, and equity were found to be 0.89. 0.91, 0.096 and 0.07 respectively. Therefore, dependability, equity, and efficiency were under good condition and adequacy was under fair condition. The irrigation ratio and sustainability of irrigated areas were 54% and 123% respectively. The effectiveness of infrastructure and water surface elevation ratios were 73.33% and 94% respectively.

Morphometry of Gelionys and Žaliasis Lakes

Bathymetric surveys of Gelionys and Žaliasis Lakes (located in the Baltic Uplands, Aukštadvaris Regional Park, Lithuania) were carried out on April 21, 2020, from a boat with attached Lowrance HDI SKIMMER XDCR transducer (200 kHz), Simrad GO5 chartplotter and Lowrance Point-1 GPS/Glonass receiver. At the same time, the shorelines of the lakes were revised. Average distance between profiles was ~10 m and depth measurement accuracy up to 2–5 cm. Accuracy of water surface elevation measurement using GNSS receiver Topcon Hiper SR up to 1–2 cm. Later, detailed (0.5 × 0.5 m) digital lake bottom models (DEM) were developed, bathymetric plans of the lakes were created, the main morphometric features were calculated, the boundaries and area of the lake catchments were defined, and the physical-geographical characteristics of the lakes were described based on field observations and various data. Gelionys and Žaliasis are small lakes of glaciokarst origin. Gelionys Lake is oval-shaped while shape of Žaliasis Lake is closer to the circle. Despite small surface area the lakes are quite deep. According to survey data, the surface area of Gelionys Lake is 4.79 ha, water surface elevation 216.1 m a.s.l., maximum depth 19.8 m, mean depth 6.0 m, volume 288.3 thousands m3, catchment area 71 ha. The surface area of Žaliasis Lake is 2.14 ha, water surface elevation 120.9 m a.s.l., maximum depth 15.84 m, mean depth 5.7 m, volume 122.2 thousands m3, catchment area 60 ha. During the observation period (from May of 2018 to September of 2020), the annual amplitude of water level fluctuations in Gelionys Lake reached up to 0.47 m, and in Žaliasis Lake up to 0.33 m. Keywords: Gelionys, Žaliasis, glaciokarst, lake, bathymetric chart, morphometry, Lithuania, Aukštadvaris Regional Park.

Calibrating 1D hydrodynamic river models in the absence of cross-sectional geometry: A new parameterization scheme

Hydrodynamic modeling has been increasingly used to simulate water surface elevation which is important for flood prediction and risk assessment. Scarcity/inaccessibility of in-situ bathymetric information has hindered hydrodynamic model development at continental-global scales. Therefore, river cross-section geometry has commonly been approximated using highly simplified generic shapes. However, strong correlations appear between cross-section shape parameters and hydraulic roughness in a hydraulic inversion approach. This study introduces a novel parameterization of 1D hydrodynamic models that reduces ambiguity by combining cross-section geometry and roughness into a conveyance parameter. Flow area and conveyance are expressed as power-law functions of flow depth, and thus are assumed to be linearly related in log-log space at reach scale. Data from a wide range of river systems show that the linearity approximation is globally applicable. Because the two are expressed as power-law functions of flow depth, no further assumptions about channel geometry are needed. Therefore, the hydraulic inversion approach allows for calibrating flow area and conveyance curves in the absence of bathymetry and hydraulic roughness. Its feasibility and performance are illustrated using satellite observations of river width and water surface elevation.

Morphodynamic stability and characteristic length scales of bifurcations and confluences loops

<p>The morphodynamics of multi-thread fluvial environments like braided and anastomosing rivers is fundamentally driven by the continuous concatenation of channel bifurcations and confluences, which govern the distribution of flow and sediment among the different branches that are reconnecting further downstream. Almost all studies performed to date consider the two processes separately, although they frequently appear as closely interconnected. In this work, we tackle the problem of analyzing the coupled morphodynamics of such bifurcation-confluence systems by studying the equilibrium and stability conditions of a channel loop, where flow splits into two secondary anabranches that rejoin after a prescribed distance. Through the formulation of a novel theoretical model for erodible bed confluences based on the momentum balance on two distinct control volumes, we show that the dominating anabranch (i.e. that carrying more water and sediment) is subject to an increase of the water surface elevation that is proportional to the square of the Froude number. This increase in water surface elevation tends to reduce the slope of the dominating branch, which produces a negative feedback that tends to stabilize the bifurcation-confluence system. A linear analysis of the coupled model reveals that the stabilizing effect of the confluence depends on the ratio between the length of the connecting channels and the average water depth, independently of the channel slope and Froude number. Furthermore, the effect of the confluence is potentially able to stabilize the channel loop in conditions where the classic stabilizing mechanism at the bifurcation (i.e. the topographical effect related to the gravitational pull on the sediment transport) is very weak, as expected when most of the sediment is transported in suspension. The identification of a characteristic length scale that produces a coupling between the confluences and bifurcations opens intriguing possibilities for interpreting the self-adjustment of the planform scale of natural multi-thread rivers.</p>

The FLOod Probability Interpolation Tool (FLOPIT): A Simple Tool to Improve Spatial Flood Probability Quantification and Communication

Understanding flood probabilities is essential to making sound decisions about flood-risk management. Many people rely on flood probability maps to inform decisions about purchasing flood insurance, buying or selling real-estate, flood-proofing a house, or managing floodplain development. Current flood probability maps typically use flood zones (for example the 1 in 100 or 1 in 500-year flood zones) to communicate flooding probabilities. However, this choice of communication format can miss important details and lead to biased risk assessments. Here we develop, test, and demonstrate the FLOod Probability Interpolation Tool (FLOPIT). FLOPIT interpolates flood probabilities between water surface elevation to produce continuous flood-probability maps. FLOPIT uses water surface elevation inundation maps for at least two return periods and creates Annual Exceedance Probability (AEP) as well as inundation maps for new return levels. Potential advantages of FLOPIT include being open-source, relatively easy to implement, capable of creating inundation maps from agencies other than FEMA, and applicable to locations where FEMA published flood inundation maps but not flood probability. Using publicly available data from the Federal Emergency Management Agency (FEMA) flood risk databases as well as state and national datasets, we produce continuous flood-probability maps at three example locations in the United States: Houston (TX), Muncy (PA), and Selinsgrove (PA). We find that the discrete flood zones generally communicate substantially lower flood probabilities than the continuous estimates.