Application of Basic Excel Programming to Linear Muskingum Model for Open Channel Routing

Flood routing as the process of determining the reservoir stage, storage volume of the outflow hydrograph corresponding to a known hydrograph of inflow.  It is viable technique for determining the flood hydrograph at a section of a river by utilizing the flow data at one or more upstream sections. It can be hydraulic and hydrologic. Some hydrological routing techniques include Muskingum method, Muskingum-Cunge method, Lag method and Kalinin-Milyukov method while many sophisticated computer programs like Matlab had been deployed for river routing.Muskingum Method for stream routing was considered by using spreadsheet for. Coefficients were determine using various hydrologic data and formula for the Muskingum method. A popular data with other three data sets were considered in a linear model. The value of k and x was calculated using the basics of Microsoft Excel cell programming. Analysis of variance (One- way) was performed to detect any significant difference in the methods compared with other study without basics of excel.The result shows no significant difference with the values computed in this present study, limitations of Muskingum method were highlighted and further research the subject is recommended. Keywords: Flood routing, hydrograph, Muskingum method, hydraulic, hydrologic

Penggabungan Metode 0\u27 Donnel Dan Muskingum-Cunge Untuk Penelusuran Banjir Pada Jaringan Sungai

Muskingum method of flood routing has some weaknesses. First, to define the value of routing parameters (Cd are difficult and require upstream and downstream hydrographs at the same time. Second, the lateral inflow has not yet been included. Cunge (/969) developed modification of Muskingum method by adding the physical aspect of stream, therefore it only requires upstream hydrograph. It is also not consider the lateral inflow. O\u27Donnel (1985) developed another modification of Muskingum method to get Ci value by matrix system and add the lateral inflow. Khan (1993) developed another modification Muskingum method on the stream with some branch, without considering the location of the join between the main stream and the branch. The model in this research combines O\u27Donnel-Muskingum-Cunge methods that can be applied on river system with branches and only require upstream hydrograph. The model is tested through historical data of Goseng catchment area and the result is satisfactory

Evaluation of Regional-Scale River Depth Simulations Using Various Routing Schemes within a Hydrometeorological Modeling Framework for the Preparation of the SWOT Mission

The Surface Water and Ocean Topography (SWOT) mission will provide free water surface elevations, slopes, and river widths for rivers wider than 50 m. Models must be prepared to use this new finescale information by explicitly simulating the link between runoff and the river channel hydraulics. This study assesses one regional hydrometeorological model’s ability to simulate river depths. The Garonne catchment in southwestern France (56 000 km2) has been chosen for the availability of operational gauges in the river network and finescale hydraulic models over two reaches of the river. Several routing schemes, ranging from the simple Muskingum method to time-variable parameter kinematic and diffusive waves schemes, are tested. The results show that the variable flow velocity schemes are advantageous for discharge computations when compared to the original Muskingum routing method. Additionally, comparisons between river depth computations and in situ observations in the downstream Garonne River led to root-mean-square errors of 50–60 cm in the improved Muskingum method and 40–50 cm in the kinematic–diffusive wave method. The results also highlight SWOT’s potential to improve the characterization of hydrological processes for subbasins larger than 10 000 km2, the importance of an accurate digital elevation model, and the need for spatially varying hydraulic parameters

River network routing on the NHDPlus dataset

International audienceThe mapped rivers and streams of the contiguous United States are available in a geographic information system (GIS) dataset called National Hydrography Dataset Plus (NHDPlus). This hydrographic dataset has about 3 million river and water body reaches along with information on how they are connected into net- works. The U.S. Geological Survey (USGS) National Water Information System (NWIS) provides stream- flow observations at about 20 thousand gauges located on theNHDPlus river network.Ariver networkmodel called Routing Application for Parallel Computation of Discharge (RAPID) is developed for the NHDPlus river network whose lateral inflow to the river network is calculated by a land surface model. A matrix-based version of the Muskingum method is developed herein, which RAPID uses to calculate flow and volume of water in all reaches of a river network with many thousands of reaches, including at ungauged locations. Gauges situated across river basins (not only at basin outlets) are used to automatically optimize the Muskingum parameters and to assess river flow computations, hence allowing the diagnosis of runoff com- putations provided by land surfacemodels.RAPIDis applied to theGuadalupe and SanAntonioRiver basins in Texas, where flow wave celerities are estimated at multiple locations using 15-min data and can be reproduced reasonably with RAPID. This river model can be adapted for parallel computing and although the matrix method initially adds a large overhead, river flow results can be obtained faster than with the traditionalMuskingummethod when using a few processing cores, as demonstrated in a synthetic study using the upper Mississippi River basin

An Analysis of MLR and NLP for Use in River Flood Routing and Comparison with the Muskingum Method

River, Estuarine and Coastal Dynamic

Flood Routing Based on Diffusion Wave Equation Using Lattice Boltzmann Method

AbstractOne-dimensional diffusion wave equation is a simplified form of the full Saint Venant equations by neglecting the inertia terms. In this study, the Lattice Boltzmann method for the linear diffusion wave equation was developed. In order to verify the calculation accuracy of it, the analytical solution and Muskingum method were also introduced. Excellent agreement was obtained between observed data and numerical prediction. The results show that the Lattice Boltzmann method is a very competitive method for solving diffusion wave equation in terms of computational efficiency and accuracy

Determination of lateral inflows in the Kuparuk River watershed, a study in the Alaskan Arctic

Thesis (M.S.) University of Alaska Fairbanks, 2015The objectives of this research were to investigate the relationships between lateral inflows and watershed characteristics within the Kuparuk watershed of Arctic Alaska, as well as to quantify the lateral inflows to be used as an input for calibrating and running a process-based instream water temperature model. Determination of lateral inflows was accomplished by constructing hydrographs at multiple locations along Imnavait Creek and the Kuparuk River using stage and discharge field measurements. The hydrographs were then routed between gauging stations downstream (starting upstream) using the Muskingum routing method; and finally subtracting the routed hydrograph from the downstream measured hydrograph to calculate any additional water that had entered the reach between gauging stations. Results showed, as a general trend, that reaches within the northern foothills of the Brooks Range experienced larger lateral inflow contributions per square kilometer and had larger runoff ratios than subsequent reaches to the north where the terrain flattens out and transitions into the coastal plain. Two reaches within the watershed contradicted the general trend. The low-gradient reach nearest to the Arctic Ocean experienced larger lateral inflows throughout the summer that were unaffected by rainfall precipitation events; this is believed to be caused by snowmelt water initially stored in the low gradient terrain and slowly released into the drainage network during summer months. This area is rich with wetlands, ponds, and lakes and snow-damming during break up is prevalent. The other reach was located upstream of the Kuparuk aufeis field and was observed to lose water during the summer of 2013, supporting a hypothesis that the aufeis formation in this area is fed throughout the winter by a large talik upstream

River discharge simulation using variable parameter McCarthy–Muskingum and wavelet-support vector machine methods

In this study, an extended version of variable parameter McCarthy–Muskingum (VPMM) method originally proposed by Perumal and Price (J Hydrol 502:89–102, 2013) was compared with the widely used data-based model, namely support vector machine (SVM) and hybrid wavelet-support vector machine (WASVM) to simulate the hourly discharge in Neckar River wherein significant lateral flow contribution by intermediate catchment rainfall prevails during flood wave movement. The discharge data from the year 1999 to 2002 have been used in this study. The extended VPMM method has been used to simulate 9 flood events of the year 2002, and later the results were compared with SVM and WASVM models. The analysis of statistical and graphical results suggests that the extended VPMM method was able to predict the flood wave movement better than the SVM and WASVM models. A model complexity analysis was also conducted which suggests that the two parameter-based extended VPMM method has less complexity than the three parameter-based SVM and WASVM model. Further, the model selection criteria also give the highest values for VPMM in 7 out of 9 flood events. The simulation of flood events suggested that both the approaches were able to capture the underlying physics and reproduced the target value close to the observed hydrograph. However, the VPMM models are slightly more efficient and accurate, than the SVM and WASVM model which are based only on the antecedent discharge data. The study captures the current trend in the flood forecasting studies and showed the importance of both the approaches (physical and data-based modeling). The analysis of the study suggested that these approaches complement each other and can be used in accurate yet less computational intensive flood forecasting

Numerical approaches to flood routing in rivers

Flood routing is commonly used to calculate the shape of the flood hydrograph at the downstream end of a reservoir or a river reach, if the flood hydrograph at the upstream end of the reach is known. The flood routing procedure also enables prediction of the time at which the flood will occur at the downstream station. One of the methods of flood routing which has been widely applied in engineering practice because of its simplicity and accuracy is the Muskingum method. This method is based on the assumption of a linear algebraic relationship between inflow I, outflow Q and storage S in a reach. The equation used is basically and numerically derived from the differential equation of continuity or conservation of mass. As mentioned above, flood routing normally involves the use of an upstream hydrograph to estimate a downstream hydrograph, an example is estimating the flood hydrograph at the downstream end of a river reach. An estimate of the upstream hydrograph from the recorded flood hydrograph at the downstream end is sometimes required. This case is less common, but still significant. For example, it can be needed to fill in missing records using those at a downstream station. This reverse routing equation, mathematically, can be deduced easily from the conventional Muskingum equation, i.e.: re-arranging the Muskingum equation to solve for inflow I given outflow Q. Difficulties often arise, since the process is numerically unstable. This numerical instability can cause the process to diverge from the true solution or oscillations to occur in the calculated upstream hydrograph. In practice, satisfactory upstream hydrographs cannot be obtained. This project is intended to investigate that problem, to determine the cause of the numerical instability and to develop some alternative approaches which can overcome the problem. Several methods of solution were investigated, including an iterative approach combined with a smoothing and averaging algorithms. Results using this method show that the numerical instability can be overcome by selecting an appropriate time step (routing period), which has been shown to depend on the values of the Muskingum model parameters. The solution converges rapidly because of the use of the averaging algorithm, and accurate estimates of the upstream hydrograph are obtained. It can be said that this method has the same order of accuracy as the conventional downstream routing using the Muskingum method

Real Time Flow Forecasting in a Mountain River Catchment Using Conceptual Models with Simple Error Correction Scheme

[EN] Methods in operational hydrology for real-time flash-flood forecasting need to be simple enough to match requirements of real-time system management. For this reason, hydrologic routing methods are widely used in river engineering. Among them, the popular Muskingum method is the most extended one, due to its simplicity and parsimonious formulation involving only two parameters. In the present application, two simple conceptual models with an error correction scheme were used. They were applied in practice to a mountain catchment located in the central Pyrenees (North of Spain), where occasional flash flooding events take place. Several relevant historical flood events have been selected for calibration and validation purposes. The models were designed to produce real-time predictions at the downstream gauge station, with variable lead times during a flood event. They generated accurate estimates of forecasted discharges at the downstream end of the river reach. 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