Application of HEC-HMS Model for Flow Simulation in the Lake Tana Basin: The Case of Gilgel Abay Catchment, Upper Blue Nile Basin, Ethiopia

Abstract

Understanding the complex relationships between rainfall and runoff processes is necessary for the proper estimation of the quantity of runoff generated in a watershed. The surface runoff was simulated using the Hydrologic Modelling System (HEC-HMS) for the Gilgel Abay Catchment (1609 km2), Upper Blue Nile Basin, Ethiopia. The catchment was delineated and its properties were extracted from a 30 m × 30 m Digital Elevation Model (DEM) of the Lake Tana Basin. The meteorological model was developed within HEC-HMS from rainfall data and the control specifications defined the period and time step of the simulation run. To account for the loss, runoff estimation, and flow routing, Soil Conservation Service Curve Number (SCS-CN), Soil Conservation Service Unit Hydrograph (SCS-UH) and Muskingum methods were used respectively. The rainfall-runoff simulation was conducted using six extreme daily time series events. Initial results showed that there is a clear difference between the observed and simulated peak flows and the total volume. Thereafter, a model calibration with an optimization method and sensitivity analysis was carried out. The result of the sensitivity analysis showed that the curve number is the sensitive parameter. In addition, the model validation results showed a reasonable difference in peak flow (Relative Error in peak, REP = 1.49%) and total volume (Relative Error in volume, REV = 2.38%). The comparison of the observed and simulated hydrographs and the model performance (NSE = 0.884) and their correlation (R2 = 0.925) showed that the model is appropriate for hydrological simulations in the Gilgel Abay Catchment.

The Role of the Spatial Distribution of Radar Rainfall on Hydrological Modeling for an Urbanized River Basin in Japan

“…Control specifications are designed to control the time interval of the simulation of any event. The details of the model structures are given in the technical reference manual [37] and the user's manual [39] of the HEC-HMS, which has been used for a variety of analysis and engineering studies due to its flexibility and applicability in other regions to simulate rainfall-runoff processes [5,[17][18][19][20]22,23,[40][41][42][43][44][45][46]. The model looks applicable for predicting hydrological responses using radar rainfall during extreme storm events over Japanese river basins [19,20].…”

“…We used 10-m digital elevation model data downloaded from the website of the Geological Survey Institute. Different methods have been applied to calculate runoff volume, surface runoff, and base flow in the simulations in previous studies [5,[17][18][19][20][40][41][42][43][44][45][46]. Each method has its advantages and disadvantages.…”

“…The Muskingum-Cunge standard method was used to simulate flow in open channels, and the exponential recession method was selected for modeling base flow. The mathematical explanations for each method have been described in previous studies [5,[17][18][19][20]37,38,[40][41][42][43][44][45][46], and the processes followed are described in the HEC-HMS quick guide [39]. Therefore, because we selected various methods for use in each part of the model set-up for the basin, we had to set the initial conditions of the key parameters for each method before conducting the simulations.…”

“…High-resolution land-use data show that the basin is mainly dominated by urban areas, but includes forests, bare land, and small areas of paddy fields (Figure 4). These land-use and soil-type datasets are generated from different sources and have been used in the HEC-HMS m odel in many studies [5,17,[18][19][20][40][41][42][43][44][45][46]. The two datasets were considered in the creation of the SCS CN at each grid of the selected basin.…”

“…The optimizations of parameters have been done in different ways in several studies. In some studies, optimizations of the parameters are fixed for each event case [41][42][43], while in other studies they are fixed for all events [19,[44][45][46]. Of course, parameters can be optimized for single events first, and they can then be applied to other selected events.…”