Abstract:
Water resource managers have undertaken comprehensive rainfall-runoff hydrologic studies
to model the hydrological response in many regions around the world to meet different
desirable needs with the goal of efficient and proper planning and management of water
resources for present and future uses. However, such research does not pay enough attention
to the Hanger watershed, Abbay basin, Ethiopia, which may be affected by water insecurity.
Therefore, the main objective of this study was to simulate rainfall-runoff processes and
analysis using Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) for
the Hanger watershed to see if the model works well in this study field. The input data used
were the meteorological data, spatial data and, hydrological data obtained from the National
Meteorological Service Agency and the Ministry of Water, Irrigation and Energy, respectively.
The missing value of precipitation data was filled using the normal ratio method, and the
consistency of data was checked using a double mass curve. Hydrologic Engineering Center Geospatial Hydrologic Modeling System (HEC- GeoHMS) used for each sub-basin; the curve
number was generated using DEM, land use land cover data, and soil data, and prepare basin
model imported to HEC-HMS. The SCS-CN loss, SCS unit hydrograph, Constant monthly, and
Muskingum methods are used to measure precipitation loss modeling, transform modeling,
base flow modeling, and flood routing. For model calibration (1990-2009) and validation
(2010-2014), hydro-meteorological data were used. The parameters used to evaluate the
models' sensitivity were; curve number, initial abstraction, basin lag, Muskingum k, and
Muskingum x. The results show that the model was most sensitive to Muskingum (K) and
Muskingum (x), but Muskingum k is more sensitive than Muskingum x for this study. During
the calibration and validation phase, the performance of the model was assessed by Nash Sutcliffe Efficiency (NSE), Root means square error (RMSE), Coefficient of determination (R2
),
Percent bias (PBIAS), Percent error in volume (PEV), and Percent error in peak flow (PEPF),
indicating NSE (0.702), R2
(0.7143), RMSE (0.5), PBIAS (-2.04%), PEV (2.035), and PEPF
(8.764) and NSE (0.707), R2
(0.743), RMSE (0.5), PBIAS (14.61%), PEV (14.58), and PEPF
(8.15), respectively. The simulated and observed peak discharges differed by 91.2 m3/s in
calibration time. This indicates that the peak discharge was well predicted. In the validation
period, there was a difference of 79.9 m3/s between the observed and simulated peak
discharge. This means that the peak discharge was slightly lower than expected. For this study,
calibrated and validated model results showed that the model performed well. Flood prediction
was conducted in the HEC-HMS using 24-hour rainfall depth of 2, 5,10, 25, 50,100, and 200
years return period and found to be 608.4 m3
/s, 967.2 m3
/s, 1225.2 m
3
/s, 1565.9 m3
/s, 1830.6
m
3
/s, 2103.2m
3
/s, and 2382.7 m3
/s, respectively. Also using the General extreme value of the
Statistical flood frequency analysis, the peak flow discharge for 2,5,10,25,50,100 and 200 year
return period were 600.7m3
/s, 895.8 m
3
/s, 1180.6 m
3
/s, 1394.9 m
3
/s, 1772.3 m
3
/s, 1962.5 m
3
/s,
and 2243 m
3
/s, respectively. The minimum and maximum peak flow records in HEC-HMS were
608.4 m3
/s and 2382.7 m3
/s, respectively. Therefore, these predicted values will aid future
researchers in creating a flood inundation map and taking appropriate flood-control measures
for the study area.