The Improvement of Synthetic Unit Hydrograph Performance by Adjusting Model Parameters for Flood Prediction I Gede Tunas #1 , Nadjadji Anwar #2 and Umboro Lasminto #3 #1,2,3 Department of Civil Engineering, Institut Teknologi Sepuluh Nopember (ITS) Surabaya 60111, Indonesia #1 Department of Civil Engineering, University of Tadulako, Palu 94118, Indonesia 1 tunasw@yahoo.com; 2 nadjadji@gmail.com; 3 umboro_hydro@yahoo.com Abstract—One of the important factors in water resources management is the determination of design flood associated with determining the size, capacity and age of the water resources structures to be built. Determination of design flood can be done in various ways, one of which is very popular to date is discharge prediction using synthetic unit hydrograph (SUH) approach. The use of unit hydrograph models has been widely applied in various parts of the world, especially in Indonesia, some of which are Snyder, Nakayasu, GAMA I and ITB-1. These methods are considered to have a good performance because it has to accommodate the characteristics of watersheds in a model parameter that greatly contributed to the process of rainfall-runoff transformation. However, in some cases it also provides a sizeable deviation, especially in Indonesia, considering that watersheds in Indonesia have different characteristics with watersheds in the United States where Snyder Unit Hydrograph developed. To overcome these problems, the unit hydrograph performance must be improved so that it can be used in various watersheds to obtain the smallest deviations. This research was conducted in 8 watersheds located in Central Sulawesi Province, Indonesia. This study aimed to improve the performance of Snyder Unit Hydrograph Model, covering Snyder, Nakayasu, SCS, GAMA I, ABG and ITB-1. The improvement of model performance was conducted by adjusting model parameters, in this case using Solver Tool on Microsoft Excel. Evaluation was done by the error indicator such as coefficient of Nash-Sutcliffe model efficiency (E). The study result showed that model parameter adjustment could decrease a deviation of SUH model parameter for peak discharge and average peak time up to 30% and could increase Nash– Sutcliffe Model Efficiency Coefficient (E) up to over 80%. The decrease of a deviation of SUH model parameter and the increase of E coefficient revealed that optimization using solver facility was effectively undertaken. However, not all deviations decreased but even increased significantly after optimization. It happened because the process of parameter optimization occurred simultaneously, and it was only based on a purpose function by maximizing Nash–Sutcliffe Model Efficiency Coefficient (E). The adjustment in this coefficient caused the increase or decrease of a parameter deviation of SUH Model depending on E value achieved on the optimization process. Overall, it could be declared that the decrease of a parameter deviation of SUH model was accompanied by the increase of Nash–Sutcliffe Model Efficiency Coefficient (E). Keywords : performance improvement, synthetic unit hydrograph, model parameters, flood prediction I. INTRODUCTION One of the important factors in water resources management and planning was flood discharge estimation functioned to determine optimum discharge size associated with dimension and a life of structures. The aim of optimum flood discharge estimation was to plan structures which did not have over a dimension (over estimated) implying on the big cost of structures or too small dimension (under estimated) causing a bigger risk of structure failures. One method that could be deployed to predict flood discharge was a hydrograph base. This method had been widely used either in overseas or in Indonesia as it was assumed to be able to imitate flood behavior from the beginning up to the end of the flood in a hydrograph format. Some of hydrograph bases particular a synthetic unit hydrograph commonly used in Indonesia, among others, were Snyder, Nakayasu, SCS, GAMA I, ABG and ITB-1. However, in some cases, these methods had obvious weaknesses because they could produce bigger deviation resulting in discharge size. Therefore, these method performances needed to be improved by adjusting their model parameters using optimization. Optimization was a procedure to maximize or minimize purpose function by changing a constraint function so that optimum value parameters could be determined. This study became very important as on 8 observed watersheds as objects of the study did not have a guidance used for references how to predict flood with the best performance. The best way produced from the optimization process was expected to be references for flood prediction, particularly in Central Sulawesi Province – Indonesia. ISSN (Print) : 2319-8613 ISSN (Online) : 0975-4024 I Gede Tunas et al. / International Journal of Engineering and Technology (IJET) DOI: 10.21817/ijet/2017/v9i2/170902163 Vol 9 No 2 Apr-May 2017 847