Flood Hydrograph Analysis Through Employing Physical Attributes Using Two and Multiple Variables Regression Factor and Cluster Analysis

Document Type: Research Paper


1 Associate Professor, University of Tehran, Karaj, Iran

2 Academic Staff, University of Jiroft, Jiroft, Iran

3 Emeritus Professor, University of Tehran, Karaj, Iran

4 Associate Professor, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran


Since direct experimental evidence is not available, this must be verified through a modeling approach, provided
adequate data be available. Many statistical methods are used to study the relation between independent and
dependent variables.This research was carried out at the western part of Jazmurian basin tlocated in the southeast of
Iran. In this paperused ten physical characteristics such as area (A), perimeter (Pr), average elevation of basin (av.e),
average slope (av.s), gravelious coefficient (G), length of main stream (L), pure slope of main stream (P), length of
output to one point equivalent center of basin (Lc), Time of concentration (Tc) and lag time( Tl) as independent
variables and nine hydrograph component such as Qp, Q25, Q50, Q75, Tp, T25, T50, T75 and Tb as dependent
variables.We investigate flood hydrograph through the physical attributes using two and multiple variables regression
factor and cluster analysis.With the data of twelve hydrometric stations. Normality test was done using Kolmograph-
Smironov. After using four mentioned methods and with the use of modeling, the relations between dependent and
independent variables weres defined. The evaluation of hydrologic model behavior and performance is commonly
made and reported through comparisons of simulated and observed variables. Frequently, comparisons are made
between simulated and measured stream flow at the catchments outlet. Significant models have correlation coefficient
bigger than 0.325 at 0.01 significant level and higher than 0.250 at 0.05 significant levels. Three criteria such as root
mean square error (RMSE), relative error (RE) and coefficient of efficiency (CE) were used for selecting the ultimate
models. The results revealed that with the use of physical characteristics of the basin we can determine the synthetic
hydrograph. The results also showed that the two- variable models have higher efficiency in estimating the discharge
variables of the simulated hydrographs. After the cluster analysis for group in which are more station s, it results in
more significance of the model than one whose group included less stations.