Hydrological Flood Routing in Rivers

Transcription

1 International Research Journal of Applied and Basic Sciences 201 Available online at ISSN X / Vol, 4 (10): Science Explorer Publications Hydrological Flood Routing in Rivers V. Fasahat 1, A. Honarbakhsh *2, H. Samadi, S.J. Sadatinejad 4 1. M.sc Student of Watershed Management Engineering, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran 2. Assistant professor of Watershed Management Engineering, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran. Assistant professor of Water Engineering, Faculty of Agriculture, Shahrekord University, Shahrekord, Iran 4. Associated professor of Watershed Management Engineering, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran *Corresponding Author afshin.honarbakhsh@yahoo.com ABSTRACT: flood routing is an important part of flood management. Although hydraulic models are commonly employed in the routing studies, hydrological models offer more effective and suitable methods in this matter. Muskingum model is a commonly used hydrological model in this type of studies, which its accuracy depends on the way the coefficients of the corresponding equation (k, x) are obtained. In this research, using statistical data for the 90 km 2 area jooneghanfarsan watershed at chaharmahal & bakhtiyari province, hec-hms model and the recorded flood hydrographs at the local hydrometric station, the effectiveness of the muskingum model in the flood routing has been investigated. The results on the studied floods show little change in the amount of k and x, found to be 1.9 hour and 0.05 for the watershed. Key words: Routing, Muskingum Method, HEC-HMS, Jooneghan-Farsan Watershed. INTRODUCTION Flood is a natural phenomenon that human societies have accepted it as an inevitable event. Flood is defined as a condition in which stream flow unexpectedly is increased so as to cause financial and fatal damage (Abbasi, 2005). Hydrological issues, particularly those concerning the prevention and control of floods, have been discussed for years in the world which indicates how important it is. Nevertheless, considering this issue may focus more on application of logical and improper principles to better control of this phenomenon. The main concept of flood routing is that if there are hydrographical specifications in a point of a river, how one might estimate the hydrograph in another point in the downstream. This subject is important specially where agricultural lands located in downstream. Certainly, hydrographs of these two points may are not identical; because the specifications of the rout water is passing or is flowing in can change the shape of hydrograph. Basically routing is based on nonlinear correlation between reservoir and flow (Gill, 1978). In general, wide studies have been done regarding the flow routing in rivers (Chow,1988; Delphi,2012; Karahan, 2009; Sturm, 2010). Hence, Convex Routing method, modified Att-Kin Method and Muskingum method are methods with highest application. In addition, since the principle of each three methods is based on the continuous flow equation, their obtained results are not so different from each other. However, given the previous studies and current data from the area, Muskingum method was used for flood routing in the study area (Safavi, 2006). Hydraulic Engineering center (HEC) models were prepared by the Hydraulic Engineering Center of U.S. Army. The hydraulic HEC-HMS model is usable based on the rainfall-runoff simulation in basins using high-graphical capabilities for reservoir overflow and flood hydrology designs and etc. HEC-HMS is a rainfall-runoff model allows calibrating some models such as Clark, Snyder, SCS, HU and kinematic-wave model (Moosavinadooshani&Danandeh-mehr, 2005). Application and reviewing the HEC-HMS model in river engineering was investigated in Kor and Sivand region in Fars Province. This model was used for calculating the runoff, river routing and reservoir. Several methods can be used for flood routing in the rivers which Muskingum method was used due to its simplicity and data availability. For implementation of the model, all the required data were used such as hydraulic specifications, and reservoir. In initial review, there was a significant difference between the hydrographs obtained from the model and the observations. Therefore, the model was calibrated using the

2 available data. Finally, coordination of hydrographs obtained from the model showed their observational hydrographs. Therefore, the results showed that the calibrated model will be the best and closest result for routing. A study in Shiraz was done for routing the HEC-HMS model through genetic algorithm (GA) and PEST methods. Thus, a hypothetical and imaginary sphere was considered as square km including three subbasins. Some information such as area and a single hydrograph were used from the Muskingum method for the routing. The obtained results from the routing using the two mentioned methods showed that application of HEC-HMS model was more preferable with the GA than PEST, and the routing would have a better result. Therefore, the present study aimed to calculate the routed values K and X in Muskingum method in the study area using HEC-HMS in order to use the present research method for identical areas and regions. MATERIALS AND METHODS Study Area Chaharmahal Bakhtiary province is located in 1º9-2 º48 in north latitude and 49 º 28-51º 25 in east longitude with 16,52 square kilometers. This province is located in central Zagros Mountain. The political location of this province compared with other provinces is as north and east to Esfahan, west to Khouzestan, south to KohkilouyeBoyerahmad and north to Lorestan. Jouneghan basin is in West and Southwest of Shahrekord (capital of Chaharmahal Bakhtiary). The highest point is related to Saldoran Heights with 621 meters and the lowest point is in the outlet of Jounghan River in Darkesh and Varkesh with 1980 meters. The area of Jouneghan-Farsan basin is 90 square kilometers in the outlet of the plain and its sub-basins are Soureshjan basin (71 kilometers) and Jouneghan-Farsan basin (52 kilometers). In addition, geographically this basin is located in a mountainous area. Soureshjan basin possesses a river called Gargak encompassed from several branches such as Ab Dare Sid, Ab Dareh Mayk and Fath Abad and in the outlet of the plain is divided into several rivers such as Chelicheh and Pardenjan. Gargak River is joined to the Jouneghan River after feeding the areas at the left side of the field. Jouneghan River mostly comes from the Saldoran Heights and after measuring in Babaheidat Station (it is called Sarab River in this point) it will reach to Jouneghan plain for agricultural use. Numerous high water springs and rivers can feed the Sarab River on the way downstream such as Pirghar spring (DehCheshmeh) and SarabYekan. This river is located on the end of basin to the DarkeshVarkesh and there is a hydrometric station with the same name. In other words, the study output of watershed basin is the same place (Figure 1). Figure 1. The location of hydrometric stations and main drainage of the Jouneghan-Farsan basin Physiographical characteristics of the area Today, there is much software that can obtain physiographical specifications of an area. In this study, the required specifications were calculated in Software ILWIS version.4 (Table 1). Table 1. Summary of physiographical characteristics in the study basin at the output location Hydrometric Station Area(km^2) CN S(in) L (m) L (ft) Y(%) TL(hr) TL(min) TC(hr) TC(min) DarkeshVarkesh

3 Methods Applied hydrometric stations in this study are two stations i.e. Tang Pardenjan in the output of Soureshjan basin and DarkeshVarkesh station in the output of Jouneghan-Farsan basin, as the main stations of the study, and stations KuhSoukhteh and Behesht Abad were considered for data analysis and completing the data and their reliability. The stations of climatology network in the province and area are as synoptic, climatology, rain and evaporation measuring. Six stations were used for analyzing the rate of rainfall. Usually, 24-hour rainfall statistics are used; however most of 6-hour rainfalls are also needed. Therefore, the available statistics of weather stations were collected and were recompleted using the regression method. The most important weather station in the study area was Farsan Station; the maximum rate of 6 and 24-hour rain with different return periods are illustrated in Table 2. Such results were related to the normal statistical distribution which had a higher reliability than other distributions. These values have been calculated given the conversion factor of 24 and 6 hour precipitation in synoptic station of Shahrekord (as the only synoptic station close to the study area). Moreover, it is necessary that normal distribution of 6-hour rainfall is specified for SCS method and to do so the closest normal distribution of 6-hour rainfall in other words synoptic station of Shahrekord was used. Table 2. Maximum rainfall values for 6 and 24 hours in Farsan Station in different return periods Return period (year) Parameter hour maximum precipitation (mm) hour maximum precipitation (mm) Daily discharge statistics of hydrometric stations and 24-hour rainfall statistics were used to choose the required floods. Because, detailed statistics were not available in this area. Daily statistics of Soureshjan, Foroudgah, Kouhrang, Farsan and Dezak stations were used to determine the rainfall values. Index flood values of all the hydrometric stations were used for selecting the floods so as to observe them in all the stations of the area. Therefore, given the available statistics of hydrographs related to 1999 to 2007 were plotted. After plotting the annual hydrograph of each station, some hydrographs were selected to have maximum values in all the stations; so as to show a large and imminent flood in the area. Accordingly, over 20 large floods were obtained in the desired stations from 1999 to 2007, and for an accurate and case study 10 of them were extracted from 2001 to Since two stations (KuhSoukhteh and Behesht Abad) were out the area, obtained floods were justified from other stations with these two control stations and their flood certainty was confirmed. Extraction of Instantaneous hydrographs (1-hour) of the desired floods After determining the desired days, the statistics for instantaneous discharges (1-hour) of the desired floods were prepared from the available data and statistics stage related to the non-flood days using Limnograph. Each station in a specified time period had a regression given the correlation of stage and discharge which read numbers of Limonograph to discharge was used to do so. Other data such as delay time were obtained from Williams method for area with 167 square kilometers, minutes and area with 90 and 75 kilometers with and minutes. Then, using the Thiessen method in ILWIS Software version.4, the effective areas of each station was extracted and the rainfall related to the desired basin was calculated. The initial losses were calculated In HEC-HMS model with defining the sub-basin elements and junction with initial data of calibrated values (Table ). Flood CN Precipitation (mm) Table. Required data for simulation process Q Calibrated Initial peak (observed) Q peak(simulated ) Losses(mm) ( m / s) ( m / s) % Error ( Q peak ) S (mm) Coefficient Loss

4 Intl. Res. J. Appl. Basic. Sci. Vol., 4 (10), 01-05, 201 By implementing the outliers test (Mahdavi, 2005) and removing outlier data (1.19), the average of remained numbers obtained 0.24 whichh provided the optimal ratio of total losses in SCS formula for the study area. Then, the simulated floods were used for identifying the Muskingum coefficients. Calculating Muskingum coefficients of X and K In a study in South Africa, the routing parameters were generally done using calibrated hydrographs of output flow. Thus, the Muskingum method was obtained through the mutual effect of flow and reservoir. K and X coefficients can be identified in Muskingum linear equation using minimumm square method; however, this method requires much effort than the nonlinear one (Gill, 1978). Muskingum coefficients can be different for each flow and besides, the values of these coefficients have a close relationship with a shape similar to the hydrograph triangle of input flow; so thatt K coefficient was the space between the peak of input and output flow and X was also based on an equation from K (Overton, 1996). Three different forms of Muskingum routing formula were used with three series of variable parameters in open channels in China. The results showed that the accuracy of them have been higher than conventional Muskingum model. Muskingum method conducts routing of a river based on the discharge-reservoir correlation hydraulically i.e. by the use of continuity equation. Due to shortage of hydrometric stations, we had to divide the basin into two main upstream with 75 square kilometers and downstream with 167 square kilometers. Thus, the input hydrograph, output hydrograph from an imaginary basin with 75 square kilometers and output hydrograph and difference between the output hydrograph from sub-basinss with 90 and 167 square kilometers. Due to certain circumstance of desiredd basin and effect of other waterways, in HEC-HMS modeling for determining the output hydrograph in three models were prepared for 90, 75 and 167 square kilometers. Using the available maps, required physiographical characteristicss were prepared for every three models. Therefore, given the observational hydrographic, 10 flood events in desired basins were used to determine the Muskingum coefficients (Figure 2). Obtained CN values and initial losses for the total 90 square kilometers were true and due to data shortagess were used for two other basins as well. Figure 2. Sample of input and output values obtained in a flood event RESULTS The results showed that there was no significant difference between Muskingum coefficients obtained in all the 10 flood events and finally the obtained coefficients can be used as the optimized values for the desired area. Values of parameters K = 1.9 (hour), X 0.05 and t which weree considered equal to K/, value 0..6 was obtained using the Muskingum method. With implementing the modeling of the desiredd area regardless of dams, river routing and obtained coefficients for different return periods indicated the acceptable coefficients for this area (Figure ). Figure. Input and output hydrograph from the model using Muskingum coefficients in different return periods, coefficients A. 2 year, B. 50 year and C. 100 year.

5 By preparing some models from the HEC-HMS model for the desired basin which are with and without considering the Muskingum coefficients, it can be concluded that the result of river routing and obtained impact of coefficients are illustrated in this figure in available hydrographs (Figure 6). Figure 4. Impact of flood routing on output hydrographs in the study area in return period: A. 2 year, B. 50 year and C. 100 year. Discussion In general status, the obtained results from application of Muskingum model, showed appropriate and good application of this method for the river routing. This is similar to other results obtained from previous studies related to this method. In a study in South Africa, the routing parameters were done using calibrated hydrographs of output flow. Moreover, it was suggested that the accuracy of conventional Muskingum model was higher in routing of open channels. Given the obtained values for river routing processing based on previous studies, the best method was Muskingum. So that even in basins with insufficient statistics, Muskingum values of X and K can be reliably obtained. In addition, according to the researches, application of HEC-HMS model in Kor and Sivand in Fars Province indicated the application of this model for calculating the runoff and routing of river and reservoir. Moreover, obtained results in Shiraz from the calibrating of the two methods using the Genetic Algorithm and PEST model showed that application of HEC-HMS model had the best result for the calibrated model. Therefore, HEC-HMS software has a high potential in simulating the runoffrainfall process and hydrological analysis. As a result, given the implementation of above mentioned approaches in the desired basin using optimization, value of K was equal to 1.9 hours and value of X was 0.05 which can be utilized in further studies. Given the conducted study, following recommendations can be provided for better investigation of the subject. In addition with the Muskingum routing model, other methods such as Muskingum-Cunge can also be used and results can be compared together. In addition, for identifying the initial losses, it is better to review more floods which would have more accurate results and outcomes. REFERENCES Abbasi Z Study of Chamrood watershed Hydrogeomorphology characteristics and its effect on flood. Msc.Thesis. Islamic Azad University Najafabad Branch. Chow VT, Maidment DR, Mays LW Applied Hydrology. New York: McGraw Hill. Delphi M Application of characteristics method for flood routing (Case study:karun River), Journal of Geology and Mining Research, 4:8-12. Gill MA Flood routing by the Muskingum method, Journal of Hydrology. 6:5-6. Karahan H Predicting Muskingum flood routing parameters using spreadsheets. Computational Applications in Engineering Education, PP.1-7 Mahdavi M Applied hydrology,volume 2,Tehran University. Moosavi-nadooshani S, Danandeh-mehr A Hydrological modeling system HEC-HMS, Dibagaran-e-Tehran Artistic and Cultural Institute. Overton DE Muskingum flood routing of upland streamflow. Journal of Hydrology, 4: Safavi HR Engineering hydrology, Isfahan: Arkan. Sturm TW Open Channel Hydraulics, New York: McGraw Hill.