Evaluating the effect of check dams on flood peaks to optimise the flood control measures (Kan case study in Iran)

Transcription

1 Evaluating the effect of check dams on flood peaks to optimise the flood control measures (Kan case study in Iran) Reza. Roshani January: 2003

2 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Evaluating the effect of check dams on flood peaks to optimise the flood control measures (Kan case study in Iran) By REZA. ROSHANI Thesis submitted to the International Institute for Geo-information Science and Earth Observation in partial fulfilment of the requirements for the degree of Master of Science in Watershed and Environmental Management Degree Assessment Board Prof. A.M.J. Meijerink (Chairman Supervisor) WRS Department, ITC Dr. Ir. O.E. Seyhan (External Examiner) Free University, Amsterdam Dr. B. Saghafian (member-iranian supervisor) SCWMRC Tehran M.Sc.Ir. G.N. Parodi (member) WRS Department, ITC Ir. A.M. Van Lieshout (member) WRS Department, ITC INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION ENSCHEDE, THE NETHERLANDS

3 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Disclaimer This document describes work undertaken as part of a programme of study at the International Institute for Geo-information Science and Earth Observation. All views and opinions expressed therein remain the sole responsibility of the author, and do not necessarily represent those of the institute. Dedication

4 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK In the name of God To my kind mother My dear wife and my dear Amir Hossien Table of content

5 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Acknowledgement...I Abstract. II List of figures.. ΙΙΙ List of tables.. V 1. Introduction...VI 1.1 Motivation Conceptual framework Main research question Check dams 3 2. Study area General Physiography Time of concentration Vegetation cover Field observation NDVI Climatology Rainfall Rain gage stations Annual rainfall Daily rainfall Depth area method Depth area reduction Time distributed daily precipitation Runoff and precipitation Design storm and flood Flow routing Introduction to flow routing HEC-HMS model Convex routing method Input data preparation Results of convex method Applying Manning equations..30

6 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK 3.5 Comparing the results of convex method with observed hydrographs Check dam construction Check dam functionality Number of check dams Required material Decision making General objectives DEFINITE Introduction to DEFINITE DEFINITE input data DEFINITE output results Sensitivity analyses Conclusion and recommendations. 40 References List of figures

7 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Figure 1.1 Schematic view of supposed catchment....2 Figure 1.2 Schematic objective of research... 3 Figure 1.3 Schematic free body view of check dam...4 Figure 2.1 General position of Kan catchment within Iran. 5 Figure 2.2 Location of Kan catchment on topo map...6 Figure 2.3 Digital elevation model of Study area....7 Figure 2.4 Slope map of study area using DEM.. 7 Figure 2.5 Sub catchments and their main river positions...8 Figure 2.6 Longitudinal profiles of rivers in Kan catchment...8 Figure 2.7 Vegetation cover map of study area (Using NDVI map).11 Figure 2.8 Positions of selected rain gages on DEM of Kan.12 Figure 2.9 Annual recorded rainfalls of selected rain gage stations...13 Figure 2.10 Relation between altitude and rainfall amount in Kan Figure 2.11 Correlation coefficient of pairs of stations for annual rainfall in Kan catchment versus distance...14 Figure 2.12 IDF curve of Kan station (2.9 km away from study area) Figure 2.13 Correlation coefficient of maximum daily rainfalls of pair s stations versus distance of gages Figure 2.14 Interpolated (moving avg.) daily rainfall (mm) of 6-selected high rainfall in Kan catchment...17 Figure 2.15 Precipitation (as% of total catchment precipitation) as a function of area for six-selected maximum rainfall Figure 2.16 Regression line of 6 selected events in graph Figure 2.17 Depth-area reduction curve based on 6 selected high storms...18 Figure 2.18 Daily rainfall hydrograph of Solghan station ( )...18 Figure 2.19 Position of hydrometric station in Kan 19 Figure 2.20 Correspond rainfall- runoff hydrographs ( ) 19 Figure 2.21 Daily rainfall and runoff hydrographs in Solghan station in Solghan station.20 Figure 2.22 The best-fit curves for maximum discharge and rainfall..21 I Figure 3.1 Schematic basin model of Kan catchment in HMS model 23 Figure 3.2 Convex method Inflow hydrographs of Kan catchment 26 Figure 3.3 Convex routed outflow hydrographs of Kan catchment 26

8 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Figure 3.4 Effect of TC prolongation by 0.2hr on peak flood in Kan.27 Figure 3.5 Effect of TC prolonging on peak flood in Kan catchment.27 Figure 3.6 Effect of TC prolonging in Rendan River on peak flood...28 Figure 3.7 Effect of TC prolonging in Kiga River on peak flood 28 Figure 3.8 Simple schema of Rendan channel by constructing check dams.30 Figure 3.9 Inflow and outflow hydrographs in Rendan River by Manning equation Figure 3.10 Comparing the convex routed and observed hydrographs.. 32 Figure 4.1 Functionality of check dams for stream channel slope reduction...33 Figure 5.1 Result of multicriteria analysis for Kan flood control Figure 5.2 Sensitivity of ranking for cost and flood peak reduction criterions II List of tables

9 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Table 2.1 General physiographic characteristics of Kan catchment Table 2.2 Main rivers slopes of sub catchments of study area..10 Table 2.3 TC calculation results by different methods...10 Table 2.4 Probabilities and return periods relation..21 Table 3.1 Output of HMS for various slopes using Muskingum Cunge 24 Table 3.2 Input data in convex model Table 3.3 Flood peak variation based on slope reduction Table 4.1 Number of needed check dams to gain supposed slopes...34 Table 4.2 Characteristics of designed check dam Table 5.1 DEFINITE effect table of Kan flood control project Acknowledgements III This research would never have carried out without the contribution of many individuals and organizations, to which I have the pleasure of expressing appreciations and gratitude.

10 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK First of all I would like to extend my great appreciation to JIK director DR. Aminipouri who seriously managed and supported this joint program between Jihad of Agriculture, ITC, and Khajeh Nassir University of technology. I extent my gratitude to our sponsor, watershed management deputy of forests and rangelands organization. Especial thanks to my scholarly supervisors, Prof. Dr. A. Meijerink.I am deeply indebted to him for the stimulation that he provided during countless discussions, and for his remedy ideas on integrating a number of independent technologies and methodologies. Thank to my Iranian supervisor Dr.B. Saghafian, for his guidances during the data gathering and proposal writing in Iran. Thanks to all JIK staffs and members especially Dr.A.Abkar and Mrs.Darvishzadeh who did their best to hold this program. I would like to extend my best thanks to all the JIK students. It was a pleasure time to be with them during the course. I am very grateful to my dear friends, D.Afshar and M.Fatemiqumi for their moral support and friendship. I would particularly like to thank all the ITC staffs, manageres, employees, for their pleasure behaviors and kindness. ABSTRACT IV The recent flood events in Iran positively confirm that most regions are subject to cyclic destructive floods and the extent of damages is increasing.

11 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK The depth and spatial extent of floods in economical terms demands further research as a priority. Although many studies have concentrated on causes of floods, and these factors have been identified, but the suggested flood control measures just have been concerned within the sub catchments and the effect of those measures at the main outlet of catchment have been neglected. Stream gradient is one of the most important factors in flood acceleration, particularly in mountainous regions. Slope plays an important role in time of concentration (TC). Check dams, as most commonly used measures in watershed management extremely will affect the stream gradient and TC consequently. The effect of slope variation on peak flow was explored. The most effective slope is determined and feasible method for achieving this slope identified. In each case the peak flow reduction index is identified. This index is the most important factor in any decision-making process. GIS environment was used to delineate the boundaries of catchment and sub catchments. Using 100- meter contours a digital elevation model is created. Physiographic factors such as surface slope; longitudinal profiles of stream channels are calculated. HEC-HMS model was examined to route the rivers, which didn t simulate feasible results. Convex routing method is used to simulate the inflow and outflow hydrographs. This method of routing is most capable in such cases. Manning equation was used to calculate the peak flow after constructing check dams. The result of convex method and manning calculated peak flow was compared. A decision support system (Definite 2 soft ware) selects the most cost effective planning of check dams, which should be constructed within the streams. V

12 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK 1. INTRODUCTION 1.1. Motivation There are several natural disasters occurring throughout the world within the years. Floods in particularly cause huge losses to the human lives, property, infrastructure and natural resources as well. Iran is among several countries in the world, which faces severe problems of flood each year particularly in urban catchments. Tehran (capital city of Iran) is subject to serious flood dangers. For instance in 1987 a huge flood occurred in northern Tehran and caused a lot of damages and losses. Subsequent to this event, it was decided to implement a flood control project in north of Tehran, in the affected areas. Later on many check dams were constructed through the waterways to control the flood. It was a costly project of about 1 billion of tomans (about 1.2 million $.) At that time the planners didn t care about the cost of the project and they suggested constructing check dams in all of the tributaries to reduce the slope of those tributaries and consequently reduce the peak flood at the sub catchment s outlet. Later on it was debated whether check dams are the proper measures, and if so, to what extent? However, no study was done, and because of that reason, the present research will deal with the explained problem in one of the northern Tehran catchment named KAN. This catchment has the second priority of northern Tehran flood study. (By Jihad Technical Services Co. 1996). In this thesis I will try to find out how much flood peak reduction may occur to work out a feasible method and solution to optimise the cost and efficiency of the measures Conceptual framework A catchment is a system, which should be considered as a unit. Any changes in parts of catchment will affect the outflow of the total catchment. There are two major issues in dealing with floods in a stream network of a catchment: -Peak flow of each sub catchments with and without checks dams. -Delaying time of the hydrographs of those sub catchments The first issue is the lowering of the peak flow in a sub catchment by construction of check dams. But the second issue is not as clear as the first one. It means that the flood peak at the main outlet is not just the function of sub catchments peak hydrographs. Other factor, which mostly affects the peak flood of the whole catchment, is the delay time in arrival of the peak flows. If the peak of two different hydrographs arrive at the main outlet at the same time the peak flow will 1

13 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK be more than in the case when these two peaks reach to the main outlet at different times, as illustrated in figure 1.1 and 1.2. Figure 1.1 shows a typical catchment with two sub catchments. The rivers of these two sub catchments join each other and generate the main river of catchment. Figure 1.2 shows their corresponding hydrographs. Hyd 1b and Hyd 2 represents the corresponding hydrograph of river 1 and river 2 at sub catchments outlet. Hyd 3b is the total hydrograph of whole catchment. If by constructing check dams in sub catchment no.1, delay is achieved, (Hyd no.1a); the total hydrograph will be as Hyd 3a. As can be seen a reduction of peak flow in sub catchment is achieved due to construction of check dams. But there is an increase of peak flow at the main outlet. This is the point of interest for designing the flood control measures. If the planners had taken the point in account, this situation (flood peak increasing at main outlet) would not have occurred. The most important parameter is the delaying time of hydrographs due to construction of check dams. This aspect will be investigated in this thesis. Furthermore, the economic feasibility as an effective parameter in any engineering projects will be analysed. Figure 1.1 schematic view of supposed catchment 2

14 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Discharge Time Hyd 1b Hyd 2 Hyd3b Hyd 1a Hyd 3a Figure 1.2 Schematic objective of research 1.3. Main research questions The present research is being faced with two different aspects: a) Hydrologic aspect, which is extremely dealing with the concept of flood routing in the rivers and interaction of geometry of stream channel on the peak flood. In this phase the main question is what is the desirable slope to have the lowest peak flood at main outlet? The result of this phase will produce different alternatives regardless of any other considerations. b) Economical aspect, which is the most important parameter in project feasibility and efficiency. In this phase a cost- benefit analysis will be employed to select the most cost effective plans. This phase will answer the question Which alternative has the lowest cost-benefit ratio? 1.4. Check dams Over the years, different measures have been developed to control the floods.by applying these measures the flood peak will be retarded. Check dams are the mostly commonly used measures in flood control projects. Especially in some regions where, there are no proper sites for large dam construction. Check dams are low structures built across the stream perpendicular to the flow. In hydraulic engineering the most common use for check dams is to decrease the slope and reduce the flow velocity. The number of needed check dams, to provide the desirable slope, will be determined based on the project targets and its cost. Height of designed check dam will influence the number of check dams and the total cost of project. The higher the check dams, the less number of check dams is required. However, there is a limitation for the height of check dams. The height of check dams will be limited 3

15 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK by the effective upstream area, the depth of channel valley and type of check dams. For the gabion type this height can be about 5 meters. Type of check dams is widely influenced by the available materials in the project area. In stream gradient improvement, big rocks and boulders are needed. They can be provided from streambed. These boulders can be wrapped in a gabion mesh boxes to be used as check dam body. The main force, which will resist against the flood kinematic force and other active forces, is the check dam gravity force. That is why the gabion is used to make check dams. A gabion consists of units with typical dimensions of m which are tied to each other. The other advantage of gabion is its flexibility, which helps the check dam to remain stable even though the foundation has settled down. The height and geometry of check dams will be designed regarding the acting forces on the check dam. These forces are hydrostatic forces, soil active pressures and uplift forces as active forces and weight of check dam, depth of headwater, and the soil passive force as resistance forces. Figure 1-2 shows the schematic view of the check dams and forces, which contributes in statically stability analysis.. The space, which is created behind the check dam, will be filled with the sediments during the first floods events. It makes a level streambed in the reach upstream of check dam. The sequence of this procedure ultimately will generate some drops through the stream, where the check dams are constructed. Head of water Hydrostatic force Soil active force Soil passive force Uplift force Figure 1.3- schematic free body view of check dam 4

16 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK 2. STUDY AREA 2.1. General Study area (Kan catchment) is situated in north of Tehran (capital city of Iran) and covering an area of approximately 207 km 2 (figure 2.1) Figure2.1- general position of Kan catchment within Iran It is located between latitudes to N and longitudes to E (UTM zone 39, boundary coordinates is between X= to and Y= to ). It borders with Hesarak catchment in west, Jajrood basin in north and northeast, Karaj dam basin in north and northwest, Vardij catchment in east and city of Tehran in south (Figure 2.2). As it is shown the catchment drains to Tehran city, and therefore priority was given to Kan catchment to implement a flood control project. Based on a developing program of coastal zoon of Caspian Sea, in north of Iran, it has been decided to construct a highway from Tehran to north of Iran, which will pass through the Kan catchment and enhances the priority for this catchment. Utilizing the Kan catchment as a recreational site for the people and also locating a shrine within the catchment re-emphasises the priority of Kan. 5

17 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Figure 2.2- location of Kan catchment on topo map 2.2. Physiography Kan catchment is located in a mountainous area; mountains and very steep slopes cover more than 75 percent of whole area. Elevation difference between the lowest and highest point is about 2000 meters, With the highest point about 3400 meter and the lowest point, at the main outlet, about 1400 meters. High range of variation in elevation, steep slopes, and stream slopes cause very rapid flows. Figure 3.3 shows a digital elevation model of study area, which was derived from 100-meter interval contour lines. The surface slope map, which is derived from DEM, is shown in figure 3.4 as well. As is shown, steep slopes cover the most parts of catchment area. The average slope of study area is about 40 percent. The impact of slope and slope variation in flood characteristics will be discussed. 6

18 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Figure 2.3- digital elevation model of Figure 2.4- slope map of study area using Study area Using 100-meter interval DEM (slopes are in %) Contour line (heights in M. a.s.l) Sub catchments delineation is an important part of physiographic procedure in any hydrologic study. According to the purpose of study and the objective of the research the study area is divided to five sub catchments. However it is possible to make other sub divisions for those sub catchments. Figure no: 2.5 shows the position of these sub catchments and their main streams. The general physiographic characteristics of the Kan catchment and its sub catchments are calculated in GIS environment. Table no: 2.1 shows the information. Unit Area (km^2) Main river length (km) Avg.surface slope (%) Max alt. (M) Min alt. (M) Avg alt. (M) Rendan Sanghan Keshar Kiga Solghan Table 2.1- general physiographic characteristics of Kan catchment and its sub catchments 7

19 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Figure 2.5- sub catchments and their main river positions As it is shown in above table, Kiga is the steepest and Keshar is the most gentle sub catchment out of five sub catchments. The main river, which is called Kan River, begins in Rendan and lays its outlet in Solghan. Its length is about KM. One of the most important factors in flood analysis is the stream gradient. This factor can be presented by the longitudinal profile of the river. By crossing the DEM and the point map of river (which is converted from segment map) longitudinal profile of river will be drawn. To have a more precise graphs the point interval has been taken at 20 meters Alt (M) (a) Distance (M) (a) 8

20 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Alt. (M) Distance (M) (b) Alt. (M) Distance (M) (c) Alt. (M) Dis. (M) Distance (M) (d) Alt (M) (e) Figure 2.6 (a-e) longitudinal profiles of rivers in Kan catchment Information drowns from these profiles shows the variation of altitude along the river path. 9

21 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Stream gradient of those rivers, which will be used to determining the time of concentration are given in below table. River Rendan Sanghan Keshar Kiga Slogan Gradient(%) Table 2.2- Main rivers slopes of sub catchments of study area 2.3. Time of concentration: There are different descriptions for time of concentration (TC) in hydrologic literature.two mostly common descriptions are as follows: -The time for a drop of water to travel from the furthest hydrologic point in a catchment to the outlet. -The time between the center of excess rainfall and the inflection point on the recession limb of the hydrograph. For the same volume of runoff, a longer time of concentration will reduce the peak flow magnitude and the time to peak of hydrograph. Different authors have developed different methods and formulas for TC calculation; Kerby (1959), Kirpich (1940), Bransby & Williams (1961), etc. Table 2.3- gives the results of TC calculation by different methods. UNIT Kerby (Min) Kirpich (Min) Kinematic (Min) Bransby (Min) Federal (Min) Rendan Sanghan Keshar Kiga Solghan Table 2.3- TC calculation results by different methods As it is shown different methods give various amount of TC. Based on the observations and the general conditions of rivers the Kerby method is the most proper method for the study area, and will be used here. 10

22 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK 2.4. Vegetation cover Field observation: The slopes of study area study area have a very poor vegetation cover. The riverbanks are orchards, which are safer from flood damages locally. The poor vegetation cover, because of poor rainfall, shallow soil, and overgrazing, conclusive to rapid overland flow generating flood occurrence NDVI: NDVI (Normalized Difference Vegetation Index) is a useful method for recognizing the vegetation cover by applying satellite images. This function requires 2 satellite bands (one with visible or red values and the other near-infra red values). For study area by using the LANDSAT TM images, which are taken in 2000 the NDVI map, is produced.the employed band are band 3 and ban 4.The result value of NDVI map will be between 1 to 1.The negative values represents the water bodies and clouds, the values closed to zero represents the bare soil and rocks, and the positive values represents the vegetation. For finding the orchards and any other dense vegetation the NDVI map was classified in two-categories. As it is shown in below figure there are just some small patches of vegetation in hillsides, and some Figure 2.7- vegetation cover map of study area (Using NDVI map) irrigated lands, which are shown by continuous, and narrow pattern and covers about 2% of total catchment area. 11

23 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK 2.5. Climatology Rainfall The first step to flood studying in any supposed area is, having the proper data and information about the rainfall. Rainfall is the most effective parameter in flood generation. If there is good information about rainfall, the result of flood simulating and flood analysing will be more realistic. Thus it is needed to go through the rainfall in detail Rain gage stations There are five rain gage stations, which cover the study area. Except for one, the other four stations have been equipped in The available recorded data for these stations are just for five years. The old one has had discontinuous data since 1968 to 1989, which are not reliable. But since 1990 the recorded data of this station is reliable with no gaps. Although there are some other stations around the Kan catchment because of distances and different climatologic conditions, their data are not useful for study area. Only the Kan station, located in outside the catchment in plain of Tehran has selected, because of its low proximity and long data series. During the fieldwork and rain gage station inspecting, we found another rain gage. The operator experience and his responsibility were such that we did not consider this station. Figure 2.8 positions of selected rain gages on DEM of Kan Annual rainfall: Rainfall analysing needs a common periods of records for involved stations. A period of 5 years ( ) is selected for annual rainfall analysing in study area. 12

24 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK RAINFALL(MM) YEAR kan keshar sanghan kiga rendan solghan Figure 2.9- annual recorded rainfall of selected rain gage stations in Kan ( ) It shows a more or less regular pattern of changes in rainfall amount in different rain gages. One of the most important and applicable information about rainfall is rainfall gradient. It shows relation between the rainfall amount and the elevation of different stations. A physical view of rainfall will be extract by this relation. 500 rainfall (mm) altitude (m) Figure relation between altitude and rainfall amount in Kan catchment As it is shown there is a positive gradient for rainfall up to about 2100 in study area. The recent researches have proved a negative gradient for rainfall in northern Tehran catchment. Although there is not a very sharp threshold for this phenomenon but many researchers believe to around 2600 meters (Northern Tehran watershed management plan, meteorology report, by Jihad Technical services Co. 1992). Spatial variation of rainfall was expressed as the correlation coefficient of annual rainfall amount and corresponding distance between different rain gage stations. They have been plotted in a graph. As it can be seen Keshar has the lowest correlation coefficient. 13

25 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK It can be the effect of elevation, where the keshar has the lowest mean elevation among the new established stations. 1 Correlation coefficient Distance (km) Rendan Kan Keshar Solghan Sanghan Figure 2.11 correlation coefficient of pairs of stations for annual rainfall in Kan catchment Versus distance Daily rainfall Annual rainfall gives general information about the rainfall in study area. But annual rainfall data is not a proper data to study the flood. For flood studies one has to work with daily rainfall over long Periods. The major parameters, which will be used in flood studying, are; intensity, duration, and frequency of the rainfall. Unfortunately regarding the duration of the data in the study area this information is not available. Therefore Kan station, which has long duration data, will be used. An IDF curve of Kan station, which is derived from 30 years duration data (Watershed management plan of Kan, by Jihad research s Co. 2000), is as below: INTENSITY(MM/HR) RAINFALL DURATION(min) 2 year 3 year 5 year 10 year 25 year 50 year 100 year Figure IDF curve of Kan station (2.9 km away from study area) The spatial pattern of maximum daily precipitation of the five stations within the Kan catchment is shown by the correlation coefficient between pairs of stations. See figure

26 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK As can be noted at a short distance of about 4 km, the daily maximum precipitation is poorly correlated (C.C=0.4, 0.25); therefore high intensity rainfalls do not cover large part of the catchment uniformly. It means that, considering the available data, the spatial pattern of rainfall is not known well. correlation co distance(km) Figure Correlation coefficient of maximum daily rainfalls of pair s stations Versus distance of gages (compared with Rendan station) Depth-area methods Studying the depth and distribution of rainfall events over a catchment area is reliable method to know the rainfall properties. Within a GIS it is possible to produce the isohytal maps. A point interpolation procedure has to be followed as rainfall amount at discrete points. Six maximum rainfalls are selected to produce daily isohytal maps. The moving average method for point interpolation is used. Using the aggregation function in ILWIS the total depth of rainfall with high rainfall for the whole catchment is calculated. Effect of altitude is ignored. Figure no: 2.14 shows a classified result for six selected events in the Kan catchment. The spatial patterns are shown in figure 2.14.The figures shows clearly the uneven spatial distribution of the different rainfall events. As the figures show the autumn and winter storms are more generalized than the spring and summer storms. In general high intensity rains are localized in a small part of catchment but contribute substantially to the total catchment rainfall, as is shown in figure The figure no2.15 gives more information about the contribution of sub areas in total rainfall of whole catchment. 15

27 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK PRECIPITATION AS % OF TOTAL PRECIPITATION CONTRIBUTING AREA(KM^2) 13/8/ /12/ /4/ /1/ /5/ /11/2000 Figure precipitation (as% of total catchment precipitation) as a function of area for sixselected maximum rainfall, selecting with the largest precipitation class. It can clearly be seen that most of the rainfall storms, which occur in late spring and also in summer, are more localized than the rainfall events, which occur in other seasons. It can also can be seen that 50% percent of total catchment area (approx. 100 km^2) yields about 40% of total rainfall. However about 40% 0f total rainfall is yielded by less than 20% of total catchment area. These conditions are the reflection of rainfall intensity. It means that storms with high intensities are more localized than the storms with low intensities. With perfectly events spatial distribution, the percent of precipitation would be a linear function (1:1) of area. See figure 2.16 PRECIPITATION AS % OF TOTAL PRECIPITATION y = x R 2 = CONTRIBUTED AREA(KM^2) Figure Regression line of 6 selected events in graph

28 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK 13/8/99 24/12/9 23/1/99 14/5/99 16/4/99 12/11/2000 Figure interpolated (moving avg.) daily rainfall (mm) of 6-selected high rainfall in Kan 17

29 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Depth-area reductions There is another method to get more information about real rainfall distribution. This method usually determines the percent of reduction of maximum point rainfall with increasing areas. As it can be seen for instance for 100 km 2 the rainfall reduction will be about 75% and for total catchment this amount will be about 45%. See figure Rainfall reduction(%) Area km^2 Figure depth-area reduction curve based on 6 selected high storms in Kan catchment Time distributed daily precipitation Plotting the daily rainfall data in one period will give useful information about temporal distribution of precipitation. The distribution in time of daily rainfall for Solghan station in ( ) is shown in figure Runoff and precipitation There are 5 hydrometric stations within the Kan catchment. See figure The most reliable data belongs to Solghan station at the main outlet of Kan catchment. The four other stations have no long-term data. Hence Solghan hydrographs will be used to study the flood characteristics in Kan. For common period of recorded daily rainfall and daily discharge ( ) they are plotted in a same graph. See figure 2.20 Rainfall(mm) Year Figure Daily rainfall hydrograph of Solghan station in Kan catchment ( ) 18

30 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Figure Position of hydrometric station in Kan RAINFALL(MM) DISCHARG(CMS) YEARS RAINFALL DISCHARG Figure 2.20-correspond rainfall (Solghan)-runoff (total catchment) hydrographs ( ) This graph shows the poor relation between rainfall and discharge, which is due to the poor knowledge of the catchment rainfall; for instance; the large amount of rainfall which, has occurred in 1994 (78mm) produced a low discharge (approx. 10 m 3 /s). Meanwhile a less amount of rain in 1995 (55mm) has produced a greater discharge (approx.130 m 3 /s). The other interesting point, which can be extracted by studying the hydrograph, is the effect of snowmelt. Arrival of warm air can cause appreciable runoff Daily rainfall and runoff data of Solghan station for 2 years (Oct.96 to Sep. 98) are plotted in figure no: During 301st to 361st days there is no rainfall and no runoff. Since 360 th to 440 th days there is rainfall but still no runoff. This is due to accumulation of snow, and partly dries catchment condition. During 480 th to 540 th days there is a considerable rainfall amount but the amount of discharge is not considerable. It can be the effect of rainfall intensity. 19

31 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK RAINFALLl(mm) DAYS RUNOFF(cms) RAINFALL RUNOFF Figure daily rainfall and runoff hydrographs in Solghan station (Oct Sep. 1998) It means the Intensity of rainfall is not so high to produce high discharges. During the 540 th to 570 th days despite of low rainfall, high runoff occurred. It is because of soil saturation by snowmelt and rain during previous rainy days and the catchment has low capacity to absorb water. The peak flow should have been caused mainly by rain, which only partly measured by gages. In period of 570 th to 620 th days there is no rainfall but still runoff is continued. It is effect of springtime snow melting and ground water discharge. In this research we will study only the direct runoff Design storm and flood Conclusion drawn from rainfall and runoff analysing should lead to design storm and design peak flood for study area. As it was explained in previous sections there is no sufficient correlation for maximum rainfall events within the catchment. In order to simulate a realistic amount of rainfall and Peak flow we should have a judgement based on observed events and existing data. Frequency analysis has been done for peak discharge (30 years record period) and maximum rainfall (12 years record period) for Solghan station. The best distribution for both of them is identified. See figure 2.22 (a) and 2.22(b). Based on frequency analysis the discharge of about 345 m 3 /s (which is equal to the maximum observed flood data) will be generated by 100 years return period of daily rainfall of about 135 mm. This amount of rainfall occurs just in Solghan sub catchment. Considering the results of depth-area reduction methods if we suppose a point rainfall, by generalizing this point to the total catchment, about 50% reduction will be occurred. Therefore this amount will be reduced by 67.5 mm. If we assume a 25mm/hr rainfall with 2.5 hours duration (aprox. Equal to the TC of Solghan) occurs, this amount of rainfall will be provided. 20

32 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Log Pearson Type III Discharge (m 3 /s) 200 Actual Data Weibull Probability Distribution (a) Log Pearson Type III Rainfall (mm) Actual Data Distribution Weibull Probability (b) Figure2.22 (a), (b) the best fit curves for maximum discharge and rainfall in Solghan station Considering that: T= (1/1-P) (3.1) Where T= return period (year) P= weibull probability The calculated return periods for various probabilities could be as table 2.4 Probability Return period (Year) Table 2.4 probabilities and return periods relation 21

33 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK 3. FLOW ROUTING 3.1. Introduction to flow routing Flow routing is a mathematical procedure for predicting the changing magnitude, speed, and shape of a flood wave as a function of time at various points along the river as a flood wave travels through the river. Flood forecasting, reservoir design, catchment simulation and water resource planning generally utilize some form of routing technique. While a river is carrying a flow some part of the flow will be stored along the different reaches. This is simply because the slope of the surface is not uniform during floods. This procedure along a river causes some differences between inflow and outflow hydrographs. Since we are going to investigate the effect of slope and its variation on the peak flood, the flow routing models will be required. As flow routing has been an important type of hydrologic analysis, which is complex and requires computations, many routing models have been developed. Routing models are concerned with two different methods, hydrologic routing and hydraulic routing. Hydrologic routing uses the equation of continuity with an analytical or assumed relation between storage and discharge within a system. Hydraulic routing uses both the continuity and momentum equations. In river routing applications, the hydrologic as well as the hydraulic routing type offer advantage of simplicity wherever it is applicable. Selection of a flow routing model for a purposed application is affected by so many factors such as capability of model to response the user s questions, required accuracy, type of available data and so on. Many trials were done to select a suitable model for river routing in Kan catchment. 3.2 HEC-HMS model The HEC- HMS model was examined. HMS contains different type of routing models such as Muskingum, Maskingum- Cunge, and kinematic wave. To select a routing model, one must consider the routing method s assumptions and conditions. The most important assumption and limitations, which can be faced in our application, are: - Backwater effect: practically none of the routing models that are included in HEC-HMS will simulate the channel flow well if the down stream conditions have a significant impact on upstream flow. - Interaction of channel slope and hydrograph characteristics: As the channel slopes lessen, assumption made to many of the models included in HEC-HMS will be violated. 22

34 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK - Availability of data for calibration: in general if the observed data are not available, the physically based models will be easier to set up and apply with some confidence. Thus these empirical models will not give accurate results in the case that there is not enough observed data. These three points make it doubtful whether the HMS model can be utilized for our application. Various routing options in HMS were tried but none of them were sensitive to changes of slope. Considering the effect of check dams in slope breaking it seems these methods will not applicable for this application. Beside these points, because of the narrow width of rivers there is no considerable capacity to be used as storage in flood routing. Thus these models should not be used for this kind of application. Figure 3.1 schematic basin model of Kan catchment in HMS model As it can be seen there is no considerable changes in discharge due to slope reduction in streams. The first run has considered the original slope of those rivers and the amount of peak discharge in rivers has been simulated. Second run has considered 50 % reduction in gradient of rivers. For instance in Kiga which is the steepest one by reducing the gradient to half, peak discharge just about 0.3 m 3 /s has been reduced. Despite of the small reduction in river discharges the total discharge at the main outlet has been increased a little. While the natural peak discharge was about m 3 /s by reducing the slopes to half the total discharge is simulated about m 3 /s. 23

35 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Table 3.1 output of HMS for various slopes Using Muskingum Cunge routing method 3.3. Convex routing method Many numerical approaches have been developed to route stream flow. Most of these methods have been simplified by assumptions. However, even these simplifications needs detailed data. There are more, simple routing methods, which have been developed by taking two basic hydraulic equations in consideration; Continuity and momentum equations. Some of the models just take the continuity alone. One of these models is convex method (Weinman and Laurreson 1979). Application of convex method requires 1) determination of the flood wave travel time through the stream which is named (T*), and (2) selected time step for flood routing which is named (t). The inflow hydrograph is assumed as a triangular hydrograph. There is a condition to select the time step for routing in convex method. The selected time step should be less than T* and 20% of the time to peak of the inflow hydrograph. This condition causes diffusivity in outflow hydrograph. The diffusivity factor indicates the tendency of hydrograph to be flattening. This tendency is due to the pressure force and increases with depth and decrease with slope and channel roughness as the flow moves downstream. As the method is a physically based method, it mostly deals with Chezy and Manning equations and their required data. The time of rising and falling limbs of hydrograph also are required. Since most of the required data are available, it was decided to use it in this study. 24

36 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Input data preparation To run the convex routing model it is required to determine the peak discharge of a catchment. As it was explored in rainfall analysing, to get a more accurate and realistic value for flood discharges, it was decided to take 25mm/hr, as the intensity of design storm in study area. By applying this intensity of rainfall, the calculated peak flow of entire catchment will be in a reasonable range. Rational formula will be used to calculate the peak discharge in various sub catchments. Comparing the recorded rainfall and runoff data determines the runoff coefficient of study area. Based on existing data this coefficient was calculated of about 20%. As it was explained before, the convex routing method will simulate the outflow hydrograph assuming a triangular inflow hydrograph. The main input data to run this model is: length of stream channel, width of streambed, bed slope, Manning coefficient, time to peak (TP) and the peak discharge of corresponding channel. The geometric data of channels are determined based on field measurements and some distance measurements in ILWIS. The input data to run the convex model are given table 3.2. Catchment QP (m 3 /s) River length (Km) Channel width (M) Manning (n) Bed Slope (%) Rendan Sanghan Keshar Kiga Solghan Results of convex model Table 3.2- input data in convex model Tp (hr) The convex model has been run for all sub catchments by considering 0.1 hr time step. The model calculates a simple triangular inflow hydrograph regarding the time steps and other assumed data. The input hydrographs are shown in figure 3.1. The starting time is a function of streams distances to the main outlet and its TC. It is obvious that the closer the distance to the outlet, the earlier time of starting. Based on these two parameters, the hydrographs are arranged. Delaying time of each sub hydrograph is an essential factor to generate the total hydrograph of entire catchment. It is taken in account to produce the total hydrograph of Kan catchment. As it clearly shown the total flood peak is about 210 m 3 /s, which will pass trough the main outlet in Solghan. Regarding the model requirements to rout the flow and assuming a diffusivity factor equal to 0.5 the out flow hydrograph for those sub catchment and consequently for whole catchment have been simulated. The outflow hydrographs are shown in figure

37 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK DISCHARG(CMS) TIME(HR) SOLGHAN KESHAR SANGHAN RENDAN KIGA TOTAL Figure 3.2- Convex method Inflow hydrographs of Kan catchment 250 DISCHARGE(CMS) TIME(HR) SOLGHAN KESAR SANGHAN RENDAN KIGA TOTAL Figure 3.3- convex routed outflow hydrographs of Kan catchment These two figures clearly show the effect of delaying time of sub hydrographs on total peak flow. Figure 3.2 indicates that the outflow sub hydrographs have been flattening due to the diffusivity factor. For instance in Rendan the peak inflow is about 91 m 3 /s, meanwhile peak outflow is about 85 m 3 /s and such a reduction has occurred in other rivers. Beside the peak flow, time to peak in those rivers has been lengthened. However no sufficient reduction in total peak flow is simulated. The sub hydrographs peaks are reduced but still the total peak is about 210 m 3 /s. Considering different TC for various rivers will give completely different values for flood peak. Some of these results, which have been obtained by assuming different TC for some of streams, are given in below figures. 26

38 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK DISCHARG(CMS) TIME(HR) kig+0.2hr san+0.2hr kas&sol+0.2hr sol+0.2hr ren&kig+0.2hr normal Figure 3.4- effect of TC prolongation by 0.2hr on peak flood in Kan catchment As is shown in figure 3.3 prolonging the TC of streams by 0.2 hr does not have much impact on flood peak and shape of hydrograph. Even in some cases it increases the peak at outlet. DISCHARG(CMS) TIME(HR) normal hy. ki&ren+0.2hr ren+0.2hr san&kes+0.2hr ren+0.4hr ren+0.6hr Figure 3.5- effect of TC prolonging on peak flood in Kan catchment Different combinations of assigning times of concentrations to sub catchments tested. The cases, which resulted in lowering peak flow, are retrieved. Figure 3.5 and 3.6 shows the impact of TC prolonging in Rendan and Kiga on peak flood. 27

39 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK DISCHARG(CMS) TIME(HR) normal ren+0.2hr ren+0.4hr ren+0.6hr ren+0.8hr ren+1hr Figure 3.6- effect of TC prolonging in Rendan River on peak flood reduction in Kan catchment DISCHARG(CMS) TIME(HR) normal kiga+0.4hr kiga+0.6hr kiga+0.8hr kiga+1hr Figure 3.7- effect of TC prolonging in Kiga River on peak flood reduction in Kan catchment Different alternatives, which affect the peak flood, are shown in below table. In some cases slope reduction on numbers of streams has no more lowering than the slope reduction within individual stream. For instance prolonging the TC of both Kiga and Rendan by 0.3 hr has less impact than prolonging TC of just Rendan by the same time. This is shown in below table. As it clearly shows different alternatives gives various flood reduction indexes. The maximum index indicates that by reducing the slope of Rendan by 80% (prolonging the TC by1 hour) the peak flood will be reduced by 31 %. Catchment Slope reduction (%) Flood peak reduction (%) at main outlet 28

40 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Rendan Rendan Rendan Rendan Rendan Rendan Kiga Kiga Kiga Kiga Kiga Kiga Kiga Kiga Kiga Sanghan Sanghan Sanghan Sanghan Sanghan Sanghan Sanghan Sanghan Solghan Solghan Solghan Solghan Solghan Solghan Keshar Keshar Keshar Keshar Keshar Keshar Keshar Keshar Keshar Table 3.3-flood peak variation based on slope reduction of sub catchments 3.4 Applying Manning equations 29

41 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Since the Manning formula is the most commonly used formula in river and hydraulic engineering applications and it is based on hydraulic radius and slope, it was selected to compare the results. Two different cross sections have been supposed; Natural condition of Rendan river (initial slope, manning coefficient, and cross section) and secondary condition after constructing check dams. V1 V2 C1 C2 C3 C3 C4 Figure 3.8- Simple schema of Rendan channel by constructing check dams Manning formula indicates; Q 1 = A 1 * n 1 1 * R 2/ * S 1 (3.1) Q 3 = A 3 * n 1 3 * R 2/ * S 3 (3.2) By applying continuity; A 1 * n 1 1 * R 2/3 1 * S 0.5 = 1 A 3 * n 1 3 * R 2/3 3 * S Whereas C1 is the initial cross section and C3 is the check dam site cross section. By substituting the Y1=4.29 m Y3=5.33 m B1= 4.5 m B3=5.2 m S1= S3=0.001 (very gentle slope) N1=0.065 N3=0.045 Z1=z3= 1:1 channel bank side slope In equations 3.1 and 3.2 and assuming that the calculated perimeter in natural channels is two times of smooth channels we will have: A1=19.85 m 2 A3=41.92 m 2 P1=23.6 m P3= m R1=0.84 m R3=1.633 m V1=4.6 m/s V3=2.18 m/s The slope and corresponding velocity in C2 (the ultimate cross section) will be calculated. V2=(V1+V3)/2=3.39 m/s S2=(S1+S3)/2= 5% If the desirable slope is assumed about 2% then the corresponding velocity will be as: V2=(4*V3+V1)/5=2.66 m/s If we assume that the offloading time of flow is proportional to flow velocity then: V1/V2=T2\T1 where T1 and T2 are the offloading time of flow. Assuming the convex input flow as the input hydrograph and considering no lateral inflow the offloading time after constructing check dams will be: T2=4.6*3*/2.66 = 5.18 hrs The area under the inflow hydrograph is the total amount of flow, which will be: 30

42 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Total volume= 91.35*3*3600/2= m 3 Considering the equality of the areas under the curve and similarity (figure 3.8) we will have: Q2=493290*2/(5.18*3600)= 52.9 m 3 /s discharge(cms) inflow time(hr) outflow Figure 3.9- inflow and outflow hydrographs before and after constructing check Rendan River By Manning equation Manning equation can t be considered as a real routing method because it doesn t deal with the length of river as a main component in routing procedure. It can be used just for determining the peak flow at any certain cross section. Due to the absence of stream length it will exaggerate the differences in short reaches. 3.5 Comparing the results of convex model with observed hydrographs To have a general view of the utilized methods and approaches it will be more useful, if the output result of the routing model and the impact of check dams compare with the real events and physically based formulas. To compare the result of convex routing model with the real time events, two observed outflow hydrographs in Solghan station are plotted with the convex model out flow hydrographs in a dimensionless graph. It will be a good scale to evaluate the applied models and approaches. What ever the shapes of simulated and observed hydrographs look closed to each other, the simulating method is more confirmed. However the accuracy of measurements should be considered as a main issue in this comparison. Figure 3.9 shows these hydrographs. 31

43 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK DISCHARG TIME Convex routed Observed 1/12/2000 Observed 18/10/2000 Figure 3.10 comparing the convex routed and observed dimensionless hydrographs in Solghan station As it can be seen there are some breaking points in falling limb of observed hydrographs. It can be the effect of delayed discharges within the catchment. Convex routed hydrograph doesn t show this point clearly. Generally and with respect to the lack of detail data the results of convex method is not so far from the real events and recorded data. 32

44 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK 4. CHECK DAM CONSTRUCTION 4.1. Check dam functionality The overall slope (after construction of check dams) is a linear function of the number of check dams. If the crest of downstream check dam and toe of the upstream one be at the same level the channel bed will be almost level. See figure 4.1. Some other functionality of check dams can be supposed such as water storage within the first duration of operating by infiltration. This study deals just with slope reduction functionality. The other ones can be studied later on in more detail in the future. Secondary slope Height of check dam Initial slope Figure 4.1- functionality of check dams in stream channel slope reduction 4.2. Number of check dams Numbers of check dams, which should be constructed through a stream to reduce the slope, Is a function of original slope, overall slope, length of stream, and height of check dams. N.O.C.D = (S 1 -S 2 )*L / H (4.1) Where as; S 1 : original slope % S 2 : secondary slope % N.O.C.D: number of check dams H: height of check dam (m) L: length of channel (m) By applying equation 4.1, number of check dams with various heights for the supposed slopes in table 3.2, can be calculated. See Table 4.1 The table also shows the secondary time of concentration of streams based upon corresponding slope. Catchment Secondary slope Secondary TC NOCD NOCD 33

45 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK S2 (%) TC2 (min) H=1.5m H=3m Rendan Rendan Rendan Rendan Rendan Rendan Kiga Kiga Kiga Kiga Kiga Kiga Kiga Kiga Kiga Sanghan Sanghan Sanghan Sanghan Sanghan Sanghan Sanghan Sanghan Table 4.1 Number of needed check dams to gain supposed slopes If the height of check dams becomes double the number of check dams will be half. But regarding the stability of the structures the required material will increase. Height and needed material increment are not linearly proportional to each other, because the two important forces which acts on check dams are proportional to the second power of height Required material 34

46 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Considering the forces, which are acting on the check dams, two types of gabion check dams have been considered. The main characteristics of these two types are given in below table. It can be clearly seen that volume of needed material per meter of unit width of rivers for 1.5-meter height check dam is about one-third of 3-meter height check dam. Check dam Height Crest width Bottom width Needed Material Type (m) (m) (m) (M 3 )/m Type Type Table 4.2- characteristics of designed check dams These factors will be transferred to DEFINITE software to generate a decision support system (DSS). This software will be used to select the most feasible alternative to be carried out in Kan catchment as an optimised flood control project. 5. DECISION MAKING 35

47 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK 5.1. General objectives In view of the stress on district level planning in the country, and regarding the limitation of funds decision makers need to have a clarified perspective of the offered alternatives. There are two main types of decision criteria evaluation; objective and subjective evaluation. Objective evaluation deals with effective potentials and their impacts considering the market value of involved criteria. Subjective evaluation will deal with various approaches that share to common purpose of suggested alternative options. It will help make a rational and feasible decision. The method, which is employed by the subjective evaluation, is called multiple criteria decision- making (MSDM). These methods can provide a simple and clear performance of those alternatives to help the decision makers to have a judgment and choose the best option. There is some applicable software to be involved with these methods. A useful package for this application is Definite which will apply a complete decision support system DEFINITE Introduction to DEFINITE DEFINITE (decisions on a finite set of alternatives) is a decision support software package that has been developed to improve the quality of decision-making. DEFINITE is, in fact, a whole toolkit of methods that can be used for a wide variety of problems. If the alternatives can be identified, then DEFINITE will help us to solve the problem of interest. The program contains a number of methods for supporting problem definition as well as graphical methods to support representation. To be able to deal with all types of information DEFINITE includes multicriteria methods, cost-benefit analysis and graphical evaluation methods. Related procedures such as weight assessment, standardization, discounting and a large variety of methods for sensitivity analysis are also available. A unique feature of DEFINITE is a procedure that systematically leads an expert through a number of rounds of an interactive assessment session and uses an optimisation approach to integrate all information provided by the experts to a full set of value functions. DEFINITE supports the whole decision process, from problem definition to report generation. Its structured approach ensures that the decisions arrived at are systematic and consistent DEFINITE input data Due to the hydrologic analysis 20 alternative options based on reduction of Qp by constructions of check dams identified. By defining the problem in DEFINITE software these 20 options will be as considered alternatives. For those alternatives 4 common effects have been identified and quantified. The quantitative values are transferred to DEFINITE to do the multicriteria analysis. 1.number of check dams 36

48 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK 2.height of check dams 3.cost of each option 4.flood reduction index These are the most important factors in engineering measures of watershed management projects and will affect the general characteristics of project. These criteria have been standardized using the maximum method of standardization. The maximum method is the best choice whenever we want to exaggerate the differences on purpose. The other advantage of this method is that the standardization values are proportional to the original values. Especially in analysing the cost effects it is most important: if an alternative is twice expensive it means it is twice worse and its chance is twice less. Among the different criteria the priority orders have been justified regarding the actual execution expected difficulties and project maintenance. There are various options to be selected, as a weighting method. The direct method, which is based on the experiments and manager judgment, is the most reasonable method to be chosen. These are the major inputs for DEFINITE software to be run and select the most rational alternatives, which can be recommended to decision- makers. By applying inefficient alternatives option in DEFINITE the number of alternatives were reduced by 12 alternatives. Table 5.1 DEFINITE effect table of Kan flood control project DEFINITE output results: As was mentioned 12 most efficient alternatives were selected. By maximum standardization, direct assessment method of weighting, and ratio scale measurement, the program was run and the following results were taken. I assumed that the weight of cost and flood peak reduction is equal. See figure

49 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Figure 5.1 result of multicriteria analysis for Kan flood control As it can be seen alternative number 5 which indicate that, constructing 565 check dam with 1.5 meter height in Rendan river, by spending $ will reduce the flood peak by 31 % is the most rational alternative Sensitivity analyses A ranking of alternatives is only certain if the given scores, priorities, value functions can be estimated by complete certainty. Whenever the uncertainty goes up the ranking will be unstable and unreliable. To investigate the impact of those effects on the decision-making procedure, one needs to have a clarified perspective of those effects and their impacts on the purpose of the project. Sensitivity analysis is a very good method to compare priority of alternatives regarding the variation of the weights of effects. For two main effects of interest, cost and flood peak reduction, this method has been carried out and the results are given in figure 5.2. It can be seen that by considering the given weight to the cost effect (w=0.45) on the multicriteria analysis the first rank of alternatives is stable if the variation of cost weight is between It means that if the given weight gets smaller till 0.12 still the A5 is the first rank. Meanwhile if it increases a little and comes to 0.5 the first rank (A5) will be reversed by A2 and will remain stable by increasing the weight of cost by the end. Based on the weight of flood peak reduction the ranking will be stable from 0.42 and greater. If the weight of flood peak reduction decrease by 0.42 and less the ranks will be varied. 38

50 EVALUATING THE EFFECET OF CHECK DAMS ON FLOOD PEAK Figure 5.2. Sensitivity of ranking for cost and flood peak reduction criterions 6. CONCLUSION AND RECOMMENDATIONS 39