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An innovative methodology for the prioritization of sub-catchments for flood control
International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87 www.elsevier.com/locate/jag
An innovative methodology for the prioritization of sub-catchments for flood control Mohammad Roughani *, Mohammad Ghafouri, Mahmoodreza Tabatabaei Soil Conservation and Watershed Management Research Institute (SCWMRI), P.O. Box 13445-1136, Tehran, Iran Received 4 May 2005; accepted 15 June 2006
Abstract Iran is dominated by arid and semi-arid climate with sporadic rainfall which creates seasonal floods and causes considerable damages and occasionally loss of life. The current research with the aim of flood damage reduction presents an innovative applied methodology for spatial optimization of flood control measures based on sub-catchments location. The presented methodology determines the contribution of each sub-catchment to the main catchment outlet flood peak and prioritizes sub-catchments for implementation of flood control measures. For this purpose catchment flood hydrographs are simulated by calibration and evaluation of a hydrologic model. The isochrones of the catchment have been computed and drawn and sub-catchment spatial distribution is investigated in relation to isochronal areas. Considering both spatial distribution and flooding potential of subcatchments and their combined effects on the flood peak, their contribution to flood peak was modified by implementing flood control measure. Testing of this methodology on an experimental catchment indicated that sub-catchments located near the centroid of the catchment with an area of 64.6 km2 have the greatest effects on flood peak for the overall catchment with an area of 284.6 km2. It was concluded that flood control measures should be concentrated in these sub-catchments as the first priority. # 2006 Elsevier B.V. All rights reserved. Keywords: Watershed management; Rainfall–runoff; Isochronal models; Flood control; Spatial optimization
1. Introduction Widespread studies of the effects of land use change have been undertaken on flood generation and catchment response. Urbanization, for example, will change the overland flow roughness coefficient, time of concentration and reduces vegetal cover and changes infiltrability of soil and results in different behaviors of the catchment in runoff generation and flood hydrograph (Roughani, 1997). Similarly, flood control * Corresponding author. Tel.: +98 21 44901215; fax: +98 21 44905709. E-mail addresses: [email protected] (M. Roughani), [email protected] (M. Ghafouri), [email protected] (M. Tabatabaei). 0303-2434/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.jag.2006.06.001
gabions, terraces, dikes and non-structural measures such as plantation and restriction have different effects on rainfall–runoff relationships. Brooks et al. (1991) showed that deforestation may increase flooding, however the timing of upstream and downstream flows is important and deforestation may reduce flood peaks as well. Using mathematical models Ghafouri (1996) studied the effects of impervious areas change in urban catchment and their effects on flood peaks and showed that the spatial distribution of urban development or consolidation has different effects on the flood peak. Jones (2000) highlighted the significance of human activities on flood magnitude and frequency. Karbowski (1993) and Shim et al. (2002) recommended cascade reservoirs to minimize flood peak discharge. Conjunctive use of structural and non-structural measures for
80
M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87
increasing flood control success is proposed by Simonovic (2002). Land use planning is considered as a suitable managerial measure for flood control (Friesecke, 2004). Gorokhovich (2000) used GIS to investigate flood contributing areas of catchments during selected time interval to find out effective areas on flood peak without any efforts to prioritize these areas. Wurbs (2005) emphasizes on using computer models for watershed and river management. The above studies indicate the significance of spatial optimization of urban development and other land use change within a catchment to manage any increases in flood peaks compared with that of natural conditions. In 1997 Roughani used RAFTS-XP (XP-Software, 1996) rainfall–runoff model to develop a methodology
to identify the areas of Roodak catchment in Iran that had the greatest impact on flood peaks. In another research project he identified area that had the greatest impact on the flood peak and concentrated flood control measures in these areas. The restriction of flood control measures such as small dams and retention basins was considered to be more cost effective (Roughani, 2003). Khosroshahi (2001) using HEC-HMS model studied the flood generation of sub-catchments of the Damavand catchment east of Tehran and concluded that the spatial position of sub-catchments affects the magnitude of the flood peak which supported Roughani’s studies in Roodak catchment. In 1994 Ghaemi et al. identified six effective parameters that influence on flood peak in Karkheh
Fig. 1. Flow chart of spatial optimization of flood control measures.
M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87
81
Fig. 2. The location of Roodzard catchment.
basin including: rainfall depth, time of rainfall, snow depth, soil type, vegetal cover, slope and shape of catchments. In their study the role of river routing and other processes were ignored which affects the accuracy of the results (Khosroshahi, 2001).
A flood hydrograph reflects the spatial and temporal characteristics of rainfall, soil moisture conditions, physiography and evapotranspiration. It presents valuable information about these interactions of parameters and the catchment response. The research by Clark (1945),
Fig. 3. Sub-catchments in Pole Manjanigh sub-basin.
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M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87
Maidment (1993), Maidment et al. (1996), Laurenson (1964) and Donker (1992) in relation to time–area method indicate the importance of the spatial distribution of subcatchments and their role in flood hydrograph generation. While the role of spatial distribution of sub-catchments on flood peak was either implicitly or explicitly emphasized, there was no specific method for characterizing the spatial significance of sub-catchments. In Iran, according to the published statistics more than 3700 floods have occurred in the period of 1951–2001 (Ghaemi et al., 1994). This shows that flooding in 1990s compared with 1960s has increased 10-fold. Total damages in year 1992 flood, which caused destruction of 100,000 dwellings, was estimated as 500 billion Rials which approximately equals to US$ 350m (Iranian Hydraulic Association, 2001). The increasing frequency of floods in Iranian catchments has the potential to impact on the annual country budget due to the need to fund post-flood reconstruction (Roughani, 1997). Using the methodology discussed below, the effects of control measures on flood peaks is predictable. The areas that have the greatest impact on flood peaks can be recognized and prioritized for control measures. 2. Material and methods The approach is demonstrated in Fig. 1 and is applied to the Pole Manjanigh basin, a gauged sub-catchment of the main representative and experimental catchment of Roodzard, located in the south of Iran as follows.
DEM, slope, flow direction and isochrones were prepared (refer Table 1). 2.2. Mathematical models application A model is a simple presentation of a complex system. In mathematical models the behaviors of a system are presented with a series of interconnected mathematical equations with logical statements (Ghafouri, 1989). Understanding physical processes and their hydrologic components and their effects on catchment response to rainfall is one of the basic principles in watershed management and flood control. The variations in hydrological processes due to land use change has an impact on the quantity and quality of runoff from a catchment. Hence rainfall–runoff models are very useful tool for assessing rainfall and runoff and the impact of flood control measures. The RAFTS rainfall–runoff model was first developed in Australia in 1974 (XP-Software, 1996) and has been applied widely on rural, urban and urbanizing catchments throughout Australia and in other countries. The general structure of the model is based on storage processes in the catchment and routing of generated runoff. For a complete description of the model refer to the model manual (XP-Software, 1996). The Pole Manjanigh catchment was subdivided into 49 sub-basins (refer Fig. 3). A RAFTS model of the catchment was assembled (refer Fig. 4). Curve Numbers were calculated from the main catchment outlet observed data by using Eqs. (1) and (2): 0:5
2.1. Location and physical characteristics of the region
S ¼ 5½P þ 2Q ð4Q2 þ 5PQÞ CN ¼
Pole Manjanigh is one of the large sub-catchments of the representative catchment of Roodzard (refer Fig. 2) in south of Iran located on Zagrous Range with an area of 284.6 km2 between 498520 and 508100 eastern longitude and between 318280 and 408310 northern latitude (Fig. 3). Using a GIS software, ILWIS (Integrated Land and Water Information System, 2001), spatial data for this sub-catchment including:
25; 400 S þ 254
Table 1 Physical characteristics of Poleh Manjanigh sub-catchment Area (km2) Stream length (km) Minimum elevation (m) Maximum elevation (m) Average slope (%) Time of concentration (h)
284.6 42.2 753 3113 45 3.6
Fig. 4. Hydrological model of Pole Manjanigh catchment.
(1) (2)
M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87 Table 2 Comparison of observed and predicted peak flows for various floods Stage
Polemanjenigh catchment 3
Calibration Verification Calibration Calibration Verification Calibration Verification Verification
3
Qpred (m /s)
Qobs (m /s)
158.5 44.7 26.6 57.0 16.0 56.0 16.9 92.8
158.0 44.5 26.8 56.0 15.0 54.0 16.5 99.0
Soil condition
Date
III III II III III III III III
86/11/7 82/12/13 84/11/14 79/12/14 79/12/12 79/12/2 79/12/7 77/11/11
where P is the rainfall depth (mm), Q the runoff depth (mm), S the maximum retention (mm) and CN is the Curve Number.
83
In RAFTS model there is no option for the input of CN. Hence CNs were estimated based on land use and soil type for 49 sub-basins from available tabulated values. Sub-basins’ CNs were converted to runoff coefficients, by using CN and runoff coefficient at the main catchment outlet, to be applicable in RAFTS model. This quantitative conversion is essential when runoff coefficient for the model is estimated for design rainfall. The model calibration and verification results are presented in Table 2 and Fig. 5. The comparison of three parameters of flood peak, time to peak and flood volume of simulated and observed hydrographs shows the accuracy of the simulation. The small difference in some cases may be due to using only one rainfall recording station. RME index and Student’s T-test are used for statistical assessment of the model results
Fig. 5. Comparison of observed and predicted hydrographs.
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Table 3 Student’s T-test for evaluation and calibration of the model-Pole Manjanigh catchment H0 = H1 0.99 48.4 51.4 51.7
Result Significance level Standard deviation Upper limit Lower limit
Mendenhall et al. (1989, 1990). From Eqs. (3) and (4) the error percentage was calculated as 2.8. Furthermore the Student’s T-test results show that there is no significant difference between observed and simulated discharges at 99% level which indicates accuracy of calibration and evaluation processes (Table 3). When physical and hydrological parameters of a watershed become known in a mathematical model, it is possible to examine different scenarios and management practices and study the results before implementation of any costly control structures or land use change:
where Qobs is the observed discharge, Qpred the predicted discharge, REi the relative error and RME is the relative mean error. 2.3. Isochrones
n 1X RME ¼ REi n i1
REi ¼
Fig. 6. The Tc model in ArcView 3.2a environment.
(3)
jQobs Qpred j 100 Qobs
(4)
In order to apply the proposed methodology it is necessary to prepare isochronal map of the catchment. The map was prepared for the catchments using a distributed model of time of concentration, Tc model,
Fig. 7. Flow direction, maximum travel time and TC of each cell (Tabatabaei, 2003).
M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87
85
Fig. 8. Spatial distribution of sub-catchments overlaid on isochrones-Pole Manjanigh catchment.
2.4. Spatial distribution of effective areas on flood peak
which has been designed and developed in ArcView (Tabatabaei, 2003) (refer Fig. 6). The Tc model is developed by using object oriented programming such as Visual C++ and Avenue. By inputting some preliminary data layers as Digital Elevation Model, DEM, and watershed stream network to the model, it can calculate time of concentration for each cell in the watershed. At first, the maximum travel time of each cell based on common equations such as Kirpich equation is calculated. Along the flow direction of the watershed, the maximum travel time of all cells is summed up and time of concentration to any sections of the watershed is calculated as isochrones (refer Figs. 7 and 8).
In order to prioritize sub-catchments for flood control, areas that have the greatest effect on flood peak to be identified. After determining the spatial location of sub-catchments and each isochronal area, their separate and cumulative contribution to the flood hydrograph is studied. Assuming either flood control or flood reduction measures in the sub-catchments located on each isochronal area, their proportions of the outlet hydrograph are deleted completely or modified using the catchment simulation model. The model is frequently run and all regions are tested for their affect
Table 4 The results of deletion of sub-catchments on isochrones and their affect on the flood peak Isochrones
Sub-catchment area (ha) Flood peak after operation (m3/s) Flood reduction (m3/s) Proportion of area (%) Flood reduction (%) Spatial efficiency
1
2
3
4
5
6
7
782 317.5
1060 316.6
5055 280
4088 267
6459 219
6733 269
4029 300
0.5 2.8 0.2 0.06
1.5 3.8 0.5 0.13
38 17.9 11.9 0.67
51 14.5 16 1.11
99 22.9 31.1 1.36
49 23.9 15.4 0.65
18 14.3 5.7 0.4
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M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87 Table 5 Flood peak reduction after prioritization of sub-catchments Sub-catchment no. Area (ha) Flood peak after control (m3/s) Flood peak reduction (m3/s) Proportion of area (%) Flood reduction (%) Spatial efficiency
Fig. 9. Comparison of the effects of flood control measures in each isochronal area-Pole Manjanigh catchment.
on flood peaks. For the purpose of this study flood peak with a return period of 100 years was analyzed. Table 4 shows the results of the modelling of different options. Table 4 shows the performance of sub-catchments in response to rainfall. Comparison of flood peaks shows that moving from the outlet towards middle sections of the catchment, the effect of flood control measures in sub-catchments on the flood peak is significantly increased. On the other hand, moving from middle sections to upper sections the effect of sub-catchments on the flood peak is reduced. Fig. 9 indicates the effectiveness of different group of sub-catchments lied on each isochronal area on flood peak. The comparison of spatial efficiency in Table 4, obtained by dividing the percentage of flood reduction by the percentage of the
I-26 to I-32, I-35 to I-36 5676 228 90 19.9 28.3 1.42
catchment area, indicates that sub-catchments located on the isochronal areas 1 and 2 near the outlet with spatial efficiency of 0.06 and 0.13 have the least effect on the flood peak while sub-catchments located on isochrones 5 have the highest efficiency 1.36 as the index and have the most effects on the outlet flood peak formation. The sub-catchments located on upper parts of the catchment with efficiencies of 0.65 and 0.4 have a moderate effect on the flood peak. 3. Results Although total area of sub-catchments of isochronal area 5 is smaller than that of 6 the spatial efficiency group of sub-catchments is twice as much as that of isochronal area 6 (Table 4). It is concluded that subcatchments located on isochronal areas 4 and 5 in Pole Manjanigh catchment with the highest spatial efficiencies have the highest priority for any flood control measures (refer Fig. 10). The results of simulation of the
Fig. 10. Comparison of spatial efficiency of sub-catchments in Pole Manjanigh catchment.
M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87
critical sub-catchments on isochronal areas of 4 and 5 are summarized in Table 5 and Fig. 10. 4. Conclusions The innovative methodology for identifying and prioritizing key sub-catchments for efficient flood control developed in this research can be used in watershed management for flood control. It is concluded that: 1. Land use change close to the catchment outlet will have the least impact on flood peaks of any location. 2. Sub-catchments that have times of concentration to the catchment outlet around 50% of the overall catchment time of concentration are the most spatially efficient. References Brooks, K.N., Folliott, P.F., Gregersen, H.M., Thames, J.L., 1991. Hydrology and the Management of Watershed, vol. 1. Iowa State University, p. 220. Clark, C.O., 1945. Storage and the unit hydrograph. Trans. ASCE 110, 1419–1488. Donker, N.H.W., 1992. Automatic extraction of catchment hydrologic properties from digital elevation model. ITC J. 257–265. Friesecke, F., 2004. Precautionary and sustainable flood protection in Germany—strategies and instruments of spatial planning. In: Third FIG Regional Conference, Jakarta, Indonesia. Ghafouri, M., 1989. Digital simulation of hydrologic cycle in Rood Zard experimental and representative catchment. M.Sc. Thesis. Faculty of Agriculture, Shiraz University, Shiraz, Iran (in Persian). Ghafouri, R.A., 1996. Deterministic analysis and simulation of runoff in urban catchments. Ph.D. Thesis. Wollongong University, Wollongong, NSW, Australia. Ghaemi, H. et al., 1994. Watershed Management Reconnaissance and Feasibility Studies in Karkheh Basin. Watershed Management Deputy Section, Ministry of Agricultural Jehad (in Persian). Gorokhovich, Y., 2000. Modeling and potential use of hydrologic contributing areas for environmental application. In: Fourth International Conference on Integrating GIS and Environmental Modeling (GIS/EM4): Problems, Prospects and Research Needs, Banff, Alberta, Canada.
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Iranian Hydraulic Association, 2001. Newsletter. Mehr. Mah. (23), 3 (in Persian). ITC Publication, 2001. User Guide ILWIS, Netherland. Jones, J.A., 2000. The physical causes and characteristics of floods. In: Parker (Eds.), Floods, vol. II. p. 93. Karbowski, A., 1993. Optimal Flood Control in Multireservoir Cascade Systems with Deterministic Inflow Forecasts. Institute of Automatic Control, Warsaw University of Technology, Warsaw, Poland. Khosroshahi, M., 2001. Determination of sub-catchments role in flooding rate of catchment, Case Study in Damavand catchment. Ph.D. Thesis. Irrigation Department, Tarbiat Modaress University, Tehran, Iran (in Persian). Laurenson, E.M., 1964. A catchment storage model for runoff routing. J. Hydrol. 2, 141–163. Mendeenhall, W., Reinmuth, J.E., Beaver, R., 1989. Stat. Management Econ. 700–701. Mendenhall, W., wacyerly, D.D., Scheaffer, R.L., 1990. Mathematical statistics with application. Pws-kent.. Maidment, D.R., Olivera, J.F., Calver, A., Eatherral, A., Fraczek, W., 1996. A unit hydrograph derived from a spatially distributed velocity field. Hydrol. Process. 10 (6), 831–844. Maidment, D.R., 1993. In: Kovar, Nachtnebel, (Eds.), A Spatially Distributed Unit Hydrograph by Using GIS in Application Hydrology and Water of Geographic Information System in Water Resources Management. pp. 181–192. Roughani, M., 1997. Investigation of spatial distribution of effective areas on flood peak. M.Sc. Thesis. Natural Resources Faculty, Tehran University, Tehran, Iran (in Persian). Roughani, M., 2003. Investigation of spatial distribution of effective areas on flood peak in order of flood reduction hazard in Iranian catchments. Final Research Report. Soil Conservation and Watershed Management Research Center, Tehran, Iran (in Persian). Shim, K.C., et al., 2002. Spatial Decision Support System for Integrated River Basin Flood Control. J. Water Resour. Plng. Mgmt. 128 (3), 190–201. Simonovic, P., 2002. Non-structural measures for water management problems. In: Proceeding of the International Workshop, London, Ontario, Canada. Tabatabaei, M., 2003. Development of a distributed model of catchment time of concentration using GIS and Object Oriented programming. Final Research Report. Soil Conservation and Watershed Management Research Center, Tehran, Iran (in Persian). Wurbs, R.A., 2005. Comparative Evaluation of Generalized River/ Reservoir System Models. Texas Water Resources Institute College Station, Texas. XP-Software, 1996. RAFTS-XP User manual. XP-Software Inc., Canberra, Australia.
An innovative methodology for the prioritization of sub-catchments for flood control Mohammad Roughani *, Mohammad Ghafouri, Mahmoodreza Tabatabaei Soil Conservation and Watershed Management Research Institute (SCWMRI), P.O. Box 13445-1136, Tehran, Iran Received 4 May 2005; accepted 15 June 2006
Abstract Iran is dominated by arid and semi-arid climate with sporadic rainfall which creates seasonal floods and causes considerable damages and occasionally loss of life. The current research with the aim of flood damage reduction presents an innovative applied methodology for spatial optimization of flood control measures based on sub-catchments location. The presented methodology determines the contribution of each sub-catchment to the main catchment outlet flood peak and prioritizes sub-catchments for implementation of flood control measures. For this purpose catchment flood hydrographs are simulated by calibration and evaluation of a hydrologic model. The isochrones of the catchment have been computed and drawn and sub-catchment spatial distribution is investigated in relation to isochronal areas. Considering both spatial distribution and flooding potential of subcatchments and their combined effects on the flood peak, their contribution to flood peak was modified by implementing flood control measure. Testing of this methodology on an experimental catchment indicated that sub-catchments located near the centroid of the catchment with an area of 64.6 km2 have the greatest effects on flood peak for the overall catchment with an area of 284.6 km2. It was concluded that flood control measures should be concentrated in these sub-catchments as the first priority. # 2006 Elsevier B.V. All rights reserved. Keywords: Watershed management; Rainfall–runoff; Isochronal models; Flood control; Spatial optimization
1. Introduction Widespread studies of the effects of land use change have been undertaken on flood generation and catchment response. Urbanization, for example, will change the overland flow roughness coefficient, time of concentration and reduces vegetal cover and changes infiltrability of soil and results in different behaviors of the catchment in runoff generation and flood hydrograph (Roughani, 1997). Similarly, flood control * Corresponding author. Tel.: +98 21 44901215; fax: +98 21 44905709. E-mail addresses: [email protected] (M. Roughani), [email protected] (M. Ghafouri), [email protected] (M. Tabatabaei). 0303-2434/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.jag.2006.06.001
gabions, terraces, dikes and non-structural measures such as plantation and restriction have different effects on rainfall–runoff relationships. Brooks et al. (1991) showed that deforestation may increase flooding, however the timing of upstream and downstream flows is important and deforestation may reduce flood peaks as well. Using mathematical models Ghafouri (1996) studied the effects of impervious areas change in urban catchment and their effects on flood peaks and showed that the spatial distribution of urban development or consolidation has different effects on the flood peak. Jones (2000) highlighted the significance of human activities on flood magnitude and frequency. Karbowski (1993) and Shim et al. (2002) recommended cascade reservoirs to minimize flood peak discharge. Conjunctive use of structural and non-structural measures for
80
M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87
increasing flood control success is proposed by Simonovic (2002). Land use planning is considered as a suitable managerial measure for flood control (Friesecke, 2004). Gorokhovich (2000) used GIS to investigate flood contributing areas of catchments during selected time interval to find out effective areas on flood peak without any efforts to prioritize these areas. Wurbs (2005) emphasizes on using computer models for watershed and river management. The above studies indicate the significance of spatial optimization of urban development and other land use change within a catchment to manage any increases in flood peaks compared with that of natural conditions. In 1997 Roughani used RAFTS-XP (XP-Software, 1996) rainfall–runoff model to develop a methodology
to identify the areas of Roodak catchment in Iran that had the greatest impact on flood peaks. In another research project he identified area that had the greatest impact on the flood peak and concentrated flood control measures in these areas. The restriction of flood control measures such as small dams and retention basins was considered to be more cost effective (Roughani, 2003). Khosroshahi (2001) using HEC-HMS model studied the flood generation of sub-catchments of the Damavand catchment east of Tehran and concluded that the spatial position of sub-catchments affects the magnitude of the flood peak which supported Roughani’s studies in Roodak catchment. In 1994 Ghaemi et al. identified six effective parameters that influence on flood peak in Karkheh
Fig. 1. Flow chart of spatial optimization of flood control measures.
M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87
81
Fig. 2. The location of Roodzard catchment.
basin including: rainfall depth, time of rainfall, snow depth, soil type, vegetal cover, slope and shape of catchments. In their study the role of river routing and other processes were ignored which affects the accuracy of the results (Khosroshahi, 2001).
A flood hydrograph reflects the spatial and temporal characteristics of rainfall, soil moisture conditions, physiography and evapotranspiration. It presents valuable information about these interactions of parameters and the catchment response. The research by Clark (1945),
Fig. 3. Sub-catchments in Pole Manjanigh sub-basin.
82
M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87
Maidment (1993), Maidment et al. (1996), Laurenson (1964) and Donker (1992) in relation to time–area method indicate the importance of the spatial distribution of subcatchments and their role in flood hydrograph generation. While the role of spatial distribution of sub-catchments on flood peak was either implicitly or explicitly emphasized, there was no specific method for characterizing the spatial significance of sub-catchments. In Iran, according to the published statistics more than 3700 floods have occurred in the period of 1951–2001 (Ghaemi et al., 1994). This shows that flooding in 1990s compared with 1960s has increased 10-fold. Total damages in year 1992 flood, which caused destruction of 100,000 dwellings, was estimated as 500 billion Rials which approximately equals to US$ 350m (Iranian Hydraulic Association, 2001). The increasing frequency of floods in Iranian catchments has the potential to impact on the annual country budget due to the need to fund post-flood reconstruction (Roughani, 1997). Using the methodology discussed below, the effects of control measures on flood peaks is predictable. The areas that have the greatest impact on flood peaks can be recognized and prioritized for control measures. 2. Material and methods The approach is demonstrated in Fig. 1 and is applied to the Pole Manjanigh basin, a gauged sub-catchment of the main representative and experimental catchment of Roodzard, located in the south of Iran as follows.
DEM, slope, flow direction and isochrones were prepared (refer Table 1). 2.2. Mathematical models application A model is a simple presentation of a complex system. In mathematical models the behaviors of a system are presented with a series of interconnected mathematical equations with logical statements (Ghafouri, 1989). Understanding physical processes and their hydrologic components and their effects on catchment response to rainfall is one of the basic principles in watershed management and flood control. The variations in hydrological processes due to land use change has an impact on the quantity and quality of runoff from a catchment. Hence rainfall–runoff models are very useful tool for assessing rainfall and runoff and the impact of flood control measures. The RAFTS rainfall–runoff model was first developed in Australia in 1974 (XP-Software, 1996) and has been applied widely on rural, urban and urbanizing catchments throughout Australia and in other countries. The general structure of the model is based on storage processes in the catchment and routing of generated runoff. For a complete description of the model refer to the model manual (XP-Software, 1996). The Pole Manjanigh catchment was subdivided into 49 sub-basins (refer Fig. 3). A RAFTS model of the catchment was assembled (refer Fig. 4). Curve Numbers were calculated from the main catchment outlet observed data by using Eqs. (1) and (2): 0:5
2.1. Location and physical characteristics of the region
S ¼ 5½P þ 2Q ð4Q2 þ 5PQÞ CN ¼
Pole Manjanigh is one of the large sub-catchments of the representative catchment of Roodzard (refer Fig. 2) in south of Iran located on Zagrous Range with an area of 284.6 km2 between 498520 and 508100 eastern longitude and between 318280 and 408310 northern latitude (Fig. 3). Using a GIS software, ILWIS (Integrated Land and Water Information System, 2001), spatial data for this sub-catchment including:
25; 400 S þ 254
Table 1 Physical characteristics of Poleh Manjanigh sub-catchment Area (km2) Stream length (km) Minimum elevation (m) Maximum elevation (m) Average slope (%) Time of concentration (h)
284.6 42.2 753 3113 45 3.6
Fig. 4. Hydrological model of Pole Manjanigh catchment.
(1) (2)
M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87 Table 2 Comparison of observed and predicted peak flows for various floods Stage
Polemanjenigh catchment 3
Calibration Verification Calibration Calibration Verification Calibration Verification Verification
3
Qpred (m /s)
Qobs (m /s)
158.5 44.7 26.6 57.0 16.0 56.0 16.9 92.8
158.0 44.5 26.8 56.0 15.0 54.0 16.5 99.0
Soil condition
Date
III III II III III III III III
86/11/7 82/12/13 84/11/14 79/12/14 79/12/12 79/12/2 79/12/7 77/11/11
where P is the rainfall depth (mm), Q the runoff depth (mm), S the maximum retention (mm) and CN is the Curve Number.
83
In RAFTS model there is no option for the input of CN. Hence CNs were estimated based on land use and soil type for 49 sub-basins from available tabulated values. Sub-basins’ CNs were converted to runoff coefficients, by using CN and runoff coefficient at the main catchment outlet, to be applicable in RAFTS model. This quantitative conversion is essential when runoff coefficient for the model is estimated for design rainfall. The model calibration and verification results are presented in Table 2 and Fig. 5. The comparison of three parameters of flood peak, time to peak and flood volume of simulated and observed hydrographs shows the accuracy of the simulation. The small difference in some cases may be due to using only one rainfall recording station. RME index and Student’s T-test are used for statistical assessment of the model results
Fig. 5. Comparison of observed and predicted hydrographs.
84
M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87
Table 3 Student’s T-test for evaluation and calibration of the model-Pole Manjanigh catchment H0 = H1 0.99 48.4 51.4 51.7
Result Significance level Standard deviation Upper limit Lower limit
Mendenhall et al. (1989, 1990). From Eqs. (3) and (4) the error percentage was calculated as 2.8. Furthermore the Student’s T-test results show that there is no significant difference between observed and simulated discharges at 99% level which indicates accuracy of calibration and evaluation processes (Table 3). When physical and hydrological parameters of a watershed become known in a mathematical model, it is possible to examine different scenarios and management practices and study the results before implementation of any costly control structures or land use change:
where Qobs is the observed discharge, Qpred the predicted discharge, REi the relative error and RME is the relative mean error. 2.3. Isochrones
n 1X RME ¼ REi n i1
REi ¼
Fig. 6. The Tc model in ArcView 3.2a environment.
(3)
jQobs Qpred j 100 Qobs
(4)
In order to apply the proposed methodology it is necessary to prepare isochronal map of the catchment. The map was prepared for the catchments using a distributed model of time of concentration, Tc model,
Fig. 7. Flow direction, maximum travel time and TC of each cell (Tabatabaei, 2003).
M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87
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Fig. 8. Spatial distribution of sub-catchments overlaid on isochrones-Pole Manjanigh catchment.
2.4. Spatial distribution of effective areas on flood peak
which has been designed and developed in ArcView (Tabatabaei, 2003) (refer Fig. 6). The Tc model is developed by using object oriented programming such as Visual C++ and Avenue. By inputting some preliminary data layers as Digital Elevation Model, DEM, and watershed stream network to the model, it can calculate time of concentration for each cell in the watershed. At first, the maximum travel time of each cell based on common equations such as Kirpich equation is calculated. Along the flow direction of the watershed, the maximum travel time of all cells is summed up and time of concentration to any sections of the watershed is calculated as isochrones (refer Figs. 7 and 8).
In order to prioritize sub-catchments for flood control, areas that have the greatest effect on flood peak to be identified. After determining the spatial location of sub-catchments and each isochronal area, their separate and cumulative contribution to the flood hydrograph is studied. Assuming either flood control or flood reduction measures in the sub-catchments located on each isochronal area, their proportions of the outlet hydrograph are deleted completely or modified using the catchment simulation model. The model is frequently run and all regions are tested for their affect
Table 4 The results of deletion of sub-catchments on isochrones and their affect on the flood peak Isochrones
Sub-catchment area (ha) Flood peak after operation (m3/s) Flood reduction (m3/s) Proportion of area (%) Flood reduction (%) Spatial efficiency
1
2
3
4
5
6
7
782 317.5
1060 316.6
5055 280
4088 267
6459 219
6733 269
4029 300
0.5 2.8 0.2 0.06
1.5 3.8 0.5 0.13
38 17.9 11.9 0.67
51 14.5 16 1.11
99 22.9 31.1 1.36
49 23.9 15.4 0.65
18 14.3 5.7 0.4
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M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87 Table 5 Flood peak reduction after prioritization of sub-catchments Sub-catchment no. Area (ha) Flood peak after control (m3/s) Flood peak reduction (m3/s) Proportion of area (%) Flood reduction (%) Spatial efficiency
Fig. 9. Comparison of the effects of flood control measures in each isochronal area-Pole Manjanigh catchment.
on flood peaks. For the purpose of this study flood peak with a return period of 100 years was analyzed. Table 4 shows the results of the modelling of different options. Table 4 shows the performance of sub-catchments in response to rainfall. Comparison of flood peaks shows that moving from the outlet towards middle sections of the catchment, the effect of flood control measures in sub-catchments on the flood peak is significantly increased. On the other hand, moving from middle sections to upper sections the effect of sub-catchments on the flood peak is reduced. Fig. 9 indicates the effectiveness of different group of sub-catchments lied on each isochronal area on flood peak. The comparison of spatial efficiency in Table 4, obtained by dividing the percentage of flood reduction by the percentage of the
I-26 to I-32, I-35 to I-36 5676 228 90 19.9 28.3 1.42
catchment area, indicates that sub-catchments located on the isochronal areas 1 and 2 near the outlet with spatial efficiency of 0.06 and 0.13 have the least effect on the flood peak while sub-catchments located on isochrones 5 have the highest efficiency 1.36 as the index and have the most effects on the outlet flood peak formation. The sub-catchments located on upper parts of the catchment with efficiencies of 0.65 and 0.4 have a moderate effect on the flood peak. 3. Results Although total area of sub-catchments of isochronal area 5 is smaller than that of 6 the spatial efficiency group of sub-catchments is twice as much as that of isochronal area 6 (Table 4). It is concluded that subcatchments located on isochronal areas 4 and 5 in Pole Manjanigh catchment with the highest spatial efficiencies have the highest priority for any flood control measures (refer Fig. 10). The results of simulation of the
Fig. 10. Comparison of spatial efficiency of sub-catchments in Pole Manjanigh catchment.
M. Roughani et al. / International Journal of Applied Earth Observation and Geoinformation 9 (2007) 79–87
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