دوماه نامه

نوع مقاله : مقالات پژوهشی

نویسندگان

دانشگاه شهرکرد

چکیده

شماره منحنی (CN) یک پارامتر هیدرولوژیکی با مبنای تجربی است که جهت پیش­بینی مقدار رواناب مستقیم و یا مقدار بارش مازاد نفوذ یافته در خاک استفاده می­شود. از بین ویژگی­های سطح زمین، پوشش گیاهی یکی از عوامل مؤثر بر مقدار دبی اوج و حجم سیلاب می­باشد. یکی از شاخص­های معرف وضعیت پوشش گیاهی، شاخص سطح برگ است که از طریق اطلاعات سنجش از دور در دسترس است. در این مطالعه با هدف بررسی رابطه شاخص سطح برگ و شماره منحنی در مقیاس حوضه آبخیز، هیدروگراف سیلاب حوضه آبخیز کره­بس با استفاده از مدل HEC-HMS شبیه­سازی و مقادیر شماره منحنی سالانه حوضه برآورد شد. فایل­های رستری شاخص سطح برگ نیز از پایگاه اینترنتی مودیس تهیه و برای برقراری رابطه­­ای بین شماره منحنی حوضه و شاخص سطح برگ استفاده شد. دقت شبیه­سازی هیدروگراف با استفاده از ضریب کارایی نش- ساتکلیف 72/0 نشان داد که رابطه به­دست آمده با تابع انتقال، شماره منحنی حوضه مورد مطالعه را به خوبی برآورد می­کند. همچنین نتایج این تحقیق نشان داد که با افزایش شاخص سطح برگ، مقدار شماره منحنی کاهش می­یابد. این نشان می­دهد که افزایش پوشش گیاهی در منطقه موجب کاهش دبی اوج و حجم سیلاب می­شود. مقایسه کلاس­های شیب نیز مبین آن است که این عامل توپوگرافی نیز بر دبی اوج و حجم سیلاب اثر مستقیم دارد.

کلیدواژه‌ها

عنوان مقاله [English]

Curve Number Estimation Based on the Leaf Area Index (A Case Study: Kareh-BasBasin)

نویسندگان [English]

  • Khodayar Abdollahi
  • Somayeh Bayati

Shahrekord University

چکیده [English]

Introduction: Curve number (CN) is a hydrologic parameter used to predict the direct runoff depth or the excessive rainfall that infiltrates into the soil. This parameter, which indicates surface water retention, is very important in the processes relating to flooding. Vegetation of the region is a major factor affecting peak flow and flood volume. The peak flow is highly influenced by the land surface characteristics, for example at the time that vegetation coverage is naturally low or while vegetated areas are decreasing, the peak discharges increase as well. In this study, the flood hydrograph of Kareh-Bas Basin was simulated using the HEC-HMS model. The simulation was used to estimate the values of the annual curve number in the basin of interest.
Materials and Methods: Model data requirements for this study were temperature, precipitation, and evapotranspiration and discharge time series. The model was calibrated for the period 2000-2010. Then, the model was implemented independently for simulating of rainfall-runoff for each year without any change in the optimized parameters. The model was calibrated only by changing curve number. The average curve number of the basin for each year was computed using the weighted mean method. The MODIS leaf area index raster maps were downloaded from the Modis site.  The maps were converted into ASCII format for spatial statistics and calculating the monthly spatial average. The correlation between the curve number and leaf area index was investigated by a nonlinear curve fitting. This lead to the development of a curve number as a function of the vegetation cover for each year. Finally, the accuracy of the developed relationship was investigated using the Nash-Sutcliffe efficiency coefficient by comparing the curve number obtained from the HEC-HMS model and the simulated values from the new relationship.
Results and Discussion: The obtained Nash-Sutcliff coefficient of 0.58 showed that the HEC-HMS model was capable to simulate the flood hydrograph with relatively good accuracy. The sub-basin spatial mean showed that the sub-basins 1 and 2 take the highest curve number values. This indicates that surface water retention in these sub-basins is less than the other sub-basins, which may lead to a sharper hydrological response or flood. In sub-basins 3 and 4, where vegetation density is higher thus land use acts as a predominant factor in hydrologicalbehavior of these sub-basins, the curve number was lower. The study shows the hydrological response depends on the temporal variation of the land cover, for instance in 2010, when the leaf area index increased by a factor of 1.4, the curve number has decreased to 47. As it is predictable with decreasing vegetation the peak discharge and flood volume was increasing. We found a direct nonlinear relationship between basin scale Leaf Area Index and Curve Number with a correlation coefficient of 0.7, indicating that the variation of the curve number is a function of the leaf area index. The developed model allows calculating curve number values based on the remotely sensed leaf area index. This relationship can be used as an auxiliary function for capturing the vegetation changes and dynamics. The accuracy of the derived equation was evaluated in terms of Nash-Sutcliffe's efficiency coefficient. A value of Nash-Sutcliff coefficient of 0.72 showed that this relationship is good enough for calculating basin or sub-basin curve number values capturing the dynamics of leaf area index.
Conclusions: The obtained Nash-Sutcliff efficiency coefficient from HEC-HMS showed that the model was able to simulate the flood hydrograph of Kareh-bas basin with relatively good accuracy. However, the visual interpretation shows there is a weakness in the simulation of the falling limb of the simulated hydrographs. This may be an indication that the drainage of stored water at the basin was not well-simulated by the model. In general, it can be said that peak discharge and flood volume were under-estimated. By increasing the curve number, the peak discharge values also were increasing. The pair data for spatially weighted values for curve number and averaged annual leaf area index showed that an increase in leaf area index leads to a lower value in obtained curve number. This may result in lower peak discharge and volume of the flood. Such relationships may be taken as a measure for flood control. Meanwhile remotely sensed leaf area index products may be considered as an opportunity to capture the dynamics of the land cover.

کلیدواژه‌ها [English]

  • Flood
  • HEC-HMS
  • simulation
  • Vegetation cover
1. Abu-hashim M., Mohamed E., and Belal A.E. 2015. Identification of potential soil water retention using hydric numerical model at arid regions by land-use changes. International Soil and Water Conservation Research, 3(4):305-315.
2. Arekhi S. 2012. Runoff modeling using HEC-HMS model (Case study: Khan Watershed, Iran). International Journal of Agriculture and Crop Science, 4(23):1807-1811.
3. Choudhari K., Panigrahi B., and Chandra P. 2014. Simulation of rainfall-runoff process using HEC-HMS model for Balijore Nala watershed, Odisha, India. International Journal of Geomatics and Geosciences, 5(2):253-265.
4. Chow V.T., Maidment D.R., and Mays L.W. 1988. Applied hydrology, New York: McGraw-Hill.
5. Coyea M.R., and Margolis H.A. 1994. The historical reconstruction of growth efficiency and its relationship to tree mortality in balsam fir ecosystems affected by spruce bud worm. Canadian Journal of Forest Research, 24:2208-2221.
6. Dai X., and Khorram S. 1999. A feature-based image registration algorithm usingimproved chain-code representation combined with invariant moments. IEEETransactions on Geoscience and Remote Sensing, 37(5): 2351-2362.
7. Faridhosseini A., Astaraei A.R., Sanaeinejad S.H.,and Mirhoseini Moosavi P. 2012. Estimation of Leaf Area Index Using IRS Satellite Images. Iranian Journal of Field Crops Research, 10(3):577-582. (In Persian)
8. Gholami V., Bashirgonbad M., Azodi M., and Jokar Sarhangi E. 2010. The influence of land use changes on intensifying runoff generation and flood hazard in Kasilian Watershed. Iran-Watershed Management Science and Engineering, 3(9):55-58. (In Persian with English abstract)
9. Gitau M.W., and Chaubey I. 2010. Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds. Water, 2: 849-871.
10. Hamdami Gh., Sheidai Karkaj E., and Akbari Majdar H. 2012. Constructing curve number map (CN) for Maraveh-Tappeh Watershed using GIS. Journal of Conservation and Utilization of Natural Resources, 1(3):1-8. (In Persian with English abstract)
11. Hawkins R.H. 1993. A symptotic determination of runoff curve numbers from data. Journal of Irrigation and Drainage Engineering, 119(2):334-345.
12. Hawkins R.H., Ward T. J., Woodward D. E., and Van Mullem J. A. 2008. Curve number hydrology: State of the practice. American Society of Civil Engineering, Washington.
13. King K.W., and Balogh J.C. 2008. Curve numbers for golf course watersheds. Transactions of the American Society of Agricultural and Biological Engineers, 51(3):987-996.
14. Kosmas C., Danalatos N.G., and Gerontidis St. 2000. The effect of land parameters on vegetation performance and degree of erosion under Mediterranean conditions. Catena, 40(1):3-17.
15. Krause P, Boyle D.P., and Base F. 2005. Comparison of different efficiency criteria for hydrological model assessment. Advances in Geosciences, 5:89-97.
16. Liu R., Chen J.M., Liua F.,Deng R., and Sunk D. 2007. Application of a new leaf area index algorithm to China’s land mass using MODIS data for carbon cycle research. Journal of Environmental Management, 85:649-658.
17. Mahdavi M. 2002. Applied hydrology, Tehran University press. (In Persian)
18. Mathevet T., Michel C., Andreassian V., and Perrin C. 2006. A bounded version of the Nash-Sutcliffe criterion for better model assessment on large sets of basins. International Association of HydrologicalSciences Publication, 307:211-219.
19. Melesse A.M., and Shih S.F. 2002. Spatially distributed storm runoff depth estimation using Landsat images and GIS. Computers Electronics in Agriculture, 37(1):173-183.
20. Michel C., Andreassian V., and Perrin C. 2005. Soil conservation service curve number method: How to mend a wrong soil moisture accounting procedure?. Water Resource Research, 41(2):1-6.
21. Mishra S.K., and Singh V.P. 2006. A relook at NEH-4 curve number data and antecedent moisture condition criteria. Hydrological Processes, 20(13):2755-2768.
22. Nash JE., and Sutcliffe JV. 1979. River flow forecasting through conceptual models 1: a discussion of principles. Journal of Hydrology, 10:282-290.
23. Nastiti K.D., Kim Y., Jung K., and An H. 2015. The application of Rainfall-Runoff-Inundation (RRI) model for inundation case in upper Citarum Watershed, West Java-Indonesia. Procedia Engineering, 125:166-172.
24. Oleyiblo J.O., and Li Z.J. 2010. Application of HEC-HMS for flood forecasting in Misai and Wan’an catchments in China. Water Science and Engineering, 3(1):14-22.
25. Pandey A., and Sahu A.K. 1999. Generation of curve number using remote sensing and Geographic Information system, north eastern regional institute of science and technology, Department of agricultural engineering, India. Letter 2. 15p.
26. Ponce V.M., and Hawkins R.H. 1996. Runoff curve number: has it reached maturity? Journal of Hydrologic Engineering, 1(1):11-18.
27. Reshma T., Venkata Reddy K., and Deva P. 2013. Simulation of Event Based Runoff Using HEC-HMS model for an Experimental Watershed. International Journal of Hydraulic Engineering, 2(2):28-33.
28. Romero P., Castro G., Gomez J.A., and Fereres J.A. 2007. Curve number values for olive orchards under different soil moisture management. Soil Science Society of America Journal, 71(6):1758-1769.
29. Saghafian B., Farazjoo H., Sepehr A., and Najafinejad A. 2006. Evaluation of landuse effect on watershed flooding of Golestan Dam. Water Resource Researches of Iran, 3(1):18-28. (In Persian with English abstract)
30. Sellers P.J., Randall D.A., Collatz G.J., Berry J.A.,Field C.B.,Dazlich D.A., Zhang C., Collelo G.D, and Bounoua L. 1996. A revised land surface parameterization (SiB2) for atmospheric GCMs, Part I: Model Formulation. Journal of Climate, 9:676-705.
31. Sharma K.D. 1998. The hydrological indicators of desertification. Journal of Arid Environments, 39:121-132.
32. Shokri S., Behnia A.A., Radmanesh F., and Akhond Ali A.M. 2012. Watershed flood hydrograph estimation using HEC-HMS and Geographic Information System (case Study: Idanak watershed). Journal of Watershed Management Research, 3(5):63-80. (In Persian with English abstract)
33. Sumarauw J.S.F., and Ohgushi K. 2012. Analysis on curve number, land use and land cover changes and the impact to the peak flow in the Jobaru River Basin, Japan. International Journal of Civil and Environmental Engineering, 12(02):17-23.
34. Wanielista M.P. 1990. Hydrology and Water Quantity Control. Wiley, New York.
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