برآورد عمر مفید مخزن سد نگارستان با ترسیم منحنی هیپسومتریک به‌روش Strahler اصلاح‌شده و تصاویر ماهواره‌ای

نوع مقاله : مقالات پژوهشی

نویسندگان

• عبدالرضا ظهیری
• خلیل قربانی
• حامد فیض آبادی
• حسین شریفان

گروه مهندسی آب، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران

10.22067/jsw.2024.89646.1432

چکیده

مخازن سدها از منابع حیاتی تأمین­آب جوامع بشری محسوب می­شوند که آگاهی­داشتن از مقدار حجم آب ذخیره­شده در آن­ها امری ضروری است. استفاده از اشل و منحنی حجم-سطح-ارتفاع مخزن که به­کمک عملیات نقشه­برداری تهیه می­شود، روش معمول برای تخمین ظرفیت ذخیره­سازی مخازن می­باشد. با گذشت­زمان و وقوع رسوب­گذاری­های متعدد، منحنی حجم-سطح-ارتفاع مخزن تغییر می­کند که استفاده مجدد از آن نیازمند تصحیح این منحنی است. عملیات هیدروگرافی مخازن با­استفاده از ابزاری مثل اکوساندر روشی مرسوم برای تصحیح این منحنی­است که علاوه بر پرهزینه بودن، زمان­بر نیز می­باشد. در سال­های اخیر مطالعات مختلفی برمبنای سنجش­از­دور با هدف تخمین حجم آب­ذخیره­شده در مخازن، به­محاسبه سطوح آب برای ترسیم منحنی حجم-سطح-ارتفاع پرداخته­اند. اساس کار این مطالعات تفکیک پهنه­های آب­وخشکی به­کمک شاخص­های طیفی، محاسبه سطوح­آب و ترسیم منحنی­های سطح-ارتفاع مخازن با­استفاده از روابط خطی یا چندجمله­ای­ها می­باشند. محدودیت این روش­ها عدم­دقت مناسب روابط خطی یا چندجمله­ای در برازش منحنی سطح-ارتفاع مخزن برای نقاط ابتدایی و انتهایی بازه تغییرات عمق­آب است. در این پژوهش با هدف رفع­محدودیت روابط خطی و چند­جمله­ای برای پیش­بینی دقیق نقاطی از منحنی سطح-ارتفاع مخزن که داده­های مشاهداتی به­دلیل عدم وقوع موجود نیستند، از ترسیم منحنی هیپسومتریک به­روش استرالر اصلاح­شده استفاده شده است. با­استفاده از منحنی هیپسومتریک می­توان ظرفیت ذخیره­سازی مخزن بین سطوح­آب متوالی را محاسبه کرد و حجم­نهایی آب ذخیره­شده در آن­را به­دست آورد. براین اساس با مقایسه حجم آب ذخیره­شده در زمان فعلی و ظرفیت ذخیره­سازی طراحی­مخزن در زمان شروع بهره­برداری، نرخ رسوب­گذاری و عمر مفید مخزن سد نگارستان برآورد شد. نتایح نشان­داد که در بازه­زمانی 9 ساله، ظرفیت ذخیره مخزن در تراز سطح آب حدود 5/189 متر که معادل تراز تقریبی تاج سرریز می­باشد، از حدود 24 به 20 میلیون­متر مکعب کاهش یافته­است که بر­این اساس نرخ متوسط رسوبگذاری سالانه مخزن حدود 6/1 درصد برآورد شد. همچنین در این­مدت، تراز کف مخزن سد نگارستان به­دلیل انباشته­شدن رسوبات به‌طور متوسط حدود 10 متر افزایش داشته است و کمترین تراز کف­مخزن از 160 به حدود 170 متر رسیده است. مطابق نتایج به­دست­آمده از این پژوهش و با فرض ثابت بودن شرایط اقلیمی، عمرمفید مخزن سد نگارستان از ابتدای سال 1403 حدود 53 سال برآورد شد.

کلیدواژه‌ها

• سنجش‌از دور
• ظرفیت ذخیره
• لندست 8
• مخزن سد
• نرخ رسوب گذاری

موضوعات

• علوم آب

عنوان مقاله [English]

Assessment of Useful Life of Negarestan Reservoir Dam Using Hypsometric Curve by Modified Strahler Method and Satellite Imagery

نویسندگان [English]

• A. Zahiri
• Kh. Ghorbani
• H. Feiz Abady
• H. Sharifan

Water Engineering Department, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

چکیده [English]

Introduction
Reservoirs are crucial for water supply to human societies, making their proper and planned management essential. Dams serve multiple purposes, including urban water supply, agricultural irrigation, flood control, and hydroelectric power generation. In order to properly manage and monitor the consumption of these important reserves, it is inevitable to know their capacities. Using water stage and the reservoir's initial volume-area-elevation curve, which is prepared with the hydrographic operations, is a common method for estimating the storage capacity of reservoirs at different water levels. Over time, the occurrence of numerous sedimentations, often due to factors such as floods, can alter the initial volume-area-elevation curve of a reservoir, requiring it to be updated. Hydrographic operations, using tools like eco-sounders, are conventional methods for updating this curve; however, these methods are both expensive and time-consuming. In recent years, various studies have focused on remote sensing techniques aimed at estimating the volume of water stored in reservoirs, using water levels to establish the surface area-elevation curve. The basis of these studies is the separation of water-land masks using spectral indices, the calculation of water levels, and the development of reservoir surface area-elevation curves through linear or polynomial relationships. However, the main limitation of these methods is the inaccuracy of linear or polynomial relationships in fitting the surface area-elevation curves at the beginning and end points of the water stage change interval, which correspond to the empty or full states of the reservoir. This inaccuracy arises due to factors such as drought or flood events. In this research, the limitation of linear and polynomial relationships in accurately predicting the points of the reservoir surface area-elevation curves, where observational data are unavailable due to non-occurrence, was addressed by using the Modified Strahler method to draw the hypsometric curve. This method allows for the calculation of the storage capacity of the reservoir between successive water levels and the determination of the final volume of water stored in the reservoir. By comparing the volumes of water stored at the present and initial reservoir capacities, the sedimentation rate and the useful life of the Negarestan Dam reservoir were estimated.
 
Material and Methods
Negarestan Dam (Kabudval) is located on the Qarasu (Zarin Gol) river, 45 km east of Gorgan in the Golestan Province. This dam is used for purposes such as supplying urban water to Aliabad city and supplying water needed for the agricultural irrigation network of Qarasu. In this study, landsat8 satellite images were used to estimate the useful life of the Negarestan reservoir. The required images of the ROI were downloaded through the USGS database and pre-processed in Envi5.3 software. Using visible and infrared spectral bands, water indices NDWIMCFeeters, NDWIGao, MNDWI, AWEISh and TCWet were calculated to separate land-water masks. After evaluating the accuracy of the obtained water level results by comparing it with the initial volume-area-elevation curve of Negarestan reservoir, the MNDWI index was used as the most accurate index to calculate water levels. In this study, the modified Strahler method was used to obtain the hypsometric curve of the surface area-elevation of the reservoir, which has high accuracy in extrapolating the beginning and end points of the curve. By using the hypsometric curve, water levels were extracted for arbitrary water levels, and with the help of the prismoidal method, the volume between consecutive water levels was calculated. The sum of these volumes equaled the current storage capacity of the reservoir. To estimate the sedimentation rate of the Negarestan Dam reservoir, the current storage capacity was compared with the initial storage capacity in 2015. Based on this comparison, the useful life of the reservoir was accurately predicted.
 
Results and Discussion
Validation results for calculating water surface areas using NDWIMCFeeters, NDWIGao, MNDWI, AWEISh and TCWet water indices showed that the MNDWI index with an average water surface areas calculation error equal to 5% is more accurate than other indices. Therefore, the MNDWI index was used in this study. Additionally, the comparison of the volume of water stored in the Negarestan reservoir with its initial storage capacity at the time of operation revealed that, over a period of 9 years, the storage capacity of the reservoir (at a water level of approximately 189.5 meters), which is close to the overflow crest level, had significantly decreased. It has decreased from about 24 to 20 million cubic meters, based on which the average annual sedimentation rate of the reservoir was estimated, to about 1.6%. The results showed that in a period of 9 years, the average level of the bathymetry of Negarestan reservoir has increased by 10 meters due to the accumulation of sediments, and the minimum level of the batymetry has reached from 160 to about 170 meters. According to the statistics of the International Commission on Large Reservoirs (ICOLD), the average annual sedimentation rate of the world's reservoirs is reported to be about 0.95%, and the results show that this amount in the Nagaristan Dam reservoir is almost 2 times the average rate. It is universal. According to the results obtained from this research and assuming constant climatic conditions, the useful life of the Nagarestan dam reservoir was estimated to be about 53 years from the beginning of 2024.
 
Conclusion
Considering the increasing importance of water resources management, including dam reservoirs, this study employed a fast and cost-effective method based on remote sensing to calculate the volume of water stored in dam reservoirs and estimate their useful life. In addition to providing appropriate accuracy, this method was able to overcome the limitations of previous approaches in estimating the volume of accumulated sediment in the deeper parts of the reservoir. As a result, it offers a reliable tool for the effective management of water resources.

کلیدواژه‌ها [English]

• Dam reservoir
• Landsat8
• Remote sensing
• Sedimentation rate
• Storage capacity

©2024 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).

مراجع

1. Arsen, A., Crétaux, J. F., Berge-Nguyen, M., & Abarca del Rio, R. (2013). Remote sensing-derived bathymetry of Lake Poopó. Remote Sensing, 6(1), 407-420. https://doi.org/10.3390/rs6010407
2. Banasik, K., Hejduk, L., Krajewski, A., & Wasilewicz, M. (2021). The intensity of siltation of a small reservoir in Poland and its relationship to environmental changes. Catena, 204, 105436. https://doi.org/10.1016/j.catena. 2021.105436
3. Chen, C.Y., McGee, D., Woods, A., Pérez, L., Hatfield, R.G., Edwards, R.L., & Rodbell, D.T. (2020). U-Th dating of lake sediments: Lessons from the 700 ka sediment record of Lake Junín, Peru. Quaternary Science Reviews, 244, 106422. https://doi.org/10.1016/j.quascirev.2020.106422
4. Crist, E.P. (1985). A TM tasseled cap equivalent transformation for reflectance factor data. Remote Sensing of Environment, 17(3), 301-306. https://doi.org/10.1016/0034-4257(85)90102-6
5. Droujko, J., Sudha, S.H., Singer, G., & Molnar, P. (2023). Sediment source and sink identification using Sentinel-2 and (kayak-based) lagrangian river turbidity profiles on the Vjosa River. EGUsphere, 1-24. https://doi.org/10.5194/ egusphere-2023-156
6. Duan, Z., & Bastiaanssen, W.G.M. (2013). Estimating water volume variations in lakes and reservoirs from four operational satellite altimetry databases and satellite imagery data. Remote Sensing of Environment, 134, 403-416. https://doi.org/10.1016/j.rse.2013.03.010
7. Feizabady, H., Ghorbani, K., & Zahiri, R. (2024). Monitoring time series of reservoir water surface area changes using remote sensing approaches. Journal of Water and Soil Conservation.
8. Feyisa, G.L., Meilby, H., Fensholt, R., & Proud, S.R. (2014). Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery. Remote Sensing of Environment, 140, 23-35. https://doi.org/ 10.1016/J.RSE.2013.08.029
9. Gao, B.C., & Goetz, A.F. (1994). Extraction of dry leaf spectral features from reflectance spectra of green vegetation. Remote Sensing of Environment, 47(3), 369-374. https://doi.org/doi:10.1016/0034-4257(94)90104-X
10. Ghanbari, R., Tayfehrostami, A., Forouzanfar, M., & Tashakori, M. (2024). Using Optical Satellite Images and Satellite Altimetry Data to Estimate Volume Variations in Dams. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 48, 189-196. https://doi.org/10.5194/isprs-archives-XLVIII-4-W9-2024-189-2024
11. Gonzalez Rodriguez, L., McCallum, A., Kent, D., Rathnayaka, C., & Fairweather, H. (2023). A review of sedimentation rates in freshwater reservoirs: recent changes and causative factors. Aquatic Sciences, 85(2), 60. https://doi.org/10.1007/s00027-023-00960-0
12. Gourgouletis, N., Bariamis, G., Anagnostou, M.N., & Baltas, E. (2022). Estimating reservoir storage variations by combining Sentinel-2 and 3 measurements in the Yliki Reservoir, Greece. Remote Sensing, 14(8), 1860. https://doi.org/10.3390/rs14081860
13. Haregeweyn, N., Melesse, B., Tsunekawa, A., Tsubo, M., Meshesha, D., & Balana, B.B. (2012). Reservoir sedimentation and its mitigating strategies: a case study of Angereb reservoir (NW Ethiopia). Journal of Soils and Sediments, 12, 291-305. https://doi.org/10.1007/s11368-011-0447-z
14. Imanshoar, F., Hassanzadeh, Y., & Aalami, M.T. (2009). An introduction to environmental impacts of sedimentation and erosion due to dam’s construction. In Workshop on Reservoir Sedimentation Control, Regional Centre on Urban Flood Management, Karaj, Iran.
15. Jain, S.K., Singh, P., & Seth, S.M. (2002). Assessment of sedimentation in Bhakra Reservoir in the western Himalayan region using remotely sensed data. Hydrological Sciences Journal, 47(2), 203-212. https://doi.org/ 10.1080/02626660209492924
16. Kondolf, M., & Yi, J. (2022). Dam renovation to prolong reservoir life and mitigate dam impacts. Water, 14(9), 1464. https://doi.org/10.3390/w14091464
17. Lemma, H., Nyssen, J., Poesen, J., Assaye, H., Adgo, E., & Frankl, A. (2024). Impact of reservoir construction on the sediment budget of a downstream-linked freshwater lake. Hydrological Sciences Journal, 1-11. https://doi.org/ 10.1080/02626667.2024.2337052
18. Madadi, M.R. (2022). Reservoir sedimentation management: A state-of-the-art review. Journal of Applied Research in Water and Wastewater, 9(2), 194-202.
19. McFEETERS, S.K. (1996). The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17(7), 1425–1432. https://doi.org/10.3390/rs5073544
20. Nyikadzino, B., & Gwate, O. (2021). Estimation of Reservoir Capacity and Sedimentation Rate Using Direct and Indirect Methods. International Journal Earth Science Geophysics, 7, 045. https://doi.org/10.35840/2631-5033/1845
21. Ren, S., Zhang, B., Wang, W.J., Yuan, Y., & Guo, C. (2021). Sedimentation and its response to management strategies of the Three Gorges Reservoir, Yangtze River, China. Catena, 199, 105096. https://doi.org/10.1016/j.catena.2020.105096
22. Schwatke, C., Dettmering, D., & Seitz, F. (2020). Volume variations of small inland water bodies from a combination of satellite altimetry and optical imagery. Remote Sensing, 12(10), 1606. https://doi.org/10.3390/rs12101606
23. Sedláček, J., Bábek, O., Grygar, T.M., Lenďáková, Z., Pacina, J., Štojdl, J., & Elznicová, J. (2022). A closer look at sedimentation processes in two dam reservoirs. Journal of Hydrology, 605, 127397. https://doi.org/10.3390/ w14213481
24. Sekertekin, A., Abdikan, S., & Marangoz, A.M. (2018). The acquisition of impervious surface area from LANDSAT 8 satellite sensor data using urban indices: a comparative analysis. Environmental Monitoring and Assessment, 190, 1-13. https://link.springer.com/article/10.1007%2Fs10661-018-6767-3
25. Strahler, A.N. (1952). Hypsometric (area-altitude) analysis of erosional topography. Geological Society of Americabulletin, 63(11), 1117-1142. https://ui.adsabs.harvard.edu/link_gateway/1952GSAB...63.1117S/doi:10.1130/0016-7606(1952)63[1117: HAAOET]2.0.CO;2
26. Teixeira Pinto, C., Jing, X., & Leigh, L. (2020). Evaluation analysis of Landsat level-1 and level-2 data products using in situ measurements. Remote Sensing, 12(16), 2597. https://doi.org/10.3390/rs12162597
27. Tesfaye, A.T., Moges, M.A., Moges, M.M., Worqlul, A.W., Defersha, D.T., & Wassie, A.B. (2023). Reservoir sedimentation evaluation using remote sensing and GIS approaches for the reservoirs in the upper Blue Nile Basin. Sustainable Water Resources Management, 9(1), 23. https://doi.org/10.1007/s40899-022-00792-0
28. Vidya, A., Poompavai, V., & Hebbar, R. (2023). Geospatial techniques for assessment of loss in reservoir storage capacity a case study of tungabhadra reservoir. In 2023 IEEE India Geoscience and Remote Sensing Symposium (InGARSS) (pp. 1-4). IEEE. https://doi.org/10.2166/wpt.2023.188
29. Wagh, S., & Manekar, V. (2021). Assessment of reservoir sedimentation using satellite remote sensing technique (SRS). Journal of The Institution of Engineers (India): Series A, 102(3), 851-860. https://doi.org/10.1007/s40030-021-00539-8
30. Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing, 27(14), 3025-3033. https://doi.org/10.1080/01431160600589179
31. Yao, F., Minear, J.T., Rajagopalan, B., Wang, C., Yang, K., & Livneh, B. (2023). Estimating reservoir emendation rates and storage capacity losses using high‐resolution sentinel‐2 satellite and water level data. Geophysical Research Letters, 50(16), e2023GL103524. https://doi.org/10.1029/2023GL103524
32. Yulianto, F., Kushardono, D., Budhiman, S., Nugroho, G., Chulafak, G.A., Dewi, E.K., & Pambudi, A.I. (2022). Evaluation of the threshold for an improved surface water extraction index using optical remote sensing data. The Scientific World Journal, 2022(1), 4894929. https://doi.org/10.1155/2022/4894929