Indirect estimation of Arvand River discharge using numerical modeling and remote sensing: A novel approach in water resources management

Einali, Abbas; Sadrinasab, Masoud; Akbarinasab, Mohammad; Azizpour, Jafar

doi:10.22098/mmws.2025.18232.1662

دانشگاه محقق اردبیلی

تعداد نشریات	31
تعداد شماره‌ها	471
تعداد مقالات	4,152
تعداد مشاهده مقاله	6,934,176
تعداد دریافت فایل اصل مقاله	4,680,042

	Indirect estimation of Arvand River discharge using numerical modeling and remote sensing: A novel approach in water resources management
مدل سازی و مدیریت آب و خاک
مقاله 17، دوره 5، شماره 4، 1404، صفحه 277-300 اصل مقاله (2.1 M)
نوع مقاله: پژوهشی
شناسه دیجیتال (DOI): 10.22098/mmws.2025.18232.1662
نویسندگان
Abbas Einali^* ¹؛ Masoud Sadrinasab²؛ Mohammad Akbarinasab³؛ Jafar Azizpour⁴
¹Assistant Professor of Physical Oceanography, Faculty of Environmental and Marine Sciences, University of Mazandaran, Mazandaran, Iran
²Associate Professor of Physical Oceanography, Department of Environmental Design, University of Tehran, Tehran, Iran
³Associate Professor of Physical Oceanography, Faculty of Environmental and Marine Sciences, University of Mazandaran, Mazandaran, Iran
⁴Assistant Professor of Physical Oceanography, Iranian National Institute for Oceanography and Atmospheric Science, Tehran, Iran
چکیده
The river discharge is the most critical parameter in the hydrologic cycle, and its measurement is vital considering climate change and water resource management. Due to local problems, the discharge of the Arvand River located in the Middle East (hot-dry climate) has not yet been measured directly. The Arvand River is considered the main source of freshwater inflow in the Persian Gulf and plays an essential environmental role in the northwest coastal zones of the Persian Gulf. For this reason, an indirect method was derived and used for the Arvand River discharge in this study. This method estimates the river discharge based on the river plume dimension. For this purpose, numerical modeling extracted the relationship between river discharge and river plume area in the first part. Thus, the Persian Gulf's temperature, salinity, and water circulation were modeled using FVCOM. In the following, the sensitivity of the river plume to the discharge and wind was investigated more accurately by applying fourteen different wind modes plus eight different discharge modes to the model. The numerical model results indicate that the river plume of Arvand is a "surface-advected plume" with a high sensitivity to wind fluctuations. Numerous experiments extracted the mathematical relation between the Plume Area and the River Discharge (PA-RD) within various wind conditions. A surface salinity of 37 psu determined the river plume border. The second step extracted the Arvand River plume (salinity plume) area using remote sensing techniques. The linear relationship between the sea surface salinity in-situ measurements and surface reflectance (SSS-SR) of Landsat TM5 satellite bands was obtained using a regression model at the river mouth in 1992. The surface salinity pattern at the Arvand River mouth was revealed by applying the SSS-SR relation to all of the Landsat pixels. Eventually, in 1992, the river plum (salinity plume) area was extracted, and then by substituting it in the PA-RD relation, the river discharge was estimated at 540 m³.s^-1. The present work is the first serious step toward studying the Arvand River discharge.
کلیدواژه‌ها
River Discharge؛ FVCOM؛ Landsat TM5؛ Arvand River؛ River Plume؛ Sea Surface Salinity

مراجع
References Abdullah, A. D., Gisen, J. I., Zaag, P. v. d., Savenije, H. H., Karim, U. F., Masih, I., & Popescu, I. (2016). Predicting the salt water intrusion in the Shatt al-Arab estuary using an analytical approach. Hydrology and earth system sciences, 20(10), 4031-4042. doi: 10.5194/hess-20-4031-2016 Al-Aesawi, Q., Al-Nasrawi, A. K., Jones, B. G., & Yang, S.-Q. (2021). Geomatic freshwater discharge estimations and their effect on saltwater intrusion in alluvial systems: a case study in Shatt Al-Arab estuary. Environmental Earth Sciences, 80, 1-15. doi: 10.1007/s12665-021-09945-4 Bricker, J. D., Okabe, I., & Nakayama, A. (2006). Behavior of a small pulsed river plume in a strong tidal cross-flow in the Akashi Strait. Environmental Fluid Mechanics, 6(3), 203-225. doi: 10.1007/s10652-006-9013-4 Chao, S.-Y. (1988). River-forced estuarine plumes. Journal of Physical oceanography, 18(1), 72-88. doi: 10.1175/1520-0485(1988)018<0072:RFEP>2.0.CO;2 Chao, S.-Y., & Boicourt, W. C. (1986). Onset of estuarine plumes. Journal of Physical oceanography, 16(12), 2137-2149. doi: 10.1175/1520-0485(1986)016<2137:OOEP>2.0.CO;2 Chen, C., Beardsley, R. C., & Cowles, G. (2006). An unstructured grid, finite-volume coastal ocean model: FVCOM user manual. SMAST/UMASSD. doi: 10.5670/oceanog.2006.92 Cheng, R. (2000). Defining hydrologic instrumentation for the 21st Century. search of techniques for monitoring river discharge. US Geol. Survey Remote-Sensing Workshop (Menlo Park, California, USA, Collins, C., & Macdonald, H. S. (2025). Modelling the variability and dynamics of river plumes in Hawke’s Bay, Aotearoa New Zealand. Frontiers in Marine Science, 12, 1536550. doi: 10.3389/fmars.2025.1536550 Duenwald, M. C., Abdih, M. Y., Gerling, M. K., Stepanyan, V., Al-Hassan, A., Anderson, G., Baum, M. A., Saksonovs, M. S., Agoumi, L., & Chen, C. (2022). Feeling the Heat: Adapting to Climate Change in the Middle East and Central Asia. International Monetary Fund. doi: 10.5089/9781513591094.087 Duvvuri, B., Gehring, J., & Beighley, E. (2024). Methodological evaluation of river discharges derived from remote sensing and land surface models. Scientific Reports, 14(1), 25653. doi: 10.1038/s41598-024-75361-w Eddin, M. H. S., Zahng, Y., Kollet, S., & Gall, J. (2025). RiverMamba: A State Space Model for Global River Discharge and Flood Forecasting. arXiv preprint arXiv:2505.22535. doi: 10.48550/arXiv.2505.22535 Flint, A., Flint, L., Curtis, J., & Boesch, C. (2011). A Preliminary Water Balance Model for the Tigris and Euphrates River System. In: USGS. Garvine, R. W. (1981). Frontal jump conditions for models of shallow, buoyant surface layer hydrodynamics. Tellus, 33(3), 301-312. doi: 10.3402/tellusa.v33i3.10717 Garvine, R. W. (1982). A steady state model for buoyant surface plume hydrodynamics in coastal waters. Tellus, 34(3), 293-306. doi: 10.3402/tellusa.v34i3.10813 Garvine, R. W. (1995). A dynamical system for classifying buoyant coastal discharges. Continental Shelf Research, 15(13), 1585-1596. doi: 10.1016/0278-4343(94)00065-U Global Runoff Data Centre (GRDC). World Meteorological Organization WMO and Federal Institute of Hydrology (BfG ). https://grdc.bafg.de/data/data_portal/ Gonçalves, H., Teodoro, A. C., & Almeida, H. (2012). Identification, Characterization and Analysis of the Douro River Plume From MERIS Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(5). doi: 10.1109/JSTARS.2012.2199740 Jafar, A., Vahid, C., Maziar, K., & Abbas, E. (2014). Study of the Physical Oceanographic Properties of the Persian Gulf, Strait of Hormuz and Gulf of Oman Based on PG-GOOS CTD Measurements. Journal of the Persian Gulf, 5(18), 12. https://www.researchgate.net/profile/Jafar-Azizpour/publication/285581886_Study_of_the_Physical_Oceanographic_Properties_of_the_Persian_Gulf_Strait_of_Hormuz_and_Gulf_of_Oman_Based_on_PG-GOOS_CTD_Measurements/links/568121d208ae1975838f62af/Study-of-the-Physical-Oceanographic-Properties-of-the-Persian-Gulf-Strait-of-Hormuz-and-Gulf-of-Oman-Based-on-PG-GOOS-CTD-Measurements.pdf. [In Persian] Kamidis, Sylaios, & Tsihrintzis. (2015). Nestos River plume dynamics under variable physical forcing. Πανελλήνια και Διεθνή Γεωγραφικά Συνέδρια, Συλλογή Πρακτικών, 549-566. http://geolib.geo.auth.gr/index.php/pgc/article/view/10460/10208 Kämpf, J., & Sadrinasab, M. (2006). The circulation of the Persian Gulf: a numerical study. Ocean Science, 2(1), 27-41. doi: 10.5194/os-2-27-2006 Karami, N. (2019). The modality of climate change in the Middle East: drought or drying up? J Interrupted Stud 2 (1): 118–140. In. Khorram, S. (1982). Remote sensing of salinity in the San Francisco Bay Delta. Remote Sensing of Environment, 12(1), 15-22. doi: 10.1016/0034-4257(82)90004-9 Klein, L., & Swift, C. (1977). An improved model for the dielectric constant of sea water at microwave frequencies. IEEE Journal of Oceanic Engineering, 2(1), 104-111. doi: 10.1109/JOE.1977.1145319 Koblinsky, C., Hildebrand, P., LeVine, D., Pellerano, F., Chao, Y., Wilson, W., Yueh, S., & Lagerloef, G. (2003). Sea surface salinity from space: Science goals and measurement approach. Radio Science, 38(4). doi: 10.1029/2001RS002584 KOMIJANE, F., NASROLLAHEE, A., NAHEID, S., & NAZARI, N. (2014). The Persian Gulf wind analysis using meteorological synoptic stations data. NIVAR Journal of Meteorological Organization, 38, 27-44. https://nivar.irimo.ir/article_13157_84e92d58f9b03ffe469397bb3e6fd9a6.pdf?lang=en. [In Persian] Kourafalou, V. H., Oey, L. Y., Wang, J. D., & Lee, T. N. (1996). The fate of river discharge on the continental shelf: 1. Modeling the river plume and the inner shelf coastal current. Journal of Geophysical Research: Oceans, 101(C2), 3415-3434. doi: 10.1029/95JC03024 Lagerloef, G. S., Swift, C. T., & Le Vine, D. M. (1995). Sea surface salinity: The next remote sensing challenge. Oceanography, 8(2), 44-50. doi: 10.5670/oceanog.1995.17 Legleiter, C. J., Grant, G., Bae, I., Fasth, B., Yager, E., White, D. C., Hempel, L., Harlan, M. E., Leonard, C., & Dudley, R. (2025). Remote sensing of river discharge based on critical flow theory. Geophysical Research Letters, 52(9), e2025GL114851. doi: 10.1029/2025GL114851 Liu, J. T., Chao, S.-Y., & Hsu, R. T. (1999). The influence of suspended sediments on the plume of a small mountainous river. Journal of Coastal Research, 1002-1010. https://www.jstor.org/stable/4299020 Ma, C., He, W., Zhang, G., Li, X., & Zhao, J. (2025). Spatiotemporal variations in Pearl River plume dispersion over the last decade based on VIIRS-derived sea surface salinity. Marine Pollution Bulletin, 218, 118179. doi: 10.1016/j.marpolbul.2025.118179 Mellor, G. L., & Yamada, T. (1982). Development of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics, 20(4), 851-875. doi: 10.1029/RG020i004p00851 Miller, J. L., Goodberlet, M. A., & Zaitzeff, J. B. (1998). Airborne salinity mapper makes debut in coastal zone. Eos, Transactions American Geophysical Union, 79(14), 173-177. doi: 10.1029/98EO00126 Osadchiev, A. (2015). A method for quantifying freshwater discharge rates from satellite observations and Lagrangian numerical modeling of river plumes. Environ. Res. Lett, 10. doi: 10.1088/1748-9326/10/8/085009 Ou, S., Zhang, H., Wang, D., & He, J. (2007). Horizontal characteristics of buoyant plume off the Pearl River Estuary during summer. Journal of Coastal Research, SI, 50, 652-657. https://www.jstor.org/stable/26481667 Reynolds, R. M. (1993). Physical oceanography of the Gulf, Strait of Hormuz, and the Gulf of Oman—Results from the Mt Mitchell expedition. Marine Pollution Bulletin, 27, 35-59. doi: 10.1016/0025-326X(93)90007-7 Robert Brakenridge, G., Cohen, S., Kettner, A. J., De Groeve, T., Nghiem, S. V., Syvitski, J. P. M., & Fekete, B. M. (2012). Calibration of satellite measurements of river discharge using a global hydrology model. Journal of Hydrology, 475, 123-136. doi: 10.1016/j.jhydrol.2012.09.035 Selch, D. (2012). Comparing salinity models in Whitewater Bay using remote sensing. FLORIDA ATLANTIC UNIVERSITY. https://search.proquest.com/openview/39474e9cd0d7ebba0cb8ee600e3427cf/1?pq-origsite=gscholar&cbl=18750 Smagorinsky, J. (1963). General circulation experiments with the primitive equations: I. The basic experiment. Monthly weather review, 91(3), 99-164. doi: 10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2 Swift, C. T., & Mcintosh, R. E. (1983). Considerations for microwave remote sensing of ocean-surface salinity. IEEE Transactions on Geoscience and Remote Sensing(4), 480-491. doi: 10.1109/TGRS.1983.350511 Tarya, A., Van der Vegt, M., & Hoitink, A. (2015). Wind forcing controls on river plume spreading on a tropical continental shelf. Journal of Geophysical Research: Oceans, 120(1), 16-35. doi: 10.1002/2014JC010456 Tayfehrostami, A., Ardalan, A. A., & Pourmina, A. H. (2021). River discharge monitoring using satellite missions: Sentinel-1, Sentinel-2, and Sentinel-3 (Case study: The Karun River, Iran). Earth Observation and Geomatics Engineering, 5(2), 96-111. doi: 10.22059/eoge.2022.336941.1112. [In Persian] Townend, J. (2013). Practical statistics for environmental and biological scientists. John Wiley & Sons. https://www.wiley.com/en-us/Practical+Statistics+for+Environmental+and+Biological+Scientists-p-9780471496656 UN-ESCWA, B. (2013). United Nations economic and social commission for western Asia; Bundesanstalt für Geowissenschaften und Rohstoffe. Inventory of Shared Water Resources in Western Asia, Beirut. https://www.unescwa.org/sites/default/files/pubs/pdf/e_escwa_sdpd_13_inventory_e.pdf Urquhart, E. A., Zaitchik, B. F., Hoffman, M. J., Guikema, S. D., & Geiger, E. F. (2012). Remotely sensed estimates of surface salinity in the Chesapeake Bay: A statistical approach. Remote Sensing of Environment, 123, 522-531. doi: 10.1016/j.rse.2012.04.008 Wang, Q., Guo, X., & Takeoka, H. (2008). Seasonal variations of the Yellow River plume in the Bohai Sea: A model study. Journal of Geophysical Research, 113(C8). doi: 10.1029/2007jc004555 Wiseman, W., & Garvine, R. (1995). Plumes and coastal currents near large river mouths. Estuaries, 18(3), 509-517. doi: 10.2307/1352368 Xing, J., & Davies, A. M. (1999). The effect of wind direction and mixing upon the spreading of a buoyant plume in a non-tidal regime. Continental Shelf Research, 19(11), 1437-1483. doi: 10.1016/S0278-4343(99)00025-4 Yankovsky, A. E., & Chapman, D. C. (1997). A simple theory for the fate of buoyant coastal discharges. Journal of Physical oceanography, 27(7), 1386-1401. doi: 10.1175/1520-0485(1997)027<1386:ASTFTF>2.0.CO;2.
آمار تعداد مشاهده مقاله: 458 تعداد دریافت فایل اصل مقاله: 224

سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب

پیوندهای مفید

آمار

Indirect estimation of Arvand River discharge using numerical modeling and remote sensing: A novel approach in water resources management