| تعداد نشریات | 286 |
| تعداد نشریات سازمان | 84 |
| تعداد شماره‌ها | 3,012 |
| تعداد مقالات | 33,667 |
| تعداد مشاهده مقاله | 44,681,199 |
| تعداد دریافت فایل اصل مقاله | 36,211,962 |
ارزیابی مدل هیدرولوژیکی VIC در شبیهسازی رواناب با استفاده از پایگاه داده‌‌های بارش اقلیمی، مطالعه موردی: حوزه آبخیز حبله‌رود | ||
| مهندسی و مدیریت آبخیز | ||
| دوره 16، شماره 2، تیر 1403، صفحه 224-243 اصل مقاله (1.91 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijwmse.2023.362817.2027 | ||
| نویسندگان | ||
| حسین صالحی1؛ سعید قره چلو* 2؛ سعید گلیان3؛ محمدرضا رنجبری4؛ عماد محجوبی5 | ||
| 1دانشجوی دکتری، دانشکده فیزیک، دانشگاه ترنتو، ترنتو، ایتالیا | ||
| 2استادیار گروه نقشه‌برداری، دانشکده مهندسی عمران، دانشگاه صنعتی شاهرود، شاهرود، ایران | ||
| 3محقق ارشد، موسسه SKR، کاردیف، انگلستان | ||
| 4دانشجو دکتری، دانشکده عمران، دانشگاه اصفهان، اصفهان، ایران | ||
| 5استادیار گروه مهندسی آب و محیط‌زیست، دانشکده مهندسی عمران، دانشگاه صنعتی شاهرود، شاهرود، ایران | ||
| چکیده | ||
| مقدمه مدل‌سازی هیدرولوژیکی، جهت شبیهسازی رواناب برای یک دوره بلندمدت در راستای مطالعات اقلیمی از اهمیت بالایی در مدیریت منابع آب حوزه آبخیز برخوردار است. این دسته از شبیه‌‌سازی‌‌ها، نیاز به داده‌‌های ورودی با طول دوره بلندتر دارد که در مناطق دورافتاده و صعب‌العبور که دارای کمبود داده هستند، قابل‌انجام نیست. داده‌‌های بارش اقلیمی با طول دوره بلند در دو دهه اخیر کارایی زیادی از خود نشان داده‌‌اند. مواد و روش‌ها در این پژوهش، با استفاده از سه داده بارش اقلیمی APHRODITE، PERSIANN-CDR و ERA5-Land و داده بارش درون‌یابی شده ایستگاه‌‌های باران‌‌سنجی با روش (IDW) شبیهسازی رواناب در حوزه آبخیز حبله‌رود در دوره 1996-1992 پرداخته شد. مدل هیدرولوژیکی نیمه توزیعی (VIC) در این مطالعه، در حالت تعادل آبی با هدف بهینه‌‌سازی ضریب کارایی (KGE)مورد استفاده قرار گرفت. جهت ارزیابی دقت داده‌‌های بارش هر پایگاه داده در مقیاس سلول، از روش IDW استفاده شد. نتایج و بحث نتایج نشان داد پایگاه APHRODITE بیشترین دقت و PERSIANN-CDR کمترین دقت را داشته است. همچنین، نتایج شبیهسازی رواناب نشان داد مدل هیدرولوژیکی VIC در مقیاس روزانه و ماهانه توانایی مناسبی در شبیهسازی رواناب دارد. میزان شاخص کارایی KGE رواناب شبیه‌‌سازی‌‌شده روزانه با استفاده از بارش مشاهداتی در دوره واسنجی برابر با 78/0 و در دوره صحت‌‌سنجی برابر با 0.76 بود. نتایج ارزیابی رواناب شبیهسازی شده توسط داده‌‌های بارش اقلیمی نشان داد، داده بارش ماهواره‌‌ای PERSIANN-CDR باوجود اینکه دقت کمتری در تشخیص میزان بارش داشت، عملکرد بهتری در شبیهسازی رواناب دارد. به‌‌طوری که میزان KGE برای این داده در مقیاس روزانه در دوره واسنجی برابر با 0.64 و در دوره صحت‌‌سنجی برابر با 0.77 به دست آمد. داده بارش APHRODITE که یک داده بارش بر اساس ایستگاه‌‌های زمینی است، با شاخص KGE برابر با 0.62 در دوره واسنجی و 0.75 در دوره صحت‌‌سنجی در رده دوم قرار گرفت. داده بارش ERA5-Land که یک داده بازتحلیل شده است در رده سوم قرار گرفت که شاخص KGE برابر با 0.5 در دوره واسنجی و 0.66 در دوره صحت‌‌سنجی بود. نتیجه‌گیری نتایج این پژوهش نشان داد، داده‌‌های بارش اقلیمی در حوضه‌های فاقد شبکه منظم یا با طول دوره کوتاه‌مدت از داده‌‌ها، می‌‌توانند عملکرد مناسبی و مشابه با داده‌‌های بارش ایستگاه‌‌های زمینی داشته و در مطالعات مدیریت حوزه آبخیر با هزینه کم و دقت مناسب مورد استفاده قرار گیرند. | ||
| کلیدواژه‌ها | ||
| مدل بارش-رواناب VIC؛ داده‌‌های بارش جهانی؛ درون‌یابی IDW؛ APHRODITE؛ ERA5-Land؛ PERSAINN-CDR | ||
| عنوان مقاله [English] | ||
| Evaluation of VIC Hydrological Model in Runoff Simulation using Climatic Precipitation Datasets, case study: Hableroud Watershed | ||
| نویسندگان [English] | ||
| Hossein Salehi1؛ Saeid Gharechelou2؛ Saeed Golian3؛ Mohammad Reza Ranjbari4؛ Emad Mahjoobi5 | ||
| 1hD Student, Department of Physics, University of Trento, Trento, Italy | ||
| 2Assistant Professor, Department of Surveying, Faculty of Civil Engineering, Shahrood University of Technology, Shahrood, Iran | ||
| 3Senior Researcher, SKR, Cardiff, UK | ||
| 4PhD Student, Department of Water Management, Faculty of Civil Engineering, Isfahan University, Isfahan, Iran | ||
| 5Assistant Professor, Department of Water and Environmental Engineering, Faculty of Civil Engineering, Shahrood University of Technology, Shahrood, Iran | ||
| چکیده [English] | ||
| Introduction The rapid growth of the global population has led to a significant surge in water consumption across various sectors such as agriculture, industry, and domestic use. This heightened demand for water has profound implications, particularly in ensuring food security, meeting industrial needs, and providing safe drinking water. However, alongside this population growth, climate change has emerged as a critical factor, altering precipitation patterns and exacerbating water scarcity issues. In response to these challenges, there is a growing need to identify and manage accessible water resources effectively. This involves understanding the complex interactions between different components of the hydrological cycle, including surface water, groundwater, soil moisture, and atmospheric water. Hydrological models have emerged as valuable tools in this regard, offering insights into water availability, flow patterns, and quality assessment. These models play a crucial role in various aspects of water resource management, including mitigating environmental impacts, managing floods, and predicting future water stress scenarios. Additionally, they facilitate the analysis of watershed-scale dynamics and provide a basis for informed decision-making. Global Hydrological Models (GHMs) have gained prominence due to their ability to capture the interconnectedness of water systems across different regions. They enable researchers to assess and predict hydrological processes on a large scale, contributing to a more comprehensive understanding of water resource dynamics. Recent studies have focused on evaluating the performance of hydrological models, such as the Variable Infiltration Capacity (VIC) model, in simulating river discharge, soil moisture, and precipitation patterns. These evaluations often utilize various data sources, including satellite imagery, to validate model outputs and improve their accuracy. Moreover, the integration of advanced optimization algorithms, such as NSGA-II, enhances the modeling process by optimizing model parameters and improving simulation results. In light of limited ground station data in extensive watersheds, researchers increasingly rely on long-term weather data and modeling techniques to bridge data gaps and improve the accuracy of hydrological predictions. Overall, ongoing research efforts aim to refine hydrological modeling approaches, integrate diverse data sources, and develop robust strategies for sustainable water resource management in the face of growing population pressures and climate uncertainties. Materials and methods The Heblehroud Watershed, situated in the southern part of the Central Alborz mountain range, covers approximately 326,991 hectares and lies between coordinates 52° 13' to 53° 13' East longitude and 35° 17' to 35° 58' North latitude. It spans across Tehran, Mazandaran, and Semnan provinces. Mount Sefidab, with an elevation of 4047 meters, marks its highest point. The region features a semi-arid climate, receiving 272 mm of annual rainfall predominantly in winter and spring. The Heblehroud River, originating from the northern mountains, serves as the main drainage outlet. The semi-distributed hydrological model (VIC) was employed in this study to optimize the coefficient of efficiency (KGE) in simulating runoff on daily and monthly scales in the state of water balance. The study validated the VIC model using data from the Bonekooh station and applied the NSGA-II optimization algorithm to calibrate soil parameters from 1992 to 1996, considering the impact of watershed management. Soil data were obtained from the HWSD database available on the FAO website and categorized into 36 classes based on physical and chemical soil properties. Land cover data were sourced from the MODIS satellite database and classified into 17 categories according to the IGBP standard. Elevational bands are crucial in the VIC hydrological model for assessing soil water pressure distribution and surface runoff. In the Heblehroud basin, elevation differences can reach several thousand meters, impacting flow estimation. Therefore, using elevation bands derived from SRTM data is essential for accurate simulation. The accuracy of precipitation data from each database at the cell scale was evaluated using the IDW method. Results and discussion The results indicated that the APHRODITE database had the highest accuracy, while PERSIANN-CDR had the lowest. Additionally, the runoff simulation results demonstrated that the VIC hydrological model performed well in simulating daily and monthly runoff. The KGE efficiency index for simulated daily runoff was 0.78 during the calibration period and 0.76 during the validation period. Evaluating the simulated runoff using climatic precipitation data revealed that PERSIANN-CDR satellite precipitation data was less accurate in detecting precipitation amounts but performed better in simulating runoff. The KGE for this data on a daily scale was 0.64 during the calibration period and 0.77 during the validation period. The KGE index for APHRODITE precipitation data based on ground stations ranked second, with values of 0.62 and 0.75 during the calibration and validation periods, respectively. ERA5-Land precipitation data, which is reanalyzed data, ranked third with a KGE index of 0.50 during the calibration period and 0.66 during the validation period. Conclusions These findings indicate that climatic precipitation data can be effectively utilized in watershed management studies with low cost and appropriate accuracy, particularly in basins lacking a regular network or long-term data availability. | ||
| کلیدواژه‌ها [English] | ||
| APHRODITE, ERA5-Land, Global precipitation data, IDW, PERSAINN-CDR, VIC Rainfall-Runoff Model | ||
| مراجع | ||
|
Ashouri, H., Hsu, K.-L., Sorooshian, S., Braithwaite, D.K., Knapp, K.R., Cecil, L.D., Nelson, B.R., Prat, O.P., 2015. PERSIANN-CDR: daily precipitation climate data record from multisatellite observations for hydrological and climate studies. Bull. America. Meteorol. Soci. 96(1), 69-83. Dang, T.D., Vu, D.T., Chowdhury, A.F.M.K., Galelli, S., 2020. A software package for the representation and optimization of water reservoir operations in the VIC hydrologic model. Environ. Model. Soft. 126, 104673. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T., 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evolu. Comput. 6(2), 182-197. Dwarakish, G., Ganasri, B., 2015. Impact of land use change on hydrological systems: A review of current modeling approaches. Cogent Geosci. 1(1), 1115691. Ghoreishi GharahTikan, S., Gharechelou, S., Mahjoobi, E., Golian, S., Salehi, H., 2022. Evaluation of available surface water resources in Qarah Tikan border basin using satellite products and GIS. Water Soil Manage. Model. 2(1), 1-13. Gupta, H.V., Kling, H., Yilmaz, K.K., Martinez, G.F., 2009. Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling. J. Hydrol. 377(1-2), 80-91. Islam, M.S., Oki, T., Kanae, S., Hanasaki, N., Agata, Y., Yoshimura, K., 2007. A grid-based assessment of global water scarcity including virtual water trading. Water Resou. Manage. 21(1), 19-33. Kauffeldt, A., Wetterhall, F., Pappenberger, F., Salamon, P., Thielen, J., 2016. Technical review of large-scale hydrological models for implementation in operational flood forecasting schemes on continental level. Environ. Model. Soft. 75, 68-76. Li, Q., Yu, X., Xin, Z., Sun, Y., 2013. Modeling the effects of climate change and human activities on the hydrological processes in a semiarid watershed of loess plateau. J. Hydrol. Engin. 18(4), 401-412. Liang, J., Liu, Q., Zhang, H., Li, X., Qian, Z., Lei, M., Li, X., Peng, Y., Li, S., Zeng, ., 2020. Interactive effects of climate variability and human activities on blue and green water scarcity in rapidly developing watershed. J. Cleaner Produc. 265, 121834. Liang, X., Lettenmaier, D.P., Wood, E.F., Burges, S.J., 1994. A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geophysi. Res.: Atmos. 99(D7), 14415-14428. Markert, K.N., Griffin, R.E., Limaye, A S., McNider, R.T., 2018. spatial modeling of land cover/land use change and its effects on hydrology within the Lower Mekong Basin. In Land-Atmospheric Research Applications in South and Southeast Asia (pp. 667-698). Springer. Martin, E., Gascoin, S., Grusson, Y., Murgue, C., Bardeau, M., Anctil, F., Ferrant, S., Lardy, R., Le Moigne, P., Leenhardt, D., 2016. On the use of hydrological models and satellite data to study the water budget of river basins affected by human activities: examples from the Garonne Basin of France. Surv. Geophys. 37, 223-247. Mauser, W., Bach, H., 2009. PROMET–Large scale distributed hydrological modelling to study the impact of climate change on the water flows of mountain watersheds. J. Hydrol. 376(3-4), 362-377. Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., 2021. ERA5-Land: A state-of-the-art global reanalysis dataset for land applications. Earth Sys. Sci. Data 13(9), 4349-438. Nachtergaele, F., Velthuizen, H., Verelst, L., Wiberg, D., 2009. Harmonized World Soil Database (HWSD). Food and Agriculture Organization of the United Nations, Rome. Nepal, S., Krause, P., Flügel, W.A., Fink, M., Fischer, C., 2014. Understanding the hydrological system dynamics of a glaciated alpine catchment in the Himalayan region using the J2000 hydrological model. Hydrolo. Proces. 28(3), 1329-1344. Sabzi, H.Z., Moreno, H.A., Fovargue, R., Xue, X., Hong, Y., Neeson, T.M., 2019. Comparison of projected water availability and demand reveals future hotspots of water stress in the Red River basin, USA. J. Hydrol.: Regional Studies 26, 100638. Salehi, H., Sadeghi, M., Golian, S., Nguyen, P., Murphy, C., Sorooshian, S., 2022. The Application of PERSIANN Family Datasets for Hydrological Modeling. Remote Sens. 14(15), 3675. Sayama, T., McDonnell, J.J., 2009. A new time‐space accounting scheme to predict stream water residence time and hydrograph source components at the watershed scale. Water Resou. Res. 45. Schulzweida, U., Kornblueh, L., Quast, R., 2006. CDO user’s guide. Climate Data Operators, Version, 1(6), 205-209. Shayeghi, A., Azizian, A., Brocca, L., 2020. Reliability of reanalysis and remotely sensed precipitation products for hydrological simulation over the Sefidrood River Basin, Iran. Hydrol. Sci. J. 65(2), 296-310. Strahler, A.H., Muller, J., Lucht, W., Schaaf, C., Tsang, T., Gao, F., Li, X., Lewis, P., Barnsley, M.J., 1999. MODIS BRDF/albedo product: algorithm theoretical basis document version 5.0. MODIS documentation, 23(4), 42-47. Sulla-Menashe, D., Friedl, M.A., 2018. User guide to collection 6 MODIS land cover (MCD12Q1 and MCD12C1) product. USGS: Reston, VA, USA, 1-18. Wang, W., Shao, Q., Yang, T., Peng, S., Xing, W., Sun, F., Luo, Y., 2013. Quantitative assessment of the impact of climate variability and human activities on runoff changes: a case study in four catchments of the Haihe River basin, China. Hydrolo. Proces. 27(8), 1158-1174.
| ||
|
آمار تعداد مشاهده مقاله: 459 تعداد دریافت فایل اصل مقاله: 190 |
||