مدل‌سازی تغییرات مکانی – زمانی بارش به منظور استفاده در مدل‌های دینامیکی و توزیعی بارش – رواناب

پارسامهر, امیرحسین; سلاجقه, علی; خلیقی سیگارودی, شهرام; احمدآلی, خالد

doi:10.22059/jrwm.2023.360794.1712

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه احیاء مناطق خشک و کوهستانی، دانشکده منابع طبیعی، دانشگاه تهران، تهران، ایران

10.22059/jrwm.2023.360794.1712

چکیده

هدف از پژوهش حاضر ارائه رویکردی برای مدل‌سازی تغییرات مکانی–زمانی بارش است که می‌تواند به عنوان ورودی مدل‌های بارش – رواناب مورد استفاده قرار گیرد. برای این منظور از داده‌های رگبار چهار ایستگاه پایش باران در حوزه آبخیز پسکوهک، واقع در 27 کیلومتری غرب شیراز، استفاده شد. پنج پارامتر ارتفاع از سطح دریا، درجه شیب، جهت شیب، طول و عرض جغرافیایی به عنوان عوامل موثر در تغییرات مکانی بارش انتخاب شد. ترکیبات مختلف این پنج پارامتر، با استفاده از آزمون گاما در نرم‌افزار WinGammaTM ، اولویت‌بندی شد. مدل‌سازی رگرسیونی و تعیین ضرایب عددی معادلات، با استفاده از الگوریتم بهینه‌سازی لونبرگ–مارکوارت در محیط MATLAB انجام شد. سپس با استفاده از معیارهای ارزیابی ضریب تعیین (R^2)، ریشه میانگین مربعات خطا (RMSE) و دیاگرام تیلور(Taylor Diagram)، بهترین مدل انتخاب و نقشه رستری یک رگبار انتخابی در محیط Arc GIS ترسیم شد. در انتها با استفاده از رویکرد پیشنهادی استفاده از روش نسبت معادلات، مدل تغییرات مکانی–زمانی بارش نهایی شد. نتایج نشان داد که با استفاده از مدل غیرخطی درجه دو و پارامترهای ارتفاع از سطح دریا و عرض جغرافیایی، می‌توان با دقت بالایی، توزیع مکانی بارش را به صورت یک شبکه منظم پیکسلی (100 متر مربعی) بدست آورد (917/0 =.R^2 و 2277/0=RMSE). با توجه به اینکه در رگبارهای مختلف حوزه‌های کوچک، نسبت تغییرات بارش هر پیکسل به پیکسل‌های دیگر (از جمله پیکسل ایستگاه پایش باران) تقریبا ثابت است، بنابراین با استفاده از رویکرد پیشنهادی در این پژوهش می‌توان تغییرات مکانی و زمانی هر رگبار را به صورت یک ماتریس سه بعدی در منطقه مدل‌سازی کرد.

کلیدواژه‌ها

عنوان مقاله [English]

Modeling Spatiotemporal Changes in Rainfall for Use in Dynamic and Distributed Rainfall-Runoff Models

نویسندگان [English]

Amir Hossein Parsamehr
Ali Salajegheh
Shahram Khalighi
Khaled Ahmadaali

Department of Reclamation of Arid and Mountainous Region, Faculty of Natural Resources, University of Tehran, Tehran, Iran

چکیده [English]

Aim: The aim of this study is to propose an approach for modeling spatiotemporal changes in rainfall that can be used as input for rainfall-runoff models.
Research Method: To achieve this, rainfall data from four rain gauge stations in the Paskouhak catchment were used. Five parameters, including elevation, slope, aspect, longitude, and latitude, were identified. The different combinations of these five parameters were prioritized using the gamma test in WinGammaTM software. After the use of different regression models, the best model was selected based on evaluation criteria such as R2, RMSE, and the Taylor diagram. A raster map of a selected rainfall event was drawn in the Arc GIS environment. Finally, using the proposed approach of relative equations, the spatiotemporal changes in rainfall were modeled.
Results: The results showed that using a second-degree nonlinear model and parameters of elevation and latitude, it is possible to accurately obtain the spatial distribution of rainfall in the form of a regular pixel grid (100 square meters) with high precision (R2=0.917 and RMSE=0.2277).
Conclusion: In different rainfall events in small catchment areas, the variation in rainfall in each pixel is almost constant relative to other pixels, including the rain gauge station, the proposed approach in this study can model the spatiotemporal changes of each rainfall event as a three-dimensional matrix in the study area. The approach can be valuable in predicting potential flood events and in water resource management and planning. However, further research is required to validate the results and test the approach in other areas.

کلیدواژه‌ها [English]

Levenberg-Marquardt
Paskouhak catchment
Rainfall modelling
Regression modeling

مراجع

Alijani, B., & Zahedi, M. (2002). Statistical and synoptic analysis of Azarbaijan area rainfall. Iranian Journal of Research in Geography, 65, 202-217. (In Persian).

Asakereh, H., & Seifipour, Z. (2013). Spatial modeling of annual precipitation in Iran. Geography and development, 10(29), 6-9. (In Persian).

Ayoubi Ayoublu, S., Vafakhah, M., & Pourghasemi, H. (2022). Flood Risk Assessment using Multi-Criteria Decision-Making Models (MCDM) and Data Mining Methods (Case Study: Shiraz District 4). Journal of Water and Soil Science, 26 (3), 247-265. (In Persian).

Balyani, S. (2017). Spatial analysis of annual precipitation of khuzestan province; an approach of spatial regressions analysis. Journal of geographical sciences, 16(43), 125-147. (In Persian).

Barooti, H., Esmaili, K., & Ghahraman, B. (2020). Stochastic simulation of daily rainfall using generalized linear models in semiarid simulation of rainfall. Journal of Climate Research, 1398(37), 1-20. (In Persian).

Besalatpour, A. A., Hajabbasi, M. A., & Ayoubi, Sh. (2013). Use of Gamma test technique for choosing the optimum input variables in modeling of soil shear strength using artificial neural networks. Journal of Water and Soil Conservation, 20(1), 97-114. (In Persian).

Callau Poduje, A. C., & Haberlandt, U. (2017). Short time step continuous rainfall modeling and simulation of extreme events. Journal of Hydrology, 552, 182-197.

Chow, T. T., Long, H., Mok, H. Y., & Li, K.W. (2011). Estimation of soil temperature profile in Hong Kong from climatic variables. Energy and Building Journal, 43, 3568-3575.

Ghayur, H. A., & Masoudiyan, S. A. (1996). An spatial analysis of elevation – precipitation models (Case study: Iran). Geographic Researches, 41, 124-143. (In Persian).

Gill, P. R., Murray, W., & Wright, M. H. (1981). The Levenberg-Marquardt Method. §4.7.3 in Practical Optimization. London, Academic Press.

Gleckler, P. J., Taylor, K. E., & Doutriaux, C. (2008). Performance metrics for climate models. Journal of Geophysical Research: Atmospheres, 113(D6), 1-20.

Houghton, J. G. (1979). A Model for Orographic Precipitation in the North-Central Great Basin. Monthly Weather Review, 107, 1462-1475.

Levenberg, K. (1944). A Method for the Solution of Certain Problems in Least Squares. Quarterly Applied Mathematics, 2, 164-168.

Loukas, A., & Quick, M. C. (1996). Effect of climate change on hydrologic regime of two climatically different watersheds. Journal of Hydrologic Engineering, 1(2), 77-87.

Marquardt, D. (1963). An Algorithm for Least-Squares Estimation of Nonlinear Parameters. SIAM Journal on Applied Mathematics, 11, 431-441.

Masoodian, S. A., Keikhosravi Kiany, M. S., & Rayat Pishe, F. (2014). Introduction and a comparison among gridded precipitation database of asfazari with GPCC, GPCP and CMAP. Geographical research, 29(1), 73-87. (In Persian).

Moghaddamnia, A., Ghafari Gousheh, M., Piri, J., Amin, S., & Han, D. (2009). Evaporation estimation using artificial neural networks and adaptive Neurofuzzy inference system techniques. Advances in Water Resources, 32(1), 88-97.

Mojarad, F., & Moradifar, H. (2003). Modelling the Relation of Precipitation with Elevation in the Zagros Region. Modarres Human Sciences, 7(2), 163-182. (In Persian).

Mouneskhah, V., Khaledi Alamdari, M., Hadi, M., & Samadianfard, S. (2023). Comparison of the efficiency of intelligent and statistical methods in the reconstruction of sunshine hours data (Case study: East of Urmia Lake basin). Journal of Agricultural Meteorology, 10(2), 28-36. (In Persian).

Nouri, M., & Salmasi, F. (2019). Predicting seepage of earth dams using artificial intelligence techniques. Irrigation Sciences and Engineering (scientific journal of agriculture), 42(1), 83-97. (In Persian).

Panahi, H., Asadi, S. (2018). Prediction of Nano-Droplet Spreading on the Surface using the Multivariate Non-Linear Regression. Advanced Materials and New Coatings, 7(26), 1881-1886. (In Persian).

Papailiou, I., Spyropoulos, F., Trichakis, I., & Karatzas, G.P. (2022). Artificial Neural Networks and Multiple Linear Regression for Filling in Missing Daily Rainfall Data. Water, 14(18), 2892. https://doi.org/10.3390/w14182892.

Pourgholam-Amiji, M., Ahmadaali, K., & Liaghat, A. (2021). Sensitivity Analysis of Parameters Affecting the Early Cost of Drip Irrigation Systems Using Meta-Heuristic Algorithms. Iranian Journal of Irrigation & Drainage, 15(4), 737-756. (In Persian).

Sigaroodi, S. K., Chen, Q. (2016). Effects and consideration of storm movement in rainfall–runoff modelling at the basin scale, Hydrology and Earth System Sciences, 20-5063-2016.

Sigaroodi, S. K., Chen, Q., Ebrahimi, S., Nazari, A., and Choobin, B. (2014). Long-term precipitation forecast for drought relief using atmospheric circulation factors: a study on the Maharloo Basin in Iran, Hydrology and Earth System Sciences, 18, 1995–2006.

Singh, P., & Kumar N., (1997). Effect of orographic precipitation in the western Himalayan region. Journal of Hydrology, 199(2), 183-206.

Storr, D., & Ferguson, H. L. (1972, July). The distribution of precipitation in some mountainous Canadian watersheds, Paper presented in WMO Symposium on Distribution of Precipitation in Mountainous Areas, Geilo, Norway.

Taylor, K. E. (2001). Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research: Atmospheres, 106 (D7), 7183-7192.

Withmore, J. S. (1972). The variation of mean annual rainfall with altitude and locality in South Africa, as determined by multiple curvilinear regression analysis, Distribution of precipitation in mountainous area, WMO Publication, 326.

Zahedi, M., Sari Sarraf, B., & Jamee, J. (2007). The Analysis of Spatio-Temporal Variations of Temperature in the North –West of Iran. Geography and development, 10, 183-198. (In Persian).

نشریه علمی - پژوهشی مرتع و آبخیزداری

مدل‌سازی تغییرات مکانی – زمانی بارش به منظور استفاده در مدل‌های دینامیکی و توزیعی بارش – رواناب

مراجع

مراجع

Alijani, B., & Zahedi, M. (2002). Statistical and synoptic analysis of Azarbaijan area rainfall. Iranian Journal of Research in Geography, 65, 202-217. (In Persian).

Ayoubi Ayoublu, S., Vafakhah, M., & Pourghasemi, H. (2022). Flood Risk Assessment using Multi-Criteria Decision-Making Models (MCDM) and Data Mining Methods (Case Study: Shiraz District 4). Journal of Water and Soil Science, 26 (3), 247-265. (In Persian).

Ghayur, H. A., & Masoudiyan, S. A. (1996). An spatial analysis of elevation – precipitation models (Case study: Iran). Geographic Researches, 41, 124-143. (In Persian).

Houghton, J. G. (1979). A Model for Orographic Precipitation in the North-Central Great Basin. Monthly Weather Review, 107, 1462-1475.

Loukas, A., & Quick, M. C. (1996). Effect of climate change on hydrologic regime of two climatically different watersheds. Journal of Hydrologic Engineering, 1(2), 77-87.

Nouri, M., & Salmasi, F. (2019). Predicting seepage of earth dams using artificial intelligence techniques. Irrigation Sciences and Engineering (scientific journal of agriculture), 42(1), 83-97. (In Persian).

Panahi, H., Asadi, S. (2018). Prediction of Nano-Droplet Spreading on the Surface using the Multivariate Non-Linear Regression. Advanced Materials and New Coatings, 7(26), 1881-1886. (In Persian).

Sigaroodi, S. K., Chen, Q., Ebrahimi, S., Nazari, A., and Choobin, B. (2014). Long-term precipitation forecast for drought relief using atmospheric circulation factors: a study on the Maharloo Basin in Iran, Hydrology and Earth System Sciences, 18, 1995–2006.

Storr, D., & Ferguson, H. L. (1972, July). The distribution of precipitation in some mountainous Canadian watersheds, Paper presented in WMO Symposium on Distribution of Precipitation in Mountainous Areas, Geilo, Norway.

Withmore, J. S. (1972). The variation of mean annual rainfall with altitude and locality in South Africa, as determined by multiple curvilinear regression analysis, Distribution of precipitation in mountainous area, WMO Publication, 326.

Zahedi, M., Sari Sarraf, B., & Jamee, J. (2007). The Analysis of Spatio-Temporal Variations of Temperature in the North –West of Iran. Geography and development, 10, 183-198. (In Persian).

دوره 77، شماره 1
اردیبهشت 1403
صفحه 33-49

مدل‌سازی تغییرات مکانی – زمانی بارش به منظور استفاده در مدل‌های دینامیکی و توزیعی بارش – رواناب

مراجع

مراجع

Alijani, B., & Zahedi, M. (2002). Statistical and synoptic analysis of Azarbaijan area rainfall. Iranian Journal of Research in Geography, 65, 202-217. (In Persian).

Ayoubi Ayoublu, S., Vafakhah, M., & Pourghasemi, H. (2022). Flood Risk Assessment using Multi-Criteria Decision-Making Models (MCDM) and Data Mining Methods (Case Study: Shiraz District 4). Journal of Water and Soil Science, 26 (3), 247-265. (In Persian).

Ghayur, H. A., & Masoudiyan, S. A. (1996). An spatial analysis of elevation – precipitation models (Case study: Iran). Geographic Researches, 41, 124-143. (In Persian).

Houghton, J. G. (1979). A Model for Orographic Precipitation in the North-Central Great Basin. Monthly Weather Review, 107, 1462-1475.

Loukas, A., & Quick, M. C. (1996). Effect of climate change on hydrologic regime of two climatically different watersheds. Journal of Hydrologic Engineering, 1(2), 77-87.

Nouri, M., & Salmasi, F. (2019). Predicting seepage of earth dams using artificial intelligence techniques. Irrigation Sciences and Engineering (scientific journal of agriculture), 42(1), 83-97. (In Persian).

Panahi, H., Asadi, S. (2018). Prediction of Nano-Droplet Spreading on the Surface using the Multivariate Non-Linear Regression. Advanced Materials and New Coatings, 7(26), 1881-1886. (In Persian).

Sigaroodi, S. K., Chen, Q., Ebrahimi, S., Nazari, A., and Choobin, B. (2014). Long-term precipitation forecast for drought relief using atmospheric circulation factors: a study on the Maharloo Basin in Iran, Hydrology and Earth System Sciences, 18, 1995–2006.

Storr, D., & Ferguson, H. L. (1972, July). The distribution of precipitation in some mountainous Canadian watersheds, Paper presented in WMO Symposium on Distribution of Precipitation in Mountainous Areas, Geilo, Norway.

Withmore, J. S. (1972). The variation of mean annual rainfall with altitude and locality in South Africa, as determined by multiple curvilinear regression analysis, Distribution of precipitation in mountainous area, WMO Publication, 326.

Zahedi, M., Sari Sarraf, B., & Jamee, J. (2007). The Analysis of Spatio-Temporal Variations of Temperature in the North –West of Iran. Geography and development, 10, 183-198. (In Persian).

دوره 77، شماره 1اردیبهشت 1403صفحه 33-49

دوره 77، شماره 1
اردیبهشت 1403
صفحه 33-49