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پایش یکپارچه خشک‌سالی‌های هوا-آبشناسی در حوزه آبریز کسیلیان (استان مازندران) | ||
| فیزیک زمین و فضا | ||
| مقاله 14، دوره 44، شماره 2، تیر 1397، صفحه 463-477 اصل مقاله (599.31 K) | ||
| شناسه دیجیتال (DOI): 10.22059/jesphys.2018.244236.1006933 | ||
| نویسندگان | ||
| مجید چراغعلی‌زاده1؛ آرزو نازی قمشلو2؛ جواد بذرافشان* 3 | ||
| 1دانش آموخته کارشناسی ارشد، گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران | ||
| 2استادیار، گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران | ||
| 3دانشیار، گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران | ||
| چکیده | ||
| در مطالعه حاضر، پایش یکپارچه وضعیت خشک‌سالی هواشناسی (بر مبنای متغیر‌های دما و بارش) و خشک‌سالی آبشناسی (بر مبنای جریان رودخانه) در حوضه کسیلیان مازندران مورد توجه قرار گرفت. هدف اصلی تحقیق حاضر، ارائه یک شاخص خشک‌سالی ترکیبی با استفاده از روش چند متغیره تحلیل مؤلفه اصلی (PCA) در حوضه مورد بررسی است. برای پایش خشک‌سالی هواشناسی از شاخص‌های بارش استاندارد (SPI) و شاخص بارش- تبخیر و تعرق پتانسیل استاندارد (SPEI) و برای پایش خشک‌سالی آبشناسی از شاخص خشک‌سالی جریان رودخانه (SDI) استفاده شد. دادههای مورد نیاز این مطالعه از ایستگاههای هواشناسی و آبشناسی مستقر در حوضه کسیلیان برای یک دوره آماری 43 سال آبی (50-1349 تا 92-1391) گردآوری شد. پس از انجام کنترل‌های مقدماتی روی کیفیت دادهها، شاخص‌های خشک‌سالی هواشناسی و آبشناسی در چهار پنجره زمانی 3، 6، 9 و 12 از ابتدای سال آبی محاسبه شد. در مرحله بعد، دو شاخص ترکیبی برای ارزیابی خشک‌سالی‌های هوا-آبشناسی، یکی SPI-SDI و دیگری SPEI-SDI با استفاده از روش PCA ساخته شد. شاخص ترکیبی که فرم استاندارد شده نخستین مؤلفه اصلی شاخص‌های مورد استفاده در ترکیب است، به‌طور جداگانه برای ایستگاههای آبشناسی ولکبن و شیرگاه واقع در بالادست و پایین‌دست حوضه محاسبه گردید. نتایج نشان داد که در شناسایی سال‌های خشک، در بالادست حوضه، ترکیب SPEI-SDI به دلیل ساختار همبستگی قوی‌تر و توجیه درصد تغییرپذیری بیشتر توسط اولین مؤلفه اصلی آنها (5/75 تا 9/87 درصد) موفقیت بیشتری نسبت به ترکیب SPI-SDI دارد. این در حالی است که بین دو ترکیب در پایش خشک‌سالی‌ها در پایین‌دست تفاوت چندانی وجود ندارد. همچنین، در دوره‌های خشک ممتد، شاخص ترکیبی یک ماه زودتر از شاخص‌های منفرد وضعیت خشک‌سالی را اعلام می‌کند. | ||
| کلیدواژه‌ها | ||
| بارش؛ جریان رودخانه؛ شاخص‌های ترکیبی؛ روش چند متغیره؛ تبخیر و تعرق | ||
| عنوان مقاله [English] | ||
| Integrated Monitoring of Hydro–Meteorological Droughts in Kasilian's Basin (Mazandaran Province) | ||
| نویسندگان [English] | ||
| Majid Cheraghalizadeh1؛ Arezoo Nazi Ghameshloo2؛ Javad Bazrafshan3 | ||
| 1M.Sc. Graduated, Department of Irrigation and Reclamation Engineering, Natural Resources and Agricultural Campus, University of Tehran, Karaj, Iran | ||
| 2Assistant Professor, Department of Irrigation and Reclamation Engineering, Natural Resources and Agricultural Campus, University of Tehran, Karaj, Iran | ||
| 3Associate Professor, Department of Irrigation and Reclamation Engineering, Natural Resources and Agricultural Campus, University of Tehran, Karaj, Iran | ||
| چکیده [English] | ||
| Drought is a temporary status of water deficit with respect to its long term average condition. Combined Drought Indices (CDIs) are new tools to evaluate general status of drought in a region. In this study, we focus on the integrated monitoring of meteorological droughts (based on temperature and precipitation data) and hydrological droughts (only based on streamflow data) in the Kasilian's basin. The main goal of the investigation is to present a combined drought index called Hydro–Meteorological Drought Index (HMDI) using Principal Component Analysis (PCA) in the basin. PCA is a multivariate technique to reduce dimensionality of data in a number of principal components. The Standardized Precipitation Index (SPI) and the Standardized Precipitation–Evapotranspiration Index (SPEI) were applied to monitor meteorological droughts and the Streamflow Drought Index (SDI) for monitoring hydrological droughts. The data were gathered from the meteorological and hydrometric stations located in Kasilian's basin for the period 1349–50 to 1391–92 as the water year. The station Derzikola (in the upstream) was selected for meteorological analysis and two stations Valikbon and Shirgah were employed to analyze hydrologic drought conditions in the upstream and downstream of the basin, respectively. The preliminary controls on the quality of available data were accomplished using some statistical tests for randomness, normality, adequacy of record length, outliers and temporal trend. Employing 49 probability distributions showed that Wakeby is the best fit distribution for precipitation and streamflow data and General Extreme Value for the difference series of precipitation minus evapotranspiration. The meteorological (SPI and SPEI) and hydrological (SDI) drought indices were calculated at four time windows including 3, 6, 9 and 12 months (each of which starts from the month Octobr). In the next stage, for calculation of hydro–meteorological droughts, using PCA technique, two combined drought indices including SPI–SDI and SPEI–SDI were built. The combined indices, which are the standardized form of the first principal component (PC1), was individually calculated at upstream (for hydrometric station of Valikbon) and downstream (for hydrometric station of Shirgah) of the basin. PC1s were able to explain 74.3–87.9% of variabilities in data. The PC1 of the combination SPEI–SDI explained more variability than the SPI–SDI, both in upstream and in downstream of the basin. This may be related to the high correlation of SPEI and SDI series. The results showed that, for identification of dry years, SPEI–SDI is more successful than SPI–SDI at the upstream station. Therefore, combination of two indices with high correlation made satisfactory results in detecting overall status of droughts in the basin of interest. On the other hand, both combined drought indices have no differences in monitoring droughts at the downstream station. Also, during continuing dry periods, combined indices indicated drought status one month earlier in comparison with single indices. Accordance of the classified series of SPI and SPEI with combined drought indices was higher at larger time scales than smaller ones. This may be due to smoother series of single drought indices at larger time scales as well as high correlation level between indices employed in constructing HMDI. | ||
| کلیدواژه‌ها [English] | ||
| precipitation, Streamflow, Combined Indices, Multivariate Methods, evapotranspiration | ||
| مراجع | ||
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هاشمی‌نسب، آ.، بذرافشان، ج. و قمشلو، آ.، 1394، ارزیابی شاخص خشک‌سالی کمبود توأم تحت شرایط اقلیمی ایران، م. حفاظت منابع آب‌وخاک ایران، 4 (3)، 53-64. نادی، م.، 1393، بازسازی حلقه درختی دوره‌های خشک دو قرن اخیر در چند رویشگاه جنگلی ایران، رساله دکتری، دانشگاه تهران، بهمن 1393.
Abdi, A., Hassanzadeh, Y. and Ouarda, T. B. M. J., 2017, Regional frequency analysis using Growing Neural Gas network, Journal of Hydrology, 550, 92-102. American Meteorological Society, 1997, Meteorological drought-policy statement. Bulletin of the American Meteorological Society, 78, 847–849. Arabzadeh, R., Kholoosi, M. M. and Bazrafshan, J., 2016, Regional Hydrological Drought Monitoring Using Principal Components Analysis. Journal of Irrigation and Drainage Engineering, 142, 04015029. Bazrafshan, J., Hejabi, S. and Rahimi, J., 2014, Drought monitoring using the multivariate standardized precipitation index (MSPI). Water Resources Management, 28(4), 1045–1060. Bazrafshan, J., Nadi, M. and Ghorbani, K., 2015, Comparison of empirical copula–based joint deficit index (JDI) and multivariate standardized precipitation index (MSPI) for drought monitoring in Iran. Water Resources Management, 29(6), 2027–2044. Guttman, N. B., 1998, Comparing the palmer drought index and the standardized precipitation index1. Water Resources Management, 34(1), 113–121. Hao, Z. and AghaKouchak, A., 2013, Multivariate standardized drought index: a parametric multi–index model. Advances in Water Resources, 57, 12–18. Hao, Z. and Singh, V. P., 2015, Drought characterization from a multivariate perspective: A review. Journal of Hydrology, 527, 668–678. Hubert, M. and Vandervieren, E., 2008, An adjusted boxplot for skewed distributions. Computational Statistics & Data Analysis, 52(12), 5186–5201. Hurst, H. E., 1951, Long–term storage capacity of reservoirs. Transactions of the American Society of Civil Engineers, 116, 770–808. Kao, S. C. and Govindaraju, R. S., 2010, A copula–based joint deficit index for droughts. Journal of Hydrology, 380(1), 121–134. Kendall, M., 1975, Multivariate analysis. Lnoden: Charles Griffin and Company Ltd. Keyantash, J. A. and Dracup, J. A., 2004, An aggregate drought index: Assessing drought severity based on fluctuations in the hydrologic cycle and surface water storage. Water Resources Research, 40(9), W09304, doi:10.1029/2003WR002610. Mann, H. B., 1945, Nonparametric tests against trend, Econometrica. Journal of the Econometric Society, 13(3), 245–259. McKee, T. B., Doesken, N. J. and Kleist, J., 1993, The relationship of drought frequency and duration to time scales. Proceedings of the Eighth Conference on Applied Climatology, American Meteorological Society, Boston, 17(22), 179–184. Mirabbasi, R., Anagnostou, E. N., Fakheri–Fard, A., Dinpashoh, Y. and Eslamian, S., 2013, Analysis of meteorological drought in northwest Iran using the Joint Deficit Index. Journal of Hydrology, 492, 35–48. Nalbantis, I. and Tsakiris, G., 2009, Assessment of hydrological drought revisited. Water Resources Management, 23(5), 881–897. Nalbantis, I., 2008, Evaluation of a hydrological drought index. European Water, 23(24), 67–77. Pettitt, A. N., 1979, A non–parametric approach to the change–point problem. Applied Statistics, 28(2), 126–135. Rad, A. M., Ghahraman, B., Khalili, D., Ghahremani, Z. and Ardakani, S. A., 2017, Integrated meteorological and hydrological drought model: A management tool for proactive water resources planning of semi-arid regions. Advances in Water Resources, 107, 336-353. Rasmusson, E. M., Dickinson, R. E., Kutzbach, J. E. and Cleveland, M. K., 1993, Climatology, Handbook of Hydrology. DR Maidment, Ed. McGraw–Hill, 2, 44. Sen, P. K., 1968, Estimates of the regression coefficient based on Kendall's tau. Journal of the American Statistical Association, 63(324), 1379–1389. Sepulcre, G., Horion, S. M. A. F., Singleton, A., Carrao, H. and Vogt, J., 2012, Development of a Combined Drought Indicator to detect agricultural drought in Europe. Natural Hazards and Earth System Sciences, 12(11), 3519–3531. Sharma, S., 1996, Applied Multivariate Techniques. John Wiley & Sons, Inc., USA. Thornthwaite, C. W., 1948, An approach toward a rational classification of climate. Geographical review, 38(1), 55–94. Vicente–Serrano, S. M., Begueria, S. and Lpez–Moreno, J., 2010, A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. Journal of Climate, 23(7), 1696–1718. Wald, A. and Wolfowitz, J., 1940, On a test whether two samples are from the same population. The Annals of Mathematical Statistics, 11(2), 147–162. White, D. H. and Walcott, J. J., 2009, The role of seasonal indices in monitoring and assessing agricultural and other droughts: a review. Crop and Pasture Science, 60(7), 599–616. Wilhite, D. A. and Glantz, M. H., 1985, Understanding: the drought phenomenon: the role of definitions. Water International, 10(3), 111–120. Wilhite, D. A., 2000, Drought: A Global Assessment. Natural Hazards and Disasters Series, U.K: Routledge Publishers. Wilks, D. S., 2011, Statistical methods in in the Atmospheric Sciences (third edition). Academic Press, 676pp. Young, K. C., 1992, A three–way model for interpolating for monthly precipitation values. Monthly Weather Review, 120(11), 2561–2569. Zare, M., Nazari Samani, A. A., Mohammady, M., Salmani, H. and Bazrafshan, J., 2017, Investigating effects of land use change scenarios on soil erosion using CLUE–s and RUSLE models. International Journal of Environmental Science and Technology, 14(9), 1905–1918. | ||
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