تخمین مکانی بارش مبتنی بر خصوصیات مکانی و مدل PRISM در حوضه سفیدرود بزرگ

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد دانشگاه تهران

2 دانشکده مهندسی عمران، پردیس دانشکده های فنی، دانشگاه تهران

3 استادیار دانشکده مهندسی عمران دانشگاه تهران

چکیده

تخمین دقیق توزیع مکانی بارش در بسیاری از فرآیندهای برنامه ریزی و مدیریت بهره برداری از منابع آب و فعالیت‌های کشاورزی، نقش کلیدی ایفا می‌کند. در این تحقیق، به منظور تخمین ماهانه بارش با دقت مطلوب مکانی، مدلی بر پایه چهارچوب PRISM مبتنی بر الگوی ارتفاعی و سایر خصوصیات مکانی، توسعه داده شد و در حوضه آبریز سفیدرود و در بازه زمانی سال آبی 1379 الی 1394 پیاده‌سازی شد. در گام اول نتایج حاصل از این روش در مقیاس ماهانه با روش بهبود یافته معکوس فاصله وزندار2 مقایسه شد. با توجه به درجه آزادی‌های موجود در هر دو روش، پارامترهای این دو روش ابتدا در مقیاس زمانی سالانه با استفاده از الگوریتم ژنتیک بهینه‌یابی شده و از مجموعه پارامترهای بدست آمده به منظور تخمین عملکرد آماری مدل ماهانه از طریق اعتبار سنجی3 متقابل استفاده شد. بر اساس نتایج ماهانه محاسبه شده، هر دو مدل در تخمین مقدار بارش در محل ایستگاه‌ها، عملکردی نزدیک داشتند. اما علیرغم این عملکرد تقریبا یکسان، توزیع مکانی بارش محاسبه شده توسط روش مبتنی بر PRISM از انطباق بهتری نسبت به الگوی توپوگرافی و شواهد موجود برخوردار است. در گام بعدی عملکرد این مدل در تخمین میانگین بارش ماهانه با روش کریجینگ معمولی مقایسه شد، نتایج مدل توسعه داده شده در ماه‌های پربارش و روش کریجینگ در ماه‌های خشک مطلوب‌تر ارزیابی می شود. . با توجه به حجم اندک بارش‌های تابستانه، PRISM ابزار مناسب تری نسبت به کریجینگ به منظور درورن‌یابی مکانی بارش شناخته شد.

کلیدواژه‌ها


عنوان مقاله [English]

Spatial Estimation of Precipitation Based on Spatial Characteristics and PRISM Framework in Sefidroud Basin

نویسندگان [English]

  • Omid Zandi 1
  • Banafsheh Zahraie 2
  • Mohsen Nasseri 3
1 Graduate student, University of Tehran
2 School of Civil Engineering, College of Engineering, University of Tehran
3 Assistant Professor, School of Civil Engineering, University of Tehran
چکیده [English]

Accurate spatial estimation of precipitation plays a key role in many hydrological modelling, water resources planning and agricultural management studies. In order to estimate high-resolution precipitation in the current research, an estimation model based on PRISM framework considering Digital Elevation Model (DEM) and other spatial attributes is developed and applied to Sefidroud basin during the years 2000-2015. In the first step, the monthly results were compared with modified Inverse Distance Weighted (IDW) as a benchmark method. Considering both models’ degrees of freedom, the parameters are calibrated with Genetic Algorithm in annual time scale and the obtained parameters are utilized to estimate model monthly cross validation error. According to the monthly results, both models had roughly same statistical performance in estimating precipitation at the selected rain gauges. In spite of similar statistical performance of the models, the spatial distribution of precipitation provided by the PRISM based method is more consistent with topographic pattern and existing evidences. In the next step the proposed model’s ability to estimate mean monthly precipitation is compared with ordinary kriging method and according to the results, in wet months the developed model and in dry months kriging method represents more optimal results. According to small amount of summer precipitation, PRISM based approach is considered to be a better tool for spatial interpolation of precipitation than kriging.

کلیدواژه‌ها [English]

  • Spatial Interpolation of Precipitation
  • Genetic Algorithm
  • Inverse distance weighted
  • Sefidroud Watershed
  • Kriging
Abedini MJ and Nasseri M (2008) Inverse distance weighted revisited. In: 4th APHW, Conf. Beijing
Azizian A and Amini S (2020) The effect of climate and topographic conditions on the performance of PERSIANN family products over iran. Iran-Water Resources Research 16(1):86–101 (In Persian)
Barbulescu A, Bautu A, and Bautu E (2020) Optimizing inverse distance weighting with particle swarm optimization. Applied Sciences 10(6):2054
Bayat B, Zahraie B, Taghavi F, and Nasseri M (2012) Evaluating of the efficiency of spatial geostatistical methods for identifying the spatial patterns of precipitation a case study of namak lake watershed. Iraninan Journal of Geophysics 5(4):89–110 (In Persian)
Bayat B, Zahraie B, Taghavi F, and Nasseri M (2013) Evaluation of spatial and spatiotemporal estimation methods in simulation of precipitation variability patterns. Theoretical and Applied Climatology 113(3):429–444
Castro LM, Gironás J, and Fernández B (2014) Spatial estimation of daily precipitation in regions with complex relief and scarce data using terrain orientation. Journal of Hydrology 517:481–492
Crespi A, Brunetti M, Lentini G, and Maugeri M (2018) 1961–1990 High-resolution monthly precipitation climatologies for italy. International Journal of Climatology 38(2):878–895
Daly C (2006) Guidelines for assessing the suitability of spatial climate data sets. International Journal of Climatology 26(6):707–721
Daly C, Gibson WP, Taylor GH, Johnson GL, and Pasteris P (2002) A knowledge-based approach to the statistical mapping of climate. Climate Research 22(2):99–113
Daly C, Halbleib M, Smith JI, Gibson WP, Doggett MK, Taylor GH, Pasteris PP, Curtis J, and Pasteris PP (2008) Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous united states. International Journal of Climatology 28(15):2031–2064
Daly C, Helmer EH, and Quiñones M (2003) Mapping the climate of puerto rico, vieques and culebra. International Journal of Climatology 23(11):1359–1381
Daly C, Neilson RP and Phillips DL (1994) A statistical-topographic model for mapping climatological precipitation over mountainous terrain. Journal of Applied Meteorology 33(2):140–158
Daly C, Slater ME, Roberti JA, Laseter H, Swift LW, Laseter SH, and Swift Jr LW (2017) High-resolution precipitation mapping in a mountainous watershed ground truth for evaluating uncertainty in a national precipitation dataset. International Journal of Climatology 37(S1):124–137
Delbari M, Afrasiab P, and Jahani S (2013) Spatial interpolation of monthly and annual rainfall in northeast of iran. Meteorology and Atmospheric Physics 122(1–2):103–113
Gibson W, Daly C, and Taylor G (1997) 7.1 Derivation of FACET grids for use with the PRISM model. In: 10th AMS Conf. on Applied Climatology, Reno, NV, 208-209
Goovaerts P (2000) Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology 228(1–2):113–129
Gupta H V, Kling H, Yilmaz KK, and Martinez GF (2009) Decomposition of the mean squared error and NSE performance criteria implications for improving hydrological modelling. Journal of Hydrology 377(1–2):80–91
Hutchinson MF (1995) Interpolating mean rainfall using thin plate smoothing splines. International Journal of Geographical Information Systems 9(4):385–403
Jeong H-G, Ahn J-B, Lee J, Shim K-M, and Jung M-P (2020) Improvement of daily precipitation estimations using PRISM with inverse-distance weighting. Theoretical and Applied Climatology 139(3–4):923–934
Kankash omran consulting engineers (2016) Studies of updating water balance of The Sefidrood watershed ending to 1389-90 water year. Technical Report (In Persian)  
Karamouz M, Fallahi M and Nazif S (2010) Analysis of spatial variation of precipitation comparison of conventional and kriging methods. Iran-Water Resources Research 6(1):1–9 (In Persian)
Kurtzman D, Navon S, and Morin E (2009) Improving interpolation of daily precipitation for hydrologic modelling spatial patterns of preferred interpolators. Hydrological Processes 23(23):3281–3291
Liu FCC, Chen F-W, and Liu C-W (2012) Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan. Paddy and Water Environment 10(3):209–222
Meersmans J, Weverberg K Van, Baets S De, Ridder F De, Palmer SJ, Wesemael B Van, Quine TA, Van Weverberg K, De Baets S, De Ridder F, …, and Quine TA (2016) Mapping mean total annual precipitation in belgium, by investigating the scale of topographic control at the regional scale. Journal of Hydrology 540:96–105
Robertson GP (2000) Geostatistics for environmental sciences, GS+ user’s guide, Version 5. Gamma Design Software
Saghafian B and Rahimi Bondarabadi S (2005) Comparison of interpolation and extrapolation methods for estimating spatial distribution of annual rainfall. Iran-Water Resources Research 1(2):74–84 (In Persian)
Saghafian B and Rahimi Bondarabadi S (2008) Validity of regional rainfall spatial distribution methods in mountainous areas. Journal of Hydrologic Engineering 13(7):531–540
Sharples JJ, Hutchinson MF and Jellett DR (2005) On the horizontal scale of elevation dependence of australian monthly precipitation. Journal of Applied Meteorology 44(12):1850–1865
Shayeghi A, Azizian A and Brocca L (2019) Evaluating the efficiency of reanalysis and remote-sensing based rainfall data sets for hydrological modeling using VIC-3L large scale model (Case study: Sefidrood catchment). Iran-Water Resources Research 15(2):57-72 (In Persian)
Shin S-C, Kim M-K, Suh M-S, Rha D-K, Jang D-H, Kim C-S, Lee W-S, and Kim Y-H (2008) Estimation of high resolution gridded precipitation using GIS and PRISM. Atmosphere 18(1):71–81