Hydro-Estimator Algoritmasının Mevsimsel Ölçekte Suudi Arabistan’da Değerlendirilmesi

Year 2019, Volume: 9 Issue: 2, 900 - 910, 01.06.2019

Arzu Özkaya

https://doi.org/10.21597/jist.487485

Abstract

Meteoroloji ve hidroloji uygulamalarında, bölgesel ve küresel ölçekte kaliteli yağış tahminlerinin bulunması çok önemlidir. Yağış verisinin mekânsal ve zamansal düzlemdeki yüksek değişkenliğinden dolayı, kabul edilebilir veri gösterimi için sık ve yakın aralıklı gözlemler gerekmektedir. Bu nedenle de birçok araştırma alanında uydu-tabanlı yağış ürünleri kullanılmaktadır. Bu çalışmanın amacı uydu tabanlı yağış verisi olan Hydro-Estimator (HE) ürününü kurak iklim koşullarına sahip olan Suudi Arabistan bölgesi için mevsimsel ölçekte değerlendirmektir. Çalışmada 30 adet yağış gözlem istasyonu kullanılmış ve bu istasyonlardan temin edilen aylık toplam yağış verileri mevsimsel ölçekte HE ürünü ile değerlendirilmiştir. Değerlendirmede yağış miktarı ve topoğrafya gibi değişkenler yağış rejimleriyle kıyaslanmıştır. Buna göre aylık tabanda iki veri seti arasında anlamlı bir ilişki saptanamamıştır. Ancak, yağış rejimleri gözetilerek yapılan değerlendirmelerde HE ürününün istasyon verisiyle olan ilişkisi belirlenmiştir. İki veri arasındaki ilişkiyi ölçmek için, determinasyon katsayısı (r2) kılavuz olarak kullanılmıştır. Sonuçlara göre HE ürünü yağışlı mevsimde daha az tahmin sunarken, geçiş ve kurak mevsimlerde daha fazla tahmin sunmuştur. Ayrıca, en iyi sonuç (r2 = 0.86) kurak mevsimde gözlenmiştir. Her iki veri setinde de genel olarak topoğrafyanın yüksek olduğu yerlerde yüksek yağış değerleri bulunmuştur. Ancak yüksekliğin yağış dağılımında tek faktör olmadığı da görülmüştür.

Keywords

Uydu-tabanlı yağış verisi, Hydro-Estimator ürünü, yağış dağılımı

Evaluation of the Hydro-Estimator Algorithm over Saudi Arabia on a Seasonal Scale

Abstract

In applications of meteorology and hydrology, the availability of good-quality precipitation estimates at regional and global scales is very important. For acceptable data representation, frequent and closely spaced observations are required due to high variability of precipitation data in spatial and temporal domain. Consequently, satellite-based precipitation products have been used in many research fields. The aim of this study is to evaluate the satellite-based precipitation data Hydro-Estimator (HE) product in seasonal scale over the Saudi Arabian region that has arid-climate conditions. In this study, 30 rainfall observation stations were used and monthly total rainfall data obtained from these stations were evaluated with the HE product in seasonal scale. In the evaluation, amount of rainfall and topography were compared with rainfall regimes. According to results, significant relationship between these two datasets was not determined in monthly based evaluations. However, generalized relation between the HE product and the gauge data was obtained in seasonal-based evaluations. To measure the relation between two data, the coefficient of determination (r2) was used as a guideline. Based on the results, the HE product underestimated the rainfall amounts in wet season whereas, overestimated the rainfall amounts in dry and transitional seasons. Moreover, the best result (r2=0.86) was observed in dry season. Generally, both datasets gave high rainfall amounts in topographically high regions. However, it was also observed that the height was not the only factor in the distribution of rainfall.

Keywords

Satellite-based rainfall data, the Hydro-Estimator product, rainfall distribution

References

• Abdullah M, Al-Mazroui M, 1998. Climatological study of the southwestern region of Saudi Arabia. I. Rainfall analysis. Climate Research 9: 213–223.
• Almazroui M, 2011. Temperature Variability over Saudi Arabia and its Association with Global Climate Indices. Journal of King Abdulaziz University-Meteorology, Environment and Arid Land Agriculture Sciences 23: 85–108.
• Behrangi A, Khakbaz B, Jaw TC, AghaKouchak A, Hsu K, Sorooshian S, 2011. Hydrologic evaluation of satellite precipitation products over a mid-size basin. Journal of Hydrology 397: 225–237.
• Deyzel ITH, South Africa, Water Research Commission, 2004. Spatial interpolation and mapping of rainfall (SIMAR). Volume 2, Water Research Commission, Pretoria.
• Ghile Y, Schulze R, Brown C, 2010. Evaluating the performance of ground-based and remotely sensed near real-time rainfall fields from a hydrological perspective. Hydrological Sciences Journal 55: 497–511.
• Hasanean H, Almazroui M, 2015. Rainfall: Features and Variations over Saudi Arabia, A Review. Climate 3: 578–626.
• Hong Y, Adler RF, Hossain F, Curtis S, Huffman GJ, 2007. A first approach to global runoff simulation using satellite rainfall estimation. Water Resources Research 43.
• Hughes DA, 2006. Comparison of satellite rainfall data with observations from gauging station networks. Journal of Hydrology 327: 399–410.
• Kuligowski B, 2014. STAR Satellite Rainfall Estimates - Hydro-Estimator - Technique Description [web Document]. URL https://www.star.nesdis.noaa.gov/smcd/emb/ff/HEtechnique.php (Erişim tarihi: 20.11.2018)
• Li L, Hong Y, Wang J, Adler RF, Policelli FS, Habib S, Irwn D, Korme T, Okello L, 2009. Evaluation of the real-time TRMM-based multi-satellite precipitation analysis for an operational flood prediction system in Nzoia Basin, Lake Victoria, Africa. Nat Hazards 50: 109–123.
• Pan M, Li H, Wood E, 2010. Assessing the skill of satellite-based precipitation estimates in hydrologic applications. Water Resources Research 46.
• Petty GW, Krajewski WF, 1996. Satellite estimation of precipitation over land. Hydrological Sciences Journal 41: 433–451.
• Ramirez-beltran ND., Kuligowski RJ, Harmsen EW, Cruz-pol S, Cardona MJ, 2008. Rainfall Estimation from Convective Storms Using the HydroEstimator and NEXRAD, in: WSEAS TRANSACTION on SYSTEMS. pp. 1016–1027.
• Rudolf B, 2005. The Global Precipitation Climatology Centre (GPCC), in: Proc. Second Workshop of the Int. Precipitation Working Group. pp. 231–247.
• Sapiano MRP, Arkin PA, 2009. An Intercomparison and Validation of High-Resolution Satellite Precipitation Estimates with 3-Hourly Gauge Data. J. Hydrometeor. 10: 149–166.
• Scofield RA, Kuligowski RJ, 2003. Status and outlook of operational satellite precipitation algorithms for extreme-precipitation events. Weather and Forecasting 18: 1037–1051.
• Shrestha MS, Artan GA, Bajracharya SR, Sharma RR, 2008. Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin. Journal of Flood Risk Management 1: 89–99.
• Vicente GA, Scofield RA, Menzel WP, 1998. The Operational GOES Infrared Rainfall Estimation Technique. Bull. Amer. Meteor. Soc. 79: 1883–1898.
• Wu H, Adler RF, Tian Y, Huffman GJ, Li H, Wang J, 2014. Real-time global flood estimation using satellite-based precipitation and a coupled land surface and routing model. Water Resources Research 50: 2693–2717.
• Yücel I, 2015. Assessment of a flash flood event using different precipitation datasets. Natural Hazards 79: 1889–1911.
• Yücel I, Kuligowski RJ, Gochis DJ, 2011. Evaluating the hydro-estimator satellite rainfall algorithm over a mountainous region. International journal of remote sensing 32: 7315–7342.