GOÜ. Ziraat Fakültesi Dergisi, 2005, 22 (1), 37-44 Regional Frequency Analysis of Maximum Daily Rainfalls Based on L-Moment Approach Kadri Yürekli Gaziosmanpasa University, Faculty of Agriculture, Department of Farm Structure and Irrigation, 60250 Tokat Abstract: The main goal of the study is to perform regional frequency analysis of maximum daily rainfalls selected for each year among daily rainfalls measured over Tokat region by using L-moment approach. Initially, using Runs and Mann-Whitney statistics to detect whether the conditions of randomness and homogeneity were implemented were applied to the maximum daily rainfalls. Thereafter, the most suitable distribution among the selected various statistical distributions whose parameters were predicted via L- moment approach for four hydrologic homogeneous regions of Tokat region, which was divided into four hydrologic homogeneous region as West-W, Central North-CN, Central South-CS and East-E, was determined according to the mean absolute deviation index (MADI) and mean square deviation index (MSDI) measures. The results of MADI and MSDI showed that the most suitable statistical distributions were, generalized logistic (GLO) for W and CN, generalized pareto (GPA) for CS, and generalized extreme value type I (GEV) for E. Key Words: Maximum rainfall, hydrologic homogeneous region, L-moment L-Moment Yaklaşımı ile Maksimum Günlük Yağmurların Bölgesel Frekans Analizi Özet: Bu çalışmanın ana amacı, Tokat bölgesinde ölçülen günlük yağmurlar arasından her yıl için seçilen maksimum günlük yağmurların bölgesel frekans analizini yapmaktır. Öncelikl e, rasgelelik ve homojenlik şartlarının yerine getirilip getirilmediğini saptamak için Runs ve Mann-Whitney istatistikleri maksimum günlük yağmurlara uygulandı. Daha sonra, Batı-W, Orta Kuzey-CN, Orta Güney-CS ve Doğu-E olarak dört hidrolojik homojen bölgeye ayrılan Tokat bölgesinin bu homojen yöreleri için parametreleri L-moment yöntemi ile tahmin edilen seçilmiş değişik dağılımlar arasından en uygun olanı, “the mean absolute deviation index (MADI) ve mean square deviation index (MSDI)” ölçütlerine göre belirlendi. MADI ve MSDI sonuçları, W ve CN için genelleşmiş logistic (GLO), CS için genelleşmiş pareto (GPA) ve E için genelleşmiş extreme value type I (GEV)’in en uygun olasılık dağılım olduklarını gösterdi. Anahtar Kelimeler: Maksimum yağmur, hidrolojik homojen bölge, L-moment 1. Introduction Knowledge related to distributions of extreme rainfall depths has a great important on flood estimation, the design of water-related structure, erosion, and agriculture. Therefore, the main goal should be to specify the most suitable probability distribution fit to the observations. But, a common problem encouraged in many aspects of water resources engineering is that of estimating the return period of rare events such as extreme flood and precipitation for a site or a group of sites. The selected quantile of under-or over design criterion concerning with hydraulic structures is exposed to risk as the return period is determined according to cost and economic- strategic significance of the structure. Selecting a reliable design quantile, which affect on design, operation, management and maintain of a hydraulic structure, considerably depends on statistical methods used in parameter estimation belonging to probability distribution (Hosking and Wallis, 1993). Past observations is fit with a probability distribution used to predict the exceedance probability of future events. But, defining a true distribution for hydrological and meteorological observations continues to be major question facing researchers. However, many extreme event series are too short for a reliable estimation of extreme events. This condition complicates both the identification of appropriate statistical distribution for describing the observations and the estimation of the parameters of a selected distribution. But, the most popularized method to frequency analysis in recent time is that L-moment approach introduced by Hosking (1990). The advantages of this method over conventional moments are that they are relatively insensitive to outliers and do not have sample size related bounds.