Evaluation of Rainfall Temporal Distribution Models with Annual Maximum Rainfall Events in Seoul, Korea

Abstract

This study evaluated five models of rainfall temporal distribution (i.e., the Yen and Chow model, Mononobe model, alternating block method, Huff model, and Keifer and Chu model), with the annual maximum rainfall events selected from Seoul, Korea, from 1961 to 2016. Three different evaluation measures were considered: the absolute difference between the rainfall peaks of the model and the observed, the root mean square error, and the pattern correlation coefficient. Also, sensitivity analysis was conducted to determine whether the model, or the randomness of the rainfall temporal distribution, had the dominant effect on the runoff peak flow. As a result, the Keifer and Chu model was found to produce the most similar rainfall peak to the observed, the root mean square error was smaller for the Yen and Chow model and the alternating block method, and the pattern correlation was larger for the alternating block method. Overall, the best model to approximate the annual maximum rainfall events observed in Seoul, Korea, was found to be the alternating block method. Finally, the sensitivity of the runoff peak flow to the model of rainfall temporal distribution was found to be much higher than that to the randomness of the rainfall temporal distribution. In particular, in small basins with a high curve number (CN) value, the sensitivity of the runoff peak flow to the randomness of the rainfall temporal distribution was found to be insignificant.

Evaluation of Design Storms and Critical Rainfall Durations for Flood Prediction in Partially Urbanized Catchments

“…Furthermore, it could be expected that peak values continue to gradually decrease with the storm duration. These results are consistent with previous studies that similarly found that Huff's curves may underestimate peak runoff because they tend to over-smooth the representative mass curve [22,28,29]. On the other hand, there are also studies that have shown that Huff's curves can produce a wide range of corresponding flooding results (including above-average values) when combining different durations, quartiles, and isopleths [16].…”

“…Although some authors have criticized frequency based methods, primarily because they do not represent actual historical rainfall [15,28], other authors have found that these methods agree well with historical storms. For example, Balbastre-Soldevila et al [22] found that the ABM method produced average peak flow rates in an urban catchment in Spain similar to several other geometrical methods and the AVM design storm, and Na and Yoo [29] reported that the ABM method was most similar to historical storms in Korea.…”

“…In this way, the derived mass curves are unique and representative of a specific region. Some popular methods include the SCS design storms derived by the National Resources Conservation Services (NRCS) [26], where four types of curves are defined for the entire United States (U.S.), and Huff's curves, which were also initially proposed for the U.S., but today, they are widely used in many other countries, such as China, Singapore, South Korea, Italy, and Slovenia [16,[27][28][29]. Another design storm from this group is the Average Variability Method (AVM), developed by Pilgrim and Cordery [30,31], which has been used in Australia for many years now.…”

“…Pochwat et al [37] evaluated different geometrical patterns of rainfall from the point of view of dimensioning retention facilities and reported that a rainfall pattern defined by a rising quadratic function produced the most critical values (largest retention volume). Na and Yoo [29] evaluated design storms in Korea by comparing them to historical rainfall events and reported that the ABM showed the best agreement with observed storms. Bezak et al [16] assessed the impact of the rainfall duration and temporal rainfall distribution on the flood modeling in a rural catchment in Slovenia.…”

“…Despite significant efforts in evaluating and deriving design storms, the engineering community is still far from a unified view on the optimal choice of a design storm for flood estimation. The lack of clear guidelines and recommendations can be explained by the fact that previous studies [13,16,22,28,29,[34][35][36][37] had sometimes contradictory findings, which suggests that the choice of the optimal design storm depends on the catchment characteristics (size, slope, and land use [41]) and local climate (rainfall). Some of the studies that examined design storms were focused only on the hyetograph shape without an appropriate hydrological or hydraulic analysis [34,36]; some were focused only on stormwater drainage systems and urbanized catchments [22,28,37]; and some were based on a cross-comparison of different design storms without a suitable reference point (e.g., historical event) [16,22,37].…”