Comparison of methods to estimate areal means of short duration rainfalls in small catchments, using rain gauge and radar data

JOURNAL OF HYDROLOGY

卷:588

Article

Hwang, Seok Hwan¹  Kim, Kue Bum²  Han, Dawei³ 

[1] Korea Inst Civil Engn & Bldg Technol, Dept Land Water & Environm Res, Goyang Si, South Korea

[2] Minist Environm, Water Resources Policy Div, Sejong Si, South Korea

[3] Univ Bristol, Water & Environm Management Res Ctr, Dept Civil Engn, Bristol, Avon, England

关键词: Spatial interpolation method;    Thiessen polygon;    Inverse distance weighting;    Multiquadric interpolation;    Kriging;    Radar rainfall;   

DOI  :  10.1016/j.jhydrol.2020.125084

来源: Elsevier

【 摘 要 】

Flood forecasting for early alerts is a challenging task for hydrologists. This is particularly the case in small catchments due to a lack of upstream gauges and their flashy response. In such catchments, estimating areal mean rainfall at short intervals by applying spatial interpolation schemes based on rain gauge data in short time scales is a significant work for accurate flood forecasting. In this study, we compare and evaluate four commonly used spatial interpolation methods in small catchments, which have small numbers of rain gauges in South Korea. We investigate the impacts of catchment area on different spatial interpolation schemes. Then a simulation is done with hypothetical storms to illustrate the limitation of the Thiessen method. Local heavy rainfall events have been selected for case studies and 10-minute rain gauge rainfall data are used, since short time scales of rainfall data are generally needed for flash flood forecasting and alerts. Furthermore, we analyse the characteristics of different spatial interpolation techniques by comparing the results with weather radar rainfall. The results revealed that mean absolute percentage discrepancy (MAPD) of areal mean rainfall between the Thiessen polygon method and the other three interpolation schemes (Inverse distance weighting, Multiquadric interpolation, Kriging) increases rapidly as the catchment area becomes smaller, especially when the catchment area is less than 500km(2). In addition, regarding the number of rain gauges in a catchment, the smaller the number of rain gauges used in calculating areal mean rainfall, the larger the MAPD becomes, as expected. Furthermore, the number of rainfall events with outliers increased as correlation among rain gauge locations increased, which implies that outliers are more likely to happen when the gauges are located in a linear format rather than in a cluster. Finally, the temporal distributions of areal mean rainfall obtained from rain gauge and weather radar data are different depending on the direction of rainfall movement, especially in sparsely gauged catchments. This study provides a possible guideline for rain gauge number and placement to estimate areal mean rainfall accurately at small catchments.

【 授权许可】

Free