TY - JOUR
T1 - Effect of subsampling tropical cyclone rainfall on flood hydrograph response in a subtropical mountainous catchment
AU - Huang, Jr Chuan
AU - Kao, Shuh Ji
AU - Lin, Chuan Yao
AU - Chang, Pao Liang
AU - Lee, Tsung Yu
AU - Li, Ming Hsu
N1 - Funding Information:
This study is supported by the Taiwan National Science Council, Project No. NSC-99-2116-M -034-001-MY2 and 99-2621-M-002-030. The authors thank the Northern Region Water Resources Office, Taiwan Central Weather Bureau, and the Water Resources Agency for providing the precipitation, radar reflectivity, and discharge records. Likewise, the authors are grateful to the two reviewers and to Professor K.T. Chang for his insightful comments.
PY - 2011/10/28
Y1 - 2011/10/28
N2 - Accurate rainfall input is a prerequisite for simulations that aim to generate accurate hydrographs, which are crucial for flood forecasting, particularly in regions that are prone to frequent typhoon (tropical cyclone) invasions, such as Southern Asia. Few studies have investigated the effect of spatial resolution in typhoon rainfall monitoring on modeled hydrographs. Eight typhoon cases were examined in a mountainous watershed (335km2) featuring hourly radar-based 1.3-km resolution rainfall estimates. Radar-based hourly rainfall was subsampled at various densities in space, and then re-interpolated to full scale for modeling. The highest resolution rainfall datasets were taken as an ideal input in TOPMODEL for calibration and to derive the reference hydrographs, which were further used to examine the response of modeled hydrographs to imperfect rainfall. The correlation between rainfall similarities (compared with radar-based) and corresponding hydrograph similarities (compared with reference) were identified. The two most important findings were as follows: (1) in predicting flood peak timing in mesoscale watershed, high spatial resolution is not required because typhoon-induced rainfall is less variable in space and more concentrated in the temporal scale and (2) satisfactory hydrographs with EC>0.8 were obtained in 96% test cases, indicating that even a totally biased rainfall (in terms of total amount and rainfall field) may produce a plausible hydrograph. Hydrologic models transfer the spatiotemporal rainfall input into time-series discharge, in which the spatial dimension is converted into travel time. Those positive and negative rainfall biases in space may compensate once allocated in the same arrival time frame in the hydrograph. This explains why in many cases sparsely gauged rainfall input also generates promising hydrographs. In other words, as discussing the effect of other distributed factors on simulated hydrographs, the highly accurate rainfall input is an essential prerequisite to prevent the compensation.
AB - Accurate rainfall input is a prerequisite for simulations that aim to generate accurate hydrographs, which are crucial for flood forecasting, particularly in regions that are prone to frequent typhoon (tropical cyclone) invasions, such as Southern Asia. Few studies have investigated the effect of spatial resolution in typhoon rainfall monitoring on modeled hydrographs. Eight typhoon cases were examined in a mountainous watershed (335km2) featuring hourly radar-based 1.3-km resolution rainfall estimates. Radar-based hourly rainfall was subsampled at various densities in space, and then re-interpolated to full scale for modeling. The highest resolution rainfall datasets were taken as an ideal input in TOPMODEL for calibration and to derive the reference hydrographs, which were further used to examine the response of modeled hydrographs to imperfect rainfall. The correlation between rainfall similarities (compared with radar-based) and corresponding hydrograph similarities (compared with reference) were identified. The two most important findings were as follows: (1) in predicting flood peak timing in mesoscale watershed, high spatial resolution is not required because typhoon-induced rainfall is less variable in space and more concentrated in the temporal scale and (2) satisfactory hydrographs with EC>0.8 were obtained in 96% test cases, indicating that even a totally biased rainfall (in terms of total amount and rainfall field) may produce a plausible hydrograph. Hydrologic models transfer the spatiotemporal rainfall input into time-series discharge, in which the spatial dimension is converted into travel time. Those positive and negative rainfall biases in space may compensate once allocated in the same arrival time frame in the hydrograph. This explains why in many cases sparsely gauged rainfall input also generates promising hydrographs. In other words, as discussing the effect of other distributed factors on simulated hydrographs, the highly accurate rainfall input is an essential prerequisite to prevent the compensation.
KW - Hydrograph
KW - Radar-based rainfall
KW - TOPMODEL
KW - Tropical cyclone
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U2 - 10.1016/j.jhydrol.2011.08.037
DO - 10.1016/j.jhydrol.2011.08.037
M3 - Article
AN - SCOPUS:80054068328
SN - 0022-1694
VL - 409
SP - 248
EP - 261
JO - Journal of Hydrology
JF - Journal of Hydrology
IS - 1-2
ER -