Event-scaled hydrological response of a headwater catchment in Hong Kong

To improve understanding of rainfall-runoff processes and the fundamental hydrological mechanisms, rainfall and runoff data during six hydrological years (2007/06-2012/06) were collected in a small headwater catchment at the Kadoorie Agricultural Research Centre (KARC) in Shek Kong, Yuen Long District, New Territories, Hong Kong. Totally, 28 storms were selected; using the one parameter filter method, the direct and baseflow hydrographs were obtained. Their runoff coefficients (which are the ratios of direct runoff volumes to the total rainfall volumes) were computed and the values were very low (mean value is less than 2%). At the event scale, the results revealed that the runoff coefficient which represents the catchment response was highly correlated with rainfall depth, maximum 15-min rainfall intensity and initial discharge. Linear relationships were found and two variables (rainfall depth and initial discharge) gave a better result to predict runoff coefficient indicating that hydrological response depended both on rainfall depth and initial discharge. The principal component analysis and cluster method were used to discriminate types of hydrological responses. Three types of characteristics of hydrological behavior were identified. The different types of hydrological responses show similar characteristics such as the quick rise and the prolonged recession. This study highlights the importance of interflow in the rainfall-runoff process and provides insight into the relationship between rainfall and runoff. The findings have significant implications for water resources management and will help inform decision-making processes.

Automated summary

Rainfall and runoff data were collected in a small headwater catchment in Hong Kong to study the rainfall-runoff processes. The study found that rainfall depth and initial discharge are important factors in predicting the runoff coefficient. The findings have significant implications for water resources management and decision-making processes.