Mixed statistical and data mining analysis of river flow and catchment properties at regional scale

Abstract

This paper presents an application of the L-moments and L-moment ratio diagrams (LMRD) to the analysis of hydrological data at regional (country) scale. Existing research focuses on two main areas of the analysis: statistical analysis using LMRD and regression analysis. Further research mixes both approaches applying regression analysis to L-moments. Another direction of the research is clustering of the climatic and physiographic catchment properties and its validation using LMRD. However, LMRD plots can be separately used as the clustering domain. It is proposed to decompose the features into some classes, and than present these results on the LMRD. Such plots constitute the source for the clustering. Obtained clusters are then validated against k-means clustering performed in the LMRD diagram domain. Results show that statistical L-moments analysis can be improved with data mining clustering algorithms. Such combination delivers a new perspective for the interpretation of the results. It is shown that clustering in the LMRD domain is consistent with the K-means clustering. It is anther argument showing that L-moments diagrams can be considered as a very powerful and informative tool for hydrologists enabling the comparison on the regional basis with respect to various catchment properties. The method is validated on data consisting of daily river flow data from 290 gauges covering entire Poland.