Multivariate analysis as a tool to infer hydrologic response types and controlling variables in a humid temperate catchment

Abstract

Abstract:We assess the ability of multivariate statistical analyses applied to event hydrographs parameters, to characterize a catchment hydrological behaviour. Motivation for such an approach lies in the fact that streamflow records have yet to be exploited to their full potential towards hydrological interpretation and can be used to infer a catchment state of connectivity from a qualitative standpoint. We have therefore processed 96 event hydrographs from a small headwater temperate humid forested catchment using principal component analysis, variation partitioning and classification tree analysis. These techniques prove to be promising in discriminating contrasted types of hydrologic responses (e.g. low-vs high-magnitude events, slow vs quick timing events), identifying the main hydro-meteorological variables that control these responses and determining thresholds values of the hydro-meteorological variables leading to a switch between catchment response types.

A case study on the use of appropriate surrogates for antecedent moisture conditions (AMCs)

“…organic versus mineral soil water originating from riparian or upslope areas) to streamflow are strongly correlated to AP 2 and rather weakly correlated to AP 7 , Ali et al (2010b) echo the conclusions of the present study about the appropriateness of AP 2 as a proxy for the Hermine catchment AMCs and the insignificance of AP 7 in that regard. On the contrary to the current paper, Ali et al (2010c) found that AP 10 had an influence on the catchment behaviour only when the cumulative antecedent rainfall amounts lay in the range of 24.5 to 40.5 mm. There again, such a relationship between catchment discharge and AP 10 can be schematized as a rectangular function that does not bear any resemblance with any of the regression models tested in this paper.…”

“…organic versus mineral soil water originating from riparian or upslope areas) to streamflow were also found to be weakly correlated to AP 2 and rather strongly correlated to AP 7 (Ali et al, 2010b). The occurrence of high magnitude and quick timing rainfall-runoff events was also found to be coincident with 10-day cumulative antecedent precipitation amounts ranging from 24.5 to 40.5 mm (Ali et al, 2010c). These contrasting results have prompted the current paper where we wish to examine with direct measures whether the use of different AMCs measures lead to different approximations of the Hermine catchment hydrological state.…”

“…riparian ×× × versus upslope throughfall, organic and mineral soil water) to streamflow Source : Ali et al, 2010b Presence of high magnitude and quick timing rainfall-runoff × events Source : Ali et al, 2010c PET: Mean daily evapotranspiration computed after the temperature-based Hargreaves formula (Hargreaves, 1975) DSP: Number of days since the last rainfall input DSP 10 , DSP 20 , DSP 30 : Number of days since the last rainfall intensity exceeding 10, 20 and 30 mm/d AP 1 , AP 2 , AP 5 , AP 7 , AP 10 , AP 12 , AP 14 : Cumulative precipitation from 1, 2, 5, 7, 10, 12 and 14 days before the survey areas or periods (Ambroise, 2004), and this relates to hydrologic connectivity. Dynamic connectivity of catchment source areas is controlled by the time-changing availability of surface/subsurface storm water, not only in terms of magnitude but also in terms frequency, duration, timing and rate (Bracken and Croke, 2007).…”

Multi-scale hydrometeorological observation and modelling for flash flood understanding

“…For the rainfall/discharge data, several methods, summarizing the catchment behaviour, will be implemented, such as flow duration curves (Vázquez et al, 2008;Willems, 2009), and recession analysis to derive storage-discharge relationships (Kirchner, 2009). Statistical approaches (Ali et al, 2010(Ali et al, , 2012a can relate the hydrological response to explanatory variables that are representative of a scale (rainfall characteristics, lithology, land use, rainfall parameters, initial soil moisture, soil properties, slope). Bayesian networks (Maes et al, 2007) as well as fractal analysis based on lidar DTM (Martin et al, 2014) are also tested for better flash flood understanding.…”

Multi-variate flood damage assessment: a tree-based data-mining approach

“…It has been used in rainfall-runoff analysis, namely to detect thresholds in hydro-meteorological variables corresponding to switching conditions between catchment response types (Ali et al, 2010), and to identify topographic controls on overland flow generation (Loos and Elsenbeer, 2011). In these cases, tree-based models have been applied to multivariate data sets where interactions between parameters and threshold processes played a role.…”