Identification and estimation of hydrological contributions in a mixed land‐use catchment based on a simple biogeochemical and hydro‐meteorological dataset

Author:

Grandjouan Olivier1ORCID,Branger Flora1,Masson Matthieu1,Cournoyer Benoit2,Coquery Marina1

Affiliation:

1. INRAE, UR Riverly Centre de Lyon‐Villeurbanne Villeurbanne France

2. Univ Lyon, UMR Ecologie Microbienne (LEM) Université Claude Bernard Lyon 1 Marcy L'Etoile France

Abstract

AbstractWater pathways and water contamination in mixed land‐use catchments are complex to understand. Runoff‐generating sources can be numerous and water pathways modified by anthropogenic elements. Monitoring surveys considering geochemical and microbial parameters, are often carried out on such catchment, but are often simple in terms of studied parameters. Nonetheless, they can be helpful to identify the specific signatures of the main runoff‐generating sources and estimate their contribution to total runoff at the outlet of mixed land‐use catchments. Based on a monthly biogeochemical monitoring program conducted between 2017 and 2019 in the Ratier catchment (19.8 km2) near Lyon (France), a step‐by‐step approach was developed to: (1) identify the main runoff‐generating sources using a perceptual model of the Ratier catchment, (2) identify the respective biogeochemical signatures of each source using this biogeochemical dataset and hydro‐meteorological indicators and (3) estimate their contribution to the stream total runoff using an End‐Member Mixing Analysis method. We identified three main runoff‐generating sources outside of rainy periods: a colluvium aquifer, a fractured gneiss aquifer and a saprolite layer. The monitored geochemical datasets were found divided into three groups matching these sources. Contributions of these sources were estimated based on representative tracer concentrations. Microbial parameters showed a homogeneous agricultural and anthropogenic contamination among the catchment surface water, but also deeper into the fractured gneiss groundwater. This approach showed the potential of using simple monitoring datasets to identify runoff‐generating sources and estimate their contribution to total runoff.

Funder

Agence Nationale de la Recherche

INRAE

Publisher

Wiley

Subject

Water Science and Technology

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