Preprints
https://doi.org/10.5194/hess-2019-683
https://doi.org/10.5194/hess-2019-683
21 Jan 2020
 | 21 Jan 2020
Status: this discussion paper is a preprint. It has been under review for the journal Hydrology and Earth System Sciences (HESS). The manuscript was not accepted for further review after discussion.

On the value of high density rain gauge observations for small Alpine headwater catchments

Anthony Michelon, Lionel Benoit, Harsh Beria, Natalie Ceperley, and Bettina Schaefli

Abstract. Spatial rainfall patterns exert a key control on the catchment scale hydrologic response. Despite recent advances in radar-based rainfall sensing, rainfall observation remains a challenge particularly in mountain environments. This paper analyzes the importance of high-density rainfall observations for a 13.4 km2 catchment located in the Swiss Alps where summer rainfall events were monitored during 3 months using a network of 12 low-cost, drop-counting rain gauges. We developed a data-based analysis framework to assess the importance of high-density rainfall observations to help constrain hydrologic processes.

The framework is based on two steps, the identification of key hydro-meteorological metrics that explain the runoff coefficient and lag times (e.g. total event rainfall, center of mass of the precipitation field) and the identification of the optimal rain gauge network density to reliably reproduce the value of these metrics. The hydrological metrics are evaluated through correlation and regression analysis, resulting in the identification of three main drivers for the runoff coefficient and for runoff response lag times: the areal rainfall, the spatial asymmetry of the rainfall field and the antecedent rainfall over the three days preceding an event.

The relationships between these measures and the optimal network density gives insights into the importance of reliably observing the localisation of incoming rainfall. Even at the small spatial scale of this case study, the results show that an accurate representation of the rainfall field, with at least two rain gauges, is of prime importance to understand the hydrologic response. The largely data-based analysis framework developed here is readily transferable to other settings. Given the low cost of the deployed rainfall sensor network, the approach has potential for future detailed studies in to-date sparsely observed catchments. Future work could in particular also refine the presented analysis by improving the design of the rain gauge deployment to ensure a good representation of geomorphological units and of the relative distances to the stream network.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Anthony Michelon, Lionel Benoit, Harsh Beria, Natalie Ceperley, and Bettina Schaefli
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Anthony Michelon, Lionel Benoit, Harsh Beria, Natalie Ceperley, and Bettina Schaefli

Data sets

2-minute rainfall (12 locations) and discharge time series at the Vallon de Nant catchment, Switzerland, for 2017 and 2018 summer seasons Michelon, Anthony Benoit, Lionel Beria, Harsh Ceperley, Natalie Schaefli, Bettina https://doi.org/10.5281/zenodo.3613841

Anthony Michelon, Lionel Benoit, Harsh Beria, Natalie Ceperley, and Bettina Schaefli

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Latest update: 23 Nov 2024
Short summary
Rainfall observation remains a challenge particularly in mountain environments. Unlike most studies which are model based, this analysis of the rainfall-runoff response of a 13.4 km2 alpine catchment is purely data-based and rely on measures from a network of 12 low-cost raingauges over 3 months. It assesses the importance of high-density rainfall observations to inform hydrological processes and help to design a permanent raingauge network.