Prototype of a LPWA Network for Real-Time Hydro-Meteorological Monitoring and Flood Nowcasting

Douinot, Audrey; Torre, Alessandro Dalla; Martin, Jérôme; Iffly, Jean François; Rapin, Laurent; Meisch, Claude; Bastian, Christine; Pfister, Laurent

doi:10.1007/978-3-030-31831-4_40

“…Six stream-gauges have been installed along the 27.5 km long Ernz Blanche River (Douinot et al, 2019) -crossing two contrasted physiographical settings with a view to TTD comparison. In addition, four rain-gauges and soil moisture sensors were dispatched across the catchment to measure precipitation and soil water content, respectively (Figure 1).…”

Section: The Ernz Blanche Catchmentmentioning

confidence: 99%

Flood patterns in a catchment with mixed bedrock geology: causes for flashy runoff contributions during storm events

Douinot

¹

,

Iffly

²

,

Tailliez

³

et al. 2022

Preprint

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Abstract. With flash flood events having been repeatedly observed in Central and Western Europe in recent years, there is a growing interest in how catchment physiographic properties and hydrological conditions are eventually controlling rapid and concentrated hydrological responses. Here, we focus on a set of two nested catchments in Luxembourg (Europe) that have been exposed in 2016 and 2018 to flash flood events. While being of similar size (~30 km2) and having analogous hydrological distance distributions, their geological bedrock and landscape features are notably different. The upper catchment (KOE) is dominated by marly bedrock (Km3) and moderately steep Luxembourg sandstone outcrops (Li2). The lower catchment has its drainage network deeply cut into the Luxembourg sandstone, with half of it being covered by marly plateaus (Li3) featuring heavy clay soil. Based on data generated from a dedicated hydro-meteorological monitoring network, we calculated for 23 rainfall-runoff events observed between August 2019 and July 2020 the corresponding net rainfall transfer time distributions (TTDs) from the hillslopes to the catchment outlet. We then compared the TTD properties and related them to the catchment’s hydrological state and rainfall properties. We observed a seasonality in TTDs for both catchments, albeit controlled by different factors. In the KOE catchment, we found the water transfer time to be essentially driven by onset and cessation of hydrological connectivity on the flat marly terrain – the latter operating like a variable contributing area in terms of deep soil storage dynamics (except for one summer event). The HM section exhibits contrasted TTDs throughout the year, suggesting threshold dependent hydrological processes. More specifically, particularly quick runoff transfers seem to dominate under dry conditions. Correlation analyses compared to the literature on runoff generation on the one hand and our descriptive knowledge of the catchments on the other hand suggest multiple causes for the triggering of these rapid flows. The fractured marly plateaus, but also the hydrophobic forest litter forming during dry conditions, stand as our main hypotheses in this respect. Moreover, the absence of a riparian zone, preventing any dampening of (observed) abrupt and massive flows during extreme precipitation events, seems as well to be a key feature of the rapid runoff transfer. For improving our understanding and forecasting capabilities in Luxembourg (and more broadly in the nearby regions of Germany, Belgium and France with similar physiographic and climate conditions), we recommend further studies focusing on catchments with fractured bedrock and limited riparian zones. Special attention may equally be given to the hypothesized responses of forest litter and marly soils to heavy precipitation events occurring after extended dry spells.

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“…With a view to study flash flood mechanistics, we have installed a multi-parameter monitoring network in June 2019, geared towards the study of extreme rainfall-runoff responses. Six stream gauges have been installed along the 27.5 km long Ernz Blanche River (Douinot et al, 2019) -crossing two contrasted physiographical settings with a view to TTD comparison. In addition, four rain gauges and soil moisture sensors were dispatched across the catchment to measure precipitation and soil water content, respectively (Fig.…”

Section: The Ernz Blanche Catchmentmentioning

confidence: 99%

Flood patterns in a catchment with mixed bedrock geology and a hilly landscape: identification of flashy runoff contributions during storm events

Douinot

¹

,

Iffly

²

,

Tailliez

³

et al. 2022

Hydrol. Earth Syst. Sci.

4

0

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Abstract. With flash flood events having been repeatedly observed in Central and Western Europe in recent years, there is a growing interest in how catchment physiographic properties and hydrological conditions are eventually controlling rapid and concentrated hydrological responses. Here we focus on a set of two nested catchments in Luxembourg (Europe) that have been exposed in 2016 and 2018 to flash flood events and study their seasonal runoff time transfer distributions. Both catchments are of similar size (∼ 30 km2) and have analogous hydrological distance distributions, but their geological bedrock and landscape features are notably different. The upper catchment (KOE) is dominated by a low land area (38 % of the catchment is located less than 30 m above the river network) consisting of variegated marly bedrock (middle Keuper Km3) and moderately steep Luxembourg sandstone outcrops (lower Liassic Li2). The lower catchment (HM) has its drainage network deeply cut into the Luxembourg sandstone, with half of it being covered by marly plateaus (Lower Liassic Li3, located between 80 and 100 m above the river network) featuring heavy clay soil. Based on data generated from a dedicated hydro-meteorological monitoring network, we calculated for 40 rainfall–runoff events observed between August 2019 and July 2021 the corresponding net rainfall transfer time distributions (TTDs) from the hillslopes to the catchment outlet. We then compared the TTD properties and related them to the catchment's hydrological state and rainfall properties. We observed a marked seasonality in TTDs for both catchments. The KOE catchment reacts fastest during the winter period (December–February), while its response time is most delayed and spread out during periods of catchment recharging (October–November) and drying (March–May). The HM catchment exhibits similar TTDs during the mid-October to mid-April period, but they diverge markedly during the remaining part of the year, with opposite variations. During the mid-April to mid-October period, the average response time increases progressively in the KOE catchment. This behavior is in stark contrast to the HM catchment, where response times are significantly shorter (peak discharge delay time decreases by −70 % ± 28 %) and more concentrated (runoff volume occurring in 1 h increases by +48 % ± 87 %) during the mid-April to mid-October, in comparison to the extended winter period. This opposite seasonality leads us to consider different control factors of the runoff transfer processes in relation with the topographic and geological layout of the catchment areas. In the KOE catchment, we found the TTD to be essentially driven by onset and cessation of hydrological connectivity on the flat marly terrain – the latter operating like a variable contributing area in terms of deep soil storage dynamics (except for one summer event). The HM section exhibits contrasted TTDs throughout the year, suggesting threshold-dependent hydrological processes. More specifically, particularly quick runoff transfers seem to dominate under dry conditions (mid-April to mid-October). Correlation analyses compared to the literature on runoff generation on the one hand and our descriptive knowledge of the catchments on the other hand suggest multiple causes for the triggering of these rapid flows. The fractured marly plateaus, but also the hydrophobic forest litter forming during dry conditions on steep slopes, stand as our main hypotheses in this respect. Moreover, the absence of a riparian zone, preventing any dampening of (observed) abrupt and massive flows during extreme precipitation events, also seems to be a key feature of the rapid runoff transfer. For improving our understanding and forecasting capabilities in Luxembourg (and more broadly in the nearby regions of Germany, Belgium, and France with similar physiographic and climate conditions), we recommend further studies focusing on catchments with fractured bedrock and limited riparian zones. Special attention may equally be given to the hypothesized responses of hydrophobic soil surfaces on steep hillslopes and marly soils to heavy precipitation events occurring after extended dry spells.

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“…Research endeavors regarding water management entail measurements of precipitation, temperature, and flow rate. As shown by [11], several devices can be set up within a river basin to capture not only the final outputs at a confluence, but also the entire development of the water stream.…”

Section: Introductionmentioning

confidence: 99%

Usability of IoT and Open Data Repositories for Analyzing Water Pollution. A Case Study in the Czech Republic

Pavlík

¹

,

Hrnčírová²,

Stočes

³

et al. 2020

IJGI

3

0

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Recently, the process of data opening has intensified, especially thanks to the involvement of many institutions that have not yet shared their data. Some entities provided data to the public long before the trend of open data was pushed to a wider level, but many institutions have only engaged in this process recently thanks to a systemic state-level effort to make data repositories available to the public. Therefore, there are many new potential sources of data available for research, including the area of water management. This article analyses the current state of available data in the Czech Republic—their content, structure, format, availability, costs and other indicators that affect the usability of these data for independent researchers in the area of water management. The case study was conducted to ascertain the levels of accessibility and usability of data in open data repositories and the possibilities of obtaining data from IoT (Internet of Things) devices such as networked sensors where required data is either not available from existing sources, too costly, or otherwise unsuitable for the research. The goal of the underlying research was to assess the impact/ratio of various watershed factors based on monitored indicators of water pollution in a model watershed. Such information would help propose measures for reducing the volume of pollution resulting in increased security in terms of available drinking water for the capital city Prague.

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Prototype of a LPWA Network for Real-Time Hydro-Meteorological Monitoring and Flood Nowcasting

Cited by 3 publications

References 23 publications

Flood patterns in a catchment with mixed bedrock geology: causes for flashy runoff contributions during storm events

Flood patterns in a catchment with mixed bedrock geology: causes for flashy runoff contributions during storm events

Flood patterns in a catchment with mixed bedrock geology and a hilly landscape: identification of flashy runoff contributions during storm events

Usability of IoT and Open Data Repositories for Analyzing Water Pollution. A Case Study in the Czech Republic

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