Taxon-specific sensitivities to flow intermittence reveal macroinvertebrates as potential bioindicators of intermittent rivers and streams

Abstract Rapid shifts in biotic communities due to environmental variability challenge the detection of anthropogenic impacts by current biomonitoring programs. Metacommunity ecology has the potential to inform such programs, because it combines dispersal processes with niche-based approaches and recognizes variability in community composition. Using intermittent rivers—prevalent and highly dynamic ecosystems that sometimes dry—we develop a conceptual model to illustrate how dispersal limitation and flow intermittence influence the performance of biological indices. We produce a methodological framework integrating physical- and organismal-based dispersal measurements into predictive modeling, to inform development of dynamic ecological quality assessments. Such metacommunity-based approaches could be extended to other ecosystems and are required to underpin our capacity to monitor and protect ecosystems threatened under future environmental changes.

Download Full-text

Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks

10.5194/hess-2017-630 ◽

2017 ◽

Author(s):

Aurélien Beaufort ◽

Nicolas Lamouroux ◽

Hervé Pella ◽

Thibault Datry ◽

Eric Sauquet

Keyword(s):

Headwater Streams ◽

Regional Scale ◽

National Level ◽

Ephemeral Streams ◽

Field Observations ◽

Discrete Observations ◽

Data Set ◽

Intermittent Rivers ◽

The Impact ◽

Flow Intermittence

Abstract. Headwater streams represent a substantial proportion of river systems and have frequently flows intermittence due to their upstream position in the network. These intermittent rivers and ephemeral streams have recently seen a marked increase in interest, especially to assess the impact of drying on aquatic ecosystems. The objective of this paper is to quantify how discrete (in space and time) field observations of flow intermittence help to extrapolate the daily probability of drying at the regional scale. Two empirical models based on linear or logistic regressions have been developed to predict the daily probability of intermittence at the regional scale across France. Explanatory variables were derived from available daily discharge and groundwater level data of a dense gauging/piezometer network, and models were calibrated using discrete series of field observations of flow intermittence. The robustness of the models was tested using (1) an independent, dense regional data set of intermittence observations, (2) observations of the year 2017 excluded from the calibration. The resulting models were used to simulate the regional probability of drying in France: (i) over the period 2011–2017 to identify the regions most affected by flow intermittence; (ii) over the period 1989–2017, using a reduced input dataset, to analyze temporal variability of flow intermittence at the national level. The two regressions models performed equally well between 2011 and 2017. The accuracy of predictions depended on the number of continuous gauging/piezometer stations and intermittence observations available to calibrate the regressions. Regions with the highest performance were located in sedimentary plains, where the monitoring network was dense and where the regional probability of drying was the highest. Conversely, worst performances were obtained in mountainous regions. Finally, temporal projections (1989–2016) suggested highest probabilities of intermittence (> 35 %) in 1989–1991, 2003 and 2005. A high density of intermittence observations improved the information provided by gauging stations and piezometers to extrapolate the spatial distribution of intermittent rivers and ephemeral streams.

Download Full-text

An EU-wide citizen science network to monitor hydrological conditions in intermittent rivers and ephemeral streams

10.5194/egusphere-egu2020-1790 ◽

2020 ◽

Author(s):

Eric Sauquet ◽

Ilja van Meerveld ◽

Cath Sefton ◽

Josep Fortesa ◽

Helena Ramos Ribeiro ◽

...

Keyword(s):

Citizen Science ◽

Current Flow ◽

Local Scale ◽

Ephemeral Streams ◽

Intermittent Streams ◽

Flow State ◽

Intermittent Rivers ◽

Flow Intermittence ◽

International Initiative

Studying Intermittent Rivers and Ephemeral Streams (IRES) requires regular observations of streamflow. Unfortunately, intermittent streams are poorly monitored, particularly in temperate climates. To fill gaps in knowledge of the dynamics of intermittent streams, a pilot initiative within the SMIRES project (Datry et al., 2017, https://www.smires.eu/) was launched in April 2019. This initiative invited citizens to submit observations for a large number of European intermittent streams.The goal was collecting datasets that can be used in robust scientific inquiries:-&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; To identify IRES at the European scale. Everyone was encouraged to report the flow state for any stream in Europe at any time during 2019;-&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; To investigate the dynamics of flow intermittence by repeating field observations along an IRES at least once each month and if possible at multiple locations.The CrowdWater app (https://crowdwater.ch/en/crowdwaterapp-en/) was used to collect the observations. Each contributor was asked to take a picture of the stream and to identify the current flow state of the stream as one of six classes, from &#8220;dry&#8221; to &#8220;flowing&#8221;. The citizen science network has collected, in eight months, more than 3500 observations in ~500 river reaches across 15 countries.In this presentation, we will discuss the benefits and the limitations of this citizen science effort (i.e., how these data complement the information provided by gauging stations, how and why the collected data were used by the main contributors, how participants can be engaged in the long-term etc.). We will compare the success of this international initiative to other regional or local scale initiatives.References:Datry, T., Singer, G., Sauquet, E., Jorda-Capdevilla, D., Von Schiller, D., Subbington, R., Magand, C., Pa&#345;il, P., Mili&#353;a, M., Acu&#241;a, V., Alves, M., Augeard, B., Brunke, M., Cid, N., Csabai, Z., England, J., Froebrich, J., Koundouri, P., Lamouroux, N., Mart&#237;, E., Morais, M., Munn&#233;, A., Mutz, M., Pesic, V., Previ&#353;i&#263;, A., Reynaud, A., Robinson, C., Sadler, J., Skoulikidis, N., Terrier, B., Tockner, K., Vesely, D., Zoppini, A (2017) Science and Management of Intermittent Rivers and Ephemeral Streams (SMIRES). Research Ideas and Outcomes 3: e21774. https://doi.org/10.3897/rio.3.e21774

Download Full-text

Assessing flow intermittence in France under climate change

10.5194/egusphere-egu2020-9420 ◽

2020 ◽

Author(s):

Aurélien Beaufort ◽

Quentin Bottet ◽

Guillaume Thirel ◽

Eric Sauquet

Keyword(s):

Climate Change ◽

Empirical Model ◽

Headwater Streams ◽

Low Flow ◽

Additional Stress ◽

Discrete Observations ◽

Aquatic Life ◽

Current Climate ◽

Intermittent Rivers ◽

Flow Intermittence

With climate change, perennial headwater streams are expected to become intermittent and intermittent rivers to dry more often due to more severe droughts, placing additional stress on aquatic life and new constraints for water management.In this study, we quantify the changes in river flow intermittence across France over the 21st century. Using global hydrological model calibrated on gauging stations is certainly hazardous to assess changes in flow intermittence at a fine resolution (i.e. in headwater streams). Here, we suggest a modelling framework supported by field observations performed on a large number of French intermittent streams:- we used discrete observations from the ONDE network set up by the French Biodiversity Agency recording summer low&#8208;flow levels once a month. ONDE sites are located on headwater streams with a Strahler order strictly less than five and evenly distributed throughout France;- a model developed by Beaufort et al. (2017) was adapted to simulate the regional probability of drying of headwater streams (RPoD) under climate change. This empirical model is based on regional relationships established between the non-exceedance frequencies of daily discharges and the proportion of drying statuses observed at ONDE sites. Calibration was performed against the discrete flow states available at 3300 ONDE sites between May and October from 2012 to 2018. The model used daily discharges simulated at 568 gauging stations by the GR6J rainfall-runoff model (Pushpalatha et al., 2011).An ensemble of 26 high-resolution projections has been derived from GCM simulations under RCP2.6 and RCP8.5 emission scenarios, applying an advanced delta change approach (van Pelt et al., 2012). Daily discharge time series at the 568 gauging stations obtained from GR6J with the GCM-driven forcings have been used as inputs of the empirical model to estimate RPoD under future climate conditions.Characteristics of flow intermittence between May and October have been studied over France divided into 22 Hydro-EcoRegion. Results for the periods 2021-2050 and 2071-2100 show an increase in RPoD with time. The mean RPod over the whole period May&#8211;October is 12% at the national scale under the current climate, compared to 20% and 23% on average all RCPs together for the periods 2021-2050 and 2071-2100, respectively. The changes are significant in regions with historically high probability of drying. On the other hand, no change is detected in the Alps. This last result is debatable since, in these areas and under the current climate, low flows are mostly observed in winter, the ONDE sites are sparse and the model predicting RPoD shows the worst performance.References:Beaufort et al.: Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks, Hydrol. Earth Syst. Sci., 22(5), 3033&#8211;3051, 2018.Pushpalatha et al.: A downward structural sensitivity analysis of hydrological models to improve low-flow simulation, J. Hydrol., 411, 66&#8211;76, 2011.van Pelt et al.: Future changes in extreme precipitation in the Rhine basin based on global and regional climate model simulations, Hydrol. Earth Syst. Sci., 16, 4517&#8211;4530, 2012.

Download Full-text

Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks

Hydrology and Earth System Sciences ◽

10.5194/hess-22-3033-2018 ◽

2018 ◽

Vol 22 (5) ◽

pp. 3033-3051 ◽

Cited By ~ 11

Author(s):

Aurélien Beaufort ◽

Nicolas Lamouroux ◽

Hervé Pella ◽

Thibault Datry ◽

Eric Sauquet

Keyword(s):

Temporal Variability ◽

Headwater Streams ◽

Regional Scale ◽

National Level ◽

Ephemeral Streams ◽

Field Observations ◽

Discrete Observations ◽

Intermittent Rivers ◽

The Impact ◽

Flow Intermittence

Abstract. Headwater streams represent a substantial proportion of river systems and many of them have intermittent flows due to their upstream position in the network. These intermittent rivers and ephemeral streams have recently seen a marked increase in interest, especially to assess the impact of drying on aquatic ecosystems. The objective of this paper is to quantify how discrete (in space and time) field observations of flow intermittence help to extrapolate over time the daily probability of drying (defined at the regional scale). Two empirical models based on linear or logistic regressions have been developed to predict the daily probability of intermittence at the regional scale across France. Explanatory variables were derived from available daily discharge and groundwater-level data of a dense gauging/piezometer network, and models were calibrated using discrete series of field observations of flow intermittence. The robustness of the models was tested using an independent, dense regional dataset of intermittence observations and observations of the year 2017 excluded from the calibration. The resulting models were used to extrapolate the daily regional probability of drying in France: (i) over the period 2011–2017 to identify the regions most affected by flow intermittence; (ii) over the period 1989–2017, using a reduced input dataset, to analyse temporal variability of flow intermittence at the national level. The two empirical regression models performed equally well between 2011 and 2017. The accuracy of predictions depended on the number of continuous gauging/piezometer stations and intermittence observations available to calibrate the regressions. Regions with the highest performance were located in sedimentary plains, where the monitoring network was dense and where the regional probability of drying was the highest. Conversely, the worst performances were obtained in mountainous regions. Finally, temporal projections (1989–2016) suggested the highest probabilities of intermittence (> 35 %) in 1989–1991, 2003 and 2005. A high density of intermittence observations improved the information provided by gauging stations and piezometers to extrapolate the temporal variability of intermittent rivers and ephemeral streams.

Download Full-text