HS2.1.1 | Zero flow: hydrology, biogeochemistry, and ecology of non-perennial streams
EDI PICO
Zero flow: hydrology, biogeochemistry, and ecology of non-perennial streams
Convener: Ilja van Meerveld | Co-conveners: Nicola Durighetto, Mirjam Scheller, Catherine Sefton, E. Sauquet
PICO
| Fri, 19 Apr, 08:30–10:15 (CEST)
 
PICO spot A
Fri, 08:30
A large proportion of the global stream network ceases to flow periodically. These systems range from near-perennial streams with infrequent, short periods of zero flow to streams that experience flow only episodically after large rainfall events. The onset of streamflow in intermittent streams can affect the quantity and quality of water in downstream perennial rivers. Intermittent streams also support a unique and high biodiversity because they are coupled aquatic-terrestrial systems. However, non-perennial rivers and streams are usually unmonitored and often lack protection and adequate management. There is a clear need to study the hydrology, biogeochemistry and ecology of natural intermittent and ephemeral streams to characterize their flow regimes, to understand the main origins of intermittence and how this affects biogeochemistry and biodiversity, and to assess the consequences of altered flow intermittence due to climate change or other anthropogenic impacts.
This session welcomes all contributions on the science and management of non-perennial streams, and particularly those highlighting:
· current advances and approaches in monitoring and modelling flow intermittence,
· the effects of flow in non-perennial streams on downstream perennial stream water quantity and quality,
· the factors that affect the dynamics of the flowing stream network,
· land use and climate change impacts on flow intermittence,
· links between flow intermittence and biogeochemistry and/or ecology.
· public perceptions (and natural capital/ecosystem services) of non-perennial rivers,
· approaches to determine reference conditions on non-perennial rivers.

Session assets

PICO: Fri, 19 Apr | PICO spot A

Chairpersons: Ilja van Meerveld, Nicola Durighetto, Mirjam Scheller
08:30–08:35
08:35–08:37
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EGU24-15164
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ECS
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Virtual presentation
Deependra Choudhary, Sumit Sen, and Rahul Kulkarni

A comprehensive exploration of streamflow dynamics at the watershed scale in non-perennial rivers is an arduous task. In the lower Himalayan region, the presence of numerous intermittent and ephemeral streams contributes to high volume of water for small duration and transports significant amount of sediment to downstream. Fluvial alterations reshape stream geomorphology, triggering flash floods. To map those head water streams, a comprehensive study within the lower Himalayan watershed of area 56.61 km2 has been done by developing the low-cost capacitive soil moisture sensors. This real time monitoring sensor is a microcontroller-based system and an indirect method for indicating the soil moisture content. These sensors have been strategically deployed across three distinct sub-watersheds within the headwater watershed to capture the continuous soil moisture response during the monsoon period in 2023. For analyzing this study, on-field data was collected from automated weather stations (AWS) to obtain rainfall data, which was complemented by the utilization of stage-discharge curves for a more thorough understanding of discharge fluctuation. During 2023 monsoon period 9 rainfall events were recorded and identified as small, medium, and high to get the rainfall- runoff relationship with antecedent moisture condition (AMC). From the analysis different signatures in capacitance value are found to be affected by several factors which include slope, % area, stream order and land cover. These thresholds will aid in accurately mapping streams, and by quantifying discharge capacity, sediment transportation analyses can be facilitated in future. This study will enhance management strategies for sediment transport and ecological health within the high-gradient headwater watersheds. 

How to cite: Choudhary, D., Sen, S., and Kulkarni, R.: Development of low-cost soil moisture sensor to capture the response of headwater streams in lower Himalayan region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15164, https://doi.org/10.5194/egusphere-egu24-15164, 2024.

08:37–08:39
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EGU24-55
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Virtual presentation
Thallam Prashanth, Sayantan Ganguly, Manoj Gummadi, and Dharmaraj Teppala

In recent times, several countries all around the world are experiencing groundwater droughts that are drying up surface water bodies (SWBs), such as rivers, marshes, lakes, etc. For implementing proper water management strategies, it is important to identify the SWBs that are continuously dependent upon the local groundwater reserve to feed them. SWBs that have some reserve throughout the year are fed by the local groundwater during the dry seasons. The rivers, lakes, and wetlands that exhibit these characteristics are referred to as perennial SWBs. Losing SWBs refers to the rivers, lakes, and wetlands for which the groundwater table is lower than the surface water elevation, and thus do not possess perennial characteristics. The water spread areas of SWBs in the Godavari basin are mapped by utilizing Normalized Difference Water Index (NDWI) or Automatic Water Extraction Index (AWEI). The NDWI or AWEI were obtained by using multi-temporal Landsat or Sentinel Satellite datasets in the Google Earth Engine (GEE) platform. Due to the limited spatial resolution of the satellite data, this analysis only considers water bodies with a surface area greater than 3,600 m2. The standardized water spread area index (SWSAI) is used to calculate the magnitude of the surface water drought of different water bodies with respect to space and time. The SWSAI is determined by using the water spread area from NDWI or AWEI by assuming that the water spread area increases due to increase in water surface elevation.  The standardized groundwater table index (SGWTI) is used here to compute the magnitude of groundwater table drought by using the depth of the water table in different observation wells obtained from various central and state government agencies in India. The primary goal of this study is to identify and map the drought sensitive zones responsible for river aridity by plotting correlation matrix for SGWTI of different observation wells. The second objective of this study is to map the spatio-temporal variation of SWSAI of different surface water bodies like ponds, lakes, and wetlands, etc. in the Godavari River Basin, India. The third aim is to determine the correlation between the SGWTI and SWSAI as well as identify the surface water bodies that are influenced by groundwater drought. By this procedure, it would be feasible to determine whether or not there is a connection between the travel time for the groundwater drought propagating from minor surface water bodies (wetlands, lakes, ponds, etc.) to major ones (rivers). It can thus be proved that the surface water dryness in wetlands, lakes progresses towards the rivers due to presence of groundwater drought in the river basin. A correlation (ranging from 0.81 to 0.9) between the depth of connectivity of surface water-groundwater with the SGWTI is computed in this study to demonstrate that the upper Godavari River is highly affected by the groundwater drought, whereas, the middle Godavari river is moderately influenced and the lower Godavari river is less influenced by it.

How to cite: Prashanth, T., Ganguly, S., Gummadi, M., and Teppala, D.: Identification and mapping the surface water bodies that are sensitive to groundwater drought in the Godavari basin, India , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-55, https://doi.org/10.5194/egusphere-egu24-55, 2024.

08:39–08:41
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PICOA.1
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EGU24-17373
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ECS
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On-site presentation
Carmela Cavallo, Maria Nicolina Papa, Giovanni Negro, Massimiliano Gargiulo, Giuseppe Ruello, and Paolo Vezza

At present there is a great lack of hydrological information on non-perennial rivers. In many cases, there is no knowledge of which river reaches are subject to non-flow periods, and the duration of non-flow and dry periods remains unknown. Few hydrometric stations are present along non-perennial rivers, and these stations provide point information, limiting the ability to describe the flow conditions across a river reach. For example, they do not allow to distinguish a continuous line of flow from an isolated pools condition. In contrast, approaches based on field surveys or citizen science can provide information on flow condition over entire river reaches but their temporal resolution is generally poor. Within this framework, satellite remote sensing provides significant opportunities due to the possibility of monitoring large areas with high temporal resolution. However, the use of satellite images for monitoring non-perennial river regimes has so far been limited by the availability of images with adequate spatial resolution and their accessibility in terms of cost. Multispectral satellite data freely distributed by the European Space Agency's Copernicus Sentinel-2 mission, with a spatial resolution of 10 m and an acquisition frequency of approximately five days, represent an appropriate trade-off point for monitoring non-perennial rivers with active channels not covered by vegetation and larger than about 40 m.

In this study, we investigated the capability of Sentinel-2 data to differentiate among three flowing states of non-perennial rivers: "flowing" (F), "ponding" (P), and "dry" (D). The analysis was performed for 5 reaches of the streams Sciarapotamo, Mingardo and Lambro (Campania region, Italy). By analyzing the spectral signatures of land cover within river corridor, we identified the bands in which land cover classes are most differentiated. Utilizing these specific bands, we created a false-color image in which the pixels covered by water stand out from the background. The comparison between false color images and field acquired ground truth showed very good agreement. For all the archive data (since 2015) we identified one of the three possible flowing status: F, P and D. The acquired dataset was utilized to train a Random Forest model capable of predicting the daily occurrence of specific flowing statuses (F, P, D), using spatially interpolated rainfall and air temperature data as predictors. The model demonstrated strong performance in terms of accuracy (ranging from 82% to 97%) and true skill statistic (ranging from 0.65 to 0.95). In each of the five years of the observation period, all the reaches underwent no-flow condition for at least a few days and in some cases up to four months. Three of the five reaches were completely dry each year while the other two never dried completely. With its ability to monitor the presence of water in a cost-effective manner, this method has the potential to significantly improve the knowledge on non-perennial rivers regimes.

How to cite: Cavallo, C., Papa, M. N., Negro, G., Gargiulo, M., Ruello, G., and Vezza, P.: Estimating the duration of flow status along non perennial rivers by satellite data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17373, https://doi.org/10.5194/egusphere-egu24-17373, 2024.

08:41–08:43
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PICOA.2
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EGU24-9748
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ECS
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On-site presentation
Nicola Durighetto and Gianluca Botter

River networks are not static entities, as they dynamically respond to the time-variant climatic conditions in the surrounding landscape. Over time, rivers change in both the streamflow Q, as the hydrograph continuously peaks and recedes, and active length L, as the temporary (i.e. non perennial) reaches wet up and dry down. As such, a correlation between L and Q has long been recognized in literature, starting with the first empirical studies dating back to 1968. More recently, a few conceptual frameworks have attempted to explain the physical processes that relate L with Q, showing how the shape of the L(Q) relation is determined by the spatial distribution of the subsurface transport capacity along the network (i.e. the maximum specific flow by unit contributing area delivered downstream in the hyporheic region). Knowing the functional form of the L(Q) relation can be useful in a number of ways, including the following: a) it creates a link between the temporal dynamics of L and Q, allowing one to exploit widely available streamflow datasets to study temporary streams; b) it gives information on invisible subsurface properties of the hyporheic zone; and c) it may provide more reliable predictions of the configuration of the active portion of the network during hydrological conditions that have not been observed yet.

In this contribution, we studied the shape of the L(Q) relation in 45 different catchments around the world, spanning a wide range of climates, geology, morphology, and catchment area. We found that L(Q) relations can be split in 3 main categories: a) generally increasing relations, b) relations showing a plateau for the higher values of Q due to the presence of a maximum potential network that can't be exceeded, and c) relations with a sigmoid shape, when the network length is constant for the driest hydrological conditions e.g. because it is fed by a local perennial source. We speculate that, in most cases, the presence of a plateau or sigmoid shape might not be visible in the data due to the limited number of observations for the relevant high and low flow conditions. For each catchment we also tested different functional forms for the L(Q) relation and selected 3 analytical forms that are best suited to fit the available data (exponential, gamma, power-law). The power law generally performed reasonably well, even though it overestimated L for the largest values of Q in those cases in which a maximum potential wet network is observed. In most cases, the exponential distribution described the plateau quite well but has a reduced performance for the lower flowrates. The gamma distribution, instead, shows the best performance in describing L(Q) relations in all categories. The proposed contribution aims at identifying new general patterns common to all temporary streams, creating new modelling tools that enable large scale studies and giving new tools for the effective monitoring of dynamic river networks.

How to cite: Durighetto, N. and Botter, G.: The shape of the active length vs streamflow relation in temporary streams, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9748, https://doi.org/10.5194/egusphere-egu24-9748, 2024.

08:43–08:45
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PICOA.3
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EGU24-15302
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ECS
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On-site presentation
Mirjam Scheller, Nicola Durighetto, Ilja van Meerveld, Jan Seibert, and Gianluca Botter

Temporary streams (i.e., non-perennial streams) cover more than half of the global stream network. They are highly dynamic systems and important habitats. Still, they have so far not been thoroughly monitored because gauging stations are expensive, not well suited for measuring zero flows, and provide only data for a single location in the stream network. An alternative way to monitor temporary streams is by visual assessment. However, on-the-ground surveys of stream networks tend to be highly time-consuming. Hence, visual observations by citizen scientists provide a great opportunity to collect high spatial- and temporal resolution data, even though there are challenges regarding the accuracy and irregularity of the observations.

To assess the potential of citizen science data to obtain temporal resolved information on the state of temporary streams, we used the observations submitted by citizen scientists using the CrowdWater app for 63 locations on a 5 km2 forested hill in Zurich, Switzerland. The number of observations per location during the last three years varied from 1 to 257 (median: 40). There was at least one stream state observation for 402 days, with a maximum of 42 observations per day and a median of 10 observations per day. In addition, trained staff monitored 59 streams (30 overlap with the citizen science data set) at an almost bi-weekly resolution during six months (24 days of observations at all 59 points).

The hierarchical structure of channel network dynamics postulates the existence of a fixed, unique order according to which stream segments are activated during network expansion (from the most to the least persistent). To understand the hierarchical structure of stream wetting and drying at the study site, we applied the graph-based method developed by Durighetto et al. (2023) on the available data. This data-driven method would allow us to fill the gaps of the irregular citizen science data (leading to 25,728 reconstructed observations compared to the 4,354 original observations). The hierarchical structures for the two datasets differed, even if only locations that were part of both data sets and the same period were used to determine the hierarchical structure. In the citizen science dataset, the order of activation of the observed stream locations is less clearly identifiable (i.e., more uncertain). This is likely due to the non-systematic and sporadic nature of the data, i.e., only a few stream observations on the same date, as well as errors in the data. Nonetheless, this information can be used to give guidance to the citizen scientists on which streams to observe more frequently because they provide the most crucial information about the wetting and drying patterns of the network.

 

Reference: Durighetto, N., Noto, S., Tauro, F., Grimaldi, S., & Botter, G. (2023). Integrating spatially-and temporally-heterogeneous data on river network dynamics using graph theory. Iscience, 26(8).

How to cite: Scheller, M., Durighetto, N., van Meerveld, I., Seibert, J., and Botter, G.: Combining citizen science data and the hierarchical structuring of temporary streams to reconstruct the patterns of channel wetting and drying, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15302, https://doi.org/10.5194/egusphere-egu24-15302, 2024.

08:45–08:47
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PICOA.4
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EGU24-17603
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On-site presentation
Ronan Abhervé, Clément Roques, Jean-Raynald de Dreuzy, Thibault Datry, Philip Brunner, Laurent Longuevergne, and Luc Aquilina

While the role of climate conditions in controlling streamflow intermittence is well recognised, the assessment and modelling of the role of groundwater remains a challenge. In this study, we use process-based 3D groundwater flow models to simulate stream intermittency in groundwater-fed headwaters. Streamflow measurements and stream network maps are considered together to constrain the effective hydraulic properties of the aquifers. The modelling framework has been applied and validated in pilot catchments with unconfined crystalline aquifers (France) with contrasting geomorphological settings. We present the calibration framework, the analysis of uncertainties and discuss the underlying mechanisms governing the different dynamics of streamflow intermittency. The models are then used to predict streamflow intermittence under future climate scenarios. Intuitively, with decreasing recharge rates, systems with lower storage capacities lead to higher water table fluctuations, increasing the proportion of intermittent streams and reducing future perennial flows. However, the pilot sites reveal nuanced feedback mechanisms among future climate variations, groundwater recharge dynamics, and stream intermittence, where the geomorphic characteristics of the landscapes are key to regulating these feedbacks.

How to cite: Abhervé, R., Roques, C., de Dreuzy, J.-R., Datry, T., Brunner, P., Longuevergne, L., and Aquilina, L.: Process-based 3D groundwater flow model to simulate current and future stream intermittence in headwaters, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17603, https://doi.org/10.5194/egusphere-egu24-17603, 2024.

08:47–08:49
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PICOA.5
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EGU24-16251
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ECS
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On-site presentation
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Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal

Intermittent and ephemeral streams account for more than half of the world’s river channels, yet their hydrological functioning remains understudied. Modelling non-perennial river systems can help understanding the spatio-temporal patterns of drying and rewetting, but is challenging due to limited monitoring in intermittent river networks.

This study is part of the EU-funded project DRYvER, which aims to understand the repercussions of drying river networks for biodiversity, functional integrity, and ecosystem services (Datry et al. 2021). Here we propose a novel hydrological modelling approach using the J2000 distributed hydrological model (Krause et al. 2006), coupled with a Random Forest classification model, to predict daily and spatially distributed flow conditions (flowing or dry). The hybrid flow intermittence model is trained using observed flow condition data from diverse sources, such as water level measurements, photo traps, remote sensing, and citizen science applications (Mimeau et al, 2023). We evaluate the model's performance in three European River Networks in Finland, France, and Spain.

Results show that the hybrid flow intermittence model accurately predicts the drying events, with a probability of prediction of a drying event above 0.9 for the French and Finnish study cases. The spatio-temporal patterns of flow intermittence are contrasted among the 3 study cases: while the model simulates a few drying episodes during the summer season in the Finnish case study, mainly in the small upstream tributaries, it also simulates more complex drying patterns in the French and Spanish case studies, with drying episodes occurring throughout the year and drying events in the main river sections.

Additionally, we provide insights on the role of the observed data used to train the model on the simulated flow intermittence patterns. Results indicate that the quantity of observed data, as well as their temporal distribution, their spatial location in the river network, and the representativeness of the observed flow condition can have a significant impact on the simulation performance of flow intermittence. This study shows that combining different sources of observed flow condition data can help to reduce the uncertainty in predicting flow intermittence.

 

Datry et al. (2021) Securing Biodiversity, Functional Integrity, and Ecosystem Services in Drying River Networks (DRYvER). Research Ideas and Outcomes. https://doi.org/10.3897/rio.7.e77750.

Krause et al. (2006) Multiscale investigations in a mesoscale catchment: hydrological modelling in the Gera catchment. Advances in Geosciences. https://doi.org/10.5194/adgeo-9-53-2006.

Mimeau et al. (2023) Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-1322.

How to cite: Mimeau, L., Künne, A., Branger, F., Kralisch, S., Devers, A., and Vidal, J.-P.: Using a hybrid hydrological modelling approach to simulate drying patterns in 3 non-perennial European river networks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16251, https://doi.org/10.5194/egusphere-egu24-16251, 2024.

08:49–08:51
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PICOA.6
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EGU24-9917
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ECS
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On-site presentation
Andrés Casanova, Rémi Dupas, Anne Jaffrezic, and Ophélie Fovet

Intermittent rivers and ephemeral streams (IRES) are watercourses that stop flowing at some point during the year. IRES are found in all climates and biomes and their occurrence is predicted to increase with climate change and increasing demand for freshwater. Knowledge of biogeochemical cycles in IRES is mainly based on research in the Mediterranean region. The region of Brittany in western France, characterised by a temperate oceanic climate and intensive agriculture, offers research opportunities to understand C-N-P dynamics in temperate IRES with high nutrient loadings.

In this work, we analyse the spatial variability of C-N-P concentrations in the intermittent stream network of the Kervidy-Naizin catchment (7 km²) during the different phases of intermittency. We hypothesise that the spatial variability of C-N-P concentrations increases during the stream fragmentation, as the formation of isolated pools leads to different physico-chemical conditions due to variable solar radiation, temperature, and nutrient availability. To investigate this, we conducted repeated synoptic sampling campaigns at a high spatial resolution (every 100 to 200 m) along the stream network during the spring-summer of 2023. We sampled forty sites and analysed, among others, DOC, DIN and TP and physico-chemical parameters (conductivity, redox potential, temperature and pH) during four field campaigns spanning from stream recession to the rewetting phase after the summer dry period.

The results showed an increasing spatial variability of concentrations with stream fragmentation, with spatial coefficients of variation increasing from 27% to 49% for DOC, from 15% to 64% for DIN and from 44% to 74% for TP. During the stream fragmentation, mean DOC concentrations increased from 2.43 to 4.76 mg.L-1, mean DIN concentrations decreased from 15.1 to 8.47 mg.L-1 and mean TP concentrations increased from 0.023 to 0.071 mg.L-1. Spatial patterns of concentrations observed during the flowing phase tended to be disrupted by the stream fragmentation, with isolated pools exhibiting extremely high or low concentration values. We interpret these changes in spatial patterns as a consequence of redox processes and nutrient assimilation.

How to cite: Casanova, A., Dupas, R., Jaffrezic, A., and Fovet, O.: Spatial variability in C-N-P concentrations during the fragmentation of an intermittent stream in a temperate agricultural catchment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9917, https://doi.org/10.5194/egusphere-egu24-9917, 2024.

08:51–08:53
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PICOA.7
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EGU24-12388
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On-site presentation
Chiara Marchina, Amponsah William, Gelmini Ylenia, Borga Marco, and Zuecco Giulia

Hydrological studies on temporary streams are crucial for understanding their activation and response during wet and dry conditions. Additionally, the use of geochemical tracers (e.g., electrical conductivity, water stable isotopes, major ions) can help assess the impact of climate change on these ephemeral water bodies. This study aims to i) investigate the relation between discharge and tracer concentration at different spatial scales and at the seasonal and event scales; ii) analyze the effect of antecedent conditions on tracer temporal variability at different spatial scales; iii) compare the contribution of rainwater to stream runoff at three scales during selected rainfall-runoff events. The work relies on an integrated database of isotopic and geochemical compositions of water samples coupled with hydrometeorological data from the Regional Environmental Agency (ARPAV) in the 116 km2 Posina catchment in the Italian pre-Alps. The lithology consists mainly of carbonate rocks, and the typical fracturing of dolomites and limestones facilitates water infiltration, thus favoring the presence of temporary streams during dry periods. Conversely, the limited presence of volcanic rocks in some sub-catchments tends to favor perennial streams characterized by a rapid response to rainfall events. In this work, water samples were collected from the Posina river and its main tributaries between September 2015 and March 2019. Temperature and electrical conductivity were measured in the field by portable probes, whereas major ions and water stable isotopes were analyzed by ion chromatography and laser spectroscopy, respectively. Preliminary results show that relationships between discharge and tracer concentration reveal significant associations: δ18O increases with discharge, whereas electrical conductivity (EC) shows a decreasing trend with discharge, better represented by logarithmic and polynomial functions for different selected sections of the main streams and tributaries. Similar trends are observed for sulphates and sodium.  Discharge data at Ressi (a tributary flowing on volcanic rocks) and Posina at catchment outlet have also been compared with selected tracer data from water samples from these two sections. Positive correlations are found between average tracer concentration (δ2H, δ18O, and nitrates) and peak antecedent discharge, while negative correlations exist for δ2H, EC, chloride, sulphates, bicarbonate ions, sodium, magnesium, and calcium. Antecedent precipitation positively correlates with δ2H and nitrates but negatively with sulphates and sodium. EC shows positive (negative) correlations with δ2H and nitrates (sulphates and sodium), respectively, with varying patterns along different sections and tributaries. The 5-day antecedent rainfall exhibits the highest correlations with tracer compositions, particularly for EC, δ2H, and nitrates. The obtained results suggest the importance of an interdisciplinary approach in the analysis of the hydrological and geochemical connectivity of temporary stream networks.

How to cite: Marchina, C., William, A., Ylenia, G., Marco, B., and Giulia, Z.: Exploring tracer dynamics at different spatial scales in a pre-Alpine catchment with a temporary stream network, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12388, https://doi.org/10.5194/egusphere-egu24-12388, 2024.

08:53–08:55
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PICOA.8
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EGU24-153
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ECS
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On-site presentation
Famin Wang, Doerthe Tetzlaff, Jonas Freymueller, and Chris Soulsby

This study investigates the spatio-temporal dynamics of water quality in a 70 km2 mixed land use, lowland catchment in NE Germany over a four-year period (2018-2022). During this period with a consistent negative rainfall anomaly compared to the long-term average, the intermittent stream network exhibited three distinct hydrological phases each year, with important implications for water quality. Autumn and early winter featured a connecting phase, where spatially variable stream flows responded to rising water tables following increased rainfall and reduced evapotranspiration. The winter and early spring saw a fully connected phase, marked by increased stream flows throughput the catchment. Late spring and early summer experienced a disconnecting phase as flow gradually reduced and stopped in various parts of the catchment before ceasing altogether. A peat wetland in the centre of the catchment exhibited both the earliest and latest stream flows.

Water quality was characteristic of a eutrophic lowland catchment and displayed spatial variations linked to catchment soils and land use. During the connecting phase, stream water quality mirrored that of groundwater and saw mobilization of dissolved organic carbon from wetland areas. In the fully connected phase, stream water became enriched with contributions from soil water and a higher nitrate load from agricultural areas. The disconnecting phase was characterized by lower flows and higher temperatures, contributing to increasingly anoxic conditions which saw nitrate reduction, mobilization of redox elements (Fe and Mn) and release of P. Intermittency caused a transition in stream water quality from hydrological process control in the connecting phase to joint control of hydrological and biogeochemical processes in the fully connected phase and then to biogeochemical process control in the disconnecting phase.

Inter-annual water quality variation was associated with hydroclimate and catchment wetness dynamics, involving flushing and accumulation. Considering intermittency as an influencing variable changed the inter-annual characteristics of flow-concentration relationships compared with the previous perennial river stage, especially for nitrate. These findings have significant implications for the ecology and management strategies in similar catchments, highlighting the need to consider the seasonal hydrological phases for effective water quality management and ecological preservation.

How to cite: Wang, F., Tetzlaff, D., Freymueller, J., and Soulsby, C.: Hydrological connectivity dynamics in a mixed land use lowland catchment drive intra- and inter-annual variation in water quality in an intermittent stream network under drought conditions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-153, https://doi.org/10.5194/egusphere-egu24-153, 2024.

08:55–08:57
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PICOA.9
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EGU24-16283
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ECS
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On-site presentation
Yao Li, Seifeddine Jomaa, Gunnar Lischeid, and Michael Rode

River network is usually not a static item. More than half of global river exhibit an intermittent pattern, ceasing to flow during drought and rewetting again as the environment getting wetter seasonally. Recently, climate change has led to intensified droughts in central and southern Europe, causing even perennial streams to transition to intermittent flow patterns. Understanding and estimating to what extent drought can affect river network expansion and contraction is important and remains challenging.

This study aims to link river network dynamics and subsurface flow and to identify the potential influence of prolonged drought periods on the groundwater-river connection, and concomitant river network dynamics changes. To this end, we have coupled a fully-distributed hydrological model (mHM) with a groundwater model (Modflow) to investigate how prolonged droughts affect river network dynamics at the meso-catchment scale. The model was implemented in the Bode catchment, spanning 3200 km² in central Germany, from 2000 to 2022, in which the period 2018-2022 is considered as drought. We calibrated the model using discharge and groundwater table depth data from 2004 to 2008. Subsequently, we validated it using observations of discharge, groundwater table depth, and river dryness and wetness from 2009 to 2022.

The results demonstrate that the model could reproduce the dryness and wetness of river networks. For the groundwater-river exchange, the length of streams with net water loss increased by 6% in the period 2018-2022 compared to 2004-2017. For the river network dynamics, temporally, total river network length shows an apparent decline. The mean and minimum river network length during recent drought years (2018-2022) decreased by 10.4% and 10.9% compared to 2004-2017, respectively. While the maximum river network of each year was reduced only by 4.37%.  Spatially, the decline of river network length mainly occurs in first and second order streams (60.2% and 25.8%). Further analysis of stream persistence shows that approximately 3% of stream reaches shift from perennial to intermittent pattern and around 8% of stream reaches transfer from intermittent pattern to permanently dry due to the drought from 2018 to 2022. This is likely not only to harm aquatic biota but to have a major impact on stream biochemistry as well.

How to cite: Li, Y., Jomaa, S., Lischeid, G., and Rode, M.: How drought can affect river network dynamics in a central Germany lowland river catchment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16283, https://doi.org/10.5194/egusphere-egu24-16283, 2024.

08:57–08:59
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PICOA.10
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EGU24-11267
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ECS
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On-site presentation
Eugene Magee, Catherine Sefton, Simon Parry, Stuart Allen, and Judy England

The chalk streams of the UK are globally rare, strongly intermittent in their upper reaches, and highly valued for their biodiversity and historical provision of water resources. Recent projections of river flows and groundwater levels under climate change in the UK, coupled to existing statistical models of hydrological state, enable the projection of spatiotemporal intermittence patterns into the near- and far-future.  

Catchments were selected for the study based on the availability of data and the performance of statistical models in the historical period.  Cumulative logit models, previously trained on historical data, were used in conjunction with state-of-the-art ensemble projections of future river flows and groundwater levels to simulate future hydrological state at multiple sites along chalk streams in the south-east of England.  Heatmaps visualise spatiotemporal variations in state, and intermittence metrics quantify the variability.   

The results show projected increases in drying into the future, both temporally, with greater duration of drying, and spatially, with intermittence extending downstream.  Some sites are likely to alter substantially, for example, on the river Chess with notable decreases in modelled flow permanence projected, from 75% in the baseline period (2005-2020) to 25% in the far future (2065-2080). 

This research provides quantifiable spatiotemporal dynamics of intermittence, informing water resource decisions, drought management and engagement activities on these high-profile streams.  The methods developed are adaptable for transfer to other catchments for which spatiotemporal mapping of intermittence patterns and future projections of driving variables exist. 

How to cite: Magee, E., Sefton, C., Parry, S., Allen, S., and England, J.: Increasing intermittence of the UK’s chalk streams into the future , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11267, https://doi.org/10.5194/egusphere-egu24-11267, 2024.

08:59–09:01
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PICOA.11
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EGU24-12911
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Highlight
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On-site presentation
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Annika Künne, Louise Mimeau, Alexandre Devers, Sven Kralisch, Flora Branger, and Jean-Philippe Vidal

Climate change is driving a global shift in river hydrology. Future climate projections estimate that global warming will result in more frequent and intense hydrological droughts in certain regions of the world, including Europe. However, there are currently very few studies investigating the impact of climate change in non-perennial rivers, which are home to a rich aquatic biodiversity and may be particularly vulnerable to an increase in droughts. To comprehend the impact of climate change on drying river networks and its consequences on biodiversity, functional integrity and ecosystem services, it is paramount to model and project flow intermittence under climate change.

In this study, we assess flow intermittence patterns and transitions in six distinct European River Networks from the DRYvER project case studies (Datry et al. 2021), situated in diverse biogeographic regions including Spain, France, Croatia, Hungary, Czech Republic, and Finland. Encompassing watershed areas ranging from 150 km² to 350 km², we employed a hybrid modeling technique to predict spatio-temporal patterns of flow intermittence (Mimeau et al. 2023). Climate projection data were used to force the hybrid models, enabling an evaluation of future changes. Additionally, flow intermittence indicators reflecting impacts on ecological processes were jointly developed in the DRYvER project and computed to assess changes and trends in recent years from 1960 to 2021 and for projected periods up to 2100.

Results indicate that projected drying patterns expand temporally and spatially. Temporally, the increase is related to a higher frequency of ceasing streamflow, but also to prolonged individual drying events. Shifts in the seasonality of flow cessation were also observed, with flow intermittence occurring in atypical seasons, such as winter, and typical drying maxima in summer transitioning to an earlier onset in spring with later ends or second maxima in autumn. Spatially, the increase is related to both, the overall river length affected by flow intermittence and the increase of connected reaches affected by flow cessation, which in turn increases the patchiness of the river network. All streamflow intermittence indicators simulated for the six case studies in the past and future projections can be explored on the interactive web application DRYvER-Hydro (https://dryver-hydro.sk8.inrae.fr/). Besides, the calculated indicators can be utilized by other DRYvER partners for further ecological analysis and modeling. For instance Vilmi et al. (2023) used these indicators, among other data, to assess algal, fungal, bacterial, macroinvertebrate, and fish metacommunities.

This research provides valuable insights into the dynamic interactions between climate change and river hydrology, emphasizing the urgent need for adaptive strategies to mitigate the consequences on water resources, biodiversity, and ecosystem services in European river systems.

References:

Datry et al (2021) Securing Biodiversity, Functional Integrity, and Ecosystem Services in Drying River Networks (DRYvER). Res Ideas Outcomes 7:. https://doi.org/10.3897/rio.7.e77750

Mimeau et al (2023) Flow intermittence prediction using a hybrid hydrological modelling approach : influence of observed intermittence data on the training of a random forest model. 1–30. https://doi.org/10.5194/egusphere-2023-1322

Vilmi et al (2023) D2 . 6 : A report on meta-community spatio-temporal models and meta-community patterns across the six focal DRNs in Europe. https://www.dryver.eu/results/reports-and-documents

How to cite: Künne, A., Mimeau, L., Devers, A., Kralisch, S., Branger, F., and Vidal, J.-P.: Flow intermittence patterns in European river networks under climate change: Assessing temporal and spatial changes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12911, https://doi.org/10.5194/egusphere-egu24-12911, 2024.

09:01–09:03
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PICOA.12
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EGU24-9841
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ECS
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On-site presentation
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Tristan Jaouen, Lionel Benoit, and Eric Sauquet

Funded by the French Ministry of Ecology, the French Biodiversity Agency (OFB) and project partners, Explore2 aims to update knowledge about the impact of climate change on hydrology in France, and to support stakeholders in adapting their water management strategies. A multi-scenario and multi-model approach is uniformly applied across the country to encompass a wide range of possible futures for the entire 21st century and to assess uncertainties at each step of the climate and hydrology modelling.

This study aims to extend the results of Explore2 towards the prediction of flow intermittence in headwaters streams, which is initially impeded by the coarse resolution of Explore2 simulations. A statistical approach is necessary to link Explore2 hydrological projections on main rivers to the daily probability of flow intermittence in headstreams (PFI). PFI observations on historical period are derived from data of the French Observatoire National des Etiages (ONDE), which carries monthly visual assessments since 2012, from May to September, at more than 3300 upstream river sites prone to drying  [1]. PFI is then considered as the proportion of ONDE sites observed under drying conditions on partitions of France (76 second-level hydroecoregions (HER2) with median size of 4690 km² paving France).

To predict PFI, logistic regressions are adapted from previous studies [2, 3] and are first calibrated in each HER2 using time series of daily discharge provided by the French hydrometric monitoring network, HYDRO [4]. A diagnosis analysis between 2012 and 2022 consistently demonstrates good performance, with a median Kling-Gupta Efficiency (KGE) around 0.83 across all HER2. Logistic regressions are then re-calibrated considering daily discharge time series simulated by five hydrological models (HMs) of Explore2 driven by SAFRAN meteorological reanalysis [5]. Performance varies according to the HM (KGE medians ranging from 0.60 to 0.82).

Finally, the logistic regressions are applied to simulate daily PFI values at each HER2 for the entire 21st century  with future discharge simulated by the five HMs driven by 17 climate projections under RCP8.5 scenario. Results suggest an increased probability of intermittence in most of the hydrological ensemble runs and under most scenarios. This presentation will focus on the spatial variability of PFI response to climate change projected at different time leads.

 

References

[1] Nowak and Durozoi. Guide de dimensionnement et de mise en œuvre du suivi national des étiages estivaux. ONEMA, 2012.

[2] Beaufort et al. Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks. Hydrology and Earth System Sciences, 2018. doi:10.5194/hess-22-3033-2018.

[3] Sauquet et al. Predicting flow intermittence in france under climate change. Hydrological Sciences Journal, 2021. doi:10.1080/02626667.2021.1963444Y.

[4] Leleu et al. La refonte du système d’information national pour la gestion et la mise à disposition des données hydrométriques. Houille Blanche, 2014. doi:10.1051/lhb/2014004.

[5] Durand et al. A meteorological estimation of relevant parameters for snow models. Annals of Glaciology, 1993. doi:10.3189/s0260305500011277.

How to cite: Jaouen, T., Benoit, L., and Sauquet, E.: Predicting the evolution of intermittencies under climate change in France: exploitation of flow projections driven by CMIP5 climate models for Explore2 project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9841, https://doi.org/10.5194/egusphere-egu24-9841, 2024.

09:03–10:15