Hierarchical climate-driven dynamics of the active channel length in temporary streams

Looking across a landscape, river networks appear deceptively static. However, flowing streams expand and contract following ever-changing hydrological conditions of the surrounding environment. Despite the ecological and biogeochemical value of rivers with discontinuous flow, deciphering the temporary nature of streams and quantifying their extent remains challenging. Using a unique observational dataset spanning diverse geomorphoclimatic settings, we demonstrate the existence of a general hierarchical structuring of river network dynamics. Specifically, temporary stream activation follows a fixed and repeatable sequence, in which the least persistent sections activate only when the most persistent ones are already flowing. This hierarchical phenomenon not only facilitates monitoring activities, but enables the development of a general mathematical framework that elucidates how climate drives temporal variations in the active stream length. As the climate gets drier, the average fraction of the flowing network decreases while its relative variability increases. Our study provides a novel conceptual basis for characterizing temporary streams and quantifying their ecological and biogeochemical impacts.

Planothidum audax sp. nov. (Bacillariophyta, Achnanthidiaceae), a new diatom from temporary streams in southern Portugal

Temporary streams represent ca. half of the river network at the worldwide level, and in regions such as southern Europe their dominance of the landscape is evident (Larned et al. 2010, McDonough et al. 2011, Barbosa et al. 2020). Currently, these streams are receiving increased attention due to their importance as high diversity spots for algae, arthropods, plants, etc., and due to the ecosystem services they provide (Acuña et al. 2014, Datry et al. 2018b). Because of their geographical position and the land use changes in their watersheds (increased urbanization, agriculture, etc.), climate change, contamination and habitat fragmentation constitute forces threatening their integrity and ecological characteristics (Datry et al. 2018a, Bonada et al. 2020).

INTEGRATION OF DATA OF THE REMOTE SENSING, GIS, AND GAMMA-SPECTROMETRIC ANALYSIS TO STUDY SOIL MATERIAL REDISTRIBUTION

The paper discusses a problem of complex data application when accounting erosion network elements to study soil runoff and soil material redistribution on arable slopes. It is needed to estimate and account contribution of microrelief landforms to the sediment (washed out soil material) redistribution on arable areas to enhance accuracy of estimation of the soil runoff and accumulation. However, microrelief landforms are hardly detected on topographic maps and plans used traditionally in land management. For example, temporary streams formed in plowing furrows (in the case of along-slope plowing) can be detected only when survey and soil sampling data are attracted, or (partially) using remote sensing data.Due to such a context, we discover integrated analysis of map data (digital maps represented and processed in GIS environment), data of gamma-spectrometric analysis of the soil samples, and very high resolution satellite imagery, which is aimed onto detection of the role of stable and dynamically changing microrelief landforms in soil material redistribution.

Analysing river network dynamics and active length - discharge relationship using water presence sensors

Despite the importance of temporary streams for the provision of key ecosystem services, their experimental monitoring remains challenging because of the practical difficulties in performing accurate high-frequency surveys of the flowing portion of river networks. In this study, about 30 electrical resistance (ER) sensors were deployed in a high relief 2.6 km2 catchment of the Italian Alps to monitor the spatio-temporal dynamics of the active river network during the fall of 2019. The set-up of the ER sensors was personalized to make them more flexible for the deployment in the field and more accurate under low flow conditions. Available ER data were analyzed, compared to field based estimates of the nodes' persistency and then used to generate a sequence of maps representing the active reaches of the stream network with a sub-daily temporal resolution. This allowed a proper estimate of the joint variations of active river network length (L) and catchment discharge (Q) during the entire study period. Our analysis revealed a high cross-correlation between the statistics of individual ER signals and the flow persistencies of the cross sections where the sensors were placed. The observed spatial and temporal dynamics of the actively flowing channels also revealed the diversity of the hydrological behaviour of distinct zones of the study catchment, which was attributed to differences in the catchment geology and stream-bed composition. The more pronounced responsiveness of the total active length to small precipitation events as compared to the catchment discharge led to important hysteresis in the L vs. Q relationship, thereby impairing the performances of a power-law model frequently used in the literature to relate these two quantities. Consequently, in our study site the adoption of a unique power-law L-Q relationship to infer flowing length variability from observed discharges would underestimate the actual variations of L by 40%. Our work emphasizes the potential of ER sensors for analysing spatio-temporal dynamics of active channels in temporary streams, discussing the major limitations of this type of technology emerging from the specific application presented herein.

Thermal and multispectral images from Unmanned Aerial Vehicles (UAVs) for water presence detection in temporary streams: first results

<p>UAVs (Unmanned Aerial Vehicles) are increasingly used for monitoring river networks with a broad range of purposes. In this contribution, we focus on the use of multispectral sensors, either in the thermal infrared band LWIR (Long-wavelength infrared, 8-15 µm) or in the infrared band NIR (Near-infrared, 0.75-1.4 µm) to map network dynamics in temporary streams. Specifically, we discuss the first results of a set of surveys carried out in 2020 within a small river catchment located in northern Calabria (southern Italy), as part of the research activities of the ERC-funded DyNET project. Preliminary, a rigorous methodology was identified to perform on-site surveys and to process and analyse the acquired images. Experimental results show that the combined use of LWIR and NIR sensors is a suitable solution for detecting water presence in channels characterized by different hydraulic and morphologic conditions. LWIR sensors alone allow one to discriminate water presence only when the thermal contrast with the surrounding environment is high. On the other hand, NIR sensors permit to detect the presence of water in most of the analyzed settings through the estimate of the Normalized Difference Water Index (NDWI). However, NIR sensors can be misled in case of shallow water depth, due to the NIR radiation emitted by the riverbed merging with that of the water. Overall, the study demonstrates that a combined LWIR/NIR approach allows addressing a broader range of conditions. Moreover, the information provided can be further enhanced by combining it with geomorphologic information and basic hydraulic concepts.</p>

Characterizing temporary stream dynamics: the Stream Length Duration Curve

<p>Temporary streams (i.e. streams that temporarily cease to flow) are becoming a hot research topic in hydrology. These streams provide an invaluable contribution to riverine ecosystems, as they host a variety of habitats (from lotic to lentic and terrestrial) which sustain high biodiversity. Temporary streams can be found in different regions of the world and are characterized by strongly heterogeneous flow patterns, from flashy streams that flow only after rainfall events to rivers that episodically experience droughts. Many recent studies investigated temporary streams, originating interesting observational datasets about event-based or seasonal network dynamics. Empirical or conceptual models are usually employed for assessing the main physical drivers of network dynamics in each specific study site.<br>In this contribution, we develop and apply novel theoretical tools to understand how the local statistical properties of each reach of the network affect the catchment-scale variability of the active length. In particular, the Stream Length Duration Curve (SLDC) is proposed to efficiently summarize catchment-scale dynamics of the active length, providing an objective way to quantify network dynamics. The concept of SLDC is applied to a number of Italian headwater catchments, where data about temporal changes in the configuration of the flowing stream are available, providing a clue for the characterization of emergent temporal and spatial patterns of network dynamics. The Stream Length Duration Curve can facilitate comparisons across different catchments an time periods, possibly enabling and objective classification of temporary streams. </p>

CrowdWater: How well can citizens observe water levels and other hydrological variables using a smartphone app?

<p>Citizen science observations are potentially useful to complement existing monitoring networks. This is also the case in hydrology, where we often lack spatially distributed observations. Engaging the public might help to overcome the lack of data in hydrology. So far, most hydrological citizen science projects have been based on the use of different instruments or installations. For stream level observations, a staff gauge is installed in the river but it is difficult to scale this type of citizen science approach to a large number of sites because these gauges cannot be installed everywhere (or by everyone). Here, we present an evaluation of the CrowdWater smartphone app that allows the collection of hydrological data without any physical installation or specialized instruments. With the help of a free app, citizens can report the stream level, soil moisture conditions, the presence of water in temporary streams, plastic pollution in streams and on streambanks, as well as general information on streams. The approach is similar to geocaching, with the difference that instead of finding treasures, hydrological measurement sites are set up. These sites can be found by the initiator or other citizen scientists to take additional measurements at a later time. For the water level measurements, a virtual staff gauge approach is used instead of a physical staff gauge. A picture of a staff gauge is digitally inserted into a photo of a stream bank or a bridge pillar and serves as a reference of the water level. During a subsequent field visit, the stream level is compared to the virtual staff gauge on the first picture. In this presentation, we discuss how well the water level class observations agreed with measured stream levels, and in which months and during which flow conditions citizens submitted their stream level observations. We also highlight methods to ensure data quality, and illustrate how these water level data can be used in hydrological model calibration. We also give an update on new activities in the CrowdWater project.</p>