Quantifying spatiotemporal variation in headwater stream length using flow intermittency sensors

Integrating spatially-and temporally-heterogeneous data on river network dynamics using graph theory

The study of non-perennial streams requires extensive experimental data on the temporal evolution of surface flow presence across different nodes of channel networks. However, the consistency and homogeneity of available datasets is threatened by the empirical burden required to map stream network expansions and contractions. Here, we developed a data-driven, graph-theory framework aimed at representing the hierarchical structuring of channel network dynamics (i.e., the order of node activation/deactivation during network expansion/retraction) through a directed acyclic graph. The method enables the estimation of the configuration of the active portion of the network based on a limited number of observed nodes, and can be utilized to combine datasets with different temporal resolutions and spatial coverage. A proof-of-concept application to a seasonally-dry catchment in central Italy demonstrated the ability of the approach to reduce the empirical effort required for monitoring network dynamics and efficiently extrapolate experimental observations in space and time.

Headwater streams and inland wetlands: Status and advancements of geospatial datasets and maps across the United States

Headwater streams and inland wetlands provide essential functions that support healthy watersheds and downstream waters. However, scientists and aquatic resource managers lack a comprehensive synthesis of national and state stream and wetland geospatial datasets and emerging technologies that can further improve these data. We conducted a review of existing United States (US) federal and state stream and wetland geospatial datasets, focusing on their spatial extent, permanence classifications, and current limitations. We also examined recent peer-reviewed literature for emerging methods that can potentially improve the estimation, representation, and integration of stream and wetland datasets. We found that federal and state datasets rely heavily on the US Geological Survey's National Hydrography Dataset for stream extent and duration information. Only eleven states (22%) had additional stream extent information and seven states (14%) provided additional duration information. Likewise, federal and state wetland datasets primarily use the US Fish and Wildlife Service's National Wetlands Inventory (NWI) Geospatial Dataset, with only two states using non-NWI datasets. Our synthesis revealed that LiDAR-based technologies hold promise for advancing stream and wetland mapping at limited spatial extents. While machine learning techniques may help to scale-up these LiDAR-derived estimates, challenges related to preprocessing and data workflows remain. High-resolution commercial imagery, supported by public imagery and cloud computing, may further aid characterization of the spatial and temporal dynamics of streams and wetlands, especially using multi-platform and multi-temporal machine learning approaches. Models integrating both stream and wetland dynamics are limited, and field-based efforts must remain a key component in developing improved headwater stream and wetland datasets. Continued financial and partnership support of existing databases is also needed to enhance mapping and inform water resources research and policy decisions.

Eco-hydrological modelling of channel network dynamics-part 1: stochastic simulation of active stream expansion and retraction

Dynamic changes in the active portion of stream networks represent a phenomenon common to diverse climates and geologic settings. However, mechanistically describing these processes at the relevant spatiotemporal scales without huge computational burdens remains challenging. Here, we present a novel stochastic framework for the effective simulation of channel network dynamics capitalizing on the concept of 'hierarchical structuring of temporary streams'-a general principle to identify the activation/deactivation order of network nodes. The framework allows the long-term description of event-based changes of the river network configuration starting from widely available climatic data (mainly rainfall and evapotranspiration). Our results indicate that climate strongly controls temporal variations of the active length, influencing not only the preferential configuration of the active channels but also the speed of network retraction during drying. Moreover, we observed that-while the statistics of wet length are mainly dictated by the underlying climatic conditions-the spatial patterns of active reaches and the size of the largest connected patch of the network are strongly controlled by the spatial correlation of local persistency. The proposed framework provides a robust mathematical set-up for analysing the multi-faceted ecological legacies of channel network dynamics, as discussed in a companion paper.

On the Relation Between Active Network Length and Catchment Discharge

The ever-changing hydroclimatic conditions of the landscape induce ceaseless variations in the wet channel length (L) and the streamflow (Q) of a catchment. Here we use a perceptual model to analyze the links among (and the drivers of) four descriptors commonly used to characterize discharge and active length dynamics in streams, namely the L(Q) relationship and the cumulative distributions of local persistency, flowrate and active length. The model demonstrates that the shape of the L(Q) law is defined by the cumulative distribution of the specific subsurface discharge capacity along the network, a finding which provides a clue for the parametrization of L(Q) relations in dynamic streams. Furthermore, we show that L(Q) laws can be constructed combining the streamflow distribution with disjoint active length data. Our framework links previously unconnected formulations for characterizing stream network dynamics, and offers a novel perspective to describe the scaling between wet length and discharge in rivers.

Probabilistic Description of Streamflow and Active Length Regimes in Rivers

In spite of the prevalence of temporary rivers over a wide range of climatic conditions, they represent a relatively understudied fraction of the global river network. Here, we exploit a well-established hydrological model and a derived distribution approach to develop a coupled probabilistic description for the dynamics of the catchment discharge and the corresponding active network length. Analytical expressions for the flow duration curve (FDC) and the stream length duration curve (SLDC) were derived and used to provide a consistent classification of streamflow and active length regimes in temporary rivers. Two distinct streamflow regimes (persistent and erratic) and three different types of active length regimes (ephemeral, perennial, and ephemeral de facto) were identified depending on the value of two dimensionless parameters. These key parameters, which are related to the underlying streamflow fluctuations and the sensitivity of active length to changes in the catchment discharge (here quantified by the scaling exponent b), originate seven different behavioral classes characterized by contrasting shapes of the underlying SLDCs and FDCs. The analytical model was tested using data gathered in three study catchments located in Italy and USA, with satisfactory model performances in most cases. Our analytical and empirical results show the existence of a structural relationship between streamflow and active length regimes, which is chiefly modulated by the scaling exponent b. The proposed framework represents a promising tool for the coupled analysis of discharge and river network length dynamics in temporary streams.

Surface Drainage Systems Operating during Heavy Rainfall—A Comparative Analysis between Two Small Flysch Catchments Located in Different Physiographic Regions of the Western Carpathians (Poland)

In this study, the river system and the surface drainage system (SDS) operating during heavy rainfall in two Carpathian catchments located in foothills and medium-high mountain areas were compared. The results revealed that regardless of the differences in the river systems and physiographical parameters of the catchments, the SDS operating during heavy rainfall becomes similar. This similarity is reflected in the density of the SDS (11.5–12.2 km·km−2) and the structure of the SDS, confirmed by Hortonian-type analysis. This similarity in the SDS was discussed in the context of the geomorphological transformation of the hillslopes and the hydrological response of a catchment to heavy rainfall.

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.

Macroinvertebrates at the source: flow duration and seasonality drive biodiversity and trait composition in rheocrene springs of the Western Allegheny Plateau, USA

Documenting flow regimes and the ecology of source headwater streams has gained considerable attention for scientific and regulatory purposes. These streams do not appear on standard maps, and local physiographic and climatologic conditions can control their origins. We investigated macroinvertebrate assemblages seasonally and in relation to flow duration, catchment and habitat variables within 14 source headwaters (< 1 ha) in the Western Allegheny Plateau over a 19-month period. We classified 6 perennial (P) and 8 intermittent (I) streams directly with continuous flow data loggers. Several biological and trait-based metrics could distinguish flow class, but few instream physical measures could. Macroinvertebrate metrics and assemblage dispersion varied seasonally and responded significantly along a gradient of total flow duration. Separate indicator species analyses generated 22 genera and 15 families with significant affinities to P streams. Richness of P-indicator taxa was also strongly correlated with flow duration gradients, and we estimated a total flow duration changepoint at 77% (3 indicator families) followed by a sharp increase in richness. Two rapid field-based flow duration methods (NC Stream Identification index and OH Headwater Habitat Evaluation index) could distinguish upstream ephemeral reaches from P and I reaches, but misclassified P as I more frequently. Our findings highlight that diverse coldwater macroinvertebrate assemblages inhabited extremely small, low-discharge springs in the region, and responded with flow duration. These source headwater habitats are susceptible to human disturbance and should be monitored as is routinely done in larger lotic systems.

Monitoring Drought through the Lens of Landsat: Drying of Rivers during the California Droughts

Water scarcity during severe droughts has profound hydrological and ecological impacts on rivers. However, the drying dynamics of river surface extent during droughts remains largely understudied. Satellite remote sensing enables surveys and analyses of rivers at fine spatial resolution by providing an alternative to in-situ observations. This study investigates the seasonal drying dynamics of river extent in California where severe droughts have been occurring more frequently in recent decades. Our methods combine the use of Landsat-based Global Surface Water (GSW) and global river bankful width databases. As an indirect comparison, we examine the monthly fractional river extent (FrcSA) in 2071 river reaches and its correlation with streamflow at co-located USGS gauges. We place the extreme 2012–2015 drought into a broader context of multi-decadal river extent history and illustrate the extraordinary change between during- and post-drought periods. In addition to river extent dynamics, we perform statistical analyses to relate FrcSA with the hydroclimatic variables obtained from the National Land Data Assimilation System (NLDAS) model simulation. Results show that Landsat provides consistent observation over 90% of area in rivers from March to October and is suitable for monitoring seasonal river drying in California. FrcSA reaches fair (>0.5) correlation with streamflow except for dry and mountainous areas. During the 2012–2015 drought, 332 river reaches experienced their lowest annual mean FrcSA in the 34 years of Landsat history. At a monthly scale, FrcSA is better correlated with soil water in more humid areas. At a yearly scale, summer mean FrcSA is increasingly sensitive to winter precipitation in a drier climate; and the elasticity is also reduced with deeper ground water table. Overall, our study demonstrates the detectability of Landsat on the river surface extent in an arid region with complex terrain. River extent in catchments of deficient water storage is likely subject to higher percent drop in a future climate with longer, more frequent droughts.

Monitoring and Modeling Drainage Network Contraction and Dry Down in Mediterranean Headwater Catchments

Understanding the expansion and contraction dynamics of flowing drainage networks is important for many research fields like ecology, hydrology, and biogeochemistry. This study analyzes for the first time the network shrinking and dry down in two seasonally dry hot-summer Mediterranean catchments (overall area 1.15 km2) using a comprehensive approach based on monitoring and modeling of the flowing network. A field campaign consisting of 19 subweekly visual surveys was carried out in the early summer of 2019. These observations were used to calibrate and validate an integrated model aimed to estimate the time evolution of the total flowing drainage network length based on meteorological drivers and define the position of the stretches with flowing water based on topographic and geological information. We used a statistical model to describe the observed variations in the total flowing length based on the accumulated difference between antecedent precipitation and evapotranspiration. The study emphasizes the relevant role of evapotranspiration in the seasonal network contraction. Then, we modeled spatial patterns of the flowing channels using an empirical approach based on topographic data, achieving satisfactory performances. Nevertheless, the performance further increased when site-specific geological information was integrated into the model, leading to accuracies up to 92% for cell-by-cell comparisons. The proposed methodology, which combines meteorological, topographic, and geological information in a sequential manner, was able to accurately represent the space-time dynamics of the flowing drainage network in the study area, proving to be an effective and flexible tool for investigating network dynamics in temporary streams.

The Stream Length Duration Curve: A Tool for Characterizing the Time Variability of the Flowing Stream Length

In spite of the importance of stream network dynamics for hydrology, ecology, and biogeochemistry, there is limited availability of analytical tools suitable for characterizing the temporal variability of the active fraction of river networks. To fill this gap, we introduce the concept of Stream Length Duration Curve (SLDC), the inverse of the exceedance probability of the total length of active streams. SLDCs summarize efficiently the effect of hydrological variability on the length of the flowing streams under a variety of settings. A set of stochastic network models is developed to link the features of the local hydrological status of the network nodes with the shape of the SLDC. We show that the mean network length is dictated by the mean persistency of the nodes, whereas the shape of the SLDC is driven by the spatial distribution of the local persistencies and their network-scale spatial correlation. Ten field surveys performed in 2018 were used to estimate the empirical SLDC of the Valfredda river (Italy), which was found to be steep and regular-indicating a pronounced sensitivity of the active stream length to the underlying hydrological conditions. Available observations also suggest that the activation of temporary reaches during network expansion is hierarchical, from the most to the least persistent stretches. Under these circumstances, the SLDC corresponds to the spatial Cumulative Distribution Function of the nodes persistencies. The study provides a sound theoretical basis for the analyses of network dynamics in temporary rivers.

Zero or not? Causes and consequences of zero-flow stream gage readings

Streamflow observations can be used to understand, predict, and contextualize hydrologic, ecological, and biogeochemical processes and conditions in streams. Stream gages are point measurements along rivers where streamflow is measured, and are often used to infer upstream watershed-scale processes. When stream gages read zero, this may indicate that the stream has fully dried; however, zero-flow readings can also be caused by a wide range of other factors. Our ability to identify whether or not a zero-flow gage reading indicates a dry fluvial system has far reaching environmental implications. Incorrect identification and interpretation by the data user can lead to hydrologic, ecological, and/or biogeochemical predictions from models and analyses. Here, we describe several causes of zero-flow gage readings: frozen surface water, flow reversals, instrument error, and natural or human-driven upstream source losses or bypass flow. For these examples, we discuss the implications of zero-flow interpretations. We also highlight additional methodss for determining flow presence, including direct observations, statistical methods, and hydrologic models, which can be applied to interpret causes of zero-flow gage readings and implications for reach- and watershed-scale dynamics. Such efforts are necessary to improve our ability to understand and predict surface flow activation, cessation, and connectivity across river networks. Developing this integrated understanding of the wide range of possible meanings of zero-flows will only attain greater importance in a more variable and changing hydrologic climate.