scholarly journals Spatial and temporal variation in river corridor exchange across a 5th-order mountain stream network

2019 ◽  
Vol 23 (12) ◽  
pp. 5199-5225 ◽  
Author(s):  
Adam S. Ward ◽  
Steven M. Wondzell ◽  
Noah M. Schmadel ◽  
Skuyler Herzog ◽  
Jay P. Zarnetske ◽  
...  
Keyword(s):  
Conceptual Model ◽  
Tracer Test ◽  
River Network ◽  
Systematic Variation ◽  
Spatial And Temporal Variation ◽  
Mountain Stream ◽  
River Networks ◽  
Stream Network ◽  
Geologic Setting ◽  
River Corridor

Abstract. Although most field and modeling studies of river corridor exchange have been conducted at scales ranging from tens to hundreds of meters, results of these studies are used to predict their ecological and hydrological influences at the scale of river networks. Further complicating prediction, exchanges are expected to vary with hydrologic forcing and the local geomorphic setting. While we desire predictive power, we lack a complete spatiotemporal relationship relating discharge to the variation in geologic setting and hydrologic forcing that is expected across a river basin. Indeed, the conceptual model of Wondzell (2011) predicts systematic variation in river corridor exchange as a function of (1) variation in baseflow over time at a fixed location, (2) variation in discharge with location in the river network, and (3) local geomorphic setting. To test this conceptual model we conducted more than 60 solute tracer studies including a synoptic campaign in the 5th-order river network of the H. J. Andrews Experimental Forest (Oregon, USA) and replicate-in-time experiments in four watersheds. We interpret the data using a series of metrics describing river corridor exchange and solute transport, testing for consistent direction and magnitude of relationships relating these metrics to discharge and local geomorphic setting. We confirmed systematic decrease in river corridor exchange space through the river networks, from headwaters to the larger main stem. However, we did not find systematic variation with changes in discharge through time or with local geomorphic setting. While interpretation of our results is complicated by problems with the analytical methods, the results are sufficiently robust for us to conclude that space-for-time and time-for-space substitutions are not appropriate in our study system. Finally, we suggest two strategies that will improve the interpretability of tracer test results and help the hyporheic community develop robust datasets that will enable comparisons across multiple sites and/or discharge conditions.

scholarly journals Spatial and temporal variation in river corridor exchange across a 5th order mountain stream network

2019 ◽  
Author(s):  
Adam S. Ward ◽  
Steven M. Wondzell ◽  
Noah M. Schmadel ◽  
Skuyler Herzog ◽  
Jay P. Zarnetske ◽  
...  
Keyword(s):  
Conceptual Model ◽  
Tracer Test ◽  
River Network ◽  
Systematic Variation ◽  
Spatial And Temporal Variation ◽  
Mountain Stream ◽  
River Networks ◽  
Data Sets ◽  
Stream Network ◽  
River Corridor

Abstract. Although most field and modeling studies of river corridor exchange have been conducted a scales ranging from 10’s to 100’s of meters; results of these studies are used to predict their ecological and hydrological influences at the scale of river networks. Further complicating prediction, exchange are expected to vary with hydrologic forcing and the local geomorphic setting. While we desire predictive power, we lack a complete spatiotemporal relationship relating discharge to the variation in geologic setting and hydrologic forcing that are expected across a river basin. Indeed, Wondzell’s [2011] conceptual model predicts systematic variation in river corridor exchange as a function of (1) variation in discharge over time at a fixed location, (2) variation in discharge with location in the river network, and (3) local geomorphic setting. To test this conceptual model we conducted more than 60 solute tracer studies collected in a synoptic campaign in the 5th order river network of the H. J. Andrews Experimental Forest (Oregon, USA). We interpret the data using a series of metrics describing river corridor exchange and solute transport, testing for consistent direction and magnitude of relationships relating these metrics to discharge and local geomorphic setting. We confirmed systematic decrease in river corridor exchange space through the river networks, from headwaters to the larger mainstem. However, we did not find systematic variation with changes in discharge through time, nor with local geomorphic setting. While interpretation of our results are complicated by problems with the analytical methods, they are sufficiently robust for us to conclude that space-for-time and time-for-space substitutions are not appropriate in our study system. Finally, we suggest two strategies that will improve the interpretability of tracer test results and help the hyporheic community develop robust data sets that will enable comparisons across multiple sites and/or discharge conditions.

HOW DO HYDROLOGIC FORCING AND GEOLOGIC SETTING CONTROL RIVER CORRIDOR EXCHANGE IN A 5TH ORDER MOUNTAIN STREAM NETWORK?

2018 ◽  
Author(s):  
Adam S. Ward ◽  
◽  
Skuyler Herzog ◽  
Steven M. Wondzell ◽  
Noah Schmadel ◽  
...  
Keyword(s):  
Mountain Stream ◽  
Stream Network ◽  
Geologic Setting ◽  
River Corridor

scholarly journals Co-located contemporaneous mapping of morphological, hydrological, chemical, and biological conditions in a 5th-order mountain stream network, Oregon, USA

2019 ◽  
Vol 11 (4) ◽  
pp. 1567-1581 ◽  
Author(s):  
Adam S. Ward ◽  
Jay P. Zarnetske ◽  
Viktor Baranov ◽  
Phillip J. Blaen ◽  
Nicolai Brekenfeld ◽  
...  
Keyword(s):  
River Network ◽  
Mountain Stream ◽  
Sample Design ◽  
Stream Network ◽  
Cascade Mountains ◽  
Data Set ◽  
Physical Chemical ◽  
Streambed Sediment ◽  
River Corridor

Abstract. A comprehensive set of measurements and calculated metrics describing physical, chemical, and biological conditions in the river corridor is presented. These data were collected in a catchment-wide, synoptic campaign in the H. J. Andrews Experimental Forest (Cascade Mountains, Oregon, USA) in summer 2016 during low-discharge conditions. Extensive characterization of 62 sites including surface water, hyporheic water, and streambed sediment was conducted spanning 1st- through 5th-order reaches in the river network. The objective of the sample design and data acquisition was to generate a novel data set to support scaling of river corridor processes across varying flows and morphologic forms present in a river network. The data are available at https://doi.org/10.4211/hs.f4484e0703f743c696c2e1f209abb842 (Ward, 2019).

scholarly journals Co-located contemporaneous mapping of morphological, hydrological, chemical, and biological conditions in a 5th order mountain stream network, Oregon, USA

2019 ◽  
Author(s):  
Adam S. Ward ◽  
Jay P. Zarnetske ◽  
Viktor Baranov ◽  
Phillip J. Blaen ◽  
Nicolai Brekenfeld ◽  
...  
Keyword(s):  
River Network ◽  
Mountain Stream ◽  
Sample Design ◽  
Stream Network ◽  
Cascade Mountains ◽  
Data Set ◽  
Physical Chemical ◽  
Streambed Sediment ◽  
River Corridor

Abstract. A comprehensive set of measurements and calculated metrics describing physical, chemical, and biological conditions in the river corridor is presented. These data were collected in a catchment-wide, synoptic campaign in Lookout Creek within the H.J. Andrews Experimental Forest (Cascade Mountains, Oregon, USA) in summer 2016 during low discharge conditions. Extensive characterization of 62 sites including surface water, hyporheic water, and streambed sediment was conducted spanning 1st through 5th order reaches in the river network. The objective of the sample design and data acquisition was to generate a novel data set to support scaling of river corridor processes across varying flows and morphologic forms present in a river network. The data are available at http://www.hydroshare.org/resource/f4484e0703f743c696c2e1f209abb842 (Ward, 2019).

scholarly journals Setting the Flow Accumulation Threshold Based on Environmental and Morphologic Features to Extract River Networks from Digital Elevation Models

2021 ◽  
Vol 10 (3) ◽  
pp. 186
Author(s):  
HuiHui Zhang ◽  
Hugo A. Loáiciga ◽  
LuWei Feng ◽  
Jing He ◽  
QingYun Du
Keyword(s):  
Spatial Scales ◽  
Digital Elevation Models ◽  
Regional Scale ◽  
Drainage Density ◽  
River Network ◽  
Landscape Patterns ◽  
Estimation Methods ◽  
River Networks ◽  
Flow Accumulation ◽  
Digital Elevation

Determining the flow accumulation threshold (FAT) is a key task in the extraction of river networks from digital elevation models (DEMs). Several methods have been developed to extract river networks from Digital Elevation Models. However, few studies have considered the geomorphologic complexity in the FAT estimation and river network extraction. Recent studies estimated influencing factors’ impacts on the river length or drainage density without considering anthropogenic impacts and landscape patterns. This study contributes two FAT estimation methods. The first method explores the statistical association between FAT and 47 tentative explanatory factors. Specifically, multi-source data, including meteorologic, vegetation, anthropogenic, landscape, lithology, and topologic characteristics are incorporated into a drainage density-FAT model in basins with complex topographic and environmental characteristics. Non-negative matrix factorization (NMF) was employed to evaluate the factors’ predictive performance. The second method exploits fractal geometry theory to estimate the FAT at the regional scale, that is, in basins whose large areal extent precludes the use of basin-wide representative regression predictors. This paper’s methodology is applied to data acquired for Hubei and Qinghai Provinces, China, from 2001 through 2018 and systematically tested with visual and statistical criteria. Our results reveal key local features useful for river network extraction within the context of complex geomorphologic characteristics at relatively small spatial scales and establish the importance of properly choosing explanatory geomorphologic characteristics in river network extraction. The multifractal method exhibits more accurate extracting results than the box-counting method at the regional scale.

scholarly journals A new vector-based global river network dataset accounting for variable drainage density

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peirong Lin ◽  
Ming Pan ◽  
Eric F. Wood ◽  
Dai Yamazaki ◽  
George H. Allen
Keyword(s):  
Spatial Variability ◽  
Flow Direction ◽  
River System ◽  
Drainage Density ◽  
River Network ◽  
River Networks ◽  
Digital Elevation ◽  
Machine Learning Approach ◽  
Elevation Model ◽  
National Hydrography Dataset

AbstractSpatial variability of river network drainage density (Dd) is a key feature of river systems, yet few existing global hydrography datasets have properly accounted for it. Here, we present a new vector-based global hydrography that reasonably estimates the spatial variability of Dd worldwide. It is built by delineating channels from the latest 90-m Multi-Error-Removed Improved Terrain (MERIT) digital elevation model and flow direction/accumulation. A machine learning approach is developed to estimate Dd based on the global watershed-level climatic, topographic, hydrologic, and geologic conditions, where relationships between hydroclimate factors and Dd are trained using the high-quality National Hydrography Dataset Plus (NHDPlusV2) data. By benchmarking our dataset against HydroSHEDS and several regional hydrography datasets, we show the new river flowlines are in much better agreement with Landsat-derived centerlines, and improved Dd patterns of river networks (totaling ~75 million kilometers in length) are obtained. Basins and estimates of intermittent stream fraction are also delineated to support water resources management. This new dataset (MERIT Hydro–Vector) should enable full global modeling of river system processes at fine spatial resolutions.

scholarly journals An Innovative Framework for Real Time Monitoring of Pollutant Point Sources in River Networks

2021 ◽  
Author(s):  
Mehdi Mazaheri ◽  
J. M. V. Samani ◽  
Fulvio Boano
Keyword(s):  
Real Time ◽  
Transport Model ◽  
River Network ◽  
Point Sources ◽  
Release Time ◽  
River Networks ◽  
Observation Data ◽  
Geostatistical Approach ◽  
Pollutant Sources ◽  
Simultaneous Identification

Abstract The simultaneous identification of location and source release history in complex river networks is a very complicated ill-posed problem, particularly in a case of multiple unknown pollutant sources with time-varying release pattern. This study presents an innovative method for simultaneous identification of the number, locations and release histories of multiple pollutant point sources in a river network using minimum observation data. Considering two different type of monitoring stations with an adaptive arrangement as well as real-time data collection at those stations and using a reliable numerical flow and transport model, at first the number and suspected reach of presence of pollutant sources are determined. Then the source location and its intensity function is calculated by solving inverse source problem using a geostatistical approach. A case study with three different scenarios in terms of the number, release time and location of pollutant sources are discussed, concerning a river network with unsteady and non-uniform flow. Results showed the capability of the proposed method in identifying of sought source characteristics even in complicated cases with simultaneous activity of multiple pollutant sources.

scholarly journals On the propagation of diel signals in river networks using analytic solutions of flow equations

2015 ◽  
Vol 12 (8) ◽  
pp. 8175-8220 ◽  
Author(s):  
M. Fonley ◽  
R. Mantilla ◽  
S. J. Small ◽  
R. Curtu
Keyword(s):  
Analytic Solutions ◽  
River Network ◽  
Low Flow ◽  
River Networks ◽  
Signal Delay ◽  
Flow Conditions ◽  
Flow Equations ◽  
Linear Transport Equation ◽  
Daily Evapotranspiration ◽  
Self Similar

Abstract. Two hypotheses have been put forth to explain the magnitude and timing of diel streamflow oscillations during low flow conditions. The first suggests that delays between the peaks and troughs of streamflow and daily evapotranspiration are due to processes occurring in the soil as water moves toward the channels in the river network. The second posits that they are due to the propagation of the signal through the channels as water makes its way to the outlet of the basin. In this paper, we design and implement a theoretical experiment to test these hypotheses. We impose a baseflow signal entering the river network and use a linear transport equation to represent flow along the network. We develop analytic streamflow solutions for two cases: uniform and nonuniform velocities in space over all river links. We then use our analytic solutions to simulate streamflows along a self-similar river network for different flow velocities. Our results show that the amplitude and time delay of the streamflow solution are heavily influenced by transport in the river network. Moreover, our equations show that the geomorphology and topology of the river network play important roles in determining how amplitude and signal delay are reflected in streamflow signals. Finally, our results are consistent with empirical observations that delays are more significant as low flow decreases.

Identifying global hotspots of plastic waste accumulation along river networks

2021 ◽  
Author(s):  
Jesus Gomez-Velez ◽  
Stefan Krause
Keyword(s):  
Multiple Scales ◽  
Transport Model ◽  
Freshwater Ecosystems ◽  
River Network ◽  
Plastic Waste ◽  
Trapping Efficiency ◽  
River Networks ◽  
Clear Understanding ◽  
Relative Location ◽  
Plastic Pollution

<p>Global plastic pollution is affecting ecosystems and human health globally. Proposing solutions and coping strategies for this threat requires a clear understanding of the processes controlling the fate and transport of mismanaged plastics at multiple scales, going from watersheds to regions and even continents. River corridors are the primary conveyor and trap for mismanaged plastic produced within the landscape and eventually released to the ocean. New approaches that apply technological sensing innovations for monitoring plastic waste in aquatic environments can improve observations and plastic waste datasets globally. However, our understanding of when, where, and how to target monitoring is limited, reducing the benefit gained. There is therefore a critical demand for predictions of hotspots (as well as hot moments) of plastic accumulation along river networks globally, in order to optimize observational capacity.     </p><p>Here, we present a new global flow and transport model for plastic waste in riverine environments. Our model predicts that only a small fraction (roughly 2.5%) of the global mismanaged plastic that entered rivers since the 1950s has been delivered to the ocean by 2020, with an overwhelming majority sequestered in freshwater ecosystems. Furthermore, we predict the patterns of mismanaged plastic accumulation and its residence time depend on (i) the topology and geometry of the river network, (ii) the relative location of plastic sources, and (ii) the relative location and trapping efficiency of flow regulation structures, primarily large dams. Our results highlight the role of rivers as major sinks for plastic waste and the need for targeted remedial strategies that consider the structure of the river network and anthropogenic regulation when proposing intervention measures and sampling efforts.</p>

scholarly journals Quantification of drainable water storage volumes on landmasses and in river networks based on GRACE and river runoff using a cascaded storage approach – first application on the Amazon

2020 ◽  
Vol 24 (3) ◽  
pp. 1447-1465 ◽  
Author(s):  
Johannes Riegger
Keyword(s):  
Phase Shift ◽  
River Runoff ◽  
River Discharge ◽  
Time Lag ◽  
Water Storage ◽  
River Network ◽  
River Networks ◽  
Time Constants ◽  
Tropical Conditions

Abstract. The knowledge of water storage volumes in catchments and in river networks leading to river discharge is essential for the description of river ecology, the prediction of floods and specifically for a sustainable management of water resources in the context of climate change. Measurements of mass variations by the GRACE gravity satellite or by ground-based observations of river or groundwater level variations do not permit the determination of the respective storage volumes, which could be considerably bigger than the mass variations themselves. For fully humid tropical conditions like the Amazon the relationship between GRACE and river discharge is linear with a phase shift. This permits the hydraulic time constant to be determined and thus the total drainable storage directly from observed runoff can be quantified, if the phase shift can be interpreted as the river time lag. As a time lag can be described by a storage cascade, a lumped conceptual model with cascaded storages for the catchment and river network is set up here with individual hydraulic time constants and mathematically solved by piecewise analytical solutions. Tests of the scheme with synthetic recharge time series show that a parameter optimization either versus mass anomalies or runoff reproduces the time constants for both the catchment and the river network τC and τR in a unique way, and this then permits an individual quantification of the respective storage volumes. The application to the full Amazon basin leads to a very good fitting performance for total mass, river runoff and their phasing (Nash–Sutcliffe for signals 0.96, for monthly residuals 0.72). The calculated river network mass highly correlates (0.96 for signals, 0.76 for monthly residuals) with the observed flood area from GIEMS and corresponds to observed flood volumes. The fitting performance versus GRACE permits river runoff and drainable storage volumes to be determined from recharge and GRACE exclusively, i.e. even for ungauged catchments. An adjustment of the hydraulic time constants (τC, τR) on a training period facilitates a simple determination of drainable storage volumes for other times directly from measured river discharge and/or GRACE and thus a closure of data gaps without the necessity of further model runs.

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