scholarly journals Using Local Toponyms to Reconstruct the Historical River Networks in Hubei Province, China

2020 ◽  
Vol 9 (5) ◽  
pp. 318
Author(s):  
Aini Zhong ◽  
Yukun Wu ◽  
Ke Nie ◽  
Mengjun Kang
Keyword(s):  
River Network ◽  
River Networks ◽  
Geometrical Analysis ◽  
Historical Trends ◽  
Global Correlation ◽  
Time Period ◽  
Natural Landscapes ◽  
Qualitative Knowledge ◽  
Data Source ◽  
Ancient Maps

As an important data source for historical geography research, toponyms reflect the human activities and natural landscapes within a certain area and time period. In this paper, a novel quantitative method of reconstructing historical river networks using toponyms with the characteristics of water and direction is proposed. It is suitable for the study area which possesses rich water resources. To reconstruct the historical shape of the river network, (1) water-related toponyms and direction-related toponyms are extracted as two datasets based on the key words in each village toponym; (2) the feasibility of the river network reconstruction based on these toponyms is validated via a quantitative analysis, according to the spatial distributions of toponyms and rivers; (3) the reconstructed historical shape of the river network can be obtained via qualitative knowledge and geometrical analysis; and (4) the reconstructed rivers are visualized to display their general historical trends and shapes. The results of this paper demonstrate the global correlation and local differences between the toponyms and the river network. The historical river dynamics are revealed and can be proven by ancient maps and local chronicles. The proposed method provides a novel way to reconstruct historical river network shapes using toponym datasets.

scholarly journals The reasons women choose and stay in a geology major: a qualitative multi-case analysis

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Ron E. Gray ◽  
Alexis T. Riche ◽  
Isabel J. Shinnick-Gordon ◽  
James C. Sample
Keyword(s):  
Role Models ◽  
Critical Incident ◽  
Earth Science ◽  
Time Period ◽  
The Usa ◽  
Data Source ◽  
Introductory Classes ◽  
Iterative Coding ◽  
As Relationship

AbstractDespite earning half of all science and engineering undergraduate degrees between 2007 and 2016 in the USA, women were awarded only 39% of earth science degrees in the same time period. In order to better understand why women are both choosing and staying in geology programs, we conducted a multi-case study of nine current female undergraduate geology majors at a large public university in the USA within a department that is at gender parity among its undergraduate majors. The main data source was audio-recorded critical incident interviews of each participant. Data from the interviews were analyzed through an iterative coding process using codes adapted from previous studies that focused on factors both internal and external to the department. The students said that personal interests, influence by others outside of the department, and introductory classes attracted them to the geology program, but once declared, departmental factors such as relationship with faculty caused them to stay. We also found an emphasis on female role models, especially those teaching introductory courses. We believe this study offers important insights into the ways in which factors leading to recruitment and retention play out in the lived experiences of female geology majors.

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.

scholarly journals How to design optimal eDNA sampling strategies for biomonitoring in river networks

2020 ◽  
Author(s):  
Luca Carraro ◽  
Julian B. Stauffer ◽  
Florian Altermatt
Keyword(s):  
Measurement Errors ◽  
Best Practice ◽  
Transport Model ◽  
Sampling Site ◽  
River Network ◽  
Decay Rates ◽  
River Networks ◽  
Sampling Effort ◽  
Biodiversity Crisis ◽  
Model Predictions

AbstractThe current biodiversity crisis calls for appropriate and timely methods to assess state and change of bio-diversity. In this respect, environmental DNA (eDNA) is a highly promising tool, especially for aquatic ecosystems. While initial eDNA studies assessed biodiversity at a few sites, technology now allows analyses of samples from many points at a time. However, the selection of these sites has been mostly motivated on an ad-hoc basis, and it is unclear where to position sampling sites in a river network to most effectively sample biodiversity. To this end, hydrology-based models might offer a unique guidance on where to sample eDNA to reconstruct the spatial patterns of taxon density based on eDNA data collected across a watershed.Here, we performed computer simulations to identify best-practice criteria for the choice of positioning of eDNA sampling sites in river networks. To do so, we combined a hydrology-based eDNA transport model with a virtual river network reproducing the scaling features of real rivers. In particular, we conducted simulations investigating scenarios of different number and location of eDNA sampling sites in a riverine network, different spatial taxon distributions, and different eDNA measurement errors.We identified best practices for sampling site selection for taxa that have a scattered versus an even distribution across the network. We observed that, due to hydrological controls, non-uniform patterns of eDNA concentration arise even if the taxon distribution is uniform and decay is neglected. We also found that uncertainties in eDNA concentration estimates do not necessarily hamper model predictions. Knowledge of eDNA decay rates improves model predictions, highlighting the need for empirical estimates of these rates under relevant environmental conditions. Our simulations help define strategies for the design of eDNA sampling campaigns in river networks, and can guide the sampling effort of field ecologists and environmental authorities.

scholarly journals Generation and application of river network analogues for use in ecology and evolution

2020 ◽  
Author(s):  
Luca Carraro ◽  
Enrico Bertuzzo ◽  
Emanuel A. Fronhofer ◽  
Reinhard Furrer ◽  
Isabelle Gounand ◽  
...  
Keyword(s):  
Spatial Ecology ◽  
Spanning Trees ◽  
Random Search ◽  
Three Dimensional ◽  
R Package ◽  
River Network ◽  
River Networks ◽  
List Type ◽  
Freshwater Ecology ◽  
Scaling Features

AbstractSeveral key processes in freshwater ecology and evolution are governed by the connectivity inherent to dendritic river networks. These networks have extensively been analyzed from a geomorphological and hydrological viewpoint, yet network structures classically used in modelling have only been partially representative of the structure of real river basins, and have often failed to capture well known scaling features of real river networks. Pioneering work has identified optimal channel networks (OCNs) as spanning trees that reproduce all scaling features characteristic of real, natural stream networks worldwide. While these networks have been used to generate landscapes for studies on metapopulations, biodiversity and epidemiology, their generation has not been generally accessible.Given the increasing interest in dendritic riverine networks by ecologists and evolutionary biologists, we here present a method to generate OCNs and, to facilitate its application, we also provide the R-package OCNet. Owing to the random search process that generates OCNs, multiple network replicas spanning the same surface can be built, allowing one to perform computational experiments whose results do not depend on the particular shape of a single river network. The OCN construct also enables the generation of elevational gradients derived from the optimal network configuration, which can constitute three-dimensional landscapes for spatial studies in both terrestrial and freshwater realms. Moreover, the OCNet package provides functions that aggregate the OCN into an arbitrary number of nodes, calculate several metrics and descriptors of river networks, and draw relevant features of the network.We describe the main functionalities of the package and present how it can be integrated into other R-packages commonly used in spatial ecology. Moreover, we exemplify the generation of OCNs and discuss an application to a metapopulation model for an invasive riverine species.In conclusion, OCNet provides a powerful tool to generate and use realistic river network analogues for various applications. It thereby allows the design of spatially realistic studies in increasingly impacted ecosystems, and enhances our knowledge on spatial processes in freshwater ecology in general.

scholarly journals A method for predicting hydrogen and oxygen isotope distributions across a region's river network using reach-scale environmental attributes

2021 ◽  
Author(s):  
Bruce Dudley ◽  
Jing Yang ◽  
Ude Shankar ◽  
Scott Graham
Keyword(s):  
New Zealand ◽  
Surface Water ◽  
River Water ◽  
Stable Isotope Ratio ◽  
Surface Flow ◽  
River Network ◽  
River Networks ◽  
Environmental Characteristics ◽  
Validation Data ◽  
Water Isotope

Abstract. Stable isotope ratio measurements (isotope values) of surface water provide information on hydrological processes and can be used to determine provenance of hydrogen and oxygen stored in animal and plant tissues. Development of maps of the distribution of isotope values (isoscapes) for river networks is limited by methods to interpolate point measures to values for the entire network. Isotope values of precipitation and environmental characteristics that drive fractionation processes within the catchment also affect downstream reaches via flow. Many environmental characteristics, such as man-made dams, are no more likely to affect nearby unconnected reaches than distant ones. Hence, distance-based geospatial and statistical interpolation methods used to develop isoscapes for precipitation and terrestrial systems are less appropriate for river networks. We used a water balance-based method, which represents patterns of surface flow and mixing, and added a regression-based correction step using catchment environmental predictors. We applied this method across the river network of New Zealand, comprising over 600,000 reaches and over 400,000 kilometres of rivers. Inputs to the model are national rainfall precipitation isoscapes, a digital elevation layer, a national river water isotope monitoring dataset (3 years of monthly sampling at 58 sites) and reach scale river environmental databases across the New Zealand river network. δ2H and δ18O isoscapes produced using this regression-based kriging method showed improved fit to validation data, compared to a model for which residuals were applied as a correction factor across the river network using ordinary kriging. The resulting river water isoscapes have potential applications in ecology, hydrology and provenance studies for which understanding of spatial variation between precipitation and surface water isotope values are required.

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