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A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (28 February 2017) | Viewed by 70196

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Prof. Dr. Karl-Erich Lindenschmidt

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Global Institute for Water Security, School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK S7N 3H5, Canada
Interests: surface water quality modelling; ice-jam flood hazard mapping; ice-jam flood risk assessment; remote sensing of river ice covers; river ice hydraulic modelling
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Dear Colleagues,

Within the context of fluvial systems, geospatial modeling of river networks consists of describing certain patterns in the geographical or geomorphological “fabric” along the course of rivers or streams and correlating these patterns to physical, ecological, biological and chemical processes in the river/stream system’s aquatic environment. Patterns may consist of different sets of similar sequences of geomorphological characteristics, sediment substrate type or flow velocity fields. These patterns will influence processes by defining, for example, behaviors in river ice formation or breakup, (physical), fish habitat types (ecological) and transformations in water-quality constituents (biological and chemical). We invite papers in this field of fluvial geospatial modeling in which models are presented that correlate geographic/geomorphic features of a river or stream system with physical/ecological/biological/chemical processes in the lotic aquatic environment. The predictive capability of the models should also be demonstrated in the paper.

Dr. Karl-Erich Lindenschmidt
Guest Editor

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Keywords

fluvial systems
river/stream networks
geospatial modelling
geographic/geomorphic patterns
geographical/geomorphological patterns

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Published Papers (9 papers)

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Editorial

Jump to: Research

15 pages, 247 KiB

Open AccessEditorial

Geospatial Modeling of River Systems

by Karl-Erich Lindenschmidt and Meghan Kathleen Carr

Water 2018, 10(3), 282; https://doi.org/10.3390/w10030282 - 7 Mar 2018

Cited by 5 | Viewed by 4712

Abstract

Within the context of fluvial systems, geospatial modeling of river networks consists of describing certain patterns in the geographical or geomorphological “fabric” along the course of rivers or streams and correlating these patterns to physical, ecological, biological and chemical processes in the river/stream system’s aquatic environment. Patterns may consist of different sets of similar sequences of geomorphological characteristics, sediment substrate type or flow velocity fields. These patterns will influence processes by defining, for example, behaviors in river ice formation or breakup (physical), fish habitat types (ecological) and transformations in water-quality constituents (biological and chemical). In this special issue of Geospatial Modeling of River Systems, we invited papers to present models and data that correlate geographic/geomorphic features of a river or stream system with physical/ecological/biological/chemical processes in the lotic aquatic environment. Full article

(This article belongs to the Special Issue Geospatial Modeling of River Systems)

Research

Jump to: Editorial

13 pages, 6102 KiB

Open AccessArticle

Modeling of Regionalized Emissions (MoRE) into Water Bodies: An Open-Source River Basin Management System

by Stephan Fuchs, Maria Kaiser, Lisa Kiemle, Steffen Kittlaus, Shari Rothvoß, Snezhina Toshovski, Adrian Wagner, Ramona Wander, Tatyana Weber and Sara Ziegler

Water 2017, 9(4), 239; https://doi.org/10.3390/w9040239 - 29 Mar 2017

Cited by 23 | Viewed by 9526

Abstract

An accurate budget of substance emissions is fundamental for protecting freshwater resources. In this context, the European Union asks all member states to report an emission inventory of substances for river basins. The river basin management system MoRE (Modeling of Regionalized Emissions) was developed as a flexible open-source instrument which is able to model pathway-specific emissions and river loads on a catchment scale. As the reporting tool for the Federal Republic of Germany, MoRE is used to model annual emissions of nutrients, heavy metals, micropollutants like polycyclic aromatic hydrocarbons (PAH), Bis(2-ethylhexyl)phthalate (DEHP), and certain pharmaceuticals. Observed loads at gauging stations are used to validate the calculated emissions. In addition to its balancing capabilities, MoRE can consider different variants of input data and quantification approaches, in order to improve the robustness of different modeling approaches and to evaluate the quality of different input data. No programming skills are required to set up and run the model. Due to its flexible modeling base, the effect of reduction measures can be assessed. Within strategic planning processes, this is relevant for the allocation of investments or the implementation of specific measures to reduce the overall pollutant emissions into surface water bodies and therefore to meet the requirements of water policy. Full article

(This article belongs to the Special Issue Geospatial Modeling of River Systems)

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16 pages, 7162 KiB

Open AccessArticle

Use of Bathymetric and LiDAR Data in Generating Digital Elevation Model over the Lower Athabasca River Watershed in Alberta, Canada

by Ehsan H. Chowdhury, Quazi K. Hassan, Gopal Achari and Anil Gupta

Water 2017, 9(1), 19; https://doi.org/10.3390/w9010019 - 2 Jan 2017

Cited by 13 | Viewed by 7417

Abstract

The lower Athabasca River watershed is one of the most important regions for Alberta and elsewhere due to fact that it counts for the third largest oil reserve in the world. In order to support the oil and gas extraction, Athabasca River provides most of the required water supply. Thus, it is critical to understand the characteristics of the river and its watershed in order to develop sustainable water management strategies. Here, our main objective was to develop a digital elevation model (DEM) over the lower Athabasca River watershed including the main river channel of Athabasca River (i.e., approximately 128 km from Fort McMurray to Firebag River confluence). In this study, the primary data were obtained from the Alberta Environmental Monitoring, Evaluation and Reporting Agency. Those were: (i) Geoswath bathymetry at 5–10 m spatial resolution; (ii) point cloud LiDAR data; and (iii) river cross-section survey data. Here, we applied spatial interpolation methods like inverse distance weighting (IDW) and ordinary kriging (OK) to generate the bathymetric surface at 5 m × 5 m spatial resolution using the Geoswath bathymetry data points. We artificially created data gaps in 24 sections each in the range of 100 to 400 m along the river and further investigated the performance of the methods based on statistical analysis. We observed that the DEM generated using the both IDW and OK methods were quite similar, i.e., r2, relative error, and root mean square error were approximately 0.99, 0.002, and 0.104 m, respectively. We also evaluated the performance of both methods over individual sections of interest; and overall deviation was found to be within ±2.0 m while approximately 96.5% of the data fell within ±0.25 m. Finally, we combined the Geoswath-derived DEM and LiDAR-derived DEM in generating the final DEM over the lower Athabasca River watershed at 5 m × 5 m resolution. Full article

(This article belongs to the Special Issue Geospatial Modeling of River Systems)

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15 pages, 2819 KiB

Open AccessArticle

Quantifying Spatial Changes in the Structure of Water Quality Constituents in a Large Prairie River within Two Frameworks of a Water Quality Model

by Nasim Hosseini, Kwok Pan Chun and Karl-Erich Lindenschmidt

Water 2016, 8(4), 158; https://doi.org/10.3390/w8040158 - 20 Apr 2016

Cited by 12 | Viewed by 6972

Abstract

A global sensitivity analysis was carried out on a water quality model to quantify the spatial changes in parameter sensitivity of a model of a large prairie river, the South Saskatchewan River (SSR). The method is used to assess the relative impacts of major nutrient loading sources and a reservoir on the river’s water quality. The river completely freezes over during winter; hence, the sensitivity analysis was carried out seasonally, for winter and summer, to account for the influence of ice-covered conditions on nutrient transformations. Furthermore, the integrity of the river’s aquatic ecosystem was examined through the inter-relationship between variables and comparing hierarchy index values and water quality indices at four locations along the river. Sensitivities of model parameters varied slightly at different locations along the river, with the phytoplankton growth rate being the most influential parameter. Nitrogen and phosphorus transformation processes were more sensitive in winter, while chlorophyll-a and dissolved oxygen parameters showed higher sensitivity in summer. A more complicated correlation between variables was observed downstream of the junction of the Red Deer River. Our results reveal that the lower correlation between variables may suggest a more balanced and healthier system, although further analysis is needed to support this statement. Full article

(This article belongs to the Special Issue Geospatial Modeling of River Systems)

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18 pages, 1840 KiB

Open AccessArticle

Identifying Watershed, Landscape, and Engineering Design Factors that Influence the Biotic Condition of Restored Streams

by Barbara Doll, Gregory Jennings, Jean Spooner, David Penrose, Joseph Usset, James Blackwell and Mark Fernandez

Water 2016, 8(4), 151; https://doi.org/10.3390/w8040151 - 18 Apr 2016

Cited by 3 | Viewed by 8363

Abstract

Restored stream reaches at 79 sites across North Carolina were sampled for aquatic macroinvertebrates using a rapid bioassessment protocol. Morphological design parameters and geographic factors, including watershed and landscape parameters (e.g., valley slope, substrate), were also compiled for these streams. Principal component regression analyses revealed correlations between design and landscape variables with macroinvertebrate metrics. The correlations were strengthened by adding watershed variables. Ridge regression was used to find the best-fit model for predicting dominant taxa from the “pollution sensitive” orders of Ephemeroptera (mayflies), Plecoptera (stoneflies), and Trichoptera (caddisflies), or EPT taxa, resulting in coefficient weights that were most interpretable relative to site selection and design parameters. Results indicate that larger (wider) streams located in the mountains and foothills where there are steeper valleys, larger substrate, and undeveloped watersheds are expected to have higher numbers of dominant EPT taxa. In addition, EPT taxa numbers are positively correlated with accessible floodplain width and negatively correlated with width-to-depth ratio and sinuosity. This study indicates that both site selection and design should be carefully considered in order to maximize the resulting biotic condition and associated potential ecological uplift of the stream. Full article

(This article belongs to the Special Issue Geospatial Modeling of River Systems)

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18 pages, 2988 KiB

Open AccessArticle

Using a Geospatial Model to Relate Fluvial Geomorphology to Macroinvertebrate Habitat in a Prairie River—Part 2: Matching Family-Level Indices to Geomorphological Response Units (GRUs)

by Anna Grace Nostbakken Meissner, Meghan Kathleen Carr, Iain David Phillips and Karl-Erich Lindenschmidt

Water 2016, 8(3), 107; https://doi.org/10.3390/w8030107 - 18 Mar 2016

Cited by 3 | Viewed by 6996

Abstract

Many rivers are intensely managed due to anthropogenic influences such as dams, channelization, and water provision for municipalities, agriculture, and industry. With this growing pressure on fluvial systems comes a greater need to evaluate the state of their ecosystems. The purpose of this research is to use a geospatial model of the Qu’Appelle River in Saskatchewan to distinguish instream macroinvertebrate habitats at the family level. River geomorphology was assessed through the use of ArcGIS and digital elevation models; with these tools, the sinuosity, slope, fractal dimension, and stream width of the river were processed. Subsequently, Principal Component Analysis, a clustering technique, revealed areas with similar sets of geomorphological characteristics. These similar typology sequences were then grouped into geomorphological response units (GRUs), designated a color, and mapped into a geospatial model. Macroinvertebrate data was then incorporated to reveal several relationships to the model. For instance, certain GRUs contained more highly sensitive species and healthier diversity levels than others. Future possibilities for expanding on this project include incorporating stable isotope data to evaluate the food-web structure within the river basin. Although GRUs have been very successful in identifying fish habitats in other studies, the macroinvertebrates may be too sessile and their habitat too localized to be identified by such large river units. Units may need to be much shorter (250 m) to better identify macroinvertebrate habitat. Full article

(This article belongs to the Special Issue Geospatial Modeling of River Systems)

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17 pages, 4306 KiB

Open AccessArticle

Using a Geospatial Model to Relate Fluvial Geomorphology to Macroinvertebrate Habitat in a Prairie River—Part 1: Genus-Level Relationships with Geomorphic Typologies

by Anna G. N. Meissner, Meghan K. Carr, Iain D. Phillips and Karl-Erich Lindenschmidt

Water 2016, 8(2), 42; https://doi.org/10.3390/w8020042 - 29 Jan 2016

Cited by 5 | Viewed by 7540

Abstract

Modern river ecosystems undergo constant stress from disturbances such as bank stabilization, channelization, dams, and municipal, agricultural, and industrial water use. As these anthropogenic water requirements persist, more efficient methods of characterizing river reaches are essential. Benthic macroinvertebrates are helpful when evaluating fluvial health, because they are often the first group to react to contaminants that can then be transferred through them to other trophic levels. Hence, the purpose of this research is to use a geospatial model to differentiate instream macroinvertebrate habitats, and determine if the model is a viable method for stream evaluation. Through the use of ArcGIS and digital elevation models, the fluvial geomorphology of the Qu’Appelle River in Saskatchewan (SK) was assessed. Four geomorphological characteristics of the river were isolated (sinuosity, slope, fractal dimension, and stream width) and clustered through Principle Component Analysis (PCA), yielding sets of river reaches with similar geomorphological characteristics, called typologies. These typologies were mapped to form a geospatial model of the river. Macroinvertebrate data were aligned to the locations of the typologies, revealing several relationships with the fluvial geomorphology. A Kruskal-Wallis analysis and post hoc pairwise multiple comparisons were completed with the macroinvertebrate data to pinpoint significant genera, as related to the geospatial model. Full article

(This article belongs to the Special Issue Geospatial Modeling of River Systems)

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21 pages, 5942 KiB

Open AccessArticle

Modeling Typhoon‐Induced Alterations on River Sediment Transport and Turbidity Based on Dynamic Landslide Inventories: Gaoping River Basin, Taiwan

by Chih‐Hua Chang, John F. Harrison and Yu‐Chi Huang

Water 2015, 7(12), 6910-6930; https://doi.org/10.3390/w7126666 - 5 Dec 2015

Cited by 19 | Viewed by 7936

Abstract

This study examines the impacts of storm‐triggered landslides on downstream sediment and turbidity responses in the Gaoping River Basin, Taiwan using the Soil and Water Assessment Tool (SWAT). Attention is given to analyzing the increased and altered baseline of suspended sediment load and turbidity after the disturbances caused by the rainfall and landslides associated with Typhoon Morakot in 2009. SWAT parameters were calibrated by the observed hydrometric data from 1999 to 2003 using the log‐scale root‐mean‐square error (log‐RMSE) and Nash‐Sutcliffe Model Efficiency. Both parameter sets were applied for the simulation of suspended sediment yield and turbidity with annual updated landslide inventories for the period 2004–2012. The landslide updating mirrors the physical land‐cover changes and has slightly improved the model performance, yet landslides alone cannot explain the difference between Morakot‐induced and SWAT‐simulated sediment discharge. The set of parameters calibrated by log‐RMSE can better approximate the increased baseline and typhoon induced alterations. The results show alterations in sediment erosion and transport: (1) drastically increased the turbidity baseline and occurrence of high‐turbidity; (2) altered coefficient and exponent values of the sediment rating curve; and (3) altered relationship between rainfall and induced turbidity during major rainfall events. The research in this study provides an improved modeling approach to typhoon‐induced alterations on river sediment loads and turbidity. Full article

(This article belongs to the Special Issue Geospatial Modeling of River Systems)

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20 pages, 5666 KiB

Open AccessArticle

Numerical Simulation of Groundwater Flow in a River Valley Basin in Jilin Urban Area, China

by Shuwei Qiu, Xiujuan Liang, Changlai Xiao, He Huang, Zhang Fang and Fengchao Lv

Water 2015, 7(10), 5768-5787; https://doi.org/10.3390/w7105768 - 21 Oct 2015

Cited by 32 | Viewed by 9042

Abstract

In order to evaluate the groundwater resources and aquifer system of the Jilin urban area (JUA), a groundwater numerical flow model was established by using the groundwater modeling system based on data from 190 boreholes. River stages were interpolated to control the groundwater flow field. The input parameters such as hydraulic conductivity and specific yield were based on data from 260 pumping test data. The model was calibrated by trial and error, simulated results were compared to the observed head and contour maps, which were generally in good agreement, and the root mean squared error was 0.66 m. Sensitivity analysis was carried out and recharge proved to be the most sensitive factor in this model. The water budget showed that the input was 2.07× 10⁸ m³/a, which was smaller than the output of 2.21 × 10⁸ m³/a. A groundwater level decline and cone of depression exist in the Songhua and Aolong river valley. The JUA aquifer systems can be well and efficiently modeled by constructing a numerical model. Based on the supply and demand analysis of water resources, the established model would finally provide a scientific basis to use the groundwater resources sustainably in JUA. Full article

(This article belongs to the Special Issue Geospatial Modeling of River Systems)

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