Model-Based Analysis of Macrophytes Role in the Flow Distribution in the Anastomosing River System

Marcinkowski, Paweł; Kiczko, Adam; Okruszko, Tomasz

doi:10.3390/w10070953

Cited by 15 publications

(13 citation statements)

References 74 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Macrophytes, as a vital component of aquatic ecosystems, are among the groups of organisms considered by the WFD for river assessment. Plants are sensitive indicators of the aquatic environment, able to detect eutrophication [2,[5][6][7][8][9], and to some extent also acidification [10], water flow [11], and morphological degradation [8]. Furthermore, aquatic plants respond to various other environmental factors, including light, temperature, and substrate [12].…”

Section: Introductionmentioning

confidence: 99%

The Macrophyte Index for Rivers (MIR) as an Advantageous Approach to Running Water Assessment in Local Geographical Conditions

Szoszkiewicz

Jusik

Pietruczuk

et al. 2019

Water

View full text Add to dashboard Cite

The Macrophyte Index for Rivers (MIR) was developed in 2007, and it was one of the first biological methods developed in Poland under the requirements of the Water Framework Directive to assess the ecological status of running waters. It is based on the quantitative and qualitative evaluation of 153 indicator taxa. The aim of this study was to evaluate the ability of the MIR method to detect trophic degradation in rivers and to compare its efficiency with other macrophyte metrics. Our investigation was based on 100 sites, representing a very clear gradient from near oligotrophic to eutrophic conditions. The results showed that macrophytes can be distinguished in terms of their ecological requirements for nutrient concentration in water, and this can be used to develop an effective system of freshwater assessment. The MIR was shown to be the indicator most strongly correlated with various forms of nutrients, and it was demonstrated that calibration of the macrophyte method to local biogeographical conditions resulted in greater effectiveness of the assessment method.

show abstract

Section: Introductionmentioning

confidence: 99%

The Macrophyte Index for Rivers (MIR) as an Advantageous Approach to Running Water Assessment in Local Geographical Conditions

Szoszkiewicz

Jusik

Pietruczuk

et al. 2019

Water

View full text Add to dashboard Cite

show abstract

“…Nowadays, many issues related to restoration, flood protection, and the functioning of aquatic ecosystems in natural river valleys are solved using hydrodynamic flow models [1][2][3][4][5]. In most cases, terrain features are being represented using Digital Terrain Models (DTM), allowing a combination of different sources of spatial data.…”

Section: Introductionmentioning

confidence: 99%

Impact of Uncertainty of Floodplain Digital Terrain Model on 1D Hydrodynamic Flow Calculation

Kiczko

Mirosław‐Świątek

2018

Water

Self Cite

View full text Add to dashboard Cite

This study investigates the effect of the Digital Terrain Model (DTM) uncertainty effect on the output of a 1D flow model. The analysis is performed for the lowland river Biebrza, covered with dense wetland vegetation, with a high uncertainty of terrain elevations. The DTM uncertainty is modeled in two ways: (1) accounting for the uncertainty spatial dependency on the basis of the correlogram function and (2) neglecting the correlation of the elevation points. The model explanation of water levels improves when elevation uncertainty is being included. Without the elevation uncertainty, the model provided a good fit only for peak flows, with uncertainty also representation of lower flows is better. It was shown that the correlation of the elevation uncertainty had a noticeable effect on the modeling outcomes, especially for near bankfull flows, where for the uncorrelated case water levels were underestimated by 5 cm, comparing to the correlated case. The effect was also present for inundation extents, obtained by an interpolation of computed water levels. The correlation of the elevation uncertainty strongly affects estimates of standard deviations of computed water levels, which were almost twice smaller when correlation was neglected. In the result, only when the correlation of the elevation uncertainty was included, it was possible to obtain confidence bands that enclosed observation points.

show abstract

“…In still scarce studies where flood routing is analyzed with the use of vegetationroughness models, some researchers tend to consider plant properties to be model parameters that should be calibrated, i.e., identified with respect to observations. So, treating them similarly to Manning coefficients, which are usually obtained by the model calibration, where their values are adjusted, ensures an agreement between computed and observed, e.g., water levels, stream velocities, or flow rates -by solving the inverse problem (e.g., Khatibi et al, 1997;Marcinkowski et al, 2018Marcinkowski et al, , 2019Yu et al, 2019). The example is given by Dalledonne et al (2019), who identified vegetation parameters describing, e.g., stem diameters, their heights, drag coefficients, and a leaf area index in the two-dimensional flow model.…”

Section: Introductionmentioning

confidence: 99%

Predicting discharge capacity of vegetated compound channels: uncertainty and identifiability of one-dimensional process-based models

Kiczko

Västilä

Kozioł

et al. 2020

Hydrol. Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

Abstract. Despite the development of advanced process-based methods for estimating the discharge capacity of vegetated river channels, most of the practical one-dimensional modeling is based on a relatively simple divided channel method (DCM) with the Manning flow resistance formula. This study is motivated by the need to improve the reliability of modeling in practical applications while acknowledging the limitations on the availability of data on vegetation properties and related parameters required by the process-based methods. We investigate whether the advanced methods can be applied to modeling of vegetated compound channels by identifying the missing characteristics as parameters through the formulation of an inverse problem. Six models of channel discharge capacity are compared in respect of their uncertainty using a probabilistic approach. The model with the lowest estimated uncertainty in explaining differences between computed and observed values is considered the most favorable. Calculations were performed for flume and field settings varying in floodplain vegetation submergence, density, and flexibility, and in hydraulic conditions. The output uncertainty, estimated on the basis of a Bayes approach, was analyzed for a varying number of observation points, demonstrating the significance of the parameter equifinality. The results showed that very reliable predictions with low uncertainties can be obtained for process-based methods with a large number of parameters. The equifinality affects the parameter identification but not the uncertainty of a model. The best performance for sparse, emergent, rigid vegetation was obtained with the Mertens method and for dense, flexible vegetation with a simplified two-layer method, while a generalized two-layer model with a description of the plant flexibility was the most universally applicable to different vegetative conditions. In many cases, the Manning-based DCM performed satisfactorily but could not be reliably extrapolated to higher flows.

show abstract

Model-Based Analysis of Macrophytes Role in the Flow Distribution in the Anastomosing River System

Cited by 15 publications

References 74 publications

The Macrophyte Index for Rivers (MIR) as an Advantageous Approach to Running Water Assessment in Local Geographical Conditions

The Macrophyte Index for Rivers (MIR) as an Advantageous Approach to Running Water Assessment in Local Geographical Conditions

Impact of Uncertainty of Floodplain Digital Terrain Model on 1D Hydrodynamic Flow Calculation

Predicting discharge capacity of vegetated compound channels: uncertainty and identifiability of one-dimensional process-based models

Contact Info

Product

Resources

About