Modeling the Relationship between Catchment Attributes and In-stream Water Quality

Fatehi, Iman; Amiri, Bahman Jabbarian; Alizadeh, Afshin; Adamowski, Jan

doi:10.1007/s11269-015-1103-y

Cited by 25 publications

(9 citation statements)

References 57 publications

(60 reference statements)

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“…The latter is also affected by the removal of riparian buffer zones, which are an important barrier where nutrient uptake by vegetation, as well as denitrification occurs [31,32]. As a result, one of the most important predictors of the concentration of nitrogen and phosphorus ions in flowing waters is the way the area of their catchment is used, as it affects their sources, mobilization, and migration [16,33].…”

Section: Introductionmentioning

confidence: 99%

Land Cover Effects on Selected Nutrient Compounds in Small Lowland Agricultural Catchments

Łaszewski

Fedorczyk

Gołaszewska

et al. 2021

Land

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The influence of landscape on nutrient dynamics in rivers constitutes an important research issue because of its significance with regard to water and land management. In the current study spatial and temporal variability of N-NO3 and P-PO4 concentrations and their landscape dependence was documented in the Świder River catchment in central Poland. From April 2019 to March 2020, water samples were collected from fourteen streams in the monthly timescale and the concentrations of N-NO3 and P-PO4 were correlated with land cover metrics based on the Corine Land Cover 2018 and Sentinel 2 Global Land Cover datasets. It was documented that agricultural lands and forests have a clear seasonal impact on N-NO3 concentrations, whereas the effect of meadows was weak and its direction was dependent on the dataset. The application of buffer zones metrics increased the correlation performance, whereas Euclidean distance scaling improved correlation mainly for forest datasets. The concentration of P-PO4 was not significantly related with land cover metrics, as their dynamics were driven mainly by hydrological conditions. The obtained results provided a new insight into landscape–water quality relationships in lowland agricultural landscape, with a special focus on evaluating the predictive performance of different land cover metrics and datasets.

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Section: Introductionmentioning

confidence: 99%

Land Cover Effects on Selected Nutrient Compounds in Small Lowland Agricultural Catchments

Łaszewski

Fedorczyk

Gołaszewska

et al. 2021

Land

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“…The link between the anthropogenic impacts of changes in land use/land cover on water quality has been previously studied extensively, [16][17][18][19] but the effect of other naturally-occurring landscape characteristics such as geology, soil type, and topography have been relatively less studied. 20,21 This review focuses on suspended sediments, nutrients (particulate and dissolved phosphorus and nitrogen species), and salts. These constituents have been selected because they have been widely studied, and because they can have deleterious impacts on receiving rivers.…”

Section: Introductionmentioning

confidence: 99%

“…This review aims to summarize the current understanding of the key landscape characteristics that influence spatial variability in riverine water quality and to highlight the remaining major knowledge gaps. The link between the anthropogenic impacts of changes in land use/land cover on water quality has been previously studied extensively, but the effect of other naturally‐occurring landscape characteristics such as geology, soil type, and topography have been relatively less studied . This review focuses on suspended sediments, nutrients (particulate and dissolved phosphorus and nitrogen species), and salts.…”

Section: Introductionmentioning

confidence: 99%

Key factors influencing differences in stream water quality across space

et al. 2017

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Globally, many rivers are experiencing declining water quality, for example, with altered levels of sediments, salts, and nutrients. Effective water quality management requires a sound understanding of how and why water quality differs across space, both within and between river catchments. Land cover, land use, land management, atmospheric deposition, geology and soil type, climate, topography, and catchment hydrology are the key features of a catchment that affect:(1) the amount of suspended sediment, nutrient, and salt concentrations in catchments (i.e., the source), (2) the mobilization ,and (3) the delivery of these constituents to receiving waters. There are, however, complexities in the relationship between landscape characteristics and stream water quality. The strength of this relationship can be influenced by the distance and spatial arrangement of constituent sources within the catchment, cross correlations between landscape characteristics, and seasonality. A knowledge gap that should be addressed in future studies is that of interactions and cross correlations between landscape characteristics. There is currently limited understanding of how the relationships between landscape characteristics and water quality responses can shift based on the other characteristics of the catchment. Understanding the many forces driving stream water quality and the complexities and interactions in these forces is necessary for the development of successful water quality management strategies. This knowledge could be used to develop predictive models, which would aid in forecasting of riverine water quality.

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“…This HSG has the highest runoff potential and the lowest infiltration (Sangani et al, 2015;USDA, 1986) (Figure 3). Digital geological maps (http:/www.gsi.ir, scale 1 : 250,000), documenting 19 geological classes (Sangani et al, 2015), were reclassified into three geological permeability classes (GPCs) based on effective porosity, type, size and connectivity of cavities, rock density, pressure gradient and features of the fluid such as viscosity (Fatehi et al, 2015). Spatial variations in geological permeability across the study area was re-classified based on the standpoint of the measure of the rock permeability, which was accordingly termed low permeable rocks G1, medium permeable rocks G2 and high permeable rocks G3.…”

Section: Methodsmentioning

confidence: 99%

Regionalizing time of concentration using landscape structural patterns of catchments

Amiri

Gao

Fohrer

et al. 2019

Journal of Hydrology and Hydromechanics

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There is an emerging challenge within water resources on how, and to what extent, borrowing concepts from landscape ecology might help re-define traditional concepts in hydrology in a more tangible manner. A stepwise regression model was adopted in this study to assess whether the time of concentration of catchments could be explained by five landscape structure-representing metrics for land use/land cover, soil and geological patches, using spatial data from 39 catchments. The models suggested that the times of concentration of the catchments could be predicted using the measures of four landscape structure-representing metrics, which include contiguity index (r2 = 0.46, p ≤0.05), fractal dimension index (r2 = 0.51, p ≤0.05), related circumscribing circle (r2 = 0.52, p ≤0.05), and shape index (r2 = 0.47, p ≤0.05). The models indicated that the regularity or irregularity in land use/land cover patch shape played a key role in affecting catchment hydrological response. Our findings revealed that regularity and irregularity in the shape of a given patch (e.g., urban and semi-urban, rangeland and agricultural patches) can affect patch functions in retarding and/or increasing flow accumulation at the catchment scale, which can, in turn, decrease or increase the times of concentration in the catchments.

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Modeling the Relationship between Catchment Attributes and In-stream Water Quality

Cited by 25 publications

References 57 publications

Land Cover Effects on Selected Nutrient Compounds in Small Lowland Agricultural Catchments

Land Cover Effects on Selected Nutrient Compounds in Small Lowland Agricultural Catchments

Key factors influencing differences in stream water quality across space

Regionalizing time of concentration using landscape structural patterns of catchments

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