Exploring structural sediment connectivity via surface runoff in agricultural lands of Finland
Spatial information on the distribution of erosion areas and sediment transport pathways within agricultural landscapes is limited. Thus, we assess structural sediment connectivity via surface runoff by using a digital elevation model (2 × 2 m2) and RUSLE-based erosion estimates to compute index of...
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Format: | Article |
Language: | English |
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Taylor & Francis Group
2022-12-01
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Series: | Acta Agriculturae Scandinavica. Section B, Soil and Plant Science |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/09064710.2022.2136583 |
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author | M. Tähtikarhu T. Räsänen J. Oksanen J. Uusi-Kämppä |
author_facet | M. Tähtikarhu T. Räsänen J. Oksanen J. Uusi-Kämppä |
author_sort | M. Tähtikarhu |
collection | DOAJ |
description | Spatial information on the distribution of erosion areas and sediment transport pathways within agricultural landscapes is limited. Thus, we assess structural sediment connectivity via surface runoff by using a digital elevation model (2 × 2 m2) and RUSLE-based erosion estimates to compute index of connectivity (IC) and sediment delivery estimates. The variables were analyzed within and between two topographically contrasting subcatchments. We found greater spatial variability of IC within a subcatchment than between the subcatchments. The majority of field parcel areas (65%–97%) were structurally connected to adjacent open ditches and streams. Areas with high erosion estimates also tended to be structurally well-connected, both at the pixel (Pearson r = 0.58–0.63) and parcel scale (r = 0.49–0.67). The IC model was not highly sensitive to parameter variations. In contrast, the magnitude of sediment delivery estimates was highly sensitive to parameter variations. However, based on the high rank correlation (Spearman rs > 0.95) between computed sediment delivery estimates, the tool provided consistent information on potentially high sediment delivery areas. More empirical data and dynamic model applications could be applied to improve the accuracy of the estimates. The method provides a feasible tool to generate open data on connectivity. |
first_indexed | 2024-03-12T00:27:51Z |
format | Article |
id | doaj.art-0f98b1395f7444ebb7d3a5fc09df3740 |
institution | Directory Open Access Journal |
issn | 0906-4710 1651-1913 |
language | English |
last_indexed | 2024-03-12T00:27:51Z |
publishDate | 2022-12-01 |
publisher | Taylor & Francis Group |
record_format | Article |
series | Acta Agriculturae Scandinavica. Section B, Soil and Plant Science |
spelling | doaj.art-0f98b1395f7444ebb7d3a5fc09df37402023-09-15T10:26:28ZengTaylor & Francis GroupActa Agriculturae Scandinavica. Section B, Soil and Plant Science0906-47101651-19132022-12-0172195797010.1080/09064710.2022.21365832136583Exploring structural sediment connectivity via surface runoff in agricultural lands of FinlandM. Tähtikarhu0T. Räsänen1J. Oksanen2J. Uusi-Kämppä3Natural Resources Institute Finland (LUKE)Natural Resources Institute Finland (LUKE)National Land Survey of FinlandNatural Resources Institute Finland (LUKE)Spatial information on the distribution of erosion areas and sediment transport pathways within agricultural landscapes is limited. Thus, we assess structural sediment connectivity via surface runoff by using a digital elevation model (2 × 2 m2) and RUSLE-based erosion estimates to compute index of connectivity (IC) and sediment delivery estimates. The variables were analyzed within and between two topographically contrasting subcatchments. We found greater spatial variability of IC within a subcatchment than between the subcatchments. The majority of field parcel areas (65%–97%) were structurally connected to adjacent open ditches and streams. Areas with high erosion estimates also tended to be structurally well-connected, both at the pixel (Pearson r = 0.58–0.63) and parcel scale (r = 0.49–0.67). The IC model was not highly sensitive to parameter variations. In contrast, the magnitude of sediment delivery estimates was highly sensitive to parameter variations. However, based on the high rank correlation (Spearman rs > 0.95) between computed sediment delivery estimates, the tool provided consistent information on potentially high sediment delivery areas. More empirical data and dynamic model applications could be applied to improve the accuracy of the estimates. The method provides a feasible tool to generate open data on connectivity.http://dx.doi.org/10.1080/09064710.2022.2136583connectivitylowlandserosionrusleconnectivity index |
spellingShingle | M. Tähtikarhu T. Räsänen J. Oksanen J. Uusi-Kämppä Exploring structural sediment connectivity via surface runoff in agricultural lands of Finland Acta Agriculturae Scandinavica. Section B, Soil and Plant Science connectivity lowlands erosion rusle connectivity index |
title | Exploring structural sediment connectivity via surface runoff in agricultural lands of Finland |
title_full | Exploring structural sediment connectivity via surface runoff in agricultural lands of Finland |
title_fullStr | Exploring structural sediment connectivity via surface runoff in agricultural lands of Finland |
title_full_unstemmed | Exploring structural sediment connectivity via surface runoff in agricultural lands of Finland |
title_short | Exploring structural sediment connectivity via surface runoff in agricultural lands of Finland |
title_sort | exploring structural sediment connectivity via surface runoff in agricultural lands of finland |
topic | connectivity lowlands erosion rusle connectivity index |
url | http://dx.doi.org/10.1080/09064710.2022.2136583 |
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