Muddying the Picture? Forecasting Particulate Sources and Dispersal Patterns in Managed Catchments
Satellite imagery and climate change projections improve our ability to map and forecast sediment sources and transport pathways at high resolution, which is vital for catchment management. Detailed assessment of temporal and spatial changes in erosion risk are key to forecasting pollutant dispersal...
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doaj-9d9ce780bacc42b7acf6fad4b4b3f9f42020-11-25T01:11:15ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632019-11-01710.3389/feart.2019.00277470726Muddying the Picture? Forecasting Particulate Sources and Dispersal Patterns in Managed CatchmentsJanet Cristine Richardson0David Mark Hodgson1Paul Kay2Benjamin J. Aston3Andrew C. Walker4Stratigraphy Group, School of Earth and Environment, University of Leeds, Leeds, United KingdomStratigraphy Group, School of Earth and Environment, University of Leeds, Leeds, United KingdomSchool of Geography, University of Leeds, Leeds, United KingdomYorkshire Water, Clean Water and Catchment Strategy, Bradford, United KingdomYorkshire Water, Clean Water and Catchment Strategy, Bradford, United KingdomSatellite imagery and climate change projections improve our ability to map and forecast sediment sources and transport pathways at high resolution, which is vital for catchment management. Detailed assessment of temporal and spatial changes in erosion risk are key to forecasting pollutant dispersal, which affects water treatment costs and ecology. Outputs from scenario modeling of the River Derwent catchment, Yorkshire, indicate clear spatial and temporal trends in erosion risk. These trends are not picked up by using traditional methods, which rely on static land use maps. Using satellite-derived maps show that lower resolution traditional land-use maps relatively underestimate erosion risk in terms of location of source areas and seasonal variation in erosion risk. Seasonal variation in agricultural practices can be assessed by incorporating bare land variation into models, which show that erosion risk is relatively overestimated if all agricultural land is assumed to have the same character. Producing seasonal land use maps also allows the assessment of temporal variation in rainfall, which in combination with climate change projections allows for adaptable management plans. The bias in gradient in modeling, which assumes that high gradients result in greater sediment erosion risk, show that traditional models underestimate the contribution of erosion risk in lowland areas. This is compounded by the absence of artificial drainages in topographic rasters, which increases connectivity in lowland areas. By producing end member scenarios, model outputs help to inform where catchment management should be targeted, and whether seasonal interventions should be implemented. This information is vital to communicate with landowners when they implement catchment management practices, such as sediment traps and earth bunds. Adaption of erosion risk modeling practices is urgently needed in order to quantify the impact of artificial interference in which human activity disrupts ‘natural’ sediment source-to sink configurations, such as integrating new pathways and stores due to land use change and management. Furthermore, integrating higher resolution catchment modeling and improved seasonal forecasts of pollutant flux to oceans will permit more effective interventions. This paper highlights single output erosion risk maps are not effective to inform catchment management.https://www.frontiersin.org/article/10.3389/feart.2019.00277/fullerosion risksatellite imageryseasonalityland usesediment budgetdiffuse pollution |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Janet Cristine Richardson David Mark Hodgson Paul Kay Benjamin J. Aston Andrew C. Walker |
spellingShingle |
Janet Cristine Richardson David Mark Hodgson Paul Kay Benjamin J. Aston Andrew C. Walker Muddying the Picture? Forecasting Particulate Sources and Dispersal Patterns in Managed Catchments Frontiers in Earth Science erosion risk satellite imagery seasonality land use sediment budget diffuse pollution |
author_facet |
Janet Cristine Richardson David Mark Hodgson Paul Kay Benjamin J. Aston Andrew C. Walker |
author_sort |
Janet Cristine Richardson |
title |
Muddying the Picture? Forecasting Particulate Sources and Dispersal Patterns in Managed Catchments |
title_short |
Muddying the Picture? Forecasting Particulate Sources and Dispersal Patterns in Managed Catchments |
title_full |
Muddying the Picture? Forecasting Particulate Sources and Dispersal Patterns in Managed Catchments |
title_fullStr |
Muddying the Picture? Forecasting Particulate Sources and Dispersal Patterns in Managed Catchments |
title_full_unstemmed |
Muddying the Picture? Forecasting Particulate Sources and Dispersal Patterns in Managed Catchments |
title_sort |
muddying the picture? forecasting particulate sources and dispersal patterns in managed catchments |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Earth Science |
issn |
2296-6463 |
publishDate |
2019-11-01 |
description |
Satellite imagery and climate change projections improve our ability to map and forecast sediment sources and transport pathways at high resolution, which is vital for catchment management. Detailed assessment of temporal and spatial changes in erosion risk are key to forecasting pollutant dispersal, which affects water treatment costs and ecology. Outputs from scenario modeling of the River Derwent catchment, Yorkshire, indicate clear spatial and temporal trends in erosion risk. These trends are not picked up by using traditional methods, which rely on static land use maps. Using satellite-derived maps show that lower resolution traditional land-use maps relatively underestimate erosion risk in terms of location of source areas and seasonal variation in erosion risk. Seasonal variation in agricultural practices can be assessed by incorporating bare land variation into models, which show that erosion risk is relatively overestimated if all agricultural land is assumed to have the same character. Producing seasonal land use maps also allows the assessment of temporal variation in rainfall, which in combination with climate change projections allows for adaptable management plans. The bias in gradient in modeling, which assumes that high gradients result in greater sediment erosion risk, show that traditional models underestimate the contribution of erosion risk in lowland areas. This is compounded by the absence of artificial drainages in topographic rasters, which increases connectivity in lowland areas. By producing end member scenarios, model outputs help to inform where catchment management should be targeted, and whether seasonal interventions should be implemented. This information is vital to communicate with landowners when they implement catchment management practices, such as sediment traps and earth bunds. Adaption of erosion risk modeling practices is urgently needed in order to quantify the impact of artificial interference in which human activity disrupts ‘natural’ sediment source-to sink configurations, such as integrating new pathways and stores due to land use change and management. Furthermore, integrating higher resolution catchment modeling and improved seasonal forecasts of pollutant flux to oceans will permit more effective interventions. This paper highlights single output erosion risk maps are not effective to inform catchment management. |
topic |
erosion risk satellite imagery seasonality land use sediment budget diffuse pollution |
url |
https://www.frontiersin.org/article/10.3389/feart.2019.00277/full |
work_keys_str_mv |
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