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Identifying critical source areas using multiple methods for effective diffuse pollution mitigation

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Identifying critical source areas using multiple methods for effective diffuse pollution mitigation. / Reaney, S. M.; Mackay, E. B.; Haygarth, P. M. et al.
In: Journal of Environmental Management, Vol. 250, 109366, 15.11.2019.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Reaney, SM, Mackay, EB, Haygarth, PM, Fisher, M, Molineux, A, Potts, M & Benskin, CMWH 2019, 'Identifying critical source areas using multiple methods for effective diffuse pollution mitigation', Journal of Environmental Management, vol. 250, 109366. https://doi.org/10.1016/j.jenvman.2019.109366

APA

Reaney, S. M., Mackay, E. B., Haygarth, P. M., Fisher, M., Molineux, A., Potts, M., & Benskin, C. M. W. H. (2019). Identifying critical source areas using multiple methods for effective diffuse pollution mitigation. Journal of Environmental Management, 250, Article 109366. https://doi.org/10.1016/j.jenvman.2019.109366

Vancouver

Reaney SM, Mackay EB, Haygarth PM, Fisher M, Molineux A, Potts M et al. Identifying critical source areas using multiple methods for effective diffuse pollution mitigation. Journal of Environmental Management. 2019 Nov 15;250:109366. Epub 2019 Sept 5. doi: 10.1016/j.jenvman.2019.109366

Author

Reaney, S. M. ; Mackay, E. B. ; Haygarth, P. M. et al. / Identifying critical source areas using multiple methods for effective diffuse pollution mitigation. In: Journal of Environmental Management. 2019 ; Vol. 250.

Bibtex

@article{dc463a8cc5a947889b1655e77d82c7b1,
title = "Identifying critical source areas using multiple methods for effective diffuse pollution mitigation",
abstract = "Diffuse pollution from agriculture constitutes a key pressure on the water quality of freshwaters and is frequently the cause of ecological degradation. The problem of diffuse pollution can be conceptualised with a source-mobilisation-pathway (or delivery)-impact model, whereby the combination of high source risk and strong connected pathways leads to {\textquoteleft}critical source areas{\textquoteright} (CSAs). These areas are where most diffuse pollution will originate, and hence are the optimal places to implement mitigation measures. However, identifying the locations of these areas is a key problem across different spatial scales within catchments. A number of approaches are frequently used for this assessment, although comparisons of these assessments are rarely carried out. We evaluate the CSAs identified via traditional walkover surveys supported by three different approaches, highlighting their benefits and disadvantages. These include a custom designed smartphone app; a desktop geographic information system (GIS) and terrain analysis-based SCIMAP (Sensitive Catchment Integrated Modelling and Analysis Platform) approach; and the use of a high spatial resolution drone dataset as an improved input data for SCIMAP modelling. Each of these methods captures the locations of the CSAs, revealing similarities and differences in the prioritisation of CSA features. The differences are due to the temporal and spatial resolution of the three methods such as the use of static land cover information, the ability to capture small scale features, such as gateways and the incomplete catchment coverage of the walkover survey. The relative costs and output resolutions of the three methods indicate that they are suitable for application at different catchment scales in conjunction with other methods. Based on the results in this paper, it is recommended that a multi-evidence-based approach to diffuse pollution management is taken across catchment spatial scales, incorporating local knowledge from the walkover with the different data resolutions of the SCIMAP approach.",
keywords = "Critical source area, Diffuse pollution, Drones, Mapping, Phone app, Walkover survey",
author = "Reaney, {S. M.} and Mackay, {E. B.} and Haygarth, {P. M.} and M. Fisher and A. Molineux and M. Potts and Benskin, {C. Mc W.H.}",
note = "Funding Information: The authors would like to acknowledge the funding for this work from the Defra Demonstration Test Catchment (DTC) project LM0304 and the NERC Environmental Virtual Observatory pilot (EVOp) project NE/I002200/1. In addition, we thank our colleagues on the Eden DTC and EVOp projects for assistance with data collection, logistics and helpful comments on the study approach. We are also very grateful to the farmers of the Newby Beck catchment for allowing us access to their land to enable us to conduct the data collection work. Funding Information: The authors would like to acknowledge the funding for this work from the Defra Demonstration Test Catchment (DTC) project LM0304 and the NERC Environmental Virtual Observatory pilot (EVOp) project NE/I002200/1 . In addition, we thank our colleagues on the Eden DTC and EVOp projects for assistance with data collection, logistics and helpful comments on the study approach. We are also very grateful to the farmers of the Newby Beck catchment for allowing us access to their land to enable us to conduct the data collection work. Publisher Copyright: {\textcopyright} 2019 The Authors",
year = "2019",
month = nov,
day = "15",
doi = "10.1016/j.jenvman.2019.109366",
language = "English",
volume = "250",
journal = "Journal of Environmental Management",
issn = "0301-4797",
publisher = "Academic Press",

}

RIS

TY - JOUR

T1 - Identifying critical source areas using multiple methods for effective diffuse pollution mitigation

AU - Reaney, S. M.

AU - Mackay, E. B.

AU - Haygarth, P. M.

AU - Fisher, M.

AU - Molineux, A.

AU - Potts, M.

AU - Benskin, C. Mc W.H.

N1 - Funding Information: The authors would like to acknowledge the funding for this work from the Defra Demonstration Test Catchment (DTC) project LM0304 and the NERC Environmental Virtual Observatory pilot (EVOp) project NE/I002200/1. In addition, we thank our colleagues on the Eden DTC and EVOp projects for assistance with data collection, logistics and helpful comments on the study approach. We are also very grateful to the farmers of the Newby Beck catchment for allowing us access to their land to enable us to conduct the data collection work. Funding Information: The authors would like to acknowledge the funding for this work from the Defra Demonstration Test Catchment (DTC) project LM0304 and the NERC Environmental Virtual Observatory pilot (EVOp) project NE/I002200/1 . In addition, we thank our colleagues on the Eden DTC and EVOp projects for assistance with data collection, logistics and helpful comments on the study approach. We are also very grateful to the farmers of the Newby Beck catchment for allowing us access to their land to enable us to conduct the data collection work. Publisher Copyright: © 2019 The Authors

PY - 2019/11/15

Y1 - 2019/11/15

N2 - Diffuse pollution from agriculture constitutes a key pressure on the water quality of freshwaters and is frequently the cause of ecological degradation. The problem of diffuse pollution can be conceptualised with a source-mobilisation-pathway (or delivery)-impact model, whereby the combination of high source risk and strong connected pathways leads to ‘critical source areas’ (CSAs). These areas are where most diffuse pollution will originate, and hence are the optimal places to implement mitigation measures. However, identifying the locations of these areas is a key problem across different spatial scales within catchments. A number of approaches are frequently used for this assessment, although comparisons of these assessments are rarely carried out. We evaluate the CSAs identified via traditional walkover surveys supported by three different approaches, highlighting their benefits and disadvantages. These include a custom designed smartphone app; a desktop geographic information system (GIS) and terrain analysis-based SCIMAP (Sensitive Catchment Integrated Modelling and Analysis Platform) approach; and the use of a high spatial resolution drone dataset as an improved input data for SCIMAP modelling. Each of these methods captures the locations of the CSAs, revealing similarities and differences in the prioritisation of CSA features. The differences are due to the temporal and spatial resolution of the three methods such as the use of static land cover information, the ability to capture small scale features, such as gateways and the incomplete catchment coverage of the walkover survey. The relative costs and output resolutions of the three methods indicate that they are suitable for application at different catchment scales in conjunction with other methods. Based on the results in this paper, it is recommended that a multi-evidence-based approach to diffuse pollution management is taken across catchment spatial scales, incorporating local knowledge from the walkover with the different data resolutions of the SCIMAP approach.

AB - Diffuse pollution from agriculture constitutes a key pressure on the water quality of freshwaters and is frequently the cause of ecological degradation. The problem of diffuse pollution can be conceptualised with a source-mobilisation-pathway (or delivery)-impact model, whereby the combination of high source risk and strong connected pathways leads to ‘critical source areas’ (CSAs). These areas are where most diffuse pollution will originate, and hence are the optimal places to implement mitigation measures. However, identifying the locations of these areas is a key problem across different spatial scales within catchments. A number of approaches are frequently used for this assessment, although comparisons of these assessments are rarely carried out. We evaluate the CSAs identified via traditional walkover surveys supported by three different approaches, highlighting their benefits and disadvantages. These include a custom designed smartphone app; a desktop geographic information system (GIS) and terrain analysis-based SCIMAP (Sensitive Catchment Integrated Modelling and Analysis Platform) approach; and the use of a high spatial resolution drone dataset as an improved input data for SCIMAP modelling. Each of these methods captures the locations of the CSAs, revealing similarities and differences in the prioritisation of CSA features. The differences are due to the temporal and spatial resolution of the three methods such as the use of static land cover information, the ability to capture small scale features, such as gateways and the incomplete catchment coverage of the walkover survey. The relative costs and output resolutions of the three methods indicate that they are suitable for application at different catchment scales in conjunction with other methods. Based on the results in this paper, it is recommended that a multi-evidence-based approach to diffuse pollution management is taken across catchment spatial scales, incorporating local knowledge from the walkover with the different data resolutions of the SCIMAP approach.

KW - Critical source area

KW - Diffuse pollution

KW - Drones

KW - Mapping

KW - Phone app

KW - Walkover survey

U2 - 10.1016/j.jenvman.2019.109366

DO - 10.1016/j.jenvman.2019.109366

M3 - Journal article

C2 - 31494409

AN - SCOPUS:85071721672

VL - 250

JO - Journal of Environmental Management

JF - Journal of Environmental Management

SN - 0301-4797

M1 - 109366

ER -