A critical source area phosphorus index with topographic transport factors using high resolution LiDAR digital elevation models

Ian Thomas, Paul N.C. Murphy, O Fenton, O. Shine, P.E. Mellander, P Dunlop, Philip Jordan

Research output: Contribution to conferenceAbstract

Abstract

A new phosphorus index (PI) tool is presented which aims to improve the identification of critical source areas (CSAs) of phosphorus (P) losses from agricultural land to surface waters. In a novel approach, the PI incorpo- rates topographic indices rather than watercourse proximity as proxies for runoff risk, to account for the dominant control of topography on runoff-generating areas and P transport pathways. Runoff propensity and hydrological connectivity are modelled using the Topographic Wetness Index (TWI) and Network Index (NI) respectively, util- ising high resolution digital elevation models (DEMs) derived from Light Detection and Ranging (LiDAR) to cap- ture the influence of micro-topographic features on runoff pathways. Additionally, the PI attempts to improve risk estimates of particulate P losses by incorporating an erosion factor that accounts for fine-scale topographic vari- ability within fields. Erosion risk is modelled using the Unit Stream Power Erosion Deposition (USPED) model, which integrates DEM-derived upslope contributing area and Universal Soil Loss Equation (USLE) factors. The PI was developed using field, sub-field and sub-catchment scale datasets of P source, mobilisation and transport factors, for four intensive agricultural catchments in Ireland representing different agri-environmental conditions. Datasets included soil test P concentrations, degree of P saturation, soil attributes, land use, artificial subsurface drainage locations, and 2 m resolution LiDAR DEMs resampled from 0.25 m resolution data. All factor datasets were integrated within a Geographical Information System (GIS) and rasterised to 2 m resolution. For each factor, values were categorised and assigned relative risk scores which ranked P loss potential. Total risk scores were calculated for each grid cell using a component formulation, which summed the products of weighted factor risk scores for runoff and erosion pathways. Results showed that the new PI was able to predict in-field risk variability and hence was able to identify CSAs at the sub-field scale. PI risk estimates and component scores were analysed at catchment and subcatchment scales, and validated using measured dissolved, particulate and total P losses at subcatchment snapshot sites and gauging stations at catchment outlets. The new PI provides CSA delineations at higher precision compared to conventional PIs, and more robust P transport risk estimates. The tool can be used to target cost-effective mitigation measures for P management within single farm units and wider catchments.

Conference

ConferenceEuropean Geosciences Union
General Assembly
Abbreviated titleEGU
CountryAustria
CityVienna
Period12/04/1517/04/15
Internet address

Fingerprint

digital elevation model
phosphorus
runoff
catchment
erosion
index
detection
agricultural catchment
Universal Soil Loss Equation
soil test
risk factor
mobilization
connectivity
agricultural land
GIS
environmental conditions
topography
farm
saturation
drainage

Keywords

  • phosphorus
  • LiDAR
  • Critical source area

Cite this

Thomas, I., Murphy, P. N. C., Fenton, O., Shine, O., Mellander, P. E., Dunlop, P., & Jordan, P. (2015). A critical source area phosphorus index with topographic transport factors using high resolution LiDAR digital elevation models. Abstract from European Geosciences Union
General Assembly, Vienna, Austria.
Thomas, Ian ; Murphy, Paul N.C. ; Fenton, O ; Shine, O. ; Mellander, P.E. ; Dunlop, P ; Jordan, Philip. / A critical source area phosphorus index with topographic transport factors using high resolution LiDAR digital elevation models. Abstract from European Geosciences Union
General Assembly, Vienna, Austria.1 p.
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keywords = "phosphorus, LiDAR, Critical source area",
author = "Ian Thomas and Murphy, {Paul N.C.} and O Fenton and O. Shine and P.E. Mellander and P Dunlop and Philip Jordan",
note = "Conference presentation; European Geosciences Union<br/>General Assembly : EGU, EGU ; Conference date: 12-04-2015 Through 17-04-2015",
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Thomas, I, Murphy, PNC, Fenton, O, Shine, O, Mellander, PE, Dunlop, P & Jordan, P 2015, 'A critical source area phosphorus index with topographic transport factors using high resolution LiDAR digital elevation models' European Geosciences Union
General Assembly, Vienna, Austria, 12/04/15 - 17/04/15, .

A critical source area phosphorus index with topographic transport factors using high resolution LiDAR digital elevation models. / Thomas, Ian; Murphy, Paul N.C.; Fenton, O; Shine, O.; Mellander, P.E.; Dunlop, P; Jordan, Philip.

2015. Abstract from European Geosciences Union
General Assembly, Vienna, Austria.

Research output: Contribution to conferenceAbstract

TY - CONF

T1 - A critical source area phosphorus index with topographic transport factors using high resolution LiDAR digital elevation models

AU - Thomas, Ian

AU - Murphy, Paul N.C.

AU - Fenton, O

AU - Shine, O.

AU - Mellander, P.E.

AU - Dunlop, P

AU - Jordan, Philip

N1 - Conference presentation

PY - 2015/4/12

Y1 - 2015/4/12

N2 - A new phosphorus index (PI) tool is presented which aims to improve the identification of critical source areas (CSAs) of phosphorus (P) losses from agricultural land to surface waters. In a novel approach, the PI incorpo- rates topographic indices rather than watercourse proximity as proxies for runoff risk, to account for the dominant control of topography on runoff-generating areas and P transport pathways. Runoff propensity and hydrological connectivity are modelled using the Topographic Wetness Index (TWI) and Network Index (NI) respectively, util- ising high resolution digital elevation models (DEMs) derived from Light Detection and Ranging (LiDAR) to cap- ture the influence of micro-topographic features on runoff pathways. Additionally, the PI attempts to improve risk estimates of particulate P losses by incorporating an erosion factor that accounts for fine-scale topographic vari- ability within fields. Erosion risk is modelled using the Unit Stream Power Erosion Deposition (USPED) model, which integrates DEM-derived upslope contributing area and Universal Soil Loss Equation (USLE) factors. The PI was developed using field, sub-field and sub-catchment scale datasets of P source, mobilisation and transport factors, for four intensive agricultural catchments in Ireland representing different agri-environmental conditions. Datasets included soil test P concentrations, degree of P saturation, soil attributes, land use, artificial subsurface drainage locations, and 2 m resolution LiDAR DEMs resampled from 0.25 m resolution data. All factor datasets were integrated within a Geographical Information System (GIS) and rasterised to 2 m resolution. For each factor, values were categorised and assigned relative risk scores which ranked P loss potential. Total risk scores were calculated for each grid cell using a component formulation, which summed the products of weighted factor risk scores for runoff and erosion pathways. Results showed that the new PI was able to predict in-field risk variability and hence was able to identify CSAs at the sub-field scale. PI risk estimates and component scores were analysed at catchment and subcatchment scales, and validated using measured dissolved, particulate and total P losses at subcatchment snapshot sites and gauging stations at catchment outlets. The new PI provides CSA delineations at higher precision compared to conventional PIs, and more robust P transport risk estimates. The tool can be used to target cost-effective mitigation measures for P management within single farm units and wider catchments.

AB - A new phosphorus index (PI) tool is presented which aims to improve the identification of critical source areas (CSAs) of phosphorus (P) losses from agricultural land to surface waters. In a novel approach, the PI incorpo- rates topographic indices rather than watercourse proximity as proxies for runoff risk, to account for the dominant control of topography on runoff-generating areas and P transport pathways. Runoff propensity and hydrological connectivity are modelled using the Topographic Wetness Index (TWI) and Network Index (NI) respectively, util- ising high resolution digital elevation models (DEMs) derived from Light Detection and Ranging (LiDAR) to cap- ture the influence of micro-topographic features on runoff pathways. Additionally, the PI attempts to improve risk estimates of particulate P losses by incorporating an erosion factor that accounts for fine-scale topographic vari- ability within fields. Erosion risk is modelled using the Unit Stream Power Erosion Deposition (USPED) model, which integrates DEM-derived upslope contributing area and Universal Soil Loss Equation (USLE) factors. The PI was developed using field, sub-field and sub-catchment scale datasets of P source, mobilisation and transport factors, for four intensive agricultural catchments in Ireland representing different agri-environmental conditions. Datasets included soil test P concentrations, degree of P saturation, soil attributes, land use, artificial subsurface drainage locations, and 2 m resolution LiDAR DEMs resampled from 0.25 m resolution data. All factor datasets were integrated within a Geographical Information System (GIS) and rasterised to 2 m resolution. For each factor, values were categorised and assigned relative risk scores which ranked P loss potential. Total risk scores were calculated for each grid cell using a component formulation, which summed the products of weighted factor risk scores for runoff and erosion pathways. Results showed that the new PI was able to predict in-field risk variability and hence was able to identify CSAs at the sub-field scale. PI risk estimates and component scores were analysed at catchment and subcatchment scales, and validated using measured dissolved, particulate and total P losses at subcatchment snapshot sites and gauging stations at catchment outlets. The new PI provides CSA delineations at higher precision compared to conventional PIs, and more robust P transport risk estimates. The tool can be used to target cost-effective mitigation measures for P management within single farm units and wider catchments.

KW - phosphorus

KW - LiDAR

KW - Critical source area

UR - https://meetingorganizer.copernicus.org/EGU2015/EGU2015-10625.pdf

M3 - Abstract

ER -

Thomas I, Murphy PNC, Fenton O, Shine O, Mellander PE, Dunlop P et al. A critical source area phosphorus index with topographic transport factors using high resolution LiDAR digital elevation models. 2015. Abstract from European Geosciences Union
General Assembly, Vienna, Austria.