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פותח על ידי קלירמאש פתרונות בע"מ -
Interpolation of extensive routine water pollution monitoring datasets: Methodology and discussion of implications for aquifer management
Year:
2014
Authors :
גרבר, אלן
;
.
Volume :
16
Co-Authors:
Yuval, Department of Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa 32000, Israel
Rimon, Y., Department of Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa 32000, Israel
Graber, E.R., Institute of Soil, Water and Environmental Sciences, Volcani Center, Agricultural Research Organisation, Israel
Furman, A., Department of Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa 32000, Israel
Facilitators :
From page:
2007
To page:
2017
(
Total pages:
11
)
Abstract:
A large fraction of the fresh water available for human use is stored in groundwater aquifers. Since human activities such as mining, agriculture, industry and urbanisation often result in incursion of various pollutants to groundwater, routine monitoring of water quality is an indispensable component of judicious aquifer management. Unfortunately, groundwater pollution monitoring is expensive and usually cannot cover an aquifer with the spatial resolution necessary for making adequate management decisions. Interpolation of monitoring data is thus an important tool for supplementing monitoring observations. However, interpolating routine groundwater pollution data poses a special problem due to the nature of the observations. The data from a producing aquifer usually includes many zero pollution concentration values from the clean parts of the aquifer but may span a wide range of values (up to a few orders of magnitude) in the polluted areas. This manuscript presents a methodology that can cope with such datasets and use them to produce maps that present the pollution plumes but also delineates the clean areas that are fit for production. A method for assessing the quality of mapping in a way which is suitable to the data's dynamic range of values is also presented. A local variant of inverse distance weighting is employed to interpolate the data. Inclusion zones around the interpolation points ensure that only relevant observations contribute to each interpolated concentration. Using inclusion zones improves the accuracy of the mapping but results in interpolation grid points which are not assigned a value. The inherent trade-off between the interpolation accuracy and coverage is demonstrated using both circular and elliptical inclusion zones. A leave-one-out cross testing is used to assess and compare the performance of the interpolations. The methodology is demonstrated using groundwater pollution monitoring data from the coastal aquifer along the Israeli shoreline. The implications for aquifer management are discussed. This journal is © the Partner Organisations 2014.
Note:
Related Files :
analysis
aquifer
environmental monitoring
groundwater
Ground Water
human
Israel
pollution monitoring
seashore
water pollutant
עוד תגיות
תוכן קשור
More details
DOI :
10.1039/c4em00190g
Article number:
Affiliations:
Database:
סקופוס
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
27194
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:28
Scientific Publication
Interpolation of extensive routine water pollution monitoring datasets: Methodology and discussion of implications for aquifer management
16
Yuval, Department of Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa 32000, Israel
Rimon, Y., Department of Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa 32000, Israel
Graber, E.R., Institute of Soil, Water and Environmental Sciences, Volcani Center, Agricultural Research Organisation, Israel
Furman, A., Department of Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa 32000, Israel
Interpolation of extensive routine water pollution monitoring datasets: Methodology and discussion of implications for aquifer management
A large fraction of the fresh water available for human use is stored in groundwater aquifers. Since human activities such as mining, agriculture, industry and urbanisation often result in incursion of various pollutants to groundwater, routine monitoring of water quality is an indispensable component of judicious aquifer management. Unfortunately, groundwater pollution monitoring is expensive and usually cannot cover an aquifer with the spatial resolution necessary for making adequate management decisions. Interpolation of monitoring data is thus an important tool for supplementing monitoring observations. However, interpolating routine groundwater pollution data poses a special problem due to the nature of the observations. The data from a producing aquifer usually includes many zero pollution concentration values from the clean parts of the aquifer but may span a wide range of values (up to a few orders of magnitude) in the polluted areas. This manuscript presents a methodology that can cope with such datasets and use them to produce maps that present the pollution plumes but also delineates the clean areas that are fit for production. A method for assessing the quality of mapping in a way which is suitable to the data's dynamic range of values is also presented. A local variant of inverse distance weighting is employed to interpolate the data. Inclusion zones around the interpolation points ensure that only relevant observations contribute to each interpolated concentration. Using inclusion zones improves the accuracy of the mapping but results in interpolation grid points which are not assigned a value. The inherent trade-off between the interpolation accuracy and coverage is demonstrated using both circular and elliptical inclusion zones. A leave-one-out cross testing is used to assess and compare the performance of the interpolations. The methodology is demonstrated using groundwater pollution monitoring data from the coastal aquifer along the Israeli shoreline. The implications for aquifer management are discussed. This journal is © the Partner Organisations 2014.
Scientific Publication
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