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Integrated use of GIS-based field sampling and modeling for hydrologic and water quality studies
Author(s) -
Enrique R. Vivoni,
Kevin T. Richards
Publication year - 2005
Publication title -
journal of hydroinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.654
H-Index - 50
eISSN - 1465-1734
pISSN - 1464-7141
DOI - 10.2166/hydro.2005.0021
Subject(s) - water quality , sampling (signal processing) , watershed , geographic information system , environmental science , hydrology (agriculture) , data collection , field (mathematics) , data quality , computer science , remote sensing , database , geography , engineering , statistics , ecology , metric (unit) , operations management , geotechnical engineering , mathematics , filter (signal processing) , machine learning , pure mathematics , computer vision , biology
Enhancements to traditional catchment-scale water quality assessments can be realized by leveraging geographical information systems (GIS) for both field data collection and hydrologic and water quality (H/WQ) modeling. In this study, we describe a GIS-based data collection system for geo-referenced environmental sampling utilizing mobile, wireless and Internet technologies. Furthermore, sampled field data is combined with historical measurements within a GIS-based semi-distributed watershed model for simulating water quantity and quality in a large regional catchment. The GIS-based sampling and modeling system is intended to streamline water quality assessments as compared to current practices. We describe an application and field study in the Williams River, New South Wales, Australia designed to assess the impacts of point and non-point source pollution on water quality. Historical data were utilized for calibrating and validating the Hydrologic Simulation Program ‐ Fortran (HSPF) with the BASINS GIS interface over the 1988‐ 2000 period. Results from the study indicate that short-duration, spatially extensive field campaigns provide useful data for enhancing modeling studies based on historical measurements at sparse sites. In addition, the study suggests that the conjunctive use of data collection and modeling is a step towards real-time integration of field data in hydrologic and water quality modeling efforts.

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