Machine learning and linear regression models to predict catchment-level base cation weathering rates across the southern Appalachian Mountain region, USA

Water Resources Research

Volumn 50, Issue 4, 2014, Pages 2798-2814

  Povak, Nicholas A ^a   Hessburg, Paul F ^a   McDonnell, Todd C ^b   Reynolds, Keith M ^c   Sullivan, Timothy J ^b   Salter, R Brion ^a   Cosby, Bernard J ^d  

^a PACIFIC NORTHWEST RESEARCH STATION   (United States)

^b EandS Environmental Chemistry Inc Oregon   (United States)

^c PACIFIC NORTHWEST RESEARCH STATION   (United States)

^d UNIVERSITY OF VIRGINIA   (United States)

Author keywords

acid deposition; base cation weathering; critical loads; machine learning; regression; sulfur

Indexed keywords

CLIMATE MODELS; DECISION TREES; DEPOSITION; FORECASTING; FORESTRY; LEARNING SYSTEMS; LITHOLOGY; POSITIVE IONS; REGRESSION ANALYSIS; RUNOFF; SOILS; SULFUR; WEATHERING;

ACID DEPOSITION; BASE CATIONS; CRITICAL LOAD; LINEAR REGRESSION MODELS; MACHINE LEARNING APPROACHES; REGRESSION; SOIL MINERAL WEATHERINGS; SOUTHERN APPALACHIAN MOUNTAINS;

CATCHMENTS;

ACCURACY ASSESSMENT; ACID DEPOSITION; ACIDIFICATION; ARTIFICIAL INTELLIGENCE; CATCHMENT; CATION; CHEMICAL WEATHERING; CLAY; CONIFEROUS FOREST; CRITICAL LOAD; DECIDUOUS FOREST; DECISION MAKING; ENVIRONMENTAL RISK; ERROR ANALYSIS; LITHOLOGY; NUMERICAL MODEL; PREDICTION; REGRESSION ANALYSIS; SULFUR;

CATIONS; DEPOSITION; FORECASTS; FORESTRY; REGRESSION ANALYSIS; RUNOFF; SOIL; SULFUR; WEATHERING;

APPALACHIANS; UNITED STATES;

EID: 84897260029     PISSN: 00431397     EISSN: 19447973     Source Type: Journal    
DOI: 10.1002/2013WR014203     Document Type: Article

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