Using catchment characteristics to model seasonality of dissolved organic carbon fluxes in semi-arid mountainous headwaters

A - Papers appearing in refereed journals

Nosrati, K., Collins, A. L. and Fiener, P. 2020. Using catchment characteristics to model seasonality of dissolved organic carbon fluxes in semi-arid mountainous headwaters. Environmental Monitoring And Assessment. 192 (Article), p. 674.

AuthorsNosrati, K., Collins, A. L. and Fiener, P.

Prediction of dissolved organic carbon (DOC) based on catchment characteristics is a useful tool for efficient and effective water management, but in the case of arid and semi-arid regions, such predictive capacity is scarce. Accordingly, the main objective of this study was to evaluate the significance of principal components for predicting DOC concentrations and fluxes in nine headwater catchments of the Hiv catchment located in the Southern Alborz Mountains in the west of Tehran, Iran. To achieve this aim, data were assembled on 24 headwater catchment characteristics comprising soil properties, physiography, seasonal rainfall, and flow attributes, as well as estimates of DOC concentrations and fluxes across four seasons. The results revealed a major positive correlation between DOC and soil organic matter parameters related to soil biological processes. Using general linear modelling, an organic matter component related to soil biology, a seasonal component related to the dummy effect of sampling seasons, and a soil physical component related to soil texture were found to be the best predictors for DOC responses in the study area.

KeywordsOrganic matter ; Soil enzyme activities; Modelling; Headwater catchments; General linear model
Year of Publication2020
JournalEnvironmental Monitoring And Assessment
Journal citation192 (Article), p. 674
Digital Object Identifier (DOI)
Open accessPublished as non-open access
FunderBiotechnology and Biological Sciences Research Council
Funder project or codeS2N - Soil to Nutrition - Work package 3 (WP3) - Sustainable intensification - optimisation at multiple scales
Output statusPublished
Publication dates
Online03 Oct 2020
Publication process dates
Accepted20 Sep 2020

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