Your browser doesn't support javascript.
loading
Modeling the isotopic evolution of snowpack and snowmelt: Testing a spatially distributed parsimonious approach.
Ala-Aho, Pertti; Tetzlaff, Doerthe; McNamara, James P; Laudon, Hjalmar; Kormos, Patrick; Soulsby, Chris.
Afiliação
  • Ala-Aho P; Northern Rivers Institute, School of Geosciences University of Aberdeen Aberdeen UK.
  • Tetzlaff D; Northern Rivers Institute, School of Geosciences University of Aberdeen Aberdeen UK.
  • McNamara JP; Department of Geosciences Boise State University Boise Idaho USA.
  • Laudon H; Department of Forest, Ecology and Management Swedish University of Agricultural Sciences Umeå Sweden.
  • Kormos P; United States Department of Agriculture Agricultural Research Service Boise Idaho USA.
  • Soulsby C; Northern Rivers Institute, School of Geosciences University of Aberdeen Aberdeen UK.
Water Resour Res ; 53(7): 5813-5830, 2017 07.
Article em En | MEDLINE | ID: mdl-28983132
ABSTRACT
Use of stable water isotopes has become increasingly popular in quantifying water flow paths and travel times in hydrological systems using tracer-aided modeling. In snow-influenced catchments, snowmelt produces a traceable isotopic signal, which differs from original snowfall isotopic composition because of isotopic fractionation in the snowpack. These fractionation processes in snow are relatively well understood, but representing their spatiotemporal variability in tracer-aided studies remains a challenge. We present a novel, parsimonious modeling method to account for the snowpack isotope fractionation and estimate isotope ratios in snowmelt water in a fully spatially distributed manner. Our model introduces two calibration parameters that alone account for the isotopic fractionation caused by sublimation from interception and ground snow storage, and snowmelt fractionation progressively enriching the snowmelt runoff. The isotope routines are linked to a generic process-based snow interception-accumulation-melt model facilitating simulation of spatially distributed snowmelt runoff. We use a synthetic modeling experiment to demonstrate the functionality of the model algorithms in different landscape locations and under different canopy characteristics. We also provide a proof-of-concept model test and successfully reproduce isotopic ratios in snowmelt runoff sampled with snowmelt lysimeters in two long-term experimental catchment with contrasting winter conditions. To our knowledge, the method is the first such tool to allow estimation of the spatially distributed nature of isotopic fractionation in snowpacks and the resulting isotope ratios in snowmelt runoff. The method can thus provide a useful tool for tracer-aided modeling to better understand the integrated nature of flow, mixing, and transport processes in snow-influenced catchments.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Water Resour Res Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Water Resour Res Ano de publicação: 2017 Tipo de documento: Article