What can we learn from multi-data calibration of a process-based ecohydrological model?-Reference-Cited by-同舟云学术

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What can we learn from multi-data calibration of a process-based ecohydrological model?

Published:2018-03 Issue: Volume:101 Page:301-316
ISSN:1364-8152
Container-title:Environmental Modelling & Software
language:en
Short-container-title:Environmental Modelling & Software

Author:

Kuppel Sylvain,Tetzlaff Doerthe,Maneta Marco P.,Soulsby Chris

Funder

European Research Council

U.S National Science Foundation

U.S National Science Foundation EPSCoR Cooperative Agreement

Publisher

Elsevier BV

Subject

Ecological Modeling,Environmental Engineering,Software

Reference111 articles.

1. Integrated surface-subsurface model to investigate the role of groundwater in headwater catchment runoff generation: a minimalist approach to parameterisation;Ala-aho;J. Hydrol.,2017

2. Using isotopes to constrain water flux and age estimates in snow-influenced catchments using the STARR (Spatially distributed Tracer-Aided Rainfall–Runoff) model;Ala-aho;Hydrol. Earth Syst. Sci.,2017

3. A comparison of wetness indices for the prediction of observed connected saturated areas under contrasting conditions;Ali;Earth Surf. Process. Landforms,2014

4. Forest ecosystem processes at the watershed scale: hydrological and ecological controls of nitrogen export;Band;Hydrol. Process.,2001

5. Changes in forest productivity across Alaska consistent with biome shift;Beck;Ecol. Lett.,2011

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