23 citations as recorded by crossref.

1. Quantification of agricultural best management practices impacts on sediment and phosphorous export in a small catchment in southeastern Sweden B. Oduor et al. https://doi.org/10.1016/j.agwat.2023.108595
2. Using multi-model averaging to improve the reliability of catchment scale nitrogen predictions J. Exbrayat et al. https://doi.org/10.5194/gmd-6-117-2013
3. Multi-model data fusion as a tool for PUB: example in a Swedish mesoscale catchment J. Exbrayat et al. https://doi.org/10.5194/adgeo-29-43-2011
4. Addressing sources of uncertainty in runoff projections for a data scarce catchment in the Ecuadorian Andes J. Exbrayat et al. https://doi.org/10.1007/s10584-014-1160-x
5. Optimal reliability ensemble averaging approach for robust climate projections over China Y. Gao et al. https://doi.org/10.1002/joc.8485
6. Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties J. Exbrayat et al. https://doi.org/10.5194/esd-9-153-2018
7. Gridded climate data products are an alternative to instrumental measurements as inputs to rainfall–runoff models J. Ledesma & M. Futter https://doi.org/10.1002/hyp.11269
8. Climate Change Impact on Riverine Nutrient Load and Land-Based Remedial Measures of the Baltic Sea Action Plan B. Arheimer et al. https://doi.org/10.1007/s13280-012-0323-0
9. Regional catchment classification with respect to low flow risk in a Pleistocene landscape B. Thomas et al. https://doi.org/10.1016/j.jhydrol.2012.10.020
10. Quantifying model uncertainty using Bayesian multi-model ensembles M. Wagena et al. https://doi.org/10.1016/j.envsoft.2019.03.013
11. Finding options to improve catchment water quality—Lessons learned from historical land use situations in a Mediterranean catchment in Slovenia M. Glavan et al. https://doi.org/10.1016/j.ecolmodel.2013.04.004
12. Long-term dynamics of dissolved organic carbon: Implications for drinking water supply J. Ledesma et al. https://doi.org/10.1016/j.scitotenv.2012.05.071
13. Probabilistic multi-model ensemble predictions of nitrogen concentrations in river systems J. Exbrayat et al. https://doi.org/10.1029/2011GL047522
14. Model intercomparison to explore catchment functioning: Results from a remote montane tropical rainforest I. Plesca et al. https://doi.org/10.1016/j.ecolmodel.2011.05.005
15. Quantifying the impact of climate change on enteric waterborne pathogen concentrations in surface water N. Hofstra https://doi.org/10.1016/j.cosust.2011.10.006
16. Development of multi-model ensemble approach for enhanced assessment of impacts of climate change on climate extremes G. Tegegne et al. https://doi.org/10.1016/j.scitotenv.2019.135357
17. Evaluating the accuracy of two in situ optical sensors to estimate DOC concentrations for drinking water production S. Hoffmeister et al. https://doi.org/10.1039/D0EW00150C
18. Multimodel ensemble projection of precipitation over South Korea using the reliability ensemble averaging G. Tegegne & A. Mellesse https://doi.org/10.1007/s00704-022-04350-8
19. An overview of methods to evaluate uncertainty of deterministic models in decision support L. Uusitalo et al. https://doi.org/10.1016/j.envsoft.2014.09.017
20. Measures to sustain seasonal minimum runoff in small catchments in the mid-latitudes: A review B. Thomas et al. https://doi.org/10.1016/j.jhydrol.2011.07.045
21. A SWAT model validation of nested-scale contemporaneous stream flow, suspended sediment and nutrients from a multiple-land-use watershed of the central USA S. Zeiger & J. Hubbart https://doi.org/10.1016/j.scitotenv.2016.07.178
22. Spatiotemporal Reliability Ensemble Averaging of Multimodel Simulations G. Tegegne et al. https://doi.org/10.1029/2019GL083053
23. Toward a framework for the multimodel ensemble prediction of soil nitrogen losses K. Liao et al. https://doi.org/10.1016/j.ecolmodel.2021.109675