The pan-Arctic watershed contains many rivers with several of Earth’s largest rivers. These rivers exert a disproportionate influence on the Arctic ocean as they transport more than 10% of global river discharge into the Arctic Ocean, which contains only ~1% of global ocean volume. In order to understand the dynamics of the Arctic ocean it is crucial to be able to quantify the discharge and nutrient fluxes originating from the rivers from this pan-Arctic watershed into the Arctic ocean. There are six Arctic rivers in this pan-Arctic watershed that have basin area’s exceeding 500 000km2 (the Ob’, Yenisey, Lena, Mackenzie, Yukon and Kolyma). Combined these “Big 6” cover 67% of the pan-Arctic watershed and 63% of the total discharge into the Arctic ocean. The next eight largest rivers and their watersheds together only cover an additional 11% of this area and 16% of the discharge, with 22% of the area and 21% of the discharge left for the remaining ‘smaller rivers’ of the Arctic.
Figure 1: Map of the pan-Arctic watershed, showing its major rivers with the six largest in dark grey and the next eight largest in light grey. The dark grey line indicates the boundary of the pan-Arctic watershed (Holmes et al., 2013)
The objective for the River Challenge of the Sea Basin Checkpoint Arctic project was to provide time series of the annual input into the Arctic Ocean of:
Water volume - Time series of annual water discharge
Water temperature - Time series of annual water temperature
Total nitrogen and Phosphates - Discharge of Total Nitrogen and Phosphates
Salmon (inwards and outwards)
Eel (inwards and outwards)
The data availability is very different for the requested parameters. Most data is available for the volume of water discharge. For some large Russian rivers time series are quite long, more than 70 years, up to more than 100 years. But many time series are relatively short, a few decades in many cases, and often incomplete. It is worrying that stations have been closed and data are delayed.
The data availability for the other parameters is much worse. Water quality monitoring is expensive, especially at remote sites. Therefore measurements are erratic, time series are short and measurement protocols differ between sites.
Bring and Destouni (2009) have also studied the status of the Arctic monitoring effort. They conclude that especially the water quality monitoring is fragmented and this restricts environmental modelers, policy makers and the public in their ability to integrate accessible data and accurately assess bio- geochemical changes in the Arctic environment. They note that the recent PARTNERS project (now continued as the Arctic-GRO) improved the situation, but large areas remain unmonitored. Bring and Destouni (2009) show that there is a significant difference between the characteristics of the monitored and unmonitored areas which limits the possibilities to generalize hydrological and hydrochemical impact assessments based on monitoring data. Even if the quality monitoring were at a level comparable to the quantity monitoring, the short time series still poses a significant problem.
An overview of available data sets can be found below.
Key data sets
In climate research the modelling the hydrological cycle is of key importance. In the hydrological cycle, the river discharge provides the major link between land and sea. The Arctic Ocean receives fresh water from several major rivers while the Arctic Ocean is relatively small and well confined by land masses. This makes it the Ocean with the largest fresh water influence. The urge to understand the role of the arctic in climate change has led to several initiatives that gather data on the hydrology of the arctic. These initiatives have compiled databases containing the water discharge and in some cases various other parameters for at least the six largest rivers: Ob’, Yenisey, Lena, Kolyma, Yukon and Mackenzie, but in some cases also many small streams. The databases that have been identified and used to compile time series are:
A notable data set that compiles information from the aforementioned databases is the ARDAT-database (Whitefield et al., 2015). In this database the monthly discharge and temperature cycle have been compiled and mapped to a 1/6° grid. This data set is particularly useful to drive environmental models like sea ice models and climatological models.
All these databases are freely accessible, in some cases registration is required.
This project is an international effort to collect and analyse a time series of water samples from the six largest Arctic rivers using identical sampling and analysis protocols. This project focuses on gathering a complete data set on the discharge and constituent loads. The following data-sets have been gathered:
Arctic-GRO II constituent data (2012-2016): Ongoing; 28 campaigns carried out every other month on the six Great Arctic Rivers
Arctic-GRO I constituent data (2009-2011): Completed; 15 comprehensive campaigns with a focus on freshet, late summer, and under-ice periods; daily samples over the freshet
PARTNERS constituent data (2004-2007): Completed; 17 comprehensive campaigns
This is the only identified data source that provides data on all requested physical parameters for the major rivers (Water volume and temperature, Sediment, Total nitrogen and Phosphates)
The ArcticRIMS project is a monitoring system for the hydrological cycle. Therefore its database contains data like precipitation, runoff, snow cover and air temperature. For this challenge only the discharge data are directly relevant and were considered. It appears that the ArcticRIMS discharge data is linked to the R-ArcticNET discharge data.
The R-ArcticNET database contains the monthly averaged discharges of all large and most small arctic rivers. The database is hosted at the Water Systems Analysis Group of the University of New Hampshire. The most recent data in this database is from 2003. It is probably no longer maintained as the people who worked on this data set are now contributing to ArcticHYCOS, which contains a superset of the Arctic discharge data. Also the ART-Russia Temperature Data set is hosted here.
The Arctic-HYCOS project aims to improve the monitoring of freshwater fluxes and pollutants into the Arctic Ocean with the objective of improving climate predictions in the Northern Hemisphere and assessing the pollution of Arctic coastal areas and the open Arctic Ocean. Currently there is a database with monthly and daily discharge data for all large rivers and many small ones. Currently suitable monitoring stations are being identified to observe the total flow to the Arctic Ocean. There were ambitions to extend the database with additional parameters (temperature), but first observation methods need to be standardized (Looser BfG, pers. comm. 2016). This data set is hosted as a special subset of the global runoff database at the Global Runoff Data Centre at the Bundesanstalt fuer Gewaesserkunde (BfG) in Germany.
All previously described data sets contain discharge data gathered by the national agencies: United States Geological Survey (USGS), Wateroffice Canada and the State Hydraulic Institute (SHI) of Russia. Therefore basically they contain the same data, albeit with potentially different post processing and data gaps. The USGS and Wateroffice Canada offer download websites where the data can be downloaded directly from the collecting agency. Apart from discharge also some suspended sediment concentration measurements were found.
- The Arctic Great Rivers Observatory (Arctic-GRO)
- HYDAT – Wateroffice Canada
- NWIS United States Geological Survey
- Déry, Stephen & A. Stadnyk, Tricia & K. MacDonald, Matthew & Gauli-Sharma, Bunu. (2016). Recent trends and variability in river discharge across northern Canada. Hydrology and Earth System Sciences. 20. 4801-4818. Doi:10.5194/hess-20-4801-2016.
- Prinsenberg, S.J. 1986. Salinity and temperature distributions of Hudson Bay and James Bay. In: Canadian inland seas, I.P Martini, ed. Elsevier Publishers Ltd., Amsterdam.
- Whitefield, J., Winsor P., McClelland J., Menemenlis D., A new river discharge and river temperature climatology data set for the pan-Arctic region, Ocean Modelling, Volume 88, 2015, Pages 1-15, ISSN 1463-5003, http://dx.doi.org/10.1016/j.ocemod.2014.12.012.
- Zhang, X. He, J. Zhang, J. and Wu, P. (2013) Enhanced poleward moisture transport and amplified northern high-latitude wetting trend Nature Climate Change 3(1):47-51 January 2013 DOI: 10.1038/nclimate1631