With one of the largest streamflow networks globally, administered by South Africa's Department of Water Affairs (DWA) and the South African Environmental Observation Network (SAEON), South Africa is one of 30 countries worldwide to have contributed to a global dataset to detect climate-driven hydrological trends.
The newly released dataset, called the Reference Observatory of Basins for International hydrological climate change detection (ROBIN), contains daily river flow data for 2, 386 gauging stations across the globe which have natural or near-natural catchments. Data from river basins that are relatively undisturbed by human impacts are important for efforts to detect climate-driven hydrological trends and make informed decisions on climate adaptation strategies.
The ROBIN dataset is now publicly available here. Additionally, a new open access Data Descriptor paper explains how the network and dataset were developed.
Dr Andrew Watson, a senior researcher in Stellenbosch University's School for Climate Studies, says they worked with SAEON to contribute streamflow data to ROBIN: “SAEON has a number of critically important observation points away from human-made distribution infrastructure such as reservoir releases, wastewater treatment plants, and irrigation. This data can be used to analyse climate change impacts and trends," he explains.
One such observation point is at Jonkershoek outside Stellenbosch – the Jonkershoek multiple catchment experiment has been running since the 1930s and is the oldest in Africa and one of the longest running in the world. One can even view real time data from SAEON's high altitude weather station here. The streamflow data, shared with ROBIN, is archived and stored on the SAEON Data Portal.
The ROBIN initiative, established in March 2022 and led by the United Kingdom Centre for Ecology & Hydrology (UKCEH), has created a long-term collaboration of international experts, now including more than 60 partner organisations from 30 countries across five continents.
In a media release issued by UKCEH, Prof. Peter Thorne from Maynooth University in Ireland said the latest Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) indicated “low confidence" in patterns of observed change in global streamflow trends: “Much of this lack of confidence relates to the relative absence of rivers which are unperturbed by other human factors. With ROBIN providing a set of long-term, sustained measurements which are, to the extent practical, free of human perturbations, future assessments of global streamflow can potentially discern with higher confidence any signal that may exist."
By bringing this information together and making it available for wider use, ROBIN represents a significant advance in global-scale, accessible streamflow data. The ROBIN dataset also has full metadata for 3,060 gauging stations, including those providing daily flow data. Most records span at least 40 years, though some date to the late 19th century.
According to the media release, global-scale analysis of trends in river flows using undisturbed catchments is important for many reasons. Future IPCC assessments and other policy-relevant reports need such data to better understand how climate change affects river flows but there are other potential uses beyond looking at climate impacts. Hydrologists and water managers need to know natural variations in river flow in order to detect the impacts of human disturbances (dams, abstractions) in more modified catchments. In turn, ecologists can help understand these impacts on river ecosystems.
Notes on the dataset
ROBIN is an 'open science' initiative where all data and code are shared, to enable partners (and the wider community) to replicate analysis. A code library for ROBIN is available here, highlighting its potential for research and educational purposes across the environmental sciences.
Data were quality controlled by the central ROBIN team before being added to the dataset, and two levels of data quality are applied to guide users towards appropriate the data usage.
