River Network Toolkit (RivTool) — ASN Events

River Network Toolkit (RivTool) (#102)

Gonçalo Duarte 1 , Tiago Oliveira , Pedro Segurado 1 , Paulo Branco 1 , Gertrud Haidvogl 2 , Didier Pont 3 , Teresa Ferreira 1
  1. CEF, ISA-UL, Cascais, Portugal
  2. Institute of Hydrobiology and Aquatic Ecosystem Management, University of Natural Resources and Life Sciences, Vienna, Austria
  3. National Research Institute of Sciences and Technology for Environment and Agriculture (IRSTEA), Antony, France

Studying freshwater environments at broad spatial scales using detailed river network information can be challenging. Not only biological data is hard to obtain but also environmental, hydraulic and hydrological information is difficult to acquire and relate with biological information along a river network.

Here we present an innovative software containing a set of tools that allows to obtain, through several mathematical calculations, environmental, hydraulic and hydrological data from a given river network. Because it is database driven, not spatially driven, its implementation is very straightforward; calculations are fast (e.g., calculating cumulative drainage basin value for 1.4 million segments takes 20 s); and, more relevant, it can simplify the computation of mathematical complex variables such as stream power which involves discharge, precipitation, upstream drainage area and temperature. Although implemented and tested for the River and Catchment Database from the Catchment Characterisation and Modelling Database (CCM), its use is not restricted to a specific network or continent. There is a feature that allows the upload of any river network and, if it complies with the required key fields, the software will generate a matrix that enables all computations based on the new network information.

This free software not only helps linking biological data with other variables, but also allows the acquisition, over a river network, of complex variables. RivTool will facilitate studies of freshwater species along river networks, regardless of their extent and complexity, enhancing thus the use of environmental (e.g., climate, land-use), hydraulic and hydrologic information on such studies.