Classifying rivers into homogeneous categories based on hydrological and/or environmental attributes supports the implementation of environmental flows to sustain aquatic ecosystems and support the resource needs of society. Hydrological classifications provide decision-makers with a pragmatic number of water management units by grouping individual rivers or river segments expected to exhibit similar biophysical responses to flow alteration. Such classifications are particularly useful across broad geographies and in data-limited contexts, such as in Tanzania, where the legal requirement to implement environmental flows for all major waterbodies remains constrained by scant data. We present a two-level hydrological classification of all Tanzanian basins and the Rufiji River Basin. For the Rufiji River Basin, the largest river basin in the country, we performed an inductive classification based on the availability of long-term time series of daily average discharge. We clustered 28 gauging stations into seven classes according to ecologically relevant hydrological metrics and used boosted classification trees to predict the hydrological class of all 95,909 river segments in the basin based on environmental attributes that influence flow regimes. In the absence of consistent, readily-available gauged flow data, we conducted a deductive classification of all Tanzanian rivers whereby segments were directly grouped by multivariate similarity using the same environmental attributes. This analysis revealed 10 river classes reflecting the diversity of ecohydrological conditions characterizing the 486,681 river segments draining in and out of Tanzania. The new hydrological classifications presented here provide the foundation to guide implementation of management practices within the water policy framework of Tanzania.
All Science Journal Classification (ASJC) codes
- Ecology, Evolution, Behavior and Systematics
- Aquatic Science
- Earth-Surface Processes