Hydrologic classification of Tanzanian rivers to support national water resource policy

Abstract

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.

Predictability of flow metrics calculated using a distributed hydrologic model across ecoregions and stream classes: Implications for developing flow–ecology relationships

“…The use of a stream classification system (SCS) to focus ecological relationships on specific segments of the hydrologic regime is an important step in developing ecological flows (Olden et al, 2012; Poff et al, 2010, 2017). Several studies have provided potential classification systems available for ready application based on hydrologic characteristics, typically determined from long‐term daily streamflow observations (Archfield et al, 2014; McManamay et al, 2012; Olden et al, 2021; Poff, 1996). However, expanding these metric‐based classification systems beyond the streamflow gages can be problematic (Eng et al, 2017).…”

“…We made initial assignments based on the following criteria, which follows the basic principles of several recent studies (McManamay & DeRolph, 2019; Olden et al, 2021). First, the network surrounding the calibrated gages is divided into groupings of HUC12s so that the mainstem and nearby tributaries are assigned the calibration parameters of the closest gage.…”

Enhancing whole-of-river conservation

“…This can involve statistical classification of management units (e.g. Olden et al 2021) but, again, this approach requires substantial data input. Alternatively, generic typologies (e.g.…”

Assessing placement bias of the global river gauge network

“…For example, skewed spatial representation in the rain gauge network is a source of bias in precipitation estimates 9 , and similar landscape bias exists in the locations of US Geological Survey (USGS) stream gauges 10,11 . Similar placement bias in the global stream gauge network may limit our understanding of human water-supply systems, compromise efforts to achieve global biodiversity goals 12 , challenge the estimation of hydrologic impacts of human activities 13 and undermine best practices for determining environmental and cultural flow standards 14 . Yet our ability to assess the global representativeness of gauges has, until recently, been limited by a lack of global-scale stream gauge and environmental data.…”