Spatial assessment of water quality in a hierarchically structured river system using stream order classification and multivariate statistical techniques: A case study from Tunduma, Tanzania

Abstract

Water quality assessment is essential for understanding pollutant dynamics, supporting evidence-based watershed management, and protecting public health. While numerous studies have utilized statistical and modeling approaches, limited attention has been paid to how stream order influences water quality variability, particularly in urban catchments of sub-Saharan Africa. This study investigates spatial patterns of water quality in a hierarchically structured stream network in Tunduma, Tanzania, by integrating Strahler stream order classification with multivariate statistical techniques, based on monthly monitoring of six surface water points over 12 months (n = 72) during both wet and dry seasons to analyze physicochemical, nutrient, and microbial parameters. Hierarchical cluster analysis, combined with Pearson correlation matrices and significance testing, was employed to assess pollutant similarity and accumulation patterns across different stream orders. Results revealed that phosphate (PO₄³⁻) concentrations ranged from 0.42 to 1.49 mg/L and nitrate (NO³⁻) levels ranged from 4.3 to 13.2 mg/L. Strong positive correlations (r > 0.95) were observed among ion-derived parameters, such as electrical conductivity, total dissolved solids, and the concentrations of calcium (Ca²⁺) and magnesium (Mg²⁺). Third-order stream segments exhibited elevated concentrations of total suspended solids (0.990), biochemical oxygen demand (0.982), and microbial indicators, with fecal coliforms of 0-5 CFU/100 mL and total coliforms of 0-18 CFU/100 mL, reflecting cumulative pollutant loading in downstream reaches. The integration of Strahler stream ordering and cluster-based analytics enabled the identification of pollution hotspots and revealed the critical role of hydrological connectivity in shaping water quality trends. This research contributes a novel spatial-statistical framework for stream-based water quality assessment in East African urban contexts, offering practical insights for catchment-scale pollution control and resource management.

Keywords

Water quality assessment / Hierarchical cluster analysis / Strahler stream order / Nutrient and microbial pollution / Catchment management

Funding

None.

Conflict of interest

The authors declare no conflicts of interest. The funders had no role in the study design, data collection, data analysis, decision to publish, or preparation of the manuscript.

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