Performance Assessment and Prospective Scenario Analysis of the Drinking Water Supply System in the Urban Commune of Diffa, Niger

This study assesses the performance of the drinking-water supply system in the Urban Commune of Diffa, Niger, and develops a prospective scenario analysis to 2040. It evaluates water demand, service coverage, production, distribution, billing, and selected network-performance indicators using documentary review, field observations, and interviews with water-service staff. The system comprises a mixed distribution network of 177.14 km, supplied by 12 boreholes and a 500 m³ storage reservoir, with 6,494 subscribers. Estimated water demand increased from 5,923.80 m³/day in 2019 to 6,983.52 m³/day in 2023, while population access was 54.5% in 2023. For January–June 2023, primary efficiency ranged from 76% to 96%, and the distribution-to-billing gap ranged from approximately 4% to 24%. The weighted production-to-billing gap over the six months was 22.39%. A prospective model using a 4.2% annual population-growth rate indicates that demand could reach approximately 14,055 m³/day by 2040. Three scenarios were evaluated: (i) a trend scenario maintaining the current overall efficiency of 77.61%; (ii) an improvement scenario progressively reaching 90% efficiency by 2040; and (iii) an optimal scenario combining 95% efficiency with production-capacity expansion and phased network extension. By 2040, the required production is estimated at approximately 18,110, 15,617, and 14,795 m³/day under the three scenarios, respectively. Diffa should pursue efficiency improvements and infrastructure investment together to improve the reliability and sustainability of drinking water services.

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Publication Details

Journal
Current Journal of Applied Science and Technology
Published
2026-11-04
DOI
https://doi.org/10.9734/cjast/2026/v45i114809
Primary Topic
Water Systems and Optimization
Type
article
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article

Performance Assessment and Prospective Scenario Analysis of the Drinking Water Supply System in the Urban Commune of Diffa, Niger

Rabe Kane, Mani Hassan Maman Salissou
Current Journal of Applied Science and Technology
Water Systems and Optimization
article

Performance Assessment and Prospective Scenario Analysis of the Drinking Water Supply System in the Urban Commune of Diffa, Niger

Rabe Kane, Mani Hassan Maman Salissou
article en

Abstract

This study assesses the performance of the drinking-water supply system in the Urban Commune of Diffa, Niger, and develops a prospective scenario analysis to 2040. It evaluates water demand, service coverage, production, distribution, billing, and selected network-performance indicators using documentary review, field observations, and interviews with water-service staff. The system comprises a mixed distribution network of 177.14 km, supplied by 12 boreholes and a 500 m³ storage reservoir, with 6,494 subscribers. Estimated water demand increased from 5,923.80 m³/day in 2019 to 6,983.52 m³/day in 2023, while population access was 54.5% in 2023. For January–June 2023, primary efficiency ranged from 76% to 96%, and the distribution-to-billing gap ranged from approximately 4% to 24%. The weighted production-to-billing gap over the six months was 22.39%. A prospective model using a 4.2% annual population-growth rate indicates that demand could reach approximately 14,055 m³/day by 2040. Three scenarios were evaluated: (i) a trend scenario maintaining the current overall efficiency of 77.61%; (ii) an improvement scenario progressively reaching 90% efficiency by 2040; and (iii) an optimal scenario combining 95% efficiency with production-capacity expansion and phased network extension. By 2040, the required production is estimated at approximately 18,110, 15,617, and 14,795 m³/day under the three scenarios, respectively. Diffa should pursue efficiency improvements and infrastructure investment together to improve the reliability and sustainability of drinking water services.

Current Journal of Applied Science and TechnologyVol. 45(11)
Openalex Percentile: Top 20%
Water Systems and Optimization
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