Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

<p>Relative sensitivity of the criterion.</p>

Domain:

environment and energyclimate

Record type:

paper
Creator:
BilDerDanSol
Host:avatar

Rapid urbanization and climate variability in Addis Ababa’s steeply sloped watersheds—characterized by poorly draining Vertisol soils and high impervious cover—have increasingly overwhelmed stormwater infrastructure, resulting in frequent flooding and erosion. To address the lack of systematic performance data, this study conducted a systematic performance evaluation of 30 representative stormwater infrastructure units across five spatially delineated blocks within a 30-hectare urban micro-watershed in Addis Ababa, Ethiopia. The objective was to develop an evidence-based framework for prioritizing maintenance and green infrastructure (GI) retrofitting interventions. Six critical performance criteria—flood conveyance capacity, structural integrity, erosion control effectiveness, sediment accumulation, maintenance accessibility, and flood control effectiveness (from hydrologic modeling)—were assessed through structured field inspections and Personal Computer Storm Water Management Model (PCSWMM) simulations. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), integrated with expert-derived weights from the Analytic Hierarchy Process (AHP), was applied to rank the five blocks. A comprehensive sensitivity analysis tested ranking robustness against five alternative weighting scenarios. Results showed that sediment accumulation and flood conveyance capacity emerged as the most influential criteria. Spearman’s rank correlation coefficients exceeded 0.92 in all cases, confirming strong ranking stability. Block 3 achieved the highest performance score (Cᵢ = 0.7), while Block 4 ranked lowest (Cᵢ = 0.43) due to structural deficiencies and sediment buildup. The analysis revealed that 42.3% of the study area is ready for GI retrofitting, while 57.7% requires prioritized maintenance and rehabilitation. The TOPSIS–AHP–PCSWMM framework provided a transparent, evidence-based mechanism for prioritizing interventions, offering practical insights for optimizing stormwater management in Addis Ababa and comparable data-scarce urban environments in the Global South. This work supports the United Nations Sustainable Development Goals (UN-SDGs) 11 (Sustainable Cities), 12 (Responsible Consumption), and 13 (Climate Action).

Visit

figshare.com

Tags

BiotechnologyEcologySociologyScience PolicyEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedtopsis &# 8211systematic performance evaluationstructured field inspectionsspearman &# 8217+45

Licenses

CC BY 4.0

Similar

<p>Fornell-Larcker criterion.</p><p>Sensitivity of cluster analysis.</p><p>SBP sensitivity analyses.</p><p>BMI sensitivity analyses.</p><p>LDL sensitivity analyses.</p><p>HbA1C sensitivity analyses.</p>

<p>Fornell-Larcker criterion.</p>

Understanding the synergy of Artificial Intelligence (AI) literacy among teachers is imperat

<p>Sensitivity of cluster analysis.</p>

Background

Klebsiella pneumoniae is the leading cause of sepsis among neonates

<p>SBP sensitivity analyses.</p>

Cardiometabolic diseases (CMDs) disproportionately affect vulnerable populations wo

<p>BMI sensitivity analyses.</p>

Cardiometabolic diseases (CMDs) disproportionately affect vulnerable populations wo

<p>LDL sensitivity analyses.</p>

Cardiometabolic diseases (CMDs) disproportionately affect vulnerable populations wo

<p>HbA1C sensitivity analyses.</p>

Cardiometabolic diseases (CMDs) disproportionately affect vulnerable populations wo