Bottom-Up Adaptive Decision-Support for Resilient Urban Water Security: Lusaka Case Study

Submitted by Meadow Poplawsky | published 31st Oct 2021 | last updated 20th Apr 2022
pools of water in a water treatment plant with a blue sky

Iolanda Water Treatment Works, Lusaka, Zambia. Credits: FRACTAL

Introduction

This article explores knowledge and decision-making for urban water resilience in the context of climate change through a case study of Lusaka. The aim of the research is to improve urban water decision-making under uncertainty at a city scale, through a case study of the city of Lusaka in Zambia. Lusaka is a co-dependent city of the Kafue River Basin. The study took a city-centric approach to adaptive decision-support, to better inform African city water systems’ resilience to climate and socio-economic changes. The goals of the research are therefore to:

  • Explore an African city-centric water system and the climate sensitivities of the system.
  • Quantify the vulnerabilities of African urban water security and its dependent sectors, due to external stressors. 
  • Inform short to medium term decision-making using Decision-Scaling (DS) as an adaptation framework for decision support, by evaluating system vulnerabilities. 

This article is part of the FRACTAL project, a 4-year project coordinated by the Climate System Analysis Group (CSAG) at the University of Cape Town, with an 18 month costed extension (until March 2021) to explore the sustainability and scalability of knowledge co-production processes to strengthen urban climate resilience in Africa.

*This weADAPT article is an abridged version of the original text, which can be downloaded from the right-hand column. Please access the original text for more detail, research purposes, full references, or to quote text. 

Methodology: Bottom Up Decision Scaling

Urban water resilience was explored using a bottom-up adaptation approach focussed on decision support. Resilience was explored in three ways:

  • resilience that relates to socio-economic stressors (this includes institutional structures);
  • external hazard resilience (this includes the patterns and extents of climate change related impacts); and
  • socio-ecological resilience (this includes resource extraction by water service providers) 

Decision-Scaling (DS) was the approach used to analyse which decision options are resilient to a range of futures. Decision-Scaling was chosen from several other methods of decision-making used in the FRACTAL project.  

Decision scaling:

  • is designed to engage with stakeholders and give guidance to decision makers to manage risk. This helps to inform acceptable stakeholder-defined objectives and thresholds. 
  • can rely on a wide range of sources for testing the hydrologic variations, thus including socio-economic changes, historical and modelled information and moving away from downscaled projections.
  • helps in identifying vulnerabilities early in the decision-making process, allowing for potential system trade-offs to be identified and addressed early on

The approach connected the bottom-up process of co-exploration with the top-down process of incorporating climate and socio-economic information to investigate the risks for water supply to the City of Lusaka. Information on critical water security issues were explored during a series of City Learning Labs held with key city stakeholders. The results from these Learning Labs were analysed using both a city-centric water resources model for the city of Lusaka as well as a larger city regional model of the Kafue Basin to include the risks to other water dependent sectors. 

Location of the Study Area: The focus city for this research was the city of Lusaka, Zambia. The aim was to investigate adaptation decision-support using co-exploration and a city-centric regional water system within the Kafue River Basin. The study area is downstream of Itezhi-Tezhi reservoir until, and including, Kafue Gorge Upper Reservoir and hydropower plant. The area includes the Kafue flats and the city of Lusaka.

Water Supply for the City of Lusaka: The Lusaka Water and Sewerage Company (LWSC) manages the formal water supply to the city of Lusaka. The formal water supply is from the Kafue River and the Lusaka groundwater aquifer, and is treated at the Iolanda water treatment works. Demand currently exceeds supply. Lusaka has a high amount of non-revenue water lost from the supply system due to leakages or inadequate licensing; majority of which occur in the Kafue pipeline. These losses result in loss in revenue and increased demand numbers. These losses need to be minimized before future demand can be apportioned. As a result, one of the greatest challenges to establishing resilient water security is an infrastructure capacity constraint, as opposed to a resource constraint.

The Kafue River, an important source of water for Lusaka
The Kafue River, an important source of water for Lusaka

Four Stages of the Decision Scaling Approach

  1. Identifying key climate risks and defining acceptable performance metrics
    1. Learning Labs were used to identify stakeholder preferences
  2. Developing a systems model
    1. The Water Evaluation and Planning Tool (WEAP) was chosen as the primary tool to model potential changing responses of the water system to climate change effects in the city of Lusaka. WEAP is an integrated water resources planning tool used to represent current conditions in a specified area. WEAP has been used previously for modelling the climate change risks for the Zambezi basin (Cervigni et al., 2015). 
    2. Two WEAP models were developed. The first was a simple model of just the water supply system to Lusaka integrating both surface and groundwater supply options. The second was an expanded city-region water resources model that also included critical parts of the Kafue River basin that impact on both water and energy availability for Lusaka.
  3. Conducting a vulnerability analysis
    1. This step tested the sensitivity of the system to identified critical climate and non-climate stressors and determined the vulnerability of the systems in terms of the critical performance metrics.
    2. The WEAP model was repeatedly run, for multiple climate and socio-economic changes, these potential changes were named as system stressors. The risks associated with the supply included climate changes. These changes may be based on: changes in precipitation quantity, timing or intensity; increasing temperatures or increased evaporation; environmental degradations or upgrades; or a change in the manner in which the water resources are distributed (Ray and Brown, 2015). 
  4. System evaluation
    1. The framework identified potential stressors that could result in risk and then identifies the likelihood of said climate changes using projections. The water supply stress test is based on system performance metric “breaking points”. This system evaluation helps to identify the “safe space” where decisions can be made. 

  5. Water kiosk in Kanyama peri-urban area. Credits: FRACTAL project.

     

Results: Burning Issues and Risk Analysis

City Learning Labs

The study determined that the city learning labs facilitated interaction between researchers, civilians, city officials, and university partners. This allowed stakeholders to determine burning issues and potential solutions for better management and less climate vulnerability. Stakeholders provided feedback on the initial city water model which had been developed, and identified burning issues as water supply, groundwater pollution, groundwater levels and flooding. These issues were divided into theme groups which allowed focused recommendations to be made. These burning issues gave insight into metrics to evaluate the key sectors of water, energy, and food. These metrics were domestic water demand being met, irrigation water demand being met, and hydropower generation and reliability. This community-sourced knowledge covered a data gap and provided invaluable feedback on the assumptions made by the initial models. It also allowed stakeholders to have ownership over policy decisions. 

Decision-Scaling Risk Analysis

The city-scale risk map looked at the 2017, 2020 and 2035 total domestic water demand met and showed that water system had no direct climate vulnerability. Vulnerabilities came from the socio-economic stressors and city-scale management actions. However, the analysis showed that the city-scale water system is currently vulnerable and unable to satisfy demands and create a system with low risk. This was supported by discussions from the labs. Lusaka's groundwater supply was also shown to be vulnerable to the climate. 

The use of both the city-scale and the city-regional model proved important, as the 2035 baseline development scenario demand met indicator showed the city to have a low risk (86% score), but the city-regional model showed this indicator to be at medium risk (79%). Increase in precipitation was found to be the stressor making the system most vulnerable. Hydropower showed a medium to high risk. Irrigation scenarios showed a deficit in supply. 

 

Lessons Learnt

There were several key takeaways from the study: 

  • The DS system was effective in bringing about stakeholder collaboration and a better understanding of challenges, trade-offs, and opportunities of good water governance. 
  • The risks of water resources not being adequately managed in the face of climate changes are shared between the sectors.
  • Lusaka was more vulnerable to socio-economic changes (population growth and management of non-revenue water) than climate changes, while the city-regional water system of Lusaka and the Kafue Flats had vulnerabilities to both changes.
  • Variations in precipitation would have the largest impact on Lusaka's groundwater.
  • As Lusaka does not have direct climate variability, they are able to prioritize socioeconomic stressors. 
  • If water supply is prioritized in management, there is not a direct climate risk. However, this puts hydropower sources at risk. Alternative energy supplies may be developed to address this. However, having power to pump water to Lusaka is critical. 
  • Agriculture offers potential for economic growth, but at a trade-off of increased water allocation for irrigation. 

Conclusions

This article addressed water security for sustaining urban livelihoods; adaptation in decision-making and decision-support; and resilient city-centric water systems in Lusaka, Zambia. Bottom-up, adaptive decision support was valuable in addressing potential vulnerabilities and solutions for decision-making for water security. The study was able to identify vulnerabilities and understand complexities, co-dependencies and trade-offs, at a city-scale and a city-regional scale. The city-centric model of Lusaka showed vulnerability to socio-economic changes, while the city-regional model showed vulnerability to both socio-economic and climate changes. These models were co-dependent. Bottom-up decision making methods require local knowledge and innovation, but are very useful for water-security decision making. Overall, the article proposed an innovative new method of decision making and tested it out on Lusaka, providing insight into how Decision Scaling can be used to assess climate vulnerabilities for other urban water systems.