Disaster Risk Financing Pakistan
We are enabling frontline humanitarians to access early, predictable funds to protect communities from forecasted heatwaves, flood, and drought hazards
Multi-Hazard Disaster Risk Financing
Disaster Risk Financing (DRF) allows humanitarian organisations to be better prepared in advance of cyclical events by quantifying risks in advance of crises or disasters, pre-positioning funds, and releasing them according to pre-agreed protocols.
Pakistan DRF system is made up of three key pillars:
- Use of science to understand and quantify the risks
- Development of collaborative pre-planned contingency plans
- Pre-positioning when conditions on the parametric model are met
Together, these components ensure funding can be efficiently channeled to frontline responders before a crisis turns into a disaster.
Contingency planning is central to a DRF system. Contingency plans tend to be developed at a sub-national level: either at district or livelihood-zone level, whichever delineation is appropriate to the context. The process uses participatory and inclusive approaches, working with people at risk and local groups and organisations to design and validate planned actions, and in some places, to enable local groups to have ownership of plan implementation. Contingency plans usually reflect three severity scenarios (mild, moderate, and severe at a minimum) including costs, and may also cover one or more windows of action such as preparedness, mitigation, and anticipatory response. Another crucial component of DRF is the preposition of financing - financing is realised when the agreed thresholds on the parametric model have been reached according to predefined operational protocols.
Through DRF program’s funding mechanism funds are released for anticipatory response, preparedness, and risk reduction based on information from scientific hazard prediction models and predetermined triggers.
In Pakistan, the foundations of the DRF system are built on a robust governance structure – often it is referred to as the ‘fourth pillar’ of the system and is a central part in enabling decision making to be led locally.
In creating the enabling environment for locally led decision making, a National Steering Committee (NSC) and three hazard-specific Technical Working Groups (TWGs) have been established. The National Steering Committee (NSC) is the highest decision-making body consisting of a Chair and representative Start Network members in Pakistan including 3 INGOs and 2 National Start Network member NGOs. The NSC includes representatives of three major influencing national humanitarian and development networks/consortiums i.e., National Humanitarian Network (NHN), Pakistan Humanitarian Forum (PHF), and Indus Consortium. Moreover, to support the programmes coordination and partnership with government agencies, a dedicated focal point has been officially appointed by the National Disaster Management Authority, NDMA Pakistan.
The governance structure is as under:
Thanks to funding provided by the UK's Foreign Commonwealth and Development Office (FCDO) and the Government of the Netherlands, Start Network is able pilot the first multi-hazard DRF system until the end of 2021 for the following three hazards.
These efforts to establish a DRF system in Pakistan are part of the wider efforts between Start Network members and the National Disaster Management Authority - NDMA, who have been working together since 2017 to unlock new forms of funding mechanisms to enable effective humanitarian assistance.
The overall aim is to build resilience to droughts in Pakistan. Most drought monitoring programmes in Pakistan focus on the summer monsoon and the availability of surface and sub-surface water. The secondary winter growing season is, however, also of economic and agricultural importance. Therefore the vulnerability of the communities to winter crop and pasture failures motivated Start Network to implement an agricultural drought DRF initiative for the Punjab and Sindh provinces.
Since March 2020, Start Network has been working with the University of Reading (UoR), to implement a drought Disaster Risk Financing (DRF) system for the Punjab and Sindh provinces, especially focusing on the winter growing season. Specifically, developing an anticipatory, operational drought model (based on the TAMSAT-ALERT system to predict NDVI), to trigger funds for early action intervention.
These effort plays a key role in the Start Network’s mission to protect some of the most vulnerable rural communities in Pakistan against the devastating impacts of drought due to crop failure
The University of Reading
Malick Shahbaz and Syed Sulaiman, The Drought Technical Working Group
Jeremy Benn Associates (JBA) was appointed to build the flood model in Pakistan.
JBA was selected to provide scientific modelling expertise to develop a real-time and forecast flood model for the Indus River basin. The goal was to develop a fully-automated early warning system, which provides daily forecast of flood conditions on which a series of anticipatory actions can be devised to reduce overall humanitarian impact.
Using the Copernicus Global Flood Awareness System (GloFAS) with JBAs Flood Foresight technology the model outputs daily probabilistic forecasts of flood inundation extents and depths. From these digital maps the model can estimate the population at risk in the short, medium and long-term. The model quantifies the flood risk to the population through a traditional probabilistic catastrophe risk model. See feature article here.
The model runs for the whole of the Indus Basin, outlined in the map above. The percentage of Pakistan within the Indus River basin is approximately 58%; it includes 132 districts but does not include all of the area of each district. For example, the district of Karachi is included in the Indus Basin but the city of Karachi is not. To see a detailed map of which districts fall within the Indus Basin please see Flood Technical Report (appendix A).
JBA will host, maintain, and support the system for an initial period covering the 2020 and 2021 monsoon seasons. Ownership long term to be at country level.
Jeremy Benn Associates (JBA)
Mr. Liaqat, The Flood Technical Working Group
Important note: the aim is not to replace what has been done at the national level, but rather to build on the metrics that have already been monitored and produced within the agencies in Pakistan. By building on the information already used, and is available, we can produce a model that is objectively actionable, for risk management and used by members. This provides a quantitative, probabilistic, and granular output, of the sort that is required for rapid release of pre-positioned funds via the DRF.
The overall aim is to build resilience to heatwaves in Pakistan. Heatwave conditions are the major cause of weather-related casualties in Pakistan. Heatwave is defined as the number of days when, for some consecutive days, the temperature is greater than a certain threshold, keeping in view the climatology of the station.
Extreme heat can lead to dangerous, even deadly, health consequences, including heat stress and heatstroke. Climate change drives temperatures higher, increasing the frequency and severity of heatwaves. The anticipated rise in temperatures and frequency of heatwaves in Pakistan highlights the need for inter-agency coordination to mitigate the impact of these disastrous events in the future.
This has motivated Start Network to implement a Disaster Risk Financing at several urban locations in Pakistan.
During the hottest months, Start Network implements its heatwave Disaster Risk Financing system for several urban locations in Pakistan (Larkana, Karachi City, Multan, Sibi, Jacobabad, and Nawabshah). Specifically, an anticipatory, operational heatwave model (based on the NOAA GFS model to calculate heat index values) is used to trigger funds for early action intervention.
This effort plays a key role in the Start Network’s mission to protect some of the most vulnerable in Pakistan against the devastating impacts of heatwaves.
Dr Erica Thompson (LSE)
Dr Maidment (University of Reading)
Jennifer Ankrom and Sumera Javeed, The Heatwave Technical Working Group
DRF in action
On the 20th May, the forecast predicted the maximum and minimum temperatures to exceed the model’s threshold settings at Port Qasim, Karachi. A 2-day heatwave event on the 26th-27th of May was therefore triggered. As per the pre-agreed protocols, this triggered the release of £36,000 to Action Against Hunger (ACF) and HANDS who had been pre-selected to roll out preventative, mitigating, and response activities in the Karachi area (The heatwave DRF project is hosted by Welthungerhilfe in Pakistan).
The model forecasted a heatwave event with a 6-day lead time predicting a maximum temperature of 45.3°C and a minimum of 31.4°C for the 26th of May. However, the maximum and minimum temperatures decreased by 5.6°C and 3.3°C respectively on the observed day.
Because the observed temperatures dipped below the pre-agreed threshold values (which triggers a heatwave event in Karachi) this event can be termed a false positive. A false positive event – in this context – is when the model predicts a 2-day heatwave event, but on the observed day (i.e. day 0) the event does not occur. As a result, HANDS did a long-term operation to prevent harm and damage from the subsequent heatwaves that might hit that season.
Find out more about the event here: 2020 HEATWAVE EVENT
In this first year of operation, many lessons have been learned, this includes the humanitarian impact of extreme heat in low-income countries with limited access to quality healthcare and informal dwellings which can trap heat. The KAP survey report developed in collaboration between Start Network, HANDS Pakistan, and Welthungerhilfe analyses the knowledge, attitude, and practice of Karachi residents in relation to managing extreme heat. Conducted in 2020 following a messaging campaign led by HANDS related to extreme heat. The project was triggered through a disaster risk financing approach, using a heatwave model to trigger funding automatically when extreme heat was forecast.