Technology is the Frontline of Managing Climate Disasters

Technology Policy Tech for Development Net Zero

Technology is the Frontline of Managing Climate Disasters

Commentary
Posted on: 14th December 2021
Sabahat Iqbal
Policy Lead, Tech for Development Policy Unit

Sub-Saharan countries have been facing climate change related headwinds for decades resulting in loss of life and property: The Gambia just experienced devastating windstorms, Somalia tops the list of fatalities due to droughts and Mozambique is close behind as a result of cyclones. Events like these, which are occurring with increasing frequency, highlight the greater burden developing countries face from human-induced climate change in the immediate- and short-terms.

The 21st century has brought advancements in technology that can help mitigate these burdens, and it is imperative governments enlist the life-changing power of these technological tools. However, many governments have limited knowledge about which technologies should be used and when, so…  

…what kinds of technology can policymakers use to help minimize the impact of these climate disasters?

Predicting, even mere hours ahead, when a climate shock will take place, where they will occur and who will be affected is fundamental to providing early warning and enabling early action, which saves lives and livelihoods and reduces the cost and time of response efforts. To make these kinds of predictions, it is necessary to collect data on weather related indicators; this data collection is directly facilitated by 21st century technologies. For example, advanced sensors in satellites, airplanes, drones, automated weather stations, and Internet of Things are some of the digital tools facilitating data collection. They minimize the need for human intervention, making the data easier and cheaper to collect and enabling more data observations to be taken over a longer period.

The type of data available to policymakers has also expanded dramatically thanks to broader tech adoption by the general population. For example, mobile phones hold data useful for identifying low-income people and their locations. Supplementing weather-related data with such non-traditional data can result in more useful predictions: instead of predicting where and when extreme rainfall might occur, for example, authorities can predict how many low-income people would be impacted by potential landslides triggered by excess rainfall.

Technology also facilitates the analysis and interpretation of data, which is essential for policymakers to turn data into signals and then into action. Advances in data storage and computing capacities have led to faster analysis of ever larger and diverse data sets. Traditional statistical methods supplemented with artificial intelligence, machine learning, and deep learning methods uncover previously undetectable patterns, providing policymakers more quickly with accurate and detailed risk information that can be used to determine appropriate action.

As with collecting and analysing data, technology is fundamental to automatically triggering appropriate, pre-negotiated actions. Communication channels that range from mass media (TV, radio, social media) to more targeted channels (such as mobile phones) are essential to providing local authorities and vulnerable communities with information on how to minimise damage. Digital financial products and services facilitate faster, better, cheaper methods of cash payments, which when deployed ahead of a disaster can have an outsize effect on mitigating the worst impacts, and digital IDs facilitate rapid identification and verification of beneficiaries.

Technology also plays an important role in supporting rapid response efforts once a climate-linked disaster does occur. For example, digital data from mobile phones can help track populations on the move; knowing where vulnerable populations are heading can ensure that hygiene and shelter resources are deployed to the correct locations. Blockchain is emerging as a decentralized tool for inventory and supply chain management across disaster response organizations. Aerial technology, such as drones, can be deployed more quickly than emergency responders for situational awareness. Robots can navigate unfriendly environments such as precarious buildings to locate survivors.  

What is needed for policymakers to build these tech-enabled approaches?

The breadth and depth of data required for tech-enabled disaster risk management systems and the potential for misuse means that governments must take charge of data collection and sharing efforts. First, governments must map out their data requirements and how data can be obtained. The result should be a roadmap that articulates a clear digital data pipeline from collection to analysis to recommendations for action. In addition, governments must institute best data-sharing practices for their own data as well as that of other organizations, such as mobile network operators. Implementing such a framework ahead of time reduces ambiguity for both owners and users of the data.

Beyond data management, governments should promote a tech-enabled disaster risk management ecosystem built on standards that encourage collaboration and integration of digital products and services. The disaster preparedness and response delivery chain is a tightly linked series of steps. Tech-enabled solutions in any phase should be able to link digitally to other complementary solutions along the delivery chain. Tech-enabled solutions must also align with the governance structures of existing national disaster management plans. For example, if a decision-making process relies on inputs from various government departments, a tech-enabled solution should be designed to automatically facilitate those interactions. Finally, governments should encourage solutions that are user-centred and problem-driven. If, for example, most members of a vulnerable community only have a basic phone, a smartphone-based app is redundant, and worse, may sow distrust in the community it was meant to serve.

Tech-enabled solutions can trigger a virtuous cycle for the most vulnerable populations. Solutions that are built on a foundation of responsible data management, openness, effective integration, and user-centeredness, will be more impactful and reinforce the donor and business case for greater investment in tech-enabled solutions which in turn leads to greater impact.

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