Every year, monsoon storms bring flash floods that sweep across Thailand's northern mountains at the border with Myanmar. As mountain streams in the Sai-Ruak River basin overflow, the fast-moving waters wash logs and rocks downstream and trigger mudslides on water-saturated hillsides. The flash flooding leads to deaths and destruction of property and livelihoods, as homes, roads and communications can be decimated.
Need for better flood warnings
An existing early warning system built to give people in the region a chance to escape and protect their property has proven inadequate. In November 2021, in one of the worst flash floods in this area, the sirens came too late. Several days of torrential rain raised the river level, and the severity and suddenness of the flood waters was too much for the early warning system. The flooding in the downtown Mae Sai district alone destroyed houses and the town's principal market, causing damage costing around half a million US dollars.
An assessment SEI developed in collaboration with researchers at Mae Fah Luang University eventually led to an improvement in predictions for the region. The early warning sirens are now complemented by an app, developed with SEI researchers' input. But this is just the beginning of what can be done to address flood risk in the region.
Modelling and decision-support fill gaps
A lack of meteorological observation networks in the mountainous Sai-Ruak River Basin, in particular for Mae Sai municipality, means that the municipality has been unable to provide effective flood prevention and response ahead of flood events. And in general, state agencies have not had enough information to provide timely warnings for the many communities in the region. Sparse data is also a major challenge for early warning systems for the upstream part of the basin, which lies across the border in Myanmar.
In the 2021 disaster, the Thai Meteorological Department, one of the key government agencies in Thailand linked to disaster prevention and response, could only share generic rainfall information through their website and social media platforms for the 240-km radius covered by the radar station. Another agency, the Department of Water Resources, monitors river levels. However, the agency has no modelling or decision support system to simulate water levels in the Sai-Ruak River.
SEI researchers provided exactly that capacity in a project led by researchers at Mae Fah Luang University, with the Thai Office of National Water Resources. The result was the State of the Sai-Ruak River 2022, a report that provides baseline information on water resources, the socio-economic context, and transboundary cooperation in the region. Based on the assessment, the SEI team helped Mae Sai municipality identify five locations for installing new hydro-met stations in the basin.
"SEI's flooding model simulated the river's flow across the mountain to better plan for the flow of flood waters across the Mae Sai district. This [could] help us identify the locations across the basin to install new hydro-met stations to monitor rainfall and water levels," said Chaiyon Srisamut, Mayor of Mae Sai district. The mayor also emphasized that a better understanding of flood patterns can help prevent flood risk, and that cooperation between agencies on both sides of the Thailand-Myanmar border is vital to effectively manage flood risk.
In 2023, Srisamut could also share the assessment's findings with the Thai-Myanmar Township Border Committee (TBC), a transborder NGO in which the municipality office of Mae Sai district participates.
App provides better warnings for flash floods and drought
The next step was to take the river basin assessment and provide better warnings for flash flooding. SEI researchers provided input for the development of a local app that can provide both flood and drought warnings for the region, created by researchers from the Mae Fah Luang University. The smartphone app, named Usurapong and available on Google Play, displays information on location-specific weather and water levels with related advisory information from government agencies and news media. The app gives information in both Thai and Myanmar languages, currently based on data from Thailand.
Since its launch in May 2022, the app has had more than 1000 downloads. SEI team member Uttam Ghimire said that "early warning is one of four main ways to improve responses to floods", in addition to improving the accuracy of warnings and educating people about preparedness ahead of disasters.
Working for future resilience
While the damage from flash floods can be reduced using the app and early warning systems, other supporting measures are needed. SEI researchers have provided hydrological models for decision support systems for water management, and this has become a catalyst for increased public participation in official water and flood management plans. Next, the team plans to do land-use change scenarios in relation to climate change predictions, to strengthen communities' resilience to flooding in the future.
Thanapon Piman, SEI Senior Researcher, said: "Flood risk management in this transboundary basin has many challenges, including coordination across many agencies and actors both in Thailand and Myanmar. We have been providing scientific information that is accessible and useful for the agencies and communities. We are working with local policymakers to ensure our science can support them in doing better water management in the Sai-Ruak basin."