Forecasting Floods and their Financial Implications: Iran

Chase Walz
Apr 10, 2019 · 5 min read
Alluvial Fan in Iran. Photo Credit: USGS

Since March 19th, heavy rains and flash floods have inundated Iran. Over 1900 cities, towns, and villages across 25 provinces have been overrun by this historic downpour.

Yet this unfortunate start to the Persian New Year is not ending anytime soon. Media outlets predict more rain and more flooding. In response to these forecasts, tens of thousands of Iranians have been evacuated. Airlifts and emergency shelters will bear the brunt of the relief efforts. Hopefully, the preparations can help stem the tide against this once-in-a-century climate catastrophe.

The 2019 Iran floods strike the Planet OS Data Integration team as a valuable case study in forecasting. The capability to accurately predict and promptly respond to weather events depends on the data and analysis gathered by weather forecasters all over the world. Disaster response and relief depend on two qualities — precision and timeliness — for actionable forecasts.

Precipitation in Tehran, Iran from December 2018-April 2019

Prompt Predictions

The first series of rainfall that made their way through central Iran caught the government’s disaster management systems by surprise. After nearly a year of drought, the downpours brought down over one year’s worth of rain in a couple of hours. Iran’s disaster response systems simply could not mobilize fast enough.

The two satellite images above demonstrate the speed at which the rains transformed Iran’s landscape. The right image (March 29th) was photographed only one week before the image on the left (April 5th). Yet, they could not be more dissimilar. The former photo captures an arid landscape with few pockets of moisture. The latter photo showcases a complete transformation, with significant water run-off flowing through the country and into the sea. The compression of these events into such a short timespan underlies the need for time-sensitive forecasts.

Yet, prompt predictions are worthless without accuracy. Not knowing where or to what extent a weather disaster will strike leaves little room for effective emergency preparations. Below you’ll see a video that shows just how quickly and how heavily the rains poured in over Iran the last two weeks.

Credit: Eneli Toodu

This visualization tracks the level of precipitable water over Iran every six hours from March 24th to April 5th. The graphic utilizes data from the National Centers for Environmental Prediction’s Global Forecast System (GFS). At a base resolution of 18 miles (28 kilometers) between grid points, GFS predicts a multitude of atmospheric variables in stunning detail.

While not a direct measure of rainfall, precipitable water provides a close corollary to the level of precipitation over a given region. In this case, GFS suggests that heavy rain may beset Iran’s southwest provinces of Khuzestan and Lorestan towards the end of March. This forecast largely matched up with the resulting weather pattern. On March 31st, Khuzestan declared a state of emergency after the Karkheh Dam floodgates were opened. On April 1st, Lorestan’s capital, Khorramabad, recorded 106.9 mm of rain and reported five killed in the flooding that ensued.

Precipitation Moving over Khuzestan, Iran from 3/23 to 4/06

Floods and Finance

As the Khuzestan Province is considered the heart of Iran’s oil industry, majors floods like these run the risk of having significant effects on Iran’s national economy. Water penetration of natural gas systems or electrical equipment can cause safety hazards or disrupt utility services. Furthermore, heavy rainfall, water run-off, and flood debris have been known to erode the ground around pipelines, which can lead to deterioration that costs millions in losses and property damage. Flooding may also overload sewers and pipes, consequently affecting the quality of the drinking water and sewage services.

Forecasting the Future

While the occurrence of floods like these are largely out of our control, knowing the forecast ahead of time and making informed decisions on the implementation of infrastructure can reduce the social, economic, and environmental impact of these disastrous events. This insight can include the ability to anticipate when and where certain weather-based challenges may occur so that companies can take preventative and proactive actions.

It has been Planet OS’s mission to connect people and organizations internationally to reliable and comprehensive climate and environmental data. With forecasts and many other datasets easily accessed from a single platform, companies, disaster risk management teams, city planners, and climate scientists can optimize climate derivatives and reduce weather risks. We are excited to provide a platform that enables global communities to utilize vast flows of data to predict environmental risks and prepare for unwieldy climate events.

Data in Your Hands

With this in mind, we have released a new notebook that provides step-by-step instructions on how you can use the Planet OS package API to visualize and analyze a variety of climate variables in Iran. To forecast your own predictions on the rains in Iran or anywhere else in the world, click here.

Github Notebook Tutorial Generated by Eneli Toodu

Many of the datasets made available through the Planet OS Datahub have been at the request of our users. For those who require a consolidated, easy to use, resource for accessing large and complex material that the Datahub does not already offer, please reach out to the team and we will work toward bringing it onboard. If you’d like to be notified when new content becomes available, follow Planet OS on Facebook and Twitter or subscribe to the Planet OS newsletter.

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Provided by Intertrust Technologies

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