article Pakistan Flood 2022

Floods are the most frequent type of natural disaster, causing widespread devastation, resulting in loss of life, damage to personal property and critical public health infrastructure. Flood risk management poses a multitude of challenges that require careful consideration and strategic planning. One significant challenge is the dynamic nature of weather patterns and climate change. With the increasing frequency and intensity of extreme weather events, such as heavy rainfall and storms, predicting and mitigating flood risks becomes more complex. Climate change exacerbates the unpredictability of precipitation patterns, making it challenging to develop accurate flood models and anticipate potential threats to vulnerable areas.

The effective execution of disaster response initiatives necessitates the analysis of a broad spectrum of data, encompassing sociographic details about human settlements and physical parameters like rain intensity. Additionally, predictive models play a crucial role in anticipating the potential inundation of land. By adopting this multifaceted approach to flood risk mapping, it becomes possible to engage in efficient planning for mitigating measures, including the development of targeted evacuation plans.

The Destination Earth Data Lake (DEDL) combines disparate data sources in one large virtual database. Moreover, this virtual database comes with a set of tools that facilitates the search for relevant resources as well as the analysis of data by performing computationally expensive operations close to the data source. These tools are used to showcase the following “what-if” scenario:

“A disaster management expert is called to assess what the flood risk of the Indus River plain is if heavy rainfall continues in the next days. The expert wants to make use of the DestinE Data Lake services Discovery and Data Access as well as the Stack Service for big data processing to deduce information about areas under risk to trigger mitigation actions. Analyzing data from several resources provided via DestinE Data Lake, such as data of human settlements as well as rainfall data, is used to generate maps for flood risk mapping. This ensures efficient planning of mitigating measures, such as targeted evacuation plans.”

This dedicated use case serves as an example of how the service provided by DestinE Data Lake could have helped with a disaster response assessment during the 2022 Pakistan flood.

Data Sources used:

In this use case, data is retrieved from the EU-funded Copernicus Emergency Management Service ( CEMS ), the European Centre for Medium-Range Weather Forecasts ( ECMWF ), the Copernicus Digital Elevation Model ( COP-DEM )) and the Global Human Settlement ( GHS ) layer.

• The CEMS catalogue is used to obtain Global Flood Monitoring (GFM) data. The GFM data product is a worldwide flood monitoring system which consists of microwave imaging data and is acquired by EU’s Copernicus Sentinel-1 satellites. Microwave imaging is a technique that is relatively unaffected by cloud cover and is especially sensitive to variations in near surface water content. This type of data has been successively employed to monitor flooding. The binary data consists of daily measurement with a 20m by 20m spatial resolution which indicate whether a pixel has been flooded or not.
• The ECMWF catalogue is used to obtain the multi-decadal ERA5-Land dataset. This product is a reanalysis dataset that gives insight in the seasonal variation of land variables by averaging data over multiple decades with a 9 km spatial resolution. The ERA5-Land data is retrieved to estimate the risk of further flooding for next several days by aggregating precipitation on a 20m by 20m spatial grid. This dataset is for demonstration purposes only, and will be replaced with a high resolution rainfall prediction dataset in the future.
• The Copernicus DEM data is used highlight the low-lying areas around the Indus river under the highest risk of flooding. This product consists of radar data acquired during the TanDEM-X mission between 2011 and 2015.
• The Global Human Settelment (GHS) layer is used to make a risk assessment for flooding of regional settlements. THE GHS-BUILT-S data provides a yearly measure of built-up surfaces on a 10m by 10m spatial grid. The product is a composite dataset consisting of Landsat (MSS, TM, ETM sensor) and Sentinel-2 imaging and represents the square meters of built-up surface in a cell.

Enhanced flood risk management in general can have far-reaching positive impacts on both communities and ecosystems. By employing advanced technology, predictive modeling, and comprehensive planning, the potential devastation caused by floods can be significantly mitigated. Efficient flood risk management enables timely and targeted response measures, reducing the risk of loss of life, property damage, and disruption of essential services. Furthermore, enhanced flood risk management strategies contribute to the overall resilience of communities, fostering a better-prepared and adaptive populace.

Beyond the immediate human impact, improved flood risk management can also benefit ecosystems and natural habitats. Sustainable management practices can help preserve wetlands and natural drainage systems, mitigating the adverse effects of urbanization on water absorption and runoff. Additionally, the conservation of natural landscapes plays a crucial role in maintaining biodiversity and ecosystem health. Overall, an enhanced approach to flood risk management not only safeguards human lives and property but also promotes the long-term sustainability and resilience of both urban and natural environments.