Regarding Dataset prepartion for Kelaniya River Basin, Sri Lanka

[Hrekhani97]

Hello,

I am Madhawa, a student from Sri Lanka. I am planning to use the LISFLOOD model for my research on the Kelaniya River Basin in Sri Lanka. I have successfully installed the model and run the test cases. Currently, I am working on creating a custom dataset for the Kelaniya River Basin. I’ve already developed general maps and topography maps, except for the elvstd.map, and have created land use fraction maps based on local land use data.

I am facing a few challenges and would appreciate your guidance on the following issues:

I used the MERIT DEM to create all the general and topography maps and plan to run the model at a 1 km x 1 km spatial resolution. Could you please advise on how to create the elvstd.map file using PCRaster within QGIS? Do I have to calculate the elevation standard deviation for the original Merit DEM file and resample that to my target resolution?

For the land use fraction maps, I relied on a local land use survey to obtain accurate data. Could you explain the process for calculating land-use-dependent layers, such as the crop coefficient and crop group number? The methodology on the website involves a large number of land use classes, whereas my dataset for the Kelaniya Basin uses a simplified local classification. How should I proceed to develop these two layers in this context?

Thank you very much for your time and assistance. Your support would be greatly appreciated.

Best regards

[StefaniaGrimaldi]

Dear @Hrekhani97,

we are pleased to know that you plan to use OS LISFLOOD in the frame of your research study.

Please find in this page the protocol for the computation of the elvstd map: https://ec-jrc.github.io/lisflood-code/4_Static-Maps_topography/ . The elevation field at the target resolution (1 km) is obtained by computing the average of the original high resolution map (mean.unweighted()). elvstd is the standard deviation of the elevation of all the high resolution cells included into one grid of your target grid (stDev.unweighted()). To achieve this aim, you can use the software and protocol of your choice.

In each pixel, the sum of all land use fractions must be 1. This is a strict requirement to ensure mass balance and correct computations. This page https://ec-jrc.github.io/lisflood-code/4_Static-Maps_land-use-depending/ explains how the classes included in the "Copernicus Global Land Cover Layers: CGLS-LC100 collection 2" were associated to the land cover fractions. When using the local classification available for your study area, you can allocate each class of your database to the most representative land cover fraction (forest, irrigation, other).

As a general piece of advice, we strongly recommend using netcdf format, rather than pcraster format (for example, the netcdf format allows you to define pivotal metadata information such as the geographical reference system).

I hope that this answer was helpful.
Please let me know if I missed or misunderstood parts of your inquiry.
Kind regards,
Stefania