Epsilon Archive for Student Projects

Abstract

Flooding caused by extreme rainfall events has gained increased attention. To predict the potential extent and risks of such floods, dynamic flood model tools are crucial. However, flood simulation efforts lack standardized data on infiltration rates across different soil and land cover types. This study develops a standardized soil land cover (SLC) infiltration rate table, including both infiltration rate ranges and Manning coefficients. The table was constructed through a comprehensive literature review, analysis of the Soil Water Infiltration Global (SWIG) database, and logical estimations where data gaps existed. The aim of this table is to support urban planners, municipalities, and other hydrological modelers in more realistic flood simulations. The table was applied to a case study in Lomma Municipality (Sweden) using high-resolution GIS data and the dynamic flood model tool in ArcGIS Pro.
Flood simulations were conducted using minimum and maximum infiltration scenarios in a 10-year return rainfall event. Results show significant differences in flood extent depending on infiltration input, especially in flood depths greater than 30cm, where the area experiences ca. 33% less in the maximum infiltration scenario. Notably, SLCs on sandy soils with high infiltration showed substantial flood reduction potential, whereas clay-dominated areas remained flood-prone.
This study demonstrates the crucial role of accurate infiltration data in flood modelling and highlights the benefits of integrating soil and land cover characteristics. The developed SLC infiltration table offers a valuable planning tool for improving flood risk assessments and promoting climate-resilient urban design in Sweden and other regions with similar climate conditions.