Changes in land use cover and its effects on hydrometeorological risk in Tuxtla Gutiérrez (Mexico)

• Published in: IOP conference series. Earth and environmental science Vol. 392; no. 1; pp. 12045 - 12056
• Main Authors: Silva, M, García, A, Hernando, A, Manzanera, A, Aguilar, M, Guichard, D
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.11.2019
• Subjects: Coverage; Flood levels; Floods; Hydrometeorology; Land cover; Land use; Landsat; Landsat satellites; Maximum probable flood; Overflow; Pasture; Rainfall; Remote sensing; Risk; River basins; Rivers; Runoff; Satellite imagery; Satellites; Simulation; Soil water; Soils; Two dimensional analysis; Two dimensional models; Urban development; Urban sprawl; Warning systems; Water depth; Mexico
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/392/1/012045

To better understand the space-time dynamics and the effect of urban growth on the transformation of territory, this article presents the results of Iber 2D simulation tests to analyze flood events in the lower Sabinal river basin, Tuxtla Gutiérrez, Chiapas, Mexico. First, Landsat 5 and Landsat 8 satellite images from 1986 and 2014 years were processed to generate classified images of the land cover of the study area. From the identified coverages, the soil roughness values were defined, as well as the infiltration parameter of water in the soil. Both values were used as input data in an Iber 2D simulation model to analyze and compare the maximum flood level with different precipitation values in the two reference years. Between 1986 and 2014, the coverage of urbanizations increased considerably, while the coverage of trees, pastures and agriculture decreased. Due to this change in coverages, in 2014 rainfall caused higher values of direct runoff, increasing water heights levels and therefore the risk of overflowing the Sabinal River. With the model shown here, it is possible to calculate the depth and water heights reached and identify the points and moments of overflow of the river. This model can be used to provide feedback to flood risk warning systems and to analyze basins that lack monitoring infrastructure.