Elsevier

Ecological Informatics

Volume 71, November 2022, 101777
Ecological Informatics

Modelling and evaluation of land use changes through satellite images in a multifunctional catchment: Social, economic and environmental implications

https://doi.org/10.1016/j.ecoinf.2022.101777Get rights and content
Under a Creative Commons license
open access

Highlights

  • Random Forest provided a classification accuracy of 83.18%

  • The NBS method used mitigates flood hazard in all three simulations

  • Environmental and social benefits exceed costs in all three simulations

  • Tools and the use of NBS used enhance the achievement of several SDGs

  • The use of NBS is more optimal upstream than downstream

Abstract

Floods are recurrent phenomena with significant environmental and socio-economic impacts. The risk of flooding increases when land use changes. The objective of this research is to detect land cover changes via Sentinel-2 images in the Umia Basin (Galicia, NW Spain) in 2016–2021 and to analyse the associated flood risk. This study focuses on how forest use and nature-based solutions (NBS) can reduce the risk and hazard of flooding in cities and crops in the high-risk area. A flood simulation was performed with the land use obtained from Sentinel-2 (Observed) and three more simulations were performed changing the location of afforestation and NBS, i.e. “S-Upstream”, “S-Downstream” and “S-Total”. Finally, the environmental, economic and social impacts of the scenarios designed and estimated are analysed and discussed. Land cover change was successfully monitored with Sentinel-2 imagery. The catchment area showed noteworthy changes in land use, most notably for the category of trees, which covered 6700 ha in 2016 and 10,911 ha in 2021. However riparian vegetation decreased by almost 11%. For the flood hazard simulations, an average reduction in peak discharge was obtained for all three scenarios (9.3% for S-Up; 8.6% for S-Down and 13% for S-Total). From the economic perspective, all three scenarios show a positive net present value for the period studied. However, S-Down is the scenario with the lowest benefits (€15,476,487), while S-Up and S-Total show better values at €29,580,643 and €65,158,130 respectively. However, investment cost is much higher for the S-Total scenario, and upstream actions affect the whole catchment, so S-Up is the best decision. This study concludes that the information provided by satellites is a large-scale analysis tool for small heterogeneous plots that facilitates the comprehensive analysis of a territory. This information can be incorporated into flood analysis models, facilitating simulation through the use of NBS. It has been proven that the use of reforestation upstream only is almost as beneficial as reforestation in the entire catchment and is economically more viable. This confirms that the methodology used reduces flood hazard, despite the territorial complexity, facilitating decision making on the use of NBS.

Keywords

Nature-based solutions
Flood hazard management
Water Governance
Land-use change, Random Forest, HEC-HMS, Sentinel-2

Abbreviations

NBS
Nature-based solutions
LULC
Land use and land cover
HEC-HMS
Hydrologic Modelling System
RS
remote sensing
GIS
geographic information system
L1C
Level 1C
TOA
Top of atmosphere
L2A
Level 2A
BOA
Bottom of the atmosphere
DOS
Dark Object Subtraction
RF
Random Forest
PNOA
National Aerial Orthophotography Plan
SCS
Soil Conservation Service
CN
Curve Number
CBA
Cost-benefit analysis

Data availability

Data will be made available on request.

Cited by (0)