ICG2022-579
https://doi.org/10.5194/icg2022-579
10th International Conference on Geomorphology
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Monitoring channel response and recovery of ephemeral Mediterranean streams using diachronic orthophotography analysis with machine learning (Rambla de Cervera, Spain)

Maria Pilar Rabanaque1, Vanesa Martínez-Fernández1, Mikel Calle2, Carles Sanchis-Ibor3, Francisca Segura-Beltrán4, Yolanda Sánchez-Moya5, and Gerardo Benito1
Maria Pilar Rabanaque et al.
  • 1National Museum of Natural Sciences (MNCN) - CSIC, Department of Geology, Spain (m.rabanaque@mncn.csic.es)
  • 2Department of Geography and Geology, University of Turku, Turku, Finland
  • 3Universitat Politècnica de València, Valencian Center for Irrigation Studies, Valencia, Spain
  • 4Department of Geography, Universitat de València, Valencia, Spain
  • 5Department of Geodynamics, Statigraphy and Paleontology. Faculty of Geology. Universidad Complutense de Madrid, Spain

Since the 70s, Mediterranean ephemeral rivers in Spain have been subject to large-scale in-stream gravel mining. In the 90s, this activity ceased to a large extent, although nowadays new controlled in-stream gravel extraction pits have continued. The decreased on gravel mining activity, together with the longitudinal transport of sediment generated by flooding, has allowed these streams to begin to recover their alluvial landforms although their development and continuity is controlled by channel entrenchment and limited by sediment supply.

This study aims to quantify the spatial-temporal changes generated along the river in order to characterise the transmission of sediment longitudinally.  For this purpose, remote sensing methods offer efficient and powerful techniques. Particularly, a supervised classification with SVM (support vector machine) was carried out annually from 2018 to 2021 in the Rambla de Cervera, an ephemeral stream at the Castelló province in eastern Spain. Orthophotographs from the Institut Cartografic Valencia with a resolution of 0.25 m/pixel and RGBI bands were used for the classification. In this classification, three landforms have been differentiated: bedrock (exposed at riverbed), channel (channel gravels and unvegetated gravel bars) and vegetated gravel bars (gravel bars with vegetation cover). Subsequently, an automatic segmentation along the river corridor was performed every 100 m. Finally, the classification values for each segment were extracted and data analysis was performed.

Preliminary results show that river recovery is controlled longitudinally by geological and structural controls. On wide alluvial reaches lateral river supply from bank erosion contributes to forming lateral gravel bars within a narrower alluvial active belt. Conversely, on confined reaches with structural control, gravel bars in the channel bed are discontinuous and alternate with erosional stretches indicating supply-limited conditions. At the most depleted sediment transmission conditions, dense vegetation is stablished decreasing the alluvial longitudinal continuity. The diachronic analysis of the orthophotographs (2018-2021) indicates an incipient recovery of the alluvial landforms at the most downstream reaches which were subject to the most extensive in-channel gravel mining. In summary, the combined use of high-resolution orthophotography with machine learning algorithms provided an effective technique for monitoring spatial-temporal stream recovery and the identification of river sectors where management and restoration efforts are urgent.

How to cite: Rabanaque, M. P., Martínez-Fernández, V., Calle, M., Sanchis-Ibor, C., Segura-Beltrán, F., Sánchez-Moya, Y., and Benito, G.: Monitoring channel response and recovery of ephemeral Mediterranean streams using diachronic orthophotography analysis with machine learning (Rambla de Cervera, Spain), 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-579, https://doi.org/10.5194/icg2022-579, 2022.