Assessing soil salinity using remote sensing in Campo de Cartagena
- 1Centro de Edafología y Biología Aplicada del Segura (CEBAS-CSIC), Department of Irrigation, Cartagena, Spain (fpedrero@cebas.csic.es)
- 2Universidad de Murcia (UMU), Departament of Geography , Murcia, Spain (pedrope@um.es)
A pioneering study in Murcia within the framework of the ASSIST (Use of Advanced information technologies for Site-Specific management of Irrigation and SaliniTy with degraded water) research project, seeks to lay the foundations for a new integrated system for the assessment of salinity through combined use of traditional techniques (soil and plant sampling) and new technologies (multispectral aerial videography or satellite observation; and image analysis) to help quantify and map soil salinization / degradation and the effects of soil-plant interactions (salinity-toxicity) on the growth and yield of irrigated crops. In this sense, the initial objective was to evaluate the salinity of the soil and the development of lettuces irrigated with unconventional water resources through thermal and multispectral images. Different soil and plant salinity indices were studied, observing that the temperature (on plant) and salinity index (SI) (on soil), had a moderate correlation with the soil salinity. Although the results obtained have been encouraging, more research is needed to develop specific equations capable to predic soil salinity from the values of these indices taken remotely. In this context, a review of the spectral salinity indices has been prepared to be applied at a regional scale. As an experimental area, El Campo de Cartagena located in the southeast of the Iberian Peninsula has been chosen, since there is intensive irrigated agriculture in a semi-arid environment. Due to this, farmers resort to using non-conventional and saline water sources, consequently the use of saline irrigation water is causing salinization of the soils and damage to the crops. Values from existing salinity records combined with soil salinity data obtained in various plots, provided information that was correlated with time series of Landsat images (1984-2020). Regression models were also applied in which environmental variables provided an improvement in the estimation of soil salinity. The results allowed us to determine the main salinity concentration areas, as well as inputs to establish criteria for improvement in the management of irrigation systems.
How to cite: Pedrero Salcedo, F., Alarcón Cabañero, J. J., and Pérez Cutillas, P.: Assessing soil salinity using remote sensing in Campo de Cartagena, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14478, https://doi.org/10.5194/egusphere-egu21-14478, 2021.