Estimation of the Monthly Dynamics of Surface Water in Wetlands from Satellite and Secondary Hydro-Climatological Data

Abstract

Satellites produce valuable information for studying the surface water in wetlands, but in many cases the period covered, the spatial resolution and/or the revisit frequency is not enough to produce long historical series. In this paper we propose a novel method which uses regression models that include climatic and hydrological variables to complete the satellite information. We used this method in the Lagunas de Ruidera wetland (Spain). We approached the monthly dynamic of the surface water for a long period (1984–2015). Information from LANDSAT (30-m resolution) and MODIS (250-m resolution) satellites were tested but, due to the size of some lagoons, only the LANDSAT approach produced satisfactory results. An ensemble of regression models based on hydro-climatological explanatory variables was defined to complete the gaps in the monthly surface water. It showed a root mean squared error of around 476 pixels (0.4 Km2) in the cross-validation analysis. Our analysis showed that the explanatory variables with a more significant participation in the regression ensemble are the aquifer discharge, the effective precipitation and the surface water from the previous month. From January to June, the mean surface water in Lagunas de Ruidera is around 4.3 Km2. In summer a reduction of around 13% of the surface water can be observed, which is recovered during the autumn.