# Sentinel-1 and -2 Based near Real Time Inland Excess Water Mapping for Optimized Water Management
## 3 Results and Discussion
### Maps and Statistics
In 2018, the majority of inland excess water inundations affected natural grasslands, and in agricultural land the proportion of meadow pastures (21%) was higher than that of arable land (15%), while in 2016 the inundation mostly occurred on arable lands (34%). More than 83% of the detected inundations were due to patches larger than 1 ha, but in 2016 there were many patches that  
Figure 7: Relationship between the setting of the integration threshold and the total area of inland excess water in hectares in 2018.  
consisted of one large polygon: several 40-60 ha patches were detected, while the largest had an area of 331 ha. Figure 8 shows a set of submaps of the detection results of 2018. At the top, it can be seen that the three detection workflows identified similar patterns of water, but there were some differences. The MNDWI-based water maps showed the most water, while the ISODATA-based map was the least sensitive to water in this area. The frequency map showed for each pixel in how many source images inland excess water was detected. It can be clearly seen that deep waterbodies were detected most of the time, while more shallow water at the border of the deep IEW patches was detected less often. These areas form the fuzzy boundary between water, saturated soil and dry land. The integration stored water pixels that were detected more often than the relative frequency threshold. Often cloud and cloud shadows disturb the IEW detection, as can be seen on the natural color composite. The algorithm takes this into account by masking the clouds and shadows in the optical data and ignoring these pixels in the relative frequency calculation. The cloud/shadow masking prevents the algorithm to derive IEW from the optical data, but since radar images are not influenced by atmospheric disturbance, these areas are evaluated for water by the active satellite data based workflow. Figure 9 shows the differences in IEW area between the three detection methods and the total area of detected inland excess water in the integration result for the same sub-area as used in Figure 8. In the sub-area, the results for the optical data based workflows contained smaller IEW areas due to the clearly identifiable clouds and shadows in the area. At those locations, pixels were not evaluated by the ISODATA and MNDWI algorithms because they were masked out in the preprocessing phase before the algorithms were run, based on the cloud mask incorporated with the Sentinel-2 level 2 data set. The radar-based result contained IEW pixels in cloud/shadow areas because the atmospheric disturbances did not influence the active remote sensing data. Figure 8: Sub-results (**A–C**), frequency of water detection (**D**) and the integrated final inland excess water map (**E**) on a selected area during the 13 th week of 2018. Figure 10 shows the distribution of inland excess water per algorithm for the whole study area. Here, the misclassifying of shadow as water by the optical data based ISODATA is clearly shown. In areas with cloud shadows that were not masked out by ESA's Sen2 Cor cloud/shadow detection algorithm, the ISODATA classifier mixed up shadow and water. The MNDWI algorithm is also based on optical data, but it is not sensitive to this misclassification. The integration result was not influenced by the errors due to shadows because these only occurred in one sub-result and, therefore, do not meet the integration threshold to be incorporated in the final result. Maps of aggregated values for the absolute and relative number of hectares of inundations were generated per administrative IEW defense areas (Figure 11). They support operative water management planning by the local Water Directorates, and they can help to estimate the required pumping capacity and expected duration of the floods. The aggregated inundation maps for all IEW defense areas can be combined to a country-wide IEW preparedness map that is used for the national water management program.