The hydrological effects of the conversion of forested land to other land uses (and vice versa) are to a large degree
unknown. The present study investigate the effect of natural regrowth of forest on the regional hydrological cycle,
and in particular the effects on streamflow. The Dragonja catchment (covering SW Slovenia and NW Croatia)
was chosen because the land use changed significantly in this region over the last 50 years. Satellite data and
field observations were used to study the hydrological effect of land use change. Historical remote sensing data
from Landsat and ASTER revealed a significant change from agriculture to forest within the catchment. From
1973 to 2002 26% changed from agricultural field to forest. In the same period both the baseflow and the storm
and flood frequency dropped significantly. A large part of the streamflow changes may probably be linked to
precipitation changes in this region, making the hydrological study on reforestation a difficult task. Until now
no significant link between reforestation and changes in the hydrological cycle was found and more research is
needed to fully understand the hydrological system in this region.
KEYWORDS: Soil science, Data modeling, Satellites, Floods, Data centers, Data conversion, Remote sensing, Geographic information systems, Microwave radiation, Visualization
The remote sensing and GIS communities are still separate worlds with their own tools and data formats. It is extremely
difficult to easily share data among scientists representing these communities without performing some cumbersome
conversions. This paper shows in a case study how these two worlds can benefit from each other by implementing online
satellite derived soil moisture in a GIS based operational flood early warning system. We obtained near real time satellite
data from the currently active satellite microwave sensor AQUA AMSR-E from the National Snow and Ice Data Center
data pool and converted the data to soil moisture maps with the Land Parameter Retrieval Model. The soil moisture
maps, with a spatial resolution of 0.1 degree and temporal resolution of approximately 1 day, were converted in a
gridded format and directly added to an operational Flood Early Warning System. The developed opportunity to directly
visualize soil moisture in such a system appears to be a powerful tool, because it creates the ability to study both the
spatial and temporal evolution of soil moisture within the river basin. Furthermore, near real time qualitative information
on soil moisture conditions prior to rainfall events, such as generated by our system, can even lead to more accurate
estimations for flood hazard conditions. Finally, the current and future role and value of remote sensing products in flood
forecasting systems are discussed.
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