Characterization of Landscape Structures and Precipitation in relation to Flooding events in Pampa Deprimida : A Minor Field Study in Argentina

Abstract: The purpose of the thesis is to characterize flood events within the agricultural fields of flooding Pampa in Argentina. The characterization divides the flat landscape into flood prone areas and endeavour at linking driving factors to flood response based on past events. The characterization is based on information freely available from remote sensing (satelliteimages, digital elevation, and estimated rain data), from precipitation data from a weatherstation and from field measurements carried out with Universidad Nacional de La Plata. The main research question is: Which are the driving factors contributing to the flooding? Data from remote sensing was used to visualize previous areal water extents, to calculate the topographic wetness index, the upslope areas for the field study sites and for a precipitationtrend analysis. Furthermore, data from remote sensing was used to replace missing days of rain data from the weather station. The complemented rain data was compared with the water extent for the events. Relationships between event precipitation, previous precipitation, land-use, and surface runoff was evaluated with the Soil Conservation-Curve Number method, SCS-CN, and the runoff coefficients for different antecedent conditions were calculated. The precipitation data and the satellite images showing water extents were also used to calculatethe 100-year and 20-year storm- and flood event. The measured infiltration capacity was used as input data in the SCS-CN-method to calculate the surface runoff and the measured soilmoisture was used to verify results from the Topographic Wetness Index, TWI, map. The flood risk areas are visualized with satellite images and the calculated Modified Normalized Difference Water Index. The TWI also visualizes the more flood prone or wetter areas and delineates the lower depressions where soil moisture was also measured to be higher, however not significantly. With the available satellite images within the study results indicate that floods are more common wintertime and that great flood events cannot be foreseen with only antecedent precipitation and event precipitation with the SCS-CN method. However, the events in the study with larger water extents, had high precipitation. No clear correlation between water extents from satellite images calculated by Instituto Nacional de Tecnología Agropecuaria, and estimated surface runoff from the SCS-CN method could be seen. However, the obtained runoff coefficients from the SCS-CN method can be used for estimating surface runoff for future storm events were higher Antecedent Moisture Condition, AMC, and low infiltration capacities increases surface runoff. The infiltration capacity of the studied fields is approximately 16 mm/hour and hence not alone a driving factor causing inundation since the soil can absorb, for example, a 20-year storm event of 125 mm/day. However, that is not the case since a 20-year storm flood has covered 9 % of the area around Don Joaquin and El Amanecer with water. No seasonal precipitation trends can be seen in Punta Indio during the last 40 years analysing precipitation data from remote sensing. In flooding Pampa the agricultural fields inundate almost on yearly basis in the depressionsdue to the gentle slopes and high intense precipitation (yearly maximum daily precipitation is always higher than 60 mm/day). To decrease the flood risk the management should ensure high vegetative cover which increases infiltration and balances the hydrological responses.