Differential GPS as a monitoring tool on Volcano Santa Ana (Illamatepec) and the Coatepeque Caldera, El Salvador

We used differential GPS measurements from a 13 station GPS network spanning the Santa Ana Volcano and Coatepeque Caldera to characterize the inter-eruptive activity and tectonic movements near these two active and potentially hazardous features. Caldera-forming events occurred from 70-40 ka and at Santa Ana/Izalco volcanoes eruptive activity occurred as recently as 2005. Twelve differential stations were surveyed for 1 to 2 hours on a monthly basis from February through September 2009 and tied to a centrally located continuous GPS station, which serves as the reference site for this volcanic network. Repeatabilities of the averages from 20-minute sessions taken over 20 hours or longer range from 2-11 mm in the horizontal (north and east) components of the inter-station baselines, suggesting a lower detection limit for the horizontal components of any short-term tectonic or volcanic deformation. Repeatabilities of the vertical baseline component range from 12-34 mm. Analysis of the precipitable water vapor in the troposphere suggests that tropospheric decorrelation as a function of baseline lengths and variable site elevations are the most likely sources of vertical error. Differential motions of the 12 sites relative to the continuous reference site reveal inflation from February through July at several sites surrounding the caldera with vertical displacements that range from 61 mm to 139 mm followed by a lower magnitude deflation event on 1.8-7.4 km-long baselines. Uplift rates for the inflationary period reach 300 mm/yr with 1σ uncertainties of +/- 26 – 119 mm. Only one other station outside the caldera exhibits a similar deformation trend, suggesting a localized source. The results suggest that the use of differential GPS measurements from short duration occupations over short baselines can be a useful monitoring tool at sub-tropical volcanoes and calderas.

FLOOD RISK ASSESSMENT UNDER HISTORICAL AND PREDICTED LAND USE CHANGE USING CONTINUOUS HYDROLOGIC MODELING

Current procedures for flood risk estimation assume flood distributions are stationary over time, meaning annual maximum flood (AMF) series are not affected by climatic variation, land use/land cover (LULC) change, or management practices. Thus, changes in LULC and climate are generally not accounted for in policy and design related to flood risk/control, and historical flood events are deemed representative of future flood risk. These assumptions need to be re-evaluated, however, as climate change and anthropogenic activities have been observed to have large impacts on flood risk in many areas. In particular, understanding the effects of LULC change is essential to the study and understanding of global environmental change and the consequent hydrologic responses. The research presented herein provides possible causation for observed nonstationarity in AMF series with respect to changes in LULC, as well as a means to assess the degree to which future LULC change will impact flood risk. Four watersheds in the Midwest, Northeastern, and Central United States were studied to determine flood risk associated with historical and future projected LULC change. Historical single framed aerial images dating back to the mid-1950s were used along with Geographic Information Systems (GIS) and remote sensing models (SPRING and ERDAS) to create historical land use maps. The Forecasting Scenarios of Future Land Use Change (FORE-SCE) model was applied to generate future LULC maps annually from 2006 to 2100 for the conterminous U.S. based on the four IPCC-SRES future emission scenario conditions. These land use maps were input into previously calibrated Soil and Water Assessment Tool (SWAT) models for two case study watersheds. In order to isolate effects of LULC change, the only variable parameter was the Runoff Curve Number associated with the land use layer. All simulations were run with daily climate data from 1978-1999, consistent with the 'base' model which employed the 1992 NLCD to represent 'current' conditions. Output daily maximum flows were converted to instantaneous AMF series and were subsequently modeled using a Log-Pearson Type 3 (LP3) distribution to evaluate flood risk. Analysis of the progression of LULC change over the historic period and associated SWAT outputs revealed that AMF magnitudes tend to increase over time in response to increasing degrees of urbanization. This is consistent with positive trends in the AMF series identified in previous studies, although there are difficulties identifying correlations between LULC change and identified change points due to large time gaps in the generated historical LULC maps, mainly caused by unavailability of sufficient quality historic aerial imagery. Similarly, increases in the mean and median AMF magnitude were observed in response to future LULC change projections, with the tails of the distributions remaining reasonably constant. FORE-SCE scenario A2 was found to have the most dramatic impact on AMF series, consistent with more extreme projections of population growth, demands for growing energy sources, agricultural land, and urban expansion, while AMF outputs based on scenario B2 showed little changes for the future as the focus is on environmental conservation and regional solutions to environmental issues.