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EEWR Brown Bag Seminar wtih Colby Fisher and Benjamin Schaffer, Graduate Students

Speaker: Colby Fisher and Benjamin Schaffer, Graduate Students
Series: EEWR Brown Bag Seminars
Location: Engineering Quad E225
Date/Time: Friday, May 5, 2017, 12:00 p.m. - 1:00 p.m.

Abstract:

Colby Fisher: Observability of global rivers with future SWOT observations

The Surface Water and Ocean Topography (SWOT) mission is designed to provide global observations of water surface elevation and slope from which river discharge can be estimated using a data assimilation system. This mission will provide increased spatial and temporal coverage compared to current altimeters, with an expected accuracy for water level elevations of 10 cm on rivers greater than 100 m wide. Within the 21-day repeat cycle, a river reach will be observed 2-4 times on average. Due to the relationship between the basin orientation and the orbit, these observations are not evenly distributed in time, which will impact the derived discharge values. There is, then, a need for a better understanding of how the mission will observe global river basins. In this study, we investigate how SWOT will observe global river basins and how the temporal and spatial sampling impacts the discharge estimated from assimilation. SWOT observations can be assimilated using the Inverse Streamflow Routing (ISR) model of Pan and Wood [2013] with a fixed interval Kalman smoother. Previous work has shown that the ISR assimilation method can be used to reproduce the spatial and temporal dynamics of discharge within many global basins: however, this performance was strongly impacted by the spatial and temporal availability of discharge observations. In this study, we apply the ISR method to 32 global basins with different geometries and crossing patterns for the future orbit, assimilating theoretical SWOT-retrieved “gauges”.
  
Benjamin Schaffer: Plant biomass dynamics in a desert ecosystem, NW China: present condition and climate change scenarios

The temporal dynamics of vegetation biomass is of vital importance for evaluating the sustainability of arid and semi-arid ecosystems. Both theory and field observations indicate that soil moisture and plant biomass fluctuate stochastically with the occurrence of rainfall events. Based on long-term field observations, it is found that the dynamics of the vegetation biomass can be quantified by its analytically derived time dependent probability distribution, validating the underlying stochastic-dynamical model of water-limited carbon assimilation. This allows for the study of the impact of climate change scenarios on vegetation cover and plant water resource competition. It is found that in a restored desert ecosystem in NW China, the changes in the growing season leaf biomass are expected to be near 25% of the present one.