Previous research

Punjab, India

Kenya and Tanzania

United States

Monitoring riparian wetland infiltration and drainage in Poopenaut Valley, Yosemite National Park

Poopenaut Valley is approximately three kilometers downstream of the Hetch Hetchy reservoir on the Tuolumne River. Several riparian wetlands in the valley have been impacted by a lack of natural flooding over the last 90 years, due to flow regulation by the O`Shaughnessy Dam. Recently, San Francisco Public Utilities Commission and Yosemite National Park have implemented controlled flood releases which are hoped to assist with riparian wetland restoration in the valley. Our research project was designed to monitor the soil moisture and shallow groundwater response to flooding, to assess the relatively roles of groundwater rise and inundation in developing and sustaining wetland conditions adjacent to the river, and evaluate what kinds of "design floods" might be most useful in meeting wetland restoration requirements while reducing the total water release from the Hetch Hetchy Reservoir. We collected soil samples in several locations, and installed moisture content sensors, groundwater piezometers, and thermal probes for measuring streambed infiltration rates, prior to the Spring 2009 controlled flood release. Our research suggests that inundation plays a more important role than rising groundwater levels in developing wetland conditions adjacent to the river, although groundwater does play a quantifiable role in this process. We also found that wetland restoration requirements might be met with a smaller release through pulsing of flood flows with a timing that is set to take advantage of the drainage properties of shallow soils.

Measuring hyporheic exchange response to forest fire in Scott Creek Watershed

Forty percent of the Scott Creek Watershed in northern Santa Cruz County burned in the 2009 Lockheed wildfire. Scott Creek is spawning habitat for Coho salmon (Oncorhynchus kisutch) and steelhead trout (Oncorhynchus mykiss), which could be impacted as a result of a large fire. This project aims to quantify the impact of sediment delivery triggered by the fire on changes in streambed properties and the nature of hyporheic exchange (movement of water back and forth between the stream channel and shallow subsurface), an important process for regulating temperature and delivering nutrients and dissolved oxygen to the aquatic habitat. We selected three reaches for monitoring and experiments, two downstream of the burned area and one upstream of the burned area, as a relative control. Airborne light detection and ranging (LiDAR) data sets before and after the fire will be used to identify areas of erosion and deposition on the reach scale. Supplemental channel profile measurements will provide a more accurate local assessment of streambed morphology changes with time, in select locations. Discharge tracer tests will be repeated over two to three years to measure hyporheic exchange processes at a reach scale. Each reach also has a cluster of streambed instruments, including thermal probes and pressure piezometers, to provide information on local hyporheic exchange rates and changes in streambed hydraulic conductivity over time. We hope to distinguish between potential fire-related impacts and seasonal patterns by comparing relative changes at each site with the control site, and through repeated measurements under similar flow conditions over several water years.

Assessing suitability for Managed Aquifer Recharge in the Pajaro Valley, CA

The Pajaro Valley Groundwater Basin (PVGB), central coastal California, relies almost entirely on groundwater to satisfy agricultural and municipal/domestic needs. Extraction in excess of recharge over the last five decades have resulted in a lowering of water levels throughout the basin and seawater intrusion near the coast. Managed aquifer recharge (MAR) will likely be increasingly important for sustaining the groundwater supply in future years, but identifying areas amenable to MAR projects remains a common challenge. Our project aims to address this challenge using three components: 1) a geographical information systems (GIS) analysis of recharge related parameters, used to identify the relative suitability for MAR projects across the basin, 2) percolation testing at potential MAR sites using a custom-designed system for delivering water and measuring field infiltration for three to ten days, and 3) use of a regional groundwater model to quantify the potential influences of distributed MAR projects throughout the PVGB.

Regional and local increases in storm intensity in the San Francisco Bay Area, 1890 to 2010

Studies of extreme precipitation have documented changes at the continental scale during the twentieth century, but few studies have quantified changes at small to regional spatial scales during the same time. We analyze historic data from over 600 precipitation stations in the San Francisco Bay Area (SFBA), California, to assess whether there have been statistically significant changes in extreme precipitation between 1890 and 2010. An annual exceedance probability analysis of extreme precipitation events in the SFBA, coupled with a Markov chain Monte Carlo algorithm, reveals an increase in the occurrence of large events. The depth-duration-frequency characteristics of maximum annual precipitation events having durations of 1 h to 60 days indicate on average an increase in storm intensity in the last 120 years, with the intensity of the largest (least frequent) events increasing the most. Mean annual precipitation (MAP) also increased during the study period, but the relative increase in extreme event intensity exceeds that of MAP, indicating that a greater fraction of precipitation fell during large events. Analysis of data from subareas within the SFBA region indicates considerable heterogeneity in the observed nonstationarity; for example, the 5 day, 25 year event exceedance depth changed by +26%, +16%, and -1% in San Francisco, Santa Rosa, and San Jose, respectively. These results emphasize the importance of analyzing local data for accurate risk assessment, emergency planning, resource management, and climate model calibration.