Evaluation of flood risk in response to climate variability

Standard procedures for forecasting flood risk (Bulletin 17B) assume annual maximum flood (AMF) series are stationary, meaning the distribution of flood flows is not significantly affected by climatic trends/cycles, or anthropogenic activities within the watershed. Historical flood events are therefore considered representative of future flood occurrences, and the risk associated with a given flood magnitude is modeled as constant over time. However, in light of increasing evidence to the contrary, this assumption should be reconsidered, especially as the existence of nonstationarity in AMF series can have significant impacts on planning and management of water resources and relevant infrastructure. Research presented in this thesis quantifies the degree of nonstationarity evident in AMF series for unimpaired watersheds throughout the contiguous U.S., identifies meteorological, climatic, and anthropogenic causes of this nonstationarity, and proposes an extension of the Bulletin 17B methodology which yields forecasts of flood risk that reflect climatic influences on flood magnitude. To appropriately forecast flood risk, it is necessary to consider the driving causes of nonstationarity in AMF series. Herein, large-scale climate patterns—including El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO)—are identified as influencing factors on flood magnitude at numerous stations across the U.S. Strong relationships between flood magnitude and associated precipitation series were also observed for the majority of sites analyzed in the Upper Midwest and Northeastern regions of the U.S. Although relationships between flood magnitude and associated temperature series are not apparent, results do indicate that temperature is highly correlated with the timing of flood peaks. Despite consideration of watersheds classified as unimpaired, analyses also suggest that identified change-points in AMF series are due to dam construction, and other types of regulation and diversion. Although not explored herein, trends in AMF series are also likely to be partially explained by changes in land use and land cover over time. Results obtained herein suggest that improved forecasts of flood risk may be obtained using a simple modification of the Bulletin 17B framework, wherein the mean and standard deviation of the log-transformed flows are modeled as functions of climate indices associated with oceanic-atmospheric patterns (e.g. AMO, ENSO, NAO, and PDO) with lead times between 3 and 9 months. Herein, one-year ahead forecasts of the mean and standard deviation, and subsequently flood risk, are obtained by applying site specific multivariate regression models, which reflect the phase and intensity of a given climate pattern, as well as possible impacts of coupling of the climate cycles. These forecasts of flood risk are compared with forecasts derived using the existing Bulletin 17B model; large differences in the one-year ahead forecasts are observed in some locations. The increased knowledge of the inherent structure of AMF series and an improved understanding of physical and/or climatic causes of nonstationarity gained from this research should serve as insight for the formulation of a physical-casual based statistical model, incorporating both climatic variations and human impacts, for flood risk over longer planning horizons (e.g., 10-, 50, 100-years) necessary for water resources design, planning, and management.

IMPACTS OF CLIMATE CHANGE ON SOIL MICROORGANISMS IN NORTHERN HARDWOOD FORESTS

As global climate continues to change, it becomes more important to understand possible feedbacks from soils to the climate system. This dissertation focuses on soil microbial community responses to climate change factors in northern hardwood forests. Two soil warming experiments at Harvard Forest in Massachusetts, and a climate change manipulation experiment with both elevated temperature and increased moisture inputs in Michigan were sampled. The hyphal in-growth bag method was to understand how soil fungal biomass and respiration respond to climate change factors. Our results from phospholipid fatty acid (PLFA) analyses suggest that the hyphal in-growth bag method allows relatively pure samples of fungal hyphae to be partitioned from bacteria in the soil. The contribution of fungal hyphal respiration to soil respiration was examined in climate change manipulation experiments in Massachusetts and Michigan. The Harvard Forest soil warming experiments in Massachusetts are long-term studies with 8 and 18 years of +5 °C warming treatment. Hyphal respiration and biomass production tended to decrease with soil warming at Harvard Forest. This suggests that fungal hyphae adjust to higher temperatures by decreasing the amount of carbon respired and the amount of carbon stored in biomass. The Ford Forestry Center experiment in Michigan has a 2 x 2 fully factorial design with warming (+4-5 °C) and moisture addition (+30% average ambient growing season precipitation). This experiment was used to examine hyphal growth and respiration of arbuscular mycorrhizal fungi (AMF), soil enzymatic capacity, microbial biomass and microbial community structure in the soil over two years of experimental treatment. Results from the hyphal in-growth bag study indicate that AMF hyphal growth and respiration respond negatively to drought. Soil enzyme activities tend to be higher in heated versus unheated soils. There were significant temporal variations in enzyme activity and microbial biomass estimates. When microbial biomass was estimated using chloroform fumigation extractions there were no differences between experimental treatments and the control. When PLFA analyses were used to estimate microbial biomass we found that biomass responds negatively to higher temperatures and positively to moisture addition. This pattern was present for both bacteria and fungi. More information on the quality and composition of the organic matter and nutrients in soils from climate change manipulation experiments will allow us to gain a more thorough understanding of the mechanisms driving the patterns reported here. The information presented here will improve current soil carbon and nitrogen cycling models.

Using water balance models to approximate the effects of climate change on spring catchment discharge : Mt. Hanang, Tanzania

This project addresses the potential impacts of changing climate on dry-season water storage and discharge from a small, mountain catchment in Tanzania. Villagers and water managers around the catchment have experienced worsening water scarcity and attribute it to increasing population and demand, but very little has been done to understand the physical characteristics and hydrological behavior of the spring catchment. The physical nature of the aquifer was characterized and water balance models were calibrated to discharge observations so as to be able to explore relative changes in aquifer storage resulting from climate changes. To characterize the shallow aquifer supplying water to the Jandu spring, water quality and geochemistry data were analyzed, discharge recession analysis was performed, and two water balance models were developed and tested. Jandu geochemistry suggests a shallow, meteorically-recharged aquifer system with short circulation times. Baseflow recession analysis showed that the catchment behavior could be represented by a linear storage model with an average recession constant of 0.151/month from 2004-2010. Two modified Thornthwaite-Mather Water Balance (TMWB) models were calibrated using historic rainfall and discharge data and shown to reproduce dry-season flows with Nash-Sutcliffe efficiencies between 0.86 and 0.91. The modified TMWB models were then used to examine the impacts of nineteen, perturbed climate scenarios to test the potential impacts of regional climate change on catchment storage during the dry season. Forcing the models with realistic scenarios for average monthly temperature, annual precipitation, and seasonal rainfall distribution demonstrated that even small climate changes might adversely impact aquifer storage conditions at the onset of the dry season. The scale of the change was dependent on the direction (increasing vs. decreasing) and magnitude of climate change (temperature and precipitation). This study demonstrates that small, mountain aquifer characterization is possible using simple water quality parameters, recession analysis can be integrated into modeling aquifer storage parameters, and water balance models can accurately reproduce dry-season discharges and might be useful tools to assess climate change impacts. However, uncertainty in current climate projections and lack of data for testing the predictive capabilities of the model beyond the present data set, make the forecasts of changes in discharge also uncertain. The hydrologic tools used herein offer promise for future research in understanding small, shallow, mountainous aquifers and could potentially be developed and used by water resource professionals to assess climatic influences on local hydrologic systems.

INSTANTANEOUS PHOTOSYNTHETIC RESPONSE TO TEMPERATURE OF MATURE FOREST CANOPIES AND EXPERIMENTALLY WARMED SEEDLINGS

Tropical trees have been shown to be more susceptible to warming compared to temperate species, and have shown growth and photosynthetic declines at elevated temperatures as little as 3oC above ambient. However, regional and global vegetation models lack the data needed to accurately represent physiological response to increased temperatures in tropical forests. We compared the instantaneous photosynthetic responses to elevated temperatures of four mature tropical rainforest tree species in Puerto Rico and the temperate broadleaf species sugar maple (Acer saccharum) in Michigan. Contrary to expectations, leaves in the upper canopy of both temperate and tropical forests had temperature optima that are already exceeded by mean daily leaf temperatures. This indicates that tropical and temperate forests are already seeing photosynthesis decline at mid-day temperature. This decline may worsen as air temperatures rise with climate change if trees are unable to acclimate, increasing the likelihood that forests may shift from carbon sinks to sources. A secondary study was conducted on experimentally warmed sugar maple seedlings to determine if photosynthesis had been able to acclimate to +5oC air temperature over four years. Species abundance models had predicted a decline of sugar maple within the Upper Peninsula of Michigan over the next 100 years, due to elevated temperature and altered precipitation. Instantaneous photosynthetic temperature response curves on both control and heated seedlings showed that the differences between treatments were not statistically significant, though there was a 16% increase in temperature optima and a 3% increase in maximum rates of photosynthesis in warmed plots. Though evidence of acclimation was not significant, the seedlings did not fare poorly as the models suggest.