Mohammad Danesh-Yazdi defends PhD dissertation titled, "Inferring the Impacts of Anthropogenic Changes and Catchment Spatial Heterogeneity on the Water Cycle Dynamics and Transport Time Scales"

PhD candidate Mohammad Danesh-Yazdi successfully defended his dissertation in Civil, Environmental, and Geo-Engineering on February 2nd, 2017. He is advised by Professor Efi-Foufoula-Georgiou, formerly of the St. Anthony Falls Laboratory and currently professor at the University of California - Irvine. Congratulations, Dr. Danesh-Yazdi!

Dissertation Title: Inferring the Impacts of Anthropogenic Changes and Catchment Spatial Heterogeneity on the Water Cycle Dynamics and Transport Time Scales

Climatic trends and anthropogenic interventions during past decades have undeniably impacted the hydrology and water quality of streams at the field, watershed, and regional scales in complex ways. This dissertation has developed a quantitative framework within which first order estimates of the relative changes in travel time statistics in those landscapes undergoing substantial alterations in land-use land-cover can be quantified. Results from analysis of a subbasin in the Minnesota River Basin located in the Midwestern United States indicated a significant decrease in the mean travel time of water in the shallow subsurface layer during the growing season under current conditions compared to the pre-1970’s conditions. Highly damped year-to-year fluctuations in the mean travel time were also found, which were attributed to the homogenization of the hydrologic response due to artificial drainage. Regarding the lack of high spatiotemporal resolution hydro-chemical data (in many catchments) required for an accurate estimation of transport time scales, this work has explored whether a lumped system representation via a time-varying stochastic Lagrangian formulation can provide reliable estimates of mean travel time in spatially heterogeneous catchments in the absence of within catchment observations. This time (variability) for space (heterogeneity) substitution yielded mean travel times that are not significantly biased to the aggregation of spatial heterogeneity under different sampling assumptions. Despite the significant variability of mean travel time at small spatial scales, there exists a characteristic scale above which the mean travel time is not impacted by the aggregation of spatial heterogeneity. Extensive simulations of randomly generated river networks revealed that the ratio between the characteristic scale and the mean incremental area is on average independent of river network topology and the spatial arrangement of incremental areas. As the river network structure (which is typically considered self-similar) might impose a significant control on the in-stream transport time scales and be used to explain some properties of the relating physical processes, we further explored those river networks that do not obey the typical self-similar relationships over a range of spatial scales. We proposed methodologies that can probe into the structure of such outlier basins, called self-dissimilar, in ways that are able to reveal their spatially heterogeneous organization and quantify preferential scales of dissection, which in turn can influence the transport and storage time scales at large-scale catchments with implications for solute transport and water quality.