GEOG 566






         Advanced spatial statistics and GIScience

April 5, 2019

My Spatial Problem: Streamflow variability and associated processes in rain-dominated, coastal basins

Filed under: 2019,My Spatial Problem @ 10:37 pm

My research explores the variability in streamflow patterns in rain-dominated systems of the Pacific Northwest. Rain-dominated climate regimes occur primarily in the coastal portion of the PNW. Because precipitation only occurs as rain and does not occur in significant quantities during the summer season, underground storage is a crucial component of both the water cycle and streamflow stability in these systems. The objectives of my research are: first) to describe variations in stream hydrograph stability across multiple catchments and multiple catchment scales, and second) to use estimations of catchment storage processes to help explain potential variations in streamflow patterns.

I will be analyzing multiple datasets in order to meet my objectives. Those include: geophysical data, land-use/management data, and streamflow data. All landscape data will be analyzed at the finest spatial resolution available for the dataset. Hourly streamflow data will be analyzed for the available period of record, which varies by site. Second-fourth order streams in the Siletz and Smith river basins have hourly discharge data for the recent 5-8 years. USGS hydrological stations have similar data for 10-30 years.

I expect to see that streams in different hydrogeologic setting demonstrate different streamflow patterns over time. Streams located in more permeable, thicker lithosphere, may demonstrate more stable stream flows. In the winter, that may appear as muted storm peaks, while in the summer, that may appear as more sustained baseflows through the non-rainy season. Land cover may play an important role in streamflow regimes as well. The amount of water taken up and stored by vegetation may depend on the density, age, structure, and species composition of the forest. Watersheds with a large areas managed under industrial timber production may confound streamflow behavior.

I envision approaching my objectives by first developing some descriptive statistics for the hydrographs at each site. Such descriptors may include: recession analysis, dynamic storage, 7q10, arc peak, and various other streamflow analysis metrics with which I am not yet familiar. All sites are of varying contributing areas, so that will have to be taken into consideration in the analysis. Once descriptive statistics are developed across each site, I would like to integrate an analysis of the landscape attributes as potential explanatory variables for any variations observed in hydrograph statistics across space to see how much explanatory power they have, and how much variation there is.

The product of this project is expected to include both maps and statistical relationships. For maps, I would like to produce: 1) a depiction of the hydrogeologic settings across the study area, and 2) a depiction of expected streamflow patterns given the hydrogeologic settings. I would like to understand the statistical relationship between various streamflow metrics and the hydrogeologic setting of the given stream.

The results of this analysis may be important to resource managers and the scientific community as it will contribute information about hydrological processes, with a focus on the critical zone, in the PNW coastal landscapes. The persistence of streams and rivers in this region is crucial to several species of native salmonids, as well as to the economic well-being of the local communities. With potential variations in the climate, understanding underlying hydrological processes and the drivers of such processes may contribute to more proactive management approaches. Furthermore, an analysis that is relevant to the fine-scale processes that exist in the study area may contribute more accurate classifications of hydrologic regimes and analyses of streamflow vulnerability to long-term changes in the hydrological cycle.

As far as preparation for this project: I am well-versed in ArcGIS software. I have used Model Builder and Python some, though could use more practice. I am most comfortable with spatial and statistical analyses through R software. I have only used imagery analyses in a class, and I’d like to use it for my analysis so I am looking forward to learning more through this class.

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1 Comment »

  1.   jonesju — April 7, 2019 @ 2:30 pm    

    Rosemary, great start. Some things to think about. 1) Resesarch question. Try rephrasing as “How are the spatial patterns of XX (geologic or topographic or land use factors) (A) related to the spatial patterns of water storage (B), via the YY (E.g., effects of geology, landforms, and land use on runoff production, mechanism C)?”. 3) Hypotheses. How do you expect timber harvest to affect streamflow variability? Rephrase this to state what you expect. 4) Analyses. For Ex 1, I suggest you determine the temporal autocorrelation in daily streamflow data at each of your sites, and also test for spatial patterns in your driver variables (geology, landforms, harvests). For Ex 2, you could use GWR or Cross-correlation or simple regression to examine how driver variables are related to the autocorrelation of streamflow.

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