Final Project. GEOG 566

Zach Butler

1. The research question that you asked (provide one question for each exercise).

E1: How are precipitation and streamflow characterized at each site and how are they correlated across sites?

E2: How are precipitation and streamflow characterized at each site? Does the catchment area, latitude, and or longitude relate to streamflow at each site?

E3: How can I relate the ACF and CCF of each collocated station to observed residence times at the same stations?

• A description of the dataset you examined, with spatial and temporal resolution and extent.

The data is from the National Ecological Observatory Network (NEON), which spans across North America. I am using stations where there is stream and precipitation data, both with the amounts and isotopes. This reduces my dataset to 22 collocated stations. Stations are often collocated with nearby stations that fulfill my four data source requirements (precipitation amount, streamflow amount, precipitation isotope, streamflow isotope). For this project, I am interested in water residence times, for which I need isotope data from precipitation and streamflow. The data begins at different time periods from 2013-2016 but continues through the present. There are occasional gaps in data records, but they are relatively small, and I am not too worried about these effects. For this project, I am only using precipitation and streamflow amounts.

• Hypotheses: predictions of patterns and processes you looked for.

I predicted to see patterns of precipitation and streamflow across the country based on climate patterns. I also expected the catchment area to affect precipitation and streamflow patterns. I expected precipitation and streamflow to relate to each other at sites across the country but knew there would be outliers to this as well. I wanted to correlate the precipitation and streamflow to each other for the collocated precipitation and streamflow sites. I was hoping to see characteristics that I could then relate to water residence times from my research at OSU.

• Approaches: analysis approaches you used.

For Exercise 1, I used the ACF function in python and the CCF function in R. For Exercise 2, I used the data from the ACF function to compare it site characteristics in excel. For exercise 3, I used Excel to relate the ACF and CCF data.

• Results: what did you produce — maps? statistical relationships? other? Present the key, important results you created.

• What did you learn from each of the analyses you conducted (i.e., from each exercise)? 

E1: I learned how to step back my research ideas to start with the basics. I wanted to relate isotope data right away but decided to proceed with the precipitation and streamflow amount data. I learned about ACF and CCF statistical analyses to relate precipitation and streamflow data separate but also together.

E2: There is a lot to take away from these functions and experimenting with different lags, I learned processes to best represent my data, and what the results mean. I experimented with ArcMap a bit to visualize some plots and how to add my csv files to ArcMap.  This did not prove to be useful but was a skill that I learned.

E3: I learned how to relate all of my parts together to produce something meaningful and useful for my research. Doing simple analyses in excel proved useful by creating ‘classes’ for the different ACF and CCF functions.

• Significance. How are these results important to science? to resource managers?

These results show how precipitation and streamflow are characterized at various long term ecological sites across North America. The results show which stations have a relation of precipitation and streamflow to each other at various lags or time periods, as well as which do not. These results help me characterize my results from the mean residence time at each site. This allows for a greater understanding of how quickly water cycles through these systems. This has implications for climate changes impact on water resources as well as potential water quality concerns. 

• Software learning. Your learning: what did you learn about software (a) Arc-Info, (b) GIS programming in Python, (c) programming in R, (d) Modelbuilder in Arc,or (e) other?

I learned how to use the ACF and CCF function in R as well as using the ACF in python. Python was easier for me to use, and it was a definite learning curve using R. I used a bit of ArcMap to visualize some of my data. This was a nice refresher since it has been a while since I used it.

• Statistics learning. What did you learn about statistics, including (a) hotspot, (b) spatial autocorrelation (including correlogram, wavelet, Fourier transform/spectral analysis), (c) cross-correlation/regression (cross-correlation, geographically weighted regression [GWR], regression trees, boosted regression trees), (d) multivariate methods (e.g., PCA, multiple component analysis), (e) other techniques (change detection/confusion matrices, other)?

I learned quite a bit about temporal autocorrelation and statistical analysis of precipitation and streamflow. I learned how to use the ACF and CCF function, and how to interpret the results are various lags based on my input data. I briefly used a geographically weighted regression in ArcMap but realized it was not helpful with the data I have. I still learned about it, and how I might be able to use it in the future. Overall, I learned the power of statistics to show conclusions and relate data to each other. This allowed myself to obtain a greater understanding of my data.

1. Evolving question. How did the results of each analysis lead you to change/refine your question?  Write out the original question you stated at the beginning of the class, and restate the question(s) you now plan to address. 

Original Question: How do isotope concentrations in precipitation and streamflow vary across the NEON network and what does this tell us about water residence times?

I changed my first research question several times to step back and start with the basics of my data. Once I fine-tuned and made my first research question, I did not know how I could continue from there. The results of each analysis allowed me to develop my research questions throughout the class, while investigating the next step during this process. It allowed me to ask other questions with the data. For question 3, I ended up going back to results from question 1 to gain a further understanding. This allowed me to have a nice final product using each research question to gain an understanding for precipitation and streamflow characteristics as well as the interrelation at each of my sites. I would like to continue to relate my data in the future to catchment characteristics as well as obtain more catchment characteristics from the sites.

1. Future techniques. What techniques would you like to explore to answer your research questions in the future?

I want to get stream length and catchment gradient data to further understand the relationship of catchment characteristics to streamflow and precipitation. This would further help me understand how precipitation and streamflow influence water residence times through these additional catchment characteristics. I can do this in GIS or python but am not exactly sure how to. This would be an additional tool I can learn and add to my toolbox.