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Just got back from Eagle's Nest. The basin was tannic and the visibility in the cave was some of the worst I've seen. The ballroom and entire upstream was 10-15 feet, with a little patch of 20' at around 1400 feet upstream.
If you're thinking of going this weekend, save yourself the trouble.
Andy
Was the same last weekend as well. Never got around to sending a report...sorry.
Thanks for the Dive report. My dive partner and I have been considering it, so we are going to wait till after the rainy season ends.
Wow, on the 6th the viz (upstream to the super-room/ballroom) was fantastic.
The first time I dove EN was in the "winter" dry season. Vis was not bad, much further than the HID Video light could illuminate, but as we started down the cone that primary light failed. It was short but the dive was nice.
The visibility at EN is hard to predict, but there are a few trends that emerge over several years. In general visibility is better in the summer, particularly after a dry spell. It is also affected by the tides, being better at times of lower tidal variation (neap tides) than higher (spring tides). However, there is a lot of scatter around these trends.
My personal theory is that anything that increases the amount of surface water syphoning into the system will worsen visibility. Cold surface water (in the winter) doesn't tend to float on top of the warmer aquifer water, hence the worse visibility in the winter. When there is more of it after heavy summer rainfall it will still tend to get in, despite being warmer. The hydrostatic pressure changes caused by large (spring) tides tends to allow more surface runoff to seep in.
Just a theory. If anyone knows a lot about statistical modelling, we could try putting these environmental factors into a multivariate regression model and see if anything shakes out.
Andy
Finally, someone needs a multivariate statistician slash cave diver!! I could help with a quantitative approach, if empirical data are available. Otherwise, a hydrographer might provide a better qualitative, conceptual model. At any rate, it would be fun to install some Hobo temps and a pressure sensor in the Nest and collect observational data from visibility reports. These could then be combined with some of the regional environmental data archived by the various management agencies, etc.Quote:
Originally Posted by apitkin
Anyone have a Minnus they could donate to the cause???
Dave
Andy, one of the interesting thing about having 6 years worth of condition reports is I can generally see how long systems take to clear after floods, how tides and rain affect systems, etc. It is anecdotal but interesting nonetheless. I was using some of the Google visualization API tools to chart this as version one of Cave Atlas but it just seemed now novel than helpful. In the case of the Nest, there are 247 conditions reports since 8.10.2005Quote:
Originally Posted by apitkin
We did some modeling somewhat like this in Physical Oceanography. I just don't have access to that program anymore. Dissolved material is effected by rainfall and hydrologic pressures of tidal influence. Water column turbidity I think is the primary factor, measured as a function of solution saturation. Water samples with dates, and time for reference to local conditions will be most important.
Actually, I was thinking that those hundreds of conditions reports would be the empirical data we could use. Collate those with tidal, rainfall, and other environmental data such as mean daily temperature and see what happens. Is there any correlation, positive or negative, with output from local springs (e.g. Weeki)? It's all available. Then you can make a hypothesis (e.g. 2 weeks of heavy rain in the summer trashes the viz) and then test it against the historical data.Quote:
Originally Posted by DeepSea
It might even be possible to build a mathematical model that will predict visibility there within certain confidence intervals.
I'd suggest coding the visibility reports as categorical response data and reformulate your hypothesis as a falsifiable null. Then, if the environmental data, coded as multivariate predictors, yield significant effects in, say, a MANOVA, construct a set of discriminate functions to make predictions and use cross-validation to gauge it effectiveness. Child's play. The only REAL effort involves aggregating the data...
Dave
That makes sense. How many categories would you use for the observation reports? 5 (e.g. terrible, poor, OK, good, excellent)?
What is the null hypothesis? Is it "environmental condition x does not predict visibility result"?
If I put it all in an Excel spreadsheet and send it to you, can you do the rest? I have only a very basic understanding of statistics.
Yes, I think a categorical visibility variable with 5 levels would work well.
Yes, the Ho: "No significant effect of environmental variable(s) on visibility". We can use a variable selection procedure to construct a parsimonious model, which only includes the environmental variables important in predicting visibility.
If you can aggregate the data, I'm happy to do the analysis. At table in Excel would be great, with rows = observations and columns = variables. One column should be date, so we can examine temporal lags in the response of visibility to the environmental variables over a range of time scales. I'll PM you my email.
Dave