This is an informal work in progress on a continually developing hydrologic time series.  I plan to update, improve and revise this throughout the current year.  As other posts describe, the Otowi gage is a key stream flow monitor along the Upper Rio Grande Watershed (URGW) in North Central New Mexico and parts of Southern Colorado.  Please note that this data compilation does not claim to reflect hydroclimatologic or stream flow conditions outside of the URGW.  In addition, this is simply an informal post and has not been subjected to peer review or other technical feedback. 

The 1950s drought is the starting point I chose for this post.  Time series data extends further back in time and readers are encouraged to learn more by reviewing the actual USGS gages and related reports.

 

 

 

 

 

The time series as I build them now include simplifications and assumptions. These regard:

1.  Upstream reservoirs are not yet represented in this simple exercise.  The potential capacities of the reservoirs at times can be significant, equivalent to the total annual volume of flows past the Otowi gage.

2.  San Juan Chama Project (SJCP) flows represent the trans basin diversion.  Water is taken from the Upper Colorado River watershed (in the San Juan mountains) and transferred by tunnel to the Chama River watershed  which is tributary to the Rio Grande.  That flow component is accounted for in this exercise through records for the Azotea gage.   However this gage is missing some information after 2008 and so for those missing months I’ve populated with an average flow value.  Typically, SJCP flows run about 10% of total Otowi flows.

3.  The Closed Basin Project (CBP) is the product of pumping from a shallow aquifer underlying the Closed Basin into the Rio Grande within the Colorado side of the watershed.  Some discharge data here is also missing from the record and so later values here are based on extrapolations of published estimates.

4.  Colorado flows are defined here as the amount flowing past Lobatos gage, near the state line, after the CBP flows are accounted for.

5.  New Mexico Upper Rio Grande (NMURG) flows represent the flow total after the other sources have been accounted for.

6.  Pumping and other water diversions for irrigation from within San Luis Basin, Conejos flows (from New Mexico, into Colorado, then back to New Mexico via Rio Grande), and various other impacts (including carriage losses and evapotranspiration, gaining streams and losing streams) are not directly evaluated, but are assumed to be intrinsically captured by records at the selected gages.

As I progress on evaluations of stream flow data, the PDO continues to show real strength for areas relatively close to the Otowi stream flow gage in North Central New Mexico, and some diminishing strength to more distant gages.  I considered two additional stream gages for initial confirmation, both the relatively close Navajo gage and the relatively distant Gila river gage as shown in the next two images [1] (note that the second image is a close up of the black rectangular outline in the first image).

 

 

 

 

 

 

 

 

 

 

 

 

Next, here is a plot directly taken from a recent report by the US Geological Survey for the Navajo gage [2].

 

 

 

 

 

Clearly the pattern corresponds closely to that for the Otowi gage (see recent post).  Finally (for now), here is a chart I developed from the USGS stream gage for the Gila River site and related.[3]  The chart is suggestive of some PDO influence and yet not as clear as for the sites near/within the Upper Rio Grande.   ENSO may play a more distinctive role on the Gila region than it does to the north.  Other papers no doubt have  looked.  Mine is merely a blog here on work in progress.

 

 

 

 

 

Sources:

[1] annotations overlaid upon Aster DEM 30 m coverage from DEM Explorer at http://ws.csiss.gmu.edu/DEMExplorer/

[2] Falk, S.A., S.K. Anderholm, and K.A. Hafich, 2013, Water Quality, Streamflow Conditions, and Annual Flow-Duration Curves for Streams of the San Juan–Chama Project, Southern Colorado and Northern New Mexico, 1935–2010.  Scientific Investigations Report 2013–5005.  U.S. Department of the Interior, U.S. Geological Survey.    at http://pubs.usgs.gov/sir/2013/5005/

[3.1] USGS 09430500 Gila River near Gila, NM   also

[3.2] Otowi source: USGS 08313000 Rio Grande At Otowi Bridge, NM and PDO Sources:

[3.3]  Zhang, Y., J.M. Wallace, D.S. Battisti, 1997: ENSO-like interdecadal variability: 1900-93. J. Climate, 10, 1004-1020

[3.4]  Mantua, N.J. and S.R. Hare, Y. Zhang, J.M. Wallace, and R.C. Francis,1997: A Pacific interdecadal climate oscillation with impacts on salmon production. Bulletin of the American Meteorological Society, 78, pp. 1069-1079

 

I continue to comb through the Pacific Decadal Oscillation (PDO) index and the Upper Rio Grande Otowi gage data.  As a primary index of water supply (therefore drought) through a major swath of the southwestern United States, the Otowi gage can potentially be used to evaluate associated purported climate drivers such as the PDO and Greenhouse Gases (ghgs).

While trying different moving averages just for fun, I observed that when a four year trailing average is applied, three pronounced mini peaks of both the PDO and of the Otowi gage show up after 1980.  Those peaks can hardly be seen under longer moving averages, such as the 10 year average in my previous post on this topic.   Those peaks are also not as clear in finer-grained representations such as the moving 1 year average, or the raw data.

 

 

 

In any case, the Otowi gage – PDO correlation for the 4-yr average, as is the case for any moving average length or approach I have tried, remains high, over 0.7 in fact (see next figure below).

Since some reports claim a strong correlation between other drivers such as ENSO, AMO, and/or GHG emissions and the current southwest US drought, I decided to test those claims directly for a paper.  One preliminary result is shown below.

exploring correlations of candidate drivers with drought in New Mexico

 

 

*details of bottom plot development:

1.   After the normalization procedure (searching for the max, and the min, calculating the resulting total span, then subtracting the min from each individual value and dividing that result by the maximum span) each data set has its maximum value = 1 and its minimum value = 0.   Given normalization, each series becomes dimensionless.

2.  In calculating the trailing 4 year moving average, I worked from original monthly data .   That led to a smooth time series that still covered every monthly value (except now a 4 year trailing average was assigned at every monthly value). Finally I selected the first of each year for this plot set.