Weekly Climate, Water and Drought Assessment of the Upper #ColoradoRiver Basin

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Click here to read the current assessment. Click here to go to the NIDIS website hosted by the Colorado Climate Center.

Water supply good, storage space short — La Junta Tribune-Democrat

Lower Arkansas River near Bent
Lower Arkansas River near Bent

From the La Junta Tribune-Democrat (Bette McFarren):

The Lower Arkansas Valley Water Conservancy District maintains its position on current issues with flood control in Colorado Springs but acknowledges not much storage space available for water.

Roy Vaughan of the Bureau of Reclamation reported as of Aug. 16, 230,980 acre-feet are stored in Pueblo Reservoir. Turquoise, Twin Lakes and Pueblo Reservoir are all fuller than they were last year at this time.

Jack Gobel and Henry Schnable of Lamar reported the Colorado Water Protection and Development Association and possibly other well associations will go together to talk with lobbyist and try to get more water storage, for the benefit of well farmers.

Henry Schnable is interested in creating a role for John Martin Reservoir in the storing of water for areas nearer that reservoir.

State Senator Larry Crowder reported he is withdrawing his support for a dam on Fountain Creek because local constituents oppose it.

What Did All That Rain Really Mean For Colorado? — 5280.com

Upper Colorado River Basin May 2015 precipitation as a percent of normal
Upper Colorado River Basin May 2015 precipitation as a percent of normal

From 5280.com (Dahlia Singer):

That means Coloradans have a lot of reasons to celebrate. “Statewide, we’re in the best situation we’ve been in since 2011,” says Taryn Finnessey, a climate change risk management specialist with CWCB. “The rains really have not only alleviated drought conditions, but, in most portions of the state, they’ve eliminated them. And as far as reservoirs, we’re doing great. We’re better off than we were last year in all portions of the state.” Per the USDA Natural Resources Conservation Service, Colorado reservoir storage was at 117 percent of average at the end of July, the most recent info available; soil moisture is up, which typically makes farmers and ranchers do a happy dance; and cooler weather has also helped reduce demand on our water resources.

Of course, recent news that “this year’s El Niño weather pattern could be the most powerful on record” leaves just one question on the tip of Coloradans’ tongues: What’s that mean for the upcoming ski season? “An El Niño year does typically mean more moisture for Colorado,” Finnessey says, “But I don’t know that we have the information yet to determine whether or not that’s going to fall in the mountains or along the Front Range.”

Unfortunately, Klaus Wolter, a local climate scientist, says Colorado’s highest elevations typically don’t benefit from the system. “It’s the flip side of El Niño,” he says. But it’s not all bad news: “Typically what happens is you go through the winter and if you come out just slightly below normal, which is a very typical outcome, there is a good chance you might still play catch-up in the spring.

What risk do Larimer County waters face from mining? — the Fort Collins Coloradoan

LegacyMineWorkCDPHE

From the Fort Collins Coloradoan (Jacy Marmaduke):

A map released last week by the Colorado Division of Reclamation, Mining and Safety shows the majority of the mines clustered in the Silverton area and the Summit and Clear Creek county areas.

The closest leaking mines to Fort Collins are a Boulder County cluster of seven, four of which aren’t undergoing active water treatment. There are about 23,000 abandoned mines in Colorado, according to the state geographical survey.

The map also charts mine-related impaired streams — waterways with levels of potential mining-related minerals that surpass state standards. Red lines on the map denote mine-related impaired streams.

The map shows a short red section on the North Fork of the Poudre River and a lot of red lines around the Big Thompson River in the southern part of the county.

The North Fork of the Poudre is red because it contains higher-than-normal levels of lead, cadmium and copper. The Big Thompson is red because of higher levels of the same minerals, plus selenium and zinc as well as low pH levels indicating acidity.

But it’s not as bad as it sounds, said Nicole Rowan, watershed section manager with the Colorado Department of Public Health and Environment.

“It could be mining or it could be the geology of the area,” Rowan said. “This is one of the most mineralized areas in the world. That’s why people mine here.”

Federal law requires the state to assess its water quality and report the results. The map draws from the state’s last complete report in 2012. Of the Larimer County waterways included on the map, three segments are ranked high priority — meaning they’re a source of public drinking water or contain an endangered or threatened species with no plan in place to protect it.

These segments are:

•Big Thompson River’s Fish Creek below Mary’s Lake, due to low pH levels

•Big Thompson River from Rocky Mountain National Park to Home Supply Canal Diversion due to sulfide, copper, cadmium and zinc levels as well as high temperature

•Big Thompson’s North Fork due to copper levels

Zack Shelley, program director of the Big Thompson Watershed Forum, said the metals in the Big Thompson probably aren’t results of mining. The copper levels in particular are high because federal and state government used to treat algae in the river with copper sulfide, Shelley said. Other potential sources of metal in the Big Thompson include abandoned landfills, forest fires and septic systems in the area.

“To my knowledge, I don’t see a human health risk,” Shelley said, but the metals do present risks for fish and other aquatic life in the river.

The Big Thompson Watershed Forum will present new data on the river’s water quality next month.

Colorado Water Congress summer conference recap: Ag nutrient program in the works

Blue-Green algae bloom
Blue-Green algae bloom

From the Sterling Journal-Advocate (Marianne Goodland):

The Colorado Water Congress last week took a look at the Michigan Agriculture Environmental Assurance Program, known as MAEAP. It’s a program that has had limited success in other states, largely dependent on whether it gets support from the ag community.

According to Joe Kelpinski, who runs the program for the Michigan Department of Agriculture and Urban Development, the ag industry is being pressured to do “something” to demonstrate that farms and related businesses are being responsible about water quality. “We were under tremendous pressure from the environmental movement, especially for livestock,” Kelpinski told the audience at the CWC’s Vail summer conference.

That’s where MAEAP comes in. About 15 years ago, a coalition of farmers, commodity groups, state and federal agencies, and conservation and environmental groups in Michigan designed the voluntary program to minimize agricultural pollution risks. But it had low participation until 2011, when the state legislature added incentives to encourage more farmers to be involved.

The program has three phases: education, on-farm risk assessment and third-party verification. Producers are required to attend a state-reviewed meeting in environmental best management practices and conservation.

In the second phase, state technicians work directly with the farmers to provide technical assistance, conduct a risk assessment on the operation; whether it’s farm, livestock, cropping or forestry/wetland and habitat. The technician walks the operation with the producer, looking at pesticide or fertilizer storage, soil and water erosion and wells, or location of wetlands, for example. The assessments are confidential. The technician then scores the assessment and comes up with an improvement or action plan, and what to do to mitigate risks so the third phase, verification, can take place.

The verification is done by a third-party verifier. Kelpinski said environmentalists wanted the third-party verification instead of self-certification. A verification then lasts for five years.

According to the program’s website, verification reduces legal and environmental risks through use of proven scientific standards, balances efficient production and sound environmental practices; and helps ensure safe storage of fuel, fertilizer and pesticides. Verification is also a tool for local emergency responders. Technicians develop emergency plans, using aerial photographs, which help first responders know where fuel or fertilizer is stored when there’s a fire or other emergency situation.

With these three systems, “we can look at farms holistically,” Kelpinski said.

But buy-in from the agriculture industry is essential, he added. “If you don’t have industry support, it will fail,” and he noted that other states have tried without having buy-in from the agricultural industry, only to see their programs flop. Michigan’s program now has about 11,000 participating farms, out of 52,000 total in the state. Kelpinski said that last year, sediment runoff was reduced by 357 tons, phosphorus levels have dropped and 566,000 acres have approved pesticide management plans. And once the incentives were added in 2011, the department went from 150 verifications per year to about 500.

The incentives included eliminating fines for accidental discharges, which Kelpinski called “the golden carrot.” There are also incentives related to watershed management.

Cindy Lair of the Colorado Department of Ag has had a proposal waiting for a similar program for several years, and believes the time has come. “But we won’t do anything without complete support of the industry,” she said. “Farmers are asking for details and for certainty.” She’s hoping for dialogue between Colorado ag producers and those in other states where this program has been successful. “It would take the scare and fear out of it,” she said. Ag producers feel vulnerable about this, but there are benefits, too, she said, such as getting higher ranking for certain federal programs that provide technical and financial assistance on conservation practices. She believes a pilot program might be the best way to get this started.

“Municipalities have already been working on their side of nutrient pollution,” Lair explained. “It’s appropriate for the ag industry to show some goodwill and activity in this area.”

A group in Colorado is already looking at something similar to MAEAP. The Colorado Agricultural Nutrient Taskforce started last January, in response to a new regulation from the Colorado Water Quality Monitoring Council, part of the state’s water quality control division. Regulation 85 looks at nutrient pollution resulting from excess nitrogen and phosphorus, a leading cause of degradation of U.S. water quality, according to the council. Reg 85, as it is known, seeks to establish scientifically-based nutrient regulations and allow those who discharge those chemicals time to develop plans to begin treating both nitrogen and phosphorus. The regulation was passed in March 2012, with a ten-year waiver for ag on nutrient control.

Mary Gearhart of Brown and Caldwell is facilitating the taskforce. She explained that in 2022, if there has been no substantial progress by the ag community in improving water quality, the commission will consider whether to regulate agricultural runoff and discharge. “It’s a touchy subject,” Gearhart noted. The taskforce is looking at a modest assurance program, not as substantial as Michigan, she said, adding that a lot of farms are doing best practices but there isn’t a formal documentation or verification process.

Former ag Commissioner Don Ament of Iliff is a member of the taskforce. Water quality is becoming more of an issue, he told this reporter. “Agriculture is very willing to step up to the plate and do their fair share. It just needs to be science-based,” he explained. “I want ag to be in the front, being a part of the solution — but a scientific one, not an emotional one.”

Reductions in ag runoff have improved dramatically, Ament said. “We can make the case that we’re an environmentally-sound partner. We can demonstrate a lot of that already.”

And how will the legislature react? Sen. Jerry Sonnenberg, R-Sterling, told this reporter he is hesitant to back yet another program with a permit or registration process for a farmer to do what they’re already doing. “We’ve become a little gun-shy of giving any information to government on how we do business,” he said. “The vast majority are doing things correctly and doing things that are environmentally sensitive, because they have to leave the land better tomorrow than they did today, or it doesn’t provide for their families.”

NOAA: One forecaster’s view on extreme El Niño in the eastern Pacific

From Climate.gov (Ken Takahashi):

El Niño was first identified by fisherman in the late 19th century off the coasts of Peru and Ecuador (Carranza, 1892; Carrillo, 1893). Unusually high Pacific Ocean temperatures depressed the region’s fisheries, and intense rainfall led to coastal flooding. The most extreme El Niño events, in terms of the surface warming in the eastern and central Pacific, occurred during 1982-1983 and 1997-1998. During these two events, Piura, a city in the coastal desert in northern Peru, experienced annual rainfall amounts equivalent to the other 40 rainiest years combined! The economic loss due to extreme weather in Peru during those events is estimated as 7% and 4.5% of its GDP, respectively (CAF, 2000).

The desire to help society prepare for those kinds of disruptions has led to great scientific advances in understanding El Niño. Still, one of the most frustrating things about El Niño for forecasters is why it doesn’t have the same impacts in the same places every time. In the past decade, the scientific community began to focus research on the diversity or flavors of El Niño and La Niña (the cold phase) as a possible explanation for the variability of impacts.

ENSO flavors map via NOAA
Pattern of sea surface temperature deviation from average (°C) associated with a unit value of the C index (top) and the E index (bottom), based on Takahashi et al., 2011. The Niño 3.4 and 1+2 regions are indicated as dashed boxes. Most El Niño events can be described as a combination of these two patterns. Image from Ken Takahashi

In particular, they’ve focused on where along the equator the surface warming is largest, which does affect how El Niño and La Niña impact the global climate (Larkin & Harrison, 2005). Especially in Peru, El Niño can lead to very different rainfall impacts depending on whether the warming occurs in the eastern (wetter) or central Pacific (drier) (Lavado-Casimiro & Espinoza, 2014).

There are many different ways of classifying El Niño, but it is most common to measure it using sea surface temperature (SST) anomalies (departures from average conditions). In order to classify the different types of El Niño, however, we need at least two indices or time series (Trenberth and Stepaniak, 2001). Some colleagues and I introduced an E index and a C index (data here), which isolate the SST changes in the Eastern and Central Pacific, respectively, that are unique to each region (Takahashi et al, 2011).

How different are the extreme El Niño events from the regular ones?
Usually the SST warming in the central and eastern Pacific overlap, or correlate, during El Niño. But during the two “extreme” El Niño events (1997-98 and 1982-83), the warming in the east, near the coast of South America was much stronger than the warming farther west in the central Pacific (as can be seen in the left panel below).

December-February average eastern and central Pacific sea surface temperature deviations from average: (left) Niño 1+2 (east Pacific; on x-axis) and Niño 3.4 (central Pacific; on y-axis); and (right): E (east Pacific; x-axis) and C (central Pacific; y-axis) departures from average. The year corresponding to December is indicated. Extraordinary El Niño events are indicated in red, while other eastern Pacific and central Pacific El Niño events are in green and blue, respectively. Gray indicates non-El Niño years. In both graphs, the dotted lines are an attempt to summarize the relationships shown by the dots, and the abrupt change of the slope of the dotted line highlights the uniquely different behavior shown by the 1982 and 1997 cases, and to a much smaller extent the 1972 case
December-February average eastern and central Pacific sea surface temperature deviations from average: (left) Niño 1+2 (east Pacific; on x-axis) and Niño 3.4 (central Pacific; on y-axis); and (right): E (east Pacific; x-axis) and C (central Pacific; y-axis) departures from average. The year corresponding to December is indicated. Extraordinary El Niño events are indicated in red, while other eastern Pacific and central Pacific El Niño events are in green and blue, respectively. Gray indicates non-El Niño years. In both graphs, the dotted lines are an attempt to summarize the relationships shown by the dots, and the abrupt change of the slope of the dotted line highlights the uniquely different behavior shown by the 1982 and 1997 cases, and to a much smaller extent the 1972 case

In fact, the values of the central Pacific Niño 3.4 index were only slightly greater than those of the 1972-1973 event, but the values were around 3 times greater in the eastern Pacific Niño 1+2 region. These geographic differences are also clearly depicted using the E and C indices (right panel), with very high E values during the two extreme El Niño events. This difference in central versus eastern Pacific warming during extreme events compared to regular ones is also evident in monthly C and E index values (see graphs below).

(top) Central Pacific (C) and (bottom) eastern Pacific (E) monthly SST indices during selected El Niño events and the current year. The estimated values for August 1-19, 2015, are indicated with an open circle. Graph by Ken Takahashi
(top) Central Pacific (C) and (bottom) eastern Pacific (E) monthly SST indices during selected El Niño events and the current year. The estimated values for August 1-19, 2015, are indicated with an open circle. Graph by Ken Takahashi

We found that this is because, once the normally cooler eastern Pacific warms enough for heavy precipitating storms, El Niño shifts to a faster gear: the Walker circulation shifts dramatically towards the eastern Pacific and the processes that lead to El Niño growth strengthen threefold (Takahashi & Dewitte, 2015).

Predicting extreme El Niño this year
If the physics of extreme El Niño events are different, then they should sometimes be analyzed separately from the rest; this also makes sense considering their large societal importance. Of great urgency this year: Are our scientific understanding and models good enough for the prediction of an extreme El Niño?

Although climate models provide objective predictions, models are far from perfect. They have common errors (particularly large in the eastern Pacific) and misrepresentation of slower changes in SST (decadal or 10-year timescales) or SST trends (2). By considering a collection of different models, or a multi-model ensemble (3), we hope that the errors cancel out among the different models. However, there are errors common to all models, such as the warm and rainy tendency in the cold and dry southeastern Pacific.

And we know that the models have a harder time making accurate predictions in the eastern Pacific. In particular, the models do not predict large enough SST anomalies in the far eastern Pacific during the extreme El Niño events (Takahashi et al, 2014). Even so, many models are predicting a strong El Niño in the central and eastern Pacific this year, similar to (or stronger than) 1972-1973, 1982-1983, and 1997-1998.

In addition to models, forecasters have other tools available, such as observational predictors and ideas based on physical common sense. The limitation in this case is the small number of events, with only two well-observed extremes, coupled with the fact that one El Niño is never a perfect mirror image of another El Niño, not even the extremes.

This year the ocean has accumulated a substantial amount of heat, a necessary condition for El Niño, but this does not tell us whether El Niño will be extreme or not in the eastern Pacific (Takahashi & Dewitte, 2015). Again, an extreme El Niño is a very different beast from the others in terms of impacts on weather and wildlife in the coastal regions of northern Peru and Ecuador, so El Niño strength is not just a detail.

One feature we found potentially useful is that if the trade (easterly) winds in the central Pacific become very weak around August, this allows the eastern Pacific to warm up a few months later, possibly enough to trigger strongly enhanced precipitation that could help El Niño become extreme (Takahashi & Dewitte, 2015). This did not happen in 1972, which is perhaps why that El Niño did not become as extreme.

Difference from average sea surface temperature (colors) and difference from average of surface wind stress (arrows showing direction and strength by the length of the arrow line) in August 1982 (top) and January 1983 (bottom). The red box outlines the averaging region for the wind stress predictor for judging the probability of occurrence of an extreme condition in the Eastern Pacific 5 months later in January. Images adapted from Ken Takahashi
Difference from average sea surface temperature (colors) and difference from average of surface wind stress (arrows showing direction and strength by the length of the arrow line) in August 1982 (top) and January 1983 (bottom). The red box outlines the averaging region for the wind stress predictor for judging the probability of occurrence of an extreme condition in the Eastern Pacific 5 months later in January. Images adapted from Ken Takahashi

This year we are putting this tool to the test. So far, the trade winds in August have not weakened as much as in 1997 but more than in 1982, indicating the probability of an extreme El Niño in 2015-2016. However, the eastern Pacific (E index) has been tracking the substantially weaker 1972 event and it would have to surge upwards, as in 1982, to become extreme (Fig. 3b). A quite different outcome could be that E keeps following 1972, remaining below the extreme threshold, while the central Pacific continues to warm into perhaps a larger version of the 2009-2010 El Niño (see bottom graph of Figure 3).

Predicted departure from average westerly wind stress (see footnote 1) in August (x-axis) vs. the eastern Pacific warming (E) in the following January (y-axis). Observations are in red, while the CM2.1 model ensemble forecasts (repeated model runs with different starting conditions) are grey, with their 10%, 50%, and 90% percentiles shown by the black sloping curves to summarize the positions of most of the gray dots. Adapted from Takahashi & Dewitte (2015)
Predicted departure from average westerly wind stress (see footnote 1) in August (x-axis) vs. the eastern Pacific warming (E) in the following January (y-axis). Observations are in red, while the CM2.1 model ensemble forecasts (repeated model runs with different starting conditions) are grey, with their 10%, 50%, and 90% percentiles shown by the black sloping curves to summarize the positions of most of the gray dots. Adapted from Takahashi & Dewitte (2015)

As you can see, the chance of an extreme El Niño in the eastern Pacific is not straightforward to assess (5). Several factors will affect such a estimation. This year’s El Niño is already different from anything seen before. Furthermore, the rules of how the climate system works do not stay the same throughout time (e.g. climate change may affect El Niño), so statistical relationships found in a previous period might not be valid anymore.

Also, it is possible that random factors outside of the El Niño system could go against El Niño to keep it below the extreme threshold. Although several climate models are predicting a very strong El Niño, due to their common errors, we cannot fully trust them. Perhaps the only reliable rule is that El Niño can surprise us, and this year could be yet another example.

Anthony Barnston, lead reviewer

Footnotes
(1) The wind stress is based on the wind speed squared. Here, we are talking about the departure from average of the westerly wind stress. When the trades winds (winds from the east) become weaker, as they do during an El Niño event, the departure from average of the westerly wind becomes positive (because weaker trade winds mean stronger westerly winds, even if the actual wind is still from the east, but less strong than average). Then we square that departure from average. For example, if the westerly wind is usually -9 miles per hour, and now it is only -2 miles per hour, then the departure from average of the westerly wind is +7 miles per hour. And the departure from average of the westerly wind stress is the square of 7 miles per hour, which is 47 miles per hour.

(2) Changes in the entire North Pacific plus tropical Pacific on an approximately 10-year time scale, known as decadal variability, can change the backdrop behind El Niño and La Niña and encourage one of these at the expense of the other. As it turns out, much of the advances in El Niño science took place during a warm Pacific decadal phase, but we have been in a cold phase since approximately the year 1999 (although there are hints that we might be switching back to warm; we need to wait another year or two to make sure). Which decadal phase we are in can subtly, but noticeably, affect the strength of El Niño or La Niña, and our prediction models may not adequately take this decadal variability into account.

(3) A multi-model ensemble refers to the use of more than one model to make a forecast of deviations from average of climate or of sea surface temperature. Because each single model has its own biases or peculiarities, averaging the forecasts of several models tends to cancel these out and deliver a forecast having fewer specific biases. If several models have common biases, however, using more than one model does not help as much.

(4) The 1953-54 El Niño (leftmost green dot in both panels) had its largest warming in the eastern Pacific around mid-1953, but in DJF the eastern Pacific became relatively cool.

(5) Despite the large uncertainties in the eastern Pacific, Peru’s ENFEN will produce an estimate of the probabilities of the various strengths of El Niño, including the extreme type, later this week.