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Welcome to Kansas, the bastion of how not to run a state, but claim things are just dandy.  I noted in a prior blog that Kansas has no reserves.  And apparently a $350 million deficit in 2016, a continuing trend for a number of years now.  And bigger deficits to come.  Kansas is the poster child of why cutting taxes a lot does not work.

How did they get here?  The state governor and legislature decided that cutting taxes spurs economic growth.  So if you cut a lot of taxes, you get lots of growth. They cite the Laffer curve, a  totally discredited economic tool drawn on the back of a napkin  by Arthur Laffer at a 1974 dinner to argue why Gerald Ford should not raise taxes.  On the face of it it makes no sense but that has not stopped supply side politicians from using it for nearly 40 years  to cut taxes.  The problem, it is wrong.

Cutting taxes does not spur enough economic growth to make up for the loss in taxes when you go down the Kansas role.  If you s cut them too much, it is really hard to raise them if you run short.  The result is that  economic growth in most of Kansas will be stunted for years due to the lack of investment in Kansans.  Now you would think that Kansans would be up in arms about the poor stewardship by elected officials. But no.  See if you get constant bad news, just stop reporting revenues and deficits.  No news is good news right?  Welcome to Kansas!

http://www.governing.com/topics/finance/gov-kansas-connecticut-budget-news.html


The troubling aspect of that is that Governing magazine reports that many state are likely to see less revenue in 2017 vs 2016.  Governing‘s analysis of projected 2017 budget data from the National Association of State Budget Officers shows shows states now have a median 4.9 percent of annual expenditures saved for the fiscal year, down from 5.1 percent the previous year.  Illinois, Nevada, New Jersey and North Dakota have no reserves as of 2017.  They add to Kansas, Oklahoma, Arkansas, and Montana who had no reserves last year.  And Alaska that is burning though theirs.  Economic and tax policies are to blame.  The Kansas solution to cut taxes to create economic growth has not worked.  The state continues to get farther behind and it is becoming harder to pretend all is well.  Having no reserves is a crazy bad idea.  It is hard to explain just how crazy bad this idea is – it means that if a negative economic issue occurs, these states are in huge trouble unless they start cutting education and other essential services.  The best way to get out of a budget hole is not cutting education – the one thing needed to dig out and attract new economic activity.  Clearly these officials did not learn from 2008-2011 when there reserves were depleted to address the economic downturn. That makes no sense and dooms their residents to a repeat of 2009/2010, only worse.

 


The reliability of the assets within the area of interest starts with the design process in the asset management plan. Decision-making dictates how the assets will be maintained and effective means to assure the maximum return on investments. Through condition assessment, the probability of failure can be estimated. Assets can also fail due to a growing area that may contribute to exceeding its maximum capacity. Operation and maintenance of the assets are important in reassuring a longer life span as well as getting the most out of the money to be spent. Prioritizing the assets by a defined system will allow for the community to see what areas are most susceptible to vulnerability/failure, which assets need the most attention due to their condition, and where the critical assets are located in relation to major public areas (hospitals, schools, etc.) with a high population.

So what happens when conditions change?  Let’s say sea levels are rising and your land is low.  What would the potential costs be to address this?  Better yet, what happens if it rains? We looked at one south Florida community and the flood stage for each based on 3 storm events: the 1:10 used by FDOT (Assumes 2.75 inches in 24 hours), the Florida Building Code event that includes a 5 in in one hour event (7 in in 24 hrs), and the 3 day 25 year event (9.5-11 inches).

Of no surprise is that the flooding increases as rainfall increases.  Subsequent runs assumed revisions based on sea level rise. The current condition, 1, 2 and 3 ft sea level rise scenarios were run at the 99 percentile groundwater and tidal dates and levels.  Tables 2-5 depict the flood stage results for each scenarios.  The final task was designed to involve the development of scenarios whereby a toolbox options are utilized to address flooding in the community.  Scenarios were to be developed to identify vulnerabilities and cost effectiveness as discussed previously.

The modeling results were then evaluated based of the accompanying infrastructure that is typically associated with same.  A summary of the timelines and expected risk reductions were noted in the tables associated with storm and SLR scenarios.  This task was to create the costs for the recommended improvements and a schedule for upgrading infrastructure will be developed in conjunction with staff.  Two issues arise.  First, the community needs to define which event they are planning to address and the timelines as the costs vary form an initial need of $30 million to over $300 million long-term.  Figure 1 shows how these costs rise with respect to time.  The long-term needs of $5 million per 100 acres matches with a prior effort in Palm Beach County.

SLR costs

Figure 1  Summary of Costs over the 3 ft of potential sea level Rise by 2011, under the 3 storm planning concepts.


The average is 4% of visible infrastructure is in poor condition.  Actually 4-6% depending on the municipality.  And this was visible infrastructure, not buried, but there is not particular reason to believe the below ground infrastructure is somehow far worse off.  Or better.   That 4-6% is infrastructure that needs to be fixed immediately, which means that as system  deteriorate, there is catch –up to do.  The good news is many of the visible problems were broken meter boxes, damaged valve boxes, broken curbs and broken cleanouts- minor appearing issues, but ones that likely require more ongoing maintenance that a water main.  And the appearance may be somewhat symptomatic – people perceive that the system is rundown, unreliable or poorly maintained when they see these problems.  It raises a “Tipping Point” type discussion.  “Tipping Points” Is a book written by Malcolm Gladwell that I read last year (great book – my wife found it in a book exchange for free in Estes Park last summer).  It was along a similar vein of thought as the Freakanomics books – the consequences of certain situations may be less clear than one thinks.  The Tipping point that is most relevant is crime in New York in the early 1990s after Bernard Goetz shot several assailants in the subway.  The problem was significant and the subways were thought to be among the higher risk areas.  The new police chief and Mayor decided that rather that ignore the petty crimes (like many large cities do), they would pursue those vigorously.  So fare hopping on the train and the like were challenged immediately.  They decided that no graffiti would be visible on the subways and cleaned cars every night to insure this remained the case.  Cars with graffiti were immediately removed from service.  New subway cars were ordered.  Pride and public confidence improved.  Crime dropped.  The impact of their efforts was that people recognized that criminal behavior would not be tolerated and fairly quickly criminal activity decreased.  It was a big success story, but the underlying reasons were less discussed, but easily transferrable to our infrastructure.  If we have broken valve boxes, meters, cleanouts, storm drains etc., the same perceptions of a rundown community rise.  Rundown communities lead to a loss of public confidence and trust and pride.   And none of those help our mission or our efforts to increase infrastructure spending.  4% might not look like much, but it can drastically change the perception of the community.  So let’s start to fix those easy things; and document that we did in our asset management programs.

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How many utilities have a 3D map of their infrastructure?  Not many I bet.  But FAU does.  Here is a recently completed project we did with students and the Facilities Maintenance staff at FAU (costs involved).  They needed better mapping and will tie this to their work order system.  It was an excellent opportunity for two groups within one organization that otherwise seem to have little in common wot work toward a great project.  We will be inputting this data into an online asset management system this summer along with some data for Dania Beach so they will have a portion of their utility system in 3D also.  This is part of a tiny project we did for their downtown area.

GIS is a powerful tool and one utilities should embrace wholeheartedly.  There is so much more than mapping to do.  Data gathering in critical, but with Leica and Trimble units, a lot of data can be gathered easily.  LiDAR can be expensive, but the value is tremendous.  You can see that the FAU system is laid on a 3D LiDAR topographic map (6 in vertical accuracy).  Asset condition assessments were also done concurrently, which adds a lot of information to the system (all assets were also photographed and linked).  Drawing files can be downloaded and extruded from 2D to 3D. Engineers know GIS or can learn it, which makes a fully expanded GIS system for the utility easy to derive if the time is spent.  This is a valuable tool when linked to work orders and asset management programs.

So is your utility in 3D?  Capture

 


Here is an example of getting to a condition assessment with limited data using power point slides.  Note that where there are categorical variables (type of pipe for example), these need to be converted to separate yes/no questions as mixing.  Categorical and numerical variable do not provide appropriate comparisons = hence the need to alter.  Take a look – but the concept is to predict how well this model explains the break history on this distribution system.  Call me and we can try it on yours….

Step 1  Create a table of assets (this is a small piece of a much larger table).

Asset Dia
water main 2
water main 2
water main 2
water main 2
water main 4
water main 6
water main 6
water main 6
water main 6

 

Step 2  Create columns for the variables for which you have data (age, material, soil type, groundwater level, depth, traffic, trees, etc.)

 

Asset breaks in 10 year Dia Age soil traffic Trees depth pressure material Filed estimate of cond.ition
water main 17 2 45 1 1 2 1 55 4 3
water main 11 2 45 2 1 2 1 55 4 3
water main 12 2 45 1 1 2 1 55 4 3
water main 10 2 45 1 1 2 1 55 4 3
water main 2 4 50 1 1 2 1 55 1 2
water main 3 6 60 2 2 2 1 55 1 2
water main 1 6 60 2 2 2 1 55 1 2
water main 1 6 60 2 2 2 1 55 1 2
water main 0 6 20 1 1 2 1 55 3 1

 

Step 3  All variables should be numeric.  So descriptive variables like pipe material need to be converted to binary form – i.e. create a column for each material and insert a 1 or 0 for “yes” and “no.”

Step 4 Run Linear regression to determine factors associated with each and the amount of influence that each exerts.  The result will give you a series of coefficientcoefs:

Step 5 – Use this to predict where your breaks will likely be in the next 5-10 years.

Pred breaks

The process is time consuming but provides useful information on the system.  It needs to be kept up as things change, but exact data is not really needed.  And none of this requires destructive testing.  Not bad for having no information.


An asset management program should be developed accordingly to the client’s goals and objectives. It consists of determining the selected area of study, type of system and the quality of data used for evaluation. Before a condition assessment can be determined, an inventory of assets needs to be established – maps, etc. are helpful.  So now you have a map of your water and sewer system and you want to develop a useful system for asset management.  Depending on the accuracy wanted, the data can be gathered in many ways ranging from onsite field investigation which could take a lot of time, to using existing maps, using maps while verifying the structures using aerial photography and video, or field investigations. But most local governments still lack data.  You cannot dig up pipe, or do a lot of destructive testing on buried infrastructure.  So what to do?

The reality is that you have a lot more data than one thinks.  For one thing, most utilities have a pretty good idea about the pipe materials.  Worker memory can be very useful, even if not completely accurate.  In most cases the depth of pipe is fairly similar – the deviations may be known. Soil conditions may be useful – there is an indication that that aggressive soil causes more corrosion in ductile iron pipe, and most soil information is readily available.  Likewise tree roots will wrap around water and sewer pipes, so their presence is detrimental.  Trees are easily noted from aerials.  Likewise road with truck traffic create more vibrations on roads, causing rocks to move toward the pipe and joints to flex.  So with a little research there are at least 5 variables known.  If the break history or sewer pipe condition is known, the impact of these factors can be developed via a linear regression program.  That can then be used as a predictive tool to help identify assets that are mostly likely to become a problem.   We are working on such an example now, but suspect that it will be slightly different for each utility.  Also, in smaller communities, many variables (ductile iron pipe, pvc pipe, soil condition…) may be so similar that differentiating would be unproductive.  That also remains to be seen, which brings up another possible variable- the field perception – what do the field crews recall about breaks?  Are there work orders?  If so do they contain the data needed to piece together missing variables that would be useful to add to the puzzle?

After all we want to avoid this before it happens….

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