Tag Archives: stormwater
We recently completed our first revisions to the Training Plan for Water, Wastewater and Stormwater Utilities that we initially released in early November.
We’ve made some minor content changes based on feedback from water utilities, done some formatting clean up and also significantly reduced the file size by optimizing the graphics in the document. So it should be much easier to download and email the plan now. You can download the updated Training Plan below.
Over the past few years, we’ve seen water and wastewater utilities increasingly recognize that they can leverage GIS to reduce fuel consumption in their fleet vehicles and more efficiently carry out their work through route optimization.
No doubt the increased interest in routing solutions for water utilities is driven by 3 factors, first that regulated water and wastewater utilities have a fixed rate structure which leads to rigid budgets. When the cost of things like fuel, water treatment chemicals, electricity, raw construction materials, etc. fluctuate than a utility has to look at its entire operations for place where cost can be reduced to keep budgets balanced.
The second factor, which arguable was the wake up call to water and wastewater utilities, was the fuel price spike around 2 years ago. When fuel prices were spiking, ESRI had an exponential rise in interested from water and wastewater utilities to optimize their routing. That interest has not subsided with the decline in gas prices. Many forward thinking utilities are using the economic pullback to prepare for when full prices do rise again in the future.
The third factor is that water utilities view themselves as stewards of the environment. The quality of our source water supplies is directly linked to the health of our environment, and many water utilities are taking proactive steps to be more environmental friendly. We’ve heard a lot of talk about the water-energy nexus recently and also about carbon footprints. Water utilities can reduce their overall energy usage (in the form of less fossil fuel usage) through fleet optimization and also can reduce their carbon footprint.
From discussions with ESRI’s water utility customers, we increasingly hear about the need to optimize vehicle routing for maintenance activities for fixed meter reading routes and for maintenance activities. For the purpose of our discussion, we’ll lump workorders, off cycle final meter reads, customer service visits, in person billing dispute resolutions and emergency routing together as ad-hoc routing.
Whatever type of routing you are using, spatially, descriptively and temporarily accurate GIS data about the location of your assets and your customer locations (premise locations in particular), are critically important. More accurate destination information will yield better routing. We’ve seen a lot of technology demonstrations for utility routing, and one thing we’ve seen lacking in many utility routing solutions is the ability to route to an asset. The ability to route to an asset is often missing when routing solutions intended for the general public are proposed to utilities. For example, if a utility crew needs to turn off valve number V-2421 during an emergency, they need to be routed right to valve itself, not the nearest property with a valid address near the valve.
For utilities, route optimization isn’t just about the fastest way to get from point A to B to C. It’s also about optimizing the sequence of how you deliver your work. Meaning that it to be truly beneficial a route optimization solution needs to be able to do things like honor time windows, handle routing and work sequencing for multiple crews some of which have specialty equipment or knowledge, allow you to add more stops and reroute all of your field vehicle on the fly and be able to leverage you existing GIS asset and customer premise locations.
Meter Reading Routing
First, let’s examine fixed routing for meter reading. If your utility currently uses meters that require either proximity (drive by meter reading) or premise visits (manual reads), you’ve most likely created a fixed set of meter reading routes. If your utility has to visit a customer premise for routing meter reads, than your meter reading route probably include a mix of vehicle route and then on foot routes (this require multimodal routing).
We often hear from utilities that want to either optimize their existing routes because they are outdated or they want to establish formal routes for the first time. From experience, we view meter reading routing as a specialty application of GIS and we suggest that you work an ESRI business partner such as Routesmart who understand how to deploy ESRI technology to overcome some of the special challenges of both drive by and manual meter reading route optimization.
I use the term “ad-hoc routing” to describe routing for maintenance activities, emergency activities, customer service and bill resolution done on the customer premise, final meter reads that are off the normal meter reading cycle and inspections. I lump these activities together into the category of ad-hoc routing because these are not rigid routes like fixed meter reading routes.
Why do I consider maintenance routing to be ad-hoc routing when some of it is planned well in advance? Because even though you plan for maintenance proactively and track that in your CMMS or workorder system, if a utility sequences the work to be done, assigns to a crew and creates a route that is often done the day before or the day of the actual work happening. Utilities often mix in proactive work with reactive work (you didn’t plan ahead to do that task) into a crews daily work, so this is really ad-hoc routing. It’s done the day of or day before doing the work and you may also need to reshuffle this on the fly based on the events of the day.
ESRI has a powerful core technology solution (of course this can also be extended by our business partners) for routing. Our core solution is ArcLogistics.
A few things to keep in mind about route optimization
We often get asked how to quantify the return on investment (ROI) for route optimization. ESRI has recently released an ArcLogistics Cost Saving Calculator that you can plug in variable from your utility to estimate the ROI for ArcLogistics – http://roi.esri.com/costsavings2009/index.cfm
If you are selecting a new workorder, CMMS or EAM system think about how this will integrate with a GIS to enable route optimization. Your workoder system is where you will create and track your proactive and reactive maintenance activities, but when you allocate crews and dispatch work route optimization will help you become more efficient.
Like geocoding, route optimization relies on an underlying dataset to use for route generation. Make sure that if you are routing, you have the appropriate dataset with the accuracy level and routing capabilities that fit the business needs of your utilities. For example some datasets for routing are able to take into left hand turn restrictions, underpass clearances and road weight limits, those can be very important factors if you are moving large or heavy equipment around.
Think about who will be generating the routes. Do they need to be automatically generated, will someone create routes in a desktop application or will many people need to create routes (for themselves or others) with a web based or mobile application? Also think about whether field crews should be empowered to route themselves, that is really a business decision at a utility. In actuality, route optimization should be available to any system or employee that needs to optimize routes. So it is really part of enterprise GIS at water utilities.
Understand how you will share routes once they are created. Do you give field crews their daily routes and sequenced work orders on paper print outs or do you have computer in the field that you can use a mobile application like the ArcGIS Mobile or ArcLogistics Navigator to push routes to and enable turn by turn navigation. When looking at a route optimization solution, you should assess how you can disseminate the routes and use them around your utility.
Feel free to comment or share any experience you’ve had with route optimization at your utility.
We’ve decided to repeat our webcast that explored the Water Utility Resource Center and gave an overview of ESRI Enterprise License Agreements for water, wastewater and stormwater utilities. When we offered this webcast last month we had to 2 completely full sessions and hand a good number of people registered on a waiting list. So we thought it would be best if we gave everyone another opportunity to participate in these webcasts.
On the webcast we’ll briefly touch on the business drivers for water utility GIS and then demonstrate the templates currently available on the Water Utility Resource Center. We’ll than explore the ELA as an licensing mechanism for water utilities.
We’ll also have time to answer your questions at the end of the webcast. We had some excellent discussions about water utility GIS during our November webcasts, so we encourage you to bring your questions.
You can sign up for the December 2nd webcast here: http://events.esri.com/info/index.cfm?fuseaction=showSeminar&shownumber=13107
We’ve had a lot of great comments from the water utility GIS community saying that we should do water utility GIS focused webcasts more often. So starting in January 2010, we are also planning on doing a series of monthly webcasts focused on water, wastewater and stormwater GIS. We tentatively planning on a webcast focused on ArcGIS Water Distribution Capital Planning template in January. We’ll post more details shortly.
Whether you are implementing GIS in your water, wastewater or stormwater utility and creating a data model for the first time or you are updating your existing GIS datamodel, you will no doubt ask yourself this question –
How should I model my utility’s asset in a geometric network and why should I use a geometric network? You should model a Geometric networks can enable utility system tracing, error checking, and better productivity while editing.
But how should I build it. That one simple question spawns many sub questions. Should I use complex edges, what edge to junction or edge to edge rules should I implement? What are weights? Should I worry about cardinality? We get these questions or have this conversation all the time with utilities and partners.
Below, you will find information and some guidance to help you answer these questions. Also, we always recommend that you read through ESRI’s webhelp as a starting point on geometric on networks:
First, you will need to create your network. When creating your network, you have a few options. The most important are choosing which layers participate in the geometric network and what layers, if any, are sources or sinks.
So what layers should you include in your geometric network? Keep in mind that the geometric network should encapsulate how your distribution or collection systems actually operate. So include only layers that participate in the logic network – or to think of it another way the layers that include assets that determine how your collection or distribution system function.
These typically are mains, valves, fittings, hydrants, laterals, virtual lines, manholes, catch basins, etc. Since the geometric network should only contain layers that affect the network, a change in geometry or information can affect analysis on that network. Data like Leaks, or SCADA sensor locations, are operational data sets. It is showing some incident on the network or some value or reading of the network. So these operational layers should be included in the operations dataset and not in the geometic network.
In order to create a geometric network, you’ll need to have a feature dataset which contains all of the feature classes for that network. You’ll also need at least the ArcEditor level of ArcGIS Desktop. When prompted to build the geometric network from existing features or an empty network or to create an empty network, you’ll typically choose the first option.
After you determine the layers that should be part of your geometric network, you need to think about how you are going to model flow. When setting sources or sinks, make sure to only set one of these. This is critically important, and a mistake that we see all too often. Do not set one feature as source and another as sinks. You only need one and having both in a geometric network for water, wastewater or stormwater will lead to odd network behaviors. Typically the NetworkStructure feature class or similar feature class containing a relatively small number of points is used. While creating the network you don’t specify whether it is a source or sink just that it could be one or the other. This adds a field called AncillaryRole to any feature classes you specify. Later, in ArcMap you can set the value of this field for individual features to source, sink or none. These values can be used to establish flow direction for the non-looped portion of your network. You could instead choose to use the digitized direction of your lines to establish flow direction, in this case sources and sinks are not used.
After the geometric network has been created, you need to set up the core properties of the network.
Let’s first think about complex edges versus simple edges. This is an easy one to make a decision on. In a geometric network, a simple edge must be split at every junction, so every valve, manhole, fitting, etc, on an edge, splits that edge. Complex edges allow one segment to have many junctions on top of it and it does not require that segment to be split. And by split, I mean separate records in the geodatabase. Usually, complex edges only are used on your mains and laterals for water, sewer, and storm. This allows you to model your segments by the method defined by your utility – meaning that there is no standard industry definition for what a “pipe segment” is and we often see utilities making a conscious decision for how they want to define a pipe segment and use that definition across all of their operation and business systems. We have seen people model laterals as simple edges. Typically, simple edges are used here because the lateral and the connection point (meter, service connection) is a representation of the actual meter and lateral. The representation allows you to perform tracing through the network to the meter and connect the meter id to a billing or customer system.
Next we need to determine whether to set connectivity rules. Keep this in mind – if you set just one connectivity rule in your geometric network and wish to use the validation tools, then you need to set up all the rules. This can be a complex process to figure out how all your assets connect in every situation-. Despite being complex to implement and maintain, there are certainly large benefits to using connectivity rules.
Connectivity rules allow you to model the logic connection of your network. To support all connection types, you need to make sure your datamodel will support this. Connectivity rules can leverage a geodatabase design element called subtypes. Subtype allow more complex modeling of your data so that within a feature class, features are assigned to a subtype which may have different default values, different domains, and different connectivity rules than the other subtypes within that feature class. The example template geodatabase is simplified and doesn’t include any subtypes. This means that for connectivity purposes a fitting is just a fitting not a tee, bend, or cap. Likewise for connectivity purposes a lateral line is just lateral line not a hydrant lateral or service lateral. With a more detailed design which includes subtypes you can make more extensive use of connectivity rules. That is you could have a rule that says a hydrant must connect to a hydrant lateral line and that a hydrant lateral line must connect to one hydrant. You could also specify that a hydrant feature be added by default at the free end of a hydrant lateral and that a tap fitting be placed automatically where the lateral line connects to the main. You could set up a similar set of rules for service lines and meters.
Within connectivity rules, there is an option to set cardinality. So you can go beyond just how your assets can connect and you can define how many assets can connect to each other. Let’s think about fittings again, with subtypes for fittings, you could specify that a tee fitting must connect to 3 pipes, an end cap to 1 pipe, etc. So you can see that to model proper cardinality, you need to model your data in a way to properly define the number each asset can connect to.
With a simple data model, like the data model that is included with the Water Utility Resource Center templates, you can still set a connectivity rule if desired. For instance, you can specify that wLateralLine should connect to a wMain and by default a fitting must be added.
Some of the Edit Tools in the Network Editing Template are designed to assist with automation and basic connectivity testing without the use of geodatabase connectivity rules. For example, the connectivity checker tool merely looks at feature types and makes sure they logically connect to each other. So if you want to use connectivity to enhance your editing experience, you can do so, without modeling connectivity to represent every asset’s connectivity restrictions in the geodatabase. For instance, you can model a hydrant to a lateral to a main and not worry about modeling everything, you will just have some connectivity errors when you validate, which you can choose to ignore.
Next, you will see an option for setting weights. Geometric network weights can be used in two ways. Weights can be a filter, tracing only features with matched values. This is somewhat advanced and is used primarily in telecom and electric networks. Weights can also be used to aggregate flow. This is second usage is helpful for wastewater and storm water networks where flow direction is known – that is the non-looped portion of the network. Using trace weights, we can accumulate flow upstream from a specified location. You might add a trace weight on the length of your gravity mains and laterals in order to later obtain the total length of pipes upstream from a given location. You might also add a field to your wastewater lateral points representing estimated gallons entering the system. By creating a trace weight on this field, you can summarize gallons at any point in your network using the Find Upstream Accumulation trace task on the Utility Network Analyst toolbar. If desired, the system could then store these values of accumulated flow along your network in the manholes and gravity mains. For an example of this, see the Calculate Accumulation script:
In short, weights are typically not used for most utilities. You can see that they do provide some advance functions but are not required to model and work with a geometric network.
Lastly, we like to recommend that if you are tackling some of these issues, that you take ESRI training so you can understand all of the implications of what we’ve discussed in this blog. The proper training or consulting help with creating your datamodel or implementing the geometric network will undoubtedly save you a lot of time and money when your data model is in production.
One of the things we can’t stress enough is the importance of GIS training for water, wastewater and stormwater utilities. The proper skill sets are critical to the success of any GIS implementation or operation and training is one of the ways a water utility can ensure they have the proper organizational skill sets to capitalize on their investment in GIS.
As a best practice, ESRI recommends that our water, wastewater and stormwater utility customers plan for their training needs. This includes both short term training needs to support a GIS implementation or a specific GIS project and long term training needs to ensure that a water utility can support their enterprise GIS progression.
Some of the typical benefits of GIS training for water utilities are faster GIS deployment, significantly reduced potential for mistakes (both GIS software use mistakes and GIS deployment mistakes), best practice enterprise architectures, better workflows and improved data QA & QC which ultimately yield a better return on your investment in GIS. We seen many utilities that continue to develop their employee’s GIS skills reap the benefits of faster enterprise deployments that are more soundly planned for.
During the past few years, ESRI’s Training Group has created a large number of training plans for water utilities. The plans were created through a consultative process where our training group would spend time working with a utility to ensure they had the necessary organizational skills to support their GIS plans. Through this process ESRI identified some patterns in the training needs of water utilities. These patterns included common GIS training classes taken by certain water utility staff roles, the relationship between size of a water utility and training needs and the sequencing of water utility GIS training.
From the experience of our training group coupled with typical GIS deployment patterns, core water utility functional areas, and best practices for water utility GIS, ESRI has now created a Generic GIS Staff Development Plan for Water Utilities. You can download the plan from the attachment link below this post.
After you download the Generic Staff Plan, we suggest you first read the Document Purpose section. This explains how the document is intended to be used. Since this is a generic document, we suggest that you contact an ESRI Training Consultant to help you customize this training plan to your utility. We’ve also created the plan to be a living document, so we’ll be updating the plan regularly as ESRI continues to expand our training offerings and the field of water, wastewater and storm GIS continues to evolve.
November 5th Webcast exploring the Water Utility Resource Center & Enterprise License Agreements for Water Utilities
You can sign up now for a webcast ESRI will be giving that explores the templates on the Water Utility Resource Center and also how water, wastewater and stormwater utilities can benefit from an ESRI Enterprise License Agreement (ELA). We’ll touch on how you can leverage the GIS best practices from the Water Utility Resource Center and then demonstration of each of the templates in action, including the newly released Water Distribution Capital Planning Template. The webcast will also explore how water utilities are benefiting from both negotiated Enterprise License Agreements and Small-Utility Enterprise License Agreements. At the end of the webcast we’ll answer any of your questions about the Water Utility Resource Center, the templates or ELAs.
You can sign up here:
Session 1 – November 5th 2009 1 to 2 PM EST – http://events.esri.com/info/index.cfm?fuseaction=showSeminar&shownumber=12971
Session 2 – November 5th 2009 3 to 4 PM EST –
As you may have seen, we released the Water Distribution Capital Improvement Planning (CIP) Template a last week. First, we wanted to say a big thank you to all of our users and business partners who helped us to refine the initial geoprocessing models and the toolset also shared their workflows for capital planning.
We’ve already had a few questions about why we chose the term Capital Improvement Planning (CIP) to describe this template, since not all utilities use that term. So when we use the term CIP, what we mean is the long term plans of a utility to manage their assets and/or to expand their system, what you may also call a “Capital Plan”, “Long Term Plan” or “5 year plan”.
Personally, I think the CIP Template is great example of how ESRI listens to our water utility customers and responds to their needs. We’ve had numerous customers over the past few years tell us that they want to be able to leverage their asset data in GIS as well as their operational data (workorders, CIS, water quality) better to support their long term plans. Of course, we thought that giving our customers a geographic view of all that asset and operational data was the best place for them to start. We also heard from many of our water and wastewater customers that their long term planning has evolved from an occasional event to a continual process; because of funding issues, grant availability, coincidence with other projects that a utility could share costs with and the desire to be quick and proactive to eliminate the risk of future critical asset failures.
Also, we are excited, because the CIP template is great example of GeoDesign. We’ll be doing a blog shortly that explores the principals of GeoDesign and relates them back to the CIP template.
2 Parts of the CIP Workflow
As we dug into the CIP process, we observed 2 distinct, but related workflows happening. The first part of the workflow was to assemble data from many sources and analyze that data to look for where projects are needed. This part of the process is tailor made for the benefits of GIS – to use GIS as the place where different types of data are assembled together into a common view and also to use the analytical capabilities of GIS to gain better insight into the aggregated data. Because this analysis needs to be iterative (looking at multiple data layers with different weighted criteria), an auditable process (you have to be able to defend your findings to a PUC and your ratepayers) and an automated workflow (to save time, money and resources) this is a perfect match for Geoprocessing Models in ArcGIS.
GIS Analysis for CIP Decision Making
At first we took the approach that ESRI should try and build a few geoprocessing models that all water and wastewater utilities could use to score and rate their assets by estimated remaining asset life, condition or criticality. We figured that we could do some research, interview some of our users and figure out these geoprocessing models (our inner geography geek begged us to take this approach first). What we quickly realized was that there isn’t a silver bullet set of geoprocessing models we could build because every utility system has their own approach to long term asset management and their own priorities (KPIs, level of service they want to provide, hot button issues, fiscal condition, etc) that drive their long term planning.
This was also a great reminder that even though we have the ability to use technology to automate a process, the human element is still critical, meaning that the more we talked with the engineers who are creating these CIP plans, the more we realized they need a better way to manipulate and process data so they could apply their engineering expertise to make decisions about capital projects. We also noticed when talking to engineers doing capital planning, that while they were somewhat aware of the analytical capabilities of GIS, they weren’t aware of the geoprocessing framework core to ArcGIS and how to use ModelBuilder to automate analysis and create a reusable toolset.
So we decided that we need to focus our CIP template on showing the water utility community how they could benefit from automating spatial analysis with the ArcGIS geoprocessing framework by providing some generic models. So, please keep in mind that the intent of the models we’ve provided in the CIP template is to show you how geoprocessing and ModelBuilder work within ArcGIS so you can create geoprocessing models that reflect how your utility wants to manage assets and plan for the long term. Incidentally, if you want to learn more about GIS analysis, Geoprocessing or Model Builder within ArcGIS, ESRI has lots of great resource including on-line training, books and class room instruction.
Estimating Project Costs
The second part of the CIP workflow we observed was estimating CIP project costs. Basically this workflow was estimating the cost of a project based on either replacing existing infrastructure or adding new infrastructure (main extensions, interconnections, extending service to new sub-divisions, etc). It’s important to note that all of the functionality in this part of the CIP process is core to ArcGIS and the geodatabase, all we’ve done is customized the application to automate and simplify this part of the workflow. This is what we decided to call the Costing Estimating Tools.
The first step in estimating project costs is to create projects by grouping assets together into projects. In this part of the process you are visualizing the data you brought into GIS and also the results of your analysis and then determining what assets you want to include in a project, your rehab or replacement strategy for those assets and then saving that information. So you are literally visualizing data in GIS (most likely working with many data layers of data, including the same feature datasets symbolized different ways) and doing some spatial and attribute queries to come up with candidate assets to include in CIP projects.
From there, assets that are in need of replacement or rehabilitation and spatially close to together are grouped in projects. We’ve heard from many water utilities that without a spatial context it was a real challenge for them to group assets together into appropriate projects without and also it was a challenge for them to track and manage information about candidate assets for CIP projects throughout the CIP planning process. Water utilities were struggling with supporting their CIP process with paper maps and tracking assets that were part of a project, including costs to replace those assets, in spreadsheets.
So traditionally, this CIP process took a lot of staff time and also lead to uncertainty about whether utilities were actually spending their money on the most appropriate capital projects. We also heard that utilities were struggling with how to update data when they tried to refine a large candidate list of CIP projects down to just a few to carry forward into design and that it was next to impossible to look at multiple scenarios for the same project area (assets grouping and rehab or replacement approach) because so much of this process was manual or spreadsheet driven.
We took the approach that if a utility has their assets (water distribution, wastewater collection or stormwater) in GIS, they should use their GIS asset data to group into CIP projects and then to store information about the CIP projects (like the extent and also all of the assets that are part of the project) as new data layers in GIS. This enables a utility to create an authoritative source of data about their proposed capital projects in GIS. So this drove us to create the Cost Estimating Tools.
As we began to demonstrate early versions of the Cost Estimating Tools to our utility users, we got a lot of great feedback that helped us to refine the tools. We were told that to be really useful, the tools should include the ability to either rehab or replace existing assets and to extend mains, so we programmed that functionality into the tools. We also were told by our users that they needed to be able to compare the costs of different replacement strategies (open cut, trenchless, etc) for the same set of assets so we designed the tools to make it easy to compare the costs of use using different rehab methodologies. Also we knew that the costing element of the tools needed to be flexible, because individual utilities favor different pipe materials which can be set as defaults and that unit costs are often specific to a utility and those can be easily configured in a simple table.
So what we wanted to do with this blog was to explain how we arrived at version 1 of the Water Distribution CIP Template. We are very interested in your feedback so we can incorporate more useful changes in version 2. Also we’d like to hear about any geoprocessing models that you would like to use for CIP planning. So, please leave us feedback here – http://forums.esri.com/forums.asp?c=55&s=426#426
In the next few weeks we’ll be recording a video of the Water Distributions CIP Template in action and we are also going to do a webcast in December that takes a deep dive into the CIP Template.
If you have been following us on twitter, you already know that we released the ArcGIS Water Distribution Capital Planning template (we are calling this the CIP Template for short) yesterday. The CIP template includes a set of models to help you understand how to you can use GIS to score and rank your infrastructure and a set of tools to provide cost estimates for rehabilitating, replacing or building new infrastructure.
We will film a video at the end of October that shows you in detail how these tools work, and we’ll be doing a live webcast in December to explore the CIP template in depth. So in the mean time, below is a little help with the CIP Template.
We included 6 models that show different ways you can analyze your data. To run these models, you will need to create a temporary file geodatabase and set the environmental variables for each model. The two variables you need to set are Current Workspace (the folder that has the CapitalPlanning.gdb in it) and the Scratch Workspace (the folder that has the temporary File GDB you just created).
The Project Cost Estimating tools use three tables in the CapitalPlanning.gdb for configuration. These tables are shipped to work with the data in the Sample.gdb. If you want to start changing cost or the configuration, you will need to change these tables.
CIPDEFINITON – This tables defines which featureclass’s to cost, the fields to look at(such as Diameter and Material) and a few other parameters.
CIPCOST – This table defines the cost for a particular asset. When costing an asset, you can define a Strategy, like Replacement or Rehabilitate, then an action for that Strategy, like Open cut for a Replacement . For each Strategy and Action, then you define the cost based on the fields you set up in the definition table. So if you are looking at wMains as a layer, you are interested in the Field’s, Diameter and Material, you would select your Strategy, the Action for that Strategy, the Material(say PVC), then Diameter(say 12) and define a cost for what each foot would cost. So by using a Strategy, Action and two filter fields, you can provide very detailed cost estimates.
CIPREPLACEMENT – This table allows you to provide lookups for replacement. If you are going to replace a 6” DI, you may have a rule saying that each 6” DI is going to be replaced with a 8” PVC. This table allows you to define this replacement. So that costing is preformed an 8” PVC, not a 6” DI.
Since this is our initial release of the CIP Template, we want your feedback. So please post any questions or feedback to our forums under the Water Utilities Template section: http://forums.esri.com/forums.asp?c=55
At first glance, that might seem like a silly question to a water, wastewater or storm water utility. After all, how hard is it to find your customers…. they are in your service area, connected to your infrastructure and you have an address to send them bills. But do you really accurately know where you are providing service to?
We are seeing a trend where water utilities are recognizing the importance of accurately knowing where they are providing service to (your real customer locations) and also understanding that there are many facets to accurately establishing your customer locations.
So what do we mean by customer location and how do you store that in your GIS?
For the purpose of our discussion here, by customer locations we mean the location where you as a utility are providing service to. This is the location where you are distributing flow to in a water system or where you are accepting flow in a sanitary sewer system
There are some common approaches that we see utilities using to store customer information in their GIS. Just like any GIS data model, you should pick an approach to store your customer locations that fits your utility’s specific needs.
For water utilities we commonly see customer location stored as a meter feature class (if you have meters) or with a feature class called customer, premise location or service location. With a geometric network, these feature classes are snapped to lateral which are snapped to mains. An important distinction for many utilities is that billing location of a customer, where the bill is sent to, is often different than the location you are serving that customer (premise or customer location).
For wastewater utilities we commonly see customer locations stored with a cleanout feature class, a customer or premise feature class or if a combined water/wastewater utility then water and wastewater both may use the meter feature class from the water distribution network.
Of course if you don’t have your water or wastewater networks in GIS yet, or don’t even have a GIS, customer locations are a great starting point for building a GIS system. It is relatively cheap to record them and you’ll immediately get high value from having those location accurately measured.
Some common attributes we see for customer location feature classes are: unique ID, customer type, active, customer name, premise address, customer phone number. Unique ID is should be an ID that will allow you to join your customer locations with your billing system so you can visualize consumption patterns.
Benefit of accurately locating your customers:
Some of the ways we’ve seen water and wastewater utilities benefit from accurately knowing their customer locations are:
- Reducing non-revenue water – We’ve seen accurate customers as a critical data component to reducing non-revenue water. A simple example of reducing non-revenue water with accurate customer locations is to create a map that shows all of your customer locations and then to look for where places (such as a buildings) that should be a customer location but are not. Another way to use customer locations to reduce non-revenue water is to join your billing data to customer locations and visualize customer consumption by creating a thematic map of graduated symbol sizes or colors. In this case you are looking for active customers that have abnormally low consumption and may have a defective meter. Anecdotally we’ve heard from a number of ESRI customers that the simple actions above have made significant reductions in non-revenue water. We’ve also seen some very sophisticated analysis using consumption data linked to customer locations and metering data to try to identify zones within a water distribution system that may a high amount of water loss due to leaks.
- Allocating demands – More accurate customer locations will yield better demand allocation for hydraulic models, especially when linked to consumption data.
- Estimating flow – For wastewater utilities, more accurate customer locations can be used to better estimate flow through being able to more precisely calculate the EDUs flowing into pipes from upstream.
- Better Customer Service – For example you can gain better insight into how customer complaints and customer service requests track back to the actual infrastructure that they are served by. A good example of this is water utilities that are using their customer locations in GIS to track the location of water quality complaints over a multiyear period back to common pipes or water sources that could be the cause of an issue.
- Improved routing – More accurate customer locations will yield better routes for field crews, saving fuel and time.
- Validating premise addresses in other utility systems – We often hear from utilities that while they have very good billing address data for customers in their CIS or billing system, that premise locations (stored as an address) in these systems is often wrong. So better premise address locations generated with GIS can be used to fix bad premise locations in your CIS (you should have one system of record for premise locations, but we’ll save that discussion for another day).
- Better emergency notifications – We’ve heard a number of horror stories from utilities that have an emergency notification system that has not notified customers during an emergency because their customer locations are bad. 2 common ways to notify customers during emergencies are doing a broadcast notification (notifying all customers in a service area or a municipal boundary) or doing a target notification based on the pipes that serve a customer (just notify customers that are affected by a broken main because you know they are served by that main). In both of these examples accurate customer locations are key to being able to perform emergency notifications.
So how do you get your customers located accurately?
The most common way that utilities initially get their customer locations into a GIS is through geocoding their billing roster. When geocoding any address data, the 2 critical components that determine the quality of your geocodes is the input address data and the dataset that you are geocoding against.
We’ve heard from a lot of water utilities that the premise locations in their CIS or billing system are of dubious quality and often time there is not a lot of consistency in how the address fields for premises were used. So while billing address data is usually of high quality (otherwise you’d never get paid) premise location is not accurately stored because it was perceived to be of less importance. In this case, step one would be to try and fix some of the issues in the address data you are trying to geocode before you geocode the address data. This may include trying to standardize the input address data (street abbreviations, data structure, etc).
You also want to use the best dataset available to geocode against. Increasingly we are seeing water utilities licensing commercial dataset for geocoding. Particularly they are choosing to license datasets that frequently updated and have the ability to geocode down to a rooftop level.
We somtimes see water and wastewater utilities use parcel centroids as the first step to establishing customer locations. So if you can get a good dataset of parcels in your service area you can use GIS to calculate the centroid of each parcel as the first step to establishing customer locations.
Also we are increasingly speaking with water utilities that are GPSing their meter locations and curb stops during meter replacement projects or wastewater utilities that are GPSing clean outs during field data collection projects.
No matter what automated process you use to get your customers on the map initially, no doubt you’ll have to do some data clean up. For example, you will probably have to do some manual data creation and editing to establish customer locations at commercial and industrial locations or for multi-unit housing. Also you must develop a workflow to keep your customer location dataset in GIS up to date.
Many of you have had a chance to test out the Mobile template and provided great feedback. One question that keeps coming up is “How do I interface (or integrate) the mobile map with my other utility systems?” Typically, when we get asked this question, people are referring to their workorder system (also called a CMMS or EAM). Occasionally we are asked about interfacing with a LIMS system, mobile leak detection system, customer information system (CIS), billing system, heck we’ve been asked about interfacing with a utility’s time card system. Hopefully you notice the trend here, that water and wastewater utilities can and do want to “spatially enable” their other business systems because most of these systems contain information that has a location to it, but the other business system can’t store spatial information at all or can’t store it well.
Well, there is one simple easy answer because there are some many types of systems, vendors, API’s, gateways, etc… So I wanted to talk about a few general ways to communicate with other systems and some ideas how to work with other systems. First you need to decide what functions the field crew is going to need. For instance, if you are flushing hydrants, do they need to access to when the hydrant was flushed lasted or every time it was flushed? The reason I would ask this question is the answer is going to help us define how to work with other systems.
Lets start by looking at were to record the inspection or flushing report in the above case. If we are storing our field reports/inspections in the geodatabase, then this is fairly easy process. We can create a feature class with all fields for the hydrant flushing. This is exactly what we did with the template. The user can click the hydrant, copy some relevant information to the hydrant inspection record, such as Asset ID and populated the geometry of the report from either the hydrant or the GPS location of the field crew doing the inspection. The crew can fill out the rest of the information, click save, and use ArcGIS Server to post that information directly back to the Geodatabase. If the user wants access to all historical inspection data, then that information can either be in the same feature class as the new inspections or in a separate one. I would suggest that all historical information been in a separate featureclass. The reason is that the historical inspection or field report data can be very large. You want to manage the update of the devices with this information separately then the newly created field inspections. If all the inspections, both new and old, are in one feature class, then the map may have 100’s of inspections at the same location, may be very confusing for the field crews. The historical inspections never really need to be displayed, they really just need a tool to click the asset and pull up all related information. With the new inspection, once they create it, they then can visually see on the map that they created and save the inspection and are done working with that asset. So in summary, if you are using the GDB as you system of record for assets and their related information, inspections, flushing, etc.., then create a data schema for new data and historical data. This will provide ultimate flexibilty and usability. Just one more note on the above. If you are going to load all your historical inspection information into the geodatabase from another system, then use a process to join your historical, non GIS inspection data, to the geometry of your asset and load this to your historical field inspection data.
Now if you are storing some asset information in another system, like extended asset data in your workorder system, then you have a few ways to interface that data with the mobile map. One way is to use the Geodatabase as your connection to other systems. What I mean is build a backend process to pull out new inspections from the Geodatabase and push them to whatever system you have, and vice versa, use the same process to push information from the other system into the geodatabase. This way you can use ArcGIS Server and ArcGIS Mobile to interface with the information in the field. It is much easier to write back end database scripts to move information around then it is to build a process to push out other systems data into a field, in a format that they can access offline, make edits or entries to that information and push it back into the office.
If want to connect to the other system information store directly, without having to move it into the geodatabase, you have two options. You can work with a local copy or cached representation of that other system. This means that a set or all the data from that system will be loaded on the device. The other option is to use a web services approaches or a Enterprise Service Bus(ESB) to directly talk to those other systems.
If you want to work with the other systems directly on the mobile device, then you are going to need to figure out how to get that information on the device you are using and write a module for the mobile app to talk to that data store. ArcGIS Mobile is built with the .Net framework, so it is very easy get your Mobile GIS Information to talk to other data stores. The biggest challenge with this method is figuring out how to get the information on the device, keep it updated and push changes back into the office. Some vendors have ways to do this, some do not. I would suggest talk to your vendor and discuss what options they have. You can also look at using provisioning software that can manage pushing out information to the field and pulling back in. If you have a homegrown system, then you will need to develop a homegrown field version of the data and a synchronization method.
If the above is technical daunting and you want to use web services to have ArcGIS Mobile talk to your other systems, then I would ask yourself one question. Can your field personal do their job if they do not have a connection to that service? If so, this is a great way to interface mobile and office systems. If your answer is no, then proceed down this route with caution. Even with cell coverage getting better and better, there are always dead spots or connection issues. What is one of the first things that happen when there is an incident, the cell networks get overloaded. Also think about bandwidth. This could be a chatty system. According to Gartner, the days of unlimited data on cell networks are coming to an end, btw, unlimited data is 5GB on most carriers. If you are ok with all the above or your field crews do not need access to this information to do their jobs, then web services are great, effective and easy ways to talk to other systems. They are easy to implement and they can support many applications. All you need to do is build a module for ArcGIS Mobile that when I click an asset, it hits the appropriate web service and displays the results. This could be a simple hyperlink in the attributes of a feature.
In closing there are a number of ways to interface an ArcGIS Mobile Applications with other utility systems and we wanted to highlight few of them. The above strategies are not the only strategies; there are many ways to implement communication between different systems. If there methods you would like to discuss further, please contact us and we can help you figure out the best approach for your utility. You also may find that combining some of the approaches best suites you. For example, with new inspections, you may use ArcGIS Mobile to create a new record, store it in the cache, and post it to the geodatabase using ArcGIS Server, then nightly, use a backend script to move it to the proper system. When that field user wants to look at the historical info tied that asset they are inspection, they can hit a web service. If your field crews do not have coverage broadband, well at least they can complete their work.