Complex Network Analysis of the Washoe County Water Distribution System Presentation By: Eric Klukovich Date: 11/13/2014

Overview  Previous Work  Distribution Systems  The Dataset  Creating the Network  Network Analysis  Conclusion

Previous Presentation  Discussed an overview of what studies have been done in energy, water, and environment complex networks.  Topic was vague.  Changed topic to focus in on the Washoe County water distribution network.  Combines natural and engineered water sources in the network.  Has not been done before.  Focus on understanding the relationship between them.

Previous Work  Water distribution is infrastructure that must always be available.  Can analyze the efficiency, vulnerability, and create plans for alternative resources.  Rivers can also be modeled  Monitor the water flow.  Take protective action if the river is being depleted.

Study 1 - Water Distribution Analysis  Modeled four different water distribution networks  Nodes represented source, control, and storage/processing facilities.  Edges were the pipes.

Study 1 - Water Distribution Analysis  Each network’s density was calculated  All networks were sparse and resemble the urban areas.  The efficiency of the water distribution was measured  Distance between the supply node and the demand source  Construction and cost has a major factor on how the network is created.  The robustness was measured by random removal of nodes.

Study 2 - Modeling River Networks  Modeled the Haihe Basin River network in China  565 nodes (319 natural and 246 engineered nodes)  Natural and engineered nodes  Edges - n atural or artificial water channels.  The degree distribution was calculated to categorize the different nodes.  Could identify the sources, the sea nodes.

Study 2 - Modeling River Networks River network River Node/Edge Example

Water Distribution Systems  Water distribution systems are a critical part of everyday life.  Provides fresh drinking water to entire cities and towns.  Can grow to be very complex.  Pipe layouts that guarantee water availability.  Complex networks can model and analyze the water distribution network.  Can calculate the efficiency and vulnerability of the system.  Improve the system by added or removing edges or nodes.  Understand what the impacts are if a node in the network failed.

The Dataset  Need a complete dataset in order to create a realistic complex network.  Types of nodes  Pipe diameter and length  How they are connected  Need data for the engineered and natural nodes  Comes from two different sources.  Water distribution in Washoe County is controlled by the Truckee Meadows Water Authority.  The natural sources of water come from the lakes, rivers, wells, and ground water that surround the Reno area.

Engineered Node Dataset  The data available to the public was vague and did not provide a complete dataset.  Contacted the Washoe County Community Services Department to get credentials to their Geographical Information System (GIS)  Contained a complete dataset for all the water utilities in Reno  GIS Maps contains data for the different neighborhoods  Arrow Creek  Double Diamond  Steamboat

GIS Maps  Provides information on the different nodes  Water mains and water values  Service points  Wells  Storage tanks  Water treatment facilities  Fire hydrants  Provides information for the edges (pipes)  Pipe length  Diameter

GIS Maps – Overview

GIS Maps – Double Diamond

Natural Node Dataset  Data for the natural sources of water was found through the Truckee Meadows Water Authority.  Lakes  Rivers  Creeks  Reservoirs  Information for the flow of the rivers and creeks were provided.  Lake and reservoir capacity was given.

Creating the Network - Nodes  Two types of nodes in the network, natural nodes and engineered nodes.  The natural nodes can be divided into two types  Surface water sources, such as lakes and rivers that are on the surface of the Earth.  Groundwater sources that are located under the Earth’s surface and requires wells to extract the water.  Engineered nodes  Structures that humans created in order to process and transport large amounts water to different areas.  Water mains, booster pump stations, pressure regulator stations, storage tanks, treatment facilities, and reservoirs.

Creating the Network - Edges  Two types of edges - natural and engineered.  The natural edges are the channels between two natural nodes.  Rivers and creeks tend to go from one large body of water to another.  The river flow will be used for the weights.

Creating the Network - Edges  The engineered edges are the artificial channels and pipes.  The pipes are used within urban areas to provide water to all of the different areas within the city.  The pipe diameter and pipe length data will be used for the weights.  Natural to engineered  Engineered to engineered

Creating the Network  The network will be arranged based on the location of where the nodes and edges are located.  Creates a more realistic network.  Allows for an easier comparison to maps.  The dataset shows the water distribution system follows closely to the surface streets.  The network will be created to represent this layout.

Network Analysis - Patterns  The network can be analyzed to find patterns within the data.  Can determine what factors impacted the network layout.  Ideally, a system should be efficient as possible, but the cost would be unrealistic.  Systems of this size have a limited budget and resources and impacts how the system is laid out.  The distribution network will be analyzed to determine if the construction costs and resources had an impact.  Will compare the network to a minimum spanning tree graph, with the same vertices.  If the two graphs differ, then cost and resources impacted the layout.

Network Analysis – Comparison  Can compare the natural water network to the man- made water network.  The degree distribution for each network can be calculated to compare the hubs.  Other complex network metrics can be calculated to determine if there are any similarities  Betweenness  Closeness  Clustering Coefficient

Network Analysis - Efficiency  Can also determine the efficiency of the system.  Cost and energy to transport water can be substantial.  If the water distribution network is inefficient, then it could lead to extra structures that could have been avoided.  Pumping stations to move the water.  Pressurizing stations to guarantee water pressure.  The efficiency will be measured by taking the Euclidean distance from the source to destination.  This value will then be compared to the amount of pipe that was used to move the water to the same destination.

Network Analysis - Robustness  Robustness of the network can be calculated.  A system failure can have a major impact on the people using it.  Shows the amount of redundancy in the distribution system.  There should be enough redundancy so the entire system will not fail if a few nodes fail.  Robustness will be measured by removing nodes randomly and by highest degree first.  The nodes will continue to be removed until the system completely fails.  The number of removed nodes that caused the failure can be determined to conclude if the system is robust or not.

Network Analysis - Clustering  The complex network can also show clustering within the data.  In Reno there are many different housing developments throughout the city.  The clustering coefficient in the network can be calculated.  Can determine if the water distribution system also creates clusters to supply water.  The network should be sparse because the nodes do not connect to every other node.

Conclusion  Water distribution is a crucial part of todays infrastructure and cannot afford to be disrupted because many people depend on it.  A new approach is taken that combines natural and man-made water sources into one network.  The data to create the network primary comes from the GIS maps that contain data for the water utilities in Reno.  The efficiency, robustness, and other metrics will be calculated to understand different aspects within the network.

Questions