Eleza Kollannur

Abstract: ( Eleza Kollannur, Priya Gaikwad)

Flooding has become a recurring natural calamity in the past few years and has claimed many lives, damaged property and crop. This scenario calls for the urgent need for a decision support system to provide up-to-date warning and emergency services to the flood victim as well as the governing bodies in the area to effectively overcome this disaster as well as minimize damage. 

Let’s take the recent tsunami flooding across the world in the past few years like India, Japan. In the coastal town of Tamil Nadu, India integrated coastal zone management plans and vulnerability maps were prepared using software like GIS and MIKE21. It helped in assessing the shoreline changes, surge levels, wave run up along the coast by analyzing historical data. This study along with the contour survey of the site and satellite data helped in identifying the emergency relocation sites, rehabilitation sites as well as design suitable sand bars along the shoreline for preventing further damage in case of a future occurrence. 

We would like to take up this challenge to share some of our past experience in this field and elaborate various decision support capabilities of GIS for planning and management.

Abstract: (Kulkarni,A , Kollannur,E, Loya,A.)

The essence of the topic is to provide innovative solutions for conserving water by harvesting rainwater in arid and semi arid regions using a decision based model on Geospatial technologies and multi criteria analysis. The spatial decision modeling tool (SDMT) will help identify rain water harvesting zones with suitable sites for various structures like check dams, farm ponds and percolation tanks. 

AWWA is the largest non profit, scientific and educational association dedicated to managing and treating water in US, since 1881. 

Abstract: (Eleza Kollannur, Tim Clay, Amol Kulkarni)

Geospatial analysis and programming is improving operational efficiencies in the Wastewater Sector resulting in faster and higher-quality decision-making, saving both time and money. As such, we have developed a suite of ArcGIS based routines using Python Scripting and Model Builder, to identify catchment needs and opportunities across a study area on current and future scenarios, considering factors such as climate change and population growth.

These tools identify opportunities to remove surface water from drainage network and areas of new development, which forms a key part of an environmentally friendly and sustainable future, whilst also ensuring resilience around critical infrastructure such as hospitals. One of the routines also help auto generate standard forms and maps for survey data collected through ArcCollector.

These tools combine the strength of programming with geoprocessing to clean, check and consolidate input data from various sources into a structured dataset for further geospatial analysis. It has helped share information with other stakeholders, allowing quick decisions and sharing of information, using ArcOnline.

The tools have used several geospatial analysis techniques including:

 ·Calculating distance and gradient from the lowest point of development to the nearest drainage option using raster processing, proximity analysis and attribute querying,

 · Identifying flooding extent caused by sewer blockage using hydrology tools,

·  Iteratively tracing and querying geometric network to generate hydraulically independent areas.

All these tools have given Stantec a competitive edge in the Wastewater Sector. The abstract will share details on how several water companies have opted for these technologies over their current practices to provide reliable drainage solutions to the communities they serve. It will discuss upon advantages and challenges of combining geospatial analysis with programming. It will also touch upon a checklist to follow when you develop a customized GIS toolbox for a client. 

Abstract: (Eleza Kollannur, Andrew Sitti)

The challenge of collecting Utility Network during mobile ArcCollector survey is that flow direction, ancillaries and connectivity must be correctly represented during the survey in understanding the data collectively. It is important to capture connected assets like incoming and outgoing pipes, update additional pipe data and even represent photos with bearing during a survey.

Python along with geospatial analysis helps putting the ‘what’ to ‘where’. As such we created a set of tools using GIS automation and programming tools, which first creates data structure for survey data collection, followed by post-processing tools which re-engineers standard survey forms to correctly represent mobile survey network data based on flow direction and connectivity, as automated forms and maps.

The tools use python programming to sort spatial data across excel tabs based on incoming and outgoing pipe data collected from a manhole, along with autogenerated pipe clocks. This helps the engineers in familiarizing data collected as per traditional survey form layouts. It also has the capability of arranging and tagging photos collected to node names to corelate with the data collected.

The abstract will share details on how several water companies in UK have opted for these tools over their current practices and generated solutions 60% faster giving Stantec a competitive operational advantage. It will elaborate on how Python can automatically generate all standard deliverables for a project which can bring huge time and cost savings.