{"id":579556,"date":"2025-10-15T15:42:01","date_gmt":"2025-10-15T15:42:01","guid":{"rendered":"https:\/\/www.esri.com\/en-us\/industries\/blog\/?post_type=blog&p=579556"},"modified":"2025-10-16T14:35:46","modified_gmt":"2025-10-16T14:35:46","slug":"geoenabled-asset-management","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/en-us\/industries\/blog\/articles\/geoenabled-asset-management","title":{"rendered":"The Path to Geoenabled Asset Management: A Case Study of J\u016brmala\u2019s Hydrants"},"content":{"rendered":"

Situated 25 kilometers west of Latvia\u2019s capital, Riga, J\u016brmalas \u016bdens is the municipally owned water and wastewater utility serving the coastal city of J\u016brmala. The utility delivers potable water to over 55,000 permanent residents\u2014and serves a summer tourist population exceeding 100,000 people\u2014across more than 1,000 kilometers of water and sewer networks. Each year, it produces 3.1 million cubic meters of drinking water and treats 2.9 million cubic meters of wastewater with a team of more than 140 employees.<\/p>\n\n

Since the early 2000s, J\u016brmalas \u016bdens has invested more than \u20ac145 million to reach 99 percent service coverage. The utility has been formally recognized by the International Water Association\u2019s Climate Smart Utilities (CSU) program. Today, J\u016brmalas \u016bdens is embracing this role\u2014using geographic information system (GIS) technology, analytics, and renewable energy to advance the CSU principles of sustainability, resilience, and digital transformation.<\/p>\n\n

The Challenge<\/h2>\n\n

On paper, J\u016brmala\u2019s hydrant network looked highly resilient, averaging 7.1 hydrants per 200-meter service area\u2014more than triple the regulatory requirement. From a firefighter\u2019s perspective, this level of redundancy suggested robust fire safety coverage.<\/p>\n\n

But in practice, the excess became a liability. Each hydrant carried recurring inspection and maintenance obligations, consuming crew capacity and driving up operational costs. Ironically, the very redundancy meant to support resilience actually eroded another core pillar of resilience\u2014reliability\u2014by diverting resources away from preventive maintenance, leak detection, and system upgrades.<\/p>\n\n

This contradiction highlighted the need to move from object-driven resilience (more hydrants, greater safety) to objective-driven resilience (the right number of hydrants, in the right places, supporting both fire safety and operational reliability).<\/p>\n\n

The Solution<\/h2>\n\n

J\u016brmalas \u016bdens launched an in-house GIS program to test advanced decision-support workflows. Using ArcGIS Pro, ArcGIS Notebooks, and ArcGIS Field Maps, the utility designed a three-part framework:<\/p>\n\n

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This flowchart outlines the main steps of the hydrant optimization framework.<\/em><\/figcaption><\/figure>\n\n

Data Aggregation and Hydrant Scoring<\/h3>\n\n

Hydrant data was combined with open datasets on building footprints, population density, land use, and road networks. A combination of geoprocessing tools available in ArcGIS Pro was then used to assign each hydrant a score based on its surroundings\u2014including proximity to residents, access roads, and critical buildings.<\/p>\n\n

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Integration of input variables was used to calculate building, road, and hydrant scoring models.<\/em><\/figcaption><\/figure>\n\n

Hydrant Layout Optimization<\/h3>\n\n

The optimization engine was entirely coded in ArcGIS Notebooks, where experts implemented a custom Python-based simulated annealing algorithm. Notebooks enabled rapid prototype creation, algorithm refinement, and repeatable model runs, accelerating the shift from manual map edits to automated decision-support workflows.<\/p>\n\n

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Hydrant Optimization Results in One of the Test Neighborhoods<\/em><\/figcaption><\/figure>\n\n

Inspection-Driven Validation<\/h3>\n\n

Field crews carried out hydrant inspections using ArcGIS Field Maps, capturing condition, accessibility, and operational data. This inspection data was then integrated into the optimization framework to ensure that only hydrants meeting both regulatory and operational criteria were considered for removal.<\/p>\n\n

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Field crews fully leverage the capabilities of ArcGIS Field Maps and ArcGIS Survey123 apps to conduct on-site hydrant inspections.<\/em><\/figcaption><\/figure>\n\n

Economic Analysis<\/h3>\n\n

Long-term costs and benefits were assessed through a net present value (NPV) model\u2014also developed in ArcGIS Notebooks\u2014providing financial justification alongside operational efficiency.<\/p>\n\n

The Results<\/h2>\n\n

The hydrant optimization pilot delivered measurable outcomes:<\/p>\n\n