A Four-Layer Digital Framework for BIM and FM Integration in a Sustainable Urban Drainage System ^†

Abstract

This paper introduces a digital framework that integrates Building Information Modeling (BIM) and Facility Management (FM) to enhance the lifecycle performance of Sustainable Urban Drainage Systems (SuDS). Addressing the limitations of traditional drainage such as poor resilience and fragmented maintenance, the framework consists of the following four layers: BIM-based 3D asset modeling, sensor-driven monitoring, FM-integrated operations, and climate-informed adaptive planning. Grounded in systems engineering and aligned with International Standard ISO 19650 standards, it enables a dynamic digital twin to support continuous feedback and predictive maintenance. Illustrated through diagrams and comparison, the framework promotes adaptability and long-term sustainability in urban water infrastructure.

1. Introduction

Urban flooding, intensified by climate change and accelerated land-surface sealing, presents a significant challenge for contemporary urban environments. Sustainable Drainage Systems (SuDSs) provide a decentralized and ecologically adaptive alternative to traditional piped drainage infrastructure by promoting surface water attenuation, infiltration, and treatment through natural processes [1]. These systems are designed to mimic natural hydrological functions and enhance urban resilience. Empirical analyses indicate that a substantial proportion of Sustainable Drainage Systems (SuDS) exhibit declining performance within a few years post-implementation, a trend largely attributed to inconsistent maintenance protocols and the lack of real-time monitoring systems [2].

Emerging digital technologies such as Building Information Modeling (BIM) and Facility Management (FM) systems hold substantial promise for improving the lifecycle performance of SuDS infrastructure. BIM provides structured visualization, data integration, and simulation capabilities, while FM platforms support routine operations and maintenance workflows. Yet, the integration of BIM and FM within the context of SuDS remains limited and underexplored in current practice [3,4,5].

This study proposes a four-layer digital framework to bridge this gap and support the performance of SuDS assets.

2. Literature Review

2.1. SuDS Challenges in Urban Environments

Sustainable Drainage Systems (SuDSs) components, such as bioswales, infiltration basins, and permeable pavements, provide ecologically effective solutions for managing urban runoff. However, their spatially distributed nature presents ongoing challenges for asset tracking and performance management. In the absence of a centralized digital asset register or real-time condition monitoring mechanisms, deterioration often remains undetected until system failures emerge [2,6]. Empirical findings from urban projects demonstrate a persistent dependence on manual inspection routines, which are both labor-intensive and subject to variability [6]. Moreover, SuDS designs frequently fail to incorporate feedback from operational performance, limiting adaptive improvements and resulting in recurring inefficiencies and weak institutional loops [3].

2.2. BIM and FM in Water Infrastructure

BIM tools generate comprehensive 3D parametric representations of infrastructure assets, facilitating hydrological modeling, construction sequencing, and strategic maintenance planning [2]. Concurrently, FM systems are responsible for capturing and processing operational data, including work orders, inspection records, and condition assessments [4]. Integrating BIM and FM platforms enables the creation of a digital twin as a synchronized virtual model that mirrors both the physical characteristics and real-time operational status of infrastructure components. In the context of urban stormwater management, such BIM and FM integration, particularly when coupled with sensor networks, has demonstrated measurable gains in efficiency, responsiveness, and system resilience.

3. The Four-Layer Digital Framework

The proposed BIM–FM–SuDS framework is organized into four integrated functional layers, each layer addresses a discrete system function: modeling, sensing, managing, and adapting. This is aligned with ISO 19650-compliant BIM workflows. A digital twin needs the following [4]:

• Physical Model;
• Sensor Feedback;
• Decision Engine;
• Environmental Context.

The overall structure of the proposed four-layer integration approach is illustrated in Figure 1.

3.1. Layer 1: BIM-Based SuDS Modeling

This foundational layer involves 3D modeling of SuDS components using Industry Foundation Classes (IFCs) classifications within compliant BIM tools. Features such as soil infiltration rate, vegetation type, and hydraulic properties are embedded in the model. Geographic Information System (GIS) integration enables large-scale mapping of urban catchments.

3.2. Layer 2: Sensor-Based Monitoring

Internet of Things (IoT)-enabled sensors collect real-time data on water levels, soil moisture, and flow rates. This data feeds directly into the BIM model, establishing a digital twin that supports failure prediction and condition-based maintenance.

3.3. Layer 3: Facility Management Integration

FM systems use sensor inputs to manage inspections, generate maintenance schedules, and trigger alerts. Beyond routine operational tasks, this layer establishes a continuous data feedback mechanism that updates and refines the BIM environment. As-built conditions, maintenance histories, vegetation health assessments, infiltration performance, and hydraulic behavior observations are systematically synchronized back into the BIM model. This bidirectional exchange transforms the BIM environment from a static design representation into a living operational database, ensuring that the digital twin evolves in parallel with real-world asset conditions. Such dynamic updating is essential for enabling predictive analytics, optimizing maintenance strategies, and supporting long-term lifecycle planning for SuDS infrastructure.

3.4. Layer 4: Climate Adaptation Feedback

The final layer integrates external datasets—such as updated rainfall projections and land-use maps—to inform adaptive design adjustments. This ensures that the SuDS system remains robust in the face of climate change and urban expansion.

The lifecycle integration of SuDS within the digital twin environment is illustrated in Figure 2.

Field observations from case studies across Europe and Asia demonstrated that adding more than four layers introduced redundancy without delivering additional value. Therefore, the four-layer structure offers a functionally complete yet streamlined solution.

The comparative assessment of traditional and BIM–FM–SuDS management approaches is summarized in

Table 1. Comparison of traditional vs. BIM–FM–SuDS management.

Aspect	Traditional SuDS	BIM–FM–SuDS Integration
Asset Visibility	Fragmented, paper-based asset records	Centralized 3D digital models with rich metadata
Maintenance Strategy	Reactive (typically post-failure)	Proactive, using predictive analytics and alerts
Monitoring Method	Manual, periodic inspections	Continuous, sensor-driven performance tracking
Design Responsiveness	Limited feedback, anecdotal adjustments	Data-informed, scenario-driven design updates
Compliance Reporting	Static, infrequent documentation	Dynamic, real-time digital dashboards
Climate Adaptability	Low resilience and poor responsiveness	Flexible through simulation and real-time updates

.

4. Discussion

The four-layer framework delivers several key benefits:

• Lifecycle Optimization: Enables complete visibility from design through maintenance and adaptation.
• Centralized Data Management: Merges design, operational, and environmental data into one system.
• Predictive Maintenance: Real-time monitoring informs proactive interventions.
• Resilience and Adaptability: Dynamic adaptation to changing climatic and urban conditions.

Despite these benefits, challenges such as high sensor installation costs, FM system complexity, and interoperability issues must be addressed. Solutions include prioritizing high-risk areas, training for FM tools, and adopting open standards like IFC.

Future work may explore integration with AI-based flood prediction, community-driven sensor inputs, and national digital infrastructure policies.

5. Conclusions

This study presents a robust digital framework that integrates BIM and FM technologies to enhance the design, monitoring, and adaptation of SuDS. Each of the four layers plays a vital role in transitioning SuDS from static systems to intelligent, adaptive infrastructure. Cities striving for resilience must adopt such digital paradigms to address the growing challenges posed by urbanization and climate variability.