IEEE Systems, Man and Cybernetics Magazine - July 2019 - 14

component is briefly summarized in Table 1. Infrastructure
and scenario data are held in a shared national infrastructure database, NISMOD-DB. That rigorous structure
enables each combination of scenarios and strategies to be
accessed and scrutinized. Visualization functions enable
the presentation of maps, time series, and other graphics
(Figure 2). Additionally, optimization routines enable combinations of interventions to be developed that meet specified objectives or are subject to given constraints.
NISMOD1 has been widely used for the analysis of the
future of U.K. national infrastructure, including Infrastructure U.K.'s National Infrastructure Plan [22] and the recently completed U.K. National Infrastructure Assessment [23].
Our model combines national-scale representations of the
energy system, a high-level model of multimodal transport,
a model of municipal water supplies, and a spatially
resolved representation of solid waste treatment facilities.
It has been converted to a parallel computing environment
and has accompanying visual reporting tools.
NISMOD2 integrates a newly developed mapping and
optimization of the nation's digital communications network, along with a high-resolution modeling of the urban
drainage infrastructure. The new water model includes
all water users (in the power sector, agriculture, and
industry as well as public water supplies). The transport
model is much higher resolution and includes a full multimodel origin-destination matrix. NISMOD2 also provides

compute a series of metrics through the simulation period (typically decades into the future) that can be used to
evaluate system performance (see the subsequent discussion). We thereby use simulation to explore the performance of alternative infrastructure investments and
policies in the context of a wide range of possible future
conditions. It would be unrealistic to optimize system
performance in the context of multiple objectives and
often severe uncertainties, but optimization can be used
to illustrate system sensitivities and tradeoffs between
different objectives.
NISMOD also keeps track of all of the significant interdependencies among infrastructure sectors. Although there
are many interrelationships, from an infrastructure assessment and planning perspective, the dependencies that matter most are 1) when demand for one infrastructure sector
is highly correlated with demand for another (e.g., domestic
demand for both water and energy) and/or 2) when one
infrastructure sector can potentially consume a significant
proportion of the capacity of another, notably in power generation, which is responsible for 40% of nontidal surface
water abstractions [20]. Another instance of the latter type
of interreliance would become critical if there were to be a
large-scale uptake of electric vehicles, which could eventually use more than 15% of electricity generation in 2050.
The ITRC has built two versions of our NISMOD model.
NISMOD1 is described in our 2016 book [21], and each

Scenarios

Strategies of Infrastructure Provision

Population

Economy

New Infrastructure

Improved Efficiency

Technology

Climate

Demand Management

Spatial Planning

Interdependent Infrastructure System Models
Energy

Water

Transport

Flood Risk
Management

National
Infrastructure
Database

Digital
Communications
Solid Waste

Metrics of Infrastructure Performance
Service Quality,
e.g., Reliability and Security

Affordability

Externalities,
e.g., Environmental Impact

Visualization

Figure 1. A schematic overview of the use of NISMOD for national infrastructure assessment. (Adapted and

used with permission from [18].)

14

IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE Ju ly 2019



IEEE Systems, Man and Cybernetics Magazine - July 2019

Table of Contents for the Digital Edition of IEEE Systems, Man and Cybernetics Magazine - July 2019

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