Paradigm shift in the asset management of wastewater

Dec 11, 2023

A paradigm shift has taken place in the asset management of wastewater network in the Federal Republic of Germany over the last 18 years.


The starting point was the realization that essential technical and commercial data, which is used as the basis for asset management, is not sufficient to develop efficient investment and rehabilitation strategies for maintaining the value of wastewater networks. In the area of technical data, these quality deficits mainly concern the focus on damage and condition classes and in the area of commercial data the focus on book and remaining book values. A problem with the defect and condition classes is the fact that the detection of defects in a sewer system using the CCTV inspection takes place over a longer period of time. It can take several decades for a sewer system to be fully inspected.

The same applies to repeat inspections, although Germany stipulates periods of 10 to 15 years for this. Over such long periods of time, there will always be changes to the normative assessment and classification systems for defects. As a result, there are no homogeneous assessment and therefore they are not comparable with the information in the database. Irrespective of this, only a small proportion of the defect and condition data represents the current structural situation. In addition, the condition class is defined by the most severe individual defect detected in a sewer section. This may be sufficient for deriving a rehabilitation priority, but not for deriving a rehabilitation decision with regard to the need for repair, renovation or replacement of a sewer section ([Stein04a], [STEIN04b], [Stein05a]). Furthermore, the significant uncertainty given by the inspection recordings, and thus by the defect assessment could lead to one or more class changes in the condition classes ([Caradot18]). The condition class is therefore not a very resilient criterion for assessing sewer section objects.

The book and remaining book values are also only of limited use as management information for optimizing investment decisions. The depreciation period on which the book values are based is often an estimated, political parameter. Ideally, the depreciation period represents the average useful life of asset elements within the network. This means, even if the average useful life value is representative, that many network objects do not reach the average useful life, so that depreciation losses will occur and, on the other hand, can be operated for longer without being able to generate income in the form of fees ([STEIN09a], [Stacho19], [STEIN23a]). A realistic derivation of object-specific useful lives is not possible with this method.

To compensate for the deficits of condition class and remaining book value described above, STEIN ([STEIN14a], [STEIN13a], [STEIN16a]) developed the object-specific key figure "fabric deterioration class" and "fabric value” respectively “net asset value" as supplementary management information in 2003, which revolutionizes the quality and scope of performance of data-based asset management with the inclusion of ageing models. Both the process and the results that are possible with this information as part of an extended Urban Infrastructure Life Cycle Management process are explained below using the STATUS [] asset management system as an example. STATUS is a life cycle asset management system which includes sophisticated data analysis, a stochastic aging model and simulation engine to model strategies, which can consider any kind of strategic decision parameters allowing the development, analysis, and optimization of rehabilitation and maintenance activities leading to complex strategies. STATUS has been applied successfully for the management of sewer assets in many German cities for two decades.

Fabric deterioration class as the basis for the structural fabric and the fabric value

An extended evaluation concept has been integrated into STATUS, which divides the evaluation of a sewer system into a condition class and a fabric deterioration class, as explained below.

The condition class of a sewer section as a key figure for the actual function fulfilment (priority) is determined analogously to the standard evaluation models also in STATUS by the most severe single defect within the considered sewer section. As it is shown in Figure 2, the standard evaluation model assesses the defects using the principle of condition classification rigid class boundaries given as result a discrete classification.

However, the discrete condition classes are not useful, since the defect assessment is already carried out in a stepless manner, taking structural boundary conditions into account. This allows a realistic evaluation of the individual defects without loss of information due to classification in a discrete defect and condition class. Therefore, STATUS suggests a continues assessment following the principle of condition classification with no class boundaries (Figure 3). The pro-posed classification increases the quality of information and analysis, the defects are classified according to their impact on the environment (leak tightness), structural integrity and operational safety. This differentiation avoids that e.g. defect assessment, like deposits, influence the structural integrity evaluation of a sewer section. Management decisions from a structural, operational or environmental point of view can thus be derived cleanly and separately from each other.

The fabric deterioration class represents the overall condition of a sewer section, taking into account all of its defects, and thus characterizes the remaining wear reserve until the mandatory replacement is required. A rehabilitation action with a correspondingly high wear stock - even before it is completely consumed - enables the use of more cost-effective rehabilitation solutions, e.g. through renovation or repair. Thus, with precise knowledge of the fabric deterioration class of a sewer section, forward-looking and cost-optimized rehabilitation planning is possible on the basis of reliable data.

All the defects listed and assessed in the structure are included in the fabric deterioration class assessment with their respective individual defect class as well as their spatial distribution or concentration and their individual defect length.

Taking all defects into account significantly increases the resilience of the fabric deterioration class as an important management criterion. For the analysis according to the protection targets (tightness, structural integrity and operational safety), only the defects that has also been assigned a defect class in the corresponding protection target is taken into account (Figure 4).

Figure 5 shows the difference between condition and fabric deterioration class.

Figure 6 shows a real data based example of the relationship between condition class and fabric deterioration class. It is clearly visible that the critical fabric deterioration class (Very severe fabric deterioration) at the time of inspection is much lower at 1% than the critical condition class (CC 0) at 12.2%. This shows that even sewer sections with severe individual defects can still have a good fabric deterioration class. However, the figure also shows that condition data collected over longer periods of time do not allow a realistic assessment of the current structural situation. The actual rehabilitation task could be only identified by a present-day forecast of the development of condition classes and fabric deterioration classes (see right column).

Remaining useful live and fabric value (net asset value)

The fabric deterioration class and the replacement costs can be used to calculate the fabric value. This value represents the material value of a sewer network or an individual sewer section, taking into account all existing defects. The fabric value is expressed in current prices. At the time of proper construction, the fabric value of a structure and the replacement cost are identical. At the time of decommissioning of the building for construction reasons, the fabric value is depleted and amounts to 0.

Based on the age, characteristics of the sewers and the previous assessment of the CCTV inspections, STATUS simulate the aging process of the sewer network using survival functions and semi-Markov chains ([STEIN14a]). With the help of the STATUS aging model, the deterioration of the condition and the consumption of the wear reserve (fabric deterioration) can now be predicted. Knowing this prediction and installation year, it is possible to compute the useful life of the sections, and thus “remaining useful life” (counting from the present day). This makes it possible to visualize the potential depreciation losses, considering the respective depreciation periods (see Figure 7).

Strategy development and optimization

Strategic planning should include the optimization of the selected strategy. In the optimization it is taken into account the determination of the metrics for evaluating the maintenance and rehabilitation program, such as the budget, rehabilitation project duration or deadline. For this purpose, the process analysis of the current management approaches and their optimization is required to consider the conditions, criteria and limits of intervention decisions. It must be ensured that all background and boundary conditions influencing the client's decision on the main type of rehabilitation (repair/ renovation/ replacement) and the timing of the rehabilitation are transferred without contradiction into a transparent decision model. This means that all rehabilitation decisions made within the framework of the strategies are comprehensible at any time and can be justified on the basis of the decision model (Figure 8).

Finding the most appropriate strategy is an iterative optimization process. As a rule, network operators formulate at least 3 objectives, which all of them should be achieved:

• Reducing risks in the network by reducing the most critical defects.

• Preservation of asset value and minimization of depreciation losses

• Stabilization of fee income and transparent communication with the facilities and citizens.

The optimal path of action to achieve these objectives must consider a wide range of structural, hydraulic, operational, and environmental issues of similar priority, while respecting social, legal, eco-nomic, and environmental constraints. The first step of this optimization process consists of defining the objectives. In the next step, "volatile variables" (e.g., budget, rehabilitation length limits, etc.) are estimated and intervention criteria are defined to achieve these objectives. These are then modelled accordingly, integrated into the simulation, and evaluated by means of a strategy run. Indicator variables are calculated and presented from the results of this strategy run. Indicator variables are quantities from which it can be derived whether certain goals are achieved or not. These are compared and evaluated with future or previous strategy runs. To be able to evaluate individual strategies in terms of their effectiveness and efficiency as part of the strategic optimization process, a benchmark is required. This benchmark is provided by the "carry on" strategy. In the end of this iterative searching process, it is possible to find the “optimized strategy”.

This strategy variant implies that the previous rehabilitation practice of the network operator is continued for the future. Thus, it is investigated how the drain and sewer system will develop with unchanged actions and current budgets. The "carry on" strategy is the most important reference strategy, as it can be used to analyze the previous approach and examine its future stability and sustainability, and to ex-amine the effectiveness of alternative strategies.

Figure 9 and Figure 10 investments for renovation and replacement measures (d) in particular leading to a significant increase in the annual rehabilitation length (e). Accordingly, this strategy succeeds in reducing the rehabilitation backlog (f) (see also Figure 9).

The effects of the two strategies on the objectives "Reducing risks in the network by reducing the most critical defects" and "Preservation of asset value" are shown in Figure 9. With the carry-on strategy (a), the proportion of sewer sections with critical condition classes (CC 0) and thus the proportion of necessary immediate measures increases from 37% to 44% over a period of 50 years. The same applies to the development of the fabric deterioration class (b). At the start time, the reserve of wear and tear has been used up in 11% of the sewer sections (FDC 0); this proportion increases to 38% by the end of the forecast. The carry-on strategy is therefore based on a clear depletion of the wastewater infrastructure. In contrast, the "Optimized" strategy achieves both objectives. Both the proportion of critical defects (c) and the proportion of sewers with "very severe fabric deterioration" (d) are significantly reduced in the long term, which contributes to strengthening the resilience of the network and is confirmed by the reduction of the rehabilitation backlog Figure 9f.

In summary, it can be stated that with the "Optimized" strategy, the risks in the network decrease, the resilience of the network increases and the probability of successful strategy implementation increases over time. The computation of the fabric deterioration class and the derived fabric value (net asset value) for each network object allows a unique monetary comparison of the two strategies. Table 1 compares the cumulative financial / asset values over a 30-year observation period for the carry-on strategy and the optimized strategy. In addition, the "natural", undisturbed network ageing in the form of the "zero investment" strategy is also listed as a further reference system. As expected, undisturbed network ageing, which does not include any investments in the network, leads to the highest asset depletion of € 135 million (line 3, Table 1).

It is interesting to note that a continuation of the original rehabilitation practice (continue as before) also leads to a loss of substance amounting to € 13 million. In order to assess the efficiency of the optimized strategy, it is appropriate to consider the rehabilitation costs. This is characterized by an additional investment of € 89 million compared to the carry-on strategy. With this additional investment, asset value maintenance amounting of € 154 million is generated. The efficiency of the optimized strategy is made clear by the additional added value of € 65 million (line 5,Table 1). The € 65 million corresponds to an adjusted value retention of € 2.3 million per year. If the income from fees in the form of a "net asset value balance" is also included, it can be seen that an increase in rehabilitation costs of 92% can increase the net asset value balance by 360% (line 7).


Network operators are trying to achieve at least three main objectives with their asset management approaches:

• Reduce risks in the network by reducing the most critical defects

• Preservation of asset value and minimization of depreciation losses

• Stabilization of fee income and transparent communication with administrative bodies and citizens.

These objectives can only be achieved with modern asset management systems that can compute and forecast a realistic, engineering-based assessment of the structural / fabric deterioration of an object and its fabric / asset value as well as its development over time. With this information base, network-specific, well-founded and reproducible effectiveness analyses of strategy in relation to the above-mentioned objectives are possible. This makes the long-term consequences of current strategy decisions transparent and allows strategies to be adapted to the respective targets. With the help of "STATUS", this forward-looking strategic planning is possible in a consistent and reproducible manner. The exact and resilient integrated forecast model allows a well-founded prediction of the network development, both for an "intervention-free" network aging and due to a selected strategy, by means of a realistic, mathematically exact modeling of the aging processes of sewer sections and manholes.

With this decision support, a consistent assessment of risks as well as risk development and its impact on service levels and performance targets is possible. Investments can be safely planned and effectively allocated over longer periods of time, ultimately enabling sustainable asset development and transformation while optimizing budget allocation.


STEIN Infrastructure Management GmbH

Dr.-Ing. Robert Stein

Managing Director

Konrad Zuse Str. 6

44801 Bochum



+49 234 / 5167 – 110


+49 234 / 5167 – 119



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