Strategic Planning of the Integrated Urban Wastewater System using Adaptation Pathway Maps

Seyed M. K. SadrA, Arturo Casal-Campos1, Guangtao Fu, Raziyeh Farmani, Sarah Ward and David Butler 1 Centre for Water Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter, North Park Road, Harrison Building, Exeter, EX4 4QF, UK 2 Centre for Water, Communities & Resilience, Faculty of Environment and Technology, University of the West of England, Bristol, BS16 1QY, UK


Terms Definition/description Reference Adaptation
Adaptation here refers to carrying out improvements on the drainage infrastructure, i.e. the engineering assets that normally define this type of systems.

Adaptation strategies
Adaptation interventions considered in this study. These may be conventional grey infrastructure (i.e. sewer pipes, pumps, storage tanks and treatment facilities) as well as alternative green infrastructure (i.e. SuDS, BMPs).

Adaptation thresholds
1. The points where changing conditions oblige a normally stable state of a system into another state or facilitate adaptation of the system (called also tipping points) van Veelen et al.
2. The points where the magnitude of changes (e.g. due to climate change) is such that the current strategy will no longer be able to meet objectives under different future scenarios (also called tipping points) Kwadijk et al. (2010) and Renaud et al. (2013) 3. The points at which threats exceed the system's ability to respond and recover (called recovery points) van Veelen et al.
4. The physical boundary conditions where acceptable technical, environmental, societal or economic standards may be compromised, requiring implementation of new actions to meet the specified objective (called also tipping points) Manocha and Babovic, (2017) 5. An adaptation limit as a point at which an action is no longer likely to be able to provide cost effective risk reduction, subject to social and environmental considerations (called also adaptation limit) Kingsborough et al. (2016) 6. The condition (or conditions) under which the current management strategy is no longer able to meet the clearly defined objective (or objectives) across a timeline; at this point, alternative adaptation strategies should be considered. Adaptation thresholds are used to evaluate the adaption domain size This study

Adaptation domain
A set of possible future states or transient scenarios in which an adaptation strategy is compliance to the adaptation threshold or thresholds. The domain size of a strategy is identified using adaptation thresholds. The domain size is evaluated in two complementary ways: (i) the number of complying epochs across the scenarios and (ii) whether or not the pathways are uninterrupted (i.e. compliant) or interrupted (i.e. non-compliant) to one or more adaptation thresholds across the entire timeline This study

Adaptation pathways
1. Alternative possible trajectories for knowledge, intervention and change, which prioritize different goals, values and functions Leach et al. (2010) 2. An analytical and foresight approach for exploring and sequencing a set of possible strategies along the planning timeline Haasnoot et al. (2013) 3. An approach that explores alternative sequences of investment decisions to achieve objectives over time in the context of uncertain future developments and environmental changes Haasnoot et al.
4. An approach that provides a visual representation of the potential sequencing and type of actions that may be implemented in the future.  The future scenarios differ from one another with respect to nine parameters (variables) indicative of various IUWWS uncertain conditions (Casal-Campos et al., 2018: (1) Misconnections (L/s): the amount of misconnected foul sewers discharging into surface sewers was assumed to be related to existing regulations enforcing the identification of such misconnections as well as to the level of maintenance regimes required to undertake remedial reconnection work.
(2) Urban creep (ha): The level of urban creep happening in a scenario is a function of the level of regulations limiting the amount of uncontrolled re-surfacing of permeable areas as well as of the public willingness to implement decentralized surface water management measures that serve those new contributing areas. If both aspects were strong under a given scenario, the level of urban creep was therefore very low (Casal-Campos et al., 2015).
(3) Water use (L/head/day): Positive attitudes towards the decentralization of water management responsibilities had an influence in reducing domestic water use (e.g. facilitate demand-side measures), along with the role of regulations and water efficient technologies.
(4) Infiltration (L/s): infiltration of groundwater into sewers is assumed to be a consequence of both low sewer maintenance regimes and the unavailability of technological solutions to provide cost-effective maintenance.
(5) Siltation: As with infiltration, the degree of siltation is determined by the level of maintenance in the sewer infrastructure and the availability of technologies that facilitate such maintenance. . (7) CC precipitation uplift (%): the effect of climate change in rainfall intensity was considered independent of scenario conditions, since it was assumed that the sensitivity of precipitation predictions to different scenarios up to the year 2050 is modest, according to UK guidance (Kirtman et al., 2013).

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(8) Impervious area in new developments (ha): Permeability changes were represented by the rate of urban creep occurring in the baseline catchment (i.e. loss of permeable area to impervious area in the original catchment) and by the increase in impervious area occurring as a consequence of urbanization (i.e. new developments) (Casal-Campos et al., 2015).
(9) Acceptability preference: acceptability of interventions under each scenario is assessed in terms of the preference for either centralized or decentralized options). These parameters were mostly linked to variations in catchment permeability and to the changes in sewer inflows, which could deteriorate system capacity in the future (Casal Campos, 2016;Casal-Campos et al., 2018). Acceptability preference 3 C C C/D D D 1. It refers to infiltration of groundwater into the sewer system.
2. The effect of siltation, which represented system capacity loss in sewer pipes due to deposited sediment, was modelled as the corresponding reduction in pipe diameter under each scenario (corresponding to fullpipe area reduction); 1: no reduction, 0: full reduction.
3. The acceptability of interventions under each scenario is assessed in terms of the preference for either Centralized (C) or Decentralized (D) options. The Innovation scenario shows a mixed preference for centralized interventions, where decentralization is also promoted.