The Resilient Shorelines study at University of Canterbury (UC) is using the Avon Heathcote Estuary Ihutai to investigate ecosystem-based approaches to conservation planning and adaptation in response to environmental change. In particular, the study is using a novel opportunity to understand effects of the Canterbury earthquakes that may be similar to impacts of sea level rise. These result from topographic and bathymetry changes in and around the estuary and associated waterways (Beaven et al., 2012; Cochran et al., 2014) that have driven changes in hydrodynamics (Measures et al., 2011). Therefore the wider context for the work reported here is to develop methodologies for modelling the impacts of sea level rise on estuaries and coastal river mouths using the Avon-Heathcote Estuary/Ihutai as a case study. Initial objectives have included establishing the magnitude of earthquake-induced changes. Subsequent steps will include establishing the relationships between strong physical drivers such as water levels and salinity, and the spatial pattern of estuarine ecosystems. There is particular focus on understanding salinity changes in the upper estuarine ecosystem in the vicinity of the freshwater-saltwater interface. In these areas, species, habitats and ecosystems that are adapted to brackish conditions are expected to migrate in response to the inland penetration of salt water under sea level rise. An example is the location of īnanga spawning habitat that is associated with the inland extent of salt water intrusion on spring tides (Taylor, 2002). It is expected to be strongly affected by sea level rise. To facilitate the development of ecosystem-based scenario models for sea level rise, a salinity model with resolution at ecological meaningful scales was required. An existing fine scale hydrodynamic model was available using Delft3D software (Deltares, 2012) that had been developed for ECan and MBIE following the earthquakes (Measures & Bind, 2013). However, it had not been calibrated for salinity. A collaborative project was designed between UC and NIWA to calibrate the model and develop a scenario modelling approach for sea level rise at a level of resolution sufficient for understanding sea level rise impacts on īnanga (whitebait) spawning habitat. The project was allocated funding from Brian Mason Scientific and Technical Trust and commenced in late 2015. The purpose of this report is to provide a description of the model development process and an illustration of model outputs from an initial set of modelled scenarios for sea level rise.
Sewerage systems convey sewage, or wastewater, from residential or commercial buildings through complex reticulation networks to treatment plants. During seismic events both transient ground motion and permanent ground deformation can induce physical damage to sewerage system components, limiting or impeding the operability of the whole system. The malfunction of municipal sewerage systems can result in the pollution of nearby waterways through discharge of untreated sewage, pose a public health threat by preventing the use of appropriate sanitation facilities, and cause serious inconvenience for rescuers and residents. Christchurch, the second largest city in New Zealand, was seriously affected by the Canterbury Earthquake Sequence (CES) in 2010-2011. The CES imposed widespread damage to the Christchurch sewerage system (CSS), causing a significant loss of functionality and serviceability to the system. The Christchurch City Council (CCC) relied heavily on temporary sewerage services for several months following the CES. The temporary services were supported by use of chemical and portable toilets to supplement the damaged wastewater system. The rebuild delivery agency -Stronger Christchurch Infrastructure Rebuild Team (SCIRT) was created to be responsible for repair of 85 % of the damaged horizontal infrastructure (i.e., water, wastewater, stormwater systems, and roads) in Christchurch. Numerous initiatives to create platforms/tools aiming to, on the one hand, support the understanding, management and mitigation of seismic risk for infrastructure prior to disasters, and on the other hand, to support the decision-making for post-disaster reconstruction and recovery, have been promoted worldwide. Despite this, the CES in New Zealand highlighted that none of the existing platforms/tools are either accessible and/or readable or usable by emergency managers and decision makers for restoring the CSS. Furthermore, the majority of existing tools have a sole focus on the engineering perspective, while the holistic process of formulating recovery decisions is based on system-wide approach, where a variety of factors in addition to technical considerations are involved. Lastly, there is a paucity of studies focused on the tools and frameworks for supporting decision-making specifically on sewerage system restoration after earthquakes. This thesis develops a decision support framework for sewerage pipe and system restoration after earthquakes, building on the experience and learning of the organisations involved in recovering the CSS following the CES in 2010-2011. The proposed decision support framework includes three modules: 1) Physical Damage Module (PDM); 2) Functional Impact Module (FIM); 3) Pipeline Restoration Module (PRM). The PDM provides seismic fragility matrices and functions for sewer gravity and pressure pipelines for predicting earthquake-induced physical damage, categorised by pipe materials and liquefaction zones. The FIM demonstrates a set of performance indicators that are categorised in five domains: structural, hydraulic, environmental, social and economic domains. These performance indicators are used to assess loss of wastewater system service and the induced functional impacts in three different phases: emergency response, short-term recovery and long-term restoration. Based on the knowledge of the physical and functional status-quo of the sewerage systems post-earthquake captured through the PDM and FIM, the PRM estimates restoration time of sewer networks by use of restoration models developed using a Random Forest technique and graphically represented in terms of restoration curves. The development of a decision support framework for sewer recovery after earthquakes enables decision makers to assess physical damage, evaluate functional impacts relating to hydraulic, environmental, structural, economic and social contexts, and to predict restoration time of sewerage systems. Furthermore, the decision support framework can be potentially employed to underpin system maintenance and upgrade by guiding system rehabilitation and to monitor system behaviours during business-as-usual time. In conjunction with expert judgement and best practices, this framework can be moreover applied to assist asset managers in targeting the inclusion of system resilience as part of asset maintenance programmes.
