Catchment and lake water quality modelling to assess management options for Lake Tutira

Abstract

Lake Tutira is an important ecological, historical and cultural asset to the Hawke’s Bay. It is a highly utilised trout fishery, a popular recreational destination, and is particularly significant to Ngāti Kahungunu, for its historical eel fishery and rongoa (medicinal) harakeke (flax) beds. The lake and its catchment have been substantially altered from their natural condition, including conversion of forested catchment to pasture, invasion by aquatic macrophytes such as Hydrilla sp., the introduction of grass carp (Ctenopharyngaodon idella) for weed management, and diversion of the largest stream inflow, Papakiri Stream (Sandy Creek), away from the lake and directly to the outflow (Mahiaruhe Stream) in the early 1980s. Lake Tutira’s history of poor water quality dates back decades, with Trophic Level Index (TLI; a metric of overall water quality) values from the 1960s similar to recent years, and blooms of cyanobacteria (blue-green algae) recorded as early as the 1970s. Nevertheless, the years since 2010 have been characterised by very poor water quality and particularly severe blooms, sometimes resulting in near-complete loss of oxygen from surface waters and associated fish kill events. This has attracted media attention and provided impetus from community and stakeholders to assess available management options for restoring more natural conditions and improving water quality in the lake. This report examines the drivers of poor water quality and algal blooms the lake, and assesses various management options that have either been specifically proposed for Tutira, or have proven effective for other lakes in New Zealand and globally. Here we report on monitoring undertaken by Hawke’s Bay Regional Council in the catchment (surface inflows) and lake. We also apply state-of-the-art computer models for simulating physical, chemical, and biological processes in the catchment and lake. These simulations are then used to evaluate a range of management ‘scenarios’ to provide guidance on the likely effects of management options tested with the model.