Land use and climate change impacts on water quality and quantity in the Waipara River catchment North Canterbury, New Zealand : A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy at Lincoln University

Abstract

In New Zealand, degradation of water quality due to land use activities is perceived as the largest and most threatening environmental issue. The primary aim of this thesis was to assess the impact of land use and climate change on water quality and quantity of the Waipara River catchment. The Soil and Water Assessment Tool (SWAT), constituent load estimator program (LOADEST) and remote sensing techniques were used. The SWAT model was calibrated and validated for hydrology on monthly time-step using flow data (2001-2012) from the Teviotdale gauge station. Water quality data from the same station was used in calibrating for nutrients - nitrate (N) and phosphorus (P). Due to the shorter period (2001 - 2006) of the available water quality records, LOADEST was used in generating time series water quality data to match the flow records. SWAT model parameters were estimated and ranked for their sensitivity. Model performance was assessed using the Nash Sutcliffe efficiency index (NSE) and Regression Coefficient (R2). The NSE and R2 obtained for the study are 0.82, 0.85 and 0.73, 0.74 for flow calibration and validation respectively; while the NSE and R2 values for N and P calibration and validation were 0.77, 0.80 and 0.71, 0.72 respectively. Land use/cover change scenario analyses were implemented on three Landsat image data sets, and using Markov and Cellular Automata (MCA) to project for land uses in the years 2020, 2025 and 2030. The trend in land use change is based on the 2013 land cover which is considered as the baseline. Among seven land use classes identified, two potential fast growing land use types are vineyards and beef/dairy. Based on these analyses, they are expected to increase by 2.2%, 9.3%, 13.5%, and 1.8%, 7.3%, 13.0% in 2020, 2025 and 2030 respectively, assuming that current trends continue. The SWAT simulations of catchment average N yield in surface water is 4.73kg/ha/yr and will increase by 3.6%, 17.4% and 29.7% in year 2020,2025 and 2030 respectively. P yield of 0.78kg/ha/yr is estimated to increase by 2.5%, 6.3% and 9.4% respectively for years 2020, 2025 and 2030. Sediment yield is also predicted to increase from the current 0.71T/ha/yr by 7.0%, 15.9% and 21.4% in 2020, 2025 and 2030 respectively. The spatial distribution of pollutant sources: nitrogen, phosphorus and sediment in the catchment are also revealed by this study.Estimates of water demand showed that 113,805,329.4m³, 145,417,920.9m³ and 189,675,549m³ of water would be required by the increasing dairy land use in year 2020, 2025 and 2030 respectively.The extent of increase in temperatures due to climate change from years 2016 to 2050 will range between approximately +0.6°C and +1.0°C; and +1.2°C and +3.3°C in the period 2065–2099 relative to the strength of radiative forcing (Representative Concentration Pathways - RCP 8.5. 6.0 and 4.5). A decrease in surface flows of approximately 1% - 9% according to RCP strength is expected over winter in years 2039–2050. Winter months of same period will experience 4%, 1.6% and 0.5% reductions in groundwater levels under RCP 8.5, 6.0 and 4.5 climate scenarios respectively. The study showed that the projected land use changes, especially increase in beef/dairy operations, will increase nitrate and sediment loadings to the Waipara River in the future. It has also determined the amount of water required to meet the water demand for potential increases in dairy land use in the catchment, which could be vital to the Regional Council in resolving future water needs. Meanwhile, changing from predominantly grazing activities to forestry and vineyard scenarios indicates that N and P yields will decrease generally under RCP 4.5 and RCP 6.0 climatic conditions. Rate of reduction in N yield under the two climatic conditions for the respective land use change scenarios ranges between 30% and 70% while P yield will decrease by approximately 40 to 52%.