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Land cover can change frequently on intensively managed landscapes, affecting water quality across different spatiotemporal scales. Multi-resolution datasets are necessary in order to assess the extent and trends of these changes, as well as potential cross-scale interactions. In this study, both spatial and temporal analyses of land disturbance (i.e., soil exposure from vegetation removal) and water quality were performed on datasets ranging from daily to yearly time scales. Time-series analyses of land disturbance were compared against the water quality variables of total suspended solids (TSS), turbidity, and visual clarity for the Hoteo River catchment on the North Island of New Zealand for the 2000–2013 period. During forest harvest and recovery phases, exotic forests were the dominant disturbance, up to ve times the area of grassland disturbance; while after recovery, grasslands assumed the dominant role, for up to 16 times the area of forest disturbance. Time-series of TSS from eld sampling (2000–2013) and TSS-event analyses (2012–2014) displayed distinct nonlinear patterns, suggesting that after major events, sediment that is stored in the landscape is exhausted and a period of sediment build-up follows until the next major event. Time-series analyses also showed a connection between trends in connected land disturbance and visual water clarity, with connected disturbance having the potential to be a water quality indicator. Future research should be conducted at even ner spatiotemporal scales over longer periods in order to identify effects of localized land disturbances on downstream water quality

Nonlinear Changes in Land Cover and Sediment Runoff in a New Zealand Catchment Dominated by Plantation Forestry and Livestock Grazing