ABSTRACT
This chapter reviews site significance tests that are frequently used in detecting trends of hydro-meteorological time series. It presents field significance tests and examines a number of pitfalls in trend detection, both in data quality and in techniques, that scientists and practitioners should be aware of in their studies, in order to gain more accurate and correct results. The chapter provides general guidance on how to evaluate whether a time series is suitable for trend detection, how to select an appropriate methodology, and how to interpret the results. Detection and analysis of change in historical observation records provide important information. Land-use changes, such as urbanization and deforestation, can dramatically increase the surface runoff coefficient by increasing the impervious area, reducing the infiltration rate and water storage capacity, and shortening the time of concentration. The purpose of the majority of trend detection studies of hydrological data is to investigate if hydrological variables, such as streamflow, respond to climate changes.
