Hydrologic catchment response varies in time. The goal of this dissertation is to investigate how and why it varies and what controls these variations. In order to tackle these questions the first step is to develop a method that permits the capturing of the temporal variation of transit time distributions (TTDs). To this end, the established transfer function-convolution approach using time series of stable water isotopes was modified so that it is now able to determine variable mean transit times (mTTs). The type and the shape parameter of the transfer function also vary in time. We found that antecedent moisture content, saturated hydraulic conductivity, soil depth and subsequent precipitation intensity are all potential controls. We propose a dimensionless number that integrates these controls and relates available storage to incoming and outgoing water fluxes in combination with information on antecedent moisture conditions to predict TTD type and shape. The individual TTDs for every time step produced by this model can be superimposed, summed and normalized to create a classification tool for catchments that is based on its general response behavior to precipitation events: the master transit time distribution. With this model in hand the hydrologic response for three consecutive monsoon seasons in ten nested subcatchments was examined. It was found that the major response controls were changing between the years in accordance with three hydrologic response modes. The mTT correlated most strongly with soil depth in the first year, with hydraulic conductivity in the second year and with curvature in the third year. These variations were produced by differences in precipitation patterns that led to differences in soil saturation and consequently to different dominant flow processes: in the first year most of the water left the catchment via fast flow paths (macropore flow, overland flow), in the second year shallow subsurface flow in the soil matrix was more dominant and in the third year most outflowing water derived from slow base flow. To better predict hydrologic catchment response we propose to apply a dimensionless number to determine the catchment response mode for every time step before selecting the appropriate response control.