Advancing the understanding of watershed dynamics and underpinning scientific studies on the changes in water cycles, ecological patterns, and climate trends often rely on streamflow data acquired at gaging stations operated by various monitoring agencies. The monitoring methods used at these stations are based on empirical or semi-empirical rating curves obtained with statistical analysis uniformly applied to datasets collected in steady and unsteady flows. These one-to-one ratings are subsequently used for estimating steady and unsteady flows, even though, in the latter case, the relationships between flow variables are different for the rising and falling phases of the flow hydrographs. The non-singled relationships are more prominent in lowland areas subjected to high flows, where the streamflow variables display a hysteretic behavior. Recent advances in measurement technologies (e.g., acoustic-, radar-, and image-based), have dramatically transformed our capabilities to conduct in-situ measurements. This paper demonstrates such capabilities by presenting new information extracted from directly measured data and novel algorithms applied to simultaneous measurements of stages and index velocities acquired with a SonTek Side-Looker (pertaining to the family of Horizontal Acoustic Current Profilers-HADCP) at a river location prone to hysteresis. The presented results demonstrate a) the capability of the conventional monitoring methods (i.e., index-velocity approach supported by HADCPs) to capture the dynamics of the unsteady flows, b) the opportunity offered by HADCP measurements to re-think monitoring methods altogether by using directly measured data and their spatial and temporal gradients in conjunction with canonical flow equations (i.e., St Venant Equations) without using ratings, and c) the opportunity to exploit subtle features of the hysteretic behavior for developing short-term forecasting of flood crest magnitude and its arrival time using only in-situ acquired data, without making recourse to hydrologic/hydraulic modeling. Moving away from the traditional empirically based ratings, would unquestionably contribute to reducing uncertainties related to modeling flow routing, thus improving the quality of conventional forecasts.