A fundamental characteristic of all river and stream ecosystems is that of discharge water from the landscape. The volume of water flowing in a channel is measured as a function of volume through a cross section of a stream per unit time. This measurement is key to understanding the physical forces that shape streams and alter the distribution of biota within the stream. This chapter details the various techniques used to measure discharge, and ranges from volumetric analysis (the most accurate but least used) to the most commonly applied velocity–area method to more advanced slope–area methods, which require estimates of channel resistance. In addition, flood frequency analysis and the applications of flood recurrence estimates are detailed. The utilization of newer acoustic Doppler methods are described, as well as the emerging field of geographic flow pattern analysis tied to large-scale temporal change in meteorological patterns (Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation, and El Nino–Southern Oscillation) that affect hydrographs on decadal or multidecadal intervals.

Discharge Measurements and Streamflow Analysis

A multiscale and multivariate analysis of precipitation and streamflow variability in relation to ENSO, NAO and PDO

Baseflow response to climate variability induced droughts in the Apalachicola-Chattahoochee-Flint River Basin, U.S.A.

This study compared two types of approaches to downscale seasonal precipitation (P) and 2-m air temperature (T2M) forecasts from the North American Multimodel Ensemble (NMME) over the states of Alabama, Georgia, and Florida in the southeastern United States (SEUS). Each NMME model forecast was evaluated. Two multimodel ensemble (MME) schemes were tested by assigning equal weight to all forecast members (SuperEns) or by assigning equal weights to each model’s ensemble mean (MeanEns). One type of downscaling approach used was a model output statistics (MOS) method, which was based on direct spatial disaggregation and bias correction of the NMME P and T2M forecasts using the quantile mapping technique [spatial disaggregation with bias correction (SDBC)]. The other type of approach used was a perfect prognosis (PP) approach using nonparametric locally weighted polynomial regression (LWPR) models, which used the NMME forecasts of Nino-3.4 sea surface temperatures (SSTs) to predict local-scale P and T2M...

Nathan T. Johnson

Papers

Pacific and Atlantic sea surface temperature influences on streamflow in the Apalachicola–Chattahoochee–Flint river basin