Detecting river-scale turbidity disturbance after rainfall using NEXt-Generation Weather RADar (NEXRAD) and the Intelligent River

Abstract

Turbidity of surface water is a major environmental and human health issue in the United States. This study integrated two years (January 1, 2015, to December 31, 2016) of high frequency in situ turbidity and stream flow data with daily Next Generation Radar rainfall data for nine Intelligent River sensors in order to learn about river-scale turbidity dynamics and disturbances after rainfall in the Savannah River, Georgia. Analysis of Intelligent River turbidity data revealed a highly dynamic system. A prevailing spatial pattern of increasing turbidity with decreasing distance from the Atlantic Ocean was evident at any given time during the study period, but the typical distribution of turbidity can be disrupted for days to months. Observed turbidity disturbances are related to periods of increased stream flow and rainfall events. Short-term (one to seven days) turbidity disturbances at river miles 150 or greater appear to be intricately linked to rainfall, but turbidity disturbances after the same rainfall events at river miles 27 and 61 were much less dramatic or not detected at all. These results paint an expectedly complex picture of high-frequency turbidity measurements at nine locations in a large river network. However, these results also highlight the feasibility and novelty of integrating NEXt-Generation Weather RADar (NEXRAD) and in situ sensing for data-driven knowledge discovery in soil and water conservation.