Aquatic Nitrate Retention at River Network Scales Across Flow Conditions Determined Using Nested In Situ Sensors

Nonpoint pollution sources are strongly influenced by hydrology and are therefore sensitive to climate variability. Some pollutants entering aquatic ecosystems, e.g., nitrate, can be mitigated by in‐stream processes during transport through river networks. Whole river network nitrate retention is difficult to quantify with observations. High frequency, in situ nitrate sensors, deployed in nested locations within a single watershed, can improve estimates of both nonpoint inputs and aquatic retention at river network scales. We deployed a nested sensor network and associated sampling in the urbanizing Oyster River watershed in coastal New Hampshire, USA, to quantify storm event‐scale loading and retention at network scales. An end member analysis used the relative behavior of reactive nitrate and conservative chloride to infer river network fate of nitrate. In the headwater catchments, nitrate and chloride concentrations are both increasingly diluted with increasing storm size. At the mouth of the watershed, chloride is also diluted, but nitrate tended to increase. The end member analysis suggests that this pattern is the result of high retention during small storms (51–78%) that declines to zero during large storms. Although high frequency nitrate sensors did not alter estimates of fluxes over seasonal time periods compared to less frequent grab sampling, they provide the ability to estimate nitrate flux versus storm size at event scales that is critical for such analyses. Nested sensor networks can improve understanding of the controls of both loading and network scale retention, and therefore also improve management of nonpoint source pollution

Sediment identification using free fall penetrometer acceleration-time histories

Abstract Knowledge of physical properties of near-surface sediments is an important requirement for many studies of the seafloor. Dynamic or Free Fall Penetrometers (FFP), instrumented with accelerometers, are widely used to assess the mechanical properties of the sediment by deriving penetration resistance from the deceleration response of the probe as it impacts and embeds the seabed. Other field investigations, a priori knowledge or a very basic description of the type of sediment (such as a description of the sediment as soft, medium or hard) derived from studying the deceleration response (accelerometer-time histories) are used for sediment identification prior to the application of an appropriate strength determination model. In many cases this information is site-specific and in others the penetration resistance is overestimated due to the dilatory effects observed in sediment with an undetected grain fraction. In this study variables affecting a dynamic penetrometer-sediment interaction system are identified. Using data from field investigations and literature we found a relationship among five variables: peak acceleration, embedment depth, total embedment time, velocity of impact and grain size. This is used to formulate a sediment identification model. The model accounts for variables that may vary widely within one deployment and it can be applied to other FFPs with different physical characteristics (such as a different mass or size). This may lead to the increased use of FFP as a deployment tool for rapid in situ characterization of the seafloor