Detection of Estuarine Salinity Change Due to Sea-Level Rise

智力优势。将开发一种检测海平面上升对河口盐度影响的方法。 该方法利用高时间分辨率记录的盐度，径流和潮汐阶段，以开发河流和潮流对盐度的影响的统计模型。 然后将这些模型应用于时间分辨率较低的长期盐度观测。 预计海平面上升是残差趋势的主要原因（观测值减去模型值）。 该方法将应用于几个中大西洋河口，那里的数据记录很长，相对海平面上升约为全球平均水平的两倍。 模拟研究和比例参数表明，海平面信号远高于仪器误差。 不确定的和使研究具有探索性的是：（1）潮汐和河流对盐度影响的量化精度;（2）仪器记录是否具有足够的长度和分辨率。 更广泛的影响。有效的海岸管理需要强大的模型预测未来100年的河口盐度。 只有用明确揭示海平面上升信号的观测数据对模型进行校准，模型才是可靠的。 这一提议是揭示这种信号的第一次尝试。 该方法是一般性的，足以适用于任何监测河口。

Intellectual Merit. A method of detecting the impact of sea-level rise on estuarine salinity will be developed. The method exploits high temporal resolution records of salinity, streamflow and tidal stage in order to develop statistical models of the influence of rivers and tidal currents on salinity. The models are then applied to long-term salinity observations of lower temporal resolution. Sea-level rise is the expected main cause of trends in the residual (observed minus modeled). The method will be applied to several mid-Atlantic estuaries, where data records are long and relative sea-level rise is about twice the global average. Modeling studies and scaling arguments suggest that the sea-level signal is well above instrumental error. What is uncertain and what makes the research exploratory is (1) the accuracy to which tidal and riverine influences on salinity can be quantified and (2) whether the instrumental records are of sufficient length and resolution. Broader Impacts. Effective coastal management requires robust model predictions of estuarine salinity over the next 100 years. Models will be reliable only if they are calibrated with observations that clearly reveal a signal attributed to sea-level rise. This proposal is a first attempt to uncover such a signal. The method is general enough to be applied to any monitored estuary.