The Effect of Lithology and Agriculture at the Susquehanna Shale Hills Critical Zone Observatory. Issue 1 (11th October 2018) - Li, Li
Abstract : Core Ideas: Two new subcatchments are used to test the importance of lithology and land use. Differences in lithology and land use result in differences in soils and waters. Despite differences, all catchments have a shallow and a deep water table. The relative importance of flow paths controls distinct chemistry response to discharge. Cross‐site comparison will ultimately enable upscaling from the catchment to large scale. The footprint of the Susquehanna Shale Hills Critical Zone Observatory was expanded in 2013 from the forested Shale Hills subcatchment (0.08 km 2 ) to most of Shavers Creek watershed (163 km 2 ) in an effort to understand the interactions among water, energy, gas, solute, and sediment. The main stem of Shavers Creek is now monitored, and instrumentation has been installed in two new subcatchments: Garner Run and Cole Farm. Garner Run is a pristine forested site underlain by sandstone, whereas Cole Farm is a cultivated site on calcareous shale. We describe preliminary data and insights about how the critical zone has evolved on sites of different lithology, vegetation, and land use. A notable conceptual model that has emerged is the "two water table" concept. Despite differences in critical zone architecture, we found evidence in each catchment of a shallow and a deep water table, with the former defined by shallow interflow and the latter defined by deeper groundwater flow through weathered and fractured bedrock. We show that the shallow and deep waters have distinct chemical signatures. The proportion of contribution from each water type to stream discharge plays a key role in determining how concentrations, including nutrients, vary as a function of stream discharge. This illustrates the benefits of the critical zone observatory approach: having common sites to grapple with cross‐disciplinary research questions, to integrate diverse datasets, and to support model development that ultimately enables the development of powerful conceptual and numerical frameworks for large‐scale hindcasting and forecasting capabilities.