Integrating Field Observations and Reactive Transport Modeling to Predict Watershed Water Quality under Environmental Perturbations

Watersheds play a critical role in supplying water resources needed for humanuse and ecosystem health. Understanding and predicting how, when,and where changes in the quantity and quality of water resources occur underdierent environmental stresses including extreme events is crucial forsustainable management of water resources under a changing environment.However, few studies have attempted to quantify or identify the factors andprocess interactions controlling the impact of extreme events across watershedsystems. Only few large-scale studies include coordinated monitoringand modeling eorts, which limits our ability to assess the large-scale impactof extreme events on water supply and quality. Methods are lacking topropagate uncertainty in process understanding through an integrated hydrobiogeochemicalmodel framework and evaluate its importance, thus failing to take full advantage of the information potentially available through transformativeadvances in characterization technologies from high-resolution massspectrometry to airborne and satellite-based remote sensing. There are consequentrisks to our nations water security and to human and ecosystem healththat may become exacerbated with the increasing frequency of extreme eventsthat is projected for the coming decades. This paper reviews the current statusof watershed science for both water quantity and quality and identiescritical gaps in our current knowledge and modeling capability in addressingthe emergent needs in predicting watershed hydrologic and biogeochemicalresponses (i.e., water quantity and quality) under natural and anthropogenicperturbations. We highlight the need to (1) understand how environmentalperturbations including extreme events like oods and droughts propagatethrough watershed systems and assess their short- and long-term impactson watershed biogeochemistry, water quality and their recovery pathways;(2) develop and improve a watershed water quality model that reects thestate of scientic understanding gained from observations; and (3) constructa data-model fusion system for watershed characterization, process identi-cation, and mechanistic model parameterization. A large base of modeling,monitoring and data capabilities have been built by various federal governmentagencies given the relevance of water to their critical missions. Anemerging need is to build an integrated national capability for watershedwater availability and quality that can address water-related missions acrossmultiple federal agencies.