Many global to local-scale issues such as changing climate, urbanization, intensification of agricultural activities, deforestation, and geopolitical conflicts pose serious challenges to the availability, accessibility, and management of water resources. Researchers, decision makers, and the general public are interested in understanding the impacts of these emerging issues so that water resources can be managed sustainably in the future. Besides availability, decision makers and the general public are also interested in how water quality will be impacted by pesticides, nutrients, pathogens, and emerging contaminants including pharmaceuticals and hormones, which are a serious concern for water security. Simulation models play a critical role in understanding the hydrologic processes of a system, the system's behavior, and how it will change in the future due to natural and anthropogenic factors. A plethora of models exist in the field of hydrology to address hydrologic and water quality issues at various spatial and temporal scales. Among these, the Soil and Water Assessment Tool (SWAT) (Arnold et al., 1998) has been used globally to address issues related to hydrology, water quality, and agricultural management (e.g., Gassman et al., 2014; Abbaspour et al., 2015; Cousino et al., 2015; Basheer et al., 2016). SWAT is a semidistributed, conceptual and continuous time catchment-scale hydrologic model supported and used by a global community of researchers, decision makers, and practitioners. The model is open source, has multiple geographic information system interfaces such as ArcSWAT and QSWAT for creating input files, and user-friendly tools for model calibration. SWAT has been continuously improved and expanded since it was created in the early 1990s. Arnold and Fohrer (2005) describe the most significant improvements of the model between releases from its creation until SWAT2000 (e.g., incorporation of multiple hydrologic response units, instream kinetic routines, and Green-Ampt infiltration). Recent improvements include the incorporation of routing capabilities between landscape units or grids (Arnold et al., 2010). SWAT is ideally suited for addressing a wide array of issues related to climate change, land use change, bioenergy crops, blue and green water availability, sediment transport, nutrient cycle and contaminant loads, and best management practices. In addition, the model is flexible in its spatial discretization for applications ranging from watershed to continental scale. Due to its open source nature and an active development community, SWAT is constantly being improved and augmented with new process representations. The goal of this featured series is to demonstrate the versatility of SWAT in addressing traditional hydrologic problems such as Best Management Practices (BMP) implementation, land use/climate change impacts, model/data uncertainty, and emerging issues such as the impact of natural gas development and bio-cropping scenarios on hydrology. In this issue, the use of SWAT to assess the role of climate and land use changes on hydrology of three South Dakota watersheds is presented (Paul et al., 2016). The study by Radcliffe and Mukundan (2016) demonstrates the role of precipitation data quality on SWAT model calibration and validation. Mittelstet et al. (2016) use modified streambank erosion and instream phosphorus routines to study the relative contribution of phosphorus from streambank erosion compared to overland sources in Barren Fork Creek watershed in Oklahoma. Bieger et al. (2016) introduce SWAT+, the next major release of SWAT code, which includes flow and pollutant routing across the landscape, and apply it to the Little River Experimental Watershed in Georgia. Future articles in this series will report on phosphorus transport at watershed scale, upland and foot slope vegetated buffers in agricultural fields, channel representation and sediment export, and novel model calibration techniques. Overall, this featured series presents a cross section of current research topics from around the world which contribute to improved understanding of water resources management and conservation, whether through improved modeling techniques or analysis of the simulated impact of land management under current or future climate.
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