Nitrogen Subsidies from Hillslope Alder Stands to Streamside Wetlands and Headwater Streams,Kenai Peninsula,Alaska

We examined nitrogen transport and wetland primary production along hydrologic flow paths that link nitrogen‐fixing alder (Alnus spp.) stands to downslope wetlands and streams in the Kenai Lowlands, Alaska. We expected that nitrate concentrations in surface water and groundwater would be higher on flow paths below alder. We further expected that nitrate concentrations would be higher in surface water and groundwater at the base of short flow paths with alder and that streamside wetlands at the base of alder‐near flow paths would be less nitrogen limited than wetlands at the base of long flow paths with alder. Our results showed that groundwater nitrate‐N concentrations were significantly higher at alder‐near sites than at no‐alder sites, but did not differ significantly between alder‐far sites and no‐alder sites or between alder‐far sites and alder‐near sites. A survey of ¹⁵N stable isotope signatures in soils and foliage in alder‐near and no‐alder flow paths indicated the alder‐derived nitrogen evident in soils below alder is quickly integrated downslope. Additionally, there was a significant difference in the relative increase in plant biomass after nitrogen fertilization, with the greatest increase occurring in the no‐alder sites. This study demonstrates that streamside wetlands and streams are connected to the surrounding landscapes through hydrologic flow paths, and flow paths with alder stands are potential “hot spots” for nitrogen subsidies at the hillslope scale.     

AutoRAPID: A Model for Prompt Streamflow Estimation and Flood Inundation Mapping over Regional to Continental Extents

This article couples two existing models to quickly generate flow and flood‐inundation estimates at high resolutions over large spatial extents for use in emergency response situations. Input data are gridded runoff values from a climate model, which are used by the Routing Application for Parallel computatIon of Discharge (RAPID) model to simulate flow rates within a vector river network. Peak flows in each river reach are then supplied to the AutoRoute model, which produces raster flood inundation maps. The coupled tool (AutoRAPID) is tested for the June 2008 floods in the Midwest and the April‐June 2011 floods in the Mississippi Delta. RAPID was implemented from 2005 to 2014 for the entire Mississippi River Basin (1.2 million river reaches) in approximately 45 min. Discretizing a 230,000‐km² area in the Midwest and a 109,500‐km² area in the Mississippi Delta into thirty‐nine 1° by 1° tiles, AutoRoute simulated a high‐resolution (~10 m) flood inundation map in 20 min for each tile. The hydrographs simulated by RAPID are found to perform better in reaches without influences from unrepresented dams and without backwater effects. Flood inundation maps using the RAPID peak flows vary in accuracy with F‐statistic values between 38.1 and 90.9%. Better performance is observed in regions with more accurate peak flows from RAPID and moderate to high topographic relief.     

Uncertainty Models for Estimates of Physical Characteristics of River Segments Over Large Areas

Spatially comprehensive estimates of the physical characteristics of river segments over large areas are required in many large‐scale analyses of river systems and for the management of multiple basins. Remote sensing and modeling are often used to estimate river characteristics over large areas, but the uncertainties associated with these estimates and their dependence on the physical characteristics of the segments and their catchments are seldom quantified. Using test data with varying degrees of independence, we derived analytical models of the uncertainty associated with estimates of upstream catchment area (CA), segment slope, and mean annual discharge for all river segments of a digital representation of the hydrographic network of France. Although there were strong relationships between our test data and estimates at the scale of France, there were also large relative local uncertainties, which varied with the physical characteristics of the segments and their catchments. Discharge and CA were relatively uncertain where discharge was low and catchments were small. Discharge uncertainty also increased in catchments with large rainfall events and low minimum temperature. The uncertainty of segment slope was strongly related to segment length. Our uncertainty models were consistent across large regions of France, suggesting some degree of generality. Their analytical formulation should facilitate their use in large‐scale ecological studies and simulation models.     

A Spatially Explicit Resource-Based Approach for Managing Stream Fishes in Riverscapes

The article describes a riverscape approach based on landscape ecology concepts, which aims at studying the multiscale relationships between the spatial pattern of stream fish habitat patches and processes depending on fish movements. A review of the literature shows that few operational methods are available to study this relationship due to multiple methodological and practical challenges inherent to underwater environments. We illustrated the approach with literature data on a cyprinid species (Barbus barbus) and an actual riverscape of the Seine River, France. We represented the underwater environment of fishes for different discharges using two-dimensional geographic information system-based maps of the resource habitat patches, defined according to activities (feeding, resting, and spawning). To quantify spatial patterns at nested levels (resource habitat patch, daily activities area, subpopulation area), we calculated their composition, configuration, complementation, and connectivity with multiple spatial analysis methods: patch metrics, moving-window analysis, and least cost modeling. The proximity index allowed us to evaluate habitat patches of relatively great value, depending on their spatial context, which contributes to the setting of preservation policies. The methods presented to delimit potential daily activities areas and subpopulation areas showed the potential gaps in the biological connectivity of the reach. These methods provided some space for action in restoration schemes.     

SWATmodel: A Multi‐Operating System,Multi‐Platform SWAT Model Package in R

The Soil and Water Assessment Tool (SWAT) model (Arnold et al., 1998) is a popular watershed management tool. Currently, the SWAT model, actively supported by the U.S. Department of Agriculture and Texas A&M, operates only on Microsoft^® Windows, which hinders modelers that use other operating systems (OS). This technical note introduces the Comprehensive R Archive Network (CRAN) distributed “SWATmodel” package which allows SWAT 2005 and 2012 to be widely distributed and run as a linear model‐like function on multiple OS and processor platforms. This allows researchers anywhere in the world using virtually any OS to run SWAT. In addition to simplifying the use of SWAT across computational platforms, the SWATmodel package allows SWAT modelers to utilize the analytical capabilities, statistical libraries, modeling tools, and programming flexibility inherent to R. The software allows watershed modelers to develop a simple hydrological watershed model conceptualization of the SWAT model and to obtain a first approximation of the minimum expected results a more complicated model should deliver. As a proof of concept, we test the SWAT model by initializing and calibrating 314 U.S. Geological Survey stream gages in the Chesapeake Bay watershed and present the results.     

A New Open‐Access HUC‐8 Based Downscaled CMIP‐5 Climate Model Forecast Dataset for the Conterminous United States

Watershed‐scale hydrologic simulation models generally require climate data inputs including precipitation and temperature. These climate inputs can be derived from downscaled global climate simulations which have the potential to drive runoff forecasts at the scale of local watersheds. While a simulation designed to drive a local watershed model would ideally be constructed at an appropriate scale, global climate simulations are, by definition, arbitrarily determined large rectangular spatial grids. This paper addresses the technical challenge of making climate simulation model results readily available in the form of downscaled datasets that can be used for watershed scale models. Specifically, we present the development and deployment of a new Coupled Model Intercomparison Project phase 5 (CMIP5) based database which has been prepared through a scaling and weighted averaging process for use at the level of U.S. Geological Survey (USGS) Hydrologic Unit Code (HUC)‐8 watersheds. The resulting dataset includes 2,106 virtual observation sites (watershed centroids) each with 698 associated time series datasets representing average monthly temperature and precipitation between 1950 and 2099 based on 234 unique climate model simulations. The new dataset is deployed on a HydroServer and distributed using WaterOneFlow web services in the WaterML format. These methods can be adapted for downscaled General Circulation Model (GCM) results for specific drainage areas smaller than HUC‐8. Two example use cases for the dataset also are presented.