Seasonally, snow‐covered forests are a critical source of water in the Western United States and are subject to major disturbances, including fire, harvest, disease and insect‐caused mortality, that have relatively unknown effects on water availability. In this study, we investigated changes in winter season snow accumulation and ablation in a forest following the Las Conchas fire in the Jemez Mountains of New Mexico. We investigated two competing sets of processes that should determine the peak annual snowpack prior to snowmelt: (1) reduced interception by forest canopy results in greater new snow accumulation and (2) increased winter season ablation of the snowpack results in reduced peak snowpack volumes. These processes were evaluated with approximately 800 spatially distributed manual observations of new snow, 1500 manual observations of peak snowpack, and light detection and ranging‐derived snow depth, vegetation and terrain datasets collected prior to the fire. A single snowfall event yielded significantly larger snow depths in the post‐burn area versus the unburned area (p < 0.001), with 25% to 45% interception in the unburned area and near zero in the post‐burn area. Conversely, the peak snowpack depths were significantly larger in the unburned area compared with the post‐burn area (mean of 55 and 47 cm, respectively), despite nearly identical peak snowpacks prior to the fire (72 and 72 cm, respectively). The lack of strong vegetation controls led to less variability at peak snowpack in the post‐burn area and a shift towards topographically controlled variability, caused by differences in elevation and aspect, occurring at larger spatial scales. The unburned area had roughly 10% more water available for melt than the post‐burn area, with winter season ablation reducing snowpacks by nearly 50% prior to melt in the post‐burn area. The relative importance of shortwave radiation to the snowpack energy balance and sublimation suggests that the 10% reductions in peak snow water storage found in these north‐facing areas could be a conservative estimate for winter season ablation following fire. Further work is necessary to assess the role that topography plays in altering water partitioning following forest disturbance and the potential implications for ecological health and downstream water resources. Copyright © 2013 John Wiley & Sons, Ltd.

Urban hydrology and green infrastructure (GI) can be modeled using the Automated Geospatial Watershed Assessment (AGWA) Urban tool and the Kinematic Runoff and Erosion (KINEROS2) model. The KINEROS2 model provides an urban modeling element with nine overland flow components that can be used to represent various land cover types commonly found in the built environment while treating runoff-runon and infiltration processes in a physically based manner. The AGWA Urban tool utilizes a Geographic Information System (GIS) framework to prepare parameters required for KINEROS2, executes the model, and imports results for visualization in the GIS. The AGWA Urban tool was validated on a residential subdivision in Arizona, USA, using 47 rainfall events (June 2005 to September 2006) to compare observed runoff volumes and peak flow rates with simulated results. Comparison of simulated and observed runoff volumes resulted in a slope of 1.00 for the regression equation with an R2 value of 0.80. Comparison of observed and simulated peak flows had a slope of 1.12 with an R2 value of 0.83. A roof runoff analysis was simulated for 787 events, from January 2006 through December 2015, to analyze the water availability from roof runoff capture. Simulation results indicated a 15% capture of the average monthly rainfall volume on the watershed. Additionally, rainwater captured from roofs has the potential to provide for up to 70% of the domestic annual per capita water use in this region. Five different scenarios (S1 - base, S2 - with retention basins, S3 - with permeable driveways, S4 - with rainwater harvesting cisterns, and S5 - all GI practices from S2, S3, and S4) were simulated over the same period to compare the effectiveness of GI implementation at the parcel level on runoff and peak flows at the watershed outlet. Simulation results indicate a higher runoff volume reduction for S2 (53.41 m3 average capacity, average 30% reduction) as compared to S3 (average 14% reduction), or S4 (3.78 m3 capacity, average 6% reduction). Analysis of peak flows reveal larger peak flow reduction for S2. S3 showed more reduction of smaller peak flows as compared to S4.

The Automated Geospatial Watershed Assessment tool (AGWA, see: www.tucson.ars.ag.gov/agwaor http://www.epa.gov/esd/land-sci/agwa/) is a GIS interface jointly developed by the USDA Agricultural Research Service, the U.S. Environmental Protection Agency, the University of Arizona, and the University of Wyoming to automate the parameterization and execution of a suite of hydrologic and erosion models (RHEM, KINEROS2 and SWAT). Through an intuitive interface the user selects an outlet from which AGWA delineates anddiscretizes the watershed using a Digital Elevation Model (DEM). The watershed modelelements are then intersected with terrain, soils, and land cover data layers to derive the requisitemodel input parameters. The chosen model is then run, and the results are imported backinto AGWA for graphical display. AGWA can difference results from multiple simulations to examine relative change over a variety of input scenarios (e.g. climate/storm change, land cover change, implementation of BMPs, present conditions and alternative futures).This allows managers to identify potential problem areas where additional monitoring can be undertaken or mitigation activities can be focused. Application examples of AGWA will be presented including post-fire assessment, implementation of rangeland BMPs, green infrastructure, and future change analysis. Versions of AGWA are available for ESRI ArcView 3.x and ArcGIS 9.x and 10.x. Watershed Management 2015 © ASCE 2015 120 © ASCE Watershed Management 2015 Downloaded from ascelibrary.org by UNIVERSITE LAVAL on 10/07/15.

No abstract

In arid and semi-arid regions, green infrastructure (GI) designs can address several issues facing urban environments, including augmenting water supply, mitigating flooding, decreasing pollutant loads, and promoting greenness in the built environment. An optimum design captures stormwater, addressing flooding and water quality issues, in a way that increases water availability to support natural vegetation communities and landscaping in the built environment. A module was developed for the Automated Geospatial Watershed Assessment (AGWA) tool which supports the design and placement of a suite of GI practices, singularly or in combination, in order to simulate urban hydrology with and without GI features at the household and neighborhood scale.The GI tool takes advantage of the advanced, physically-based infiltration algorithms and geometric flexibility of the Kinematic Runoff and Erosion (KINEROS2) watershed model. The resulting software provides an up-to-date GISbased GI assessment framework that automatically derives model parameters from widely available spatial data. It is also capable of manipulating GI features within a graphical interface to conveniently view and compare simulation results with and without GI features at a lot, neighborhood or small catchment scale. The new tool was used to assess a variety of GI designs across a subdivision in Sierra Vista, Arizona for the design objectives: maximize stormwater capture, maximize water augmentation, and maximize ecosystem services. Watershed Management 2015 © ASCE 2015 229 © ASCEWatershed Management 2015 Downloaded from ascelibrary.org by Nanyang Technological University-Library on 08/20/15.