ABSTRACT
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 R 2 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.
ABSTRACT
This paper evaluates the retrieval of soil moisture in the top 5-cm layer at 3-km spatial resolution using L-band dual-copolarized Soil Moisture Active-Passive (SMAP) synthetic aperture radar (SAR) data that mapped the globe every three days from mid-April to early July, 2015. Surface soil moisture retrievals using radar observations have been challenging in the past due to complicating factors of surface roughness and vegetation scattering. Here, physically based forward models of radar scattering for individual vegetation types are inverted using a time-series approach to retrieve soil moisture while correcting for the effects of static roughness and dynamic vegetation. Compared with the past studies in homogeneous field scales, this paper performs a stringent test with the satellite data in the presence of terrain slope, subpixel heterogeneity, and vegetation growth. The retrieval process also addresses any deficiencies in the forward model by removing any time-averaged bias between model and observations and by adjusting the strength of vegetation contributions. The retrievals are assessed at 14 core validation sites representing a wide range of global soil and vegetation conditions over grass, pasture, shrub, woody savanna, corn, wheat, and soybean fields. The predictions of the forward models used agree with SMAP measurements to within 0.5 dB unbiased-root-mean-square error (ubRMSE) and -0.05 dB (bias) for both copolarizations. Soil moisture retrievals have an accuracy of 0.052 m3/m3 ubRMSE, -0.015 m3/m3 bias, and a correlation of 0.50, compared to in situ measurements, thus meeting the accuracy target of 0.06 m3/m3 ubRMSE. The successful retrieval demonstrates the feasibility of a physically based time series retrieval with L-band SAR data for characterizing soil moisture over diverse conditions of soil moisture, surface roughness, and vegetation.
ABSTRACT
Studies of future management and policy options based on different assumptions provide a mechanism to examine possible outcomes and especially their likely benefits and consequences. The San Pedro River in Arizona and Sonora, Mexico is an area that has undergone rapid changes in land use and cover, and subsequently is facing keen environmental crises related to water resources. It is the location of a number of studies that have dealt with change analysis, watershed condition, and most recently, alternative futures analysis. The previous work has dealt primarily with resources of habitat, visual quality, and groundwater related to urban development patterns and preferences. In the present study, previously defined future scenarios, in the form of land-use/land-cover grids, were examined relative to their impact on surface-water conditions (e.g., surface runoff and sediment yield). These hydrological outputs were estimated for the baseline year of 2000 and predicted twenty years in the future as a demonstration of how new geographic information system-based hydrologic modeling tools can be used to evaluate the spatial impacts of urban growth patterns on surface-water hydrology.
