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Cross‐scale structural and functional connectivity feedbacks can amplify exogenous forces in dryland environments leading to ecosystem state change (e.g., from grassland to shrubland). Attenuation of these connectivity feedbacks would ostensibly be required to restore transitioned ecosystems to their former state. We compared structural, hydrologic, and sediment connectivity on a shrub‐encroached semi‐arid grassland in south‐eastern Arizona, USA, to that of a nearby site experiencing an increase in non‐native perennial grass (Lehmann lovegrass) abundance 5‐year following treating shrubs with tebuthiuron herbicide. Soil/vegetation attributes were quantified and paired with hydrologic experiments at fine (0.5 m2) to hillslope (50 m2) scales. Fine‐scale rainfall simulations (120 mm·h−1 rainfall intensity; 45 min) showed interspaces between shrubs were hydrologically similar on the treated and control sites, whereas herbicided shrub patches were more resource conserving than those within the control (terminal infiltration rates of 105 and 71 mm·h−1, respectively). High structural connectivity of bare ground (basal gap lengths >200 cm) was correlated with increased concentrated flow run‐off and accompanied by greater sediment yields within the untreated site at a coarse scale (~9 m2). Hillslope‐scale modelling suggested a divergence between hydrologic and sediment connectivity: run‐off from high intensity rainfall was similar between sites, while predicted sediment yield was 44% less within the tebuthiuron‐treated site. Our results indicate (i) hydraulic properties of soils between shrubs are unresponsive to herbicide treatment, (ii) disruption of structural connectivity of these interspaces associated with grass cover increases subsequent to herbicide application attenuated run‐off and the energy needed for sediment transport, and (iii) sediment connectivity is reduced by conversion to a novel grassland ecological state. [ABSTRACT FROM AUTHOR]

Appropriate land-use, watershed-management, and flood-attenuation plans are critical in the cross-border urban environment known collectively as Ambos Nogales. This paper summarizes methodologies for predicting the watershed response associated with land-use change within a spatial and temporal context through the use of a hydrological model in a cross-border setting. The KINEROS2 model is implemented via the Automated Geospatial Watershed Assessment 2.0 geographic information system interface to evaluate the watershed of Nogales, Arizona, and Nogales, Sonora, Mexico, to assess flood vulnerability by quantifying volumes of runoff and peak flow, based on alternative land-use scenarios. Cross-border geospatial data acquisition and input to models are described. Discussions about the KINEROS2 model results identify flood-prone areas, simulate the impact of land-use change, and evaluate the impact of potential flood-control interventions in the Ambos Nogales watershed. Products from this research are being used in a comprehensive plan for sustainable development in Ambos Nogales. [ABSTRACT FROM AUTHOR]

The development of new approaches for understanding processes of urban development and their environmental effects, as well as strategies for sustainable management, is essential in expanding metropolitan areas. This study illustrates the potential of linking urban growth and watershed models to identify problem areas and support long-term watershed planning. Sediment is a primary source of nonpoint-source pollution in surface waters. In urban areas, sediment is intermingled with other surface debris in transport. In an effort to forecast the effects of development on surface-water quality, changes predicted in urban areas by the SLEUTH urban growth model were applied in the context of erosion-sedimentation models (Universal Soil Loss Equation and Spatially Explicit Delivery Models). The models are used to simulate the effect of excluding hot-spot areas of erosion and sedimentation from future urban growth and to predict the impacts of alternative erosion-control scenarios. Ambos Nogales, meaning "both Nogaleses," is a name commonly used for the twin border cities of Nogales, Arizona and Nogales, Sonora, Mexico. The Ambos Nogales watershed has experienced a decrease in water quality as a result of urban development in the twin-city area. Population growth rates in Ambos Nogales are high and the resources set in place to accommodate the rapid population influx will soon become overburdened. Because of its remote location and binational governance, monitoring and planning across the border is compromised. One scenario described in this research portrays an improvement in water quality through the identification of high-risk areas using models that simulate their protection from development and replanting with native grasses, while permitting the predicted and inevitable growth elsewhere. This is meant to add to the body of knowledge about forecasting the impact potential of urbanization on sediment delivery to streams for sustainable development, which can be accomplished in a virtual environment. [ABSTRACT FROM AUTHOR]

• A SATVI time series showed interannual vegetation abundance for a semiarid grassland. • Runoff simulations were improved with the inclusion of SATVI-based vegetative data. • Satellite-based vegetation values provide a means for improved model parameterization. The use of hydrologic models to assess long-term watershed condition through repeated simulations of runoff and erosion is one common approach for rangeland health evaluation. However, obtaining vegetative data of appropriate spatiotemporal resolution for model parameterization can be difficult. The goal of this research was to assess the utility of using time-varying, Landsat-derived vegetative values to parameterize an event-based, watershed-scale hydrologic model. This study was conducted on a small, instrumented grassland watershed in the USDA Agricultural Research Service operated Walnut Gulch Experimental Watershed in southeastern, Arizona. Cloud-free Landsat scenes were acquired over the watershed for the years 1996–2014. The Soil Adjusted Total Vegetation Index (SATVI) was calculated for each image and calibrated using ground measured data to produce a time series of satellite-based foliar cover rasters. These values were used to parameterize the Rangeland Hydrology and Erosion Model (RHEM) for 26 rainfall-runoff events with corresponding observed data. Three parameterization scenarios using these data aggregated to different temporal resolutions (static, long-term mean, annual mean, and intra-annual values) were compared to a static literature-based scenario for evaluation. The linear relationship between field-measured foliar cover and SATVI showed statistically significant agreement with R2 = 0.85 and p < 0.05. Simulated runoff volume and peak flow rate using the three remotely sensed parameterization scenarios improved upon that of the literature-based scenario, with the annual mean scenario performing the best of the three temporal aggregations. The methodological framework outlined here provides a means for improved parameterization for watershed-scale modelling where vegetative data may be scarce or unobtainable for long-term analysis. [ABSTRACT FROM AUTHOR]

The Automated Geospatial Watershed Assessment Tool (AGWA) and the Rangeland Hydrology Erosion Model (RHEM) were used to evaluate conservation practices on the Cienega Creek watershed (CCW) that were implemented under the Conservation Effects Assessment Project (CEAP) on Grazing Lands. CEAP on Grazing Lands is a multi-agency effort to quantify the environmental effects of conservation practices and programs, and develop the science base for managing rangelands for environmental quality using conservation practices (Spaeth et al. 2013). The evaluation was performed on the CCW and the Empire Ranch, located in southeastern Arizona, where numerous conservation practices have been implemented to achieve their management goals of maintaining desired plant communities and watershed processes. To assess the effects of the conservation practices on long-term soil and water loss, RHEM was applied to the entire CCW using National Resources Inventory (NRI) data. Four analysis periods were selected based on climatic contrasts, conservation spending, and availability of NRI sample points. The CCW results showed that the simulations using RHEM parameters derived from NRI data could be used to demonstrate the impact of climate on vegetation condition and sediment yield. A subsection, dubbed "select treatment areas," of the CCW, which received extensive treatments with brush removal, prescribed burns, and stock ponds, was assessed using remotely sensed data. The select treatment areas were modeled over three different periods, representing preconservation spending, postconservation spending, and later postconservation spending. Remote sensing was capable of detecting and estimating the changes in vegetation cover from brush removal and prescribed burns. Simulations of sediment yield using pre- and posttreatment data indicated a modest reduction in sediment yield. Simulations in the select treatment areas indicated mechanical brush treatments were typically more effective than prescribed burns for improving watershed condition as estimated by reductions in sediment yield, but were more costly to implement. Stock ponds had a larger impact on sediment yield than the land treatments. The assessment demonstrated the utility of remotely sensed estimates of plant growth form and cover for model inputs to estimate changes in runoff and sediment yield with changing cover conditions over large areas. [ABSTRACT FROM AUTHOR]

• Time-variant variogram analysis reveals significant event scale parameter importance variability. • The type of modeling objectives used influences parameter importance. • Input rainfall intensity and hyetograph shape affects parameters importance. • VARS is an effective and robust approach for identifying key modeling parameters. Runoff and sediment yield predictions using rainfall-runoff modeling systems play a significant role in developing sustainable rangeland and water resource management strategies. To characterize the behavior and predictive uncertainty of the KINEROS2 physically-based distributed hydrologic model, we assessed model parameters importance at the event-scale for small nested semi-arid subwatersheds in southeastern Arizona using the Variogram Analysis of Response Surfaces (VARS) methodology. A two-pronged approach using time-aggregate and time-variant parameter importance analysis was adopted to improve understanding of the control and behavior of models. The time-aggregate analysis looks at several signature responses, including runoff volume, sediment yield, peak runoff, runoff duration, time to peak, lag time, and recession duration, to investigate the influence of parameter and input on the model predictions. The time-variant analysis looks at the dynamical influence of parameters on the simulation of flow and sediment rates at every simulation time step using the different forcing inputs. This investigation was able to address Simpson's paradox-type issues where the analysis across the different objective functions and full data set vs. its subsets (i.e., different events and/or time steps) could yield inconsistent and potentially misleading results. The results indicated the uncertainties in the flow responses are primarily due to the saturated hydraulic conductivity, the Manning's coefficient, the soil capillary coefficient, and the cohesion in sediment and flow-related responses. The level of influence of K2 parameters depends on the type of the model response surface, the rainfall, and the watershed size. [ABSTRACT FROM AUTHOR]