46 research outputs found

    Simulating the Productivity of Desert Woody Shrubs in Southwestern Texas

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    In the southwestern U.S., many rangelands have converted from native grasslands to woody shrublands dominated by creosotebush (Larrea tridentate) and honey mesquite (Prosopis glandulosa), threatening ecosystem health. Both creosotebush and mesquite have well-developed long root systems that allow them to outcompete neighboring plants. Thus, control of these two invasive shrubs is essential for revegetation in arid rangelands. Simulation models are valuable tools for describing invasive shrub growth and interaction between shrubs and other perennial grasses and for evaluating quantitative changes in ecosystem properties linked to shrub invasion and shrub control. In this study, a hybrid and multiscale modeling approach with two process-based models, ALMANAC and APEX was developed. Through ALMANAC application, plant parameters and growth cycles of creosotebush and mesquite were characterized based on field data. The developed shrub growth curves and parameters were subsequently used in APEX to explore productivity and range condition at a larger field scale. APEX was used to quantitatively evaluate the effect of shrub reductions on vegetation and water and soil qualities in various topological conditions. The results of this study showed that this multi modeling approach is capable of accurately predicting the impacts of shrubs on soil water resources

    Hydrologic simulation of a neotropical alpine catchment influenced by conductive topsoils in the Ecuadorian Andes

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    Highly conductive topsoils in neotropical high-elevation grassland-dominated ecosystems, or so-called paramos in the Andean region, influence the local rainfall-runoff processes predominated by saturation-excess overland flow as the primary source of freshwater. The Soil and Water Assessment Tool (SWAT) model has shown limitations when applied to mountainous catchments with highly conductive soils that generate surface runoff as saturation-excess overland flow. In this study, we enhanced SWAT to simulate runoff as saturation-excess overland flow and examined the hydrological responses of an intensively monitored paramo catchment in Ecuador. The model setup considered a detailed representation of the hydro-physical properties of the soils at different depths, including high infiltration and lateral flow rates in the hillslopes and restricted groundwater interactions, a characteristic of the páramo catchments. SWAT reasonably reproduced the daily discharge during dry and wet periods and the cumulative occurrence of high and low flows. The performance metrics NSE, RSR, and PBIAS values during calibration/validation period were 0.86/0.84, 0.31/0.4, and −11.2/-7.58, respectively. The runoff ratio and partitioning of the total runoff into the lateral flow and surface runoff were physically meaningful. More significantly, SWAT was able to simulate saturation-excess overland flow, which is dominant compared to infiltration excess, and it is a distinctive characteristic of páramo catchments. Nevertheless, the model showed limitations in simulating low flows

    Evaluating hydrologic responses to soil characteristics using SWAT model in a paired-watersheds in the Upper Blue Nile Basin

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    Watershed responses are affected by the watershed characteristics and rainfall events. The characteristics of soil layers are among the fundamental characteristics of a watershed and they are input to hydrologic modeling similar to topography and land use/cover. Although the roles of soils have been perceived, there are limited studies that quantify the role of soil characteristics on watershed runoff responses due to the lack of field datasets. Using two adjacent watersheds (Ribb and Gumara) which have a significant different runoff response with a similar characterstics except geological settings (including soil characteristics), we studied the effects of soil characteristics on runoff and water balance. The Soil and Water Assessment Tool (SWAT) was used to simulate the surface runoff response at the outlet of the watershed and the optimal model parameters distribution was tested with a non-parametric test for similarity. Results indicated that SWAT model captured the observed flow very well with a Nash-Sutcliffe Efficiency (NSE) of greater than 0.74 and with a PBIAS of less than 10% for both calibration and validation period. The comparison of the optimal model parameter distributions of the SWAT model showed that the watershed characteristics could be uniquely defined and represented by a hydrologic model due to the differences in the soils. Using field observations and modeling experiments, this study demonstrates how sensitive watershed hydrology is to soils, emphasizing the importance of accurate soil information in hydrological modeling. We conclude that due emphasis should be given to soil information in hydrologic analysis

    Assessment of Optional Sediment Transport Functions via the Complex Watershed Simulation Model SWAT

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    The Soil and Water Assessment Tool 2012 (SWAT2012) offers four sediment routing methods as optional alternatives to the default simplified Bagnold method. Previous studies compared only one of these alternative sediment routing methods with the default method. The proposed study evaluated the impacts of all four alternative sediment transport methods on sediment predictions: the modified Bagnold equation, the Kodoatie equation, the Molinas and Wu equation, and the Yang equation. The Arroyo Colorado Watershed, Texas, USA, was first calibrated for daily flow. The sediment parameters were then calibrated to monthly sediment loads, using each of the four sediment routing equations. An automatic calibration tool—Integrated Parameter Estimation and Uncertainty Analysis Tool (IPEAT)—was used to fit model parameters. The four sediment routing equations yielded substantially different sediment sources and sinks. The Yang equation performed best, followed by Kodoatie, Bagnold, and Molinas and Wu equations, according to greater model goodness-of-fit (represented by higher Nash–Sutcliffe Efficiency coefficient and percent bias closer to 0) as well as lower model uncertainty (represented by inclusion of observed data within 95% confidence interval). Since the default method (Bagnold) does not guarantee the best results, modelers should carefully evaluate the selection of alternative methods before conducting relevant studies or engineering projects

    Model Application for Sustainable Agricultural Water Use

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    With the growing population and climate change, increasing demands for water are intensifying competition between agricultural stakeholders. Since the mid-20th century, numerous crop models and modeling techniques have emerged for the quantitative assessment of cropping systems. This article introduces a collection of articles that explore current research in model applications for sustainable agricultural water use. The collection includes articles from model development to regional and field-scale applications addressing management effects, model uncertainty, irrigation decision support systems, and new methods for simulating salt balances. Further work is needed to integrate data science, modern sensor systems, and remote sensing technologies with the models in order to investigate the sustainability of agricultural systems in regions affected by land-use change and climate change

    Estimation of Stream Health Using Flow-Based Indices

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    Existing methods to estimate stream health are often location-specific, and do not address all of the components of stream health. In addition, there are very few guidelines to estimate the health of a stream, although the literature and useful tools such as Indicators of Hydrologic Alteration (IHA) are available. This paper describes an approach developed for estimating stream health. The method involves the: (1) collection of flow data; (2) identification of hydrologic change; (3) estimation of some hydrologic indicators for pre-alteration and post-alteration periods; and (4) the use of those hydrologic indicators with the scoring framework of the Dundee Hydrologic Regime Assessment Method (DHRAM). The approach estimates the stream health in aggregate including all of the components, such as riparian vegetation, aquatic species, and benthic organisms. Using the approach, stream health can be estimated at two different levels: (1) the existence or absence of a stream health problem based on the concept of eco-deficit and eco-surplus using flow duration curves; and (2) the estimation of overall stream health using the IHA–DHRAM method. The procedure is demonstrated with a case example of the White Rock Creek watershed in Texas in the United States (US). The approach has great potential to estimate stream health and prescribe flow-based goals for the restoration of impaired streams
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