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The Walnut Gulch Experimental Watershed is a semi-arid experimental watershed and long-term agro-ecosystem research (LTAR) site managed by the USDA-Agricultural Research Services (ARS) Sout...

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.

The KINematic runoff and EROSion model (version 2; KINEROS2) provides an urban component that is capable of modeling urban hydrology including green infrastructure (GI) practices at various scales. The KINEROS2 model provides 15 parameters that can represent a variety of GI practices. The goal of this study is to understand the sensitivity of the KINEROS2 model outputs (infiltration, peak flow, runoff volume, and outflow hydrograph) to these 15 parameters, across seven different precipitation events, and at the watershed as well as the parcel scale. A global sensitivity analysis (GSA) was performed using the Variogram Analysis of Response Surfaces (VARS) framework to produce sensitivity metrics. Results from the time-aggregate GSA indicate that parameter sensitivities follow trends based on precipitation intensity and duration. Time-varying GSA indicate sensitivity of parameters to hyetograph shape, especially the duration to maximum precipitation intensity. The variation in sensitivity is influenced by the peaks and valleys in the precipitation hyetograph.

The performances of hydrological models in arid areas are significantly lower than other climates. The reasons are numerous, from the scales involved, to specific processes and the lack of adequate measurements. Effective parameters have been often observed to change between runoff events, limiting the predictive capacity of the models. We look at the problems that can be found in an operational setting and present an analysis to improve the understanding of the errors. Our method characterizes the conditions where the model fails systematically, and the conditions where the parameterization holds between floods. We applied KINEROS2 to 24 years of radar rainfall and streamflow data in 6 arid catchments. A GLUE probabilistic framework is used to characterize model performance, and a method is developed to identify floods with similar calibration. The analysis shows that uninformative conditions are difficult to generalize. A basin-specific analysis can help to identify conditions where the model fails and exclude them from calibration. Despite the large uncertainties, similar catchments display groups of floods with similar parameterization. In some basin we find that it is important to quantify antecedent moisture conditions. Hydrological models show some consistency within limited conditions. These conditions, however, depend on the errors involved, and are site-specific. There is some potential for parameter transfer, but proximity alone might not be enough, and other factors such as mean annual rainfall or storm type, should be taken into account.

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.

Temporal changes in rainfall erosivity can be expected to occur with changing climate, and because rainfall amounts are known to be in part of a function of elevation, erosivity can be expected to be influenced by elevation as well. This is particularly true in mountainous regions such as are found over much of the western United States. The objective of this study was to identify temporal and elevation trends in rainfall erosivity on a 149 km2 (58 miles2) watershed in a semi-arid region of southeastern Arizona. Data from 84 rain gages for the years 1960–2012 at elevations ranging from 1231 to 1644 m (4038–5394 ft) were used in the analyses. The average annual erosivity over the watershed as a whole was 1104 MJ mm ha−1 h−1 yr−1 (65 hundreds of foot ton inch acre−1 h−1 yr−1), and ranged from approximately 950 to 1225 MJ mm ha−1 h−1 yr−1 (56–72 hundreds of foot ton inch acre−1 h−1 yr−1), with a statistical trend showing greater erosivity at the higher elevations. No statistically significant temporal changes in annual or summer erosivities were found. This result stands in contrast to recent modeling studies of runoff and erosion in the area based on downscaled GCM information that project significant levels of erosivity changes over coming decades. These results are consistent with known orographic rainfall effects, but contrast with recent studies that presented projections of significant trends of increasing erosivity in the future based on downscaled GCM outputs for the area. The results illustrate the need for testing and developing improved techniques to evaluate future erosion scenarios for purposes of making targeted soil conservation decisions. Keywords: Climate change, R-factor, RUSLE, Semiarid, Soil erosion, Walnut Gulch

Summary Infiltration is important to modeling the overland transport of microorganisms in environmental waters. In watershed- and hillslope scale-models, infiltration is commonly described by simple equations relating infiltration rate to soil saturated conductivity and by empirical parameters defining changes in infiltration rate with soil water content. For the microbial transport model KINEROS2/STWIR used in this study, infiltration in unsaturated soil is accounted for by a net capillary drive parameter, G , in the Parlange equation. Scarce experimental data and multiple approaches for estimating parameter G introduce uncertainty, reducing reliability of overland water flow and microbial transport models. Our objectives were to evaluate reliability and robustness of three methods to estimate parameter G and associated accuracy and uncertainty in predicting runoff and fecal coliform (FC) transport. These methods include (i) KINEROS2 fitting to the experimental cumulative runoff data; (ii) estimating solely on soil texture; and (iii) estimating by individual pedotransfer functions (PTFs) and an ensemble of PTFs from basic soil properties. Results show that the most accurate prediction was obtained when the G parameter was fitted to the cumulative runoff. The KINEROS2-recommended parameter slightly overestimated the calibrated value of parameter G and yielded less accurate predictions of runoff, FC concentrations and total FC. The PTFs-estimated parameters systematically deviated from calibrated G values that caused high uncertainty in the KINEROS2/STWIR predictions. Averaging PTF estimates considerably improved model accuracy, reducing the uncertainty of runoff and FC concentration predictions. Overall, ensemble-based PTF estimation of the capillary drive can be efficient for simulations of runoff and bacteria overland transport when a single effective value is used across the study area.

Flash floods can cause extensive damage to both life and property, especially because they are difficult to predict. Flash flood prediction requires high-resolution meteorological observations and predictions, as well as calibrated hydrological models, which should effectively simulate how a catchment filters rainfall inputs into streamflow. Furthermore, because of the requirement of both hydrological and meteorological components in flash flood forecasting systems, there must be extensive data handling capabilities built in to force the hydrological model with a variety of available hydrometeorological data and predictions, as well as to test the model with hydrological observations. The authors have developed a working prototype of such a system, called KINEROS/hsB-SM, after the hydrological models that are used: the Kinematic Erosion and Runoff (KINEROS) and hillslope-storage Boussinesq Soil Moisture (hsB-SM) models. KINEROS is an event-based overland flow and channel routing model that is designed to simulate flash floods in semiarid regions where infiltration excess overland flow dominates, while hsB-SM is a continuous subsurface flow model, whose model physics are applicable in humid regions where saturation excess overland flow is most important. In addition, KINEROS/hsB-SM includes an energy balance snowmelt model, which gives it the ability to simulate flash floods that involve rain on snow. There are also extensive algorithms to incorporate high-resolution hydrometeorological data, including stage III radar data (5 min, 1° by 1 km), to assist in the calibration of the models, and to run the model in real time. The model is currently being used in an experimental fashion at the National Weather Service Binghamton, New York, Weather Forecast Office.

The Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona covers ~150 km2 and receives the majority of its annual precipitation from highly variable and intermittent summer storms during the North American monsoon. In this study, the patterns of precipitation in the U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) 88-rain-gauge network are analyzed for July through September from 1956 to 2011. Because small-scale convective systems generate most of this summer rainfall, the total (T), intensity (I), and frequency (F) exhibit high spatial and temporal variability. Although subsidiary periods may have apparent trends, no significant trends in T, I, and F were found for the study period as a whole. Observed trends in the spatial coverage of storms change sign in the late 1970s, and the multidecadal variation in I and spatial coverage of storms have statistically significant correlation with the Pacific decadal oscillation and the Atlantic multidecadal oscillation indices. Precipitation has a pronounced diurnal cycle with the highest T and F occurring between 1500 and 2200 LT, and its average fractional coverage over 2- and 12-h periods is less than 40% and 60% of the gauges, respectively. Although more gauges are needed to estimate area-averaged daily precipitation, 5–11 gauges can provide a reasonable estimate of the area-averaged monthly total precipitation during the period from July through September.

The increase in runoff from urbanization is well known; one extreme example comes from a 13-ha residential neighborhood in southeast Arizona where runoff was 26 times greater than in an adjacent grassland watershed over a 40-month period from 2005 to 2008. Rainfall-runoff modeling using the newly described KINEROS2 urban element, which simulates a contiguous row of houses and the adjoining street as a series of pervious and impervious overland flow planes, combined with tension infiltrometer measurements of saturated hydraulic conductivity (Ks), indicate that 17 � 14% of this increase in runoff is due to a 53% decrease in Ks in constructed pervious areas as compared to the undeveloped grassland. Ks in the urban watershed identified from calibrating the rainfall-runoff model to measured runoff is higher than measured Ks but much lower than indicated by a soil texture-based KINEROS2 parameter look-up table. Tests using different levels of discretization found that watershed geometry could be represented in a simplified manner, although more detailed discretization led to better model performance. DOI: 10.1061/(ASCE)HE.1943-5584.0000655. © 2013 American Society of Civil Engineers.

The rain gauge network associated with the Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona provides a unique opportunity for direct comparisons of in situ measurements and satellite-based instantaneous rain rate estimates like those from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR). The WGEW network is the densest rain gauge network in the PR coverage area for watersheds greater than 10 km2. It consists of 88 weighing rain gauges within a 149-km2 area. On average, approximately 10 gauges can be found in each PR field of view (~5-km diameter). All gauges are very well synchronized with 1-min reporting intervals. This allows generating very-high-temporal-resolution rain rate fields and obtaining accurate estimates of the area-average rain rate for the entire watershed and for a single PR field of view. In this study, instantaneous rain rate fields from the PR and the spatially interpolated gauge measurements (on a 100 m × 100 m grid, updated every 1 min) are compared for all TRMM overpasses in which the PR recorded rain within the WGEW boundaries (25 overpasses during 1999–2010). The results indicate very good agreement between the fields with low bias values (0.9). The correlation is high at overpass time but the peak occurs several minutes after the overpass, which can be explained by the fact that it takes several minutes for the raindrops to reach the gauge from the time they are observed by the PR. The correlation improves with the new version of the TRMM algorithm (V7). The study includes assessment of the accuracy of the reference products.

KINEROS (KINematic runoff and EROSion) originated in the 1960s as a distributed event-based model that conceptualizes a watershed as a cascade of overland flow model elements that flow into trapezoidal channel model elements. KINEROS was one of the first widely available watershed models that interactively coupled a finite difference approximation of the kinematic overland flow equations to a physically based infiltration model. Development and improvement of KINEROS continued from the 1960s on a variety of projects for a range of purposes, which has resulted in a suite of KINEROS-based modeling tools. This article focuses on KINEROS2 (K2), a spatially distributed, event-based watershed rainfall-runoff and erosion model, and the companion ArcGIS-based Automated Geospatial Watershed Assessment (AGWA) tool. AGWA automates the time-consuming tasks of watershed delineation into distributed model elements and initial parameterization of these elements using commonly available, national GIS data layers. A variety of approaches have been used to calibrate and validate K2 successfully across a relatively broad range of applications (e.g., urbanization, pre- and post-fire, hillslope erosion, erosion from roads, runoff and recharge, and manure transport). The case studies presented in this article (1) compare lumped to stepwise calibration and validation of runoff and sediment at plot, hillslope, and small watershed scales; and (2) demonstrate an uncalibrated application to address relative change in watershed response to wildfire.

Concerns for microbial safety of surface water facilitate development of predictive models that estimate concentrations and total numbers of pathogen and indicator organisms leaving manure-fertilized fields in overland flow during runoff events. Spatial variability of bacterial concentrations in applied manure introduces high uncertainty in the model predictions. The objective of this work was to evaluate the uncertainty in model predictions of the manure-borne bacteria overland transport caused by limited information on the spatial distribution of bacteria in surface-applied manure. Experiments were carried out at the ARS Beltsville experimental watershed site (OPE3) in Maryland. Dairy bovine manure was applied at a 59·3 t/ha rate on the 3·55 hectare experimental field. Faecal coliform (FC) concentrations in manure measured in 2004, 2005, 2007, and 2009 varied by 4 orders of magnitude each year. Both runoff volume and FC concentrations in runoff water were monitored using a runoff flume equipped with a refrigerated pump sampler. Two runoff events occurred before the manure was incorporated into the soil. A bacteria transport add-on module simulator of transport with infiltration and runoff (STWIR) was linked with the event-based kinematic runoff and erosion model (KINEROS2) to simulate convective-dispersive overland transport, bacteria release from manure, reversible attachment–detachment to soil, and surface straining of infiltrating bacteria. The model was successfully calibrated with the field experiment data. Monte Carlo simulations were carried out to account for the spatial variation in FC in applied manure and uncertainty in the FC distribution in manure caused by the small number of samples. A tenfold and twofold variation in FC concentrations in the runoff were obtained within the 90% probability interval when initial FC spatial distributions in the manure were represented by 5 and 29 samples, respectively. Copyright © 2011 John Wiley & Sons, Ltd.

Summary The difficulty of predicting rainfall–runoff responses in arid and semi-arid catchments using typically available data sets is well known, hence the need to carefully evaluate the suitability of alternative modelling approaches for a given problem and data set; and to identify causes of uncertainty in order to prioritise research and data. In this paper, we evaluate the distributed model, Kineros2, in application to an arid catchment in Oman, using rainfall–runoff data from 27 storm events. The analysis looks at model sensitivities, uncertainty and performance, based on uniform random sampling of the model parameter space and predictions of features of the observed hydrograph at the catchment outlet. A series of three experiments used different calibration strategies (an 11-parameter calibration, a 5-parameter calibration, and a 3-parameter calibration allowing some spatial variability of the saturated hydraulic conductivity). The parameters most significantly affecting flow peak and volume performance are those controlling infiltration rates on hillslopes. The model output was also generally sensitive to a parameter within the rainfall interpolation model. Relatively little sensitivity to initial catchment wetness was observed. Prediction performance was generally poor, for all events and for all the tested calibration and prediction strategies; and the uncertainty, estimated using model ensembles, was very high. A 2-parameter regression model used in previous work was found to perform better for predicting flow peaks. Literature review shows our results are consistent with experience of other modellers of arid and semi-arid climate hydrology. In order to realise the potential value of distributed, physically based models, for application to arid and semi-arid regions, significant data collection and further research is required, in particular regarding spatial rainfall observation and modelling.

Hydrologists are concerned with high-intensity rainfall and peak runoff rates for stormwater infrastructure designs, post-event assessments, and mitigation of environmental impacts. In the southwestern United States the need for accurate information about these rates is increasingly important as population growth and associated development are projected to exceed national averages. Design storm totals for various durations and return period frequencies are routinely derived from the National Oceanic and Atmospheric Administration (NOAA) Atlas 14 and are commonly used as input to hydrologic models to estimate peak runoff rates and runoff volumes. For the southwestern United States during the North American Monsoon, NOAA relies on sparse rain gauge networks to measure rainfall from limited area convective storms primarily at daily time steps and estimates of subdaily event intensities are derived by temporal downscaling from a few point locations. The USDA, Agricultural Research Service, Southwest W...

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.

Extended Abstract. Hydrologists are concerned with high intensity rainfall and peak runoff rates for stormwater infrastructure designs, post-event assessments and mitigation of environmental impacts. In the Southwestern US the need for accurate information about these rates is increasingly important as population growth and associated development is projected to exceed national averages. Design storm totals for various durations and return period frequencies are routinely derived from NOAA Atlas 14 and are commonly used as input to hydrologic models to estimate peak runoff rates and runoff volumes. For the Southwestern US during the North American Monsoon, NOAA relies on sparse rain gauge networks to measure rainfall from limited area convective storms primarily at daily time steps and estimates of sub-daily event intensities are derived by temporal down-scaling from a few point locations. The US Department of Agriculture, Agricultural Research Service, Southwest Watershed Research Center (SWRC) operates the Walnut Gulch Experimental Watershed (WGEW) in the vicinity of Tombstone, Arizona. SWRC maintains a database of 60 years of sub-daily, high temporal-precision rainfall intensities and runoff rates for WGEW (Goodrich et al., 2008). Updated, temporally-extended, rainfall intensity-duration-frequency relations for WGEW are presented. The current analysis includes intensity-duration-frequency relations for July, August and September for 53 years, 1961-2013, for 2-, 5-, 10-, 15-, 30- and 60-minute durations and 2-, 5-, 10-, 25-, 50-, 100- and 1000-year return periods. The 149 km 2 WGEW is large enough to select groups of four rain gauges whose event totals are independent. This allows combining of the four independent gauges’ 53-year time series into a longer time series of 212 years. A comparison of WGEW-generated intensity-duration-frequency curves to those of NOAA Atlas 14 indicated good agreement. However, across the range of durations, many observed events on WGEW from gauges not used in the frequency analysis are much greater than the estimated 100-year event.

In many semi-arid basins during extended periods when surface snowmelt or storm runoff is absent, groundwater constitutes the primary water source for human habitation, agriculture and riparian ecosystems. Utilizing regional groundwater models in the management of these water resources requires accurate estimates of basin boundary conditions. A critical groundwater boundary condition that is closely coupled to atmospheric processes and is typically known with little certainty is seasonal riparian evapotranspiration (ET). This quantity can often be a significant factor in the basin water balance in semi-arid regions yet is very difficult to estimate over a large area. Better understanding and quantification of seasonal, large-area riparian ET is a primary objective of the Semi-Arid Land-Surface-Atmosphere (SALSA) Program. To address this objective, a series of interdisciplinary experimental campaigns were conducted in 1997 in the San Pedro Basin in southeastern Arizona. The riparian system in this basin is primarily made up of three vegetation communities: mesquite (Prosopis velutina), sacaton grasses (Sporobolus wrightii), and a cottonwood (Populus fremontii)/willow (Salix goodingii) forest gallery. Micrometeorological measurement techniques were used to estimate ET from the mesquite and grasses. These techniques could not be utilized to estimate fluxes from the cottonwood/willow (C/W) forest gallery due to the height (20‐30 m) and non-uniform linear nature of the forest gallery. Short-term (2‐4 days) sap flux measurements were made to estimate canopy transpiration over several periods of the riparian growing season. Simultaneous remote sensing measurements were used to spatially extrapolate tree and stand measurements. Scaled C/W stand level sap flux estimates were utilized to calibrate a Penman‐Monteith model to enable temporal extrapolation between synoptic measurement periods. With this model and set of measurements, seasonal riparian vegetation water use estimates for the riparian corridor were obtained. To validate these models, a 90-day pre-monsoon water balance over a 10 km section of the river was carried out. All components of the water balance, including riparian ET, were

A comprehensive experimental plan has been designed to further investigate the potential and the limitations associated with the use of a large aperture scintillometer (LAS) to infer path average sensible and momentum fluxes over complex surfaces as part of the Semi-Arid Land-Surface-Atmosphere (SALSA) Program. The complexity of the terrain is associated with the type and the cover of the vegetation canopy as well as with changes in topography. Scintillometer based estimates of sensible heat flux and friction velocity are compared to those measured by eddy correlation systems over a grassland patch, a mesquite patch, and over a transect spanning both patches. The results show that considering the complexity of the surface, the overall performance of the scintillometer is relatively good.

Data from the Catsop catchment in South Limburg, Netherlands was simulated with the model KINEROS2. The results of calibration and validation on a split set of runoff and sediment data are reported and the variations in apparent parameters are analyzed. Calibration was performed with regard to the temporal distribution of runoff and sediment rather than single values such as total or peak rates. Based on the simulations, soil erodibility was considerably higher in 1993 than earlier years. Sediment discharge is quite sensitive to hydrologic simulation, as the amount and velocity of runoff affects sediment transport capacity which in turn determines the delivery of soil disturbed by rainsplash. Overall ability of the model to reproduce the measured data was considered relatively good.

Heavy rainfall on 27–31 July 2006 led to record flooding and triggered an historically unprecedented number of debris flows in the Santa Catalina Mountains north of Tucson, Ariz. The U.S. Geological Survey (USGS) documented record floods along four watercourses in the Tucson basin, and at least 250 hillslope failures spawned damaging debris flows in an area where less than 10 small debris flows had been documented in the past 25 years. At least 18 debris flows destroyed infrastructure in the heavily used Sabino Canyon Recreation Area (http://wwwpaztcn.wr.usgs.gov/rsch_highlight/articles/20061 l.html). In four adjacent canyons, debris flows reached the heads of alluvial fans at the boundary of the Tucson metropolitan area. While landuse planners in southeastern Arizona evaluate the potential threat of this previously little recognized hazard to residents along the mountain front, an interdisciplinary group of scientists has collaborated to better understand this extreme event.

A variety of aircraft remotely sensed and conventional ground-based measurements of volumetric soil water content (SW) were made over two subwatersheds (4.4 and 631 ha) of the U.S. Department of Agriculture's Agricultural Research Service Walnut Gulch experimental watershed during the 1990 monsoon season. Spatially distributed soil water contents estimated remotely from the NASA push broom microwave radiometer (PBMR), an Institute of Radioengineering and Electronics (IRE) multifrequency radiometer, and three ground-based point methods were used to define prestorm initial SW for a distributed rainfall-runoff model (KINEROS; Woolhiser et al., 1990) at a small catchment scale (4.4 ha). At a medium catchment scale (631 ha or 6.31 km2) spatially distributed PBMR SW data were aggregated via stream order reduction. The impacts of the various spatial averages of SW on runoff simulations are discussed and are compared to runoff simulations using SW estimates derived from a simple daily water balance model. It was found that at the small catchment scale the SW data obtained from any of the measurement methods could be used to obtain reasonable runoff predictions. At the medium catchment scale, a basin-wide remotely sensed average of initial water content was sufficient for runoff simulations. This has important implications for the possible use of satellite-based microwave soil moisture data to define prestorm SW because the low spatial resolutions of such sensors may not seriously impact runoff simulations under the conditions examined. However, at both the small and medium basin scale, adequate resources must be devoted to proper definition of the input rainfall to achieve reasonable runoff simulations.

Semiarid flash floods pose a significant danger for life and property in many dry regions around the world. One effective way to mitigate flood risk lies in implementing a real-time forecast and warning system based on a rainfall-runoff model. This study used a semiarid, physics-based, and spatially distributed watershed model driven by high-resolution radar rainfall input to evaluate such a system. The predictive utility of the model and dominant sources of uncertainty were investigated for several runoff events within the U.S. Department of Agriculture Agricultural Research Service Walnut Gulch Experimental Watershed located in the southwestern United States. Sources of uncertainty considered were rainfall estimates, watershed model parameters, and initial soil moisture conditions. Results derived through a variance-based comprehensive global sensitivity analysis indicated that the high predictive uncertainty in the modeled response was heavily dominated by biases in the radar rainfall depth estimates. Key model parameters and initial model states were identified, and we generally found that modeled hillslope characteristics are more influential than channel characteristics in small semiarid basins. We also observed an inconsistency in the parameter sets identified as behavioral for different events, which suggests that model calibration to historical data is unlikely to consistently improve predictive performance for different events and that real-time parameter updating may be preferable.

[1] This special section of Water Resources Research and the associated Web site (http://www.tucson.ars.ag.gov/dap/) describe 50 years of data collection and the most recent research results at the U.S. Department of Agriculture (USDA) Agricultural Research Service (ARS) Walnut Gulch Experimental Watershed (WGEW) in southeast Arizona. The goal of this compilation is to encourage cooperative, interdisciplinary studies of semiarid ecohydrology at WGEW based on continuing long-term measurements of soils, vegetation, hydrology, and climate.

[1] An extensive precipitation database at the ∼149 km2 Walnut Gulch Experimental Watershed (WGEW) has been developed over the past 53 years with the first records starting in August 1953 and continuing to the present. The WGEW is a tributary of the San Pedro River, is located in southeastern Arizona, and surrounds the town of Tombstone. Average annual precipitation for the period of 1956–2005, as measured with six gauges, is roughly 312 mm, with approximately 60% falling during the summer monsoon. From a historical high of 95 rain gauges, a current network of 88 gauges is operational. This constitutes one of the densest rain gauge networks in the world (∼0.6 gauges/km2) for watersheds greater than 10 km2. Through 1999, the network consisted of analog recording weighing rain gauges. In 2000, a newly designed digital gauge with telemetry was placed adjacent (∼1 m) to the analog gauges. Both the analog and digital networks of gauges were in operation from 2000 to 2005 to enable a comparative analysis of the two systems. The analog data were digitized from paper charts and were stored in breakpoint format. The digital data consist of rainfall depths at 1-min intervals during periods of rainfall. All these data can be obtained in a variety of formats and were accumulated over various time intervals (daily, monthly, and annual) via a web interface at http://www.tucson.ars.ag.gov/dap/.

[1] A multiyear comparison of two types of automated-recording, weighing bucket rain gauges was conducted using precipitation data collected at the United States Department of Agriculture, Agricultural Research Service's Walnut Gulch Experimental Watershed in southeastern Arizona. The comparison was part of the conversion of all rain gauges on the watershed from an analog-recording, mechanical-weighing rain gauge to a data logger controlled, digital-recording, electronic-weighing rain gauge with radiotelemetry. This comparison applied to nine pairs of analog and digital rain gauges that were in coincident operation during a 5-year period, 1 January 2000 to 31 December 2004. This study found that (1) high errors in event intensities may be produced when analog charts are digitized at short time intervals; (2) dual digital rain gauges recorded precipitation equivalently; (3) for several different measures of precipitation, the analog and digital data were equivalent; and (4) implications for the rainfall-runoff model, Kinematic and Erosion Runoff model (KINEROS), showed a limited but significant effect in modeled runoff due to differences between analog and digital rain gauge input precipitation intensities. This study provided a useful analysis for long-term rain gauge networks that have recently converted, or will soon convert, from analog to digital technology. Understanding these differences and similarities will benefit interpretation of the combined long-term precipitation record and provide insights into the impacts on hydrologic modeling.

Representation of precipitation is one of the most difficult aspects of modelling post-fire runoff and erosion and also one of the most sensitive input parameters to rainfall-runoff models. The impact of post-fire convective rainstorms, especially in semiarid watersheds, depends on the overlap between locations of high-intensity rainfall and areas of high-severity burns. One of the most useful applications of models in post-fire situations is risk assessment to quantify peak flow and identify areas at high risk of flooding and erosion. This study used the KINEROS2/AGWA model to compare several spatial and temporal rainfall representations of post-fire rainfall-runoff events to determine the effect of differing representations on modelled peak flow and determine at-risk locations within a watershed. Post-fire rainfall-runoff events at Zion National Park in Utah and Bandelier National Monument in New Mexico were modelled. Representations considered included both uniform and Soil Conservation Service Type II hyetographs, applying rain over the entire watershed and applying rain only on the burned area, and varying rainfall both temporally and spatially according to radar data. Results showed that rainfall representation greatly affected modelled peak flow, but did not significantly alter the model’s predictions for high-risk locations. This has important implications for post-fire assessments before a flood-inducing rainfall event, or for post-storm assessments in areas with low-gauge density or lack of radar data due to mountain beam blockage.

International audience; The Semi-Arid Land-Surface-Atmosphere Program (SALSA) is a multi-agency, multi-national research effort that seeks to evaluate the consequences of natural and human-induced environmental change in semi-arid regions. The ultimate goal of SALSA is to advance scientific understanding of the semi-arid portion of the hydrosphere-biosphere interface in order to provide reliable information for environmental decision making. SALSA approaches this goal through a program of long-term, integrated observations, process research, modeling, assessment, and information management that is sustained by cooperation among scientists and information users. In this preface to the SALSA special issue, general program background information and the critical nature of semi-arid regions is presented. A brief description of the Upper San Pedro River Basin, the initial location for focused SALSA research follows. Several overarching research objectives under which much of the interdisciplinary research contained in the special issue was undertaken are discussed. Principal methods, primary research sites and data collection used by numerous investigators during 1997-1999 are then presented. Scientists from about 20 US, five European (four French and one Dutch), and three Mexican agencies and institutions have collaborated closely to make the research leading to this special issue a reality. The SALSA Program has served as a model of interagency cooperation by breaking new ground in the approach to large scale interdisciplinary science with relatively limited resources.