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The objective of this research is to explore the relationship between small catchment properties and the temporal growth and decay of saturated source areas (SSA). A simple physics-based hydrologic model, which we call the Sandbox model, is developed for this purpose. A thorough sensitivity analysis is undertaken to evaluate model response to variations in model parameters. Sandbox model output is compared to that from the semi-distributed conceptual model, TOPMODEL, a model with a wide spread acceptance. Plotting the temporal evolution of the extent of saturated source area versus catchment average soil water content during a number of wetting and drying cycles shows a wide variety of trajectories or hysteretic loops. A parametric analysis was performed to quantify the impact of hypothetical catchment properties on the relationship between saturated area extent and basin-average soil water content, revealing hysteretic behavior. It is shown that this hysteresis is the result of changes in groundwater table slope, which is usually less than, and seldom equal to, the land-surface slope in non-saturated areas.

The need to simulate surface water flows in watersheds with diverse runoff production mechanisms has prompted the Department of Defense to invest in the development of a new, physically based hydrologic model, called the Gridded Surface/Subsurface Hydrologic Analysis (GSSHA) model. GSSHA is a reformulation and enhancement of the two-dimensional, physically based model CASC2D. The GSSHA model simulates stream flow generated by both infiltration-excess and saturation-excess mechanisms, as well as exfiltration, and groundwater discharge to streams. The model employs mass-conserving solutions of partial differential equations and closely links the hydrologic components to assure an overall mass balance. Testing of the model on a watershed with diverse runoff mechanisms indicates that the model is useful for investigating the important streamflow producing processes at the watershed scale and determining the contributions of surface water, saturated groundwater, and unsaturated groundwater to the overall water...

Analysis of data collected by four disdrometers deployed in a 1-km2 area is presented with the intent of quantifying the spatial variability of radar reflectivity at small spatial scales. Spatial variability of radar reflectivity within the radar beam is a key source of error in radar-rainfall estimation because of the assumption that drops are uniformly distributed within the radar-sensing volume. Common experience tells one that, in fact, drops are not uniformly distributed, and, although some work has been done to examine the small-scale spatial variability of rain rates, little experimental work has been done to explore the variability of radar reflectivity. The four disdrometers used for this study include a two-dimensional video disdrometer, an X-band radar-based disdrometer, an impact-type disdrometer, and an optical spectropluviometer. Although instrumental differences were expected, the magnitude of these differences clouds the natural variability of interest. An algorithm is applied to ...

A number of watershed-scale hydrological models include Richards' equation (RE) solutions, but the literature is sparse on information as to the appropriate application of RE at the watershed scale. In most published applications of RE in distributed watershed-scale hydrological modelling, coarse vertical resolutions are used to decrease the computational burden. Compared to point- or field-scale studies, application at the watershed scale is complicated by diverse runoff production mechanisms, groundwater effects on runoff production, runon phenomena and heterogeneous watershed characteristics. An essential element of the numerical solution of RE is that the solution converges as the spatial resolution increases. Spatial convergence studies can be used to identify the proper resolution that accurately describes the solution with maximum computational efficiency, when using physically realistic parameter values. In this study, spatial convergence studies are conducted using the two-dimensional, distributed-parameter, gridded surface subsurface hydrological analysis (GSSHA) model, which solves RE to simulate vadose zone fluxes. Tests to determine if the required discretization is strongly a function of dominant runoff production mechanism are conducted using data from two very different watersheds, the Hortonian Goodwin Creek Experimental Watershed and the non-Hortonian Muddy Brook watershed. Total infiltration, stream flow and evapotranspiration for the entire simulation period are used to compute comparison statistics. The influences of upper and lower boundary conditions on the solution accuracy are also explored. Results indicate that to simulate hydrological fluxes accurately at both watersheds small vertical cell sizes, of the order of 1 cm, are required near the soil surface, but not throughout the soil column. The appropriate choice of approximations for calculating the near soil-surface unsaturated hydraulic conductivity can yield modest increases in the required cell size. Results for both watersheds are quite similar, even though the soils and runoff production mechanisms differ greatly between the two catchments. Copyright © 2003 John Wiley & Sons, Ltd.

Runoff data were analyzed from the semihumid 21.2 km 2 Goodwin Creek Experimental Watershed ~GCEW! in northern Mississippi to examine watershed response over a range of scales. Runoff is monitored at the GCEW outlet and in 13 subcatchments, ranging in area from 0.06 to 17.6 km 2 . Previous data-based studies have shown that simple scaling theory fails to describe scaling of flood quantiles in large watersheds, and there is a fundamental change in scaling behavior in semihumid watersheds at an area of approximately 100 km 2 . It has been found that flood quantiles in nearly all subbasins in the GCEW are self-similar as described by simple scaling theory. It has also been found that expected values of peak flows during single runoff events are described by a power law function of catchment area. The primary reasons why flood quantiles are self-similar on Goodwin Creek are that precipitation is relatively uniform over the basin; peak discharges in smaller catchments are highly correlated with rainfall rates; nearly the entire watershed regularly contributes to runoff and; the groundwater table plays little role in runoff production.

Numerical tests indicate that Hortonian runoff mechanisms benefit from scaling effects that non-Hortonian runoff mechanisms do not share. This potentially makes Hortonian watersheds more amenable to physically based modelling provided that the physically based model employed properly accounts for rainfall distribution and initial soil moisture conditions, to which these types of model are highly sensitive. The distributed Hortonian runoff model CASC2D has been developed and tested for the US Army over the past decade. The purpose of the model is to provide the Army with superior predictions of runoff and stream-flow compared with the standard lumped parameter model HEC-1. The model is also to be used to help minimize negative effects on the landscape caused by US armed forces training activities. Development of the CASC2D model is complete and the model has been tested and applied at several locations. These applications indicate that the model can realistically reproduce hydrographs when properly applied. These applications also indicate that there may be many situations where the model is inadequate. Because of this, the Army is pursuing development of a new model, GSSHA, that will provide improved numerical stability and incorporate additional stream-flow-producing mechanisms and improved hydraulics. Copyright © 2002 John Wiley & Sons, Ltd.

This paper presents representative applications and models that can take advantage of spatially distributed data in a geographic information system (GIS) format for watershed analysis and hydrologic modeling purposes. The intention is to inform hydrologic engineers about the current capabilities of GIS, hydrologic analysis modules, and distributed hydrologic models, and to provide an initial guide on implementing GIS for hydrologic modeling. This paper also discusses key implementation issues for individuals and organizations that are considering making the transition to the use of GIS in hydrology. Widespread use of GIS modules and distributed watershed models is inevitable. The controlling factors are data availability, GIS-module development, fundamental research on the applicability of distributed hydrologic models, and finally, regulatory acceptance of the new tools and methodologies. GIS modules and distributed hydrologic models will enable the progression of hydrology from a field dominated by techniques that require spatial averaging and empiricism to a more spatially descriptive science.

The increasing proliferation of spatial data, geographic information systems (GIS), and models for hydrologic applications provide many new investigation opportunities but also present a number of challenges for the uninitiated water resources practitioner. This two-part paper is intended for the practicing engineer who wants to expand into the arena of spatial data and distributed watershed modeling. It provides an integrated overview of the multiple facets of data-GIS-modeling issues and a source of background information for selection and application of GIS in watershed modeling. This first paper addresses selected spatial data issues, data structures and projections, data sources, and information on data resolution and uncertainties. Spatial data that are covered include digital elevation data, stream and drainage data, soil data, digital orthophoto data, remotely sensed data, and radar precipitation data. The focus is on data and issues that are common to many data-GIS- modeling applications. The second paper presents issues on and examples of GIS and hydrologic models and provides recommendations with respect to organization and implementation of the integrated use of spatial data, GIS, and distributed watershed models.

Prediction of saturated area formation is important for hydrologic modeling of watersheds with shallow, highly pervious soils. This simulation study examines the relative importance of hillslope properties and rainfall rate on the evolution of saturated source areas during wetting. The study focuses on homogeneous, nonconvergent hillslope topography with constant slope. The two-dimensional, variably saturated groundwater model VS2D [Healy, 1990; Lappala et al. 1993] is used to simulate saturated area formation under the action of steady uniform rainfall. The study methodology systematically varies four hillslope properties, depth to impervious layer, slope length, slope angle, and average saturated hydraulic conductivity, and the rainfall rate. Results indicate that the fraction of the hillslope length that is saturated at equilibrium is a function of a parameter Φ, which is defined as the rainfall rate multiplied by the slope length, divided by the slope angle, soil thickness, and saturated hydraulic conductivity. The temporal evolution of saturated area is analyzed in terms of the equilibrium time. Nonlinearity in the unsaturated zone and differences in hillslope properties result in a nonunique time to equilibrium relation. The time to equilibrium is maximum when factors that tend to cause surface saturation are in approximate balance with those that tend to dissipate surface saturation. The temporal evolution of surface saturation during wetting follows a wide variety of trajectories. Equivalent hillslope soil water storage ratios on slopes with different properties can result in a wide range of surface saturation conditions. Hillslopes with shallower soils and smaller slope angles are most susceptible to saturated area formation. However, sudden changes in surface saturation are possible on steep hillslopes when 1 < Φ < 6.

Physically based, two-dimensional, distributed parameter Hortonian hydrologic models are sensitive to a number of spatially varied parameters and inputs and are particularly sensitive to the initial soil moisture field. However, soil moisture data are generally unavailable for most catchments. Given an erroneous initial soil moisture field, single-event calibrations are easily achieved using different combinations of model parameters, including physically unrealistic values. Verification of single-event calibrations is very difficult for models of this type because of parameter estimation errors that arise from initial soil moisture field uncertainty. The purpose of this study is to determine if the likelihood of obtaining a verifiable calibration increases when a continuous flow record, consisting of multiple runoff producing events is used for model calibration. The physically based, two-dimensional, distributed, Hortonian hydrologic model CASC2D [Julien et al., 1995] is converted to a continuous formulation that simulates the temporal evolution of soil moisture between rainfall events. Calibration is performed using 6 weeks of record from the 21.3 km 2 Goodwin Creek Experimental Watershed, located in northern Mississippi. Model parameters are assigned based on soil textures, land use/land cover maps, and a combination of both. The sensitivity of the new model formulation to parameter variation is evaluated. Calibration is performed using the shuffled complex evolution method [Duan et al., 1991]. Three different tests are conducted to evaluate model performance based on continuous calibration. Results show that calibration on a continuous basis significantly improves model performance for periods, or subcatchments, not used in calibration and the likelihood of obtaining realistic simulations of spatially varied catchment dynamics. The automated calibration reveals that the parameter assignment methodology used in this study results in overparameterization. Additional research is needed in spatially distributed hydrologic model parameter assignment methodologies for hydrologic forecasting.

Heavy rainfall, topography, storm motion, and storm evolution are closely linked for four storms that produced catastrophic flooding along the Front Range of the Rocky Mountains and the east slope of the Blue Ridge Mountains. Storms selected for detailed study in this paper are the Rapidan storm of June 27, 1995, the Fort Collins storm of July 28, 1997, the Buffalo Creek storm of July 12, 1996, and the Monocacy storm of June 18, 1996. The Buffalo Creek storm and the Fort Collins storm occurred in the Front Range of the Rocky Mountains in Colorado; the Rapidan and Monocacy storms occurred along the east slopes of the Blue Ridge of Virginia and southern Pennsylvania. The four storms caused catastrophic flooding at drainage basin scales between 1 and 1000 km 2 . The scale of flood response for these events imposes a need to characterize rainfall variability at very fine space scales and timescales, of the order of 1 km spatial scale and 1-5 min timescale. A fundamental issue for the hydrometeorology of extreme rainfall in mountainous terrain is whether anomalously large rainfall accumulations in orographic convection result from anomalously slow net storm motion, anomalously large rainfall rates, or both. Anomalous storm motion and processes resulting in catastrophic rainfall rates are examined for each of the four storms. Of particular importance for anomalous storm motion in orographic convection are interactions between the low-level wind field and terrain features.

Results from five physical hydraulic model studies of riverside water intakes situated along the Missouri River reach between Sioux City, Iowa, and St. Louis, Missouri, are presented. Movable-bed, undistorted Froude-scale models are used to determine the effectiveness of structural modifications in the vicinity of the intake to limit the influx of bed-load sediments. Solutions developed in each case include a series of submerged flow-turning vanes located on the riverward side of the intake. A sediment-barrier wall between the vanes and intake increases the streamwise velocity component, enhancing the effectiveness of flow-turning vanes in maintaining a deep scour trench. Effective solutions determined using physical hydraulic models are verified at the prototype scale, as demonstrated by years of trouble-free operation at locations where the recommended sediment-control measures have been installed. Results presented in this paper provide design guidelines for bed-load sediment control at riverside water-intake structures on sand-bed rivers.

Distributed, physically based watershed and irrigation advance models require robust infiltration estimation capabilities. The empirical Green and Ampt (GA) equation of infiltration is a popular method for estimating infiltration. The GA parameters have physical basis and considerable prior research has focused on relating these parameters to soil textural classification. However, the original GA method is limited in that it is applicable only for a single ponding period. An explicit Green and Ampt redistribution (GAR) technique is developed herein to estimate interstorm redistribution of soil water and allow multiple ponding simulations using the GA methodology. Soil water redistribution during interponding periods is estimated using the physical constructs of water retention curves without hysteresis. A GA wetting-front suction parameter scaling function is derived for use between arbitrary soil water contents. Simulations on 11 soil textural classifications comparing the GAR method with the numerical s...

Simonit and Perrings (1) endeavor to assess effects of land use decisions on hydrological behavior of the Panama Canal watershed. Although this is a worthy study topic, the authors used the US Department of Agriculture–Natural Resources Conservation Service Curve Number (CN) model to predict hydrologic response. Modeling of land-management effects on tropical hydrological behavior requires a model that can describe detailed spatial variability in watershed characteristics, properly simulate the effects of tropical land use on rainfall partitioning, and groundwater dynamics. The CN model does none of these (2).

Widespread, intense rainfall over the Upper Rio Chagres watershed (414 km2) in central Panama during December 2010 triggered numerous landslides that introduced large numbers of trees to the river network. We flew by helicopter along the mainstem Upper Chagres and the adjacent margins of Lake Alhajuela, into which the Upper Chagres flows, in February and June 2011. We used low-elevation video photography from these flights to tally the number of wood pieces stored along the lake margin and within the channel, and the number of landslides reaching the mainstem. We used these tallies with ground-verified estimates of average wood piece size and landslide surface area, and assumptions about wood density, carbon content, and aboveground biomass, to develop a first-order estimate of carbon export in the form of wood from the Upper Chagres following the 2010 storms. Based on the wood tally, we estimate 9 · 6 to 16 Mg C/km2 export, and from the landslide tally we estimate 24 Mg C/km2. We believe the landslide tally provides a more accurate minimum estimate of carbon export from the Upper Chagres during the December 2010 storms. These values are an order of magnitude higher than limited data for average or background rates of wood-based carbon export from other catchments, but two orders of magnitude lower than wood-based carbon export during extreme storms in Taiwan. The findings suggest that duration of flood flow above a threshold for mobilizing wood within the channel network exerts a more important control on wood export from the Upper Chagres than magnitude of flood peak. Copyright © 2013 John Wiley & Sons, Ltd.

The variability in Hortonian surface runoff discharge and volume produced by stationary rainstorms on watersheds with spatially distributed soil saturated hydraulic conductivity is examined using a two-dimensional runoff model and a Monte Carlo methodology. Results indicate that rainfall duration tr, rainfall intensity i, representative time to equilibrium tre, mean saturated hydraulic conductivityKm, and coefficient of variation Cυ play major roles in the variability of surface runoff. Similarity in surface runoff generated on heterogeneous soils is governed by the following dimensionless parameters: T* = tr/tre, K* = Km/i, and Cυ. The variability in both discharge and runoff volume for randomly distributed systems increases with K* and Cυ, compared to the runoff generated from uniformly distributed systems. Runoff variability decreases whenT* increases unless the mean value of hydraulic conductivity approaches the rainfall intensity (K* → 1). In highly pervious watersheds the steady state discharge depends on the spatial distribution of hydraulic conductivity. Lumped values of saturated hydraulic conductivity are found to typically underestimate the peak discharge and runoff volume.

The proliferation of watershed databases in raster Geographic Information System (GIS) format and the availability of radar-estimated rainfall data foster rapid developments in raster-based surface runoff simulations. The two-dimensional physically-based rainfall-runoff model CASC2D simulates spatially-varied surface runoff while fully utilizing raster GIS and radar-rainfall data. The model uses the Green and Ampt infiltration method, and the diffusive wave formulation for overland and channel flow routing enables overbank flow storage and routing. CASC2D offers unique color capabilities to display the spatio-temporal variability of rainfall, cumulative infiltrated depth, and surface water depth as thunderstorms unfold. The model has been calibrated and independently verified to provide accurate simulations of catchment response to moving rainstorms on watersheds with spatially-varied infiltration. The model can accurately simulate surface runoff from flashfloods caused by intense thunderstorms moving across partial areas of a watershed.

The influence of storm motion on runoff is explored, with a focus on dimensionless hydrologic similarity parameters. One- and two-dimensional physically based runoff models are subjected to moving rainstorms. A dimensionless storm speed parameterUte/Lp, where U is the storm speed, te is the runoff plane kinematic time to equilibrium, and Lp is the length of the runoff plane, is identified as a similarity condition. Storm motion effects on the peak discharge are greatest when the storm is traversing a one-dimensional runoff plane in the downslope direction at a dimensionless speed of Ute/Lp = 0.5. This conclusion holds for all values of the dimensionless storm sizes Ls/Lp where Ls is the length of the storm in the direction of motion. Simulations with a two-dimensional rainfall-runoff model confirm the applicability of this similarity parameter on natural watershed topography. Results indicate that the detailed simulation of storm motion is necessary when the storm is moving near the velocity of maximum effect, which is considerably slower than typical storm velocities.

This paper presents an estimation of the quantity of carbon fixed in trees in a one hectare (ha) plot at the Cerro Pelado-Gamboa Hydrology Tropical Observatory, which is located in the province of Colon, Panama. The estimation of carbon fixed in trees may provide significant information on carbon flux due to water circulation, which may ultimately enable evaluation of the carbon cycle. All trees larger than 10 cm diameter at breast height (DBH) in the plot were investigated. Carbon fixed within these trees was estimated using a parameterized formula. Tree biomass estimations for the plot were 97.21 Mg ha−1. We identified a rare arboreal pear species (Euphorbiaceous) with higher carbon density than other trees in the plot. The presence of this apparently unique species may be due to specific soil characteristics. The method was evaluated by comparing the results with a second study performed in 2011, which resulted in an estimate of net new carbon (biomass) increment (NNCI), which gives 3.88 Mg ha−1 year−1. In general, the estimation of the biomass and associated carbon content found in this investigation are useful comparative data for economic evaluation of tropical forests in terms of capacity to capture carbon. This paper presents an estimation of the quantity of carbon fixed in trees in a one hectare (ha) plot at the Cerro Pelado-Gamboa Hydrology Tropical Observatory, which is located in the province of Colon, Panama. The estimation of carbon fixed in trees may provide significant information on carbon flux due to water circulation, which may ultimately enable evaluation of the carbon cycle. All trees larger than 10 cm diameter at breast height (DBH) in the plot were investigated. Carbon fixed within these trees was estimated using a parameterized formula. Tree biomass estimations for the plot were 97.21 Mg ha−1. We identified a rare arboreal pear species (Euphorbiaceous) with higher carbon density than other trees in the plot. The presence of this apparently unique species may be due to specific soil characteristics. The method was evaluated by comparing the results with a second study performed in 2011, which resulted in an estimate of net new carbon (biomass) increment (NNCI), which gives 3.88 Mg ha−1 year−1. In general, the estimation of the biomass and associated carbon content found in this investigation are useful comparative data for economic evaluation of tropical forests in terms of capacity to capture carbon.

Rainfall rates estimated from polarimetric weather radar measurements of a convective rainstorm are used as input to a two-dimensional physically based rainfall-runoff model. The correlation length of the input rainfall field LS is 2.3 km. Runoff simulations are performed on two semi-arid watersheds covering 32 km2 and 121 km2 at basin data grid sizes LM of 125 m and 200 m, respectively. The characteristic basin length scale LW is taken as the square root of the watershed area. Rainfall data at resolutions LR of 1, 2, 3, 4, 6 and 8 km serve as model input to determine the effect of precipitation data spatial resolution on computed outflow hydrographs. Two dimensionless length parameters are identified which describe the similarity of the effect of rainfall data aggregation on both basins. The first parameter, L R L S , describes ‘storm smearing’, and the second parameter, L R L W , describes ‘watershed smearing’. Results from simulations without infiltration show storm smearing occurring as LR → LS. Watershed smearing causes more significant deviations from simulations using the finest-resolution data when L R L W exceeds 0.4. Results with infiltration reveal that excess rainfall volumes decrease with increasing L R L W . Additionally, excess rainfall volumes do not converge as L R L W is decreased to the practical lower limit provided by contemporary weather radars, which is of the order of 1 km.

urbanized catchment, the 14.3 km 2 Dead Run watershed near Baltimore, Maryland, USA, and the physics-based gridded surface/subsurface hydrologic analysis (GSSHA) model to examine the relative effect of each of these factors on ood peaks, runoff volumes, and runoff production efciencies. GSSHA was used because the model explicitly includes the spatial variability of land-surface and hydrodynamic parameters, including subsurface storm drains. Results indicate that increases in drainage density, particularly increases in density from low values, produce signicant increases in the ood peaks. For axed land-use and rainfall input, the ood magnitude approaches an upper limit regardless of the increase in the channel drainage density. Changes in imperviousness can have a signicant effect on ood peaks for both moderately extreme and extreme storms. For an extreme rainfall event with a recurrence interval in excess of 100 years, imperviousness is relatively unimportant in terms of runoff efciency and volume, but can affect the peak ow depending on rainfall rate. Changes to the width function affect ood peaks much more than runoff efciency, primarily in the case of lower density drainage networks with less impermeable area. Storm drains increase ood peaks, but are overwhelmed during extreme rainfall events when they have a negligible effect. Runoff in urbanized watersheds with considerable impervious area shows a marked sensitivity to rainfall rate. This sensitivity explains some of the contradictoryndings in the literature.

Weirs are widely used to measure discharges. In excellent installations they provide accurate measurements of discharge over a wide range of flows with a constant discharge coefficient. However, many weirs around the globe are filled with sediment and require manual rating curve adjustments or dredging. In this study we used a scale model to identify discharge coefficients with quantified uncertainty to identify the effect of sedimentation on the performance of a 140-degree sharp-edged V-notch weir. Variables changed included the discharge, channel slope, and degree of sedimentation. The experiments were performed in the University of Wyoming water resources lab, which is equipped with highly accurate weight-based flow measurement capability up to 0.1 m 3 s –1 (3.5 ft 3 s –1 ). Ultrasonic distance sensors were mounted on a computer-controlled traverse to make measurements of the water surface profile along the channel centerline, and at one transect off the channel centerline a specified distance. Data collected included discharge, and 100 water surface heights at each measurement point. Repeat measurements of water surface elevation allow statistical inference of the effect of turbulent unsteadiness on discharge measurements. Results indicate that sedimentation increases the discharge coefficient for a given channel slope, and that the discharge coefficient is not constant over the range of depths from 20% to 100% of the design depth.

Surface runoff sensitivity to spatial and temporal variability of rainfall is examined using physically based numerical runoff models. Rainfall duration tr and temporal sampling interval δt are varied systematically, and normalized by the time to equilibrium te. The relative sensitivity Rs is defined as the total volume of outflow variability over 50 Monte Carlo simulations normalized by the rainfall volume and the coefficient of variation of rainfall. Relative sensitivity to temporal rainfall variability increases with both tr and δt. An asymptotic Rs value proportional to (δt/te1/2) is approached as tr ≫ te. Two-dimensional surface runoff simulations with spatially variable rainfall, without temporal variability, on two watersheds indicate that Rs decreases as tr/te increases. Normalized Rs versus tr/te curves are identical for two watersheds and a one-dimensional overland flow plane. These findings indicate that spatial variability is dominant when tr te, particularly for larger values of δt/te.

The advantages of bentonite clay for sealing applications are well known. Bentonites have extremely low permeability, do not affect formation water chemistry, and have the ability to swell and deform in response to subsurface changes. The major limitation on the applicability of bentonite for water‐well annulus sealing is strength. Strength tests conducted in a physical model of a water well identified the expected magnitude of shear strength for several commercially available bentonite well‐sealing products. The dependence of bentonite strength in the annulus of a water well on both setting time and borehole geometry is discussed. Force balance calculations for seals constructed of both slurry grouts and granular products are presented. Seals constructed of bentonite slurry grouts do not have sufficient shear strength to resist hydrostatic forces in confined aquifer installations. Annulus seals constructed of granular bentonite products possess adequate shear strength to resist push‐out forces in limited...

Soil moisture conditions influence practically all aspects of Army activities and are increasingly affecting its systems and operations. Regional distributions of high resolution soil moisture data will provide critical information on operational mobility, penetration, and performance of landmine and UXO sensors. The US Army Corps of Engineers (USACE) developed the Gridded Surface/Subsurface Hydrologic Analysis (GSSHA), which is a grid-based two-dimensional hydrologic model that has been effectively applied to predict soil moisture conditions. GSSHA computes evapotranspiration (ET) using the Penman-Monteith equation. However, lack of reliable spatially-distributed meteorological data, particularly in denied areas, makes it difficult to reliably predict regional ET and soil moisture distributions. SEBAL is a remote sensing algorithm that computes spatio-temporal patterns of ET using a surface energy balance approach. SEBAL has been widely accepted and tested throughout the world against lysimeter, eddy-covariance and other field measurements. SEBAL estimated ET has shown good consistency and agreement for irrigated fields, rangelands and arid riparian areas. The main objective of this research is to demonstrate improved GSSHA soil moisture and hydrological predictions using SEBAL estimates of ET. Initial results show that the use of SEBAL ET and soil moisture estimates improves the ability of GSSHA to predict regional soil moisture distributions, and reduces uncertainty in runoff predictions.

[1] Development of a generally applicable rainfall-runoff model and identification of associated model parameters require understanding of connections between physical processes at disparate scales and hydrological similarities between catchments. In this study, we test the hypothesis that understanding of geomorphometric scaling relations can reduce uncertainty when transferring model parameters between catchments when applying the TOPMODEL concept. Scaling relations on contributing area, slope, and contour length were successfully used to scale the topographic index distribution in watersheds located in vastly different regions of the world: Japan, Nepal, Panama, and the United States. Model parameters were identified through calibration of TOPMODEL in the 210-km2 Kamishiiba catchment in Japan. These parameters were transferred to two Sun Koshi River subcatchments in Nepal, namely, the 850-km2 Likhu and 620-km2 Balephi catchments, the 414-km2 Upper Rio Chagres catchment in Panama, and the 37-km2 Town Brook catchment in the United States. Results show how a priori estimates of the most sensitive model parameters can be used to make predictions in poorly gauged or ungauged basins with some degree of confidence provided that scale effects are considered. This result hints at the potential universality of the topographic index distribution scaling relations in catchments where runoff is dominated by subsurface flow.

[1] A new one-dimensional infiltration and redistribution method is proposed as an alternative to the Richards equation (RE) for coupled surface and subsurface models. The proposed method discretizes soil water content into hypothetical hydraulically interacting bins. The entry and propagation of displacement fronts in each bin are simulated by means of explicit infiltration and drainage approximations based on capillary and gravitational driving forces. Wetting front advances within bins create water deficits that are satisfied by capillary-driven interbin flow. The method inherently provides numerical stability by precluding the need to directly estimate nonlinear gradients through numerical schemes. Comparisons of the performance of this method against RE solutions for theoretical, laboratory, and field data in both well-drained and high water table conditions are presented. The new method produces infiltration flux estimates with errors less than 10% compared to a widely used RE solution in tests on multiple soil textures with and without high water table conditions while providing unconditionally guaranteed conservation of mass.

Efficient and accurate simulation of the exchange between atmospheric, surface, and ground waters is essential in large-scale hydro-climatic models where high-resolution computational grids are not practical. This objective is met with a new and innovative method for simulating the entry and redistribution of water in the vadose zone using a discrete water content solution. Unlike infiltration predictors such as the solution of Richards’ equation or approximations thereof, our method employs a novel discretization in terms of water content. An explicit relationship is used to describe water movement in each discrete water-content region of the pore space. Water is advanced according to capillary drive, and is re-distributed according to the capillarity of each region of discrete water content. Evapotranspiration removes water from the profile according to a root distribution. The linear-explicit nature of the computations provides for computational efficiency in both speed and the required resolution for numerical stability and accuracy. The finite volume solution methodology guarantees conservation of mass for all soil types and wetting front conditions.

The Gridded Surface/Subsurface Hydrologic Analysis (GSSHA) model has been developed with research funding from the US Army, the US Environmental Protection Agency (EPA), US Army Corps of Engineer (USACE) civil research programs (LMS and SWWRP), and with funding for civil and military applications to fill an existing need; GSSHA has the ability to explicitly simulate spatially-varied hydrologic processes to solve a variety of common engineering problems. The GSSHA model features two-dimensional overland flow, sediment and water quality transport, coupled to one-dimensional stream flow, sediment and water quality transport, integrated with two-dimensional groundwater flow. GSSHA simulation times can be minimized by running GSSHA on parallel architectures, such as 64-bit multi-processor PCs, or any shared memory resource. Model setup and post-processing are greatly aided by the DoD Watershed Modeling System (WMS). Recent additions/improvements to the GSSHA model include: subsurface pipe networks for urban and agricultural drainage, improved sediment erosion and transport, simulation of wetlands, lakes, and reservoirs, and coupling of GSSHA to the Nutrient Sub-Module (NSM) to allow complex interaction among nitrogen and phosphorous species, with the intent to add more contaminants as modules are developed. GSSHA has been used for analysis and prediction of a wide range of issues and measures including: surface water runoff, soil moisture, groundwater recharge, transport of sediments and associated contaminants, transport of volatile contaminants, management of military training lands, and effects of urbanization on runoff and sediment loading. This paper focuses on improvements of the GSSHA erosion source and sediment transport routines.

We analyzed WSR-88D radar-rainfall estimates over the Mississippi River Basin for the period 1996–2000 at the time scale of individual events using data from over 900 rain gages that were not used in real-time adjustment of the rain rate estimates. In this paper we present an evaluation of a radar-rainfall dataset produced for the Global-Continental scale International Project (GCIP). The GCIP data were adjusted using a tuned Z-R relation to improve performance at the time scale of individual storms. Correlation between rain gage observations and the radar-rainfall estimates were computed for each RFC over the period of record analyzed. Large geographical difference in the accuracy of weather-radar rainfall estimates were quantified. Results indicate that primary indicators of radar-rainfall estimation accuracy are the number of overlapping radars, distance from radar to gage, and elevation of the gage.

Accurate estimation of sensible and latent heat fluxes as well as soil moisture from remotely sensed satellite images poses a great challenge. Yet, it is critical to face this challenge since the estimation of spatial and temporal distributions of these parameters over large areas is impossible using only ground measurements. A major difficulty for the calibration and validation of operational remote sensing methods such as SEBAL, METRIC, and ALEXI is the ground measurement of sensible heat fluxes at a scale similar to the spatial resolution of the remote sensing image. While the spatial length scale of remote sensing images covers a range from 30 m (LandSat) to 1000 m (MODIS) direct methods to measure sensible heat fluxes such as eddy covariance (EC) only provide point measurements at a scale that may be considerably smaller than the estimate obtained from a remote sensing method. The Large Aperture scintillometer (LAS) flux footprint area is larger (up to 5000 m long) and its spatial extent better constraint than that of EC systems. Therefore, scintillometers offer the unique possibility of measuring the vertical flux of sensible heat averaged over areas comparable with several pixels of a satellite image (up to about 40 Landsat thermal pixels or about 5 MODIS thermal pixels). The objective of this paper is to present our experiences with an existing network of seven scintillometers in New Mexico and a planned network of three scintillometers in the humid tropics of Panama and Colombia.

The need to simulate surface water flows in watersheds with diverse runoff production mechanisms has led to the development of the physically-based hydrologic model Gridded Surface Subsurface Hydrologic Analysis (GSSHA). GSSHA is a reformulation and enhancement of the two-dimensional, physically based model CASC2D. The GSSHA model is capable of simulating stream flow generated by a variety of sources, including runoff due to infiltration excess and saturated sources areas and seeps, as well as direct interaction between streams and the saturated groundwater. The model employs mass-conserving solutions of partial differential equations. The hydrologic components are closely linked, assuring an overall mass balance. The model has been applied to a diverse variety of projects and has been proven useful for analysis of hydrologic and sedimentation processes, and can provide information needed for designed systems and the potential effects of projects, land-use change, environmental restoration, best management practices, climate change, and related issues. This manual describes the model formulation, model input, and provides information on the practice of hydrologic modeling with GSSHA, and hydrologic modeling in general.

International audience; Increasing our understanding of the small scale variability of drop size distributions (DSD), and therefore of several bulk characteristics of rainfall processes, has major implications for our interpretation of the remote sensing based estimates of precipitation and its uncertainty. During the spring and summer of 2002 the authors conducted the DEVEX experiment (disdrometer evaluation experiment) to compare measurements of natural rain made with three different types of disdrometers collocated at the Iowa City Municipal Airport in Iowa City, Iowa in the Midwestern United States. This paper focuses on the evaluation of the instruments rather than analysis of the hydrometeorological aspects of the observed events. The comparison demonstrates discrepancies between instruments. The authors discuss the systematic and random effects in terms of rainfall quantities, drop size distribution properties, and the observed drop size vs. velocity relationships. Since the instruments were collocated, the effects of the natural variability of rain are reduced some with time integration, isolating the instrumental differences. The authors discuss the status of DSD measurement technologies and the implications for a range of hydrologic applications from remote sensing of rainfall to atmospheric deposition to soil erosion and sediment transport in the environment. The data set collected during the DEVEX experiment is made available to the research community.

Annual runoff hydrographs recorded by the Panama Canal Authority in the upper Rio Chagres basin indicate several peculiar features. First, the annual hydrograph is strikingly seasonal, with very few signs of direct runoff and a continuous decay in base flow during the dry season. Secondly, there are signs of anomalously high runoff production efficiencies early in the wet season. Thirdly, the base flow from the catchment exhibits up to three different “quasi-stable” base flow discharges as the wet season progresses. This study examined runoff generation in the upper Rio Chagres basin using the US Department of Agriculture, Natural Resources Conservation Service ‘Curve Number’ (CN) methodology. Specifically, variation curve of the CN was analyzed using rainfall and runoff observations from the basin. Results indicate significant influence of seasonality on the CN. Furthermore, there are significant inter-seasonal changes in the CN that invalidate the applicability of the CN approach in this tropical watershed.

Runoff production in tropical watersheds is governed by a wide variety of potential sources and there have been few rigorous studies to date. The 414 km2 upper Rio Chagres basin offers a unique opportunity to better understand the runoff production mechanisms in tropical watersheds through data analysis and modeling with rainfall and runoff data. Flow data and tipping bucket rain gage data are available at both the basin outlet (Chico gage) and for an 80.6 km2 internal basin location (Piedras gage). Modeling is performed using the Sacramento Soil Moisture Accounting Model (SAC-SMA), calibrated using data from 2000 and verified using data from 2001. The flood event of 28–31 December 2000 was examined in detail. Data analysis and modeling reveal critical threshold storages in the catchment, and anomalously high runoff production at the start of the wet season. This conclusion is supported by field studies that reveal evidence of high storage capacity and dry season water repellency. Observation of discrete quasi-stable baseflows in the upper Rio Chagres is not seen in the internal Rio Piedras drainage, which is shown to exhibit ephemeral behavior year-round. New data collection and monitoring is proposed for the upper Rio Chagres catchment, including measurements of rainfall above canopy, cloud stripping, stemflow, throughfall, soil moisture, interflow, and overland runoff measurements.

The upper Rio Chagres basin is a significant source of water for operation of the Panama Canal, producing a disproportionate share of the total runoff to the canal and also serving as the source of metropolitan drinking water for Panama City and Colon. To better understand the distribution of rainfall in the upper Rio Chagres watershed, a study was performed using rainfall observations from both ground- and space-based platforms in a geospatial statistical framework. The ground-based data are from two rain gages with long-term records and five additional gages installed in 1998. Given the significant topographic relief, and the sparsely distributed network of rain gages, it is likely that the spatial variability of rainfall is not accurately measured by this rain gage network. This paper asks two questions: Does a significant relationship exist between precipitation and elevation? Can the fraction of total catchment's rainfall coverage for storm events be determined? Three methods are to answer these questions ussing TRMM (Tropical Rainfall Measurement Mission) data products. The TRMM satellite provides 4 km2 resolution PR (Precipitation Radar) and much coarser TMI (TRMM Microwave Imager) observations multiple times per day. The instruments observe swath widths of 220 and 758 km respectively. Full basin coverage of a spatially distributed rain field observation is possible at PR resolution, allowing for determination of the areal extent of rain. Moreover, TRMM data can be used to develop a statistical model of the spatial variability of rainfall in an effort to make basin average estimates. Thirdly, available TRMM rainfall estimates are used directly, in validation of rain gage data.

The Watershed Systems Group (WSG) within the Coastal and Hydraulics Laboratory of the Engineer Research and Development Center (ERDC) supports the US Army and the US Army Corps of Engineers in both military and civil operations through the development, modification and application of surface and sub-surface hydrologic models. The Department of Defense (DoD) is also charged with managing approximately 200,000 km 2 of land within the United States on military installations and flood control and river improvement projects. The WSG provides the Army with predictions of stream flow and stage, inundated areas, saturated areas, soil moistures, groundwater levels, and contaminant fate and transport. Predictions are provided for anticipated changes in weather conditions, project alternatives and land-use changes. The WSG group uses a variety of models that are supported by the DoD graphical user interfaces (GUI) Watershed Modeling System ( WMS ), Groundwater Modeling System ( GMS ), and Surface water Modeling System ( SMS ). These GUIs are commonly referred to the XMS system. The XMS interfaces support a variety of model classes, from simple lumped-parameter runoff models, to 2-D overland, and 3-D unsaturated groundwater models.

We performed a detailed research comparison in an urban watershed between The U.S. Army Corps of Engineers, Engineer Research and Development Center (ERDC), Gridded Surface/Subsurface Hydrologic Analysis (GSSHA) model and the U.S. Army Corps of Engineers Hydrologic Engineering Center (HEC) HEC-1 watershed model. GSSHA represents a reformulation and enhancement of the CASC2D model. GSSHA has been successfully applied in a number of nonurbanized watersheds. This paper compares the performance of the two-dimensional, distributed parameter model GSSHA against the standard practice conceptual, lumped parameter model HEC-1 for runoff predictions in a small, urbanized watershed. Specific focus is on the calibration and verification results using data from nearly 40 rainfall events in an urbanized watershed. One longstanding criticism of distributed models, such as GSSHA, is that despite more detailed representation of the spatial variability of watershed characteristics and precipitation, their performance has not shown significant improvement over lumped parameter models. Only through marked improvements in runoff prediction can the benefits of the distributed approach be shown superior to the simpler to apply lumped parameter models. Urbanized watersheds provide the best opportunity for this demonstration because they contain a modified drainage network that can have a large effect on the runoff as seen at the watershed outlet. Further, lumped parameter model formulations cannot adequately describe the amount of heterogeneity and the unique spatial organization of an urban watershed. For this reason, accurate urban modeling with widely used standard-practice, conceptual rainfall-runoff models in the United States (i.e. HEC-1, TR20) can be difficult. Statistical analysis of simulation results compared with observed hydrographs clearly demonstrate that GSSHA is superior to standardpractice lumped-conceptual rainfall-runoff models, because of its distributed hydrodynamic formulation. This result has important implications for the development of advanced techniques for runoff modeling and flood prediction in urbanized areas.

[1] The application of physically based hydrologic models implies they properly simulate processes at the computational scale. A chief criticism is that model predictions are compared only to discharge data. The physically based, hydrologic model CASC2D is reformulated such that soil moistures and fluxes can be computed using Richards' equation. The gridded surface subsurface hydrologic analysis (GSSHA) model is calibrated and verified against outlet discharge measurements during the growing season. The verified model is used to simulate an extended period during which measurements of soil moisture are available. Though soil moisture data are not used in the calibration and verification efforts, the model reproduces both the trends and the magnitude of soil moisture during the growing season. With additional formulation enhancements, soil moistures during the nongrowing season are also reproduced within a root-mean-square error of 0.1. However, more work is needed to understand the underprediction of runoff during the nongrowing season.