Gridded Surface Subsurface Hydrologic Analysis Research Articles

Flash flooding in small urban watersheds: Storm event hydrologic response

AbstractWe analyze flash flooding in small urban watersheds, with special focus on the roles of rainfall variability, antecedent soil moisture, and urban storm water management infrastructure in storm event hydrologic response. Our results are based on empirical analyses of high‐resolution rainfall and discharge observations over Harry's Brook watershed in Princeton, New Jersey, during 2005–2006, as well as numerical experiments with the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model. We focus on two subwatersheds of Harry's Brook, a 1.1 km2 subwatershed which was developed prior to modern storm water management regulations, and a 0.5 km2 subwatershed with an extensive network of storm water detention ponds. The watershed developed prior to modern storm water regulations is an “end‐member” in urban flood response, exhibiting a frequency of flood peaks (with unit discharge exceeding 1 m3 s−1 km−2) that is comparable to the “flashiest” watersheds in the conterminous U.S. Observational analyses show that variability in storm event water balance is strongly linked to peak rain rates at time intervals of less than 30 min and only weakly linked to antecedent soil moisture conditions. Peak discharge for both the 1.1 and 0.5 km2 subwatersheds are strongly correlated with rainfall rate averaged over 1–30 min. Hydrologic modeling analyses indicate that the sensitivity of storm event hydrologic response to spatial rainfall variability decreases with storm intensity. Temporal rainfall variability is relatively more important than spatial rainfall variability in representing urban flood response, especially for extreme storm events.

Hydrometeorological Analysis of Tropical Storm Hermine and Central Texas Flash Flooding, September 2010

Abstract Heavy rainfall and flooding associated with Tropical Storm Hermine occurred on 7–8 September 2010 across central Texas, resulting in several flood-related fatalities and extensive property damage. The largest rainfall totals were received near Austin, Texas, and immediately north, with 24-h accumulations at several locations reaching a 500-yr recurrence interval. Among the most heavily impacted drainage basins was the Bull Creek watershed (58 km2) in Austin, where peak flows exceeded 500 m3 s−1. Storm cells were trained over the small watershed for approximately 6 h because of the combination of a quasi-stationary synoptic feature slowing the storm, orographic enhancement from the Balcones Escarpment, and moist air masses from the Gulf of Mexico sustaining the storm. Weather Research and Forecasting Model simulations with and without the Balcones Escarpment terrain indicate that orographic enhancement affected rainfall. The basin received nearly 300 mm of precipitation, with maximum sustained intensities of 50 mm h−1. The Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model was used to simulate streamflow from the event and to analyze the flood hydrology. Model simulations indicate that the spatial organization of the storm during intense rainfall periods coupled with surface conditions and characteristics mediate stream response.

A radiation-derived temperature-index snow routine for the GSSHA hydrologic model

Summary Accurate estimation of snowpack is vital in many parts of the world for both water management and flood prediction. Temperature-index (TI) snowmelt models are commonly used for this purpose due to their simplicity and low data requirements. Although TI models work well within lumped watershed models, their reliance on air temperature (and potentially an assumed lapse rate) as the only external driver of snowmelt limits their ability to accurately simulate the spatial distribution of snowpack and thus the timing of snowmelt. This limitation significantly reduces the utility of the TI approach in distributed hydrologic models because spatial variability within the watershed, including snowpack and snowmelt, is usually the primary reason for selecting a distributed model. In this paper, a new radiation-derived temperature index (RTI) approach is presented that uses a spatially-varying proxy temperature in place of air temperature within the TI model of the fully-distributed Gridded Surface Subsurface Hydrologic Analysis (GSSHA) watershed model. The RTI is derived from a radiation balance and includes spatial heterogeneity in both shortwave and longwave radiation. Thus, the RTI accounts for more local variation in the available energy than air temperature alone. The RTI model in GSSHA is tested at the Senator Beck basin in southwestern Colorado where observations for snow water equivalent (SWE) and LandSat-derived images of snow cover area (SCA) are available. The TI and RTI approaches produce similar SWE estimates at two non-forested and relatively flat sites with SWE observations. However, the two models can produce very different SWE values at sites with forests or topographic slopes, which leads to significant differences in the basin-wide SWE values of the two models. Furthermore, the RTI model provides better basin-wide SCA estimates than the TI model in 75% of the LandSat images analyzed.

Climate Change Induced Precipitation Effects on Water Resources in the Peace Region of British Columbia, Canada

Climate change would significantly affect the temporal pattern and amount of annual precipitation at the regional level, which in turn would affect the regional water resources and future water availability. The Peace Region is a critical region for northern British Columbia’s social, environmental, and economic development, due to its potential in various land use activities. This study investigated the impacts of future climate change induced precipitation on water resources under the A2 and B1 greenhouse gas emission scenarios for 2020–2040 in a study area along the main river of the Kiskatinaw River watershed in the Peace Region as a case study using the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) modeling system. The simulation results showed that climate change induced precipitation changes significantly affect monthly, seasonal and annual stream flows. With respect to the mean annual stream flow of the reference period (2000–2011), the mean annual stream flow from 2020 to 2040 under the A2 and B1 scenarios is expected to increase by 15.5% and 12.1%, respectively, due to the increased precipitation (on average 5.5% in the A2 and 3.5% in the B1 scenarios) and temperature (on average 0.76 °C in the A2 and 0.57 °C in the B1 scenarios) predicted, with respect to that under the reference period. From the seasonal point of view, the mean seasonal stream flow during winter, spring, summer and fall from 2020 to 2040 under the A2 scenario is expected to increase by 10%, 16%, 11%, and 11%, respectively. On the other hand, under the B1 scenario these numbers are 6%, 15%, 6%, and 8%, respectively. Increased precipitation also resulted in increased groundwater discharge and surface runoff. The obtained results from this study will provide valuable information for the study area in the long-term period for seasonal and annual water extractions from the river and allocation to the stakeholders for future water supply, and help develop a regional water resources management plan for climate change induced precipitation changes.

Exploring storage and runoff generation processes for urban flooding through a physically based watershed model

AbstractA physically based model of the 14 km2 Dead Run watershed in Baltimore County, MD was created to test the impacts of detention basin storage and soil storage on the hydrologic response of a small urban watershed during flood events. The Dead Run model was created using the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) algorithms and validated using U.S. Geological Survey stream gaging observations for the Dead Run watershed and 5 subbasins over the largest 21 warm season flood events during 2008–2012. Removal of the model detention basins resulted in a median peak discharge increase of 11% and a detention efficiency of 0.5, which was defined as the percent decrease in peak discharge divided by percent detention controlled area. Detention efficiencies generally decreased with increasing basin size. We tested the efficiency of detention basin networks by focusing on the “drainage network order,” akin to the stream order but including storm drains, streams, and culverts. The detention efficiency increased dramatically between first‐order detention and second‐order detention but was similar for second and third‐order detention scenarios. Removal of the soil compacted layer, a common feature in urban soils, resulted in a 7% decrease in flood peak discharges. This decrease was statistically similar to the flood peak decrease caused by existing detention. Current soil storage within the Dead Run watershed decreased flood peak discharges by a median of 60%. Numerical experiment results suggested that detention basin storage and increased soil storage have the potential to substantially decrease flood peak discharges.

Investigation of Groundwater Contribution to Stream Flow under Climate and Land Use Changes: A Case Study in British Columbia, Canada

Groundwater contributes a significant proportion of stream flow, and its contribution varies temporally throughout the year. The objective of this study was to investigate the temporal dynamics of groundwater contribution to stream flow under the effects of climate and land use changes. A study area of the Mainstem sub-watershed of the Kiskatinaw River watershed, British Columbia, Canada was used as a case study. A physically conceptual model, Gridded Surface Subsurface Hydrologic Analysis (GSSHA), was developed for the study area. One greenhouse gas (GHG) emission scenario (i.e., B1: more integrated and environmental friendly world) was used for climate change study for 2012-2016, and land use changes scenarios were generated for shortterm period (2012-2016) due to limited future projected land use data. The simulation results revealed that climate change affects significantly the temporal patterns of mean groundwater contribution to stream flow. Due to precipitation variability, these contributions varied monthly, seasonally, and annually. When land use changes (i.e., increasing forest clear cut area, and decreasing forest and agricultural areas) were combined with climate change scenarios, these contributions were decreased due to changes in the flow patterns to the regime with more surface runoff and stream flow but less groundwater discharge. Compared to the reference period (20072011), the mean annual groundwater contribution to stream flow from 2012 to 2016 under the B1 climate change scenario and the combined effects of B1 scenario and land use changes is expected to decrease by 1.8% and 4.3%, respectively, due to increased precipitation (on average 3.6% under the B1 scenario) and temperature (on average 0.36°C under the B1 scenario), and land use changes. The results obtained from this study will provide useful information for seasonal and annual water extractions from the river and allocation to the stakeholders for future water Original Research Article Saha; BJECC, 5(1): 1-22, 2015; Article no.BJECC.2015.001 2 supply, as well as ecological conditions of the stream, which will be beneficial to aquatic ecosystems. They will also provide how land use changes can impact the groundwater contribution to stream flow, which will be useful for planning of water resources management considering future climate and land use changes.

Testing the Effects of Detachment Limits and Transport Capacity Formulation on Sediment Runoff Predictions Using the U.S. Army Corps of Engineers GSSHA Model

The physics-based Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model was developed by the U.S. Army Corps of Engineers for hydrologic, sediment transport, and water quality analyses. GSSHA simulates erosion and transport of sediments on the overland flow plain based on rainfall intensity and overland flow depth and velocity. The original sediment transport capabilities in GSSHA were taken from the GSSHA predecessor, CASC2D-SED. Independent testing of the sediment transport methods in CASC2D-SED by researchers identified several deficiencies in the formulation that caused significant overestimation of sediment yield during hydrologic events that were much larger than a calibration event. Sediment detachment limits and a variety of overland sediment transport equations were incorporated into the GSSHA model to address these deficiencies. This paper presents an evaluation of these modifications in terms of GSSHA sediment yield predictions of both single-event and summer growing season sediment yields. Simulation results are compared with research-quality sediment discharge data set from the USDA Goodwin Creek Experimental Watershed (GCEW). Results show that the reformulated GSSHA sediment transport model predicts event-total sediment discharge volume within (±) 50% over hydrologic events that vary by three orders of magnitude. The transport capacity method selected for use in the simulation had a large effect on the model results.

Hydrologic response of a high altitude glacierized basin in the central Tibetan Plateau

Hydrologic cycles of most high altitude glacierized watersheds in the Tibetan Plateau are not closely monitored due to their inaccessibility. Understanding the hydrologic cycle in such a basin may provide insight into the role climate plays on changes in glacier mass. Thus, hydrologic simulations with a physical perspective in the Tibetan glacierized watershed are of great significance. A high altitude glacierized basin in the central Tibetan Plateau, Qugaqie basin, was investigated with an energy-balance based glacier-melt model and the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model. With these two models, glacier mass balance was estimated and basin runoff from glaciers was simulated at a daily time step. Results from the simulation period (October 1, 2006–September 30, 2011) demonstrated that the glaciers experienced a large negative surface mass balance with the cumulative value of −300cmw.e.. In other words, up to 13.93×106m3 water volume was melting out from the glaciers during these five years. In the 2007/08year, however, the glaciers experienced a surplus mass balance because of the low air temperature and increased precipitation in the summer season. Infiltration, evapotranspiration (ET), and overland flow were also calculated using the GSSHA model. Results showed that precipitation, the main water source, contributed roughly 95% to the total mass gain of the annual water balance in the Qugaqie basin during the study period, while the glacial runoff (snow/ice melting) contributed 5% water balance. In the water loss, 17% of annual water volume was consumed by the ET process. As a result, the remaining water volume (83%) converted to the basin river flow to the Lake Nam Co. In the summertime, the glacial runoff accounted for 15% of the total basin runoff volume, while this contribution increased in the upstream portion to 46% due to a large percentage of glacierized area. The analysis showed that the glacial runoff contributions to the total river flow decrease significantly due to the decreased air temperature in the summer of 2008. In general, the integrated model produced acceptable estimations of hydrologic response in this high altitude glacierized basin, which is jointly fed by precipitation and glacial runoff. This study suggests that, a process-based model for glacierized basins can provide a reasonable simulation of hydrologic response and further enhance our understanding of this high altitude region in the Tibetan Plateau.

The use of weather radar for rainfall-runoff modeling, case of Seybouse watershed (Algeria)

The use of radar for rainfall and runoff estimation is beneficial because of the high spatial and temporal resolution and large areal coverage; the main objective of this research is the calibration of the weather radar of Annaba for hydrological applications. To improve rainfall distribution estimation for the maritime watershed (1,129 km2) (Seybouse, Annaba), located in the north eastern of Algeria, a new technique was used based on the creation of six virtual rainfall stations uniformly throughout the area. The rainfall data for these virtual stations are estimated from raw weather radar data using a newly developed program called “Rain-Data ver1.0.” The calibrated radar-derived rainfall is used as input data in the Gridded Surface Subsurface Hydrologic Analysis model; the results show that all radar rainfall input data tend to produce more accurate runoff hydrographs than rain gauge data. Finally, the use of radar rainfall data to estimate runoff gives encouraging results, especially in regions where continuous gauge rainfall measurements are not available and rain gauges are sparsely distributed.

The Comparative Accuracy of Two Hydrologic Models in Simulating Warm‐Season Runoff for Two Small, Hillslope Catchments

AbstractThis article assesses the performance of two hydrologic models in simulating warm‐season runoff for two upland, low‐yield micro‐catchments near Coshocton, Ohio. The two models, namely the Storm Water Management Model (SWMM) and the Gridded Surface‐Subsurface Hydrologic Analysis (GSSHA), were implemented with contrasting levels of complexity, with the former representing the catchments as lumped spatial units and computing evaporation only from standing water, and the latter incorporating fine‐scale variation in topography and soil properties and computing evapotranspiration from soil based on weather data. Our investigation began with uncalibrated model runs for 1990‐2003 except for 1994 using a priori parameter values. Then a set of calibration experiments were performed wherein the sensitivity of model performance to the length of calibration records was examined. Our results pointed to large errors associated with simulations from both models: even the calibrated models were unable to reproduce the seasonal and between‐catchment contrasts in runoff response. Using a priori parameter values, SWMM attained better results than GSSHA. However, with simple calibration, GSSHA outperformed SWMM in several respects. It was also found that extending the record of calibration rendered relatively minor changes to model performance. The practical and scientific implications of the findings are discussed.

Impacts of Spatial Distribution of Impervious Areas on Runoff Response of Hillslope Catchments: Simulation Study

This study analyzes variations in the model-projected changes in catchment runoff response after urbanization that stem from variations in the spatial distribution of impervious areas, interevent differences in temporal rainfall structure, and antecedent soil moisture (ASM). In this work, an ensemble of hypothetical imperviousness scenarios created for two small (<1 ha) watersheds were incorporated into the gridded surface subsurface hydrologic analysis (GSSHA) model, which was calibrated against 41 runoff events under natural conditions. Each event was resimulated for each imperviousness scenario. Variations in the model-projected changes in runoff were characterized and related to temporal rainfall dispersion, ASM, and two metrics: (1) proximity of imperviousness from the outlet, and (2) normalized number of downstream pervious elements. Key findings include the following: First, interscenario variations in the simulated runoff were relatively subdued on an event-mean basis but were much wider for individual events. For example, the coefficient of variation (CV) was less than 7.8% for runoff peak but was beyond 20% for certain events. Second, the rate of increase in simulated runoff peaks with elevated imperviousness tends to be lower for events with higher temporal rainfall dispersion and ASM, with one of the largest events exhibiting the slowest rate of increase. Third, both metrics were found to be negatively correlated with simulated runoff depth. These findings point to the possibility of refining the model projection by incorporating indicators of overall locations of impervious areas, rainfall dispersion, and soil moisture conditions.

Physically Based, Hydrologic Model Results Based on Three Precipitation Products1

Abstract: The main objective of the study is to examine the accuracy of and differences among simulated streamflows driven by rainfall estimates from a network of 22 rain gauges spread over a 2,170 km2 watershed, NEXRAD Stage III radar data, and Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite data. The Gridded Surface Subsurface Hydrologic Analysis (GSSHA), a physically based, distributed parameter, grid‐structured, hydrologic model, was used to simulate the June‐2002 flooding event in the Upper Guadalupe River watershed in south central Texas. There were significant differences between the rainfall fields estimated by the three types of measurement technologies. These differences resulted in even larger differences in the simulated hydrologic response of the watershed. In general, simulations driven by radar rainfall yielded better results than those driven by satellite or rain‐gauge estimates. This study also presents an overview of effects of land cover changes on runoff and stream discharge. The results demonstrate that, for major rainfall events similar to the 2002 event, the effect of urbanization on the watershed in the past two decades would not have made any significant effect on the hydrologic response. The effect of urbanization on the hydrologic response increases as the size of the rainfall event decreases.

Performance of a conceptual and physically based model in simulating the response of a semi‐urbanized watershed in San Antonio, Texas

AbstractThe need for accurate hydrologic analysis and rainfall–runoff modelling tools has been rapidly increasing because of the growing complexity of operational hydrologic and hydraulic problems associated with population growth, rapid urbanization and expansion of agricultural activities. Given the recent advances in remote sensing of physiographic features and the availability of near real‐time precipitation products, rainfall–runoff models are expected to predict runoff more accurately. In this study, we compare the performance and implementation requirements of two rainfall–runoff models for a semi‐urbanized watershed. One is a semi‐distributed conceptual model, the Hydrologic Engineering Center‐Hydrologic Modelling System (HEC‐HMS). The other is a physically based, distributed‐parameter hydrologic model, the Gridded Surface Subsurface Hydrologic Analysis (GSSHA). Four flood events that took place on the Leon Creek watershed, a sub‐watershed of the San Antonio River basin in Texas, were used in this study. The two models were driven by the Multisensor Precipitation Estimator radar products. One event (in 2007) was used for HEC‐HMS and GSSHA calibrations. Two events (in 2004 and 2007) were used for further calibration of HEC‐HMS. Three events (in 2002, 2004 and 2010) were used for model validation. In general, the physically based, distributed‐parameter model performed better than the conceptual model and required less calibration. The two models were prepared with the same minimum required input data, and the effort required to build the two models did not differ substantially. Copyright © 2012 John Wiley &amp; Sons, Ltd.

Relative importance of impervious area, drainage density, width function, and subsurface storm drainage on flood runoff from an urbanized catchment

The literature contains contradictory conclusions regarding the relative effects of urbanization on peak flood flows due to increases in impervious area, drainage density and width function, and the addition of subsurface storm drains. We used data from an urbanized catchment, the 14.3 km2 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 flood peaks, runoff volumes, and runoff production efficiencies. 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 significant increases in the flood peaks. For a fixed land‐use and rainfall input, the flood magnitude approaches an upper limit regardless of the increase in the channel drainage density. Changes in imperviousness can have a significant effect on flood 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 efficiency and volume, but can affect the peak flow depending on rainfall rate. Changes to the width function affect flood peaks much more than runoff efficiency, primarily in the case of lower density drainage networks with less impermeable area. Storm drains increase flood 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 contradictory findings in the literature.

Physically Based Hydrological Modeling of the 2002 Floods in San Antonio, Texas

AbstractThe July 2002 floods in South Texas resulted from excessive precipitation caused by a slow moving tropical wave accompanied by an abundance of tropical moisture, which resulted in 12 deaths and nearly $1 billion in damage. South Central Texas is particularly vulnerable to floods because of: (1) its proximity to a moist air source (the Gulf of Mexico); (2) the Balcones Escarpment, which concentrates rainfall runoff; (3) a tendency for synoptic scale features to become cut off and stall over the area; and (4) decaying tropical cyclones stalling over the area. This paper examines the hydrology of the July 2002 floods in three urbanized watersheds in the city of San Antonio and Bexar County, Texas. The physically based, distributed parameter gridded surface subsurface hydrologic analysis hydrologic model was used to simulate the flood over the three watersheds. Various flood control features were included in the simulations. The hydrologic model, driven by the next generation radar multi-sensor precip...

On CMORPH Rainfall for Streamflow Simulation in a Small, Hortonian Watershed

Abstract The objective is to assess the use of the Climate Prediction Center morphing method (CMORPH) (~0.073° latitude–longitude, 30 min resolution) rainfall product as input to the physics-based fully distributed Gridded Surface–Subsurface Hydrologic Analysis (GSSHA) model for streamflow simulation in the small (21.4 km2) Hortonian watershed of the Goodwin Creek experimental watershed located in northern Mississippi. Calibration is performed in two different ways: using rainfall data from a dense network of 30 gauges as input, and using CMORPH rainfall data as input. The study period covers 4 years, during which there were 24 events, each with peak flow rate higher than 0.5 m3 s−1. Streamflow simulations using CMORPH rainfall are compared against observed streamflows and streamflow simulations using rainfall from a dense rain gauge network. Results show that the CMORPH simulations captured all 24 events. The CMORPH simulations have comparable performance with gauge simulations, which is striking given the significant differences in the spatial scale between the rain gauge network and CMORPH. This study concludes that CMORPH rainfall products have potential value for streamflow simulation in such small watersheds. Overall, the performance of CMORPH-driven simulations increases when the model is calibrated with CMORPH data than when the model is calibrated with rain gauge data.

Comparing the capability of distributed and lumped hydrologic models for analyzing the effects of land use change

Empirically based lumped hydrologic models have an extensive track record of use for various engineering applications. Physically based, multi-dimensional distributed models have also been in development and use for many years. Despite the availability of high resolution data, better computational resources and robust, numerical methods implemented in such models, their usage is still limited, especially in the realm of surface water runoff simulation. Lumped models are often extended to solve complex hydrologic problems that may be beyond their capabilities. Here we attempt to differentiate the ability of lumped and distributed models to analyze a common watershed development issue such as land use change. For this, we employ two common US Army Corps of Engineers (USACE) models, well established in the literature and application, using the Hydrologic Engineering Center – Hydrologic Modeling System (HEC-HMS) model in a fully lumped mode and the fully distributed model Gridded Surface Subsurface Hydrologic Analysis (GSSHA). A synthetic watershed is used to establish that a distributed model like GSSHA more intuitively simulates land use change scenarios by distinguishing the spatial location of the change and its effects on the watershed response. An actual watershed at Tifton, Georgia is used to validate the observations made from the synthetic watershed.

Tools and Algorithms to Link Horizontal Hydrologic and Vertical Hydrodynamic Models and Provide a Stochastic Modeling Framework

We present algorithms and tools we developed to automatically link an overland flow model to a hydrodynamic water quality model with different spatial and temporal discretizations. These tools run the linked models which provide a stochastic simulation frame. We also briefly present the tools and algorithms we developed to facilitate and analyze stochastic simulations of the linked models. We demonstrate the algorithms by linking the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model for overland flow with the CE‐QUAL‐W2 model for water quality and reservoir hydrodynamics. GSSHA uses a two‐dimensional horizontal grid while CE‐QUAL‐W2 uses a two‐dimensional vertical grid. We implemented the algorithms and tools in the Watershed Modeling System (WMS) which allows modelers to easily create and use models. The algorithms are general and could be used for other models. Our tools create and analyze stochastic simulations to help understand uncertainty in the model application. While a number of examples of linked models exist, the ability to perform automatic, unassisted linking is a step forward and provides the framework to easily implement stochastic modeling studies.

Application of a Distributed Hydrologic Model to the November 17, 2004, Flood of Bull Creek Watershed, Austin, Texas

This study presents a hydrologic analysis of a flood event that took place over a small urbanizing watershed in Austin, Texas. The physically based, distributed-parameter gridded surface subsurface hydrologic analysis (GSSHA) hydrologic model was used to simulate the watershed response to a very high-intensity rain event. The hydrologic model was forced by both gauge-observed and multisensor precipitation estimator (MPE) rainfall input. Observed discharge was compared to GSSHA-generated hydrograph under various degrees of representation of the watershed physiography. In addition, simulation hydrographs by GSSHA using five different model grid sizes were compared in order to evaluate the effect of grid size on model predictions. The simulation hydrograph for the model using a 30-m grid cell generally compared well to the observed flow data once the effects of storm water detention were simulated. The comparison of simulation results from models using 30, 60, 90, 120, and 150 m grid size highlighted the los...

Sensitivity of Streamflow Simulations to Temporal Variability and Estimation of Z–R Relationships

This study focuses on the sensitivity of streamflow simulations to temporal variations in radar reflectivity–rainfall (i.e., Z–R ) relationships. The physically based continuous-mode distributed hydrologic model—gridded surface subsurface hydrologic analysis—is used to predict runoff during three major rainfall-runoff periods observed in a 35 km2 experimental watershed in southern Louisiana. Z–R relationships are derived at a series of temporal scales ranging from a climatological scale, where interstorm Z–R variations are ignored, down to a subevent scale, where variations in rainfall type (convective versus stratiform) are taken into account. The analysis is first performed using Z and R data pairs derived directly from disdrometer drop size distribution measurements, and then repeated using WSR-88D radar reflectivity data. The degree of sensitivity in runoff simulations to temporal variations in Z–R relationships depends largely on the method used to derive the parameters of these relationships. Using ...