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

CHAD FURL,HATIM O. SHARIF,ALMOUTAZ EL HASSAN, AND NEWFEL MAZARI Department of Civil Engineering, The University of Texas at San Antonio, San Antonio, Texas

DANIEL BURTCH AND GRETCHEN L. MULLENDORE Department of Atmospheric Sciences, University of North Dakota, Grand Forks, North Dakota

(Manuscript received 23 July 2014, in final form 9 July 2015)

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 2 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 2 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.

1. Introduction storm near D’Hanis (560 mm in 2 h 45 min), and the 1978 event near Bluff (790 mm in 24 h; Caran and Baker 1986; In central Texas, the unique combination of flood- Caracena and Fritsch 1983). Numerous events over the prone physiography and susceptibility to extreme mete- past century in FFA have exceeded 24-h accumulations of orological events has produced some of the largest rainfall 750 mm (Asquith and Slade 1995). events and flood magnitudes in the United States and the While FFA is prone to short-lived intense convective world (Smith et al. 2000; Baker 1975). Moreover, Texas outbreaks in the absence of tropical disturbances, many consistently leads the nation in flash flood–related deaths, of the largest events are of tropical origin. These storms the majority of which occur across central Texas in an are characterized by easterly waves of air masses con- area dubbed Flash Flood Alley (FFA; Zahran et al. 2008; taining enormous moisture amounts from passage over Sharif et al. 2012). FFA is oriented from north to south warm seas (Nielsen-Gammon et al. 2005). If the moist across the central portion of the state, extending approx- air masses are able to protrude inland far enough, they imately from San Antonio to Dallas, Texas (TX). FFA are met by the Balcones Escarpment, which is thought to holds several world-record rainfall rates on time scales less serve as a barrier (Caran and Baker 1986). Orographic than 24 h (Slade and Patton 2003). Notable events include barriers act to force an air mass upward. If the upward the 1921 storm near Thrall (965 mm in 24 h), the 1935 lift forces the air mass to cool down enough, water vapor condenses to produce clouds and precipitation. Severe flash flood events have been known to occur in areas of Corresponding author address: Chad Furl, Department of Civil Engineering, The University of Texas at San Antonio, 1 UTSA orographically enhanced rainfall (Lin et al. 2001). Circle, San Antonio, TX 78249. Once precipitation falls to the surface, the physio- E-mail: [email protected] graphic features of the landscape control hydrologic

DOI: 10.1175/JHM-D-14-0146.1

Ó 2015 American Meteorological Society Unauthenticated | Downloaded 09/30/21 03:35 PM UTC 2312 JOURNAL OF HYDROMETEOROLOGY VOLUME 16 response. The Balcones Escarpment separates the lime- simulation along with the Gridded Surface Subsurface stone terrain of the Edwards Plateau from the gently Hydrologic Analysis (GSSHA) model (Downer and sloping clay and sand terrain of the Blackland Prairies and Ogden 2006) for hydrologic analysis. Coastal Plain. Landscape features augmenting stream response along the Edwards Plateau and Balcones 2. Storm description Escarpment include shallow stony soils underlain by bedrock, steep terrain, high rill densities on hillslopes, Features of the storm that produced flooding across and sparse scrubby vegetation. At the bottom of the the Bull Creek watershed are examined through analysis escarpment, clay soils permit little infiltration when of synoptic- and mesoscale features leading to and saturated (Patton and Baker 1976). In addition to en- evolving during the event. Hermine began as a depression vironmental factors, the region has experienced size- south of Mexico’s southern Pacific coast. The depression able urbanization over the last several decades, which moved northward over Mexico, becoming a remnant low can exacerbate the flood potential through the increase as it crossed land. Once in the Gulf of Mexico, deep of the impervious areas. convection formed and thunderstorm activity became On 7–8 September 2010, persistent, heavy rainbands organized with the formation of cyclonic bands. As the associated with Tropical Storm Hermine produced one storm moved away from land, it gained further organi- of the heaviest rain events in nearly 30 years for Travis zation and became a tropical storm at approximately and Williamson Counties (central Texas). While the 0600 UTC 6 September. Deep convection continued to tropical storm–associated rainfall showed similarities to develop near the storm’s center throughout the day as it other extreme events in the region, it was different from trekked across the Gulf of Mexico at an average speed of 2 most floods associated with dissipating tropical cyclones 12 knots (kt; 1 kt 5 0.51 m s 1; Avila 2010). in that heavy rains developed well away from the rem- Hermine made landfall at around 0200 UTC 7 Sep- nant center. Predecessor rain events developing on the tember, 40 km south of Brownsville, TX, along the poleward side of recurving tropical cyclones have received northeastern coast of Mexico. A minimum pressure of 2 recent attention (e.g., Schumacher 2011; Galarneau et al. 989 mb was sustained here with peak winds of 110 km h 1. 2010); however, rainfall from Hermine developed well Hermine tracked to the north-northwest across Texas, behind the center. The 24-h rainfall totals of 250–400 mm remaining a tropical storm for 16 h after making landfall. resulted in a 500-yr event at several locations along the At around 0000 UTC 8 September, the storm was Balcones Escarpment. Flash flooding occurred across downgraded to a tropical depression. The system con- numerous area watersheds, with unit runoff values near- tinued north and northeast through Oklahoma before ing the United States envelope curve at the North Fork becoming a remnant low and dissipating over Kansas 2 2 San Gabriel River (52 m3 s 1 km 2) north of Austin, TX (Avila 2010). Figure 1a displays the storm’s progression (Winters 2012). Among the most heavily impacted wa- and track (NOAA 2010). tersheds included the semiurbanized Bull Creek catch- At 1200 UTC 7 September, Hermine was located in ment (58 km2) in Austin. During the 2-day period, the southern Texas with a stalled front positioned in the 58 km2 catchment received over 290 mm of rain, sustain- panhandle region of Texas (Fig. 1b). The 500-mb height ing large amounts of flood-related damage and a fatality. field (not shown) indicates an area of high pressure be- In the present work, we examine the primary hydro- hind the stalled front with a large gradient in atmospheric meteorological controls leading to heavy rainfall across moisture present along its edge. Precipitable water values central Texas and flooding along Bull Creek. The man- greater than 50 mm (central Texas September mean ’ uscript is divided into three sections analyzing meteo- 36.6 mm, standard deviation 5 12.0 mm) covered all of rological aspects of the storm, rainfall across the Bull southern and central Texas with values at approximately Creek basin, and flood hydrology of the catchment. half in the western portion of the state (Fig. 1c; Ware Specifically, we seek to characterize the structure, mo- et al. 2000). The 1200 UTC 7 September radiosonde from tion, and evolution of the storm along with determining Brownsville (data not shown) indicated the atmosphere the effect of terrain-aided forcing from the Balcones was nearly saturated through the troposphere (pre- Escarpment. Gauge-adjusted radar is used to describe cipitable water 5 67.5 mm). CAPE values from this re- 2 spatiotemporal rainfall patterns across the catchment cording were in excess of 2000 J kg 1 indicating moderate and calculate recurrence intervals. Physics-based dis- instability. Precipitable water values measured from the tributed hydrologic modeling is conducted to examine Midland radiosonde, located near the edge of the front, the important hydrologic mechanisms of the flood event. were about one-third of those at Brownsville. Models used include the Weather Research and Fore- As Hermine moved farther into Texas, the precipi- casting (WRF) Model (Skamarock et al. 2008) for storm tation shield began to change its structure and no longer

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FIG. 1. (a) Tropical Storm Hermine’s track through Texas. Times are given as four-digit hour (UTC) and day (in September 2010) for every other point. (b) Surface map displaying pressure and frontal locations (at 1200 UTC 7 Sep). (c) Precipitable water values (mm) from 2 SuomiNet (at 1200 UTC 7 Sep). (d) Surface wind vectors and mixing ratios (g kg 1) map (0200 UTC 8 Sep). An outline of the Edwards Plateau ecoregion is shown. appeared as the classic banding seen in tropical cyclones. heavy localized accumulations (Kimball 2008). Indeed, At around 0000 UTC 8 September, as the remnant low the well-documented reintensification of Tropical center was nearing the Oklahoma border, areas of deep Cyclone Erin over Oklahoma and resultant flooding convection began developing farther south along a lin- provide an example of the complicated land surface ear boundary, showing that Hermine had undergone feedbacks that can lead to focused rainfall after landfall extratropical transition. Advanced Research version of (Arndt et al. 2009). In the case of Tropical Cyclone Erin, WRF (ARW) simulations (discussed below) show this abnormally moist soil conditions were hypothesized to linear boundary well in the surface wind field (not provide the necessary environmental conditions for re- shown). Southeasterly winds advecting moisture-rich air development over land (Evans et al. 2011). While in- from the Gulf were met by drier air wrapping around the creased soil moisture left by Hermine rain across the western side of the storm, creating a strong boundary Texas Coastal Plain may have influenced the lower- (Fig. 1d). The area of convergence roughly followed tropospheric inflow region to the MCS, the location and the Balcones Escarpment and resulted in the develop- pattern of the outbreak suggests the Balcones Escarp- ment of a mesoscale convective system (MCS). The ment provided an orographic effect. MCS assumed a squall-line structure along the linear The synoptic- and mesoscale setup for the storm synoptic-scale boundary training over the area for shows similarities to other heavy orographic rainfall approximately 6 h. events in the United States. These events are charac- Figure 2 shows a series of infrared images displaying terized by unstable airstreams impinging on the rapid convective growth along this boundary from 0015 barrier, a quasi-stationary synoptic system slowing the to 0815 UTC 8 September. The development of deep convective system, and very moist air masses sustaining convection well south of the remnant center was a the storm (Lin et al. 2001). To examine the role of unique feature of Tropical Storm Hermine. In general, a terrain, WRF Model (Skamarock et al. 2008)simula- broadening of the rainfall region and decrease in mean tions were conducted with and without inclusion of the rainfall rates can be expected after landfall. This pattern Balcones Escarpment (hereafter referred to as terrain- though, is sensitive to the presence of vertical wind included and terrain-removed simulations). In the shear, topography, and other factors that can result in terrain-removed simulations, topography over 100 m

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FIG. 2. (a)–(f) GOES infrared imagery with temperatures (8C) across Texas at 0015, 0215, 0400, 0500, 0630, and 0815 UTC 8 Sep 2010, respectively. was smoothed to 100 m, removing effects from the feature from San Antonio to north of Austin (Fig. 3g). escarpment. The rainfall event produced totals in excess of 250 mm Simulations were conducted on three nested domains over approximately 900 km2 from Austin and to the with grid spacing of 27, 9, and 3 km (Fig. 3a). USGS north. A large accumulation gradient was present nor- 10-min terrain data were used on the largest domain, mal to the line of heavy rainfall. At 75 km to the east and with 30-s terrain data used in the two smaller areas. Each west of the heaviest rainfall, 24-h totals were generally of the domains contained 50 vertical levels. The Euro- less than 65 mm. The highest recorded 24-h rain gauge pean Centre for Medium-Range Weather Forecasts total (370 mm) occurred 30 km north of Bull Creek near (ECMWF) interim reanalysis data were used for the Georgetown, TX. Interestingly, the 1921 Thrall, TX, initial and lateral boundary conditions (updated in 6-h storm (965 mm in 24 h), which held the U.S. record for intervals; Dee et al. 2011). Model simulations were over 50 years (Smith et al. 2000), occurred 30 km east of conducted for 60 h, from 1200 UTC 6 September to the maximum accumulation from Hermine. 0000 UTC 9 September 2010. The analysis period cap- The terrain-included simulations match the overall tures the approximate 24-h maxima along the Balcones observed precipitation pattern well, with a large area of Escarpment (ending 1200 UTC 8 September 2010). increased accumulations from north to south through Table 1 provides additional details on model setup. the central portion of the state. The terrain-included run Figure 3 shows WRF simulations for each domain also captures increased values across southern Okla- along with National Weather Service (NWS) River homa and Arkansas, with minimal precipitation through Forecast Center (RFC) precipitation estimates (multi- the Texas Panhandle. Maximum rainfall from the sensor stage IV). The observed rainfall isohyets aligned terrain-included simulations was approximately 130 km roughly parallel to the escarpment encompassing FFA. north of observed maxima. The peak value from the The heaviest accumulation was present as a comma-like 3-km domain was 323 mm, which agreed very well with

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FIG. 3. Observed and WRF-simulated rainfall accumulations for the three domains. (a),(d),(g) Observed values (NWS RFC stage IV) for each of the domain areas. (b),(e),(h) Control runs. (c),(f),(i) Terrain-modified simulations. The spatial extent of the middle and inner domains is shown in (a); the Bull Creek watershed location is boxed in (g). the maximum stage IV bin of 315 mm. Considering the simulations placed the areas of heaviest rainfall in dif- relative coarseness of the simulations, WRF terrain- ferent watersheds than were observed. included runs performed well in simulating broad pre- Terrain-removed simulations showed a marked dif- cipitation patterns as well as localized areas of enhanced ference when compared to the terrain-included runs. precipitation along the Balcones Escarpment. However, The simulations were not as effective in capturing the it should be noted that the terrain-included WRF general precipitation patterns as terrain-included runs,

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TABLE 1. WRF Model setup. Figure 4 displays a series of KEWX base reflectivity measurements (0.58 elevation angle) corresponding to Model parameter Configuration GOES infrared imagery times. The radar reflectivity Long- or shortwave radiation Rapid Radiative Transfer images provide a spatiotemporal view of storm motion, Model (GCM) Microphysics WRF single-moment 6-class which serves a central role in extreme accumulations Cumulus parameterization Simplified Arakawa–Schubert (Doswell et al. 1996). The reflectivity images show the Boundary layer Yonsei University scheme development and repeated training of storm cells parameterization along a linear boundary parallel to the escarpment in- Surface layer physics MM5 tersecting Bull Creek. The well-defined, banded struc- Surface physics Noah land surface model ture, along with its persistence, was an important characteristic of the event. A narrow band of reflectivity values greater than 50 dBZ remained over the water- but they did place maximum accumulation values near shed for approximately 4 h. observed maxima. Minimal precipitation across the A heterogeneous network of telemetered rain gauges Texas Panhandle was correctly modeled, while elevated in and around the City of Austin provided point mea- values in Oklahoma and Arkansas were not. In addition, surements for radar bias correction. Several rain gauges while the linear boundary seen in the observed radar used in the bias correction were located within the Bull reflectivity fields (section 3) was modeled correctly in the Creek watershed. Radar correction is based on a local terrain-included runs, the same feature was not repro- bias approach applying a spatially variable ratio of duced in the terrain-removed simulations. The primary gauge to radar accumulations. Variation of bias is dis- difference with the terrain-removed simulations was the tributed over the area on a 6-h window updated in lack of a narrow, elongated area of elevated accumula- 15-min increments. Mean bias corrections across the tions along the Balcones Escarpment. This resulted in entire telemetered network were generally near 1.5 and much lower rainfall totals across the inner domain for below during the 24-h period of maximum rainfall. the terrain-removed simulations. Average precipitation During the 6-h period of maximum rainfall over Bull acrosstheentireinnerdomain(;200 000 km2) was 68, 58, Creek, the mean bias correction was 1.53. Figure 5 shows and 23 mm for observed values, terrain-included runs, and rain gauge values (used in the bias correction) from the terrain-removed runs, respectively. The difference in Lower Colorado River Authority network along with magnitude and location of precipitation between WRF GAR values for the bin holding the gauge. Accumula- simulations suggests terrain may have had an effect in tions at these gauges were within 5%. Additional detail the high rainfall totals across central Texas. Analyses of concerning the construction of the precipitation dataset, multiple storms and additional model output would bias correction methods, and performance during provide a clearer understanding of the escarpment’s Tropical Storm Hermine across the City of Austin is effect on precipitation. provided by Looper and Vieux (2012). b. Rainfall accumulation 3. Rainfall analysis Rainfall totals across the Bull Creek watershed ranged a. Bull Creek precipitation dataset from 230 to 320 mm, with a basinwide average of 292 mm Bull Creek is a 58-km2 semiurbanized catchment on (Fig. 5a). The maximum 24-h basin total on a sliding scale the northern side of Austin. Rainfall estimates across was 275 mm (ending at 1000 UTC 8 September). Maxi- the catchment, as well as model forcing, relied on gauge- mum 1-, 3-, and 6-h basin totals were 58, 124, and 162 mm, adjusted radar (GAR) data provided by the City of respectively (Figs. 3b,c). A basinwide-average hyeto- Austin [from 0500 UTC 7 September to 0500 UTC graph is shown in Fig. 5d. Rainfall isohyets for storm to- 9 September (from 0000 CDT 7 September to 0000 CDT tals were oriented in a north–south manner running 9 September)]. The rainfall data were used by the city as parallel to the general direction of streamflow. The larg- part of an operational flash flood forecasting system. Spatial est accumulations occurred across the western central resolution of radar bins across the study area was approxi- portion of the basin (.300 mm) with rainfall decreasing mately 1 km, with accumulation values recorded in 15-min from west to east. Rainfall totals across the eastern half of increments. The NWS S-band Weather Surveillance Radar- the watershed ranged from 225 to 300 mm. 1988 Doppler (WSR-88D) 80 km south of Bull Creek Winters (2012) calculated 24-h recurrence intervals (station KEWX) provided the reflectivity measurements. for the storm at selected rain gauges across central The radar beam center height (0.58 tilt)isaround1.11km Texas. Several rain gauges across the region experi- (beamwidth 5 1.30 km) over the study area. enced 24-h recurrence intervals of 500 years or greater.

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FIG. 4. Base reflectivity images (dBZ; at 0.58 elevation angle) from NWS KEWX. Times correspond to GOES infrared images in Fig. 2. Outline of Bull Creek watershed is shown.

In the present analysis, we calculate recurrence intervals Areal reduction factors (ARFs) are often used as a for eight durations of 1 day and less following the methods means to reduce the amount of precipitation from a of Asquith (1998). The method employs a regionalization design storm for a point to an effective depth over an approach for the state of Texas utilizing a generalized entire watershed. Using a network of 108 Austin area logistic (GLO) distribution. The storm’s point annual rain gauges (;250 000 daily precipitation values), nonexceedance probability F is estimated by Asquith (1999) calculated a 1-day areal reduction factor of 0.80 for a 58 km2 basin. Since catchment-wide depth 1 5 n o values are available from radar estimates, the ARF in- F k 1/k , (1) 1 1 1 2 [X (F) 2 j] verse was used to transform catchment-wide values to a a d 2 point estimate (hereafter ARF 1 method) for non- j, a, and k are parameters of the GLO distribution esti- exceedance probability calculations. For example, the mated from L moments. Variable j describes the location 24-h point estimate is calculated by multiplying the along the GLO distribution and can be interpreted as a maximum 24-h basinwide accumulation (275 mm) by 2 2 median depth for a given duration. Variables a and the ARF 1 (275 mm 3 0.80 1 5 344 mm). It should k describe the scale and shape of the GLO distribution, be noted the ARF produced by Asquith (1999) is for a respectively, and variable Xd refers to the precipitation 1-day duration event. 2 depth for a given duration. Variable k is dimensionless In addition to the ARF 1 method, point estimates while j, a,andXd have units of inches. Asquith (1998) were also collected from individual radar bin values. For contains isomaps of the state displaying k, j,anda values, radar bin calculations, accumulations were collected which vary by duration and location. from the bin containing the largest depth for a given

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FIG. 5. Bull Creek precipitation accumulation maps for (a) event totals, (b) 6-h max, and (c) 3-h max. (d) A basin- averaged hyetograph is shown along with rain gauge–radar bin (containing rain gauge) comparisons. The location of the two rain gauges shown (d) is indicated in (c). duration (i.e., bin location was allowed to vary). Table 2 areal coverage of the storm was a unique factor. The ra- shows recurrence intervals for a point T [where F 5 1 2 dar bin recurrence intervals provide the most direct 2 (1/T)] from ARF 1 and radar bin methods. means of spatially distributed point estimates, and their The 24-h recurrence interval for a radar bin and maximum recurrence interval neared 500 years, which is catchment to point value was 440 and 692 years, re- consistent with the analysis of rain gauge data by Winters 2 spectively. Recurrence intervals increased monotonically (2012). Recurrence intervals for the ARF 1 method were with duration for both methods. At durations less than much greater than recorded by radar bin or rain gauge 3 h, recurrence intervals were less than 100 years, in- values. This suggests the storm had a broader spatial dicating the importance of storm persistence. Compari- coverage than the data used by Asquith (1999) to arrive son of the two recurrence intervals also suggests the large at the 0.80 ARF for a basin this size. In a critical

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TABLE 2. Recurrence intervals for durations of 1 day and less for factor in the region’s chronic flooding problem (Caran 21 individual radar bins and ARF point estimates. and Baker 1986). While short-duration rates were ele- 2 ARF 1 Recurrence Radar Recurrence vated in the present storm (0.25, 0.5, 1, and 2 h), they Time method interval bin interval were not particularly rare from a recurrence interval (h) (mm) (yr) (mm) (yr) standpoint (,70 years). Figure 6 shows average basin- 21 0.25 19 1 43 30 wide rainfall rates (mm h ) for the event, percent of 0.5 38 3 65 45 precipitation delivered by rainfall rate, and cumulative 172159155frequency plots of maximum intensities for each radar 2 106 27 130 70 bin. Hourly rainfall rates are shown for both 15-min and 3 155 125 157 132 6 203 225 194 180 1-h intervals. The 1-h intensity intervals are calculated 12 270 344 259 286 by summing 15-min intervals at the beginning of each 24 344 692 311 440 hour (00). About 60% of the storm was delivered at 2 basinwide rates exceeding 20 mm h 1. The 15-min in- tensity rates indicate 35% of the precipitation totals fell 2 examination of ARFs, Wright et al. (2014a) indicate at basinwide rates greater than 40 mm h 1. Smith et al. ARFs are not representative of extreme rainfall in part (2000) recorded slightly larger percentages (40%–60%) 2 because of their formulations mixing different storm delivered at 50 mm h 1 in larger flood events along the types. The authors show that rainfall events in North Texas Coastal Plain and Edwards Plateau. Maximum Carolina produced by tropical storms tend to be larger rainfall rates at individual radar bins varied by up to with longer durations than those from organized thun- threefold across Bull Creek, with half of the bins exceeding 2 2 derstorm systems. For Hermine, the ARF suggested by 80 mm h 1 and one-quarter exceeding 100 mm h 1 Asquith (1999) would need to be increased by 10% (0.88) (15-min measurements). to produce a 24-h recurrence interval matching the Roughly 60% (175 mm) of the total rainfall from the maximum from individual radar bin estimates (440 2-day event fell during two intense periods lasting a years). It is worth noting that the 1-day envelope curve combined 5 h. The first period of heavy rainfall occurred for a basin of this size within this region is almost 3 times at 2200–2300 UTC 7 September when basinwide in- 2 the amount experienced (;750 mm; Asquith and tensity values reached approximately 35 mm h 1. Rain- 2 Slade 1995). fall rates at individual radar bins peaked near 80 mm h 1 over this time period. The second period of intense c. Rainfall intensity rainfall was much longer (0230–0630 UTC 8 September) High-intensity rainfall rates characteristic of the and resulted in a large flood wave (discussed below). Edwards Plateau and Balcones Escarpment are a major From 0230 to 0630 UTC precipitation rates averaged

FIG. 6. (a) Event rainfall intensity. (b) Percent of total basinwide accumulation by rainfall rate. (c) Cumulative frequency of max intensity for each individual radar bin. Values are shown using a 15-min and 1-h averaging period.

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FIG. 7. (left) Land use and (right) soil maps for the Bull Creek catchment.

2 2 over 30 mm h 1, with mean values in excess of 50 mm h 1 the northern and eastern region of the catchment, with persisting for an entire hour (0500–0600 UTC). Basin- open lands (mixed forest) occurring through the central 2 wide rates greater than 60 mm h 1 were sustained for half region of the basin. In 2000, population in the basin was an hour (0500–0530 UTC), and peak rates neared estimated at approximately 44 000, with expected in- 2 175 mm h 1 during this time period. creases to near 70 000 by 2030 (City of Austin 2010). The effect of urbanization on stream response to pre- cipitation is unknown. While the traditional belief that 4. Flood hydrology increased urbanization has resulted in flashier streams a. Bull Creek environmental setting across the region has permeated (e.g., Veenhuis and Gannett 1986), Sung and Li (2010) present a contrary The Bull Creek watershed could be viewed as a mi- hypothesis in their analysis of 10 area watersheds in- crocosm for regional flood issues along the Edwards cluding Bull Creek. The authors suggest terraced land- Plateau and Balcones Escarpment. Most, if not all, of the scapes produced through land grading practices during dominant physiographic features resulting in flash flood home construction have suppressed the amount and responses across the region are present in the watershed. timing of surface runoff reaching stream courses. While Soils are primarily Brackett and Tarrant associations their hypotheses were not explicitly tested in the current consisting of thin gravelly clay loam and stony clay soils, work, the study highlights the importance of surface respectively (Fig. 7, right). Both soils have moderately processes in mediating storm response at Bull Creek. low permeability when saturated and are underlain by limestone (beginning at 0–0.5 m in depth) throughout b. GSSHA rainfall–runoff simulations the catchment. Adjacent to stream courses, thicker GSSHA is a fully distributed physically based water- Volente series soils can be found consisting of silty clay shed model with the capability to model the full loam. Vegetation in the undeveloped areas of the wa- tershed consists primarily of scrub oak and Ashe juniper stands. Topography within the basin varies greatly, with TABLE 3. Bull Creek geographic and land-use information. slopes ranging from nearly flat to 30% near the outlet. Basin area 58.2 km2 Table 3 provides some physical details of the basin and Max relief 173 m stream network. Mean slope 6.6% Land use is roughly split evenly between developed Impervious cover (2003 estimate) 13.6% 22 and undeveloped lands (Fig. 7, left). Developed regions Stream density 2.4 km km (mostly single-family residential) primarily occur along Main stem length 17.7 km

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TABLE 4. GSSHA infiltration and overland flow parameters.

Impervious Saturated hydraulic Capillary Manning’s Soil texture and cover conductivity head Effective roughness Retention 2 land use fraction (cm hr 1) (cm) porosity coefficient (mm) Stony clay loam — 0.20 21.85 0.33 — — Silty clay — 0.35 29.22 0.42 — — Gravelly clay loam — 0.35 23.9 0.32 — — Silty clay loam — 0.35 27.3 0.43 — — Single-family residential 0.40 — — — 0.25 5 Multifamily residential 0.60 — — — 0.25 5 Commercial 0.80 — — — 0.09 5 Streets and road 0.99 — — — 0.01 1 Mixed forest 0 — — — 0.19 15 Shrub 0 — — — 0.15 5 Grassland 0 — — — 0.15 5 Water 0 — — — 0.10 5 Wetlands 0 — — — 0.25 5

hydrologic cycle (Downer and Ogden 2004, 2006). Pa- Cleandam algorithm distributed with the GSSHA model. rameters influencing hydrologic response are distributed The USGS gauging station on Bull Creek (USGS across equally sized cells encompassing the watershed. 08154700) served as the outlet. Land-use, land-cover, and Physics-based partial differential equations describing soil type data were obtained from the City of Austin (City runoff processes are solved for each grid cell and chan- of Austin 2014), National Land Cover Dataset (Homer nel reach to route rainfall through the landscape and et al. 2015), and the Natural Resources Conservation Ser- stream network. The model and its earlier form [Cas- vice (Soil Survey 2013), respectively. cade of Planes, Two-Dimensional (CASC2D)] have Infiltration calculations were conducted using Green been used in the analysis of several flooding events and Ampt with redistribution (Ogden and Saghafian across diverse geographic settings (e.g., Ogden et al. 1997) and saturated hydraulic conductivity values pro- 2000; Sharif et al. 2006, 2010a,b, 2013; Chintalapudi et al. vided by Rawls et al. (1983). Saturated hydraulic con- 2012, 2014; Elhassan et al. 2013; Wright et al. 2014b). ductivity for developed soil texture classifications (single Sharif et al. (2010a) used the model to analyze the or multifamily and commercial) were reduced by an effect of varying precipitation inputs and land surface amount proportional to the assumed fraction of imper- features on a smaller storm event in 2004 at Bull Creek. vious cover. Streets were assumed to have infiltration Precipitation totals from the 2004 event ranged from 10 rates near zero. Grid cells were assigned to one of nine to 20 mm across the basin, and peak flows were ap- land-use classes for retention and overland roughness proximately one-quarter the size of the 2010 storm. The parameterization (Fig. 7, left). Table 4 shows surface authors calibrated the model manually and were able to parameters used in the model run. Low-intensity rainfall achieve an RMSE, error in peak, and error in volume of of approximately 20 mm occurred across the basin in the 12.4%, 5.1%, and 1.6%, respectively. The present re- days leading to the event, and initial soil moisture was sults reflect the parameterization from Sharif et al. set at 0.2. The role of initial soil moisture mediating (2010a) with some slight modifications to landscape re- flood response is discussed below. tention. Model setup is briefly described below; how- Stream channels were modeled using irregular cross sec- ever, the reader is asked to refer to Sharif et al. (2010a) tions containing the main channel and flood plain (allowing for a further discussion of model preprocessing. for control of floodplain simulation). Stream cross-sectional data and reach-specific Manning’s roughness coefficient 1) MODEL SETUP values were obtained from a City of Austin HEC-2 Hydrological processes simulated for the event include model. No cross-sectional data were available for the infiltration, landscape retention, overland flow, and stream tributaries and they were simulated as a uniform trape- routing. Evapotranspiration and deep aquifer contribu- zoidal profile. Tributary dimensions along with floodplain tions to streamflow were not included. Model pre- delineation were estimated from lidar data available from processing was conducted using ArcGIS and Aquaveo’s the City of Austin. Routing was calculated using the dif- watershed modeling system. Watershed terrain was fusive wave equation in 1D for streams and 2D for over- constructed from USGS 10-m DEMs filled using the land flow. Sharif et al. (2010a) demonstrated the large

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FIG. 8. GSSHA model output time series. (a) Simulated and observed streamflow. (b) Basinwide-average pre- 2 cipitation and infiltration rates (mm h 1) and soil saturation (%). (c) Basinwide cumulative precipitation and in- 2 filtration (mm). (d) Percent of developed and open areas receiving .20 mm h 1 of rainfall.

rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi effect that stormwater detention facilities in the basin have å 2 2 (1/N) N(esti obsi) on event flows. Major detention facilities were included in 5 5 i 1 the model by disconnecting all or part of the structure RMSE (100), (3) obsmean catchment area if modeled inflows were less than basin capacity.Themodelwasrunona30-mgridwitha5-min where i 5 index denoting individual hydrograph ordi- time step. Errors in peak flow, volume, and RMSE per- nates and N refers to the total number of hydrograph centage were calculated to assess model performance. ordinates. Error in peak flow or volume is expressed as a percentage 2) HYDROLOGIC SIMULATION RESULTS and given by The heavy rainfall over Bull Creek resulted in a large, 2 (jobs 2 estj) steep hydrograph peaking at 510 m3 s 1 in the early Err 5 (100), (2) obs morning hours of 8 September (Fig. 8a). The peak flow was the highest recorded in the gauge’s 34-yr history, 2 where observed (obs) corresponds to measured peak topping the previous high of 388 m3 s 1 in 1982. Peak flow and total volume while estimated (est) indicates flow was about half of the discharge envelope curve for GSSHA results. RMSE is also expressed as a percentage watersheds this size near Austin (Asquith and Slade and given by 1995). Mean stream velocity estimated by Winters

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2 (2012) using the slope area method was 4.1 m s 1. Peak 15-min rainfall accumulations). During the first peak in unit discharge from the contributing areas was estimated precipitation, about 90% of open areas received greater 2 2 2 at 10.97 m3 s 1 km 2 with a runoff ratio of 0.42. The unit than 20 mm h 1 compared to 75% of urban areas discharge was the third highest among 37 area gauging (Fig. 8d). The heaviest rainfall cells were centered over stations analyzed by Winters (2012). Given the soil the western side of the basin in the uplands portion of characteristics and rainfall intensity, it is likely almost all the watershed (Fig. 9a). Mixed forest land use and a of the runoff is generated from infiltration-excess large detention facility draining urban areas received mechanisms. Figure 8a displays the GSSHA-generated much of this rainfall. During the second precipitation hydrograph along with measured flow. The model sim- peak, rainfall was heavy through the central portion of ulated the event very well with error in peak, error in the basin, with the largest 1-h accumulations occurring volume, and RMSE of 2.8%, 3.9%, and 22.1%, re- within a couple of kilometers from the outlet (Fig. 9b). spectively. In their description of a real-time flood This area received lower event totals than other regions forecasting system in Austin, Looper and Vieux (2012) of the basin, but it served a large role in controlling the show similar results for a stage hydrograph. No model timing and shape of the hydrograph. performance results are reported in their work. In their 2010 Bull Creek investigation, Sharif et al. Further insight into the hydrometeorological controls (2010a) note a significant overestimation in peak (80%) on the flood event can be gained through examination and volume (100%) when the mixed forest land-use type of watershed response to the two precipitation peaks is modeled as grassland. The authors attribute this in previously discussed (2200–2300 UTC 7 September; part to the higher retention values for the forest land 0230–0630 UTC 8 September). The first pulse of heavy use. The authors used a retention value of 10 mm precipitation, 34 mm in total, produced only a modest whereas we arrive at 15 mm for the mixed forest land use 2 hydrologic response (from ;3to30m3 s 1). The time (Table 4). To further understand the effects of mixed between the first rainfall peak and the modest local forest surface retention, the event was modeled with discharge maximum was near 3 h, which was equal to the seven different retention values ranging from 0.25 to 2 of overall lag time (defined here as time difference the 15-mm value. To clarify how the changes affect the between peak discharge and the time centroid of basin- initial stream response and peak flows, results are pre- averaged rainfall). The second, larger peak in basin- sented for the initial response (small peak; from averaged precipitation (142 mm) was separated from 1845 UTC 7 September to 0300 UTC 8 September 2010), peak discharge by only 70 min. The second peak in peak flows (large peak; at 0300–0500 UTC 8 September precipitation contained accumulations around 4 times 2010), and the full hydrograph. Figure 10 displays model larger than the first, but stream response was nearly 14 performance statistics shown in Eqs. (1) and (2) for times greater. mixed forest retention perturbations. Figure 8b displays time series of basinwide averages Results indicate retention from this land use has a 2 for soil saturation (%), infiltration rate (mm h 1), and large relative effect in mediating the initial stream re- 2 rainfall rate (mm h 1). Cumulative values for infiltration sponse, but the effects are greatly subdued when ex- and rainfall (mm) are shown in Fig. 8c. The plot in- amining peak flows. The initial, smaller pulse in dicates that, leading up to the first period of enhanced streamflow has a high relative change to retention per- rainfall, infiltrability was high enough to accept nearly turbations, while RMSE and error in peak and volume all of the rainfall. Soils became saturated across the are all within 10% of original modeled values for peak basin after receiving approximately 35 mm prior to the flows and overall hydrograph. The high retention factor onset of the first precipitation peak. Modest overland for this land use may be related to losses to the karstic flow was generated during the first precipitation pulse. landscape. In the nearby Onion Creek basin, Looper During this time, and through the heaviest precipitation, and Vieux (2012) suggest losses to the karstic Edwards basinwide infiltration rates operated at or near saturated Aquifer may be responsible for reduced accuracy in hydraulic conductivity. simulations. There are numerous scattered karst fea- Despite similar soil moisture conditions, the two pe- tures across the area, such as sinkholes and dissolution- riods of rainfall exhibited vastly different flow responses. enhanced fractures, which can provide rapid recharge This can be partially explained by the spatial organiza- (Jones 2003). tion of rainfall along with landscape characteristics. Regardless of the physical mechanism mediating Distributed rainfall intensities were overlaid with land- stream response from the first peak in rainfall, retention use data to calculate percentage of open areas (49% of adjustments to the mixed forest land use had little effect basin) and developed regions (51% of basin) experi- on the accuracy of the overall hydrograph. Several 2 encing rainfall in excess of 20 mm h 1 (estimated from studies indicate land surface details are less important

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FIG. 9. During the two peaks in precipitation, 1-h max accumulations: (a) 2200–2300 UTC 7 Sep and (b) 0430–0530 UTC 8 Sep. The max 1-h accumulation occurs in (b). for extreme events, and accuracy of the hydrograph is swept from a low water crossing. The primary observa- highly dependent upon rainfall representation (e.g., tions and findings from the study are as follows: Andréassian et al. 2004). Chintalapudi et al. (2012) 1) The large-scale MCS was able to develop as a result showed the effect of land cover on hydrologic response of very moist Gulf air meeting a strong boundary of decreases as the size of the rainfall event increases. drier air from the northwest. WRF simulations with Similarly, Sharif et al. (2015) demonstrated that the ef- and without Balcones Escarpment terrain suggest fects of land use on flood peaks are higher for storms geography aided in the increased rainfall pattern with smaller recurrence intervals. To further highlight along FFA. Similar analyses of multiple events would this notion, initial soil moisture was adjusted in a similar provide a better understanding of orographic effects manner to mixed forest retention values (Fig. 10). in the region. The well-defined, narrow rainbands GSSHA and CASC2D simulations have shown high and their persistence were key features that led to sensitivities to initial soil moisture in other studies flooding. (Marsik and Waylen 2006; Senarath et al. 2000). Results 2) The Bull Creek watershed received nearly 300 mm indicate a similar pattern to soil retention perturbations for the event, with 24-h recurrence interval calcula- where initial watershed response shows large relative tions from radar bins indicating a near 500-yr storm. change, but the overall effect on the hydrograph is Recurrence interval calculations less than 3 h in- minimal. dicate events smaller than 100-yr storms, suggesting duration was the major factor in event accumula- tions. Approximately 60% of the total accumulation 5. Summary and conclusions fell during two periods lasting a combined 5 h. An MCS formed from the remnants of Tropical Storm Average intensity rates across the basin were greater 2 Hermine, producing torrential rainfall along a narrow than 50 mm h 1 during maximum 1-h accumulations. swath of central Texas bordering the Balcones Escarp- Peak intensity from individual radar bins neared 2 ment. The system was able to persist through nighttime 175 mm h 1. hours (7–8 September 2010), bringing nearly 300 mm of 3) Streamflow showed a nonlinear response to two rainfall to the 58 km2 Bull Creek watershed in Austin, periods of intense rainfall. This can be partially TX. The storm resulted in the largest flow event in the explained by the spatial organization of rainfall gauge’s 34-yr history. Flooding along the main stem of across the basin along with landscape characteristics. the creek resulted in one vehicular death as the car was Model simulations using various representations of

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FIG. 10. Model performance statistics for small peak, large peak, and full hydrograph under (left) various mixed forest retention and (right) basinwide initial soil saturation representations.

mixed land-use retention and initial soil moisture Asquith, W., 1998: Depth–duration frequency of precipitation for indicate the initial watershed response is quite sen- Texas. USGS Water Resources Investigations Rep. 98-4044, sitive to these parameters. The effect of these 107 pp. [Available online at http://pubs.er.usgs.gov/publication/ wri984044.] parameters on peak streamflow was minimal. ——, 1999: Areal-reduction factors for the precipitation of the 1-day design storm in Texas. USGS Water Resources Investigations Rep. 99-4267, 81 pp. [Available online at http://pubs.er.usgs.gov/ Acknowledgments. This work was partially funded by publication/wri994267.] U.S. Army Corps of Engineers Engineer Research and ——, and R. Slade, 1995: Documented and potential extreme peak discharges and relation between potential extreme peak dis- Development Center Contract W912H2-16-P-0160. The charges and probable maximum flood peak discharges in authors thank Bob Rose, chief meteorologist for the Texas. USGS Water Resources Investigation Rep. 95-4249, 63 Lower Colorado River Authority for his review of pp. [Available online at http://pubs.usgs.gov/wri/1995/4249/ the storm description. In addition, the writers extend report.pdf.] their thanks to three anonymous reviewers for making Avila, L., 2010: Tropical Storm Hermine 5–9 September 2010. Tropical Cyclone Rep., National Hurricane Center, 17 pp. important suggestions that improved the manuscript. [Available online at http://www.nhc.noaa.gov/data/tcr/AL102010_ Hermine.pdf.] Baker, V., 1975: Flood hazards along the Balcones escarpment in REFERENCES central Texas. Geological Circular 75-5, Bureau of Economic Geology, 22 pp. [Available online at http://www.lib.utexas. Andréassian, V., A. Oddos, C. Michel, F. Anctil, C. Perrin, and edu/books/landscapes/publications/txu-oclc-1967634/txu-oclc- C. Loumagne, 2004: Impact of spatial aggregation of inputs 1967634.pdf.] and parameters on the efficiency of rainfall–runoff models: A Caracena, F., and J. Fritsch, 1983: Focusing mechanisms in the theoretical study using chimera watersheds. Water Resour. Texas Hill Country flash floods of 1978. Mon. Wea. Rev., Res., 40, W05209, doi:10.1029/2003WR002854. 111, 2319–2332, doi:10.1175/1520-0493(1983)111,2319: Arndt, D. S., J. B. Basara, R. A. McPherson, B. G. Illston, G. D. FMITTH.2.0.CO;2. McManus, and D. B. Demko, 2009: Observations of the Caran, S. C., and V. Baker, 1986: Flooding along the Balcones overland reintensification of Tropical Storm Erin (2007). Escarpment, Central Texas. The Balcones Escarpment, Cen- Bull. Amer. Meteor. Soc., 90, 1079–1093, doi:10.1175/ tral Texas. P. Abbot and C. Woodruff, Eds., Geological Soci- 2009BAMS2644.1. ety of America, 1–14.

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