Stephen G. McLin Mark E. Van Eeckhout Everett P. Springer Leonard J. Lane

Transcription

1 LA-UR Approved for pubic reease distribution is unimited. Tite: A CHARACTERIZATION METHODOLOGY FOR POST-WILDFIRE FLOOD HAZARD ASSESSMENTS Author(s): Stephen G. McLin Mark E. Van Eeckhout Everett P. Springer Leonard J. Lane Submitted to: Internationa Congress on Modeing and Simuation MODSIM 2001, December 2001 The Austraian Nationa University Canberra, Austraia Los Aamos Nationa Laboratory, an affirmative action/equa opportunity empoyer, is operated by the University of Caifornia for the U.S. Department of Energy under contract W-7405-ENG-36. y acceptance of this artice, the pubisher recognizes that the U.S. Government retains a nonexcusive, royatyfree icense to pubish or reproduce the pubished form of this contribution, or to aow others to do so, for U.S. Government purposes. Los Aamos Nationa Laboratory requests that the pubisher identify this artice as work performed under the auspices of the U.S. Department of Energy. Los Aamos Nationa Laboratory strongy supports academic freedom and a researcher's right to pubish as an institution, however, the Laboratory does not endorse the viewpoint of a pubication or guarantee its technica correctness. FORM 836 (10/96)

2 A Characterization Methodoogy for Post-Widfire Food Hazard Assessments S.G. McLin a, M.E. Van Eeckhout a, E.P. Springer a, and L.J. Lane b a Los Aamos Nationa Laboratory, Los Aamos, NM, 87545, USA (sgm@an.gov) b Southwest Watershed Research Center, USDA, ARS, 2000 E. Aen Rd, Tucson, AZ, 85719, USA Abstract: A combined GIS-HEC modeing appication for foodpain anaysis of pre- and post-burned watersheds is described. The burned study area is ocated on Pajarito Pateau near Los Aamos, New Mexico (USA), where the Cerro Grande Widfire burned 17,353 ha (42,878 ac) in May This area is dominated by rugged mountains that are dissected by numerous steep canyons having both ephemera and perennia channe reaches. Vegetation consists of pinon-juniper woodands ocated between 1,829-2,134 m (6,000-7,000 ft) above mean sea eve (m MSL), and Ponderosa pine stands between 2,134-3,048 m MSL (7,000-10,000 ft). Approximatey seventeen percent of the burned area is ocated within Los Aamos Nationa Laboratory, and the remainder is ocated in upstream or adjacent watersheds. Pre-burn foodpains were previousy mapped in using eary HEC modes as part of the RCRA/HSWA permitting process. Numerous recording precipitation and stream gages have aso been instaed. These data provide essentia information characterizing rainfa-runoff reationships before and after the fire. They are aso being used to monitor spatia and tempora changes as forest recovery progresses. Post-burn changes in HEC-HMS predicted rainfa-runoff patterns are reated to changes in watershed vegetation cover and hydrophobic soi conditions. Stream channe cross-sectiona geometries were extracted from 0.3 m (1 ft) DEM data using ArcView GIS. Then foodpoo topwidths, depths, and fow veocities were remapped using the HEC-RAS mode. Finay, numerous surveyed channe sections were seectivey made at crucia sites for mode verification. Direct comparisons are made between aternative data acquisition and mapping techniques. Keywords: DEM GIS HEC-HMS HEC-RAS Foodpain Modeing 1. INTRODUCTION Los Aamos Nationa Laboratory (the Laboratory) was estabished in 1943 as a nationa research and deveopment faciity. It is ocated (35 52 N, W) in north-centra New Mexico (USA) about 97 km (60 mies) north-northeast of Abuquerque, and 40 km (25 mies) northwest of Santa Fe (Figure 1). Los Aamos has a semiarid, temperate mountain cimate. This 111-square km (43 square mie) faciity is situated on Pajarito Pateau between the Jemez Mountains on the west and the Rio Grande Vaey to the east. The Pateau sopes east-southeast for more than 24 channe km (15 mies), where it terminates aong the Rio Grande in White Rock Canyon. Topography ranges from 2,377 m (7,800 ft) above mean sea eve (m MSL) aong the western Laboratory margin to about 1,951 m MSL (6,400 ft) at the canyon rim. The Pateau is dissected by a system of gaged and ungaged watersheds that are dominated by ephemera stream drainage. Here we define a gaged watershed as one having at east one rain gage (input) and one stream gage (output) so that the system response can be estimated [Dooge, 1959, 1973]. Some perennia channe reaches are aso ocay defined. A of these watersheds are eongated in the west-to-east fow direction aong Pajarito Pateau, and are extremey narrow in the north-south direction. A tota, there are 13 separate watersheds draining Laboratory ands that contain over 161 channe km (100 mies) requiring foodpain identification. These foodpains are defined at approximatey 61 m (200 ft) intervas using topographic data obtained from a 0.3 m (1 ft) gridded digita eevation mode (DEM). These data were obtained from a 1992 aeria photogrammetric survey of the Laboratory and surrounding areas.

3 The Cerro Grande widfire began as a US Nationa Park Service prescribed burn on May 4, It quicky spread out of contro because of high winds and extremey dry conditions. The fire was contained on June 6, 2000, after consuming approximatey 17,353 ha (42,878 ac), incuding 3,010 ha (7,439 ac) within the Laboratory. The fire continued to burn inside the containment ine throughout Juy as seen in Figure 1. In 1990 the Laboratory became a permitted hazardous waste treatment, storage, and disposa faciity. Permit conditions stipuate that a Resource Conservation and Recovery Act (RCRA) faciities must deineate 100-year foodpain eevations within their boundaries [40 CFR (b)(11)(iii)]. These foodpains were originay mapped [McLin, 1992] using the US Army Corps of Engineers (USACE) Hydroogic Engineering Center (HEC) computer-based Food Hydrograph Package (HEC-1) and the Water Surface Profies Package (HEC-2). These techniques are we-documented and routiney used for foodpain anayses [Hoggan, 1996]. Updated mode versions [USACE, 2001a, 2001b] now incude HEC-HMS (Hydroogic Modeing System) and HEC-RAS (River Anaysis System). A foodpain boundaries are being remapped foowing the Cerro Grande widfire because they have expanded. These changes are in direct response to fire-reated modifications in the rainfa-runoff process due to reductions in watershed vegetation cover and deveopment of hydrophobic soi conditions. As the forest around the Laboratory recovers over the next severa decades, these foodpain boundaries are expected to recede sowy back toward their pre-fire boundaries at some undetermined rate. 2. HEC-HMS RAINFALL-RUNOFF MODEL HEC-HMS is a singe event, rainfa-runoff mode that can be used to simuate rea or hypothetica storm hydrographs in gaged or ungaged watersheds in response to user specified rainfa hyetographs [USACE, 2001a]. This mode was used to forecast both pre- and post-burn fooding impacts associated with the Cerro Grande widfire [McLin et a., 2001]. Output from the mode incudes the design storm hydrograph for individua subbasins. Hydrograph peaks are then utiized in the HEC- RAS mode as input data to predict foodpain boundaries. Map Area 2 km 2 mi cartography by A. Kron 7/31/01 Santa Fe Abuquerque NEW MEXICO AZ UT CO NM OK TX USA Approximate urn Severity High Moderate Low VALLES CALDERA NAT'L PRESERVE SANTA CLARA PUELO NAT'L FOREST LOS ALAMOS TOWNSITE INDIAN LANDS ANDELIER NAT'L MONUMENT DOE- LANL LOS ALAMOS NAT'L LA Figure 1. Location map of Los Aamos showing Cerro Grande widfire burn area. NAT'L FOREST NAT'L FOREST LOS ALAMOS NAT'L LA Figs. 3 and 4 Fig. 5

4 HEC-HMS can utiize five different unit hydrographs (UH) to simuate runoff. The SCS UH and SCS rainfa abstraction oss rate [SCS, 1993] were seected in this study to characterize the reationship between rainfa-runoff and peak discharge. The Muskingum method was seected to route computed food fows through downstream subbasins because channe osses and food-wave attenuation in individua watersheds have not been fuy characterized. Hence these osses were assumed to be zero even though they are known to be reativey high in certain pre-fire stream channe reaches (e.g., those channe reaches with reativey thick auvia deposits). Muskingum routing parameters were computed from average channe fow veocities using Manning's equation. In addition, eve-poo reservoir routing was seected to move water through road cuverts with high embankments and for food detention structures. Pre-fire SCS curve numbers (CN) were determined for a watersheds [McLin, 1992] and formed a starting point for post-fire simuations. These prefire CN vaues typicay ranged from the mid-50s and 60s for wooded apine forests, to 70s and 80s for mountain brush and pinon-juniper woodands. These vaues were originay obtained using a quasi-mode caibration procedure for ungaged watersheds [McLin et a., 2001]. The post-fire CN vaues were initiay modified from origina vaues using weighting factors based on the percent of subbasin areas that were burned. These burned areas were subdivided into ow (57% of tota burn area), medium (8% of tota), and high (34% of tota) severity burned areas as defined by the US Forest Service s urned Area Emergency Rehabiitation team [AER, 2000]. This cassification is quaitativey inked to changes in soi texture and infitration capacity. High burn severity areas are ocated in those areas where the surficia soi structure has been atered. These sois typicay have a hydrophobic ayer that was formed during the fire. This ayer is ocated approximatey 6.4 mm (0.25 in) beow the surface and is between 6.4 to 76 mm (0.25 to 3.0 in) thick. These hydrophobic sois deveop when high temperature fires produce heavy voatie organics that migrate into sois and condense [Imeson et a., 1992 Dekker and Ritsema, 1994]. For the Cerro Grande widfire, these hydrophobic sois are preferentiay ocated on north-facing canyon sopes with heavy ponderosa pine forests. They occur on approximatey 22% of the tota burn area. Medium severity burn areas show itte or no hydrophobicity and are concentrated on southfacing canyon sopes with sparser vegetation, on mesa tops, and in canyon bottoms. Low severity burn areas are generay ocated aong the perimeter of more severey burned areas. This hydrophobic soi distribution is reated to the distribution of fues, temperature, and heavy winds during the fire. Post-fire CN vaues of 65, 85, and 90 were assigned to the ow, medium, and high severity burn areas, respectivey. Unburned areas retained their origina pre-fire CN vaues. A composite CN vaue was then computed for each subbasin using four burn severity weight factors and four estimated CN vaues. These weight factors were computed according to the fraction of burned area within each subbasin area (i.e., unburned, ow, medium, or high severity). Each respective weight factor was mutipied by each respective CN vaue and the resuts were summed to obtain the composite CN vaue. Detais of the HEC-HMS simuations are described in McLin et a. [2001]. 3. HEC-RAS FLOODPLAIN MAPPING For the modeing efforts described here, stream channe cross-sections at varying ocations were obtained from the Laboratory's computer-based graphica information system (ArcView GIS). For this study, cross-sections are ocated approximatey every 61 m (200 ft) aong each reach. Topographic data are automaticay extracted from a trianguated irreguar network (TIN) that is created from the DEM database. This procedure minimizes channe-surveying tasks. The data extraction process is performed for each cross-section foowing the pre-seected channe reach pathway. Each point aong the cross-section forms an (x, y, z) topographic point that is geo-referenced to the New Mexico State Pane coordinate system. A typica 30 m (100 ft) ong cross section contains between 15 and 50 data points. These crosssectiona features are exported to the HEC-RAS mode using HEC-geoRAS, an ArcView extension capabiity deveoped by the USACE-HEC. In order to verify this data extraction process, approximatey 1% of a channe sections were surveyed using a network of precision benchmarks. Differences between 51 surveyed and DEM owpoint eevations from channe sections are shown in Figure 2. These eevation differences (i.e., surveyed minus DEM eevations for identica points) are normay distributed and appear random. They have a mean difference of 0.34 m (1.11 ft) and a standard deviation of 0.64 m (2.11 ft). These differences range from m (5.92 ft) to 1.19 m ( 3.89 ft). The affect of these

5 Norma Probabiity Pot the instaation of an upstream food contro structure and (3) interpretative hand smoothing of the foodpoo. Probabiity Eevation Difference (m) Figure 2. Probabiity pot of eevation differences. Figure 5 shows a second channe reach with pronounced anguar and discontinuous foodpoos. These irreguar features are a resut of the ArcView GIS representation of the imported HEC-RAS foodpoo. Note that the origina HEC-RAS crosssections and foodpoo topwidths are preserved in the hand-smoothed representation of the foodpain. The ArcView GIS foodpoo is created from rasterized data computed from the intersection of the and and water surface TINs. eevation differences on the foodpoo mapping process is presenty unknown. The independenty executed HEC-RAS mode empoys a HEC-HMS hydrograph peak to simuate a water surface eevation at each channe section using a steady, graduay varied fow approximation. Here the water surface eevation is computed as a function of channe distance using an iterative standard-step method [USACE, 2001b]. The mode computes a pair of eft and right overbank foodpoo coordinates for each section that identifies where the DEM and surface and computed foodpoo intersect. Coordinate pairs from adjacent channe sections are imported back into ArcView GIS and inked together using the geo-referenced New Mexico State Pane coordinate system. These inked coordinates define the foodpain over the entire channe reach. Parameter estimation procedures and construction of input data fies for pre- and post-fire conditions are described by McLin et a. [2001]. The idea of merging HEC-RAS modeing capabiities with ArcView mapping and geographic features is appeaing because surveying requirements can be seectivey minimized. This is especiay important if the foodpain mapping area is extensive. However, severa factors can affect the fina shape of the foodpain as iustrated beow. Figure 3 shows the 100-yr, 6-hr HEC-RAS foodpain after being imported back into the ArcView database. Note that the foodpoo appears somewhat anguar and discontinuous. Figure 4 shows the same ocation after interpretative hand smoothing of the foodpoo. Dramatic differences are obvious and can be attributed to the foowing: (1) ocaized channe modifications made between mode simuations represented by each figure (2) reductions in hydrograph peaks associated with 4. DISCUSSION AND CONCLUSIONS The successfu integration of modern GIS databases and hydroogic modes is an emerging technoogy [Maidment and Djokic, 2000]. Most federa, and many State, faciities aready have significant GIS topographic coverage. This paper describes an appication of HEC-HMS and HEC- RAS foodpain modes to compex terrain using ArcView GIS extracted topographic data. These modes are recognized by the EPA, USACE, and others as the best avaiabe technoogy for foodpain definition in ungaged watersheds. Combining these modes with a GIS capabiity represents a refinement in their continued use. However, the resuts presented here suggest that the ArcView GIS foodpoo-mapping agorithm may need some refinement. The SCS curve number method was used in this study to predict runoff. The reative merits of this empirica approach versus physicay based representations have been openy debated in the iterature for years. However, Loague and Freeze [1985] have shown that physicay based modes generay do not predict runoff any better than the reativey simpe approach used here. In addition, extension of physica modes to ungaged watersheds retains many imitations of simpe approaches. Furthermore, the SCS method has the advantage that future changes in and use patterns (e.g., pre- and post-fire watershed aterations or urbanization) are easiy addressed. Finay, the eevation differences between surveyed and DEM points shown in Figure 2 are worrisome. The impication is that excessive foodpain modeing errors may be inadvertenty introduced into an aready uncertain rainfa-runoff process. Error quantification addressing this issue is currenty underway.

6 FT FT Threemie POTRILLO ROAD Canyon ft 1/4 mi 400 m Map source: LANL GISLab G /26/01 Modified by: cartography by A. Kron 7/30/01 MESITA DEL UEY ROAD PAJARITO ROAD PAJARITO CANYON CANYON Pre-dam 100-yr foodpoo uiding/structure Paved road Dirt road Cross section ocation Contour interva 20 ft Figure 3. ArcView foodpain map for Area FT FT Threemie POTRILLO ROAD PAJARITO Canyon ft 1/4 mi 400 m Map source: LANL GISLab G /26/01 Modified by: cartography by A. Kron 7/30/01 MESITA DEL UEY ROAD CANYON PAJARITO ROAD Post-dam 100-yr foodpoo uiding/structure Paved road Dirt road Cross section ocation Contour interva 20 ft Figure 4. Smoothed foodpain map for Area 1.

7 6600 PAJARITO CANYON Cañada de uey Cañada de ue y ArcView 100-yr foodpoo Smoothed 100-yr foodpoo uiding/structure Paved road Dirt road Cross section ocation Contour interva 20 ft 6500 Potrio Canyon Canyon O CANYON PAJARITO ROAD 1/2 mi 3000 ft 1 km Map source: LANL GISLab G /26/01 Modified by: cartography by A. Kron 7/31/ WHITE ROCK 4 Figure 5. ArcView and smoothed foodpain map for Area ACKNOWLEDGEMENTS This work was funded by the Environment, Safety, and Heath Division and the Faciities and Waste Operations Division at Los Aamos Nationa Laboratory through Post-Fire Emergency Response funds. 6. REFERENCES AER, urned Area Emergency Rehabiitation Pan for Cerro Grande Fire, see US Forest Service web site, Dekker, L.W., and C.J. Ritsema, How water moves in a water repeent sandy soi. 1. Potentia and actua water repeency, Water Resources Research, 30(9), , Dooge, J.C.I., A genera theory of the unit hydrograph, Journa of Geophysica Research, 64(1), , Dooge, J.C.I., Linear theory of hydroogica systems, USDA Agricutura Research Service, Technica uetin No. 1468, US Government Printing Office, Washington, DC, , Hoggan, D.H., Computer-Assisted Foodpain Hydroogy and Hydrauics, McGraw-Hi, 676 pp., New York, Imeson, A.C., J.M. Verstraten, E.J. van Muigen, and J. Sevink, The effects of fire and water repeency on infitration and runoff under Mediterranean type forest, Catena, 19, , Loague, K.M., and R.A. Freeze, A comparison of rainfa-runoff modeing techniques for sma upand catchments, Water Resources Research, 21(2), , Maidment, D., and D. Djokic, Hydroogic and Hydrauic Modeing Support with Geographic Information Systems, Environmenta Systems Research Institute Press, 216 pp., Redands, CA, McLin, S.G., Deineation of 100-year foodpain eevations at Los Aamos Nationa Laboratory, Los Aamos Nationa Laboratory, report LA MS, 51 pp., Los Aamos, NM, McLin, S.G., E.P. Springer, and L.J. Lane, Predicting foodpain boundary changes foowing the Cerro Grande widfire, Hydroogica Processes, 15(15), in press SCS, Nationa Engineering Handbook, USDA Soi Conservation Service, Section 4, Hydroogy (NEH-4), US Government Printing Office, Washington, DC, US Army Corps of Engineers (USACE), HEC- HMS Hydroogic Modeing System, User s Manua for Version 2.11, Report CPD-74A, Hydroogic Engineering Center, Davis, CA, 2001a. US Army Corps of Engineers (USACE), HEC-RAS River Anaysis System, User s Manua for version 3.0, Report CPD-68, Hydroogic Engineering Center, Davis, CA, 2001b.