Effective prediction of localized flash flood regions for an approaching rainfall event requires an in-depth knowledge of the land surface and stream characteristics of the forecast area. Flash Flood Guidance (FFG) is currently formulated once or twice a day at the county level by River Forecast Centers (RFC) in the U.S. using modeling systems that contain coarse, generalized land and stream characteristics and hydrologic runoff techniques that often are not calibrated for the forecast region of a given National Weather Service (NWS) office. This research investigates the application of embedded geographic information systems (GIS) modeling techniques to generate a localized flash flood model for individual small watersheds at a five minute scale and tests the model using historical case storms to determine its accuracy in the FFG process. This model applies the Soil Conservation Service (SCS) curve number (CN) method and synthetic dimensionless unit hydrograph (UH), and Muskingum stream routing modeling technique to formulate flood characteristics and rapid update FFG for the study area of interest. The end result of this study is a GIS-based Flash Flood Forecasting system for ungaged small watersheds within a study area of the Blacksburg NWS forecast region. This system can then be used by forecasters to assess which watersheds are at higher risk for flooding, how much additional rainfall would be needed to initiate flooding, and when the streams of that region will overflow their banks. Results show that embedding these procedures into GIS is possible and utilizing the GIS interface can be helpful in FFG analysis, but uncertainty in CN and soil moisture can be problematic in effectively simulating the rainfall-runoff process at this greatly enhanced spatial and temporal scale. / Master of Science

Compared with other types of floods, timely and accurately predicting flash floods is particularly challenging due to the small spatiotemporal scales in which the hydrologic and hydraulic processes tend to develop, and to the short lead time between the causative event and the inundation scenario. With continuous increased availability of data and computational power, the interest in applying techniques based on machine learning for hydrologic purposes in the context of operational forecasting has also been increasing. The primary goal of the research activities developed in the context of this thesis is to explore the use of emerging machine learning techniques for enhancing flash flood forecasting. The studies presented start with a review on the state-of-the-art of documented forecasting systems suitable for flash floods, followed by an assessment of the potential of using multiple concurrent precipitation estimates for early prediction of high-discharge scenarios in a flashy catchment. Then, the problem of rapidly producing realistic highresolution flood inundation maps is explored through the use of hybrid machine learning models based on Non-linear AutoRegressive with eXogenous inputs (NARX) and SelfOrganizing Maps (SOM) structures as surrogates of a 2D hydraulic model. In this context, the use of k-fold ensemble is proposed and evaluated as an approach for estimating uncertainties related to the surrogating of a physics-based model. The results indicate that, in a small and flashy catchment, the abstract nature of data processing in machine learning models benefits from the presentation of multiple concurrent precipitation products to perform rainfall-runoff simulations when compared to the business-as-usual single-precipitation approach. Also, it was found that the hybrid NARX-SOM models, previously explored for slowly developing flood scenarios, present acceptable performances for surrogating high-resolution models in rapidly evolving inundation events for the production of both deterministic and probabilistic inundation maps in which uncertainties are adequately estimated. / Thesis / Doctor of Science (PhD) / Flash floods are among the most hazardous and impactful environmental disasters faced by different societies across the globe. The timely adoption of mitigation actions by decision makers and response teams is particularly challenging due to the rapid development of such events after (or even during) the occurrence of an intense rainfall. The short time interval available for response teams imposes a constraint for the direct use of computationally demanding components in real-time forecasting chains. Examples of such are high-resolution 2D hydraulic models based on physics laws, which are capable to produce valuable flood inundation maps dynamically. This research explores the potential of using machine learning models to reproduce the behavior of hydraulic models designed to simulate the evolution of flood inundation maps in a configuration suitable for operational flash flood forecasting application. Contributions of this thesis include (1) a comprehensive literature review on the recent advances and approaches adopted in operational flash flood forecasting systems with the identification and the highlighting of the main research gaps on this topic, (2) the identification of evidences that machine learning models have the potential to identify patterns in multiple quantitative precipitation estimates from different sources for enhancing the performance of rainfall-runoff estimation in urban catchments prone to flash floods, (3) the assessment that hybrid data driven structures based on self-organizing maps (SOM) and nonlinear autoregressive with exogenous inputs (NARX), originally proposed for large scale and slow-developing flood scenarios, can be successfully applied on flashy catchments, and (4) the proposal of using k-folding ensemble as a technique to produce probabilistic flood inundation forecasts in which the uncertainty inherent to the surrogating step is represented.

Masters Research - Master of Science / Recent flash floods and landslides in the Philippines have caused many fatalities, loss of livelihoods; destroyed infrastructures, damaged natural resources and displaced several communities. Investigation of five disaster cases of flash floods and landslides from 1991 to 2006 was undertaken to gain an understanding of the causes, behaviour, distribution and biophysical impacts of these recurrent natural hazards. Sustaining healthy and resilient communities and protecting the ecosystem from natural disasters is a key development goal. Therefore, communities at risk need to adequately prepare for, respond to, and recover from the impacts of these natural disasters. A theory model on community resilience called the Landslip-Disaster Quadrant Model was developed to examine the capacity for resilience and the vulnerability of threatened communities. Six building blocks comprise this Model. A community study of the February 17, 2006 landslides in St. Bernard, Southern Leyte, was conducted to test and refine this Model. Major findings of the study have revealed that flash floods and landslides have been frequent due to changing climatic patterns and greater interaction of natural processes. Extreme weather conditions have resulted in intense rainfall that seeps through fractures and cracks in the ground. Rains saturate and loosen soil particles, weaken slope resistance, triggering landslides that formed natural dams. Failure of these natural dams or log jams caused flash floods and debris flows. The rapidity and destructiveness of these hazards were influenced by the angular position of sliding materials, slope resistance, type of cascading materials caught in the flow, river channel configuration, and human structures that obstruct and/or intensify overflow. These were the physical conditions of vulnerability to disasters in the five cases of natural disaster investigated. Rural livelihoods and the economic base of the local people in Saint Bernard, Southern Leyte, were limited and subsistent. Though the local people have a high literacy rate, they have inadequate understanding of the natural processes associated with landslides. Natural observations such as receding water levels in the river, fractures and cracks in the ground on the mountain, excessive rains and landslides in nearby communities could have been used as early warnings by the local people and authorities for safe evacuation. Many lives in Guinsaugon village could have thus been saved from the deadly landslides of 17 February 2006. Political interests have affected progress of resettlement housing and development projects that obliged many local people to extend the period spent living in the evacuation centres. However, the local people were expressive of their faith and hope to rise from the tragedy. These ‘bouncing back’ attitudes of the local people were indicative of their strong cultural values that formed the core of their coping capacity for natural disasters. The results of the community study tested and refined the Landslip-Disaster Quadrant Model. Among the six blocks for building a disaster-resilient community, cultural values and local norms ranked first. This is followed by ecological security, then livelihood sufficiency and economic base, and further by human health and wellness. The last two blocks were structural networks and institutional arrangements, and political will and priorities. This Model could form the framework for a Comprehensive Landslide and Flash Flood Disaster Risk Assessment in the Philippines. The community assessment toolkit developed in this study could be expanded further into policy and planning guidelines of the National Disaster Coordinating Council of the Philippines.

Masters Research - Master of Science / Recent flash floods and landslides in the Philippines have caused many fatalities, loss of livelihoods; destroyed infrastructures, damaged natural resources and displaced several communities. Investigation of five disaster cases of flash floods and landslides from 1991 to 2006 was undertaken to gain an understanding of the causes, behaviour, distribution and biophysical impacts of these recurrent natural hazards. Sustaining healthy and resilient communities and protecting the ecosystem from natural disasters is a key development goal. Therefore, communities at risk need to adequately prepare for, respond to, and recover from the impacts of these natural disasters. A theory model on community resilience called the Landslip-Disaster Quadrant Model was developed to examine the capacity for resilience and the vulnerability of threatened communities. Six building blocks comprise this Model. A community study of the February 17, 2006 landslides in St. Bernard, Southern Leyte, was conducted to test and refine this Model. Major findings of the study have revealed that flash floods and landslides have been frequent due to changing climatic patterns and greater interaction of natural processes. Extreme weather conditions have resulted in intense rainfall that seeps through fractures and cracks in the ground. Rains saturate and loosen soil particles, weaken slope resistance, triggering landslides that formed natural dams. Failure of these natural dams or log jams caused flash floods and debris flows. The rapidity and destructiveness of these hazards were influenced by the angular position of sliding materials, slope resistance, type of cascading materials caught in the flow, river channel configuration, and human structures that obstruct and/or intensify overflow. These were the physical conditions of vulnerability to disasters in the five cases of natural disaster investigated. Rural livelihoods and the economic base of the local people in Saint Bernard, Southern Leyte, were limited and subsistent. Though the local people have a high literacy rate, they have inadequate understanding of the natural processes associated with landslides. Natural observations such as receding water levels in the river, fractures and cracks in the ground on the mountain, excessive rains and landslides in nearby communities could have been used as early warnings by the local people and authorities for safe evacuation. Many lives in Guinsaugon village could have thus been saved from the deadly landslides of 17 February 2006. Political interests have affected progress of resettlement housing and development projects that obliged many local people to extend the period spent living in the evacuation centres. However, the local people were expressive of their faith and hope to rise from the tragedy. These ‘bouncing back’ attitudes of the local people were indicative of their strong cultural values that formed the core of their coping capacity for natural disasters. The results of the community study tested and refined the Landslip-Disaster Quadrant Model. Among the six blocks for building a disaster-resilient community, cultural values and local norms ranked first. This is followed by ecological security, then livelihood sufficiency and economic base, and further by human health and wellness. The last two blocks were structural networks and institutional arrangements, and political will and priorities. This Model could form the framework for a Comprehensive Landslide and Flash Flood Disaster Risk Assessment in the Philippines. The community assessment toolkit developed in this study could be expanded further into policy and planning guidelines of the National Disaster Coordinating Council of the Philippines.

Yes / This paper reviews and discusses the recent studies of natural flood management (NFM) and its associated microbial risks in the UK and suggests set of numerical modelling approaches for their respective investigation. This study details the importance of precise numerical representation of the NFM to flood inundations and microbial risks caused by NFM measures. Possible future numerical advancements of the numerical modelling for the NFM and microbial activities are also discussed here.

The North American Monsoon System (NAMS) is a significant weather and climate phenomenon that brings critical rainfall to the southwestern United States and northwestern Mexico. As a result of the North American Monsoon Experiment, and research efforts surrounding the field campaign, the understanding of the NAMS has increased considerably over the last 15 years. In addition questions concerning potential flash flood causing mechanisms of the NAMS have not been thoroughly investigated. This dissertation is comprised of two papers that collectively address the aspects of the literary understanding of the NAMS as we know it today and conduct an investigation into the complex interactions between various weather systems that may influence the NAMS. In the first paper, a review of the major research of the NAMS literature since the last comprehensive review 15 years ago is conducted. The results of his review are assessed for where our understanding has been improved and where future research needs to be guided for purposes of the second paper. Based upon the results from the literature review, the second paper focuses on identification of inverted troughs and gulf surges based upon lower- and mid-level atmospheric parameters for purposes of assessing the impacts on National Weather Service Storm Report flash flood dates. This research contributes to the synthesis of the current knowledge of the NAMS in general and to the specific regional impacts that do occur during periods of heavy precipitation over the NAMS region for purposes of improving meteorological predictability of flash flooding. The results can (1) gauge our understanding of the NAMS literature to date and (2) improve meteorological forecasts through the recognition of synoptic and sub-synoptic patterns related to the NAMS that are most likely to cause flash floods.

Anticiper les inondations constitue un enjeu majeur pour les communes exposées aux crues car c’est sur cette anticipation que repose l’ensemble de la chaîne d’alerte, garante de la sécurité des personnes et des biens. Si un système de suivi du risque de dommages liés aux crues est disponible pour un cinquième du réseau hydrographique français, les petits cours d’eau composant les quatre cinquièmes restants ne font pas partie du dispositif de suivi temps réel du ministère en charge de l’écologie, appelé « Vigicrues ». Or il s’agit également des cours d’eau les plus concernés par le phénomène de crues rapides, pour lesquelles l’anticipation joue un rôle crucial en gestion de crise. Voilà pourquoi début 2017, Vigicrues a été complété par un service automatique d'avertissement des crues appelé Vigicrues Flash. Ce système permet de fournir en temps réel une information sur l’intensité de la crue des cours d’eau pour 10 000 communes françaises.Même si ce nouveau service constitue un réel progrès pour les communes jusqu’alors dépourvues de système d’anticipation, la méthode AIGA qui constitue le cœur de Vigicrues Flash possède certaines limites. L’une d’entre elles, est le fait que la méthode n’avertit que sur le niveau de rareté de la crue, sans tenir compte des enjeux présents. Or, pour générer un avertissement efficace, il est nécessaire de prendre en compte les conséquences potentielles de cette crue. Cette thèse a donc pour but de permettre l’estimation anticipée des dommages liés aux crues rapides, en particulier sur les bassins non jaugés. Pour cela, nous proposons une méthode d’estimation du risque de dommages fondée d’une part sur la qualification de l’intensité de l’aléa crue par la méthode AIGA et d’autre part sur la prise en compte de la vulnérabilité du territoire. Cette dernière a été construite à partir d’une approche bottom-up innovante, directement auprès de gestionnaires du risque. Le croisement de ces deux types d’informations a permis de fournir une première caractérisation du risque de dommages liés aux inondations sous la forme d’un indice de risque dynamique.En adaptant des tests de performances issus de la météorologie, nous avons pu évaluer notre indice par rapport à la méthode AIGA seule. Des informations sur les dommages déjà existantes (les arrêtés « CATNAT » issus de la BD GASPAR) ou spécifiquement collectées (la BD DamaGIS constituée pour cette thèse à partir d’informations présentes notamment sur les réseaux sociaux) constituent nos données de validation. Notre évaluation a porté sur 12 communes dans les Alpes-Maritimes, 69 dans le Gard et 28 dans le Var, et s’est faite de deux manières complémentaires : d’une part une évaluation en continue et exhaustive à partir des arrêtes CATNAT pris pour nos communes sur toute la période 1998-2016 ; et d’autre part une évaluation événementielle, mais à l’échelle infra-communale.Nos résultats montrent que le passage de la caractérisation de l’aléa à celle du risque améliore nettement la pertinence des avertissements émis, surtout à l’échelle infra-communale. Les dommages y sont mieux détectés, avec un taux moindre de fausse alertes. Cette thèse ouvre donc de réelles perspectives d’amélioration de la chaîne de l’alerte actuelle, permettant de mieux organiser la réponse des services de secours et de gestion de crise face à l’annonce de dommages potentiels liés aux crues rapides. / Anticipating floods is a major challenge for communities at risk of flooding as the entire warning system – responsible for the safety of people and goods - relies on this anticipation. There is an existing monitoring system “Vigicrues” for flood damage for a fifth of the river network in France. But for four-fifths of this network, made of small rivers, no monitoring is available. Yet those rivers are the most affected by flash floods which especially require anticipation for crisis management purposes. This is why at the beginning of 2017, the Vigicrues system for flood monitoring has been completed with a new flood warning system called Vigicrues Flash. This system provides automatic information in real-time on flood severity of ungauged basins for 10 000 French communities.Even if this new system is a real innovation for communities with no monitoring at all, the AIGA method which is used in Vigicrues-Flash has some limits. The first one is that the warnings are only based on the assessment of flood severity. But estimating flood severity is not enough to issue efficient flood warnings. To be able to do so, taking into account potential flood losses is essential. The main goal of this work is to enable an anticipated estimation of flood related damage, especially for ungauged basins. We offer a method to assess the risk of flood related damage based on flood severity assessed by the AIGA method and a territorial vulnerability assessment. This last one has been built on a bottom-up approach developed with crisis managers. Putting together this data has enabled a first assessment of the risk of flood risk damage as a dynamic risk index.By adjusting performance testing used in the meteorology field, we have been able to evaluate our risk index and to compare the results with the AIGA method. In order to do so, we have used existing damage data (CATNAT from the GASPAR database) as well as a specific multisource database (using notably social media data) which has been put together as part of this study (DamaGIS). The evaluation process has been tested for 12 communities in the Alpes-Maritimes, 69 in the Gard and 28 in the Var department. Two types of evaluation have been performed: a first comprehensive one continuously with CATNAT data on the 1988-2016 period; and another one per flood event at a finer scale.Our results show that moving from hazard assessment to risk assessment has significantly increased the relevance of the warnings and mostly at a smaller scale than the community one. Though, there is a better detection of flood related damage as the false alarm rate has been significantly reduced. This PhD work offers promising prospects to improve the current French warning system for floods and enable a more efficient emergency response.

Submitted by Leonardo Lima (leonardoperlim@gmail.com) on 2017-04-05T15:34:01Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) RUTZ, Elenice Crochemore.pdf: 8517082 bytes, checksum: 78a4d5508f644839d8d952e481a630f9 (MD5) / Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2017-04-25T19:18:09Z (GMT) No. of bitstreams: 2 RUTZ, Elenice Crochemore.pdf: 8517082 bytes, checksum: 78a4d5508f644839d8d952e481a630f9 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2017-04-25T19:21:38Z (GMT) No. of bitstreams: 2 RUTZ, Elenice Crochemore.pdf: 8517082 bytes, checksum: 78a4d5508f644839d8d952e481a630f9 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-04-25T19:21:48Z (GMT). No. of bitstreams: 2 RUTZ, Elenice Crochemore.pdf: 8517082 bytes, checksum: 78a4d5508f644839d8d952e481a630f9 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2015-09-28 / Sem bolsa / A pesquisa aborda as consequências das fortes precipitações que aconteceram em Pelotas o que levou a ocorrência de uma grande enxurrada em 28 e 29 de janeiro de 2009. O recorte espacial da pesquisa é a bacia hidrográfica do Arroio Quilombo, Pelotas/RS, localizada em sua maior parte na zona rural de Pelotas e uma pequena área no município de Canguçu e outra pequena área no Município de Arroio do Padre. O recorte temporal é do inicio do século XX até o ano de 2009, data da enxurrada que atingiu a bacia hidrográfica do Arroio Quilombo (BHAQ), deixando consequências bastante significativas. As enxurradas podem ser consideradas como um desastre natural, tanto pela sua intensidade, quanto pelas suas consequências. Nesse sentido o referencial teórico trata da questão dos desastres naturais, a fim de se compreender alguns conceitos que geram certa confusão, é o caso dos termos: enxurradas, enchentes, inundações e alagamentos. Nesse sentido a revisão teórica que se apresenta, vem em busca de sanar esses e outros conceitos. Sendo assim, essa pesquisa tem como objetivos: Compreender os fatores que levaram à ocorrência da enxurrada de 28 e 29 de janeiro de 2009 na BHAQ, bem como as transformações geomorfológicas consequentes; Realizar uma revisão teórica sobre a temática dos desastres naturais, geomorfologia, transformações geomorfológicas, uso e cobertura da terra, enxurradas e as suas consequências; Realizar um resgate histórico das inundações no município de Pelotas, bem como um breve histórico das enxurradas na Bacia Hidrográfica do Arroio Quilombo; Realizar um estudo morfométrico da Bacia do Arroio Quilombo; Verificar o uso e cobertura da terra na BHAQ; Investigar sobre as transformações da paisagem após as inundações na bacia hidrográfica do Arroio Quilombo e Identificar e mapear as consequências geomorfológicas e os danos ao patrimônio provocados pelas cheias de 2009. A pesquisa mostrou que a enxurrada de 2009 não foi o único evento de grande intensidade a atingir a bacia do Arroio Quilombo. Porém, a bacia hidrográfica do Arroio Quilombo não apresenta condicionante a enxurradas, e que a enxurrada de 2009 não ocorreu em toda bacia, porém atingiu de forma intensa a baixa bacia do Arroio Quilombo, deixando algumas consequências como perdas de animais, de lavoura, materiais e infraestruturais. As entrevistas realizadas mostraram que as alterações geomorfológicas mais significativas ocorreram fora dos limites da BHAQ. / This research addresses the consequences of heavy rainfall that occurred in Pelotas, which led to a great flash flood on the 28th and 29th January 2009. The area of research is the Quilombo Creek Watershed, Pelotas municipality, in the State of Rio Grande do Sul. Most of the Watershed is located in the rural zone of the Pelotas municipality, but also has a small section in the Canguçu municipality and another small section in the Arroio do Padre municipality. The time frame starts at the beginning of the twentieth century until 2009, when the flash flood hit the Quilombo Creek Watershed, leaving very significant consequences. Flash floods can be considered as a natural disaster, both for their intensity and their consequences. Thus, the theoretical background deals with the issue of natural disasters in order to understand some flood concepts that frequently create confusion in Portuguese: “enxurradas”, “enchentes”, “inundações” and “alagamentos”. This way the presented theoretical background tries to solve this confusion and other conceptual problems. This research has the following objectives: understand the factors that triggered the flash flood of the 28th and 29th January 2009 in the Quilombo Creek Watershed, as well as the consequent geomorphological changes; expose a theoretical background about natural disasters, geomorphology, geomorphological changes, land use and land cover, flashfloods and their consequences; carry out a historical review of the floods in the Pelotas municipality as well as a historical review of the floods in the Quilombo Creek Watershed; carry out a morphometrical study of the Quilombo Creek Watershed; observe the land use and land cover in the studied area; study the landscape changes and identify the damage done to the patrimony in the area of study after the 28th and 29th January flash flood. This research shows that the 2009 flash flood was not the only high intensity event to touch the Quilombo Creek Watershed. However, the studied watershed does not present natural conditions that would trigger flash floods, and the 2009 flash flood does not affect the entire Watershed in the same way. It intensely hit the lower part of the watershed creating consequences such as animal loss, land crop loss and material loss. The interviews showed that the most significant geomorphological changes occurred outside the boundaries of the studied watershed.

abstract: Severe weather affects many regions of the United States, and has potential to greatly impact many facets of society. This study provides a climatological spatial analysis by county of severe weather warnings issued by the National Weather Service (NWS) between January 1st, 1986 to December 31st, 2017 for the contiguous United States. The severe weather warnings were issued for county-based flash flood, severe thunderstorm, and tornado phenomena issued through the study period and region. Post 2002 severe weather warnings issued by storm warning area were included in this study in the form of county-based warnings simultaneously issued for each affected county. Past studies have researched severe weather warnings issued by the NWS, however these studies are limited in geographic representation, study period, and focused on population bias. A spatial analysis of severe weather warning occurrences by county identify that (a) highest occurrences of flash flood warnings are located in the desert Southwest and Texas, (b) severe thunderstorm warning occurrence is more frequent in Arizona, portions of the Midwest, the South, and the Mid and South Atlantic states, (c) the tornado activity regions of Tornado Alley and Dixie Alley (i.e. Colorado, Kansas, Oklahoma, Arkansas, Texas, Louisiana, Mississippi, Alabama, Tennessee, and Illinois) contained the highest occurrences of tornado warnings, and (d) the highest instances of aggregate warning occurrences are found in the desert Southwest, the Midwest, and the Southern regions of the United States. Generally, severe weather warning “hot spots” tend to be located in those same regions, with greater coverage. This study concludes with a comparison of local maxima and general hot spot regions to expected regions for each phenomenon. Implications of this study are far reaching, including emergency management, and has potential to reduce risk of life. / Dissertation/Thesis / Masters Thesis Geography 2019

Distributed models of the land surface are essential for global climate models because of the importance of land-atmosphere exchanges of water, energy, momentum. They are also used for high resolution hydrologic simulation because of the need to capture non-linear responses to spatially variable inputs. Continued improvements to these models, and the data which they use, is especially important given ongoing changes in climate and land cover. In hydrologic models, important aspects are sometimes neglected due to the need to simplify the models for operational simulation. For example, operational flash flood models do not consider the role of snow and are often lumped (i.e. do not discretize a watershed into multiple units, and so do not fully consider the effect of intense, localized rainstorms). To address this deficiency, an overland flow model is coupled with a subsurface flow model to create a distributed flash flood forecasting system that can simulate flash floods that involve rain on snow. The model is intended for operational use, and there are extensive algorithms to incorporate high-resolution hydrometeorologic data, to assist in the calibration of the models, and to run the model in real time. A second study, which is designed to improve snow simulation in forested environments, demonstrates the importance of explicitly representing a near canopy environment in snow models, instead of only representing open and canopy covered areas (i.e. with % canopy fraction), as is often done. Our modeling, which uses canopy structure information from Aerial Laser Survey Mapping at 1 meter resolution, suggests that areas near trees have more net snow water input than surrounding areas because of the lack of snow interception, shading by the trees, and the effects of wind. In addition, the greatest discrepancy between our model simulations that explicitly represent forest structure and those that do not occur in areas with more canopy edges. In addition, two value-added Land Cover products (land cover type and maximum green vegetation fraction; MGVF) are developed and evaluated. The new products are good successors to current generation land cover products that are used in global models (many of which rely on 20 year old AVHRR land cover data from a single year) because they are based on 10 years of recent MODIS data. There is substantial spurious interannual variability in the MODIS land cover type data, and the MGVF product can vary substantially from year to year depending on climate conditions, suggesting the importance of using climatologies for land cover data. The new land cover type climatology also agrees better with validation sites, and the MGVF climatology is more consistent with other measures of vegetation (e.g. Leaf Area Index) than the older land cover data.