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Book Spatially Modeling Snowmelt Using Intra annual Patterns with Remote Sensing in the Upper Snake River Basin

Download or read book Spatially Modeling Snowmelt Using Intra annual Patterns with Remote Sensing in the Upper Snake River Basin written by Craig D. Woodruff and published by . This book was released on 2018 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Snowmelt represents an important component of the hydrologic cycle with implications for water managers. In this research we assess the applicability of intra-annual patterns for use in spatially modeling snowmelt. This is done through remote sensing which offers daily imagery of the watershed for the time period between 2000 and 2018. This thesis assesses the applicability of intra-annual patterns and develops two spatial models describing snow extent changes throughout a melting season. In the first chapter we identify whether a pattern exists using spatial statistics and spatial comparisons. This fundamental step is the foundation for developing a model. We then address a critical assumption in the second chapter. Modeling the snowmelt progression is often done with depletion curves. We use narrowed error bounds to fit a curve, which solidifies our choice of curve to represent melt. This curve can be used to represent any snowmelt season. It is called a dimensionless curve and can be applied to any year. The heart of this research is developing a spatial model which combines years of spatial data to describe the melting patterns. This is accomplished in chapter 3 with a principal component analysis. The model developed uses information from 2000 through 2016. It is applied to the snowmelt seasons of 2017 and 2018 to verify the spatial accuracy. The final chapter creates another spatial model using a fundamentally different statistical approach. Not only are the results very similar using these two methods, but both can be accomplished quickly. This opens the door to further research into the widespread use of this type of model. Applications of both spatial models are real-time modeling, climate change modeling, cloud removal, and producing spatially distributed information in ungauged watersheds.

Book Hydrological Snowmelt Modelling in Snow Covered River Basins by Means of Geographic Information System and Remote Sensing

Download or read book Hydrological Snowmelt Modelling in Snow Covered River Basins by Means of Geographic Information System and Remote Sensing written by Houshang Behrawan and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In mountainous watersheds snow melt can have a significant impact on the water balance and at certain times of the year it could be the most important contribution to runoff. In many parts of the world snow act as natural reservoirs that can play an important role for water supply. Alas, despite its importance, many of snow driven basins suffer from a lack of hydrological infrastructure and equipment so they cannot be described adequately in terms of snow hydrological dynamics. Because of limited accessibility are the few observation stations in such areas very rarely located in the higher elevations but are concentrated mostly in the middle and low elevation resulting in an underrepresentation in data availability of the high altitudes which are important for the process dynamics. Thus the modelling of snow hydrological dynamics in mountainous regions such as the Latyan catchment is often difficult. Reasons for this are in addition to the aforementioned data availability, topographic effects and gradients that can make a spatial interpolation of the input data and the model states a complicated task. Especially in semi-arid regions, high-altitude headwater basins with a significant snow component have a large potential by balancing and distributing scarce water resources ...

Book Hydrological Snowmelt Modelling in Snow Covered River Basins by Means of Geographic Information System and Remote Sensing

Download or read book Hydrological Snowmelt Modelling in Snow Covered River Basins by Means of Geographic Information System and Remote Sensing written by Houshang Behrawan and published by . This book was released on 2010 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Snow and Glacier Melt Runoff Modeling Using Remote Sensing and GIS

Download or read book Snow and Glacier Melt Runoff Modeling Using Remote Sensing and GIS written by Gopinadh Rongali and published by . This book was released on 2023-01-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: As we know, snow is one of the forms of precipitation; however, hydrologist treats it differently due to the temporal difference between the time of its fall and the time of its runoff, groundwater recharge, and the fact that it is a part of various hydrological processes. The hydrological point of view in relation with the snow is mostly considered in middle to high latitudes and mountainous regions, where often melt period sometimes lasts for months following seasonal accumulation of snowpack. During this accumulation period, there is a very small amount or no snow melt. Precipitation (sometimes rain) falls and is temporarily retained as snowpack until the melt season starts. It is mandatory for the hydrology to record how much amount of water is collected in a basin in the form of snow. For a better knowledge of the hydrology of mountainous terrain, detailed assessment of the areal distribution of snow, its quality, and the presence of liquid water in it is also necessary. All of these snow indications are difficult to quantify and measure, and they will most certainly differ from one location to the next. Remote sensing (RS) provides a new tool for obtaining snow data for predicting snow and glacier melt runoff. Researchers have manually collected snow data manually through snow- related courses, which are labor-intensive, expensive, and potentially dangerous. Even when accessible, snow course data represents simply a location in the region and can only be used as an index of the available snow water content. Despite the fact that measurements are considered automated, the difficulty of a single point measurement or observation of snow being typical of a broader area or basin persists. It is one of the most easily identifiable forms of water resources utilising aerial photography or satellite imaging in the case of remotely sensed snow data. Satellite systems can currently only determine the area covered by snow, the depth of the snow, and the snow water equivalent; physical snow parameters cannot be monitored directly by these satellite systems. The considerable amount of freshwater has been present in the nature in snow and glacier form in the River basins which are, in most of the cases, located in high mountainous areas. Many other water resources like lakes, Rivers, streams etc. are fed by the outflow of water from these glaciers. The estimated glacier area in the world has about 14.9 x 10⁶ km2, which is approximately 10% of the overall land area present on the earth (Singh and Singh, 2001). Although just 3% of this snow is scattered over mountainous regions on many continents and even beyond the polar regions, it serves a critical role in delivering water to the majority of the world's population. It has been observed that the Himalayan mountains have a big contribution in freshwater supply globally. Major Rivers present in south Asia certainly originate from the Himalayan mountain systems. Among them, the Ganga, Indus, and Brahmaputra are said to be the lifeline of the Indian sub-continent. Snow and glacier melt runoff also contribute to the Himalayan Rivers flow.

Book Physically Based Point Snowmelt Modeling and Its Distribution in Euphrates Basin

Download or read book Physically Based Point Snowmelt Modeling and Its Distribution in Euphrates Basin written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Since snowmelt runoff is important in the mountainous parts of the world, substantial efforts have been made to develop snowmelt models with many different levels of complexity to simulate the processes at the ground, within the snow, and at the interface with the atmosphere. The land-atmosphere interactions and processing influencing heat transfer to and from a snowpack are largely variable and the conceptual representation of this temporal and spatial variability is difficult. A physically based, two layer point model, is applied to calculate the energy and mass balance of snowmelt in the Upper Karasu Basin, eastern part of Turkey during 2002-2004 snow seasons. The climate data are provided from automated weather stations installed and upgraded to collect quantitative and qualitative data with automated transfer. Each form of energy transfer is evaluated to understand the key processes that have major impact on the snow simulation during accumulation and ablation in two-hourly timesteps. The model performance is evaluated as accurate according to the results, compared with observed snow water equivalents, snow depth and lysimeter runoff yield. In the second part, calculated snowmelt values based on energy and mass balance at the automated stations are related to radiation index model through regression. Then, the spatial patterns of snow water equivalent, solar illumination, albedo and air temperature are used to predict the melt at each grid cell over the whole watershed. The results of distributed model application are evaluated in terms of snow covered area of satellite products, observed snow water equivalent at points through snow pillows and discharge values at the outlet runoff station.

Book Spatially Averaged Physics of the Snowmelt Process

Download or read book Spatially Averaged Physics of the Snowmelt Process written by Federico Ernesto Horne and published by . This book was released on 1993 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Estimation of Snow Parameters Based on Passive Microwave Remote Sensing and Meteorological Information

Download or read book Estimation of Snow Parameters Based on Passive Microwave Remote Sensing and Meteorological Information written by National Aeronautics and Space Administration (NASA) and published by Createspace Independent Publishing Platform. This book was released on 2018-07-02 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: A method to incorporate passive microwave remote sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of Snow Water Equivalent (SWE) as a function of time is implemented. The passive microwave remote sensing measurements are at 25 km resolution. However, in mountain regions the spatial variability of SWE over a 25 km footprint is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1 km resolution. In our work, the snow hydrology SWE estimates are updated and corrected using SSM/I passive microwave remote sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOTEL sites in and near the basin. The results indicate that the method incorporating the remote sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time. Tsang, Leung and Hwang, Jenq-Neng Unspecified Center NAGw-4251...

Book Dust and Black Carbon Radiative Forcing Controls on Snowmelt in the Colorado River Basin

Download or read book Dust and Black Carbon Radiative Forcing Controls on Snowmelt in the Colorado River Basin written by Sara McKenzie Skiles and published by . This book was released on 2014 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Light absorbing impurities (LAIs), like dust and black carbon (BC), initiate powerful albedo feedbacks when deposited on snow cover, yet due to a scarcity of observations radiative forcing by LAIs is often neglected, or poorly constrained, in climate and hydrological models. This has important consequences for regions like the Colorado River Basin, where dust deposition to mountain snow cover frequently occurs in the upper basin in the springtime, a relatively new phenomenon since western expansion of the US. Previous work showed that dust on snow (DOS) enhances snowmelt by 3-7 weeks, shifts timing and intensity of runoff, and reduces total water yield. Here, advanced methods are presented to measure, model, and monitor DOS in the hydrologically sensitive Colorado River Basin. A multi-year multi-site spatial variability analysis indicates the heaviest dust loading comes from point sources in the southern Colorado Plateau, but also shows that lower levels of dust loading from diffuse sources still advances melt by 3-4 weeks. A high-resolution snow property dataset, including vertically resolved measurements of snow optical grain size and dust/BC concentrations, confirms that impurity layers remain in the layer in which they are deposited and converge at the surface as snow melts: influencing snow properties, rapidly reducing snow albedo, and increasing snowmelt rates. The optical properties of deposited impurities, which are mainly dust, are determined using an inversion technique from measurements of hemispherical reflectance and particle size distributions. Using updated optical properties in the snow+aerosols radiative transfer model SNICAR improves snow albedo modeling over a more general dust characterization, reducing errors by 50% across the full range of snow reflectance. Radiative forcing by LAIs in the CRB, estimated directly from measurements and updated optical properties, is most strongly controlled by dust concentrations in the uppermost surface layer, as dust comprises 99%+ of the impurity mixture, and therefore, dominates absorption. Coupling the physically based snow model SNOWPACK, modified to track dust layers, to SNICAR, simulates the impacts of DOS radiative forcing on snow properties. This improved understanding, and representation, of DOS processes has important implications for assessing regional impacts of LAIs, for representing LAIs in climate and hydrologic models, for remote sensing of these processes.

Book Investigating the Annual Water Balance of a High altitude Watershed Using Near real Time Lidar Data Integration Into a Physically Based Snowmelt Model

Download or read book Investigating the Annual Water Balance of a High altitude Watershed Using Near real Time Lidar Data Integration Into a Physically Based Snowmelt Model written by Andrew R. Hedrick and published by . This book was released on 2018 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Knowledge of the amount of water stored in the mountain snowpack is crucial for flood prevention, drought mitigation, and energy production in the Western United States. In modeling terms, the most important component of the hydrologic water balance is the precipitation input to the system. Determining where and how much precipitation falls in mountain catchments, however, is the most difficult problem with regards to closing the water balance. The work presented in this dissertation details the modeling portion of the NASA Airborne Snow Observatory (ASO) using the iSnobal physically based snow model. This combination of remote sensing and modeling at 50 m resolution provides the most accurate quasi-operational estimates of snow distribution ever produced over a mountain basin. The first chapter supplies the background and motivation for undertaking this dissertation and presents a brief introduction to the following chapters. Chapter 2 describes the methods used for periodically inserting the ASO-derived snow depths into iSnobal over a consecutive four-year period (2013-2016) in the Tuolumne River Basin in California's Sierra Nevada. Chapter 3 provides a background for how the forcing data for our modeling approach was derived in near-real time and addresses the problem of reproducibility in the hydrologic sciences. Chapter 4 examines the water balance over the Tuolumne Basin using ASO-derived snow depth updates to iSnobal in three very dissimilar water years (2015-2017). For validation of the modeled evapotranspiration using the water balance approach, we use an independent satellite-derived estimate of annual evapotranspiration and show that the basin runoff efficiency is related to total precipitation input for each year. Finally, Chapter 5 presents a summary of the previous chapters and provides a direction for moving the research detailed in this dissertation forward. The combined results of these studies will help usher in a shift toward more wide-spread use of physics-based models for operational predictions of water storage and runoff."--Boise State University ScholarWorks.

Book Forecasting Snowmelt Runoff in the Upper Midwest

Download or read book Forecasting Snowmelt Runoff in the Upper Midwest written by Arthur F. Pabst and published by . This book was released on 1973 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Modeling Elevation Dependent Snow Sensitivity to Climate Warming in the Data Sparse Eastern Oregon Cascades

Download or read book Modeling Elevation Dependent Snow Sensitivity to Climate Warming in the Data Sparse Eastern Oregon Cascades written by Matthew Guy Cooper and published by . This book was released on 2015 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the mountains of the Western US, shifts in the timing and magnitude of snow water equivalent (SWE) over the past century are well documented and attributed to climate warming, but the magnitude of sensitivity depends on elevation. We modeled the spatial distribution of SWE and its sensitivity to climate warming in the 1500 km2 Upper Deschutes River Basin, Oregon, with a spatially distributed snowpack energy balance model forced by a gridded meteorological dataset. The forcing data, gridded at a spatial scale of 1/16°, were downscaled to a 100 m spatial-scale digital elevation model using two sets of temperature lapse rates, with and without bias-correction applied prior to downscaling. The bias-correction method adjusted the spatial patterns of temperature and precipitation in the 1/16° gridded data to match 30 arcsecond Parameter Regressions on Independent Slopes Model (PRISM) climate data. During production, the 1/16° temperature data was adjusted for the effect of elevation using a spatially uniform and temporally constant 6.5°C km−1 lapse rate, whereas PRISM adjusts temperature for the effect of elevation using spatially and temporally variable lapse rates that are computed directly from regional weather station data. Thus, bias-correction implicitly adjusted the lapse rates in the 1/16° gridded data to match measured lapse rates. To test the effect of this implicit adjustment of the input data lapse rates vs. adjusting the lapse rates during downscaling, the 30 arcsecond bias-corrected data and 1/16o original data were each downscaled with 1) a spatially uniform and temporally constant 6.5°C km−1 lapse rate, and 2) with monthly varying lapse rates computed from PRISM. Precipitation was downscaled with the same method for each case. This procedure produced four sets of 100 m spatial scale data used as input to the snow model. Model parameters that control empirical estimates of incoming irradiance and the partitioning of precipitation into rain and snow were estimated independently with each dataset to optimize the agreement between modeled and observed SWE. We then modeled the sensitivity (percent change) of basin SWE in response to +2°C and +4°C warming with each of the four downscaled datasets and their respective optimized parameters. Pre-calibration, modeled SWE for the historical climate period differed depending on bias correction and choice of downscaling lapse rates. Post-calibration, modeled SWE for the historical climate period did not differ depending on choice of lapse rates but substantial differences emerged between modeled SWE with the original and bias-corrected forcing data. Inter-forcing dataset differences in modeled SWE during the historical period were largely controlled by differences in estimates of longwave irradiance and temperature between datasets. For the warming scenarios, the SWE sensitivity differed significantly at all elevations between the bias-corrected and original data, but (as in the post-calibration historical period) did not depend on choice of lapse rates. At low to mid elevations, climate change impacts on snow were largely controlled by temperature-driven shifts from snowfall to rainfall, while at high elevations, precipitation variability controlled SWE sensitivity. With just a 2°C increase in temperature, peak snow accumulation occurred 20-30 days earlier and was 20-60% smaller, the length of the snow covered season decreased up to 50 days, and winter rainfall increased by 20-60%. With a 4°C increase, the shifts in timing were roughly doubled and the declines in snow and snowfall increased up to 80%. A 10% increase in precipitation had a negligible impact on basin-integrated declines, indicating that future precipitation variability has little chance of offsetting regional climate warming impacts on snow in the Oregon Cascades. These results highlight the challenges of modeling SWE in data sparse regions, the importance of bias correcting gridded meteorological forcing datasets for hydrologic modeling applications in regions of complex topography, and the strong temperature dependence of snow in the Oregon Cascades.

Book Principles of Snow Hydrology

Download or read book Principles of Snow Hydrology written by David R. DeWalle and published by . This book was released on 2008-01-01 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: