Simulations of energy balance components at snow-dominated montane watershed by land surface models (original) (raw)
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Journal of Geophysical Research, 1994
A generalization of the single soil layer variable infiltration capacity (VIC) land surface hydrological model previously implemented in the Geophysical Fluid Dynamics Laboratory general circulation model (GClVO is described. The new model is comprised of a two-layer characterization of the soil column, and uses an aerodynamic representation of the latent and sensible heat fluxes at the land surface. The infiltration algorithm for the upper layer is essentially the same as for the single layer VIC model, while the lower layer drainage formulation is of the form previously implemented in the Max-Planck-Institut GCM. The model partitions the area of interest (e.g., grid cell) into multiple land surface cover types; for each land cover type the fraction of roots in the upper and lower zone is specified. Evapotranspiration consists of three components: canopy evaporation, evaporation from bare soils, and transpiration, which is represented using a canopy and architectural resistance formulation. Once the latent heat flux has been computed, the surface energy balance is iterated to solve for the land surface temperature at each time step. The model was tested using long-term hydrologic and climatological data for Kings Creek, Kansas to estimate and validate the hydrological parameters, and surface flux data from three First International Satellite Land Surface Climatology Project Field Experiment intensive field campaigns in the summer-fall of 1987 to validate the surface energy fluxes.
Hydrology and Earth System Sciences, 2015
Evapotranspiration (ET) is the main link between the natural water cycle and the land surface energy budget. Therefore water-balance and energy-balance approaches are two of the main methodologies for modelling this process. The water-balance approach is usually implemented as a complex, distributed hydrological model, while the energybalance approach is often used with remotely sensed observations of, for example, the land surface temperature (LST) and the state of the vegetation. In this study we compare the catchment-scale output of two remote sensing models based on the two-source energy-balance (TSEB) scheme, against a hydrological model, MIKE SHE, calibrated over the Skjern river catchment in western Denmark. The three models utilize different primary inputs to estimate ET (LST from different satellites in the case of remote sensing models and modelled soil moisture and heat flux in the case of the MIKE SHE ET module). However, all three of them use the same ancillary data (meteorological measurements, land cover type and leaf area index, etc.) and produce output at similar spatial resolution (1 km for the TSEB models, 500 m for MIKE SHE). The comparison is performed on the spatial patterns of the fluxes present within the catchment area as well as on temporal patterns on the whole catchment scale in 8-year long time series. The results show that the spatial patterns of latent heat flux produced by the remote sensing models are more similar to each other than to the fluxes produced by MIKE SHE. The temporal patterns produced by the remote sensing and hydrological models are quite highly correlated (r ≈ 0.8). This indicates potential benefits to the hydrological modelling community of integrating spatial information derived through remote sensing methodology (contained in the ET maps derived with the energy-balance models, satellite based LST or another source) into the hydrological models. How this could be achieved and how to evaluate the improvements, or lack of thereof, is still an open research question.
A spatially distributed energy balance snowmelt model for application in mountain basins
Hydrological Processes, 1999
Snowmelt is the principal source for soil moisture, groundwater recharge , and stream-¯ow in mountainous regions of the western US, Canada, and other similar regions of the world. Information on the timing, magnitude, and contributing area of melt under variable or changing climate conditions is required for successful water and resource management. A coupled energy and mass-balance model ISNOBAL is used to simulate the development and melting of the seasonal snowcover in several mountain basins in California, Idaho, and Utah. Simulations are done over basins varying from 1 to 2500 km 2 , with simulation periods varying from a few days for the smallest basin, Emerald Lake watershed in California, to multiple snow seasons for the Park City area in Utah. The model is driven by topographically corrected estimates of radiation, temperature, humidity, wind, and precipitation. Simulation results in all basins closely match independently measured snow water equivalent, snow depth, or runo during both the development and depletion of the snowcover. Spatially distributed estimates of snow deposition and melt allow us to better understand the interaction between topographic structure, climate, and moisture availability in mountain basins of the western US. Application of topographically distributed models such as this will lead to improved water resource and watershed management.
2013
The aim of the present work is to investigate the ability of a physically-based land surface model (LSM) SWAP, which treats energy and water exchange at the land-atmosphere interface, to simulate snow and runoff formation processes in mountainous and high latitude regions. Two regions characterised by different climatic conditions were selected for this study: the French Alps and pan-Arctic river basins located in Russia. In the first case, the results of snow depth simulations by SWAP were compared with daily snow depth measured during three years at 24 mountainous sites (with the altitudes varying from 910 to 2590 m). In the second case, snow depth and river runoff simulated by SWAP for several northern river basins on a long-term basis were validated against daily observations conducted during 20-30 years. It was concluded that, in general, SWAP can capture evolution of snowpack depth and runoff hydrographs and performs fairly well statistically.
Journal of Hydrometeorology, 2004
In the Pacific Northwest (PNW), concern about the impacts of climate and land cover change on water resources and flood-generating processes emphasizes the need for a mechanistic understanding of the interactions between forest canopies and hydrologic processes. Detailed measurements during the 1999 and 2000 hydrologic years were used to modify the Simultaneous Heat and Water (SHAW) model for application in forested systems. Major changes to the model include improved representation of rainfall interception and stomatal conductance dynamics. The model was developed for the 1999 hydrologic year and tested for the 2000 hydrologic year without modification of the site parameters. The model effectively simulated throughfall, soil water content profiles, and shallow soil temperatures for both years. The largest discrepancies between soil moisture and temperature were observed during periods of discontinuous snow cover due to spatial variability that was not explicitly simulated by the model. Soil warming at bare locations was delayed until most of the snow cover ablated because of the large heat sink associated with the residual snow patches. During the summer, simulated transpiration decreased from a maximum monthly mean of 2.2 mm day Ϫ1 in July to 1.3 mm day Ϫ1 in September as a result of decreasing soil moisture and declining net radiation. The results indicate that a relatively simple representation of the vegetation canopy can accurately simulate seasonal hydrologic fluxes in this environment, except during periods of discontinuous snow cover.
Hydrological Processes, 2006
The USGS Precipitation Runoff Modeling System (PRMS) hydrologic model was used to evaluate experimental, gridded, 1-km 2 snow covered area (SCA) and snow water equivalent (SWE) products for two headwater basins in the Rio Grande and Salt River drainages in the Southwestern United States. The SCA product was the fraction of each 1-km 2 pixel covered by snow and was derived from NOAA Advanced Very High Resolution Radiometer imagery. The SWE product was developed by multiplying the SCA product by SWE estimates interpolated from National Resources Conservation Service Snow Telemetry (SNOTEL) point measurements for a six-year period (1995-2000). Measured SCA and SWE estimates were consistently lower than values estimated from temperature and precipitation within PRMS. Differences between modeled and measured snow were different for the accumulation period vs. the ablation period and had an elevational signature. Greatest difference occurred in the relatively complex terrain of the Grande, as opposed to the Black where differences were small. Assimilating the measured snow fields into a version of PRMS calibrated to achieve water balance without assimilation reduced model performance, i.e. modeled streamflow, because this effectively removed water from the basins. Incorporating observed SCA and SWE will require either model recalibration, an averaging strategy for modeled versus observed quantities, or adjustments to water balance accounting at each time step assimilation occurs in order to maintain water balance across the snowmelt season.
The Tibetan Plateau (TP) is the highest plateau in the world, playing an essential role in Asian monsoon development and concurrent water and energy cycles. In this study, the Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM) was calibrated and used to simulate water and energy cycles in a central TP watershed during the summer season. The model was first calibrated at a point scale (BJ site). The simulation results show that the model can successfully reproduce energy fluxes and soil surface temperature with acceptable accuracies. The model was further calibrated at basin scale, using observed discharges in summer 1998 and the entire year of 1999. The model successfully reproduced discharges near the basin outlet (Nash-Sutcliffe efficiency coefficients 0.60 and 0.62 in 1998 and 1999, respectively). Finally, the model was validated using MODIS land surface temperature (LST) data and measured soil water content (SWC) at 15 points within the watershed in 2010. The simulation results show that the model successfully reproduced the spatial pattern and LST means in both nighttime and daytime. Furthermore, the model can generally reproduce 15-site averaged SWC in four soil layers, with small bias error and root mean square error. Despite the absence of long-term discharge data for model verification, we validated it using MODIS LST and measured SWC data. This showed that the WEB-DHM has the potential for use in poorly gauged or ungauged areas such as the TP. This could improve understanding of water and energy cycles in these areas.
Can. J. Remote Sensing, 2008
Net primary productivity (NPP) is a key component of the terrestrial carbon cycle and is important in ecological, watershed, and forest management studies, and more broadly in global climate change research. Determining the relative importance and magnitude of uncertainty of NPP model inputs is important for proper carbon reporting over larger areas and time periods. This paper presents a systematic evaluation of the boreal ecosystem productivity simulator (BEPS) model in mountainous terrain using an established montane forest test site in Kananaskis, Alberta, in the Canadian Rocky Mountains. Model runs were based on forest (land cover, leaf area index (LAI), biomass) and climate-water inputs (solar radiation, temperature, precipitation, humidity, soil water holding capacity) derived from digital elevation model (DEM) derivatives, climate data, geographical information system (GIS) functions, and topographically corrected satellite imagery. Four sensitivity analyses were conducted as a controlled series of experiments involving (i) NPP individual parameter sensitivity for a full growing season, (ii) NPP independent variation tests (parameter µ ± 1σ), (iii) factorial analyses to assess more complex multiple-factor interactions, and (iv) topographic correction. The results, validated against field measurements, showed that modeled NPP was sensitive to most inputs measured in the study area, with LAI and forest type the most important forest input, and solar radiation the most important climate input. Soil available water holding capacity expressed as a function of wetness index was only significant in conjunction with precipitation when both parameters represented a moisture-deficit situation. NPP uncertainty resulting from topographic influence was equivalent to 140 kg C ha-1 •year-1. This suggested that topographic correction of model inputs is important for accurate NPP estimation. The BEPS model, designed originally for flat boreal forests, was shown to be applicable in mountainous terrain given appropriate image terrain corrections using the SCS+C approach. Rocky Mountain carbon dynamics were simulated with average annual NPP of Kananaskis forests estimated at 4.01 t C ha-1 •year-1 and compared favourably with the field plot estimate of 4.24 t C ha-1 •year-1 for this area. 258 Résumé. La productivité primaire nette (PPN) constitue un élément clé du cycle du carbone terrestre et elle est importante pour les études écologiques, les études de bassins versants et de gestion forestière et, plus généralement, pour la recherche sur les changements climatiques à l'échelle du globe. La détermination de l'importance relative et de l'amplitude de l'incertitude des intrants aux modèles de PPN est essentielle pour la production de rapports adéquats sur le carbone au-dessus de zones plus vastes et pour des périodes plus longues. Dans cet article, on présente une évaluation systématique du modèle BEPS (« boreal ecosystem productivity simulator ») en terrain montagneux en utilisant un site de forêt montagnarde bien connu situé à Kananaskis, en Alberta, dans les montagnes Rocheuses canadiennes. Les intrants de base utilisés pour faire tourner le modèle étaient reliés à la forêt (couvert, LAI, biomasse) et au climat et à l'eau (rayonnement solaire, température, précipitation, humidité, capacité de rétention de l'eau du sol) dérivés des dérivées d'un modèle numérique d'altitude (MNA), des données climatiques, des fonctions SIG et d'images satellitaires corrigées pour les effets topographiques. Quatre analyses de sensibilité ont été réalisées sous forme d'une série contrôlée d'expériences comprenant (i) la sensibilité des paramètres individuels de PPN au cours d'une saison de croissance entière, (ii) tests de variation indépendante de PPN (paramètre µ ± 1σ), (iii) analyses factorielles pour évaluer les interactions multifacteurs plus complexes, et (iv) correction topographique. Les résultats, validés par rapport à des mesures sur le terrain, ont montré que la PPN modélisée était sensible à la plupart des intrants mesurés dans la zone d'étude, le LAI et le type de forêt étant les intrants les plus importants, et le rayonnement solaire étant l'intrant climatique le plus important. La capacité de rétention de l'eau disponible dans le sol en tant que fonction de l'indice d'humidité était significative seulement en conjonction avec les précipitations lorsque les deux paramètres présentaient une situation de déficit d'humidité. L'incertitude de PPN résultant de l'influence topographique était équivalente à 140 kg C ha-1 •an-1. Ceci laissait supposer que la correction topographique des intrants du modèle était importante pour l'estimation précise de PPN. Le modèle BEPS, conçu au départ pour les forêts boréales à relief plat, s'est avéré applicable dans les régions montagneuses après application des corrections appropriées de terrain aux images en utilisant l'approche SCS+C. La dynamique du carbone des montagnes Rocheuses a été simulée avec des valeurs annuelles moyennes de PPN pour les forêts de Kananaskis estimées à 4,01 t C ha-1 •an-1 et celle-ci se comparait avantageusement à la valeur de 4,24 t C ha-1 •an-1 observée sur la parcelle expérimentale pour cette zone. [Traduit par la Rédaction]
A Physically Based Daily Hydrometeorological Model for Complex Mountain Terrain
Journal of Hydrometeorology, 2009
This paper describes the continued development of the physically based hydrometeorological model Generate Earth Systems Science input (GENESYS) and its application in simulating snowpack in the St. Mary (STM) River watershed, Montana. GENESYS is designed to operate a high spatial and temporal resolution over complex mountainous terrain. The intent of this paper is to assess the performance of the model in simulating daily snowpack and the spatial extent of snow cover over the St. Mary River watershed. A new precipitation estimation method that uses snowpack telemetry (SNOTEL) and snow survey data is presented and compared with two other methods, including Parameter-elevation Regressions on Independent Slopes Model (PRISM) precipitation data. A method for determining daily temperature lapse rates from NCEP reanalysis data is also presented and the effect of temperature lapse rate on snowpack simulations is determined. Simulated daily snowpack values compare well with observed values at the Many Glacier SNOTEL site, with varying degrees of accuracy, dependent on the method used to estimate precipitation. The spatial snow cover extent compares well with Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products for three dates selected to represent snow accumulation and ablation periods.