首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 31 毫秒
1.
Accurate snow accumulation and melt simulations are crucial for understanding and predicting hydrological dynamics in mountainous settings. As snow models require temporally varying meteorological inputs, time resolution of these inputs is likely to play an important role on the model accuracy. Because meteorological data at a fine temporal resolution (~1 hr) are generally not available in many snow‐dominated settings, it is important to evaluate the role of meteorological inputs temporal resolution on the performance of process‐based snow models. The objective of this work is to assess the loss in model accuracy with temporal resolution of meteorological inputs, for a range of climatic conditions and topographic elevations. To this end, a process‐based snow model was run using 1‐, 3‐, and 6‐hourly inputs for wet, average, and dry years over Boise River Basin (6,963 km2), which spans rain dominated (≤1,400 m), rain–snow transition (>1,400 and ≤1,900 m), snow dominated below tree line (>1,900 and ≤2,400 m), and above tree line (>2,400 m) elevations. The results show that sensitivity of the model accuracy to the inputs time step generally decreases with increasing elevation from rain dominated to snow dominated above tree line. Using longer than hourly inputs causes substantial underestimation of snow cover area (SCA) and snow water equivalent (SWE) in rain‐dominated and rain–snow transition elevations, due to the precipitation phase mischaracterization. In snow‐dominated elevations, the melt rate is underestimated due to errors in estimation of net snow cover energy input. In addition, the errors in SCA and SWE estimates generally decrease toward years with low snow mass, that is, dry years. The results indicate significant increases in errors in estimates of SCA and SWE as the temporal resolution of meteorological inputs becomes coarser than an hour. However, use of 3‐hourly inputs can provide accurate estimates at snow‐dominated elevations. The study underscores the need to record meteorological variables at an hourly time step for accurate process‐based snow modelling.  相似文献   

2.
Development of hydrological models for seasonal and real-time runoff forecast in rivers of high alpine catchments is useful for management of water resources. The conceptual models for this purpose are based on a temperature index and/or energy budget and can be either lumped or distributed over the catchment area. Remote sensing satellite data are most useful to acquire near real-time geophysical parameters in order to input to the distributed forecasting models. In the present study, integration of optical satellite remote sensing-derived information was made with ground meteorological and hydrological data, and predetermined catchment morphological parameters, to study the feasibility of application of a distributed temperature index snowmelt runoff model to one of the high mountainous catchments in the Italian Alps, known as Cordevole River Basin. Five sets of Landsat Multispectral Scanning System (MSS) and Thematic Mapper (TM) computer-compatible tapes (CCTs) were processed using digital image processing techniques in order to evaluate the snow cover variation quantitatively. Digital elevation model, slope and aspect parameters were developed and used during satellite data processing. The satellite scenes were classified as snow, snow under transition and snow free areas. A second-order polynomial fit has been attempted to approximate the snow depletion and to estimate daily snow cover areal extent for three elevation zones of the catchment separately. Model performance evaluation based on correlation coefficient, Nash–Sutcliffe coefficient and percentage volume deviation indicated very good simulation between measured and computed discharges for the entire snowmelt period. The use of average temperature values computed from the maximum and minimum temperatures into the model was studied and a suitable algorithm was proposed. © 1997 John Wiley & Sons, Ltd.  相似文献   

3.
Time‐lapse photography provides an attractive source of information about snow cover characteristics, especially at the small catchment scale. The objective of this study was to design and test a monitoring system, which allows multi‐resolution observations of snow cover characteristics. The main aim was to simultaneously investigate the spatio‐temporal patterns of snow cover, snow depth and snowfall interception in the area very close to the camera, and the spatio‐temporal patterns of snow cover in the far range. The multi‐resolution design was tested at three sites in the eastern part of the Austrian Alps (Hochschwab‐Rax region). Digital photographs were taken at hourly time steps between 6:00 and 18:00 in the period November, 2004 to December, 2006. The results showed that the time‐lapse photography allows effective mapping of the snow depths at high temporal resolution in the region close to the digital camera at many snow stake locations. It is possible to process a large number of photos by using an automatic procedure for accurate snow depth readings. The digital photographs can also be used to infer the settling characteristics of the snow pack and snow interception during the day. Although it is not possible to directly estimate the snow interception mass, the photos may indeed give very useful information on the snow processes on and beneath the forest canopy. The main advantage of using time‐lapse photography in the far range of the digital camera is to observe the spatio‐temporal patterns of snow cover over different landscape configurations. The results illustrate that digital photographs can be very useful for parameterising processes such as sloughing on steep slopes, snow deposition in gullies and snow erosion on mountain ridges in a distributed snow model. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

4.
Controls on event runoff coefficients in the eastern Italian Alps   总被引：3，自引：0，他引：3  
Analyses of event runoff coefficients provide essential insight on catchment response, particularly if a range of catchments and a range of events are compared by a single indicator. In this study we examine the effect of climate, geology, land use, flood types and initial soil moisture conditions on the distribution functions of the event runoff coefficients for a set of 14 mountainous catchments located in the eastern Italian Alps, ranging in size from 7.3 to 608.4 km2. Runoff coefficients were computed from hourly precipitation, runoff data and estimates of snowmelt. A total of 535 events were analysed over the period 1989–2004. We classified each basin using a “permeability index” which was inferred from a geologic map and ranged from “low” to “high permeability”. A continuous soil moisture accounting model was applied to each catchment to classify ‘wet’ and ‘dry’ initial soil moisture conditions. The results indicate that the spatial distribution of runoff coefficients is highly correlated with mean annual precipitation, with the mean runoff coefficient increasing with mean annual precipitation. Geology, through the ‘permeability index’, is another important control on runoff coefficients for catchments with mean annual precipitation less than 1200 mm. Land use, as indexed by the SCS curve number, influences runoff coefficient distribution to a lesser degree. An analysis of the runoff coefficients by flood type indicates that runoff coefficients increase with event snowmelt. Results show that there exists an intermediate region of subsurface water storage capacity, as indexed by a flow–duration curve-based index, which maximises the impact of initial wetness conditions on the runoff coefficient. This means that the difference between runoff coefficients characterised by wet and dry initial conditions is negligible both for basins with very large storage capacity and for basins with small storage capacity. For basins with intermediate storage capacities, the impact of the initial wetness conditions may be relatively large.  相似文献   

5.
Taking the Northern Xinjiang region as an example, we develop a snow depth model by using the Advanced Microwave Scanning Radiometer‐Earth Observing System (AMSR‐E) horizontal and vertical polarization brightness temperature difference data of 18 and 36 GHz bands and in situ snow depth measurements from 20 climatic stations during the snow seasons November–March) of 2002–2005. This article proposes a method to produce new 5‐day snow cover and snow depth images, using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products and AMSR‐E snow water equivalent and daily brightness temperature products. The results indicate that (1) the brightness temperature difference (Tb18h–Tb36h) provides the most accurate and precise prediction of snow depth; (2) the snow, land and overall classification accuracies of the new images are separately 89.2%, 77.7% and 87.2% and are much better than those of AMSR‐E or MODIS products (in all weather conditions) alone; (3) the snow classification accuracy increases as snow depth increases; and (4) snow accuracies for different land cover types vary as 88%, 92.3%, 79.7% and 80.1% for cropland, grassland, shrub, and urban and built‐up, respectively. We conclude that the new 5‐day snow cover–snow depth images can provide both accurate cloud‐free snow cover extent and the snow depth dynamics, which would lay a scientific basis for water management and prevention of snow‐related disasters in this dry and cold pastoral area. After validations of the algorithms over other regions with different snow and climate conditions, this method would also be used for monitoring snow cover and snow depth elsewhere in the world. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

6.
An approach to spatially distribute a snow process model by segmenting images of land cover, terrain and snow properties is reported. A small 1.7 ha study area with an existing database was selected for this preliminary evaluation. The methodology was carried out over a relatively flat valley bottom at Camp Grayling, Michigan. Meteorological measurements on two sides of the area showed only small differences, so uniform meteorological variables were assumed over the site. Initial snow cover conditions were reconstructed and were distributed over the area using snow maps and sparse snow pit measurements. One metre resolution terrain, soil, vegetation and snow type maps were individually processed into class maps. These layers were then combined to produce a segmented class map, where the attributes from the data layers were known for each class. A one-dimensional model of snow processes was run for each class, then the results were mapped back into images. Shallow snow conditions provided high sensitivity of ablation patterns to meteorological conditions over a 72 h period. The model performance was assessed by comparing predicted and observed ablation patterns. The error in total snow-covered area was less than 9%. However, the location errors were greater (predicted snow where no snow was observed and observed snow where no snow was predicted). Extensive error analysis was not justified because of the lack of multiple point measurements of snow properties.  相似文献   

7.
For two years, three French and Swiss laboratories have been making field observations and measurements on two high altitude slopes in a Northern French Alps site. The aim of this work is to study the functioning of the avalanche sites which, in their starting zones, undergo snow-transport by wind. The experimental site is located in the French Alps, at 2,800 m, above Grenoble. It is an open area, equipped with an automatic meteorological station and an altitude laboratory. The two slopes that are studied face East. One of them is artificially released but the other has a natural avalanche activity. The investigations concern:
  • -snow deposition in avalanche starting zones;
  • -temporal evolution of the snowpack characteristics;
  • -avalanche release.
    • For the field observations and measurements, continuous recording of the meteorological conditions on the site, photogrammetrical techniques and two snow depth profiles, as well as stratigraphical snow profiles and video are used. The computer modeling is based on existing computer models developed by the CEMAGREF-Nivologie (ELSA) and the CEN/Météo-France (SAFRAN-CROCUS-MEPRA), which analyse the snowpack and its stability. The field observations and measurements aim at improving snow-transport by wind modeling modules, in order to improve their whole analysis.  相似文献   

    8.
    To improve spring runoff forecasts from subalpine catchments, detailed spatial simulations of the snow cover in this landscape is obligatory. For more than 30 years, the Swiss Federal Research Institute WSL has been conducting extensive snow cover observations in the subalpine watershed Alptal (central Switzerland). This paper summarizes the conclusions from past snow studies in the Alptal valley and presents an analysis of 14 snow courses located at different exposures and altitudes, partly in open areas and partly in forest. The long‐term performance of a physically based numerical snow–vegetation–atmosphere model (COUP) was tested with these snow‐course measurements. One single parameter set with meteorological input variables corrected to the prevailing local conditions resulted in a convincing snow water equivalent (SWE) simulation at most sites and for various winters with a wide range of snow conditions. The snow interception approach used in this study was able to explain the forest effect on the SWE as observed on paired snow courses. Finally, we demonstrated for a meadow and a forest site that a successful simulation of the snowpack yields appropriate melt rates. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

    9.
    Abstract

    In physically-based land surface models, the parameters can all be prescribed a priori but calibration can be used to enhance the realism of the simulations in well instrumented domains. In such a case, the transferability of calibrated parameters under non-stationary conditions needs to be addressed, especially in the context of climate change. To this end, we used the Catchment Land Surface Model (CLSM) in the Upper Durance watershed located in the French Alps, which experienced a significant increase in temperature over the last century. The CLSM is forced by a 50-year meteorological dataset of good quality. Four parameters of the CLSM (one related to snow processes and three to soil properties) are calibrated against discharge observations with a multi-objective algorithm. First, the robustness of the CLSM parameterizations is tested by the Differential Split Sample Test (DSST). The simulations show good performances over a wide range of retrospective climatic conditions, except when the parameters are calibrated over a period with a large contribution of snowmelt to annual mean discharge. Then, the use of a climate change scenario reveals that the parameterizations of soil moisture processes in the CLSM are responsible for an increasing dispersion among simulations when facing dry and warm conditions. However, the differences between the simulated changes of river discharge remain very small. This work shows that calibration conveys some uncertainties, but they are moderate in the studied case, and pertain to the most conceptual parameterizations of this physically-based model.  相似文献   

    10.
    Mountain water resources management often requires hydrological models that need to handle both snow and ice melt. In this study, we compared two different model types for a partly glacierized watershed in central Switzerland: (1) an energy‐balance model primarily designed for snow simulations; and (2) a temperature‐index model developed for glacier simulations. The models were forced with data extrapolated from long‐term measurement records to mimic the typical input data situation for climate change assessments. By using different methods to distribute precipitation, we also assessed how various snow cover patterns influenced the modelled runoff. The energy‐balance model provided accurate discharge estimations during periods dominated by snow melt, but dropped in performance during the glacier ablation season. The glacier melt rates were sensitive to the modelled snow cover patterns and to the parameterization of turbulent heat fluxes. In contrast, the temperature‐index model poorly reproduced snow melt runoff, but provided accurate discharge estimations during the periods dominated by glacier ablation, almost independently of the method used to distribute precipitation. Apparently, the calibration of this model compensated for the inaccurate precipitation input with biased parameters. Our results show that accurate estimates of snow cover patterns are needed either to correctly constrain the melt parameters of the temperature‐index model or to ensure appropriate glacier surface albedos required by the energy‐balance model. Thus, particularly when only distant meteorological stations are available, carefully selected input data and efficient extrapolation methods of meteorological variables improve the reliability of runoff simulations in high alpine watersheds. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

    11.
    The ecological situation of the Tarim River basin in China seriously declined since the early 1950s, mainly due to a strong increase in water abstraction for irrigation purposes. To restore the ecological system and support sustainable development of the Tarim River basin region in China, more hydrological studies are demanded to properly understand the processes of the watershed and efficiently manage the water resources. Such studies are, however, complicated due to the limited data availability, especially in the mountainous headwater regions of the Tarim River basin. This study investigated the usefulness of remote sensing (RS) data to overcome that lack of data in the spatially distributed hydrological modelling of the basin. Complementary to the conventional station‐based (SB) data, the RS products that are directly used in this study include precipitation, evapotranspiration and leaf area index. They are derived from raw image data of the Chinese Fengyun meteorological satellite and from the Moderate Resolution Imaging Spectroradiometer (MODIS). The MODIS land surface temperature was used to calculate the atmospheric temperature lapse rate to describe the temperature dependency on topographical variations. Moreover, MODIS‐based snow cover images were used to obtain model initial conditions and as validation reference for the snow model component. Comparison of model results based on RS input versus conventional SB input exhibited similar results in terms of high and low river runoff extremes, cumulative runoff volumes in both runoff and snow melting seasons and spatial and temporal variability of snow cover. During summer time, when the snow cover shrinks in the permanent glacier region, it was found that the model resolution influences the model results dramatically, hence, showing the importance of detailed (RS based) spatially distributed input data. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

    12.
    T. Jonas  C. Marty  J. Magnusson   《Journal of Hydrology》2009,378(1-2):161-167
    The snow water equivalent (SWE) characterizes the hydrological significance of snow cover. However, measuring SWE is time-consuming, thus alternative methods of determining SWE may be useful. SWE can be calculated from snow depth if the bulk snow density is known. Thus, a reliable estimation method of snow densities could (a) potentially save a lot of effort by, at least partly, sampling snow depth instead of SWE, and would (b) allow snow hydrological evaluations, when only snow depth data are available. To generate a useful parameterization of the bulk density a large dataset was analyzed covering snow densities and depths measured biweekly over five decades at 37 sites throughout the Swiss Alps. Four factors were identified to affect the bulk snow density: season, snow depth, site altitude, and site location. These factors constitute a convenient set of input variables for a snow density model developed in this study. The accuracy of estimating SWE using our model is shown to be equivalent to the variability of repeated SWE measurements at one site. The technique may therefore allow a more efficient but indirect sampling of the SWE without necessarily affecting the data quality.  相似文献   

    13.
    The CRISTA/MAHRSI experiment on board a space shuttle was accompanied by a broad campaign of rocket, balloon and ground-based measurements. Supporting lower ionospheric ground-based measurements were run in Europe and Eastern Asia between 1 October–30 November, 1994. Results of comparisons with long ionospheric data series together with short-term comparisons inside the interval October-November, 1994, showed that the upper middle atmosphere (h =80–100 km) at middle latitudes of the Northern Hemisphere in the interval of the CRISTA/MAHRSI experiment (4–12 November, 1994) was very close to its expected climatological state. In other words, the average results of the experiment can be used as climatological data, at least for the given area/altitudes. The role of solar/geomagnetic and “meteorological” control of the lower ionosphere is investigated and compared with the results of MAP/WINE, MAC/SINE and DYANA campaigns. The effects of both solar/geomagnetic and global meteorological factors on the lower ionosphere are found to be weak during autumn 1994 compared to those in MAP/WINE and DYANA winters, and they are even slightly weaker than those in MAP/SINE summer. The comparison of the four campaigns suggests the following overall pattern: in winter the lower ionosphere at northern middle latitudes appears to be fairly well “meteorologically” controlled with a very weak solar influence. In summer, solar influence is somewhat stronger and dominates the weak “meteorological” influence, but the overall solar/meteorological control is weaker than in winter. In autumn we find the weakest overall solar/meteorological control, local effects evidently dominate.  相似文献   

    14.
    Snow cover patterns in a 9.4 km2 basin in the Austrian Alps are examined during spring and summer 1989. Digital mono-plotting from oblique aerophotographs is used for mapping. on the basis of a square grid with 25 m spacing, snow cover as mapped during nine surveys is analysed as a function of elevation and slope. During winter conditions the snow cover is found to be much better related to these terrain features than during the late ablation period.  相似文献   

    15.
    Knowledge about flood generating processes can be beneficial for numerous applications. Especially in the context of climate change impact assessment, daily patterns of meteorological and catchment state conditions leading to flood events (i.e., storylines) may be of value. Here, we propose an approach to identify storylines of flood generation using daily weather and snow cover observations. The approach is tested for and applied to a typical pre‐Alpine catchment in the period between 1961 and 2014. Five precipitation parameters were determined that describe temporal and spatial characteristics of the flood associated precipitation events. The catchment's snow coverage was derived using statistical relationships between a satellite‐derived snow cover climatology and station snow measurements. Moreover, (pre‐) event snow melt sums were estimated using a temperature‐index model. Based on the precipitation and catchment state parameters, 5 storylines were identified with a cluster analysis: These are (a) long duration, low intensity precipitation events with high precipitation depths, (b) long duration precipitation events with high precipitation depths and episodes of high intensities, (c) shorter duration events with high or (d) low precipitation intensity, respectively, and (e) rain‐on‐snow events. The event groups have distinct hydrological characteristics that can largely be explained by the storylines' respective properties. The long duration, high intensity storyline leads to the most adverse hydrological response, namely, a combination of high peak magnitudes, high volumes, and long durations of threshold exceedance. The results show that flood generating processes in mesoscale catchments can be distinguished on the basis of daily meteorological and catchment state parameters and that these process types can explain the hydrological flood properties in a qualitative way. Hydrological simulations of daily resolution can thus be analysed with respect to flood generating processes.  相似文献   

    16.
    The Process Modelling and Artificial Intelligence for Online Flood Forecasting (PAI-OFF) methodology combines the reliability of physically based, hydrologic/hydraulic modelling with the operational advantages of artificial intelligence. These operational advantages are extremely low computation times and straightforward operation. The basic principle of the methodology is to portray process models by means of ANN. We propose to train ANN flood forecasting models with synthetic data that reflects the possible range of storm events. To this end, establishing PAI-OFF requires first setting up a physically based hydrologic model of the considered catchment and – optionally, if backwater effects have a significant impact on the flow regime – a hydrodynamic flood routing model of the river reach in question. Both models are subsequently used for simulating all meaningful and flood relevant storm scenarios which are obtained from a catchment specific meteorological data analysis. This provides a database of corresponding input/output vectors which is then completed by generally available hydrological and meteorological data for characterizing the catchment state prior to each storm event. This database subsequently serves for training both a polynomial neural network (PoNN) – portraying the rainfall–runoff process – and a multilayer neural network (MLFN), which mirrors the hydrodynamic flood wave propagation in the river. These two ANN models replace the hydrological and hydrodynamic model in the operational mode. After presenting the theory, we apply PAI-OFF – essentially consisting of the coupled “hydrologic” PoNN and “hydrodynamic” MLFN – to the Freiberger Mulde catchment in the Erzgebirge (Ore-mountains) in East Germany (3000 km2). Both the demonstrated computational efficiency and the prediction reliability underline the potential of the new PAI-OFF methodology for online flood forecasting.  相似文献   

    17.
    The hydrology and contrasting erosional responses of two snowmelt events on arable farmland in Fife, Scotland, are compared. Snowmelt-generated runoff in January 1993 caused widespread soil erosion across eastern Scotland. Gullying was exemplified by three sites in Fife, where thaw of a drifted snowpack was augmented by rainfall to produce a larger erosive response than meteorological data alone would have predicted. Up to 127 m3 of soil was lost from individual gullies in fields sown to winter cereals. In February 1996 snowfall of comparable depth again covered the field area, but a more uniform snowpack, slower thaw, greater crop cover and lower rainfall during the thaw phase combined to lessen the impact of erosion. These case studies demonstrate the complexity of the erosion/runoff relationship for rain on snow events, in which erosional severity depends not just on snow depth but on snow distribution, thaw rate and the amount and timing of rainfall during the thaw phase. © 1998 John Wiley & Sons, Ltd.  相似文献   

    18.
    An accurate simulation of snowmelt runoff is of much importance in arid alpine regions. Data availability is usually an obstacle to use energy‐based snowmelt models for the snowmelt runoff simulation, and temperature‐based snowmelt models are more appealing in these regions. The snow runoff model is very popular nowadays, especially in the data sparse regions, because only temperature, precipitation and snow cover data are required for inputs to the model. However, this model uses average temperature as index, which cannot reflect the snowmelt simulation in the high altitude band. In this study, the snow runoff model is modified on the basis of accumulated active temperature. Snow cover calculation algorithm is added and is no longer needed as input but output. This makes the model able to simulate long‐time runoff and long‐time snow cover variation in every band. An examination of the improved model in the Manas River basin showed that the model is effective. It can reproduce the behaviour of the hydrology and can reflect the actual snow cover fluctuation. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

    19.
    A snow depletion curve (SDC), the relationship between snow mass (e.g., snow depth [SD]) and fractional snow cover area (SCF), is essential to parameterize the effect of snowpack within a physically based snow model. Existing SDCs are constructed using traditional statistic methods may not be applicable in complex mountainous areas. In this study, we developed an information fusion framework to define the relationship between SCF and SD as well as 12 auxiliary factors by using a traditional statistical method and four prevailing machine learning (ML) algorithms, which have comprehensively considered the variable conditions that cause spatiotemporal heterogeneity of snow cover. We also performed a single-dimensional sensitivity analysis to investigate the physical rationality of the newly developed SDCs. The Northern Xinjiang, Northwest China, is selected as the study area, and the data from 46 meteorological stations covering five snow seasons from 2010 to 2015 are used. The results illustrated that ML techniques can be used to establish high-accuracy and robust SDCs for complex mountainous areas. Compared with SDCs constructed by traditional statistical, the performance of the four ML-based SDCs is significantly improved, the RMSE values can be reduced by 50%, R2 above 0.75, and an average relative variance close to 0. ML-based SDCs predicted SCF values showed a range of sensitivities to different input variables (e.g., Land surface temperature, aspect, longwave radiation and land cover type), in addition to SD, that were physically representative of effects that snow cover is sensitive to. Moreover, the complexity of SDCs can be reduced by removing insensitive input variables.  相似文献   

    20.
    In this work, we used the Regional Hydro‐Ecological Simulation System (RHESSys) model to examine runoff sensitivity to land cover changes in a mountain environment. Two independent experiments were evaluated where we conducted simulations with multiple vegetation cover changes that include conversion to grass, no vegetation cover and deciduous/coniferous cover scenarios. The model experiments were performed at two hillslopes within the Weber River near Oakley, Utah watershed (USGS gauge # 10128500). Daily precipitation, air temperature and wind speed data as well as spatial data that include a digital elevation model with 30 m grid resolution, soil texture map and vegetation and land use maps were processed to drive RHESSys simulations. Observed runoff data at the watershed outlet were used for calibration and verification. Our runoff sensitivity results suggest that during winter, reduced leaf area index (LAI) decreases canopy interception resulting in increased snow accumulations and hence snow available for runoff during the early spring melt season. Increased LAI during the spring melt season tends to delay the snow melting process. This delay in snow melting process is due to reduced radiation beneath high LAI surfaces relative to low LAI surfaces. The model results suggest that annual runoff yield after removing deciduous vegetation is on average about 7% higher than with deciduous vegetation cover, while annual runoff yield after removing coniferous vegetation is on average as about 2% higher than that produced with coniferous vegetation cover. These simulations thus help quantify the sensitivity of water yield to vegetation change. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

    设为首页 | 免责声明 | 关于勤云 | 加入收藏

    Copyright©北京勤云科技发展有限公司  京ICP备09084417号