High Spatial Variability (high + spatial_variability)

Distribution by Scientific Domains

Selected Abstracts

Spatial and temporal variability of the phenological seasons in Germany from 1951 to 1996

Annette Menzel
Abstract Various indications for shifts in plant and animal phenology resulting from climate change have been observed in Europe. This analysis of phenological seasons in Germany of more than four decades (1951,96) has several major advantages: (i) a wide and dense geographical coverage of data from the phenological network of the German Weather Service, (ii) the 16 phenophases analysed cover the whole annual cycle and, moreover, give a direct estimate of the length of the growing season for four deciduous tree species. After intensive data quality checks, two different methods ,,linear trend analyses and comparison of averages of subintervals , were applied in order to determine shifts in phenological seasons in the last 46 years. Results from both methods were similar and reveal a strong seasonal variation. There are clear advances in the key indicators of earliest and early spring (,0.18 to ,0.23 d y,1) and notable advances in the succeeding spring phenophases such as leaf unfolding of deciduous trees (,0.16 to ,0.08 d y,1). However, phenological changes are less strong during autumn (delayed by +,0.03 to +,0.10 d y,1 on average). In general, the growing season has been lengthened by up to ,0.2 d y,1 (mean linear trends) and the mean 1974,96 growing season was up to 5 days longer than in the 1951,73 period. The spatial variability of trends was analysed by statistical means and shown in maps, but these did not reveal any substantial regional differences. Although there is a high spatial variability, trends of phenological phases at single locations are mirrored by subsequent phases, but they are not necessarily identical. Results for changes in the biosphere with such a high resolution with respect to time and space can rarely be obtained by other methods such as analyses of satellite data. [source]

Estimating fog deposition at a Puerto Rican elfin cloud forest site: comparison of the water budget and eddy covariance methods

F. Holwerda
Abstract The deposition of fog to a wind-exposed 3 m tall Puerto Rican cloud forest at 1010 m elevation was studied using the water budget and eddy covariance methods. Fog deposition was calculated from the water budget as throughfall plus stemflow plus interception loss minus rainfall corrected for wind-induced loss and effect of slope. The eddy covariance method was used to calculate the turbulent liquid cloud water flux from instantaneous turbulent deviations of the surface-normal wind component and cloud liquid water content as measured at 4 m above the forest canopy. Fog deposition rates according to the water budget under rain-free conditions (0·11 ± 0·05 mm h,1) and rainy conditions (0·24 ± 0·13 mm h,1) were about three to six times the eddy-covariance-based estimate (0·04 ± 0·002 mm h,1). Under rain-free conditions, water-budget-based fog deposition rates were positively correlated with horizontal fluxes of liquid cloud water (as calculated from wind speed and liquid water content data). Under rainy conditions, the correlation became very poor, presumably because of errors in the corrected rainfall amounts and very high spatial variability in throughfall. It was demonstrated that the turbulent liquid cloud water fluxes as measured at 4 m above the forest could be only ,40% of the fluxes at the canopy level itself due to condensation of moisture in air moving upslope. Other factors, which may have contributed to the discrepancy in results obtained with the two methods, were related to effects of footprint mismatch and methodological problems with rainfall measurements under the prevailing windy conditions. Best estimates of annual fog deposition amounted to ,770 mm year,1 for the summit cloud forest just below the ridge top (according to the water budget method) and ,785 mm year,1 for the cloud forest on the lower windward slope (using the eddy-covariance-based deposition rate corrected for estimated vertical flux divergence). Copyright © 2006 John Wiley & Sons, Ltd. [source]

Multi-variable and multi-site calibration and validation of SWAT in a large mountainous catchment with high spatial variability

Wenzhi Cao
Abstract Many methods developed for calibration and validation of physically based distributed hydrological models are time consuming and computationally intensive. Only a small set of input parameters can be optimized, and the optimization often results in unrealistic values. In this study we adopted a multi-variable and multi-site approach to calibration and validation of the Soil Water Assessment Tool (SWAT) model for the Motueka catchment, making use of extensive field measurements. Not only were a number of hydrological processes (model components) in a catchment evaluated, but also a number of subcatchments were used in the calibration. The internal variables used were PET, annual water yield, daily streamflow, baseflow, and soil moisture. The study was conducted using an 11-year historical flow record (1990,2000); 1990,94 was used for calibration and 1995,2000 for validation. SWAT generally predicted well the PET, water yield and daily streamflow. The predicted daily streamflow matched the observed values, with a Nash,Sutcliffe coefficient of 0·78 during calibration and 0·72 during validation. However, values for subcatchments ranged from 0·31 to 0·67 during calibration, and 0·36 to 0·52 during validation. The predicted soil moisture remained wet compared with the measurement. About 50% of the extra soil water storage predicted by the model can be ascribed to overprediction of precipitation; the remaining 50% discrepancy was likely to be a result of poor representation of soil properties. Hydrological compensations in the modelling results are derived from water balances in the various pathways and storage (evaporation, streamflow, surface runoff, soil moisture and groundwater) and the contributions to streamflow from different geographic areas (hill slopes, variable source areas, sub-basins, and subcatchments). The use of an integrated multi-variable and multi-site method improved the model calibration and validation and highlighted the areas and hydrological processes requiring greater calibration effort. Copyright © 2005 John Wiley & Sons, Ltd. [source]

Mapping snow characteristics based on snow observation probability

Bahram Saghafian
Abstract Measurement/estimation of snow water equivalent (SWE) is a difficult task in water resources studies of snowy regions. SWE point data is measured at snow courses that are normally operated with low density owing to high costs and great difficulty in reaching the stations in cold seasons. Moreover, snow is known to exhibit high spatial variability, which makes SWE studies based solely on sparse station data more uncertain. Ever-increasing availability of satellite images is a promising tool to overcome some of the difficulties associated with analyzing spatial variability of snow. Although National Oceanic and Atmospheric Administration (NOAA) satellite images have low spatial resolution with approximately 1.1-km pixel size, they are adequate for mapping snow cover at regional scales and enjoy a moderate length of record period. In this paper, rain and snow records of synoptic stations and the time series of NOAA-based snow cover maps were used to map average SWE of a vast area in southwestern Iran. First, monthly and annual snow coefficient (SC) at synoptic stations were determined on the basis of analysis of hourly observation of type and amount of precipitation. Then, two new spatially distributed snow characteristics were introduced, namely, average frequency of snow observation (FSO) and monthly frequency of maximum snow observation (FMSO), on the basis of existing satellite snow observations. FSO and monthly FMSO maps were prepared by a geographic information system on the basis of snow map time series. Correlation of these two parameters with SC was studied and spatial distribution of SC was estimated on the basis of the best correlation. Moreover, the distribution of mean annual precipitation was derived by comparing a number of interpolation methods. SWE map was generated by multiplying SC and precipitation maps and its spatial variability in the region was analyzed. Copyright © 2007 Royal Meteorological Society [source]

Diurnal and semidiurnal rainfall cycles during the rain season in SW Amazonia, observed via rain gauges and estimated using S-band radar

Cláudio Moisés Santos e Silva
Abstract The rainfall field estimated by an S-band radar was evaluated with rain gauges network measurements during the Tropical Rainfall Measuring Mission and Large-Scale Biosphere,Atmosphere Experiment in Amazonia (TRMM-LBA), then the daily variability associated with the presence (absence) of the South Atlantic convergence zone (SACZ) were studied. The results showed the high spatial variability of the rainfall over southwest (SW) Amazonia and suggest that local mechanisms (topography and/or local circulations induced by contrast of vegetation) may be associated with heavy rainfall episodes; moreover, it was possible to observe the squall line influence on the diurnal and semidiurnal cycles. Copyright © 2009 Royal Meteorological Society [source]

Reply to comment on Cao W, Bowden BW, Davie T, Fenemor A. 2006. ,Multi-variable and multi-site calibration and validation of SWAT in a large mountainous catchment with high spatial variability'.

Hydrological Processes 20(5):1057-107
No abstract is available for this article. [source]