The aim of the international project “Global Land Ice Measurements from Space (GLIMS)" headed by the US Geological Survey is to establish a world wide glacier inventory based on satellite imagery.This data set w...The aim of the international project “Global Land Ice Measurements from Space (GLIMS)" headed by the US Geological Survey is to establish a world wide glacier inventory based on satellite imagery.This data set will form a first digital baseline study for future glacier monitoring.The presented GIS_based glacier inventory for King George Island is a case study for the area of the Antarctic Peninsula.In the database of the glacier inventory topographic information,specific glaciological parameters as well as metadata will be included.The topographic data consists of drainage basin limits,basin areas,altitudinal ranges,perimeters and mean lengths.Glaciological data sets should comprise information on glacier retreat in different periods,glacier velocities,ice thickness and bedrock topography as well as derived parameters.Modelled and measured mass balance parameters could be included as additional data layers.In particular,these metadata records must comprise background information on data accuracy and data sources and should be compatible with a future data model for the King George Island GIS (KGIS).Three examples illustrate that the GLIMS database will not only contain information valuable for glaciological applications,but also other environmental studies on the island will benefit from this standardised remote sensing data sets.Therefore,a very close link between the data models of KGIS and GLIMS has to be established to enable these synergisms.Finally,better access to historic aerial photography would enable a continuous record of glacier retreat from the beginning of the 1950’s onward.展开更多
The proper determination of the curve number （CN） in the SCS-CN method reduces errors in predicting runoff volume. In this paper the variability of CN was studied for 5 Slovak and S Polish Carpathian catchments. Emp...The proper determination of the curve number （CN） in the SCS-CN method reduces errors in predicting runoff volume. In this paper the variability of CN was studied for 5 Slovak and S Polish Carpathian catchments. Empirical curve numbers were applied to the distribution fitting. Next, theoretical characteristics of CN were estimated. For loo-CN the Generalized Extreme Value （GEV） distribution was identified as the best fit in most of the catchments. An assessment of the differences between the characteristics estimated from theoretical distributions and the tabulated values of CN was performed. The comparison between the antecedent runoff conditions （ARC） of Hawkins and Hjelmfelt was also completed. The analysis was done for various magnitudes of rainfall. Confidence intervals （CI） were helpful in this evaluation. The studies revealed discordances between the tabulated and estimated CNs. The tabulated CNs were usually lower than estimated values; therefore, an application of the median value and the probabilistic ARC of Hjelmfelt for wet runoff conditions is advisable. For dry conditions the ARC of Hjelmfelt usually better estimated CN than ARC of Hawkins did, but in several catchments neither the ARC of Hawkins nor Hjelmfelt sufficiently depicted the variability in CN.展开更多
文摘The aim of the international project “Global Land Ice Measurements from Space (GLIMS)" headed by the US Geological Survey is to establish a world wide glacier inventory based on satellite imagery.This data set will form a first digital baseline study for future glacier monitoring.The presented GIS_based glacier inventory for King George Island is a case study for the area of the Antarctic Peninsula.In the database of the glacier inventory topographic information,specific glaciological parameters as well as metadata will be included.The topographic data consists of drainage basin limits,basin areas,altitudinal ranges,perimeters and mean lengths.Glaciological data sets should comprise information on glacier retreat in different periods,glacier velocities,ice thickness and bedrock topography as well as derived parameters.Modelled and measured mass balance parameters could be included as additional data layers.In particular,these metadata records must comprise background information on data accuracy and data sources and should be compatible with a future data model for the King George Island GIS (KGIS).Three examples illustrate that the GLIMS database will not only contain information valuable for glaciological applications,but also other environmental studies on the island will benefit from this standardised remote sensing data sets.Therefore,a very close link between the data models of KGIS and GLIMS has to be established to enable these synergisms.Finally,better access to historic aerial photography would enable a continuous record of glacier retreat from the beginning of the 1950’s onward.
基金supported by the Slovak Grant Agency VEGA under Project No.1/0776/13 and Project No.1/0710/15Research Project No.N N305 396238 founded by the Polish Ministry of Science and Higher Education
文摘The proper determination of the curve number （CN） in the SCS-CN method reduces errors in predicting runoff volume. In this paper the variability of CN was studied for 5 Slovak and S Polish Carpathian catchments. Empirical curve numbers were applied to the distribution fitting. Next, theoretical characteristics of CN were estimated. For loo-CN the Generalized Extreme Value （GEV） distribution was identified as the best fit in most of the catchments. An assessment of the differences between the characteristics estimated from theoretical distributions and the tabulated values of CN was performed. The comparison between the antecedent runoff conditions （ARC） of Hawkins and Hjelmfelt was also completed. The analysis was done for various magnitudes of rainfall. Confidence intervals （CI） were helpful in this evaluation. The studies revealed discordances between the tabulated and estimated CNs. The tabulated CNs were usually lower than estimated values; therefore, an application of the median value and the probabilistic ARC of Hjelmfelt for wet runoff conditions is advisable. For dry conditions the ARC of Hjelmfelt usually better estimated CN than ARC of Hawkins did, but in several catchments neither the ARC of Hawkins nor Hjelmfelt sufficiently depicted the variability in CN.
