In this paper, I investigate the scalar semantics of evaluative adjective in general, and of good in particular. Lassiter (2017) has argued that good, when taking propositions as arguments, has an interval scale. I argue that there’s evidence in support of the view that good, when taking individuals as argument, has a scale that is stronger than interval, but weaker than ratio. In particular, I propose that individual-level good has a “round” ratio scale, which allows a broader set of ratio transformations than standard ratio scales. This conclusion is consistent with the fact that good admits round ratio modifiers (twice as good), but eschews precise ones (# 1.38x as good). An important consequence of this view is that the scales of individual and propositional-level good are severed.
The processing of ombrographic data from 29 meteorological stations of the Czech Hydrometeorological Institute (CHMI), according to the terms of the Universal Soil Loss Equation for calculating long term loss of soil through water erosion, erosion hazard rains and their occurrence have been selected, with their relative amount and erosiveness - R-Factors determined for each month and years. By comparing the value of the time division of the R-Factor in the area of the Czech Republic and in selected areas of the USA it has been demonstrated that this division may be applied in the conditions of the Czech Republic. For the Czech Republic it is recommended to use the average value R = 40 based on the original evaluation.
The objective of this study is to analyse the spatial variability of seasonal flood occurrences in the Upper Danube region for the period 1961-2010. The analysis focuses on the understanding of the factors that control the spatial variability of winter and summer floods in 88 basins with different physiographic conditions. The evaluation is based on circular statistics, which compare the changes in the mean date and in the seasonal flood concentration index within a year or predefined season. The results indicate that summer half-year and winter half-year floods are dominant in the Alps and northern Danube tributaries, respectively. A comparison of the relative magnitude of flood events indicates that summer half-year floods are on average more than 50% larger than floods in winter. The evaluation of flood occurrence showed that the values of seasonal flood concentration index (median 0.75) in comparison to the annual floods (median 0.58) shows higher temporal concentration of floods. The flood seasonality of winter events is dominant in the Alps; however, along the northern fringe (i.e. the Isar, Iller and Inn River) the timing of winter half-year floods is diverse. The seasonal concentration of summer floods tends to increase with increasing mean elevation of the basins. The occurrence of the three largest summer floods is more stable, i.e. they tend to occur around the same time for the majority of analysed basins. The results show that fixing the summer and winter seasons to specific months does not always allow a clear distinction of the main flood generation processes. Therefore, criteria to define flood typologies that are more robust are needed for regions such as the Upper Danube, with large climate and topographical variability between the lowland and high elevations, particularly for the assessment of the effect of increasing air temperature on snowmelt runoff and associated floods.
Spatial and temporal variability of snow line (SL) elevation, snow cover area (SCA) and depletion (SCD) in winters 2001-2014 is investigated in ten main Slovak river basins (the Western Carpathians). Daily satellite snow cover maps from MODIS Terra (MOD10A1, V005) and Aqua (MYD10A1, V005) with resolution 500 m are used. The results indicate three groups of basins with similar variability in the SL elevation. The first includes basins with maximum elevations above 1500 m a.s.l. (Poprad, Upper Váh, Hron, Hornád). Winter median SL is equal or close to minimum basin elevation in snow rich winters in these basins. Even in snow poor winters is SL close to the basin mean. Second group consists of mid-altitude basins with maximum elevation around 1000 m a.s.l. (Slaná, Ipeľ, Nitra, Bodrog). Median SL varies between 150 and 550 m a.s.l. in January and February, which represents approximately 40–80% snow coverage. Median SL is near the maximum basin elevation during the snow poor winters. This means that basins are in such winters snow free approximately 50% of days in January and February. The third group includes the Rudava/Myjava and Lower Váh/Danube. These basins have their maximum altitude less than 700 m a.s.l. and only a small part of these basins is covered with snow even during the snow rich winters. The evaluation of SCA shows that snow cover typically starts in December and last to February. In the highest basins (Poprad, Upper Váh), the snow season sometimes tends to start earlier (November) and lasts to March/April. The median of SCA is, however, less than 10% in these months. The median SCA of entire winter season is above 70% in the highest basins (Poprad, Upper Váh, Hron), ranges between 30-60% in the mid-altitude basins (Hornád, Slaná, Ipeľ, Nitra, Bodrog) and is less than 1% in the Myjava/Rudava and Lower Váh/Danube basins. However, there is a considerable variability in seasonal coverage between the years. Our results indicate that there is no significant trend in mean SCA in the period 2001-2014, but periods with larger and smaller SCA exist. Winters in the period 2002-2006 have noticeably larger mean SCA than those in the period 2007-2012. Snow depletion curves (SDC) do not have a simple evolution in most winters. The snowmelt tends to start between early February and the end of March. The snowmelt lasts between 8 and 15 days on average in lowland and high mountain basins, respectively. Interestingly, the variability in SDC between the winters is much larger than between the basins.
Mixed evergreen-deciduous broadleaved forest is the transitional type of evergreen broadleaved forest and deciduous broadleaved forest, and plays a unique eco-hydrologic role in terrestrial ecosystem. We investigated the spatiotemporal patterns of throughfall volume of the forest type in Shennongjia, central China. The results indicated that throughfall represented 84.8% of gross rainfall in the forest. The mean CV (coefficient of variation) of throughfall was 27.27%. Inter-event variability in stand-scale throughfall generation can be substantially altered due to changes in rainfall characteristics, throughfall CV decreased with increasing rainfall amount and intensity, and reached a quasi-constant level when rainfall amount reached 25 mm or rainfall intensity reached 2 mm h–1. During the leafed period, the spatial pattern of throughfall was highly temporal stable, which may result in spatial heterogeneity of soil moisture.