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This paper presents an attempt to estimate the value of Probable Maximum Precipitation (PMP) over the Kielce Upland for one-day and multi-day intervals. Statistical methods were employed in the calculations. Precipitation data were obtained from 23 gauging stations. A regional frequency factor km (from Hershfield’s formula) was calculated for each station based on a series of maximum annual precipitation totals from 1961 to 2006. The calculated PMP values range from 120.7 mm to 228.4 mm (within the 1-day precipitation group), from 140.7 mm to 266.3 mm (2-day group), from 158.9 mm to 294.1 mm (3-day group), and from 175.2 mm to 294.8 mm (4-day group). These values became reference values used to show the spatial distribution of PMP throughout the Kielce Upland region.
This article shows the characteristics of spatial differentiation of level and dynamics of socio-economic development of rural areas in Poland. The Authors try to define typical directions of the development of gminas and look for an answer to the question: what, and what gminas’ features, determine the direction of development? The analysis presented in the paper has been based on the data originating from the Rural Development Monitoring Project. The results showed the differentiation of the development level to be a part of very dynamic contemporary reality. Criteria up to this date documented in research and arranging spatial diversity of social and economic phenomena apply specifically to description of the development’s level, while dynamics is being arranged by a different criteria. Moreover, the research describes four basic profiles of the dynamics of gminas’ development.
The Xilin Gol area is located in central Inner Mongolia, China. It had been a fertile prairie in northern China, but desertification and sand storms have increased in past decades. This study shows the spatial and temporal distribution of sand storms in the Xilin Gol area. The results of the analysis show: (i) Factors such as strong winds (usually beyond seven levels), rain and temperature have an impact on sand storms. The correlation coefficient between sand storm days and strong wind days is 0.89. (ii) There are more sand storm days in the west than in the east. (iii) In the last 30 years, the frequency of sand storms have been consistently decreasing.
The paper presents the concept of soil temperature coefficient, as a ratio of soil temperature in the given point on the area of a basin and soil temperature in the basal point located within the watershed. For modelling the distribution of the soil temperature coefficient depending on selected soil and physiographic parameters, artificial neural networks (ANN) were used. ANN were taught based on empirical data, which covered measurements of soil temperature in 126 points, in the layer of soil at the depth of 0–10 cm, within the area of the Mątny stream basin located in the Gorce mountain range of West Carpathians. The area size of the basin amounts to 1.47 km2. Temperature was measured by means of a TDR device. The soil and physiographic parameters included: slopes, flow direction, clay content, height above sea level, exposition, slope shape, placement on the slope, land-use, and hydrologic group. Parameters were generated using DEM of 5m spatial resolution and soil maps, using the ArcGIS program. The MLP 10-8-1 model proved to be the best fitted neural network, with 8 neurons in the hidden layer. The quality parameters were satisfactory. For the learning set, the quality parameter amounted to 0.805; for the testing set, 0.894; and for the validating set, 0.820. Global sensitivity analysis facilitated the assessment of percentage shares, contributing to the soil temperature ratio. Land use (25.0%) and exposition (20.5%) had the highest impact on of the aforementioned ratio, while the placement on the slope and flow direction had the lowest impact.
Spatial distribution of heathlands in Pomerania (the north-western part of Poland) was described based on the results of questionnaires sent out to the registered offices of all forest divisions (96), national (4) and landscape (15) parks of this area. According to the inventory, heathlands occur in 28 forest divisions and 3 national and landscape parks. The frequency of occurrence and the area covered by heathlands were determined. All the data were compiled in the form of a spatial database with the use of Geographic Information Systems. The paper also contains the geographical distribution of heath habitats in the area of Pomerania according to particular syntaxa. Additionally, the content of the database CORINE Land Cover was analysed at the third level for the area of Pomerania, completed for the years of 2000 and 2006. The area and the number of patches were described according to three land cover categories: heaths (code 322), conflagration sites (code 334) and peat bogs (code 412).
Spatial statistics allows to assess geographic distribution of phenomena – its concentration, magnitude and orientation of dispersion as well regularity or trends in occurrence within a space. The paper presents adaptation of point-based methods to measure spatial distribution of areal phenomena that concern agriculture: area of agricultural land, area of fertile agricultural land and soil pH. The source data in a form of chorochromatic maps (e.g. a vector soil map) are processed to 1 x 1 km grid data with use of the algorithm created in Model Builder. The research area – Lower Silesia – characterizes various environmental conditions that results in changeability of agricultural land productivity. Spatial statistics performed for a whole region would bring only global information on spatial distribution. Hence the Authors propose to conduct analysis within subareas that depict local changeability of studied phenomena. As the research is conducted in agricultural context, the subareas of similar agricultural land areas are created regarding the administrative units. Spatial distribution is described by: mean centre, standard distance and standard deviational ellipse. All three measures are weighted by a variable (i.e. the intensity of the phenomenon) as spatial distribution is not only about location, but the value of the phenomenon in particular location is important. Measures of spatial distribution drawn on a map yields clear and usually easy to interpret information on spatial character of a phenomenon. In some cases it may be useful to present these qualitative characteristics complemented with another type of cartographic visualization (e.g. a choropleth map. This paper presents maps about the application of spatial distribution measures into assessment of agricultural land productivity in the research.
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