Geographica Pannonica

Spatio-temporal Analysis of Drought Trends Recorded during the Wettest Months in the Mouhoun-Comoé Basin in Burkina Faso (Africa): an Analysis using Z-score and Linear Regression

2025-07-03T21:20:54+02:00

Meteorological drought is a natural phenomenon that occurs when there is insufficient rainfall over a more or less prolonged period. In West African countries, and particularly in Burkina Faso, this situation undermines agricultural systems. Knowledge of the spatio-temporal trends of drought is essential for optimal management of water resources and effective planning of sustainable agricultural activities. The aim of this study is the analysis of the spatio-temporal trends of drought in the Mouhoun-Comoé basin in Burkina Faso. To this end, the study used CHIRPS rainfall data in raster and CSV file form for July and August, as well as soil moisture (0-10 cm) at 1-, 2- and 3-month scales for the period 1994-2024. The data were analysed using the z-score index, linear regression and correlation. The study shows that the upward trend in drought oscillates between extreme drought and mild drought. The decade 1994-2004 was characterised by extreme drought, followed by a decrease in drought throughout the basin during the decade 2005-2014. Finally, in the decade 2015-2024, a phase of high humidity was observed throughout the basin. Drought trends have had an impact on soil moisture levels, particularly in the valleys of the basin. This situation has a negative impact on agricultural production in the basin. This situation is forcing farmers to use crops that have more or less water tolerance in order to cope with the drought.

Fine-scale Mapping of Heat-hazard Risk and Vulnerability Using Geo-spatial Techniques: Insights from a Tropical Indian City

2025-07-03T21:20:55+02:00

Unprecedented extreme heat events (EHEs) have amplified associated health risks, but they present great differences within the urban environment. This paper aims to assess heat-hazard risk (HHR) and associated vulnerability in Nagpur, a heat-prone Indian city using remotely sensed and on-site meteorological data. HHR was generated through high resolution local climate zone (LCZ) maps via the product of hazard and vulnerability which featured census-tract socio-economic variables (sensitivity and adaptive capacity) and exposure. Principal component analysis (PCA) with equal weighting was applied to develop a composite fine-scale heat vulnerability index (HVI). Out of 136 wards, a total of 68 wards were identified to have ‘high’ or ‘very high’ HVI featuring about 49.06% of the population. LCZ-based spatial mapping showed a heterogeneous heat ‘risk-scape’ across the city. ‘High’ and ‘very high’ heat vulnerability/risk (HV/R) signature was observed in city core, its adjoining areas (LCZs 3 and 3_F) and urban fringes (LCZs 9 and 9₃). Conversely, open areas with moderate vegetation cover and natural classes (LCZs 6, 6B, A and B) showed ‘moderate’ to ‘low’ HHR. The findings of this research will enable the urban practitioners and policymakers to deal with explicit determinants of heat vulnerability and risk especially in regions with low adaptive capacity.

Hydrological Shifts in the Carpathian Basin: Climate Change Impacts on Summer Low-flows

2025-07-03T21:20:55+02:00

To assess hydrological shifts in the Carpathian Basin, this study analyzes a 90-year summer minimum discharge dataset from 12 river stations. We reveal widespread, significant declines, with the most pronounced trends on the Danube showing an average decrease of (-8.9% per decade). Critically, we identify a systemic regime shift using Pettitt tests, with most changepoints occurring between 1968-1990. Self-Organizing Maps (SOMs) regionalize these trends into two clusters: a high-variability group (Danube/Sava) and a vulnerable, low-flow group (Tisza/Drava). These findings prove the region’s growing drought vulnerability and highlight the urgent need for adaptive water management.

Intracountry Regional Inequalities in the Context of the Socioeconomic Status of Selected European Countries

2025-07-03T21:20:55+02:00

The paper deals with the issue of intracountry inequalities in selected European countries with attention paid to the analysis of potential connections between the level of identified regional inequalities in the assessed countries and their socioeconomic status. Two frequently employed indicators were chosen to assess regional inequalities: Gross Domestic Product per capita in PPS and Income of Households per capita in PPS, employing the Gini coefficient and the coefficient of variation as the basic statistical measures. The obtained results refer to the highest level of regional inequalities in the countries of the former Socialist Bloc, while the strong influence of capitals was also confirmed in these countries on the level of inequalities. At the same time, the presumption that the decreasing socioeconomic status of the countries caused the increasing level of intracountry regional inequalities was largely confirmed.

Seasonal Variations in Thermal Perception of Urban Environments: Summer and Winter In-situ Assessment from a Central European Town

2025-07-03T21:20:55+02:00

Growing urbanisation, together with extreme weather events, negatively affects urban populations worldwide. Recent urban climate studies demonstrate that people-oriented approaches are needed to effectively target adaptation measures and thus improve urban populations’ well-being. In this study we used the in-situ approach of sketch mapping to identify thermally pleasant and unpleasant places during two seasons, summer and winter, in Ústí nad Orlicí, a Czech town. Generally, places perceived as the most thermally unpleasant, regardless of season, are parking lots near shopping centres, and these require priority attention from urban planners. Respondents consistently identified the planting of high greenery and the construction of shelters as preferred adaptation measures across both seasons. Our findings also point to a clear preference for more enclosed places.

Multiscale Analysis of Green Infrastructure Impacts on PM2.5 and PM10 Pollution in Delhi, India

2025-07-03T21:20:55+02:00

Urban air pollution, particularly from fine particulate matter (PM2.5 and PM10), poses critical environmental and public health challenges in rapidly urbanizing regions. This study presents a multiscale, seasonal analysis of the relationship between Green Infrastructure (GI) landscape characteristics and PM concentrations in Delhi, India. Using high-resolution Sentinel-2 imagery (2019–2021) and air quality data from 39 Central Pollution Control Board (CPCB) monitoring stations, we quantified 15 GI characteristics across five spatial scales (0.5–2.5 km) using NDVI. Empirical Bayesian Kriging was applied for spatial interpolation of PM values, and Otsu’s thresholding was used to delineate vegetated areas. Principal Component Analysis (PCA) and regression models revealed that compositional metrics—such as Class Area (CA) and Percentage of Landscape (PLAND)—showed consistent negative correlations with PM2.5 and PM10 levels across all scales and seasons. Configuration metrics, including Largest Patch Index (LPI), Edge Density (ED), and Aggregation Index (AI), exhibited scale- and season-specific influences, with stronger effects observed at broader spatial scales during winter and autumn. The findings suggest that both the quantity and spatial arrangement of urban vegetation significantly affect local air quality. The study underscores the need for scale-aware, evidence-based GI planning as a nature-based solution, supporting India’s airshed-level approach to urban pollution management. These insights offer practical guidance for urban policymakers and planners aiming to enhance air quality through strategic green infrastructure design.