Current Research on Geography, Earth Science and Environment Vol. 11

Assessment of Borehole Water Location in Relation to Distance from Septic Tanks Across Urban Residential Neighbourhoods in Port Harcourt Metropolis, Rivers State

2026-11-10T11:45:34+00:00

Boreholes and septic tanks are widely used in residential neighbourhoods of Port Harcourt metropolis, making appropriate separation important for groundwater protection. This study assessed borehole siting in relation to septic-tank distance and examined factors associated with compliance with the 30 m setback benchmark used in the manuscript. A cross-sectional design was adopted across six neighbourhood categories. Borehole-to-septic-tank distances were measured, water samples were collected over six months, and respondents' perceptions of compliance determinants were assessed. Statistical analysis included one-sample t-tests, one-way ANOVA with Duncan's post hoc test, and Spearman's rank correlation. Mean separation distances ranged from 14.04 m in the Rumuokoro-Rumuola-Rumuomasi axis to 21.06 m in outskirts and expanding residential areas. All neighbourhood categories were below the 30 m benchmark, with mean shortfalls ranging from 8.94 to 15.96 m; the reported one-sample tests were statistically significant (p = 0.000). Weighted mean scores for perceived determinants ranged from 3.96 to 4.12, with high building density (WM = 4.12) and poor urban planning (WM = 4.11) among the highest-rated factors. Correlations among the identified determinants were strong and positive (r = 0.810–0.920, p < 0.05). The findings indicate widespread setback non-compliance and interrelated institutional, spatial, socio-economic and behavioural constraints, supporting strengthened development control, monitoring, urban planning and public awareness.

Vegetation Responses and Community Livelihood Adaptation to Climate Variability in the Central Himalaya

2026-11-10T11:50:42+00:00

High-altitude alpine meadows are climate-sensitive socio-ecological systems where climatic variability influences vegetation dynamics and community livelihoods. This chapter integrates community perceptions from 175 respondents with MODIS MOD13Q1 NDVI data (2004–2024) across low-, mid-, and high-elevation zones of Byans Valley, Central Himalaya. The findings indicate widespread perceptions of rising temperatures (90%), declining snowfall (89%), altered seasonal timing (86%), shorter winters (84%), changes in agricultural practices (83%), and declining fuel, fodder, and medicinal resources (70%). NDVI analysis revealed a clear elevational gradient, with vegetation greenness generally decreasing with increasing elevation. Recent peak NDVI values were approximately 0.70, 0.60, and 0.50 in the low-, mid-, and high-elevation zones, respectively, with stronger recent vegetation activity particularly at higher elevations. These patterns indicate changes in the seasonal functioning and timing of alpine vegetation rather than a simple increase in productivity. Weak relationships between NDVI and individual climatic variables further suggest that vegetation responses are controlled by multiple interacting factors, including temperature, precipitation, snowmelt, soil moisture, grazing, and land-use practices. The study recommends long-term phenological monitoring, integration of satellite observations with field-based biomass, species composition and soil-moisture measurements, and the strengthening of community-based monitoring of climate and natural resources. Future studies should incorporate long-term temperature, precipitation and snow-cover records with species-level phenology, grazing intensity, biomass measurements, and livelihood data to identify the mechanisms driving vegetation changes along elevation gradients. Such integrated research will support evidence-based conservation and climate-adaptive livelihood planning in the Byans Valley.

Assessing the Impact of Climate Change on Agricultural Production among Smallholder Farmers in Ga-Ramokgopa Village, Molemole Local Municipality, Limpopo Province

2026-11-10T11:55:32+00:00

Aims: This study aimed to assess the impact of climate change on agricultural production among smallholder farmers in Ga-Ramokgopa Village, Molemole Local Municipality, Limpopo Province, South Africa. It also examined farmers’ perceptions of climate change and the adaptation strategies they use to manage its effects.

Study Design: The study adopted a quantitative research design.

Place and Duration of Study: The study was conducted in Ga-Ramokgopa Village, Molemole Local Municipality, Limpopo Province, South Africa. Data were collected in 2025.

Methodology: A total of 45 questionnaires were distributed to smallholder farmers, of which 35 were returned and included in the analysis, representing a response rate of 77.8%. Data were collected using structured questionnaires and analysed using descriptive statistics, including frequencies and percentages, in the Statistical Package for the Social Sciences (SPSS), version 26. The analysis focused on farmers’ perceptions of climate change, its effects on agricultural production, and the adaptation strategies employed.

Results: The findings revealed that increased temperatures (51.4%) were the most commonly observed climate change indicator, followed by irregular rainfall (22.9%) and increased droughts (20.0%). Most respondents (82.9%) attributed climate change to human activities. The main reported effects on agricultural production were reduced crop yields (37.1%), water shortages (22.9%), crop failure (14.3%) and reduced grazing land (14.3%). Using drought-resistant crops was the most common adaptation strategy (42.9%), followed by mulching and soil conservation (17.1%). However, 62.9% of respondents reported receiving no external support for climate change adaptation.

Conclusion: Respondents reported adverse effects of changing climatic conditions on agricultural production and rural livelihoods in Ga-Ramokgopa Village. Strengthening agricultural extension services, improving access to climate information and affordable farming inputs, and supporting climate-smart agricultural practices are important for improving smallholder farmers’ resilience.

GeoAI-Driven Groundwater Potential Zone Mapping in Devanahalli, Bengaluru Rural, Karnataka, India

2026-11-10T12:00:57+00:00

Aims: To develop an integrated GeoAI framework for mapping groundwater potential zones in Devanahalli, Bengaluru Rural, and to interpret the spatial influence of major hydrogeological and terrain controls for groundwater exploration and recharge planning.

Study Design: Geospatial groundwater-potential assessment integrating remote sensing, GIS-based thematic analysis and a machine-learning-oriented decision framework.

Place and Duration of Study: Devanahalli Taluk, Bengaluru Rural District, Karnataka, India. The analysis uses the spatial datasets and thematic products assembled for the 2026 study.

Methodology: Groundwater-conditioning layers representing elevation, slope, drainage, lineaments, land use/land cover, soil, geology, rainfall and related terrain characteristics were prepared and standardised in a GIS environment. Their hydrogeological significance was evaluated and integrated in a GeoAI workflow that links spatial preprocessing, feature extraction, model development, groundwater-potential prediction, zonation and validation. The final potential classes were interpreted together with observed terrain, drainage and structural patterns.

Results: The analysis indicates that groundwater favourability in Devanahalli is spatially heterogeneous. Lower-relief and gently sloping zones favour infiltration, whereas steeper terrain and densely drained sectors promote runoff. Structural discontinuities represented by lineaments provide potential pathways for groundwater storage and movement in the hard-rock setting. Agricultural, vegetated and less-impervious surfaces are comparatively supportive of recharge, while expanding built-up areas can restrict direct infiltration. The integrated groundwater-potential map delineates very high, high, moderate, low and very low potential zones and provides a spatial basis for prioritising groundwater investigation and recharge interventions.

Conclusion: Integrating geospatial evidence with GeoAI offers a reproducible framework for groundwater-potential assessment in rapidly urbanising hard-rock terrains. The resulting zonation can support borewell investigation, artificial recharge, rainwater harvesting, land-use planning and long-term groundwater management in Devanahalli.