European Journal of Science, Innovation and Technology

Design of Protective Structures to Anticipate Flood-Induced Damage to the Jenelata Bridge Abutment

Annisa Magefirah Darmawan, Basyar Bustan, Andi Maal Latief — Thu, 02 Oct 2025 17:36:39 +0300

The extreme flood in January 2019 caused significant damage to the Jenelata Bridge in Gowa Regency, including the collapse of protective structures and disruption of abutment stability. This study aims to design protective structures capable of preventing similar damage in the future. The methodology includes hydrological and hydraulic analysis, geotechnical evaluation, and assessment of gabion effectiveness as an alternative protective structure. Results indicate that a 100-year return period flood generates a peak discharge of approximately 1058 m³/s, which poses a high risk of scouring along the riverbanks. A Type-C gabion structure with dimensions of 4 × 1 × 1 m was designed for a total length of 100 m (50 m upstream and 50 m downstream) to protect the abutment. Stability analysis confirmed the structure's ability to withstand water and soil pressures with adequate safety factors. The estimated construction cost is Rp 346,190,130. This study recommends gabions as an effective solution for the rehabilitation of Jenelata Bridge to ensure sustainable transport connectivity in flood-prone areas.

The Impact of Agricultural Concessions on the Work of Farmers and on the Surrounding Villages in the Urban Rural Commune of Maluku in Kinshasa (DRC)

G. KAYEMBE KABASELE, M.R. MPURU, M.M. NYOKA, J.C. MASHINYI DIMBHITA — Wed, 15 Oct 2025 00:00:00 +0300

Maluku, being the largest of Kinshasa's peripheral communes, is unable to produce enough food crops to meet the needs of the city’s population. One of the key causes of this insufficient production is the poor use of many agricultural concessions, which limits farmers’ access to large, arable land areas. This limited production restricts farmers’ ability to sell in sufficient quantity to generate income that could improve their diets and support the development of their villages. As a result, famine and poverty remain persistent in this urban-rural zone of Maluku. We therefore propose the following measures to the Provincial Government of Kinshasa: reclaim all unused agricultural concessions; redistribute the recovered land to active local farmers; provide technical support to farmers in Maluku; offer financial assistance to support agricultural activity; build and repair rural access roads for agriculture; regulate and inspect private vehicles transporting food products, to ensure farmer safety; prohibit and intervene against the uncontrolled conversion of agricultural land into poorly planned residential areas.

Secondary Agricultural and Non-Agricultural Activities Exercised by the Peasant Populations in the Localities of the Urban-Rural Commune of Maluku in Kinshasa (DRC)

G. KAYEMBE KABASELE, L.L. NSHIMBA, M.R. MPURU, R. KAKULE — Wed, 15 Oct 2025 00:00:00 +0300

Due to unsatisfactory agricultural yields, many farmers engage in alternative activities during the lean season. The primary goal is to generate additional income to help meet basic family needs. These activities also contribute to improving household nutrition. However, despite their efforts, the income earned from these activities often remains insufficient in light of the many challenges these farmers face. The main alternative agricultural activities include market gardening, with a focus on short-lifecycle vegetables that are highly perishable and produced in small quantities due to local climate conditions. Other common non-agricultural secondary activities include: fishing, hunting, charcoal and firewood production, poultry farming, gathering wild fruits, and some artistic crafts and activities.

Malaria Risk Modelling Based on Household and Environmental Mosquito-Breeding Points: Application to Makueni County, Kenya

James M. Malusha — Thu, 16 Oct 2025 00:00:00 +0300

A sociocultural–spatial modelling approach was applied to model household-level malaria risk in Makueni County, Kenya. Using household surveys (N = 80 households sampled across affected and unaffected areas), larval habitat mapping and sociobehavioural data on vector control, we screened candidate predictors, ran Pearson correlations, and developed a stepwise multiple regression model to predict malaria incidence (household-level). We then produced a spatial risk surface using inverse distance weighting (IDW) in a GIS to identify very-low to very-high risk zones based on the combined contribution of the most important predictors. Key predictors retained in the final model were: proximity to surface water/irrigation, presence of puddles/animal hoof-prints near the house, frequency of open water storage, house eave status (open vs closed), use of insecticide-treated nets (ITNs), indoor residual spraying (IRS) history, presence of livestock near house, and solid-waste accumulation. The final model explained a large proportion of the variation in household malaria incidence (Adjusted R² = 0.87) and can guide targeted larval source management and household interventions in Makueni County.