Land use change and climate dynamics in the Rift Valley Lake Basin, Ethiopia

Association of temperature and precipitation with malaria incidence in 57 countries and territories from 2000 to 2019: A worldwide observational study

Background

The transmission of malaria is known to be affected by climatic factors. However, existing studies on the impact of temperature and precipitation on malaria incidence offer no clear-cut conclusions, and there is a lack of research on a global scale. We aimed to estimate the association of temperature and precipitation with malaria incidence globally from 2000 to 2019.

Methods

We used meteorological data from the National Centers for Environmental Information and malaria incidence data from the Global Burden of Disease Study 2019 to calculate effect sizes through quasi-Poisson generalised linear models while controlling for confounders.

Results

231.4 million malaria cases occurred worldwide in 2019. National annual average temperature and precipitation were associated with malaria incidence, with an increase in the age-standardised incidence rate (ASIR) of 2.01% (95% confidence interval (CI) = 2.00, 2.02) and 6.04% (95% CI = 6.00, 6.09) following one unit increase of national annual average temperature and precipitation. In subgroup analysis, we found that malaria incidence in Asian countries was most affected by temperature, while the incidence in African countries was most affected by precipitation (P < 0.05). Stratified by age, children under five were most affected by both temperature and precipitation (P < 0.05). We additionally found that the impact of the national annual average temperature on malaria incidence increased over time (P < 0.05).

Conclusions

We advocate for a comprehensive approach to malaria prevention, focussed on addressing the impact of climate factors through international collaboration, adaptive measures, and targeted interventions for vulnerable populations.

A study of land use changes and its impacts on flood inundation in the Konkoure River Basin, Republic of Guinea

Due to rising land development, mitigating the negative effects of land use change is becoming a problem. Understanding how land development affects flood inundation is critical for long-term water resource management. This study evaluates the land use change in the Konkoure River Basin and its impact on flood inundation. The land use changes were assessed using Landsat image (level 1) in August 2006 and August 2021. In addition, we used GIS and remote sensing applications to assess the degree of changes that took place in the Konkoure watershed. According to the findings, 32.16% of the total area became built-up areas, and 35.51% was converted to other land uses in Konkoure watershed. Konkoure's most significant change is that 29.50% of forest area transformed into built-up areas and other land uses. The rainfall-runoff-inundation model (RRI) based inundation of the Konkoure River Basin was compared to the MODIS extent between 31 August 2006 and 30 August 2021 flood events. Flood inundation variations in the Konkoure watershed were studied in terms of inundation area, peak inundation depth, runoff volume, and the infiltration rate. As a result, the flood inundation area increased from 139.98 to 198.72 km2 and the infiltration rate decrease from 7 to 5 mm/h. Moreover, we used flow duration curves (FDCs) to fully comprehend the streamflow processes. The result indicates that the Konkoure watershed has experienced flooding partly due to land use change.

Remote sensing and GIS-based study of land use/cover dynamics, driving factors, and implications in southern Ethiopia, with special reference to the Legabora watershed

This paper investigates the trends, drivers, and consequences of LULC changes in Legabora watershed, Ethiopia, by utilizing remote sensing and geographic systems. Landsat Maltispectiral scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper (ETM+), and Operational Land Imager (OLI) images of years 1976, 1991, 2001, and 2022, respectively, were used to study the dynamics of LULC. Essential image pre-processing steps were carefully carried out to correct distortions caused by sensor limitations. Eight main LULC categories were identified based on supervised image categorization methods and the maximum likelihood classification algorithm.The findings of change detection and cross-tabulation matrix demonstrate that there has been a significant increase in the area of cropland 345.1 ha/year, settlement 5.9 ha/year, forest 38.2 ha/year, and degraded lands 2.56 ha/year, respectively, over the period between 1976 and 2022. In contrast, considerable decreases were observed in grasslands (-248 ha/year) and shrublands (-144 ha/year), whereas other LULC categories augmented. The results revealed that the overall accuracy rates stood at 88.3 %, 88.4 %, and 85.6 % for 1976, 1991, and 2022, respectively. The overall kappa coefficient demonstrated values of 0.86 %, 0.86 %, and 0.83 % for the same period. Surveyed respondents perceived population growth, settlement, agricultural expansion, and infrastructure development as the most noticeable drivers of these LULC changes. In contrast, deforestation, land degradation, lack of livestock fodder, and biodiversity loss were identified as the main consequences of LULC changes. The factors and implications addressed in this study may be helpful tool for the formulation and implementation of evidence-based land use policies and strategies within in the study area and elsewhere.

An analysis of LULC changes for understanding the impact of anthropogenic activities on food security: a case study of Dudhganga watershed, India

Although the Dudhganga watershed is the primary water and food resource of the Kashmir Valley, it has undergone significant changes in food resources and strategies due to rampant urbanization in the area over the past 20 years. This urbanization has had a profound impact on the watershed and has also affected land use and land cover (LULC) patterns and environmental changes. The objective of this study is to investigate the effects of urban development on food security parameters in the Dudhganga watershed area, India, from 2000 to 2020, by evaluating LULC changes. Additionally, the study aims to examine the relationship between climate changes and LULC indices, such as the Modified Normalized Difference Water Index (MNDWI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI). The results indicate a 21.66% increase in barren areas, at the expense of snow-covered lands, during the 2000-2020 period. The primary land cover transition observed is towards barren areas. The predictions for LULC in 2030 highlight the need for careful management of land use and climate changes in the study area. This study can assist local government officials in reassessing food strategies by identifying areas where urban expansion should be controlled and climate impacts minimized, to prevent local hunger and ecological degradation. Therefore, the development of systematic urban planning approaches and mitigation of climate change sources are crucial. Furthermore, the adoption of advanced agricultural technology should be considered to mitigate the impact of urban expansion.