Search

Located in the hyper-arid regions of Algeria, the M'zab Wadi basin has historically experienced severe flash flooding, causing severe economic damage and loss of life. Identifying potential flood hazard areas in such an arid environment, challenged by data scarcity, is necessary to forecast flood and to create early warning strategies. The paper aims to map and highlight potential flood hazard areas in the M'zab Wadi basin using geographic information system coupled with the Analytical Hierarchy Process method based on seven related flood hazard factors. The accuracy of the flood hazard map was validated using the Receiver Operating Characteristic based Area Under Curves method. The results show that 3.04% (50.35 km2) and 0.53% (8.74 km2) of the basin area are under high and very high flood vulnerability levels, respectively. The obtained results can offer significant insights to policymakers and decision-makers to make well-informed judgments regarding the effectiveness of flood protective infrastructure/measures. Furthermore, the approach adopted can be advantageous for other regions under similar conditions. [ABSTRACT FROM AUTHOR]

Water is a fundamental human right and a prerequisite for sustainable development because it is an essential element of existence. Notwithstanding, a huge part of the world's population continues to face challenges in accessing clean and safe drinking water. This situation is particularly pronounced in arid and underdeveloped regions where there is a global water crisis that is a huge threat to human health, economic development, and environmental stability. Designed with solar energy, the award-winning "Parabosol" enhances water evaporation and purifies it simultaneously. Parabosol does not require any expensive machines or complicated infrastructural frameworks, making it both cost-effective and efficient for such vulnerable communities. Transporting it easily allows for quick deployment in remote areas during emergencies, ensuring a clean, dependable water supply for basic household use. This innovative measure, which reduces the risk of waterborne diseases and increases access to safe water resources within communities, could greatly contribute to public health promotion efforts. It is intended for daily performance that corresponds to the minimum needs of one family unit (no less than 35 L per person). The processing capacity of each station varies between 120 and 180 L of water per day (depending on geographical and environmental conditions), depending on geographical and meteorological (solar radiation values) factors. However, experimental values are around 250 L. Parabosol illustrates a novel model with its distinctive design and functionality, highlighting the critical role of clean energy in the development of a more sustainable and resilient future. Additionally, unlike macrosystems that require a substantial initial investment and ongoing operating costs, Parabosol is a portable solution that has the potential to address the issue of clean water scarcity in the future. [ABSTRACT FROM AUTHOR]

Background: Endemism is essential in biodiversity, biogeography, and conservation tasks. Based on herbarium specimens kept in some local herbaria, many published literature, and available information, we compiled a comprehensive list and an updated assessment of the Egyptian endemic and near-endemic taxa. The application of quantitative approaches to the distribution patterns, conservation status, and habitat preference of endemic taxa in Egypt was provided. Comparisons of the near-endemic taxa with other neighbouring flora were explained. For each taxon, the distribution patterns, most preferable habitat, biological spectrum, and taxa among 14 phytogeographical regions (Operational Geographical Units; OGUs) of Egypt were determined. Results: In this study, 19 endemics (out of 70) and 76 near-endemics (out of 181) are newly added taxa. Differentiation indices represented the taxonomic degrees of differentiation among endemic taxa. Two different indices were used to assess endemism: single-region endemic taxa (SRET) and multiple-region endemic taxa (MRET). Most endemic and near-endemic taxa were recorded from the mountainous Sinai (S) and the Mareotis sector of the Mediterranean coastal land (Mm). Generally, the most represented families in endemic and near-endemic areas were Asteraceae, Caryophyllaceae, Lamiaceae, and Fabaceae. More than 60% of the endemic taxa occurred in the sandy plains, wadis (desert valleys), and rocky plains and mountains. Applying hierarchical cluster analysis to the occurrences of 70 endemic taxa in the 14 studied OGUs revealed five main floristic groups (I–V), each characterized by certain OGUs. We provided eight groups of near-endemic taxa that represented their extension in neighbouring countries. Conclusions: The presented data will help to fill the gap in our knowledge of endemism, provide baseline information to understand biogeographical processes and facilitate further cooperation toward conservation purposes. [ABSTRACT FROM AUTHOR]

The Shule River Basin (SRB) is a typical arid area in northwest China with a fragile ecology. Understanding vegetation dynamics and its response to climate change and human activities provides essential ecological and environmental resource management information. This study extracted fractional vegetation coverage (FVC) data from 2000 to 2019 using the Google Earth Engine platform and Landsat satellite images, employing trend analysis and other methods to examine spatiotemporal changes in vegetation in the SRB. Additionally, we used partial correlation and residual analyses to explore the response of FVC to climate change and human activities. The main results were: (1) The regional average FVC in the SRB showed a significant upward trend from 2000 to 2019, increasing by 1.3 × 10−3 a–1. The area within 1 km of roads experienced a higher increase of 3 × 10−3 a–1, while the roadless areas experienced a lower increase of 1.1 × 10−3 a–1. The FVC spatial heterogeneity in the SRB is significant. (2) Partial correlation analysis shows that the FVC correlates positively with precipitation and surface water area, with correlation coefficients of 0.575 and 0.744, respectively. A weak negative correlation exists between the FVC and land surface temperature (LST). FVC changes are more influenced by precipitation than by LST. (3) The contributions of climate change to vegetation recovery are increasing. Human activities, particularly agricultural practices, infrastructure development, and the conversion of farmland to grassland, significantly influence vegetation changes in densely populated areas. (4) The area changes of different land types are closely related to climate factors and human activities. Increased construction, agricultural activity, and converting farmland back to grassland have led to an increase in the area proportions of "impervious surfaces", "cropland", and "grassland". Climate changes, such as increased rainfall, have resulted in larger areas of "wetlands" and "sparse vegetation". These results provide valuable information for ecosystem restoration and environmental protection in the SRB. [ABSTRACT FROM AUTHOR]

This research proposes a 10-step methodology for developing an enhanced IAQ dashboard and classroom index (CI) in higher educational facilities located in arid environments. The identified parameters of the enhanced IAQ dashboard–inspired by the pandemic experience, result from the literature review and the outcome of two electronic surveys of (52) respondents, including health professionals and facility management experts. On the other hand, the indicators included in the CI are based on (80) occupant survey responses, including parameters related to IAQ, Indoor Environmental Quality (IEQ), and thermal comfort, amongst other classroom operative considerations. The CI is further tested in four learning spaces at the American University in Cairo, Egypt. The main contribution of this research is to suggest a conceptual visualization of the dashboard and a practical classroom index that integrates a representative number of contextual indicators to recommend optimal IAQ scenarios for a given educational facility. This study concludes by highlighting several key findings: (1) both qualitative and quantitative metrics are necessary to capture indoor air quality-related parameters accurately; (2) tailoring the dashboard as well as the CI to specific contexts enhances its applicability across diverse locations; and finally, (3) the IAQ dashboard and CI offer flexibility for ad-hoc applications. [ABSTRACT FROM AUTHOR]

Permeable surface mapping, which mainly is the identification of surface materials that will percolate, is essential for various environmental and civil engineering applications, such as urban planning, stormwater management, and groundwater modeling. Traditionally, this task involves labor-intensive manual classification, but deep learning offers an efficient alternative. Although several studies have tackled aerial image segmentation, the challenges in permeable surface mapping arid environments remain largely unexplored because of the difficulties in distinguishing pixel values of the input data and due to the unbalanced distribution of its classes. To address these issues, this research introduces a novel approach using a parallel U-Net model for the fine-grained semantic segmentation of permeable surfaces. The process involves binary classification to distinguish between entirely and partially permeable surfaces, followed by fine-grained classification into four distinct permeability levels. Results show that this novel method enhances accuracy, particularly when working with small, unbalanced datasets dominated by a single category. Furthermore, the proposed model is capable of generalizing across different geographical domains. Domain adaptation is explored to transfer knowledge from one location to another, addressing the challenges posed by varying environmental characteristics. Experiments demonstrate that the parallel U-Net model outperforms the baseline methods when applied across domains. To support this research and inspire future research, a novel permeable surface dataset is introduced, with pixel-wise fine-grained labeling for five distinct permeable surface classes. In summary, in this work, we offer a novel solution to permeable surface mapping, extend the boundaries of arid environment mapping, introduce a large-scale permeable surface dataset, and explore cross-area applications of the proposed model. The three contributions are enhancing the efficiency and accuracy of permeable surface mapping while progressing in this field. [ABSTRACT FROM AUTHOR]

Biological nitrogen fixation (BNF) is a well-known synergistic mechanism between specific bacteria and plants that converts atmospheric nitrogen (N≡N) to plant-available forms. Biochar, a soil amendment, can significantly affect symbiotic activities and legume growth. This meta-analysis was conducted to evaluate the quantitative responses of various legume plants to biochar application under various soils, biochars, and climatic conditions. The data from 96 manuscripts were analyzed with regard to biomass, number of nodules, nodule weight, and BNF values of different legumes. We identified improvements in nodulation, BNF, and biomass production in response to biochar application in cool-season and forage legumes, compared to grain and warm-season legumes. Biochar enhancement of BNF and plant biomass was much higher in sandy and loamy soils in comparison to clay soils. The addition of biochar to soil with low N content, carbon (C), and cation exchange capacity (CEC) increased nodule formation, BNF, and plant biomass, compared to more fertile soils. Biochar produced under low pyrolytic temperatures (≤ 550 °C) from plant residues with high C content (> 50%), pH < 8, and CEC > 20 cmol kg−1 had greater improvement in BNF and plant biomass in comparison with other types of biochar. The optimum biochar rate to increase BNF and plant biomass was about 10 − 30 tons ha−1. Overall, the biochar increased the number of nodules, nodule weights, BNF, and biomass production of leguminous plants by about 13%, 12%, 28%, and 22%, respectively. [ABSTRACT FROM AUTHOR]