Rapid urbanization and population growth are increasing municipal solid waste (MSW) generation in Ethiopian cities, yet locally specific data remain limited for effective planning and policy implementation. This study assessed MSW generation rates, composition, physicochemical properties, and future quantities in Hawassa City to support sustainable management and Ethiopia’s Solid Waste Management and Disposal Proclamation of 2025. Direct measurements were conducted over seven days for 384 households stratified by socioeconomic status (127 high-, 140 middle-, and 117 low-income), together with selected commercial, institutional, and street-sweeping sources. An independent truck-volume estimate of waste delivered to the disposal facility was obtained, physical composition determined, and selected physicochemical parameters analysed. Multiple linear regression (MLR) examined associations between household characteristics and per-capita generation, while geometric projections estimated future MSW quantities to 2045. The overall household per capita generation rate was 0.42 kg person ^−1 d ^−1 , with clear socioeconomic differentiation: 0.59, 0.38, and 0.28 kg person ^−1 d ^−1 for high-, middle-, and low-income households, respectively. The truck-volume method yielded a comparable city-wide rate of ∼0.40 kg person ^−1 d ^−1 . The MLR model was statistically significant ( R ^2 = 0.744) and confirmed a positive association with income status and a negative association with household size. Organic materials dominated the waste stream (60%), followed by plastics (20%). Food-waste fractions showed high moisture and lower estimated calorific values, while non-food fractions were drier and higher in energy potential. Population is projected to rise from 576 880 in 2026–1285 683 in 2045, increasing total MSW generation from 291 to 648 t d ^−1 under a constant per capita rate. Under a near total landfilling scenario the existing ∼6 ha disposal site is already overflowing and would reach theoretical capacity within ∼10 months at 2026 rates. These findings provide updated evidence for source separation, organic and recyclable recovery, collection planning and residual disposal infrastructure in Hawassa, and offer a practical basis for implementing the 2025 Proclamation.
Increased transpiration with warming is a growing concern in the Upper Colorado River Basin (UCRB), as plants’ use of subsurface storage diverts water that may otherwise contribute to streamflow. Prior in-situ studies suggest that plants continue transpiring during dry and warm periods by shifting water uptake to deeper soil layers; however, models used to simulate the effects of warming rarely capture these complex subsurface processes. Here, we used the integrated hydrologic model ParFlow-CLM to simulate the effects of 1.5 °C of warming under interannual precipitation variability in a representative headwater catchment of the UCRB. We modeled these meteorological scenarios using two different water stress formulations—one that assumes plants are limited by water stress in the topsoil, and another that allows increased reliance on deeper root zone storage when the shallow soil dries out. Accounting for shifts in water uptake depth led to higher modeled transpiration, especially during low-precipitation periods, and amplified increases in transpiration with warming relative to the simplified stress formulation. As a result, warming-induced declines in summer subsurface storage were larger when considering plants’ sustained use of deep root zone storage. The demonstrated effects of water stress formulation on transpiration and subsurface storage have important implications for future modeling studies that seek to understand the vulnerability of UCRB hydrology to growing interannual precipitation variability, and anthropogenic warming.
Accurate segmentation of urban street trees from street-level imagery supports tree inventory, ecological assessment, biodiversity monitoring, and smart-city planning. However, irregular crown boundaries, fragmented foliage, occlusion, background clutter, and class imbalance remain significant challenges. This paper presents UrbanTreeFormer, a boundary-aware CNN–Transformer architecture for fine-grained urban tree crown segmentation. The model integrates an EfficientNet-B3 encoder for local feature extraction, a Transformer bottleneck for long-range contextual modeling, an attention-gated decoder for selective feature refinement, and an auxiliary boundary-refinement head to improve crown delineation. A combined weighted cross-entropy, Dice, and boundary loss, alongside class weighting and oversampling, addresses the foreground–background imbalance and the moderate imbalance among species. UrbanTreeFormer was evaluated on the public Urban Street Tree Segmentation dataset comprising 3,949 images and 22 tree species, using binary foreground and species-wise multiclass segmentation protocols. On the 386-image held-out test set, binary segmentation achieved Accuracy of 0.9731 ± 0.0014, Precision of 0.8695 ± 0.0032, Recall of 0.9544 ± 0.0039, Dice of 0.9100 ± 0.0021, and IoU of 0.8349 ± 0.0033. Boundary evaluation yielded BF1 of 0.8810 ± 0.0027, Boundary IoU of 0.7890 ± 0.0040, ASSD of 2.08 ± 0.08 pixels, and HD95 of 6.95 ± 0.21 pixels. Species-wise evaluation achieved macro-averaged Dice and IoU scores of 0.8731 and 0.7778, respectively. UrbanTreeFormer achieved the highest mean performance among eight CNN-, attention-, and Transformer-based baselines, with statistically significant improvements over seven, although its difference from SegFormer was not statistically significant. Ablation studies verified the contribution of each architectural component, while robustness experiments demonstrated stability under moderate photometric variations but reduced performance under severe noise, blur, and compression. These findings highlight UrbanTreeFormer's potential for accurate urban tree crown segmentation and species-level monitoring.
Fengyun-3E (FY-3E) Microwave Temperature Sounder-III (MWTS-III) provides critical early-morning-orbit observations for global numerical weather prediction (NWP). However, the assimilation of its surface-sensitive channels over land remains challenging due to the high uncertainty in characterizing land surface temperature and emissivity. This study investigates the impact of assimilating FY-3E MWTS surface-sensitive channels, with a particular focus over land using a physical land emissivity model. Three parallel experiments were conducted using the China Meteorological Administration Global Forecast System. It is shown that assimilating surface-sensitive channels effectively improves low-level atmospheric analyses. In addition, data assimilation over land shows overall positive global impacts on analyses. A case study shows that, in forecasting the heavy rainfall event associated with Typhoon Gaemi (2024), the assimilation of surface-sensitive channels over land improves spatial distributions of 24–hour accumulated precipitation and achieves higher equitable threat scores at high precipitation thresholds mainly for the 120-hour forecasts. The enhanced performance may be explained by the wetter increments and analyses of specific humidity at lower levels near the typhoon center. Overall, this study demonstrates that assimilating FY-3E MWTS surface-sensitive channels effectively improves the analysis fields and heavy rainfall forecasts, offering valuable insights for their future application in NWP.
Public debate plays an important role in shaping responses to climate-related hazards such as drought. While considerable attention has been given to the physical dimensions of drought, less is known about how public debate shapes societal understanding of drought. This study examines how drought became socially recognized, framed and contested on social media in the Netherlands, a country traditionally more familiar with flood than drought management. Using a combination of social network analysis and AI-assisted classification of Dutch tweets posted between 2015 and 2022, we tracked the evolution of drought-related online communities and how they discuss and frame drought. The results show a shift from discussions of drought as a distant international issue towards a national challenge following the severe Dutch drought of 2018. As drought impacts became increasingly visible, discussions expanded beyond reporting impacts to include debates on climate change, agriculture, nature conservation and water governance. Competing frames emerged around responsibility for drought impacts and competing water demands between nature and agriculture. Some communities emphasized the role of historical land and water management practices in exacerbating drought vulnerability, while several climate-sceptical communities questioned the attribution of drought to climate change. In parts of the discussion, farmers were also portrayed primarily as victims rather than contributors to the problem. Nature-related impacts consistently received attention throughout the study period, both with nature being portrayed as a victim of drought and as part of the solution to climate change. Meanwhile, the tone of the drought debate became increasingly sarcastic and less neutral over time. Our findings demonstrate how an emerging climate risk can evolve from a distant issue to a socially contested topic, involving competing interests, responsibilities and interpretations. Understanding these dynamics can help in making policymakers aware of public concerns, and potential support for drought adaptation strategies.
