Light is an important factor that affects cyanobacterial growth and changes in light can influence their growth and physiology. However, an information gap exists regarding light-induced oxidative stress and the species-specific behavior of cyanobacteria under various light levels. This study was conducted to evaluate the comparative effects of different light intensities on the growth and stress responses of two cyanobacteria species, Pseudanabaena galeata (strain NIES 512) and Microcystis aeruginosa (strain NIES 111), after periods of two and eight days. The cyanobacterial cultures were grown under the following different light intensities: 0, 10, 30, 50, 100, 300, and 600 μmol m⁻² s⁻¹. The optical density (OD₇₃₀), chlorophyll a (Chl-a) content, protein content, H₂O₂ content, and the antioxidative enzyme activities of catalase (CAT) and peroxidase (POD) were measured separately in each cyanobacteria species. P. galeata was negatively affected by light intensities lower than 30 μmol m⁻² s⁻¹ and higher than 50 μmol m⁻² s⁻¹. A range of 30 to 50 μmol m⁻² s⁻¹ light was favorable for the growth of P. galeata, whereas M. aeruginosa had a higher tolerance for extreme light conditions. The favorable range for M. aeruginosa was 10 to 100 μmol m⁻² s⁻¹.

Sediment yield is a complex phenomenon of weathering, land sliding, and glacial and fluvial erosion. It is highly dependent on the catchment area, topography, slope of the catchment terrain, rainfall, temperature, and soil characteristics. This study was designed to evaluate the key hydraulic parameters of sediment transport for Kali Gandaki River at Setibeni, Syangja, located about 5 km upstream from a hydropower dam. Key parameters, including the bed shear stress (τ_b), specific stream power (ω), and flow velocity (v) associated with the maximum boulder size transport, were determined throughout the years, 2003 to 2011, by using a derived lower boundary equation. Clockwise hysteresis loops of the average hysteresis index of +1.59 were developed and an average of 40.904 ± 12.453 Megatons (Mt) suspended sediment have been transported annually from the higher Himalayas to the hydropower reservoir. Artificial neural networks (ANNs) were used to predict the daily suspended sediment rate and annual sediment load as 35.190 ± 7.018 Mt, which was satisfactory compared to the multiple linear regression, nonlinear multiple regression, general power model, and log transform models, including the sediment rating curve. Performance indicators were used to compare these models and satisfactory fittings were observed in ANNs. The root mean square error (RMSE) of 1982 kg s⁻¹, percent bias (PBIAS) of +14.26, RMSE-observations standard deviation ratio (RSR) of 0.55, coefficient of determination (R²) of 0.71, and Nash–Sutcliffe efficiency (NSE) of +0.70 revealed that the ANNs’ model performed satisfactorily among all the proposed models.

The goal of the present review is to collect data on trending scientific discussions on applying green infrastructure (GI) approaches to the effective use of urban floodplains and conceptualize potential future directions. A systematic literature review methodology was employed for this review. We reviewed 120 scholarly articles published between 2011 and 2022 under a predefined protocol. In this review, we discuss the trending dialogues on GI approaches and their applications. The research gap in applying GI approaches for macro-level urban-flood-plain management is addressed by (a) speculative arguments drawn from reviewed GI case studies, (b) an analysis of the trends’ strengths, weaknesses, opportunities, and threats (SWOT), and (c) presenting the concurrent ‘green–gray’ debate on neutral ground. Evidently, GI has its strengths and opportunities, as well as weaknesses and threats. The approaches to GI can be customized according to the application purpose, the regional or locational context, and the intended capacity. Following the analysis of emerging GI discussions, we position the current GI dialogues into four categories: (i) the green–gray continuum; (ii) GI for sustainable and resilient cities; (iii) GI as a resolution for urban issues; and (iv) the green–gray debate. In this classification, we strongly argue that placing GI in a more certain and instrumental position can be optimally achieved in the ‘green–gray continuum’ concept with a win–win scenario. Therefore, scientifically investigating the ‘green–gray continuum’ possibilities in a futuristic approach is strongly recommended.

Two harmful cyanobacteria species (Phormidium ambiguum and Microcystis aeruginosa) were exposed to diurnal light-intensity variation to investigate their favorable and stressed phases during a single day. The photosynthetically active radiation (PAR) started at 0 µmol·m⁻²·s⁻¹ (06:00 h), increased by ~25 µmol·m⁻²·s⁻¹ or ~50 µmol·m⁻²·s⁻¹ every 30 min, peaking at 300 µmol·m⁻²·s⁻¹ or 600 µmol·m⁻²·s⁻¹ (12:00 h), and then decreased to 0 µmol·m⁻²·s⁻¹ (by 18:00 h). The H₂O₂ and antioxidant activities were paralleled to light intensity. Higher H₂O₂ and antioxidant levels (guaiacol peroxidase, catalase (CAT), and superoxidase dismutase) were observed at 600 µmol·m⁻²·s⁻¹ rather than at 300 µmol·m⁻²·s⁻¹. Changes in antioxidant levels under each light condition differed between the species. Significant correlations were observed between antioxidant activities and H₂O₂ contents for both species, except for the CAT activity of P. ambiguum at 300 µmol·m⁻²·s⁻¹. Under each of the conditions, both species responded proportionately to oxidative stress. Even under maximum light intensities (300 µmol·m⁻²·s⁻¹ or 600 µmol·m⁻²·s⁻¹ PAR intensity), neither species was stressed. Studies using extended exposure durations are warranted to better understand the growth performance and long-term physiological responses of both species.

The ecological dynamics of riparian areas interact with sediment transport in river systems, which plays an active role in riparian vegetation growth in the floodplain. The fluvial dynamics, hydraulics, hydro-meteorological and geomorphological characteristics of rivers are associated with sediment transport in river systems and around the riparian area. The flood disturbance, sediment with nutrients and seeds transported by river, sediment deposition, and erosion phenomena in the floodplain change the bare land area to vegetation area and vice versa. The difference in riparian vegetation area in the river floodplain is dependent on the sediment grain size distribution which is deposited in the river floodplain. Mathematical models describing vegetation growth in a short period exist in literature, but long-term modelling and validations are still lacking. In order to cover long-term vegetation growth modelling, a Dynamic Riparian Vegetation Model (DRIPVEM) was proposed. This paper highlights the existing modelling technique of DRIPVEM coupled with a Dynamic Herbaceous Model used to establish the interactive relationship of sediment grain sizes and riparian vegetation in the floodplain.