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.

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.