Vegetation dynamics in impounded marshes along the Indian River Lagoon,Florida, USA

Data are presented on the vegetation dynamics of two impounded marshes along the Indian River Lagoon, in east-central Florida, USA. Vegetation in one of the marshes (IRC 12) was totally eliminated by overflooding and by hypersaline conditions (salinities over 100 ppt) that developed there in 1979 after the culvert connecting the marsh with the lagoon was closed. Over 20% recovery of the herbaceous halophytesSalicornia virginica, S. bigelovii, andBatis maritima was observed at that site after the culvert was reopened in 1982, but total cover in the marsh remains well below the original 75%. No recovery of mangroves was observed at this site. The second site (SLC 24), while remaining isolated from the lagoon during much of the study, did not suffer the complete elimination of vegetation experienced at the first site. At this location, mangroves increased in cover and frequency with a concomitant decrease in herbaceous halophytes. Considerable damage to the vegetation was evident at IRC 12 when the impoundment was closed and flooded for mosquito control in 1986. Although the damage was temporary, its occurrence emphasizes the need of planning and constant monitoring and adjustment of management details as conditions within particular marshes change. Storms and hurricanes may be important in promoting a replacement of black mangroves by red mangroves in closed impoundments because the former cannot tolerate pneumatophore submergence for long periods of time. University of Florida-IFAS Journal Series R-00521.     

PREDICTION OF PEAK FLOWS ON SMALL WATERSHEDS IN OREGON FOR USE IN CULVERT DESIGN1

ABSTRACT: Using data from 80 Oregon watersheds that ranged in size from 0.54 km² to 27.45 km², equations were developed to predict peak flows for use in culvert design on forest roads. Oregon was divided into six physiographic regions based on previous studies of flood frequency. In each region, data on annual peak flow from gaging stations with more than 20 years of record were analyzed using four flood frequency distributions: type 1 extremal, two parameter-log normal, three parameter-log normal, and log-Pearson type III. The log-Pearson type III distribution was found to be suitable for use in all regions of the State, based on the chi-square goodness-of-fit-test. Flood magnitudes having recurrence intervals of 10, 25, 50, and 100 years were related to physical and climatic characteristics of drainage basins by multiple regression. Drainage basin size was the most important variable in explaining the variation of flood peaks in all regions. Mean basin elevation and mean annual precipitation were also significantly related to flood peaks in two regions of western Oregon. The standard error of the estimate for the regression relationships ranged from 26 to 84 percent.     

Water quality prediction of copper-molybdenum mining-beneficiation wastewater based on the PSO-SVR model

● Data acquisition and pre-processing for wastewater treatment were summarized. ● A PSO-SVR model for predicting COD_eff in wastewater was proposed. ● The COD_eff prediction performances of the three models in the paper were compared. ● The COD_eff prediction effects of different models in other studies were discussed. The mining-beneficiation wastewater treatment is highly complex and nonlinear. Various factors like influent quality, flow rate, pH and chemical dose, tend to restrict the effluent effectiveness of mining-beneficiation wastewater treatment. Chemical oxygen demand (COD) is a crucial indicator to measure the quality of mining-beneficiation wastewater. Predicting COD concentration accurately of mining-beneficiation wastewater after treatment is essential for achieving stable and compliant discharge. This reduces environmental risk and significantly improves the discharge quality of wastewater. This paper presents a novel AI algorithm PSO-SVR, to predict water quality. Hyperparameter optimization of our proposed model PSO-SVR, uses particle swarm optimization to improve support vector regression for COD prediction. The generalization capacity tested on out-of-distribution (OOD) data for our PSO-SVR model is strong, with the following performance metrics of root means square error (RMSE) is 1.51, mean absolute error (MAE) is 1.26, and the coefficient of determination (R²) is 0.85. We compare the performance of PSO-SVR model with back propagation neural network (BPNN) and radial basis function neural network (RBFNN) and shows it edges over in terms of the performance metrics of RMSE, MAE and R², and is the best model for COD prediction of mining-beneficiation wastewater. This is because of the less overfitting tendency of PSO-SVR compared with neural network architectures. Our proposed PSO-SVR model is optimum for the prediction of COD in copper-molybdenum mining-beneficiation wastewater treatment. In addition, PSO-SVR can be used to predict COD on a wide variety of wastewater through the process of transfer learning.     

Transport and biodegradation of creosote compounds in clayey till, a field experiment

The transport and biodegradation of 12 organic compounds (toluene, phenol, o-cresol, 2,6-, 3,5-dimethylphenol, naphthalene, 1-methylnaphthalene, benzothiophene, dibenzofuran, indole, acridine, and quinoline) were studied at a field site located on the island of Funen, Denmark, where a clayey till 10–15 m deep overlies a sandy aquifer. The upper 4.8 m of till is highly fractured and the upper 2.5 m contains numerous root and worm holes. A 1.5–2 m thick sand lens is encountered within the till at a depth of 4.8 m. Sampling points were installed at depths of 2.5 m, 4 m, and in the sand lens (5.5 m) to monitor the downward migration of a chloride tracer and the organic compounds. Water containing organic compounds and chloride was infiltrated into a 4 m×4.8 m basin at a rate of 8.8 m³ day⁻¹ for 7 days. The mass of naphthalene relative to chloride was 0.39–0.98 for the sampling points located at a depth of 2.5 m, 0.11–0.61 for the sampling points located at a depth of 4 m, and 0–0.02 for the sampling points located in the sand lens. A similar pattern was observed for eight organic compounds for which reliable results were obtained (toluene, phenol, o-cresol, 2,6-, 3,5-dimethylphenol, 1-methylnaphthalene, benzothiophene, and quinoline). This shows that the organic compounds were attenuated during the downward migration through the till despite the high infiltration rate. The attenuation process may be attributed to biodegradation.     

Direct and indirect effects of climate and habitat factors on butterfly diversity

Many factors, including climate, resource availability, and habitat diversity, have been proposed as determinants of global diversity, but the links among them have rarely been studied. Using structural equation modeling (SEM), we investigated direct and indirect effects of climate variables, host-plant richness, and habitat diversity on butterfly species richness across Britain, at 20-km grid resolution. These factors were all important determinants of butterfly diversity, but their relative contributions differed between habitat generalists and specialists, and whether the effects were direct or indirect. Climate variables had strong effects on habitat generalists, whereas host-plant richness and habitat diversity contributed relatively more for habitat specialists. Considering total effects (direct and indirect together), climate variables had the strongest link to butterfly species richness for all groups of species. The results suggest that different mechanistic hypotheses to explain species richness may be more appropriate for habitat generalists and specialists, with generalists hypothesized to show direct physiological limitations and specialists additionally being constrained by trophic interactions (climate affecting host-plant richness).     

Cleaning the river Damodar (India): impact of COVID-19 lockdown on water quality and future rejuvenation strategies

Globally, it is established that the partial lockdown system assists to improve the health of the total environment due to inadequate anthropogenic actions in different economic sectors. The ample research on fitness of environment has been proved that the strict imposition of lockdown was the blessings of environment. The river Damodar has historical significance and lifeline for huge population of Jharkhand and West Bengal state of India but in the recent years the water quality has been deteriorated due to untreated industrial effluents and urban sewage. The main objective of this study is to examine the water quality of river Damodar during and prelockdown phase for domestic use and restoration of river ecosystem. A total of eleven (11) effluent discharge sites were selected in prelockdown and during lockdown phase. A new approach of water quality assessment, i.e., water pollution index (WPI) has been applied in this study. WPI is weightage free, unbiased method to analysis of water quality. The result shows that the physical, chemical and heavy elements were found beyond the standard limit in prelockdown period. The cation and anion were arranged in an order of Na²⁺ ?>?K⁺ ?>?Ca²⁺ ?>?Mg²⁺ and Cl^??>?So₄^??>?No₃^??>?F^? in both the sessions. WPI of prelockdown showed that about 100% water samples are of highly polluted. WPI of lockdown period showed that around 90.90% samples improved to ‘good quality’ and 9.10% of samples are of ‘moderately polluted.’ Hypothesis testing by ‘t’ test proved that there was a significant difference (ρ?=?0.05%) in values of each parameter between two periods. Null hypothesis was rejected and indicated the improvement of river water quality statistically. Spatial mapping using Arc GIS 10.4 interpolation (IDW) helps to understand spatial intensity of pollution load in two periods. This research study should be helpful for further management and spatial diagnosis of water resource of river Damodar.

     

Ecosystem changes following the 2016 Kumamoto earthquakes in Japan: Future perspectives

Major earthquakes cause widespread environmental and socioeconomic disruptions that persist for decades. Extensive ground disturbances that occurred during the shallow-focus Kumamoto earthquakes will affect future sustainability of ecosystem services west of Aso volcano. Numbers of earthquake-initiated landslides per unit area were higher in grasslands than forests, likely owing to greater root reinforcement of trees, and mostly initiated on ridgelines and/or convex/planar hillslopes. Most landslides traveled short distances and did not initially evolve into debris flows; resultant sediments and wood accumulating in headwater channels can be mobilized into debris flows during future storms. Fissures along ridgelines may promote water ingress and induce future landslides and debris flows that affect residents downstream. Native grasses are at risk because of habitat fragmentation caused by ground disturbances, extensive damage to rural roads, and abandonment of traditional pasture management practices. Sustainable management of affected areas needs to consider future risk of cascading hazards and long-term socioeconomic impacts.     

UVΑ pre-irradiation to P25 titanium dioxide nanoparticles enhanced its toxicity towards freshwater algae Scenedesmus obliquus

Environmental Science and Pollution Research - There has recently been an increase in the usage of TiO2 nanoparticles (NPs). P25 TiO2 NPs, a mixture of anatase and rutile phase in 3:1 ratio, are...     

Comparative performance study of different configurations of organic Rankine cycle using low-grade waste heat for power generation

This paper aims at analyzing the feasibility of a waste heat recovery power generation plant based on parametric optimization and performance analysis using different organic Rankine cycle configurations and heat source temperature conditions with working fluid R-12, R-123, R-134a, and R-717. A parametric optimization of turbine inlet temperature(TIT) was performed to obtain the irreversibility rate, system efficiency, availability ratio, turbine work output, system mass flow rate, second-law efficiency, and turbine outlet quality, along the saturated vapor line and also on superheating at an inlet pressure of 2.50 MP in basic as well as regenerative organic Rankine cycle. The calculated results reveal that selection of a basic organic Rankine cycle using R-123 as working fluid gives the maximum system efficiency, turbine work output, second-law efficiency, availability ratio with minimum system irreversibility rate and system mass flow rate up to a TIT of 150°C and appears to be a choice system for generation of power by utilizing the flue gas waste heat of thermal power plants and above 150°C the regenerative superheat organic Rankine cycle configuration using R 123 as working fluid gives the same results.