scholarly journals Mathematical Modelling as a Tool for the Assessment of Impact of Thermodynamics on the Algal Growth in Dam Reservoirs – Case Study of the Goczalkowice Reservoir

2018 ◽  
Vol 29 (1) ◽  
pp. 21-29
Author(s):  
Rafał Ulańczyk ◽  
Czesław Kliś ◽  
Damian Absalon ◽  
Marek Ruman
Keyword(s):  
Chlorophyll A ◽  
Management Practices ◽  
Algal Growth ◽  
Quality Parameters ◽  
Ocean Model ◽  
Climate Conditions ◽  
Water Mixing ◽  
Dam Reservoirs ◽  
Basin Morphology ◽  
Coastal Ocean Model

Abstract Depending on climate conditions, bathymetry, basin morphology, management practices and other factors, some reservoirs are more or less prone to stratification, which can strongly affect both chemical and biological status of water. In the Goczalkowice Reservoir (the biggest dam reservoir in the south of Poland), water quality parameters, such as chlorophyll a concentration, change very dynamically. In the presented study, the Estuary, Lake and Coastal Ocean Model (ELCOM) was applied to simulate water thermodynamics in a period of summer and autumn when the highest concentrations of chlorophyll a were observed, based on the continuous water monitoring in the ZiZOZap project (Łaszczyca et al., 2011). The purpose of the application of ELCOM was to simulate the thermal stratification in the reservoir and to prepare a basis for analyses of the relationship between water thermodynamics and quality. Simulations allowed the identification of several short water mixing events in summer and the final mixing event at the end of summer. The study also included the first application of model results to analyse the relation of changes in water temperature with observed concentration of chlorophyll a (ChlA). Analysis confirmed that each water mixing event was followed by a significant increase in ChlA concentration.

scholarly journals Assessing the Effects of Agronomic Management Practices on Soybean (Glycine max L.) Post-Grain Harvest Residue Quality in the Lower Mississippi Delta

Plants ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1337
Author(s):  
Srinivasa R. Pinnamaneni ◽  
Saseendran S. Anapalli
Keyword(s):  
Management Practices ◽  
Crop Residues ◽  
Soybean Seed ◽  
Grain Filling ◽  
Quality Parameters ◽  
Neutral Detergent Fiber ◽  
Net Energy ◽  
Residue Quality ◽  
Climate Conditions ◽  
Harvest Residue

Livestock producers often resort to either baling or grazing of crop residues due to high hay prices and reduced supply of other forages and silage in the markets. Soil-water-crop management practices can affect residue nutrient qualities for its use as cattle feedstock. A two-year study (2018–2019) was conducted to investigate the effects of irrigation (AI, all row-irrigation; ARI, alternate row irrigation; and RF, rainfed) and planting pattern, PP (SR, single row; and TR, twin-row) on soybean (maturity group IV cv. 31RY45 Dyna-Gro) post-grain harvest residue quality such as crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), acid detergent lignin (ADL), net energy for maintenance (NEM), net energy for gain (NEG), net energy for lactation (NEL), total digestible nutrients (TDN), and relative feed value (RFV). Irrigation has a significant effect on CP, ADF, NDF, and TDN while PP affected only NDF. All the above parameters were significantly affected except NEM by the contrasting climate conditions, particularly during July through August coinciding with early crop reproductive stages and maturity. The RFV values ranged from 70.4 to 81.6 and this lower range was attributable to nutrient translocation to seeds and higher lignification during plant senescence towards the grain filling stage of the crop as good quality hay records over 120 RFV. These results indicate that both irrigation and weather during soybean seed development can alter post-grain harvest residue quality parameters, thereby playing critical roles in its RFV.

Seagrass depth range and water quality in southern Moreton Bay, Queensland, Australia

1996 ◽  
Vol 47 (6) ◽  
pp. 763 ◽  
Author(s):  
EG Abal ◽  
WC Dennison
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Suspended Solids ◽  
Light Attenuation ◽  
River Mouth ◽  
Total Suspended Solids ◽  
Quality Parameters ◽  
Depth Range ◽  
Moreton Bay ◽  
A Site

Correlations between water quality parameters and seagrass depth penetration were developed for use as a biological indicator of integrated light availability and long-term trends in water quality. A year-long water quality monitoring programme in Moreton Bay was coupled with a series of seagrass depth transects. A strong gradient between the western (landward) and eastern (seaward) portions of Moreton Bay was observed in both water quality and seagrass depth range. Higher concentrations of chlorophyll a, total suspended solids, dissolved and total nutrients, and light attenuation coefficients in the water column and correspondingly shallower depth limits of the seagrass Zostera capricorni were observed in the western portions of the bay. Relatively high correlation coefficient values (r2 > 0.8) were observed between light attenuation coefficient, total suspended solids, chlorophyll a, total Kjeldahl nitrogen and Zostera capricorni depth range. Low correlation coefficient values (r2 < 0.8) between seagrass depth range and dissolved inorganic nutrients were observed. Seagrasses had disappeared over a five-year period near the mouth of the Logan River, a turbid river with increased land use in its watershed. At a site 9 km from the river mouth, a significant decrease in seagrass depth range corresponded to higher light attenuation, chlorophyll a, total suspended solids and total nitrogen content relative to a site 21 km from the river mouth. Seagrass depth penetration thus appears to be a sensitive bio-indicator of some water quality parameters, with application for water quality management.

scholarly journals The Effects of Management (Tillage, Fertilization, Plant Density) on Soybean Yield and Quality in a Three-Year Experiment under Transylvanian Plain Climate Conditions

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 200
Author(s):  
Felicia Chețan ◽  
Cornel Chețan ◽  
Ileana Bogdan ◽  
Adrian Ioan Pop ◽  
Paula Ioana Moraru ◽  
...  
Keyword(s):  
Plant Density ◽  
Conventional Tillage ◽  
Quality Parameters ◽  
Soil Tillage ◽  
Reduced Tillage ◽  
Seeding Rate ◽  
Soybean Yield ◽  
Climate Conditions ◽  
Yield And Quality ◽  
Tillage System

The regional agroecological conditions, specific to the Transylvanian Plain, are favorable to soybean crops, but microclimate changes related to global warming have imposed the need for agrotechnical adaptive measures in order to maintain the level of soybean yield. In this study, we consider the effect of two soil tillage systems, the seeding rate, as well as the fertilizer dosage and time of application on the yield and quality of soybean crops. A multifactorial experiment was carried out through the A × B × C × D − R: 3 × 2 × 3 × 3 − 2 formula, where A represents the year (a1, 2017; a2, 2018; and a3, 2019); B represents the soil tillage system (b1, conventional tillage with mouldboard plough; b2, reduced tillage with chisel cultivator); C represents the fertilizer variants (c1, unfertilized; c2, one single rate of fertilization: 40 kg ha−1 of nitrogen + 40 kg ha−1 of phosphorus; and c3, two rates of fertilization: 40 kg ha−1 of nitrogen + 40 kg ha−1 of phosphorus (at sowing) + 46 kg ha−1 of nitrogen at V3 stage); D represents the seeding rate (1 = 45 germinating grains (gg) m−2; d2 = 55 gg m−2; and d3 = 65 gg m−2); and R represents the replicates (r1 = the first and r2 = the second). Tillage had no effect, the climate specific of the years and fertilization affected the yield and the quality parameters. Regarding the soybean yield, it reacted favorably to a higher seeding rate (55–65 gg m−2) and two rates of fertilization. The qualitative characteristics of soybeans are affected by the fertilization rates applied to the crop, which influence the protein and fiber content in the soybean grains. Higher values of protein content were recorded with a reduced tillage system, i.e., 38.90 g kg−1 DM in the variant with one single rate of fertilization at a seeding rate of 45 gg per m−2 and 38.72 g kg−1 DM in the variant with two fertilizations at a seeding rate of 65 gg m−2.

scholarly journals Comparison of Forecasting Models for Real-Time Monitoring of Water Quality Parameters Based on Hybrid Deep Learning Neural Networks

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1547
Author(s):  
Jian Sha ◽  
Xue Li ◽  
Man Zhang ◽  
Zhong-Liang Wang
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Deep Learning ◽  
Real Time ◽  
Best Management Practices ◽  
Input Data ◽  
Management Practices ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Real Time Monitoring

Accurate real-time water quality prediction is of great significance for local environmental managers to deal with upcoming events and emergencies to develop best management practices. In this study, the performances in real-time water quality forecasting based on different deep learning (DL) models with different input data pre-processing methods were compared. There were three popular DL models concerned, including the convolutional neural network (CNN), long short-term memory neural network (LSTM), and hybrid CNN–LSTM. Two types of input data were applied, including the original one-dimensional time series and the two-dimensional grey image based on the complete ensemble empirical mode decomposition algorithm with adaptive noise (CEEMDAN) decomposition. Each type of input data was used in each DL model to forecast the real-time monitoring water quality parameters of dissolved oxygen (DO) and total nitrogen (TN). The results showed that (1) the performances of CNN–LSTM were superior to the standalone model CNN and LSTM; (2) the models used CEEMDAN-based input data performed much better than the models used the original input data, while the improvements for non-periodic parameter TN were much greater than that for periodic parameter DO; and (3) the model accuracies gradually decreased with the increase of prediction steps, while the original input data decayed faster than the CEEMDAN-based input data and the non-periodic parameter TN decayed faster than the periodic parameter DO. Overall, the input data preprocessed by the CEEMDAN method could effectively improve the forecasting performances of deep learning models, and this improvement was especially significant for non-periodic parameters of TN.

scholarly journals Establishment of Regional Phytoremediation Buffer Systems for Ecological Restoration in the Great Lakes Basin, USA. I. Genotype × Environment Interactions

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 430 ◽  
Author(s):  
Ronald S. Zalesny ◽  
Andrej Pilipović ◽  
Elizabeth R. Rogers ◽  
Joel G. Burken ◽  
Richard A. Hallett ◽  
...  
Keyword(s):  
Great Lakes ◽  
Best Management Practices ◽  
Management Practices ◽  
Recurrent Selection ◽  
Lake Michigan ◽  
Great Lakes Basin ◽  
Annual Increment ◽  
Climate Conditions ◽  
The North ◽  
Local Soil

Poplar remediation systems are ideal for reducing runoff, cleaning groundwater, and delivering ecosystem services to the North American Great Lakes and globally. We used phyto-recurrent selection (PRS) to establish sixteen phytoremediation buffer systems (phyto buffers) (buffer groups: 2017 × 6; 2018 × 5; 2019 × 5) throughout the Lake Superior and Lake Michigan watersheds comprised of twelve PRS-selected clones each year. We tested for differences in genotypes, environments, and their interactions for health, height, diameter, and volume from ages one to four years. All trees had optimal health. Mean first-, second-, and third-year volume ranged from 71 ± 26 to 132 ± 39 cm3; 1440 ± 575 to 5765 ± 1132 cm3; and 8826 ± 2646 to 10,530 ± 2110 cm3, respectively. Fourth-year mean annual increment of 2017 buffer group trees ranged from 1.1 ± 0.7 to 7.8 ± 0.5 Mg ha−1 yr−1. We identified generalist varieties with superior establishment across a broad range of buffers (‘DM114’, ‘NC14106’, ‘99038022’, ‘99059016’) and specialist clones uniquely adapted to local soil and climate conditions (‘7300502’, ‘DN5’, ‘DN34’, ‘DN177’, ‘NM2’, ‘NM5’, ‘NM6’). Using generalists and specialists enhances the potential for phytoremediation best management practices that are geographically robust, being regionally designed yet globally relevant.

A GPU accelerated finite volume coastal ocean model

2017 ◽  
Vol 29 (4) ◽  
pp. 679-690 ◽  
Author(s):  
Xu-dong Zhao ◽  
Shu-xiu Liang ◽  
Zhao-chen Sun ◽  
Xi-zeng Zhao ◽  
Jia-wen Sun ◽  
...  
Keyword(s):  
Finite Volume ◽  
Coastal Ocean ◽  
Ocean Model ◽  
Coastal Ocean Model

Soil respiration under different agricultural land use types in Croatia

2021 ◽  
Author(s):  
Darija Bilandžija ◽  
Marija Galić ◽  
Željka Zgorelec
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Respiration ◽  
Management Practices ◽  
Agricultural Land ◽  
Ghg Emissions ◽  
Paris Agreement ◽  
Energy Crop ◽  
Climate Conditions ◽  
Uncertainty Estimates

&lt;p&gt;In order to mitigate climate change and reduce the anthropogenic greenhouse gas (GHG) emissions, the Kyoto protocol has been adopted in 1997 and the Paris Agreement entered into force in 2016. The Paris Agreement have ratified 190 out of 197 Parties of the United Nations Framework Convention on Climate Change (UNFCCC) and Croatia is one of them as well. Each Party has obliged regularly to submit the national inventory report (NIR) providing the information on the national anthropogenic GHG emissions by sources and removals by sinks to the UNFCCC. Reporting under the NIR is divided into six categories / sectors, and one of them is land use, land use change and forestry (LULUCF) sector, where an issue of uncertainty estimates on carbon emissions and removals occurs. As soil respiration represents the second-largest terrestrial carbon flux, the national studies on soil respiration can reduce the uncertainty and improve the estimation of country-level carbon fluxes. Due to the omission of national data, the members of the University of Zagreb Faculty of Agriculture, Department of General Agronomy have started to study soil respiration rates in 2012, and since then many different studies on soil respiration under different agricultural land uses (i.e. annual crops, energy crop and vineyard), management practices (i.e. tillage and fertilization) and climate conditions (i.e. continental and mediterranean) in Croatia have been conducted. The obtained site specific results on field measurements of soil carbon dioxide concentrations by &lt;em&gt;in situ&lt;/em&gt; closed static chamber method will be presented in this paper.&lt;/p&gt;

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