scholarly journals Watershed Modeling Using Swat for Hydrology and Water Quality : A Review

2021 ◽  
pp. 190-196
Author(s):  
Sravani Duvvuri
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
Best Management Practices ◽  
Management Practices ◽  
Hydrological Modeling ◽  
Quality Parameters ◽  
Hydrologic Model ◽  
Livestock Grazing ◽  
Organic Fertilizers ◽  
World Health

According to World health Organization Global health Observatory, 600 million Indians are facing extreme water stress and about two lakh people die every year due to inadequate access to safe water. This scenario indicate that many parts of the country will soon face a crisis in both water quantity and water quality unless management of water resources planned in a sustainable way. Many major rivers are polluted as a result of urbanization and industrialization, thereby quality parameters also violating the standards. In India, more than 50% of population depends on agriculture and many farmers use fertilizers, consists of harmful chemicals. The Nitrogen and phosphorous are the two nutrients originating from inorganic and organic fertilizers, that affect the water quality due to intensive agricultural farming and livestock grazing. Water availability in a catchment is necessary to plan/allocate the water resources in an equity manner. This can be estimated using a hydrologic model, which is designed to simulate the rainfall-runoff processes of watershed systems. An ArcGIS-based user interface could be used to model hydrologic and water quality parameters. SWAT is a continuous simulation-based model and is developed through a distributed hydrological modeling approach, which is one of the few hydrologic models with water quality coupling capability. This review mainly focuses on the broad aspects related to the execution and applicability of SWAT for various catchments to simulate the runoff and other quality parameters with various calibration techniques, thereby to make policies for best management practices and to promote sustainable development.

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 Operational Forest Stream Crossings Effects on Water Quality in the Virginia Piedmont

2011 ◽  
Vol 35 (3) ◽  
pp. 123-130 ◽  
Author(s):  
Wallace M. Aust ◽  
Mathew B. Carroll ◽  
M. Chad Bolding ◽  
C. Andrew Dolloff
Keyword(s):  
Water Quality ◽  
Best Management Practices ◽  
Management Practices ◽  
Quality Parameters ◽  
Site Factors ◽  
Concentration Data ◽  
Individual Site ◽  
Forest Stream ◽  
Randomized Design ◽  
Portable Bridges

Abstract Water quality indices were examined for paired upstream and downstream samples for 23 operational stream crossings and approaches during four periods. Stream crossings were (1) portable bridges (BRIDGE), (2) culverts backfilled with poles (POLE), (3) culverts with earth backfill (CULVERT), and (4) reinforced fords (FORD). The four operational periods were (1) prior to crossing installation (INITIAL), (2) after installation (INSTALL), (3) during harvest (HARVEST), and (4) after road closure (CLOSURE). Differences (Δ) in water samples collected above and below stream crossings were analyzed for Δtotal dissolved solids (ΔTDS), ΔpH, Δconductivity, Δtemperature, and Δsediment concentration. Data were analyzed as a completely randomized design with unequal replication (four to seven replications). Significant differences were observed (α < 0.10) among crossing types for Δtemperature, ΔTDS, ΔpH, and Δconductivity. Overall, the least disruptive crossing type for water quality was BRIDGE, but road standards and approach characteristics were also important. Modeled estimates of erosion demonstrated that CULVERT approaches had higher potential erosion than other crossings. Water quality parameters were most negatively affected during INSTALL and HARVEST and were apparently improving during CLOSURE. Permanent crossings were associated with significantly greater temperatures than temporary crossings, likely because of increased width of streamside management zone removal. Water quality effects could be minimized by installing appropriate best management practices during all harvest periods rather than waiting until CLOSURE. Findings should be used cautiously because individual site factors such as climate, site, soil, and operational variability will alter effects.

Effectiveness of Stormwater Best Management Practices in Headwater Streams to Mitigate Harmful Algal Blooms

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Jennifer Braswell Alford ◽  
Elizabeth Caporuscio
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
Best Management Practices ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Outdoor Recreation ◽  
Management Practices ◽  
Headwater Streams ◽  
Best Management

Pollution inputs in surface waters have resulted in extensive impairments to water resources; however, the effectiveness of stormwater best management practices (BMPs) in reducing pollution inputs related to harmful algal blooms (HABs) in headwater streams has not been widely reported. Skypark, Santa’s Village, is an outdoor recreation area in the semiarid San Bernardino National Forest, California. Recreational activities and impervious surfaces at the site contribute pollution to Hooks Creek, a first-order headwater tributary of the Mojave River. The Natural Resources Conservation Service designed and constructed a stormwater sediment erosion control basin system to reduce site gully erosion and improve surface water quality in situ and downstream. Basin water quality was tested biweekly for parameters associated with HABs including temperature, dissolved oxygen, pH, turbidity, conductivity, nitrate (NO3−), and ammonium (NH4+) in situ during wet and dry seasons, with periodic testing for total suspended solids (TSS), total dissolved solids (TDS), total coliform (TC), and Escherichia coli (EC). The BMP structure was effective in lowering temperature and pH and reducing NO3−, TDS, and turbidity during precipitation events, and increased pH levels and lower concentrations of TSS, TC, and EC were present during the dry season. Despite these advantages, the BMP was ineffective in reducing (NH4+) concentrations, a primary contributor to HABs, with 100% of the samples exceeding regulatory criteria throughout the study period. Results highlight the benefits and limitations of stormwater BMPs in protecting water resources from downstream HABs to ensure water resources are protected for current and future generations.

A Survey of Nursery Water Quality Best Management Practices

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 501e-502
Author(s):  
Cody J. White ◽  
Michael A. Schnelle ◽  
Gerrit W. Cuperus
Keyword(s):  
Water Quality ◽  
Best Management Practices ◽  
Management Practices ◽  
Cultural Practices ◽  
Plant Materials ◽  
Best Management ◽  
Employee Safety ◽  
Current Water ◽  
Management Approaches ◽  
Environmentally Sound

A survey was designed to assess high-risk areas with respect to environmental contamination, specifically how it relates to water quality. Oklahoma growers of all economic levels, retail and/or wholesale, were queried at their place of business for their current state of implementing best management practices (BMPs) and other strategic actions that could potentially affect current and future water quality standards. Specific areas such as the physical environment of the nursery, primary pesticides and fertilizers used, Integrated Pest Management (IPM) practices, and employee safety training were covered as well as other aspects germane to preserving and protecting current water quality and related environmental issues. More than 75 nurseries were surveyed and given the opportunity to participate in future training at Oklahoma State Univ. Results indicated that nurseries have not fully implemented many BMPs, but have adopted fundamental IPM approaches. The stage is set for the implementation of the next phase of expansion and refinement into ecologically based programs such as propagation and sale of low pesticide input plant materials, improved cultural practices, and the integration of environmentally sound management approaches. As an example, many growers are in the process of phasing out calendar-based pesticide application programs in favor of aesthetic and/or economic threshold-driven pesticide spray programs.

Pesticide Contamination of Groundwater in Virginia: BMP Impact Assessment

1993 ◽  
Vol 28 (3-5) ◽  
pp. 379-387 ◽  
Author(s):  
S. Mostaghimi ◽  
P. W. McClellan ◽  
R. A. Cooke
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Best Management Practices ◽  
Water Samples ◽  
Management Practices ◽  
Water Quality Monitoring ◽  
Pesticide Contamination ◽  
Cropping Patterns ◽  
Creek Watershed ◽  
Surface And Groundwater

The Nomini Creek Watershed/Water Quality monitoring project was initiated in 1985, as part of the Chesapeake Bay Agreement of 1983, to quantify the impacts of agricultural best management practices (BMPs) on improving water quality. The watershed monitoring system was designed to provide a comprehensive assessment of the quality of surface and groundwater as influenced by changes in land use, agronomic, and cultural practices in the watershed over the duration of the project. The primary chemical characteristics monitored include both soluble and sediment-bound nutrients and pesticides in surface and groundwater. Water samples from 8 monitoring wells located in agricultural areas in the watershed were analyzed for 22 pesticides. A total of 20 pesticides have been detected in water samples collected. Atrazine is the most frequently detected pesticide. Detected concentrations of atrazine ranged from 0.03 - 25.56 ppb and occurred in about 26 percent of the samples. Other pesticides were detected at frequencies ranging from 1.6 to 14.2 percent of all samples collected and concentrations between 0.01 and 41.89 ppb. The observed concentrations and spatial distributions of pesticide contamination of groundwater are compared to land use and cropping patterns. Results indicate that BMPs are quite effective in reducing pesticide concentrations in groundwater.

scholarly journals Effects of Organic Fertilizers on the Soil Microorganisms Responsible for N2O Emissions: A Review

2021 ◽  
Vol 9 (5) ◽  
pp. 983
Author(s):  
Cristina Lazcano ◽  
Xia Zhu-Barker ◽  
Charlotte Decock
Keyword(s):  
Community Structure ◽  
Microbial Community ◽  
Best Management Practices ◽  
Management Practices ◽  
Organic Fertilizers ◽  
N2o Emissions ◽  
Soil C ◽  
Best Management ◽  
C Stocks ◽  
Denitrifying Microorganisms

The use of organic fertilizers constitutes a sustainable strategy to recycle nutrients, increase soil carbon (C) stocks and mitigate climate change. Yet, this depends largely on balance between soil C sequestration and the emissions of the potent greenhouse gas nitrous oxide (N2O). Organic fertilizers strongly influence the microbial processes leading to the release of N2O. The magnitude and pattern of N2O emissions are different from the emissions observed from inorganic fertilizers and difficult to predict, which hinders developing best management practices specific to organic fertilizers. Currently, we lack a comprehensive evaluation of the effects of OFs on the function and structure of the N cycling microbial communities. Focusing on animal manures, here we provide an overview of the effects of these organic fertilizers on the community structure and function of nitrifying and denitrifying microorganisms in upland soils. Unprocessed manure with high moisture, high available nitrogen (N) and C content can shift the structure of the microbial community, increasing the abundance and activity of nitrifying and denitrifying microorganisms. Processed manure, such as digestate, compost, vermicompost and biochar, can also stimulate nitrifying and denitrifying microorganisms, although the effects on the soil microbial community structure are different, and N2O emissions are comparatively lower than raw manure. We propose a framework of best management practices to minimize the negative environmental impacts of organic fertilizers and maximize their benefits in improving soil health and sustaining food production systems. Long-term application of composted manure and the buildup of soil C stocks may contribute to N retention as microbial or stabilized organic N in the soil while increasing the abundance of denitrifying microorganisms and thus reduce the emissions of N2O by favoring the completion of denitrification to produce dinitrogen gas. Future research using multi-omics approaches can be used to establish key biochemical pathways and microbial taxa responsible for N2O production under organic fertilization.

Long-term Water Quality Trends after Implementing Best Management Practices in South Florida

2009 ◽  
Vol 38 (4) ◽  
pp. 1683-1693 ◽  
Author(s):  
Samira H. Daroub ◽  
Timothy A. Lang ◽  
Orlando A. Diaz ◽  
Sabine Grunwald
Keyword(s):  
Water Quality ◽  
Best Management Practices ◽  
Management Practices ◽  
South Florida ◽  
Best Management ◽  
Water Quality Trends

scholarly journals Using Video Messages to Promote Residential Adoption of Fertilizer Best Management Practices

EDIS ◽  
2018 ◽  
Vol 2018 (5) ◽  
Author(s):  
Amanda D. Ali ◽  
Laura A. Sanagorski Warner ◽  
Peyton Beattie ◽  
Alexa J. Lamm ◽  
Joy N. Rumble
Keyword(s):  
Water Quality ◽  
Best Management Practices ◽  
Diffusion Of Innovations ◽  
Management Practices ◽  
Relative Advantage ◽  
Water Quantity ◽  
Extension Programs ◽  
Best Management ◽  
Homeowner Associations ◽  
Quality Water

Residents are inclined to over-irrigate and over-fertilize their lawns to uphold landscape appearances influenced by homeowner associations and neighborhood aesthetics (Nielson & Smith (2005). While these practices affect water quantity and quality, water quality is most impacted by fertilizer runoff (Nielson & Smith, 2005; Toor et al., 2017). Supporting water programs and engagement in fertilizer best management practices (BMPs) can have positive impacts on water quality. The Diffusion of Innovations (DOI) theory can be used to explain how a population accepts and adopts fertilizer best management practices (BMPs) over time (Rogers, 2003). Adoption can be understood through a population's perception of relative advantage, compatibility, complexity, observability, and trialability of fertilizer BMPs. The information presented here is an exploration of how extension can use video messages to influence residents' perception of these factors which influence adoption. The videos positively influence residents' perceptions of fertilizer BMPs, and recommendations are offered for applying this research to extension programs. 

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