Iowa Statewide Stream Nitrate Loading: 2017-2018 Update

2019 ◽  
Vol 126 (1-4) ◽  
pp. 6-12 ◽  
Author(s):  
Christopher S. Jones ◽  
Keith E. Schilling

In response to ongoing hypoxia in the Gulf of Mexico, several states in the Mississippi River basin have adopted nutrient reduction plans in recent years designed to arrest the flow of nitrogen (N) and phosphorus (P) from both point and non-point sources to the stream network. Iowa's Nutrient Reduction Strategy, implemented in 2012, aims to reduce stream loading of these nutrients by 45% within a yet-to-be-defined time frame. Because the state has chosen to integrate accountability into the strategy through the numerical objective, ongoing water monitoring is necessary to credibly measure progress. The primary objective of this research was to use water quality monitoring and discharge data to update statewide nitrate-nitrogen (NO3-N) loading using the combined data sets generated by in situ water quality sensors and traditional grab sample monitoring conducted by state government. Our research shows that the 5-year running annual average of nitrate-nitrogen loading continues to increase, and after the 2018 water year is 73% higher than that calculated in 2003. Loads from Iowa areas draining to the Missouri River are increasing more rapidly than loads from areas draining to the upper Mississippi River: 132% versus 55% since 2003. This shows that best management practices designed to stem the loss of nutrients from the corn-soybean system must be widely adopted and robustly designed for extreme environmental conditions if Iowa is to meet its water quality objectives.

Author(s):  
Lei Wan ◽  
Xiaohui Fan

The Everglades, a vast subtropical wetland, dominates the landscape of south Florida and is widely recognized as an ecosystem of great ecological importance. Data from seven inflow sites to the Everglades National Park (ENP) were analyzed over three decades (1985–2014) for temporal trends by the STL (integrated seasonal-trend decomposition using LOESS) method. A cluster analysis (CA) and principal component analysis (PCA) were applied for the evaluation of spatial variation. The results indicate that the water quality change trend is closely associated with rainfall. Increasing rainfall results in increasing flow and thus, decreasing concentrations of nitrogen and phosphorus. Based on 10 variables, the seven sampling stations were classified by CA into four distinct clusters: A, B, C, and D. The PCA analysis indicated that total nitrogen (TN) and total phosphorus (TP) are the main pollution factors, especially TN. The results suggest that non-point sources are the main pollution sources and best management practices (BMPs) effectively reduce organic nitrogen. However, TN and TP control is still the focus of future work in this area. Increasing the transfer water quantity can improve the water quality temporarily and planting submersed macrophytes can absorb nitrogen and phosphorus and increase the dissolved oxygen (DO) concentration in water, continuously improving the water quality.


2020 ◽  
Author(s):  
Piet Seuntjens ◽  
Ellen Pauwelyn ◽  
Els Belmans ◽  
Ingeborg Joris ◽  
Elien Dupon ◽  
...  

<p>High-quality, safe, and sufficient drinking water is essential for life: we use it for drinking, food preparation and cleaning. Agriculture is the biggest source of pesticides and nitrate pollution in European fresh waters. Pesticide occurrences in rivers result from diffuse runoff from farmland or from point sources from the farmyard. Although many best management practices (BMPs) to mitigate these diffuse and point sources are developed and widely disseminated for several years, the effective implementation of mitigation measures in practice remains limited. Therefore, the Waterprotect project has been set up to improve the knowledge and awareness of the impact of crop protection products on the water quality among the many actors, to identify the bottlenecks for implementation of suitable BMPs and further develop new governance strategies to overcome these issues for a more effective drinking water protection. As all actors share the responsibility to deal with the water quality, government agencies (e.g. environmental agencies), private actors (e.g. drinking water company, input supplier, processing industry) and civil society actors (e.g. farmers) are involved in the project. Processes to cope with the problem are initiated in 7 action labs among which the Belgian Bollaertbeek action lab. The study area is a small agricultural catchment where surface water is used as intake to produce drinking water for the nearby city. The area is sensitive to erosion and based on a physical analysis and risk analysis of the catchment, the implementation of filling and cleaning places on individual farms and buffer strips along the watercourse are proposed as suitable measures to tackle the pollution problem. In order to implement them, mechanisms to increase the involvement of targeted farmers and alternative governance systems are studied. Results of the analysis of the water quality issues and the water governance system in the Belgian Bollaertbeek action lab and the strategies to try to improve the uptake of mitigation measures to improve water quality will be presented.</p>


2017 ◽  
Vol 76 (10) ◽  
pp. 2742-2752 ◽  
Author(s):  
Alper Elçi

Abstract Nutrient fluxes in stream basins need to be controlled to achieve good water quality status. In stream basins with intensive agricultural activities, nutrients predominantly come from diffuse sources. Therefore, best management practices (BMPs) are increasingly implemented to reduce nutrient input to streams. The objective of this study is to evaluate the impact of vegetated filter strip (VFS) application as an agricultural BMP. For this purpose, SWAT is chosen, a semi-distributed water quality assessment model that works at the watershed scale, and applied on the Nif stream basin, a small-sized basin in Western Turkey. The model is calibrated with an automated procedure against measured monthly discharge data. Nutrient loads for each sub-basin are estimated considering basin-wide data on chemical fertilizer and manure usage, population data for septic tank effluents and information about the land cover. Nutrient loads for 19 sub-basins are predicted on an annual basis. Average total nitrogen and total phosphorus loads are estimated as 47.85 t/yr and 13.36 t/yr for the entire basin. Results show that VFS application in one sub-basin offers limited retention of nutrients and that a selection of 20-m filter width is most effective from a cost–benefit perspective.


HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 501e-502
Author(s):  
Cody J. White ◽  
Michael A. Schnelle ◽  
Gerrit W. Cuperus

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.


1993 ◽  
Vol 28 (3-5) ◽  
pp. 379-387 ◽  
Author(s):  
S. Mostaghimi ◽  
P. W. McClellan ◽  
R. A. Cooke

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.


Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1547
Author(s):  
Jian Sha ◽  
Xue Li ◽  
Man Zhang ◽  
Zhong-Liang Wang

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.


2009 ◽  
Vol 38 (4) ◽  
pp. 1683-1693 ◽  
Author(s):  
Samira H. Daroub ◽  
Timothy A. Lang ◽  
Orlando A. Diaz ◽  
Sabine Grunwald

2001 ◽  
Vol 1 ◽  
pp. 10-16 ◽  
Author(s):  
James L. Baker

The primary mode of nitrogen (N) loss from tile-drained row-cropped land is generally nitrate-nitrogen (NO3-N) leaching. Although cropping, tillage, and N management practices can be altered to reduce the amount of leaching, there are limits as to how much can be done. Data are given to illustrate the potential reductions for individual practices such as rate, method, and timing of N applications. However, most effects are multiplicative and not additive; thus it is probably not realistic to hope to get overall reductions greater than 25 to 30% with in-field practices alone. If this level of reduction is insufficient to meet water quality goals, additional off-site landscape modifications may be necessary.


EDIS ◽  
2018 ◽  
Vol 2018 (5) ◽  
Author(s):  
Amanda D. Ali ◽  
Laura A. Sanagorski Warner ◽  
Peyton Beattie ◽  
Alexa J. Lamm ◽  
Joy N. Rumble

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. 


Sign in / Sign up

Export Citation Format

Share Document