scholarly journals Towards a multi-basin SWAT model for the migration of nutrients and pesticides to Puck Bay (Southern Baltic Sea)

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10938
Author(s):  
Paweł Wielgat ◽  
Dominika Kalinowska ◽  
Adam Szymkiewicz ◽  
Piotr Zima ◽  
Beata Jaworska-Szulc ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Crop Yields ◽  
Swat Model ◽  
Natura 2000 ◽  
Weather Data ◽  
Nutrient Runoff ◽  
Baltic Countries ◽  
Minimal Depth ◽  
The Impact ◽  
Puck Bay

Background This paper analyzes the impact of changes in fertilization on crop yields and the runoff of nutrients from a small agricultural catchment (176 km2) to a shallow bay, using the SWAT model. Puck Bay is part of the Gulf of Gdansk and belongs to the Baltic Sea. The whole area of Puck Bay (364 km2) is protected (Natura 2000) yet despite this it suffers from eutrophication problems due to the relatively minimal depth and difficult water exchange. Methods The paper presents a comparison of the calculated yields and the runoff of nutrients and pesticides in the SWAT model, for a small agricultural coastal catchment. Calculations were made for 13 crop scenarios with weather data from 2011 to 2019. For each crop, an agriculture calendar was made. Two variants of fertilization were considered (autofertilization mode and according to the calendar). The nutrient runoff was calculated depending on the adopted scenario. In addition, the fate of selected pesticides was simulated. Results Depending on the crop, the annual load of NO3into the stream ranged from 0.74 to 3.65 kg ha−1. The annual load of organic phosphorous into the stream was between 0.686 and 3.64 kg ha−1. This is lower than in the majority of EU or Baltic countries. The surface runoff of dissolved Glyphosate was equal to 286 mg ha−1. The annual loads of nutrients from the catchment area are equivalent in both fertilization modes. Regardless of the selected fertilization mode, in addition to the dosage, the form of nutrients is important for the model.

scholarly journals Model of Nutrient and Pesticide Outflow with Surface Water to Puck Bay (Southern Baltic Sea)

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 809 ◽  
Author(s):  
Dominika Kalinowska ◽  
Paweł Wielgat ◽  
Tomasz Kolerski ◽  
Piotr Zima
Keyword(s):  
Baltic Sea ◽  
Assessment Tool ◽  
Swat Model ◽  
Agricultural Practices ◽  
Natura 2000 ◽  
The Baltic Sea ◽  
Quality Of Water ◽  
The Baltic ◽  
The Impact ◽  
Puck Bay

Coastal basins are particularly exposed to the adverse impact of anthropogenic stress. In many places, despite only the seasonal increase in the number of residents, progressive urbanization and associated changes in the catchment characteristics are noticeable. Puck Bay is part of the Gulf of Gdansk and belongs to the Baltic Sea. Although the area of Puck Bay is covered by the Natura 2000 Network, this has not saved it from eutrophication problems. As part of the work on a complex coastal basin analysis (WaterPUCK project), the Soil and Water Assessment Tool (SWAT) model was used to determine the agricultural impact on water quality in rivers with a flow into Puck Bay: Reda, Gizdepka, Płutnica, and Błądzikowski Stream. The results include the loads of nutrients and pesticides that flow out from the agricultural areas of Puck community into Puck Bay. In this article, special attention has been paid to the impact of precipitation on the quality of water at the outflow of rivers into the Bay of Puck, because it is a decisive element in the amount of nutrients leached along with surface runoff to watercourses and then into the Gulf. The distribution of precipitation thus affects the amount of nutrients absorbed by plants. Modeling the effects of agricultural practices, taking into account long-term meteorological forecasts, is helpful in attempts to reduce the amount of pollutants entering the Baltic Sea.

scholarly journals SPREADING OF BRINE DISCHARGED INTO THE PUCK BAY (SOUTH BALTIC SEA): THEORETICAL STUDY VERSUS FIELD OBSERVATIONS

2012 ◽  
Vol 1 (33) ◽  
pp. 20
Author(s):  
Malgorzata Robakiewicz
Keyword(s):  
Baltic Sea ◽  
Natura 2000 ◽  
Regional Administration ◽  
The North ◽  
North Eastern ◽  
Shallow Water Body ◽  
Wind Driven Currents ◽  
Oil Company ◽  
North Eastern Part ◽  
Puck Bay

Increasing demands for gas storage capacity encouraged Polish Gas and Oil Company (PGNiG) to make use of salt deposits located in the north-eastern part of Poland, in the area bordering on the Gulf of Gdańsk (South Baltic Sea), and create underground gas stores. A complex of 10 chambers (250x106 m3) was designed to be built at a depth of 800-1600 m. The construction site is located about 4 km away from the sea coast. The drilling of boreholes and diluting of salt rock was proposed as a method of creating the chambers. Owing to ecological reasons, maximum discharge of brine is limited to 300 m3/h with the max. saturation of 250 kg/m3. The Puck Bay is a shallow water body with wind-driven currents and negligible tides. The main difficulty of the investment lay in the effective spreading of brine in the Puck Bay in accordance with all requirements that apply to regions protected by NATURA 2000. The most important restriction was the permitted excess salinity, defined as 0.5 PSU over the natural salinity in the Puck Bay. The location of brine discharge, number and diameters of nozzles, as well as consequences of brine discharge on the Puck Bay water, had been analyzed before the permission to install the system of diffusers was granted by the regional administration. The installation consists of a system of 16 heads spaced every 45 m, each of them equipped with 3 nozzles of 8 mm diameter.

scholarly journals Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA

Climate ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 139
Author(s):  
Manashi Paul ◽  
Sijal Dangol ◽  
Vitaly Kholodovsky ◽  
Amy R. Sapkota ◽  
Masoud Negahban-Azar ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
River Watershed ◽  
Temperature And Precipitation ◽  
The Impact

Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions.

Application of SWAT Model in Assessing the Influence of Herbage Covering to Runoff Formation Process in Ma River Basin

2014 ◽  
Vol 955-959 ◽  
pp. 3065-3070
Author(s):  
Tuan Bui Anh ◽  
Shi Hua He ◽  
Lan Vu Thi Thu ◽  
Jian Jun Zhu
Keyword(s):  
River Basin ◽  
Formation Process ◽  
Input Data ◽  
Swat Model ◽  
Weather Data ◽  
Runoff Formation ◽  
Gis Technique ◽  
Forest Coverage ◽  
Basin Water ◽  
The Impact

The SWAT model and GIS technique were applied to calculate the runoff in the Ma River basin, Vietnam. The study focused on assessing the influence of herbage coverage to runoff formation process. In this integration, GIS supplies SWAT input data included elevation, soil properties, land use and weather data and creates graphical user interface, while SWAT operates input data, delineates watershed, simulates different physical processes, displays output data as runoff. Based on the model testing and parameter calibrating, two scenarios of decreasing and increasing 30% of forest coverage are built to assess the impact to runoff changing. The results have important guiding significance for the planning, management and sustainable utilization of river basin water resources.

Analyzing Temperature and Precipitation Influences on Yield Distributions of Canola and Spring Wheat in Saskatchewan

2017 ◽  
Vol 56 (4) ◽  
pp. 897-913 ◽  
Author(s):  
Ting Meng ◽  
Richard Carew ◽  
Wojciech J. Florkowski ◽  
Anna M. Klepacka
Keyword(s):  
Crop Yield ◽  
Spring Wheat ◽  
Climate Model ◽  
Crop Yields ◽  
Wheat Yield ◽  
Growing Season ◽  
Weather Data ◽  
Growth Stages ◽  
Yield Distribution ◽  
The Impact

AbstractThe IPCC indicates that global mean temperature increases of 2°C or more above preindustrial levels negatively affect such crops as wheat. Canadian climate model projections show warmer temperatures and variable rainfall will likely affect Saskatchewan’s canola and spring wheat production. Drier weather will have the greatest impact. The major climate change challenges will be summer water availability, greater drought frequencies, and crop adaptation. This study investigates the impact of precipitation and temperature changes on canola and spring wheat yield distributions using Environment Canada weather data and Statistics Canada crop yield and planted area for 20 crop districts over the 1987–2010 period. The moment-based methods (full- and partial-moment-based approaches) are employed to characterize and estimate asymmetric relationships between climate variables and the higher-order moments of crop yields. A stochastic production function and the focus on crop yield’s elasticity imply choosing the natural logarithm function as the mean function transformation prior to higher-moment function estimation. Results show that average crop yields are positively associated with the growing season degree-days and pregrowing season precipitation, while they are negatively affected by extremely high temperatures in the growing season. The climate measures have asymmetric effects on the higher moments of crop yield distribution along with stronger effects of changing temperatures than precipitation on yield distribution. Higher temperatures tend to decrease wheat yields, confirming earlier Saskatchewan studies. This study finds pregrowing season precipitation and precipitation in the early plant growth stages particularly relevant in providing opportunities to develop new crop varieties and agronomic practices to mitigate climate changes.

scholarly journals Impact Assessment of Climate Change on Paddy Yield: A Case Study of Nepal Agriculture Research Council (NARC), Tarahara, Nepal

1970 ◽  
Vol 8 (3) ◽  
pp. 147-167 ◽  
Author(s):  
Yam K Rai ◽  
Bhakta B Ale ◽  
Jawed Alam
Keyword(s):  
Climate Change ◽  
Solar Radiation ◽  
Research Council ◽  
Crop Yields ◽  
Rice Yield ◽  
Weather Data ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
The Impact

Climate change and global warming are burning issues, which significantly threat agriculture and global food security. Change in solar radiation, temperature and precipitation will influence the change in crop yields and hence economy of agriculture. It is possible to understand the phenomenon of climate change on crop production and to develop adaptation strategies for sustainability in food production, using a suitable crop simulation model. CERES-Rice model of DSSAT v4.0 was used to simulate the rice yield of the region under climate change scenarios using the historical weather data at Nepal Agriculture Research Council (NARC) Tarahara (1989-2008). The Crop Model was calibrated using the experimental crop data, climate data and soil data for two years (2000-2001) and was validated by using the data of the year 2002 at NARC Tarahara. In this study various scenarios were undertaken to analyze the rice yield. The change in values of weather parameters due to climate change and its effects on the rice yield were studied. It was observed that increase in maximum temperature up to 2°C and 1°C in minimum temperature have positive impact on rice yield but beyond that temperature it was observed negative impact in both cases of paddy production in ambient temperature. Similarly, it was observed that increased in mean temperature, have negative impacts on rice yield. The impact of solar radiation in rice yield was observed positive during the time of study period. Adjustments were made in the fertilizer rate, plant density per square meter, planting date and application of water rate to investigate suitable agronomic options for adaptation under the future climate change scenarios. Highest yield was obtained when the water application was increased up to 3 mm depth and nitrogen application rate was 140 kg/ha respectively. DOI: http://dx.doi.org/10.3126/jie.v8i3.5941 JIE 2011; 8(3): 147-167

Geographical and seasonal variation of harbour porpoise (Phocoena phocoena) presence in the German Baltic Sea revealed by passive acoustic monitoring

2007 ◽  
Vol 87 (1) ◽  
pp. 165-176 ◽  
Author(s):  
Ursula K. Verfuß ◽  
Christopher G. Honnef ◽  
Anja Meding ◽  
Michael Dähne ◽  
Roger Mundry ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Baltic Sea ◽  
Research Effort ◽  
Natura 2000 ◽  
Acoustic Monitoring ◽  
Harbour Porpoise ◽  
Passive Acoustic Monitoring ◽  
Cetacean Species ◽  
Passive Acoustic ◽  
The Impact

The harbour porpoise is the only resident cetacean species in the German Baltic Sea. Within the last several decades this harbour porpoise stock declined drastically, causing deep concern about its status. Plans of the German government for proposing Marine Protected Areas (MPAs) to implement Natura 2000 and for assessing the impact of offshore windmill constructions on the marine environment led to an increased research effort on the harbour porpoise in German waters. For the first time, long-term passive acoustic monitoring has been conducted in the German Baltic Sea from the Kiel Bight to the Pomeranian Bay from August 2002 to December 2005. Porpoise detectors (T-PODs) have been installed five to seven metres below the water surface at up to 42 measuring positions throughout the investigated area, registering the exact times of echolocation signals of passing harbour porpoises. The proportion of monitored days with porpoise detection in each quarter of the years has been analysed. A correlation of the results with the longitude of the measuring position revealed a significant decrease from west to east in the percentage of days with porpoise detections. Comparison of data gathered in the first quarters with the third quarters of the monitoring years displayed a seasonal variation with fewer days of porpoise detections in winter time than in summer time. Nevertheless, harbour porpoises have been detected year-round at most of the measuring positions in the German Baltic Sea. The present study clearly indicates a regular use of the German Baltic Sea by harbour porpoises with a geographical and seasonal variation in the usage of the German Baltic Sea. The larger numbers of harbour porpoise detections in spring to autumn compared with winter suggests that the German Baltic Sea is an important breeding and mating area for these animals.

scholarly journals Using Machine Learning and Feature Selection for Alfalfa Yield Prediction

AI ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 71-88
Author(s):  
Christopher D. Whitmire ◽  
Jonathan M. Vance ◽  
Hend K. Rasheed ◽  
Ali Missaoui ◽  
Khaled M. Rasheed ◽  
...  
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Crop Yields ◽  
Bayesian Regression ◽  
Weather Data ◽  
Support Vector ◽  
Yield Prediction ◽  
Selection Methods ◽  
Yield Data ◽  
The Impact

Predicting alfalfa biomass and crop yield for livestock feed is important to the daily lives of virtually everyone, and many features of data from this domain combined with corresponding weather data can be used to train machine learning models for yield prediction. In this work, we used yield data of different alfalfa varieties from multiple years in Kentucky and Georgia, and we compared the impact of different feature selection methods on machine learning (ML) models trained to predict alfalfa yield. Linear regression, regression trees, support vector machines, neural networks, Bayesian regression, and nearest neighbors were all developed with cross validation. The features used included weather data, historical yield data, and the sown date. The feature selection methods that were compared included a correlation-based method, the ReliefF method, and a wrapper method. We found that the best method was the correlation-based method, and the feature set it found consisted of the Julian day of the harvest, the number of days between the sown and harvest dates, cumulative solar radiation since the previous harvest, and cumulative rainfall since the previous harvest. Using these features, the k-nearest neighbor and random forest methods achieved an average R value over 0.95, and average mean absolute error less than 200 lbs./acre. Our top R2 of 0.90 beats a previous work’s best R2 of 0.87. Our primary contribution is the demonstration that ML, with feature selection, shows promise in predicting crop yields even on simple datasets with a handful of features, and that reporting accuracies in R and R2 offers an intuitive way to compare results among various crops.

scholarly journals Multi-Step Calibration Approach for SWAT Model Using Soil Moisture and Crop Yields in a Small Agricultural Catchment

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2238
Author(s):  
Francis Kilundu Musyoka ◽  
Peter Strauss ◽  
Guangju Zhao ◽  
Raghavan Srinivasan ◽  
Andreas Klik
Keyword(s):  
Soil Moisture ◽  
Groundwater Flow ◽  
Surface Runoff ◽  
Crop Yields ◽  
Swat Model ◽  
Agricultural Watershed ◽  
Quantitative Prediction ◽  
Sediment Yields ◽  
The Impact ◽  
Calibration Approach

The quantitative prediction of hydrological components through hydrological models could serve as a basis for developing better land and water management policies. This study provides a comprehensive step by step modelling approach for a small agricultural watershed using the SWAT model. The watershed is situated in Petzenkirchen in the western part of Lower Austria and has total area of 66 hectares. At present, 87% of the catchment area is arable land, 5% is used as pasture, 6% is forested and 2% is paved. The calibration approach involves a sequential calibration of the model starting from surface runoff, and groundwater flow, followed by crop yields and then soil moisture, and finally total streamflow and sediment yields. Calibration and validation are carried out using the r-package SWATplusR. The impact of each calibration step on sediment yields and total streamflow is evaluated. The results of this approach are compared with those of the conventional model calibration approach, where all the parameters governing various hydrological processes are calibrated simultaneously. Results showed that the model was capable of successfully predicting surface runoff, groundwater flow, soil profile water content, total streamflow and sediment yields with Nash-Sutcliffe efficiency (NSE) of greater than 0.75. Crop yields were also well simulated with a percent bias (PBIAS) ranging from −17% to 14%. Surface runoff calibration had the highest impact on streamflow output, improving NSE from 0.39 to 0.77. The step-wise calibration approach performed better for streamflow prediction than the simultaneous calibration approach. The results of this study show that the step-wise calibration approach is more accurate, and provides a better representation of different hydrological components and processes than the simultaneous calibration approach.

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