APPLICATION OF PHYSICALLY-BASED EROSION 3D MODEL IN SMALL CATCHMENT

The scope of this study is the application of a new approach for the estimation of potential soil erosion using a physically-based erosion model Erosion 3D for modelling potential erosion in the Myjava River basin, Slovakia. Erosion 3D is a physically-based model for predicting soil erosion by water on agricultural land (Schmidt, 1996). The model is predominantly based on physical principles and it simulates surface runoff, erosion, deposition and the detachment of soil particles for single events, and provides good tool to simulate and quantify soil erosion, but has not been established in Slovakian basins yet. The soil system of Erosion 3D is based on the fourth edition of the soil classification of “Bodenkundliche Kartieranleitung” („KA 4“, AG Boden, 1994). Because of different soil classification it was required in the first step to create an overplot of KA 4 textural system with the USDA textural system used in Slovakia. The model requires three input parameter - relief, precipitation and soil parameters. The first two parameters are easy to obtain but soil input parameters are more complicated mainly for different areas where the model was calibrated and validated. In this study we focused to creation of the soil input data sets for Slovak condition including establishment of Parameter catalogue for every soil input parameters. The catalogue has been configured based on overplotted textural triangle. The Erosion 3D model was applied to a small catchment Tura Luka situated in the Myjava Hill Land which is known for its quick runoff response and related muddy floods. Four scenarios of initial moisture parameter, which is considered as the most sensitive soil input parameter, were applied in fallow and winter wheat. Simulations were done for 100-year design rainfall of 60 minutes duration. The results of potential erosion are well-capable to point to the spatial and temporal variability of the rainfall event with the wide range of the values

An assessment of soil water erosion in the Myjava hill land: The application of a physically-based erosion model

The scope of this study is an evaluation of potential soil water erosion using the physically-based erosion model, EROSION-3D. This model is event-based and calculates soil water erosion during an actual measured rainfall event. The calculations of the erosion model take advantage of a digital elevation model, precipitation and soil parameters, which are established in a specific parameter catalogue. The soil water erosion was modeled in two small catchments in the Myjava Hill Land (Slovakia), using 9 soil moisture scenarios and two different crops on arable areas. When considering the last 35 years of rainfall records at the Myjava meteorological station, three storm rainfall events were applied in the modeling. The results were statistically analyzed to figure out the differences between the model’s functional possibilities; the modeling under the various scenarios proved a strong interaction between the values of the input factors and the results of the soil erosion

Director\u27s report of research in Kansas 2002

This report contains the title, author, and publication information for manuscripts published by station scientists. It also contains a list of the research projects that were active during that period and a financial statement for the fiscal year

MODELING WATER QUALITY FOR SWITCHGRASS CROP PRODUCTION: IMPLICATIONS FOR BIOENERGY SUSTAINABILITY IN EAST TENNESSEE

With passing of the US Energy Independence and Security Act (EISA) of 2007, there has been considerable research conducted on the sustainability of bioenergy crop production in the United States; switchgrass has shown particular potential for bioenergy production in East Tennessee. Many studies evaluating the environmental impact switchgrass has on runoff and water quality use the Soil and Water Assessment Tool (SWAT) for watershed modeling. Because SWAT is a lumped watershed model, it evaluates the result of hydrological processes for each hydrologic response unit (HRU), without accounting for the physical interactions between these HRUs. The Water Erosion Prediction Project (WEPP) model is a physically derived, distributed watershed model that can simulated runoff and sediment transport within the watershed, accounting for the interactions that take place between these response units. This research sought to calibrate both a WEPP and SWAT model to measured data collected from a drainage basin in Lenoir City, Tennessee, an area known for growing switchgrass for bioenergy. In addition, this research evaluated the use of buffer strips as a sustainable approach to switchgrass implementation. Model calibration was evaluated based on the Nash-Sutcliffe Efficiency coefficient, which evaluates the extent to which a model reflects the measured data. Final discharge calibration yielded NSE coefficients of -0.18 and -0.09 for SWAT and WEPP, respectively. Final sediment calibration for the SWAT and WEPP models, however, could be calibrated to an NSE coefficient of -0.34 and -0.48, respectively. Calibration efforts failed, the WEPP model did outperform the SWAT model for runoff calibration. In simulating bioenergy buffer strips (BBSs), the WEPP model indicated that one or two strategically placed BBSs can have a 13% reduction in runoff and sediment delivery per storm event; results suggests that strategic use of bioenergy buffer strips can have improved reduction in runoff or sediment yield. The improved calibration results of the WEPP model indicated that a distributed hydrology and erosion model may be valuable for modeling water quality impacts of switchgrass production in a watershed. Results also indicated the potential for further investigation into how sediment transport is addressed in the SWAT and WEPP models

Reservoir Sedimentation Along the Upper Washita River in Western Oklahoma and Northern Texas

In response to Dust Bowl flooding of the 1930's, numerous flood control dams were built in Oklahoma and Texas to slow discharge of tributaries into the main stem of the Washita River, effectively reducing peak flows and downstream flooding. The dams in this region have a projected sediment storage lifetime of 50 years, and some are approaching the end of their projected lifetime. Field measurements where made to estimate the volume of sediment impounded behind flood control structures by first determining thickness of sediment at the dam. Next, volume of sediment was estimated by calculating it as a geometric wedge shape, thickest at the dam and tapering to zero upstream. Calculated sediment volume for each site was then compared to predictions by the WEPP (Water Erosion Prediction Project) model for each reservoir. The WEPP model was found to severely underestimate sediment in each reservoir, with no statistical significance between observed and predicted values. Further investigation indicated that 77.5% of residual could be explained by considering length of section line roads in each watershed. In addition, all flood control dams measured were found to be filled to only a fraction of their sediment storage capacity, or to contain immeasurably small amounts.Department of Geograph

Winter hydrology and soil erosion processes in an agricultural catchment in Norway

In regions with a Nordic climate, soil erosion rates in winter and early spring can exceed those occurring during other seasons of the year. In this context, this study was initiated to improve our understanding of the interaction between agricultural soils and occurring winter conditions. The main objective was to better understand how hydrological processes in a catchment are influenced by snow, ice, and freeze-thaw cycles of soils, leading to runoff and soil erosion in winter and spring conditions. For this purpose, detailed spatially and temporally distributed measurements and observations in a small catchment in Norway were executed during three consecutive winter/spring periods. During the winter/spring periods of 2013-2014, 2014-2015 and 2015-2016, soil water content, soil temperature, and snow cover properties were measured. In addition, numerous soil samples were taken to determine the soil hydraulic characteristics of the investigated soils and to quantify the changes in their macropore networks due to freeze-thaw events, using X-ray imaging. With the collected data and deduced process understanding, it was possible to model and quantify the spatial and temporal development of snow packs. Furthermore, the field observations revealed how the interaction of tillage, state of the soils and snow cover at a certain time can lead to none or extensive surface runoff and soil erosion. Integrating acquired data, observations and process knowledge facilitated advances in simulating and quantifying surface runoff and soil erosion rates across the catchment under investigation. The models applied and the maps and output derived are crucial elements for presenting current state and problems in the catchment to stakeholders (such as farmers), providing a starting point for discussing ways to prevent and reduce further runoff and erosion. For model calibration and validation, including interpretation of modelling results, good knowledge of the area and availability of detailed data are essential, especially when processes such as freezing-thawing of soils and ice layer and snow-pack dynamics have to be considered also. In order to reduce runoff and soil erosion during winter and snowmelt conditions in the future, more targeted research is required in order to address the full range of existing knowledge gaps in this field, as identified in this particular study also.</p

SPATIAL AND SEASONAL DISTRIBUTION OF CARBON DIOXIDE EMISSIONS FROM FOSSIL-FUEL COMBUSTION; GLOBAL, REGIONAL, AND NATIONAL POTENTIAL FOR SUSTAINABLE BIOENERGY FROM RESIDUE BIOMASS AND MUNICIPAL SOLID WASTE

Combustion of fossil fuels releases carbon dioxide (CO2) into the atmosphere, and has led to an increase in the atmospheric concentration of CO2. CO2 is a greenhouse gas, and the increase in concentration leads to an increase in global temperatures and global climatic change. Fossil-fuel consumption, along with cement production, is responsible for 80% of anthropogenic carbon emissions and consumption of fossil fuels continues to increase. Despite its importance to the global climate and the global carbon cycle, data for fossil fuel CO2 emissions are traditionally maintained only on national levels and annual time steps. A method is developed to improve the spatiotemporal resolution to the leading energy consuming countries of the world. The method uses energy consumption datasets as well as other ancillary datasets to apportion national annual emissions totals into sub-national and monthly emissions datasets by fuel type. Emissions patterns are highly variable both temporally and spatially by fuel type, and detailed information on the distribution of emissions improves our understanding of the global carbon cycle and leads to better understanding of the spatial and seasonal distribution of the drivers of global change. In the endeavor to develop alternatives to fossil fuels, advanced biomass energy has garnered much attention because of its renewable nature and its potential to approach carbon-neutrality. As co-products, agricultural and forestry residues as well as municipal solid waste (MSW) are potential low-cost and sustainable biomass feedstocks for energy production. The role of residue biomass within the future global energy portfolio is projected and quantified under the context of environmental and economic sustainability. The potential for residue biomass is projected for the next century under a reference (business-as-usual) scenario and a scenario that includes a hypothetical climate policy that limits carbon emissions. While residue biomass alone cannot replace fossil fuels, a substantial amount of energy potentially could come from this resource, particularly in a global economic market under a climate policy that caps CO2 emissions from fossil fuels

GIS-based modelling of agrochemical use, distribution and accumulation in the Lower Mekong Delta, Vietnam: A case study of the risk to aquaculture

In recent years, the Mekong delta has been strongly developed both for agriculture and aquaculture. However, there is scope for a negative impact of agriculture on aquaculture in term of production and quality of seafood products. Specifically, the large amount of pesticides imported and used in the Mekong delta not only help agriculture purposes but can also easily enter aquatic systems and affect aquaculture. Pesticides can be transported in the environment by chemo-dynamic procedures and hydrological processes. As a result, pesticides used in agriculture become dispersed and their residues in sediment, water and biota have been detected in the Mekong delta. This study investigated the overall pesticide process including pesticide use, modelling pesticide accumulation and evaluating the potential impact on aquaculture sites for some target aquatic species. The risk of pesticides use in the Mekong delta was addressed in three stages: (1) investigating current pesticide use status in the Mekong delta; (2) modelling pesticide loss and accumulation; (3) classifying pesticide risk areas for aquaculture of target cultured species. A survey of 334 farms covering a total area of ~20,000km2 in the Mekong delta took place between 2008 and 2009. Information on pesticide types and quantities was recorded using questionnaires, and it was found that 96 pesticides in 23 groups were popularly used for agricultural purposes. Dicarboximide, Carbamate and Conazole had the highest use at ~3000, ~2000 and ~2000 g/ha/year respectively. The survey revealed an increase in pesticide use per hectare since previous surveys in the Mekong delta in 1994, 2000, and 2004. However, the highly persistent compounds (WHO classification classes II, III and IV) appeared to have reduced in use. Insecticides previously represented >50% of the total pesticides used, however, the resent survey has shown their use has decreased to ~38%.There was a parallel increase in use of fungicides from previous levels of <30% of total pesticides to more recently ~41%. The combination of pesticide information and geo-location data enabled display and analysis of this data spatially using a Geographic Information System (GIS). A pesticide loss and accumulation model was established through combination of several sub-models including sediment loss and accumulation, direct loss, and water runoff, all of which were implemented and integrated within the GIS environment. MUSLE (Modified Universal Soil Loss Equation) was used to estimate sediment loss and accumulation in the Mekong delta and the Curve Number method (CN Method) was applied to predict water runoff and discharges and flow accumulation. Modelling commenced from the first pesticide application in April, based on 4 day time-steps. All mathematical calculations run within each time step automatically reiterated in the following time step with the new input datasets. The results from fuzzy classification of the pesticide model outcomes were considered in terms of the 96hr lethal concentration (LC50) in order to classify the risk and non-risk areas for catfish and tiger shrimp culture. The sediment loss and accumulation model shows that the highest loss of sediment was in the rainy season, especially in May to October. Vegetables and short term crop areas were found be most strongly eroded. The MUSLE model showed that the highest sediment accumulation was in the hilly areas (~1066.42 tonne/ha/year); lower in riverside areas (~230.39 tonne/ha/year) and lowest in flooded paddy areas (~150.15tonne/ha/year). Abamectin was used as an example throughout this study to estimate pesticide loss and its effects on aquaculture. The results showed that pesticide loss by runoff and sediment loss is less than the loss by half-life degradation (for Abamectin specifically). Accumulation of Abamectin occurred at highest rate in May and October and decreased with time. The spatial models showed that pesticide residues concentrated in the river and riverside areas. In order to evaluate the acute toxicity impacts, three levels of water depth in ponds were modelled as culture depths for catfish and tiger shrimp. The results show that the highest risk areas for catfish occurred in May and October with ~333,000 and ~420,000 ha at a pond depth of 0.5 m; ~136,000 and ~183,000 ha at a pond depth of 1.0 m; and ~10,840 and ~19,000 ha at a pond depth of 1.5 m. Risk areas for catfish mainly concentrated at the riverside and in part of the coastal areas. For tiger shrimp, the risk periods during the year were similar to those found for catfish. The highest risk areas for shrimp were ~648,000 and ~771,000 ha at 0.5 m pond depth; ~346,000 and ~446,700 ha at 1.0 m pond depth; and ~185,000 and ~250,000 ha at 1.5 m pond depth. Overall, deeper ponds reduced the risk. This study has developed a method to evaluate the negative impact of input pesticides to the environment from agricultural use related to fluctuation of aquaculture risk areas. The research indicates the potential relationship between pesticide input and the risk areas for aquaculture. The model has several significant uses: 1) it can provide information to policy makers for a more harmonized development of both aquaculture and agriculture in the Mekong delta in the future, 2) it provides data for aquaculture investment analysis to decrease the hazards caused by pesticide impacts, and 3) it provides a model capable of application to wide field scenarios and suitable for any pesticide type