کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4492142 1623284 2016 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Considerations Regarding the Agronomical Variables Associated to the Performances of SWAT Model Simulations in the Romanian eco-climatic Conditions
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم کشاورزی و بیولوژیک (عمومی)
پیش نمایش صفحه اول مقاله
Considerations Regarding the Agronomical Variables Associated to the Performances of SWAT Model Simulations in the Romanian eco-climatic Conditions
چکیده انگلیسی

The main objective of the study is to optimize the agronomical variables for prediction of water quality at river basin scale for various time intervals using the numerical modeling of the cumulative impact of agricultural operations due to the use of chemical inputs and specific tillage. SWAT (Soil & Water Assessment Tool) model was developed to determine with reasonable accuracy the effect of potential management decisions regarding the water use, sediment transport, and chemical transformations of substances discharged into surface waters in rural ungauged basins. The information flow must start with the adaptation of the inputs required by the SWAT model for the accurate definition of Hydrological Response Units that include unique combinations between slope, soil type, and land use/land cover. All thematic layers must be related to the same coordinate system using the 1970 stereographic projection and Dealul Piscului 1970 geographic coordinate system that are in force in Romania. The meteorological inputs used in SWAT include rainfall, maximum and minimum temperature, solar radiation, relative humidity and wind speed. The prediction of SWAT model considering the diffuse sources of pollution (land areas with intensive agriculture) were analyzed considering the cropping technologies used in various Romanian hydrographical basins, i.e. Ialomita River, Calmatui River, Teleajen River, and Mostistea River. The main constraints observed in the use of SWAT model for efficient predictions in various control sections can be adjusted by the careful selection/adaptation of inputs, the optimal calibration/sensitivity analysis of the model, and the updating of information regarding the land use/land cover in a specific river basin.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Agriculture and Agricultural Science Procedia - Volume 10, 2016, Pages 83–93
نویسندگان
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