Geospatial modelling for optimum management of fertilizer application and environment protection
- 165 Downloads
Soil as an important source, guaranties the plant growth and supplies more than 97% of food need of world. Knowledge of soil spatial variability is important in natural and environment resource management, interpolation and soil sampling design, but requires a considerable amount of geo-referenced data. Soil cation exchange capacity (CEC) is a vital indicator of soil fertility quality and pollutant sequestration capacity. Plants such as rice need to provide their nutrient elements by using fertilizers for much more production in surface unit. For this purpose, it is essential to recognize macro-elements amount in soils and prepare their ideal maps. 247 soil samples were collected from depth 0–30 cm with distance minimum 250 m and maximum 1500 m using a stratified random sampling scheme on central areas of Guilan province located in north of Iran. CEC, total nitrogen, available potassium and phosphorus maps prepared using kriging geostatistical method. Evaluation criteria values of root mean square error (RMSE) and mean absolute error (MAE) derived for potassium 27.84 and 0.106, phosphorus 8.17 and 4.63, total nitrogen 0.059 and 0.025 and CEC 4.06 and 3.09, respectively. Criteria value of RMSE and MAE showed that accuracy of prepared maps was ideal. The fit of the experimental semivariograms to the theoretical models indicated that kriging could successfully interpolate soil variables. Thus, the kriging geostatistical method used on a large scale could accurately evaluate the spatial variability of soil nutrient properties. With regard to soil nitrogen and phosphorus maps, application of more amounts of nitrate and phosphorus fertilizers than their optimum level cause ground waters pollution and environment damages therefore their application must be carried out with high consideration. Potash fertilizers consumption in land with high CEC results its fixation, too. Precise attention to CEC map and on-time fertilizer application can solve this problem. Therefore, accurate notice to different amounts of these parameters in prediction maps, critical and optimum levels can well manage fertilizers application, prevents additional costs to farmer, pollution of ground waters and environment resources.
KeywordsCEC Kriging Nitrogen Paddy soil Phosphorus Potassium
The authors wish to express their sincere thanks to the Department of soil science, University of Guilan for supporting field studies and samplings. We would also like to thank all the members of the Soil Science Laboratory of Faculty of Agriculture, University of Guilan, for providing the facilities to carry out this work and for their suggestions. The authors are grateful to anonymous reviewers who considerably improved the quality of the manuscript.
- Buvaneshwari S, Riotte J, Sekhar M, Mohan Kumar MS, Sharma AK, Duprey JL, Audry S, Giriraja PR, Praveenkumarreddy Y, Moger H, Durand P, Braun JJ, Ruiz L (2017) Groundwater resource vulnerability and spatial variability of nitrate contamination: insights from high density tubewell monitoring in a hard rock aquifer. Sci Total Environ 579:838–847. doi: 10.1016/j.scitotenv.2016.11.017 CrossRefGoogle Scholar
- Ducci D, Condesso de Melo MT, Preziosi E, Sellerino M, Parrone D, Ribeiro L (2016) Combining natural background levels (NBLs) assessment with indicator kriging analysis to improve groundwater quality data interpretation and management. Sci Total Environ 569–570:569–584. doi: 10.1016/j.scitotenv.2016.06.184 CrossRefGoogle Scholar
- Kauwenbergh S, Stewart M, Mikkelsen R (2013) World reserves of phosphate rock: a dynamic and unfolding story. Better Crops 97:18–20. http://www.ipni.net/publication/bettercrops.nsf/0/C3AB0523A890EBC685257BD50055E09A/$FILE/BC3%202013%20-%20p18.pdf
- Simpson RJ, Stefanski A, Marshall DJ, Moore AD, Richardson AE (2015) Management of soil phosphorus fertility determines the phosphorus budget of a temperate grazing system and is the key to improving phosphorus efficiency. Agric Ecosyst Environ 212:263–277. doi: 10.1016/j.agee.2015.06.026 CrossRefGoogle Scholar
- Sims JT, Kleinman PJA (2005) Managing agricultural phosphorus for environmental protection. In: Sims JT, Sharpley AN (eds) Phosphorus: agriculture and the environment. ASA-CSSA-SSSA, Madison, p 1021–1068. https://dl.sciencesocieties.org/publications/books/pdfs/agronomymonogra/phosph
- Soil Survey Staff (2014a). Kellogg soil survey laboratory methods manual. Soil survey investigations report no. 42, Version 5. In: Burt R, Soil Survey Staff (eds) United States Department of Agriculture, Natural Resources Conservation Service. https://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb1253871.pdf
- Soil Survey Staff (2014b) Keys to soil taxonomy, 12th edn. United States Department of Agriculture, Washington DC. https://www.nrcs.usda.gov/wps/PA_NRCSConsumption/download/?cid=stelprdb1252094&ext=pdf
- SPSS 24 (2016) Statistical analysis software (Standard Version). SPSS Inc., USAGoogle Scholar
- Sunohara MD, Gottschall N, Craiovan E, Wilkes G, Topp E, Frey SK, Lapen DR (2016) Controlling tile drainage during the growing season in Eastern Canadato reduce nitrogen, phosphorus, and bacteria loading to surface water. Agric Water Manag 178:159–170. doi: 10.1016/j.agwat.2016.08.030 CrossRefGoogle Scholar