PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2015 | 24 | 2 |

Tytuł artykułu

Use of geostatistics to determine the spatial variation of groundwater quality: a case study in beijing’s reclaimed water irrigation area

Autorzy

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
In order to determine the distribution variation of groundwater quality in the reclaimed water irrigation area of Beijing, the geostatistics method and ArcGIS9.3 module were used. Based on the normal distribution testing and global trends, the optimal geostatistical interpolation and optimal variogram models for each index were sampled, and the effects of artificial factors and space structure on the water quality index in the reclaimed water irrigation area were determined. The influence of human activities and structural factors on the water quality indicators of groundwater were determined using variability intensity and the nugget effect. The results showed that nitrate content was the water quality indicator in the groundwater that was most sensitive to human activities and could be used as an indicating factor to study groundwater pollution in the study area. In combination with the temporal and spatial variation of groundwater nitrate nitrogen in the study area, it was discovered that the amplification of nitrate nitrogen in the reclaimed water core irrigation area was far less than that in the non-core area. The reasons for such characteristics were vadose zone structure and human activity. The proposed results for groundwater Nitrate-nitrogen distribution can be used to quantify groundwater pollution risk and promote the utilization of wastewater.

Słowa kluczowe

Wydawca

-

Rocznik

Tom

24

Numer

2

Opis fizyczny

p.611-618,fig.,ref.

Twórcy

autor
  • College of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
autor
  • Beijing Institute of Water Science and Technology Research, Beijing 100044, China
  • Beijing Engineering Technique Research Center for Exploration and Utilization of Non-Conventional Water Resources and Water Use Efficiency, Beijing, 100044, China

Bibliografia

  • 1. GHAMARNIA H., SEPEHRI S., Different irrigation regimes affect water use, yield and other yield components of safflower (Carthamus tinctorius L.) crop in a semi-arid region of Iran. Journal of food agriculture & environment. 8, (2), 590, 2010.
  • 2. NOSHADI M., SEPASKHAH A. R., Application of geostatistics for potential evapotranspiration estimation. Iranian Journal of Science and Technology. Transaction B,Technology. 29, (3), 343, 2005.
  • 3. ASSAF H., SAADEH M., Geostatistical assessment of groundwater nitrate contamination with reflection on DRASTIC vulnerability assessment: the case of the upper Litani basin Lebanon. Water Resour. Manag., 23, (4), 775, 2009.
  • 4. VAFAKHAH M., Application of artificial neural networks and adaptive neuro-fuzzy inference system models to short-term streamflow forecasting. Can. J. Civ. Eng. 39, (4), 402, 2012.
  • 5. IZADY K., DAVARY A., ALIZADEH A., MOGHADDAM N. N., ZIAEI S., HASHEMINIA M., Application of NN- ARX Model to Predict Groundwater Levels in the Neishaboor Plain, Iran, Water Resour. Manag., 27, 4773, 2013.
  • 6. TA' ANY R. A., TAHBOUB A. B., SAFFARINI G. A., Geostatistical analysis of spatiotemporal variability of groundwater level fluctuations in Amman-Zarqa basin, Jordan: a case study. Environ. Geol., 57, (3), 525, 2009.
  • 7. TRIKI I., TRABELSI N., HENTATI I., ZAIRI M., Groundwater levels time series sensitivity to pluviometry and air temperature: A geostatistical approach to Sfax region, Tunisia. Environ. Monit. Assess., 186, 1593, 2014.
  • 8. NAS B., Geostatistical Approach to Assessment of Spatial Distribution of Groundwater Quality. Pol. J. Environ. Stud., 18, 1073, 2009.
  • 9. ANNA P., Spatial Variability of Total and Mineral Nitrogen Content and Activities of the N-Cycle Enzymes in a Luvisol Topsoil. Pol. J. Environ. Stud., 20, (6), 1565, 2011.
  • 10. LOKMAN H. T., SERMIN T. Spatial-Temporal Variation of Sulphur Dioxide Concentration, Source, and Probability Assessment Using a GIS-Based Geostatistical Approach. Pol. J. Environ. Stud., 22, 1491, 2013.
  • 11. ELSHALL A. S., TSAI F. T. C., HANOR J. S., Indicator geostatistics for reconstructing Baton Rouge aquifer-fault hydrostratigraphy, Louisiana, USA. Hydrogeol. J., 21, (8), 1731,2013.
  • 12. ZAWADZKI J., FABIJANCZYK P., BADURA H., Estimation of methane content in coal mines using supplementary physical measurements and multivariable geostatistics. Int. J. Coal Geol., 118, 33, 2013.
  • 13. CHRISTAKOS G., Modern spatiotemporal geostatistics, New York, USA: Oxford universAHMADI S. A., SEDGHAMIZ. Geostatistical analysis of spatial and temporal variations of groundwater level. Environ. Monit. Assess., 129, 277, 2007.
  • 14. BARCA E., PASSARELLA G., Spatial evaluation of the risk of groundwater quality degradation. A comparison between disjunctive Kriging and geostatistical simulation. Environ. Monit. Assess., 137, 261, 2008.
  • 15. ADHIKARY P., CHANDRASEKHARAN H., CHAKRABORTY D., KAMBLE K., Assessment of groundwater pollution in West Delhi, India using geostatistical approach. Environ. Monit. Assess., 167, 599, 2010.
  • 16. ADHIKARY P., CH. JYOTIPRAVA D., RENUKABALA B., CHANDRASEKHARAN H., Indicator and probability Kriging methods for delineating Cu, Fe, and Mn contamination in groundwater of Najafgarh Block, Delhi, India. Environ. Monit. Assess., 176, 663, 2011.
  • 17. THEODOSSIOU N., LATINOPOULOS P., Evaluation and optimization of groundwater observation networks using the Kriging methodology. Environ. Modell. Softw., 21, 991, 2006.
  • 18. BAALOUSHA H., Assessment of a groundwater quality monitoring network using vulnerability mapping and geostatistics: A case study from Heretaunga Plains. New Zealand, Agr. Water Manage., 97, 240, 2010.
  • 19. WA‘IL Y., RIHANI J., Application of the high performance computing techniques of parflow simulator to model groundwater flow at Azraq basin. Water Resour. Manag., 21, 409, 2007.
  • 20. ANDRADE A. I. A. S., STIGTER T. Y., Multi-method assessment of nitrate and pesticide contamination in shallow alluvial groundwater as a function of hydrogeological setting and land use. Agr. Water Manage., 96, 1751, 2009.
  • 21. BONTONA A., ROULEAUB A., BOUCHARDA C., RODRIGUEZC M., Assessment of groundwater quality and its variations in the capture zone of a pumping well in an agricultural area. Agr. Water Manage., 97, 824, 2010.
  • 22. CARREIRA P., MARQUES J., PINA A., GOMES A., FERNANDES P., SANTOS F., Groundwater assessment at Santiago Island (Cabo Verde): A multidisciplinary approach to a recurring source of water supply. Water Resour. Manag., 24, 1139, 2010.
  • 23. Beijing Water Resources Bureau. Report of Beijing Water Resources Bureau. Beijing Water Resources Bulletin. 2011.
  • 24. YIN S., WU W., LIU H., ZHANG X., Spatial variability and pollution cause analysis of nitrate content for area irrigated with reclaimed water. Transactions of the Chinese Society of Agricultural Engineering. 28, (18), 200, 2012.
  • 25. ADHIKARY P., DASH C., BEJ R., CHANDRASEKHARAN H., Indicator and probability Kriging methods for delineating Cu, Fe, and Mn contamination in groundwater of Najafgarh Block, Delhi, India. Environ. Monit. Assess., 176, (1), 663, 2011.
  • 26. GUNDOGDU K., GUNEY I. Spatial analysis of groundwater levels using universal Kriging. J Earth Syst Sci. 116, (1), 49, 2007.
  • 27. CARUSO C., QUARTA F. Interpolation methods comparison[J]. Comput. Math. Appl., 35,(12): 109,1998.
  • 28. LI W. Q., ZHANG M., LI H. F., The study of soil nitrate status in fields under plastic house gardening. Acta Pedologica Sinica. 39, (2), 283, 2002.
  • 29. NOSHADI M., SEPASKHAH A.R., Application of geostatistics for potential evapotranspiration estimation. Iran. J. Sci. Technol., 29, (3), 343, 2005.
  • 30. WHO (World Health Organization). Guidelines for drinking water quality, third edition. Geneva: WHO. 2004.
  • 31. EPA (U.S. Environmental Protection Agency). Primary Drinking Water Regulations. 2001.
  • 32. Quality standard for ground water (GB/T14848-93, CHN). 1993.
  • 33. CHEN L., FENG S., HAN Z., MENG G., CHEN S., Evaluation of the Shallow Groundwater Quality in Daxing District of Beijing City. China Rural Water and Hydropower. (5), 2, 2004.
  • 34. XU K., Analysis on the Influence of Infiltration of Recycled Water to the Groundwater Quality. Yellow River. 34, (4), 55, 2012.

Typ dokumentu

Bibliografia

Identyfikatory

Identyfikator YADDA

bwmeta1.element.agro-331e818b-f591-44f3-9fb5-dfa2f76a6c4b
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.