نوع مقاله : مقاله پژوهشی

نویسندگان

1 عضوهیات علمی

2 عضوهیات علمی مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان کرمانشاه

چکیده

در مدیریت بهینه و پایدار اراضی کشاورزی، تهیه نقشه تخمین احتمال ویژگی های خاک از جمله کربن آلی و عناصر غذایی مبتنی برمقادیرکمتر یا بیشتر از یک حد آستانه از اهمیت زیادی برخوردار است. یکی از راه های تهیه چنین نقشه هایی استفاده از روش های زمین آمار ناپارامتری مانند کریجینگ شاخص می باشد. در این مطالعه با استفاده از کریجینگ شاخص، نقشه احتمال کمبود و فزونی کربن آلی و فسفرقابل جذب خاک برای بخشی از اراضی ایستگاه تحقیقات کشاورزی اسلام آباد غرب واقع در استان کرمانشاه تهیه گردید. به منظور اجرای این پژوهش از داده های میراثی خاک شامل217 نمونه خاک سطحی (عمق0-30 سانتیمتر) با فواصل نمونه برداری 50 متر استفاده شد. پس از پردازش های اولیه آماری،تغییرنمای شاخص براساس مقادیر آستانه 1/2 درصد برای کربن آلی و 15 میلی گرم بر کیلوگرم برای فسفرقابل جذب محاسبه گردید و بر مبنای جمع باقیمانده مربعات خطای کمتر، مدل نمائی به عنوان بهترین مدل برازش یافته بر تغییرنمای شاخص تعیین شد. داده های اعتبارسنجی، از روش حذف یک داده و اجرای مدل به دست آمد. سپس برای ارزیابی کارایی کریجینگ شاخص، منحنی مشخصه عامل گیرنده ترسیم و مساحت زیرمنحنی محاسبه گردید. مساحت زیرمنحنی مشخصه عامل گیرنده به ترتیب برای فسفر قابل جذب و کربن آلی 0/7956 و 0/8005به دست آمد که نشان می دهد کریجینگ شاخص در تخمین این متغیرها نسبتاً خوب عمل نموده است. بطورکلی می توان ذکر نمود کاربردکود بر اساس نقشه های احتمال خصوصیات حاصلخیزی خاک، سبب کاهش هزینه و افزایش تولید پایدار می گردد.

کلیدواژه‌ها

عنوان مقاله [English]

Probability mapping of Deficiency or Excess of Soil Available Phosphorus and Organic Carbon by Indicator Kriging

نویسنده [English]

  • shahrokh fatehi 1

1

2

چکیده [English]

Probability mapping of soil proprieties Including soil organic carbon and nutrients based on threshold values play important role in optimum land management and sustainable agriculture development. In order to map based on critical limits need to use non parametric geostatistics methods such as kriging indicator. In this study, using indicator kriging, probability map of deficiency or excess of soil available phosphorusand organic carbon was prepared in part of Eslamabad-e Gharbagriculture research station in Kermanshah province. The soil legacy data including 217 surface soil samples on an almost regular grid, about 50 m apart is used to perform research. After preliminary statistical processing, indicator variogram was drawn based on threshold values 1.2% and 15ppm for soil organic carbon and available phosphorus, respectively. Exponential model as the best model fitted to indicator variogram is selected based on minimum residual sum of squares. The necessary data for validation was achieved through leave-one-out cross-validation (LOOCV).For assessing the performance of indicator kriging is used the area under the curve (AUC) of receiver operating characteristic (ROC). Area under the ROC curve was calculated for phosphorus and soil organic carbon was 0.796 and 0.800, respectively. These results indicated that the indicator kriging to predict these variables have relatively good performance. In general, it can be said that using fertilizer based on probability maps of soil fertility properties lead to reduce cost and increase sustainable food production.

کلیدواژه‌ها [English]

  • soil properties
  • Threshold values
  • Indicator variogram
  • Receiver operating characteristic curve
Reference
Arslan H. 2012. Spatial and temporal mapping of groundwater salinity using ordinary kriging and indicator kriging: The case of Bafra Plain, Turkey. Agricultural Water Management, 113: 57- 63.
Banaie M.H., Momeni A., Baybordi M., and Malakoti M.J. 2005. Soils of Iran. Sana Publications, Tehran, Iran, 486p. (In Persian) 
Cambardella C.A., Boorman T.B., Novak J.M., Parkin T.B., Karlen D.L., Turco R.F., and Konopka A.E. 1994. Field-scale variability of soil properties in central Iowa soils. Soil Science Society American Journal, 58: 1501-1511.
Chu H.J., Lin Y.P., Jang C.S., and Chang T.K. 2010. Delineating the hazard zone of multiple soil pollutants by multivariate indicator kriging and conditioned Latin hypercube sampling. Geoderma, 158: 242-251.
Cockx L., Meirvenne M.V., and DeVos B. 2007. Using the EM38DD soil sensor to delineate clay lenses in a sandy forest soil. Soil Science Society American Journal, 71: 1314-1322.
Delbari M., Amiri M., and Motlagh M.B. 2014. Assessing groundwater quality for irrigation using indicator kriging method. Applied Water Science, 5: 1-11.
Fatehi S.H. 2012. Spatial variability of organic carbon, available potassium and phosphorous in Eslamabad-Gharb agriculture research station, Kermanshah province. Agronomy Journal (Pajouhesh & Sazandegi), 97: 29-38. (In Persian)
Fawcett T. 2006. An introduction to ROC analysis. Pattern Recognition Letters, 27: 861–874.
Ghaemi J. 2005. Geology map of Kerned, scale: 1:100000, Geological Survey and Mineral Exploration of Iran.
Gomes F.P., and Garcia C.H. 2002. Estatrstica Aplicada an Experimentos Agronomicos e Florestais. FEALQ: Piracicaba, 309p. (In Portuguese)
Goovaerts P. 1997. Geo-statistics for Natural Resources Evaluation. Oxford University Press, New York, 783p.
Goovaerts P., Webster R., and Dubois J.P. 1997. Assessing the risk of soil contamination in the Swiss Jura using indicator geo-statistics. Environmental and Ecological Statistics, 4(1): 31-48.
Greve M.H., Greve M.B., Bou Kheir R., Bocher P.K., Larsen R., and McCloy K. 2010. Comparing Decision Tree Modeling and Indicator Kriging for Mapping the Extent of Organic Soils in Denmark. In: Boettinger J. et al., (Ed.), Digital Soil Mapping - Bridging Research Environmental Application & Operation. Springer Netherlands, pp. 267-280.
Khosh fetrat G.R. 1998. Semi Detailed Soil Survey and Land Classification for Irrigation in Eslamabade-Gharb Research Station. Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran, 35p. (In Persian).
Lark P.M., and Ferguson R.B. 2004. Mapping risk of soil nutrient deficiency or excess by disjunctive and indicator kriging. Geoderma, 118: 39–53.
Lin Y.P., Cheng B.Y., Shyu G.S., and Chang T.K. 2010. Combining a finite mixture distribution model with indicator kriging to delineate and map the spatial patterns of soil heavy metal pollution in Chunghua County, central Taiwan. Environmental Pollution, 158: 235–244.
Olfati M. 1996. Study of Soil Fertility in Eslamabade-Gharb Research Station. Kermanshah Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Kermanshah, Iran, 15p. (In Persian)
Olsen S. R., Cole C.V., Watanabe F.S., and Dean L. 1954. Estimation of Available Phosphorous in Soils by Extraction with Sodium Bicarbonate. USDA, Cire. 939, U. S. Gover. Prin. Office, Washington DC.
Pontius J.R.G., and Schneider L.C. 2001. Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA. Agriculture Ecosystem Environment, 85:239–248.
Rossiter D.G. 2012. Applied Geo-statistics, Exercise 7: Geo-statistical risk mapping. ITC, Enschede, the Netherland, 38p.
Rossiter D.G., and Loza A.V. 2012. Technical note: Analyzing Land Cover Change with Logistic Regression in R (Version 2.2, First version April 2004). ITC, Enschede, the Netherland. 67p.
Shapiro S.S., and Wilk M.B. 1965. An analysis of variance test for normality (complete samples). Biometrika, 52: 591-611.
Triantafilis J., Odeh I.O.A., Warr B., and Ahmed M.F. 2004. Mapping of salinity risk in the lower Namoi valley using non-linear kriging methods. Agricultural Water Management, 69: 203–231.
Walkley A., and Black I.A. 1934. An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Science, 37: 29–38.
Wani M.A., Wani J.A., Bhat M.A., Kirmani N.A., Wani Z.M., and Bhat S.N. 2013. Mapping of soil micronutrients in Kashmir agricultural landscape using ordinary Kriging and indicator approach. Journal of Indian Society Remote Sensing, 41(2): 319–329.
Webster R., and Oliver M.A. 2001. Geo-statistics for Environmental Scientists. John Wiley & Sons, Chichester, 271p.