توزیع مکانی برخی ویژگی‌های فیزیکی و شیمیایی خاک در برخی از اراضی زراعی استان اصفهان

نوع مقاله : مقاله پژوهشی

نویسندگان

بخش تحقیقات خاک و آب، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان اصفهان، سازمان تحقیقات، آموزش و ترویج کشاورزی، اصفهان، ایران

چکیده

آگاهی ازساختار وابستگی مکانی ویژگی‌های مختلف خاک در مزارع برای دستیابی به تولید بیشتر و مدیریت بهتر حائز اهمیت است. این پژوهش در سال 1395 بر روی تعداد 118 نمونه خاک از اراضی مناطق مختلف استان اصفهان، باهدف بررسی تغییرات مکانی برخی ویژگی‌های شیمیایی در خاک انجام شد. همبستگی مکانی هر متغیر با نیم‌تغییرنما مشخص و بهترین مدل برازش داده‌شده برای هر متغیر، با استفاده از نرم‌افزار  GS+نسخه 9، انتخاب شد. با استفاده از روش‌های درون‌یابی، کریجینگ معمولی، کوکریجینگ و روش وزن دهی عکس فاصله با توان‌های 1 تا 3 درون‌یابی انجام شد و میزان دقت نقشه پراکنش این متغیرها به کمک معیارهای آماری میانگین انحراف خطا (MBE) و ریشه میانگین مربعات خطا (RMSE) محاسبه گردید. نتایج تجزیه زمین‌آماری نشان داد که پتاسیم، درصد شن و pH دارای همبستگی مکانی قوی و سایر ویژگی‌های موردبررسی از همبستگی مکانی متوسطی در سطح منطقه برخوردار بودند. بهترین مدل ساختار مکانی برای متغیرهای فسفر، EC، CEC، درصد رس و سیلت مدل نمایی و برای پتاسیم، pH، درصد شن و کربن آلی مدل کروی بوده است. همچنین EC خاک کمترین شعاع تأثیر (86/14 کیلومتر) و pH بیشترین شعاع تأثیر (حدود 71 کیلومتر) را داشتند. بر اساس نتایج، برای متغیرهای پتاسیم، pH و EC روش وزن دهی عکس فاصله با توان 1 (IDW-1) به ترتیب با مقادیر RMSE معادل 171/0، 152/0 و 171/0 و برای سایر متغیرهای کربن آلی، فسفر، بافت، CEC به ترتیب با مقادیر RMSE  11/0، 199/0، 155/0 و 156/0 روش کریجینگ معمولی به‌عنوان بهترین روش‌های درون‌یابی شناخته شدند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Spatial distribution of some soil physico-chemical properties in agricultural soils of Isfahan province

نویسندگان [English]

  • parisa MASHAYEKHI
  • Alireza Marjovvi
Soil and Water Research Department, Isfahan Agricultural and Natural Resources Research and Education Center. Agricultural Research, Education and Extension organization (AREEO), Isfahan, Iran.
چکیده [English]

Knowing about the spatial dependence of different soil characteristics in farms is important to achieve more production and better management. The aim of this study was to evaluate the spatial variability and frequency distribution of some physical and chemical properties, including pH, EC, organic carbon, phosphorus and potassium that can be used by plants, texture and cation exchangble capacity, within the various landforms of Isfahan province. The study was conducted on 118 soil samples. The spatial correlation of each variable with a specific semi-variable and the best fitting model for each variable were selected using GS+ version 9 software. Interpolation was done using normal Kriging, Cokriging, and Inverse Distance Weighting with powers of 1 to 3. The accuracy of the distribution maps of these variables were evaluated by the mean deviation of error (MBE) and the root mean square error (RMSE). The results of the geostatistical analysis showed that potassium, sand percentage and pH had strong spatial dependent and the other characteristics had moderate spatial dependent. The exponential model was the most accurate to predict phosphorus, EC, CEC, clay and silt variables while potassium, pH, sand and organic carbon percentage were best fitted with an sphericalmodel. Also, EC had the smallest effective range (14.86 km) and pH had the largest effective range (around 71 km). For potassium, pH and EC variables, the Inverse Distance Weighting with the power of 1 (IDW-1) and for other variables the normal kriging method were recognized as the best interpolation methods.

کلیدواژه‌ها [English]

  • GS+ software
  • nutrient elements
  • semi-variable
  • spatial distribution

EXTENDED ABSTRACT

Introduction

Knowing about the spatial dependence of different soil characteristics in farms is important to achieve more production and better management. Soil pH, Electrical Conductivity (EC), organic matter, available phosphorus, potassium, Cation Exchange Capacity (CEC), and soil structure are some of the most important indicators of soil fertility. These soil parameters are highly variable in space and time, especially in agricultural areas, with implications for crop production.The aim of this study was to evaluate the spatial variability and frequency distribution of some physical and chemical properties, including pH, EC, organic carbon, soil available phosphorus and potassium, texture and cation exchange capacity.

Methods

The study was conducted on 118 soil samples, in agricultural lands of different regions of Isfahan province in 2016. The spatial correlation of each variable with a specific semi-variable and the best fitting model for each variable were selected using GS+ version 9 software. Interpolation was done using normal Kriging, Cokriging, and Inverse Distance Weighting with powers of 1 to 3 methods. The accuracy of the distribution maps of these variables were evaluated by the Mean bias error (MBE) and the root mean square error (RMSE).

Results and Discussion

The results of the geostatistical analysis showed that potassium, sand percentage and pH had strong spatial dependent and the other characteristics had moderate spatial dependent. The strong spatial dependence due to the effect of intrinsic factors such as parent material, relief and soil types. The moderate spatial dependence could result from variation in environmental factors such as flood water, irrigation, fertilizeir addition, high water table level or agriculture practices and different agricultural managements. The exponential model was the most accurate to predict phosphorus, EC, CEC, clay and silt variables while potassium, pH, sand and organic carbon percentage were best fitted with an spherical model. Also, EC had the smallest effective range (14.86 km) and pH had the largest effective range (around 71 km). For potassium, pH and EC variables, the Inverse Distance Weighting with the power of 1 (IDW-1), RMSE equal to 0.171, 0.152, and 0.171 respectively, and for organic carbon, Phosohorus, texture and CEC, RMSE equal to 0.11, 0.199, 0.155, and 0.156, respectively,  the normal kriging method were recognized as the best interpolation methods. Spatial distribution maps according to the most accurate techniques showed that the greatest soil salinity and the  sand percentage were measured in north and especially the northeast parts (in the cities of Ardestan and Aran and Bidgol in Isfahan province), also the amount of  nutrient elements and soil organic carbon reduced in these areas. The soil fertility was better in the southern and western parts of the province. In addition to management factors such as fertilization and irrigation, this is due to the climate and more rainfall in these areas, as well as the higher quality of irrigation water in these areas. In general, according to the obtained results, it was found that the geostatistical modeling can show continuous changes of soil parameters with acceptable accuracy.

 

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