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利用 ArcGIS 中的克里金工具在尼泊尔巴拉地区进行数字土壤制图。

Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS.

机构信息

Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, United States of America.

Nepal Agricultural Research Council, Lalitpur, Nepal.

出版信息

PLoS One. 2018 Oct 26;13(10):e0206350. doi: 10.1371/journal.pone.0206350. eCollection 2018.

Abstract

Digital soil mapping has been widely used to develop statistical models of the relationships between environmental variables and soil attributes. This study aimed at determining and mapping the spatial distribution of the variability in soil chemical properties of the agricultural floodplain lands of the Bara district in Nepal. The study was carried out in 23 Village Development Committees with 12,516 ha total area, in the southern part of the Bara district. A total of 109 surface soil samples (0 to 15 cm depth) were collected and analyzed for pH, organic matter (OM), nitrogen (N), phosphorus (P, expressed as P2O5), potassium (K, expressed as K2O), zinc (Zn), and boron (B) status. Descriptive statistics showed that most of the measured soil chemical variables (other than pH and P2O5) were skewed and non-normally distributed and logarithmic transformation was then applied. A geostatistical tool, kriging, was used in ArcGIS to interpolate measured values for those variables and several digital map layers were developed based on each soil chemical property. Geostatistical interpolation identified a moderate spatial variability for pH, OM, N, P2O5, and a weak spatial variability for K2O, Zn, and B, depending upon the use of amendments, fertilizing methods, and tillage, along with the inherent characteristics of each variable. Exponential (pH, OM, N, and Zn), Spherical (K2O and B), and Gaussian (P2O5) models were fitted to the semivariograms of the soil variables. These maps allow farmers to assess existing farm soils, thus allowing them to make easier and more efficient management decisions and maintain the sustainability of productivity.

摘要

数字土壤制图已广泛用于开发环境变量与土壤属性之间关系的统计模型。本研究旨在确定和绘制尼泊尔巴拉地区农业洪泛区土壤化学性质空间变异的分布。该研究在巴拉地区南部的 23 个村发展委员会(Village Development Committee,简称 VDC)进行,总面积为 12516 公顷。共采集了 109 个表层土壤样品(0-15cm 深度),用于分析 pH 值、有机质(organic matter,简称 OM)、氮(nitrogen,简称 N)、磷(以五氧化二磷 P2O5 表示)、钾(potassium,简称 K)、锌(zinc,简称 Zn)和硼(boron,简称 B)状况。描述性统计显示,大多数测量的土壤化学变量(pH 值和 P2O5 除外)呈偏态且非正态分布,随后进行了对数转换。在 ArcGIS 中使用了一种地统计学工具克里金(kriging)来对这些变量的实测值进行插值,并根据每种土壤化学特性开发了多个数字地图图层。地统计学插值确定了 pH 值、OM、N、P2O5 的中等空间变异性,K2O、Zn 和 B 的弱空间变异性,这取决于肥料的使用、施肥方法和耕作方式,以及每个变量的固有特性。指数(pH 值、OM、N 和 Zn)、球状(K2O 和 B)和高斯(P2O5)模型被拟合到土壤变量的半变异函数上。这些地图使农民能够评估现有的农场土壤,从而使他们能够做出更轻松、更高效的管理决策,并保持生产力的可持续性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc40/6203375/c7e9e607af95/pone.0206350.g001.jpg

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