Saturated Hydraulic Conductivity of US Soils Grouped According to Textural Class and Bulk Density

Pedotransfer函数 壤土 导水率 土壤水分 堆积密度 土壤科学 土壤质地 环境科学 数据库 数学 计算机科学
作者
Yakov Pachepsky,Yongeun Park
出处
期刊:Soil Science Society of America Journal [Wiley]
卷期号:79 (4): 1094-1100 被引量:70
标识
DOI:10.2136/sssaj2015.02.0067
摘要

The importance of saturated hydraulic conductivity (Ksat) as a soil hydraulic property led to the development of multiple pedotransfer functions for estimating it. One approach to estimating Ksat uses textural classes rather than specific textural fraction contents as a pedotransfer input. The objective of this work was to develop and evaluate a grouping-based pedotransfer procedure to estimate Ksat for sample sizes used in laboratory measurements. A search of publications and reports resulted in the collection of 1245 data sets with coupled data on Ksat, USDA textural class, and bulk density in the United States into a database called USKSAT. A separate database was assembled for the state of Florida that included 24,566 data sets. Data in each textural class were split into high and low bulk density groups using the splitting algorithm that created the most homogeneous groups. Sample diameters and lengths were <10 cm. Peaks of the semi-partial R2 were well defined for loamy soils. The threshold bulk density separating high and low bulk density groups is 1.24 g cm−3 for clay soils, about 1.33 g cm−3 for loamy soils, and about 1.65 g cm−3 for sandy soils. The high bulk density groups included a much broader range of Ksat values than the low bulk density groups for clays and loams but not sandy soils. Inspection of superimposed dependencies of Ksat on bulk density in the USKSAT database and in the Florida database showed their similarity. When geometric means were used as estimates of Ksat within groups, the accuracy was not high and yet was comparable with estimates obtained from far more detailed soil information using sophisticated machine learning methods. Estimating Ksat from textural class and bulk density may have the advantage of utility in data-poor environments and large-scale projects.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
李双艳完成签到,获得积分10
刚刚
英姑应助科研混子采纳,获得10
刚刚
li完成签到,获得积分10
1秒前
Hungrylunch应助woshiwuziq采纳,获得20
2秒前
合适苗条发布了新的文献求助10
2秒前
安静听白发布了新的文献求助10
2秒前
krystal发布了新的文献求助10
2秒前
3秒前
15122303完成签到,获得积分10
3秒前
lht完成签到 ,获得积分10
4秒前
传奇3应助纯真电源采纳,获得10
4秒前
环走鱼尾纹完成签到 ,获得积分10
4秒前
xiuxiu_27发布了新的文献求助10
5秒前
222完成签到,获得积分10
5秒前
zyz1132完成签到,获得积分10
5秒前
何处芳歇完成签到,获得积分10
6秒前
6秒前
LXYang完成签到,获得积分10
6秒前
6秒前
LL完成签到,获得积分10
6秒前
7秒前
7秒前
十月发布了新的文献求助20
8秒前
8秒前
针地很不戳完成签到,获得积分10
8秒前
9秒前
奋斗金连完成签到,获得积分10
9秒前
科研菜鸟完成签到,获得积分10
9秒前
圈圈发布了新的文献求助10
10秒前
zhanglh完成签到 ,获得积分10
10秒前
10秒前
Liu完成签到,获得积分10
10秒前
啊大大哇完成签到,获得积分10
10秒前
一平驳回了HEIKU应助
11秒前
11秒前
草莓奶昔完成签到 ,获得积分10
11秒前
cyx发布了新的文献求助10
11秒前
12秒前
littleJ完成签到,获得积分10
12秒前
Yolo发布了新的文献求助10
12秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527469
求助须知:如何正确求助?哪些是违规求助? 3107497
关于积分的说明 9285892
捐赠科研通 2805298
什么是DOI,文献DOI怎么找? 1539865
邀请新用户注册赠送积分活动 716714
科研通“疑难数据库(出版商)”最低求助积分说明 709678