Arid
DOI10.1016/j.jhydrol.2018.07.038
Spatial predictions of the permanent wilting point in arid and semi-arid regions of Northeast China
Jin, Xinxin1,2; Wang, Shuai1,2; Yu, Na1,2; Zou, Hongtao1,2; An, Jing1,2; Zhang, Yuling1,2; Wang, Jingkuan1,2; Zhang, Yulong1,2
通讯作者Yu, Na
来源期刊JOURNAL OF HYDROLOGY
ISSN0022-1694
EISSN1879-2707
出版年2018
卷号564页码:367-375
英文摘要

The permanent wilting point (PWP) is the minimal point of soil moisture a plant requires not to wilt. If moisture decreases to this, or any lower point, a plant wilts, and can no longer recover its turgidity when placed in a saturated atmosphere for 12 h. The PWP is an essential physical property that has a powerful influence on other soil properties and is important for agricultural production, including irrigation water use efficiency and crop yield. However, there are few published datasets on the PWP of cultivated land in the arid and semi-arid regions of Northeast China. Direct measurements of PWP are time-consuming and expensive; therefore, the aim of this study was to evaluate how environmental variables could be used in spatial predictions of PWP in an arid and semi-arid region based on boosted regression tree (BRT) and multiple linear stepwise regression (MLSR) analyses. Seventy soil samples and nine covariates (including topography and vegetation variables) were collected and analyzed. Cross-validation procedure was used to evaluate model performance and uncertainty. Accuracy evaluation results showed that the BRT model had better predictive performance than the MLSR. PWP content decreased from the southwest to the northeast of the study area, and average values of both models were 26%. BRT and MLSR models should be compared and calibrated to obtain the best prediction effect of PWP spatial distribution in similar areas. Elevation, slope gradient, profile curvature, topographic wetness index, and landuse variables are the main environmental indicators that should be included when generating PWP maps of regions with a dry, continental climate. Such information could aid local land managers and government agencies with evaluating soil quality and water sequestration potential. In conclusion, this study could be used as a reference for predicting the hydrological parameters of the topsoil in other similar ecological environments.


英文关键词Digital soil mapping (DSM) Boosted regression tree (BRT) Multiple linear stepwise regression (MLSR)
类型Article
语种英语
国家Peoples R China
收录类别SCI-E
WOS记录号WOS:000445316200030
WOS关键词SOIL ORGANIC-CARBON ; AVAILABLE WATER CAPACITY ; PEDOTRANSFER FUNCTIONS ; INTEGRAL ENERGY ; LANDSCAPE RELATIONSHIPS ; REGRESSION TREES ; FIELD-CAPACITY ; RANDOM FOREST ; LAND-USE ; SPECTROSCOPY
WOS类目Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向Engineering ; Geology ; Water Resources
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/211079
作者单位1.Shenyang Agr Univ, Coll Land & Environm, Shenyang 110866, Liaoning, Peoples R China;
2.Shenyang Agr Univ, Key Lab Northeast Cultivated Land Conservat, Minist Agr Peoples Republ China, Shenyang 110866, Liaoning, Peoples R China
推荐引用方式
GB/T 7714
Jin, Xinxin,Wang, Shuai,Yu, Na,et al. Spatial predictions of the permanent wilting point in arid and semi-arid regions of Northeast China[J],2018,564:367-375.
APA Jin, Xinxin.,Wang, Shuai.,Yu, Na.,Zou, Hongtao.,An, Jing.,...&Zhang, Yulong.(2018).Spatial predictions of the permanent wilting point in arid and semi-arid regions of Northeast China.JOURNAL OF HYDROLOGY,564,367-375.
MLA Jin, Xinxin,et al."Spatial predictions of the permanent wilting point in arid and semi-arid regions of Northeast China".JOURNAL OF HYDROLOGY 564(2018):367-375.
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