Characteristics of Agricultural Droughts and Spatial Stratified Heterogeneity and Dependence of Dominant Factors in Inner Mongolia Autonomous Region, China
Droughts have significantly damaged the environment of the Inner Mongolia Autonomous Region, China. In this study, the region was divided into two subregions. Soil moisture was used as the basic parameter to analyze the characteristics of agricultural droughts. Based on a geographical detector, the...
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MDPI AG
2021-09-01
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Online Access: | https://www.mdpi.com/2073-4433/12/10/1249 |
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author | Simin Yang Quan Quan Weijia Liang Tiejun Liu |
author_facet | Simin Yang Quan Quan Weijia Liang Tiejun Liu |
author_sort | Simin Yang |
collection | DOAJ |
description | Droughts have significantly damaged the environment of the Inner Mongolia Autonomous Region, China. In this study, the region was divided into two subregions. Soil moisture was used as the basic parameter to analyze the characteristics of agricultural droughts. Based on a geographical detector, the spatial stratified heterogeneity in different seasons was discussed. Moreover, the copula joint functions of characteristics and dominant factors of agricultural droughts were constructed. Based on the Soil Moisture Anomaly Percentage Index (SMAPI), the results demonstrate that the climate tendency rate of droughts in the summer and in spring in Subregion I shows an increasing trend, while it decreases in the autumn and winter. In Subregion II, the climate tendency rate of droughts in different seasons has no significant change. Through geographical detection, the single factor detection illustrates that temperature and Precipitation Conversion Efficiency (PCE) show the highest explanatory power in different subregions. The interactive detection also demonstrates the explanatory powers of the combination of the PCE and temperature, respectively. The t-copula function describes the correlation coefficients of the SMAPI with the PCE and temperature, with the optimal tail dependence. In short, agricultural droughts are most significantly affected by temperature and the PCE, and their balance has a significant impact on agricultural droughts. |
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issn | 2073-4433 |
language | English |
last_indexed | 2024-03-10T06:44:24Z |
publishDate | 2021-09-01 |
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spelling | doaj.art-7403a2b89d9e4a788c1838dbfd738bc72023-11-22T17:24:33ZengMDPI AGAtmosphere2073-44332021-09-011210124910.3390/atmos12101249Characteristics of Agricultural Droughts and Spatial Stratified Heterogeneity and Dependence of Dominant Factors in Inner Mongolia Autonomous Region, ChinaSimin Yang0Quan Quan1Weijia Liang2Tiejun Liu3State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, ChinaState Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, ChinaState Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, ChinaInstitute of Water Resources for Pastoral Area, Hohhot 010020, ChinaDroughts have significantly damaged the environment of the Inner Mongolia Autonomous Region, China. In this study, the region was divided into two subregions. Soil moisture was used as the basic parameter to analyze the characteristics of agricultural droughts. Based on a geographical detector, the spatial stratified heterogeneity in different seasons was discussed. Moreover, the copula joint functions of characteristics and dominant factors of agricultural droughts were constructed. Based on the Soil Moisture Anomaly Percentage Index (SMAPI), the results demonstrate that the climate tendency rate of droughts in the summer and in spring in Subregion I shows an increasing trend, while it decreases in the autumn and winter. In Subregion II, the climate tendency rate of droughts in different seasons has no significant change. Through geographical detection, the single factor detection illustrates that temperature and Precipitation Conversion Efficiency (PCE) show the highest explanatory power in different subregions. The interactive detection also demonstrates the explanatory powers of the combination of the PCE and temperature, respectively. The t-copula function describes the correlation coefficients of the SMAPI with the PCE and temperature, with the optimal tail dependence. In short, agricultural droughts are most significantly affected by temperature and the PCE, and their balance has a significant impact on agricultural droughts.https://www.mdpi.com/2073-4433/12/10/1249Inner Mongolia Autonomous Regionsoil moisture anomaly percentage indexgeographical detectorcopulaprecipitation conversion efficiency |
spellingShingle | Simin Yang Quan Quan Weijia Liang Tiejun Liu Characteristics of Agricultural Droughts and Spatial Stratified Heterogeneity and Dependence of Dominant Factors in Inner Mongolia Autonomous Region, China Atmosphere Inner Mongolia Autonomous Region soil moisture anomaly percentage index geographical detector copula precipitation conversion efficiency |
title | Characteristics of Agricultural Droughts and Spatial Stratified Heterogeneity and Dependence of Dominant Factors in Inner Mongolia Autonomous Region, China |
title_full | Characteristics of Agricultural Droughts and Spatial Stratified Heterogeneity and Dependence of Dominant Factors in Inner Mongolia Autonomous Region, China |
title_fullStr | Characteristics of Agricultural Droughts and Spatial Stratified Heterogeneity and Dependence of Dominant Factors in Inner Mongolia Autonomous Region, China |
title_full_unstemmed | Characteristics of Agricultural Droughts and Spatial Stratified Heterogeneity and Dependence of Dominant Factors in Inner Mongolia Autonomous Region, China |
title_short | Characteristics of Agricultural Droughts and Spatial Stratified Heterogeneity and Dependence of Dominant Factors in Inner Mongolia Autonomous Region, China |
title_sort | characteristics of agricultural droughts and spatial stratified heterogeneity and dependence of dominant factors in inner mongolia autonomous region china |
topic | Inner Mongolia Autonomous Region soil moisture anomaly percentage index geographical detector copula precipitation conversion efficiency |
url | https://www.mdpi.com/2073-4433/12/10/1249 |
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