Effects of land use/cover change on propagation dynamics from meteorological to soil moisture drought considering nonstationarity
Precipitation deficit will directly affect soil water, and soil water deficit will directly influence crop growth and exert a definite influence on the hydrological cycle. At present, drought propagation is based mainly on the hypothesis of serial stationarity to analyze the propagation from meteoro...
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Elsevier
2025-05-01
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| Series: | Agricultural Water Management |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0378377425001660 |
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| author | Meng Dai Ping Feng Jianzhu Li Xiaogang Shi Hanye Wang |
| author_facet | Meng Dai Ping Feng Jianzhu Li Xiaogang Shi Hanye Wang |
| author_sort | Meng Dai |
| collection | DOAJ |
| description | Precipitation deficit will directly affect soil water, and soil water deficit will directly influence crop growth and exert a definite influence on the hydrological cycle. At present, drought propagation is based mainly on the hypothesis of serial stationarity to analyze the propagation from meteorological drought (MD) to soil moisture drought (SMD), but with global climate change, the hypothesis of stationarity has been overturned. Research on drought propagation under nonstationarity is lacking. To this end, it is exceedingly meaningful to explore the propagation from MD to SMD under nonstationary conditions. Taking three regions of Luanhe River Basin (LRB) as the subject of study, the generalized additive models for location, scale and shape (GAMLSS) model was utilized to construct a nonstationary drought index. The drought propagation time (PTm) and propagation threshold (PTr) were calculated via conditional probability, and the dynamic change in drought propagation was analyzed via a moving window. Finally, the optimal parameters of the model were established on the basis of land use data from 1980 via the soil and water assessment tool (SWAT) model, and the land use data from 2000 and 2018 were replaced to investigate the comprehensive effects of land use/cover change (LUCC) and climate on drought propagation. The findings indicated that (1) the precipitation and soil moisture series were nonstationary during the growing season from 1962 to 2018; (2) the shortest static PTm was observed for Chengde in spring and autumn and Hanjiaying in summer, and the drought propagation process in Hanjiaying was accelerating during the whole growing season; (3) under the two drought scenarios (moderate and severe), the largest static PTr of drought occurred in the spring of Sandaohezi and the summer and autumn of Hanjiaying, and the MD of Sandaohezi was more likely to trigger SMD in autumn; and (4) the LUCC had little influence on the drought PTm and PTr in the basin by changing the land use data of different periods (2000 and 2018) based on the SWAT model with fixed parameters. These findings have important implications for early warning of agricultural drought and water resource management in watersheds. |
| format | Article |
| id | doaj-art-149d95509c1d4bebad8ceb2d031e9027 |
| institution | OA Journals |
| issn | 1873-2283 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Agricultural Water Management |
| spelling | doaj-art-149d95509c1d4bebad8ceb2d031e90272025-08-20T02:13:07ZengElsevierAgricultural Water Management1873-22832025-05-0131210945210.1016/j.agwat.2025.109452Effects of land use/cover change on propagation dynamics from meteorological to soil moisture drought considering nonstationarityMeng Dai0Ping Feng1Jianzhu Li2Xiaogang Shi3Hanye Wang4State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin, China; School of Social & Environmental Sustainability, University of Glasgow, Dumfries, UKState Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin, ChinaState Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin, China; Correspondence to: State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin 300072, China.School of Social & Environmental Sustainability, University of Glasgow, Dumfries, UKYunnan institute of Water & Hydropower Engineering Investigation, design Co., Ltd, Kunming, ChinaPrecipitation deficit will directly affect soil water, and soil water deficit will directly influence crop growth and exert a definite influence on the hydrological cycle. At present, drought propagation is based mainly on the hypothesis of serial stationarity to analyze the propagation from meteorological drought (MD) to soil moisture drought (SMD), but with global climate change, the hypothesis of stationarity has been overturned. Research on drought propagation under nonstationarity is lacking. To this end, it is exceedingly meaningful to explore the propagation from MD to SMD under nonstationary conditions. Taking three regions of Luanhe River Basin (LRB) as the subject of study, the generalized additive models for location, scale and shape (GAMLSS) model was utilized to construct a nonstationary drought index. The drought propagation time (PTm) and propagation threshold (PTr) were calculated via conditional probability, and the dynamic change in drought propagation was analyzed via a moving window. Finally, the optimal parameters of the model were established on the basis of land use data from 1980 via the soil and water assessment tool (SWAT) model, and the land use data from 2000 and 2018 were replaced to investigate the comprehensive effects of land use/cover change (LUCC) and climate on drought propagation. The findings indicated that (1) the precipitation and soil moisture series were nonstationary during the growing season from 1962 to 2018; (2) the shortest static PTm was observed for Chengde in spring and autumn and Hanjiaying in summer, and the drought propagation process in Hanjiaying was accelerating during the whole growing season; (3) under the two drought scenarios (moderate and severe), the largest static PTr of drought occurred in the spring of Sandaohezi and the summer and autumn of Hanjiaying, and the MD of Sandaohezi was more likely to trigger SMD in autumn; and (4) the LUCC had little influence on the drought PTm and PTr in the basin by changing the land use data of different periods (2000 and 2018) based on the SWAT model with fixed parameters. These findings have important implications for early warning of agricultural drought and water resource management in watersheds.http://www.sciencedirect.com/science/article/pii/S0378377425001660NonstationarityConditional probabilitySWAT modelPropagation dynamicsSoil moisture droughtThe Luanhe River Basin |
| spellingShingle | Meng Dai Ping Feng Jianzhu Li Xiaogang Shi Hanye Wang Effects of land use/cover change on propagation dynamics from meteorological to soil moisture drought considering nonstationarity Agricultural Water Management Nonstationarity Conditional probability SWAT model Propagation dynamics Soil moisture drought The Luanhe River Basin |
| title | Effects of land use/cover change on propagation dynamics from meteorological to soil moisture drought considering nonstationarity |
| title_full | Effects of land use/cover change on propagation dynamics from meteorological to soil moisture drought considering nonstationarity |
| title_fullStr | Effects of land use/cover change on propagation dynamics from meteorological to soil moisture drought considering nonstationarity |
| title_full_unstemmed | Effects of land use/cover change on propagation dynamics from meteorological to soil moisture drought considering nonstationarity |
| title_short | Effects of land use/cover change on propagation dynamics from meteorological to soil moisture drought considering nonstationarity |
| title_sort | effects of land use cover change on propagation dynamics from meteorological to soil moisture drought considering nonstationarity |
| topic | Nonstationarity Conditional probability SWAT model Propagation dynamics Soil moisture drought The Luanhe River Basin |
| url | http://www.sciencedirect.com/science/article/pii/S0378377425001660 |
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