1.河海大学水文水资源学院,水灾害防御全国重点实验室,南京 210098
2.河海大学地理与遥感学院,南京 211000
3.中国地质大学(北京)水资源与环境学院,北京 100083
4.黑龙江省水利水电勘测设计研究院,哈尔滨 150080
李雨轩(2002—),女,硕士研究生,主要从事农业干旱研究。E-mail:lyx_8649@163.com
吕海深(1968—),男,博士,教授,主要从事洪水、干旱过程模拟及预报研究。E-mail:lvhaishen@hhu.edu.cn
收稿:2026-01-28,
修回:2026-03-25,
录用:2026-03-31,
网络首发:2026-08-24,
纸质出版:2026-10-28
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李雨轩,吕海深,朱永华,等.土壤干旱指数不确定性及适用性分析[J].水土保持学报,2026,40(5):324-334.
Li Yuxuan, Lü Haishen, Zhu Yonghua, et al. Uncertainty and applicability analysis of soil drought indices[J].Journal of Soil and Water Conservation,2026,40(5):324-334.
李雨轩,吕海深,朱永华,等.土壤干旱指数不确定性及适用性分析[J].水土保持学报,2026,40(5):324-334. DOI: 10.13870/j.cnki.stbcxb.2026.05.014. CSTR: 32310.14.stbcxb.2026.05.014.
Li Yuxuan, Lü Haishen, Zhu Yonghua, et al. Uncertainty and applicability analysis of soil drought indices[J].Journal of Soil and Water Conservation,2026,40(5):324-334. DOI: 10.13870/j.cnki.stbcxb.2026.05.014. CSTR: 32310.14.stbcxb.2026.05.014.
目的
2
以黑龙江省为研究区域,分析多种土壤干旱指数在不同时间尺度和土壤层次条件下刻画干旱特征的差异及不确定性,为农业干旱监测中土壤干旱指数的选取与应用提供参考。
方法
2
基于ERA5-Land再分析数据,构建周、月时间尺度及浅层(0—28 cm)、中层(28—100 cm)土壤层的标准化土壤水分指数(SSMI)、土壤水分亏缺指数(SMDI)、土壤水分百分位数(SMP)及干旱严重程度指数(DSI),采用Mann-Kendall趋势检验、相关性分析和游程理论等方法对指数进行对比分析。
结果
2
1)SMDI的年变化幅度最大(约-0.025/a),DSI最小(约0.001/a)。春季指数间差异最明显,SMDI对局部轻微干旱缓解敏感,DSI识别的春季显著干旱加剧区域面积为其他指数的1.5~2.0倍。2)干旱识别一致性最高的指数组合为SSMI-SMP(0.883~1.000)与SSMI-DSI(0.879~1.000),且随干旱强度增强各指数识别结果趋于一致。3)不同土壤层条件下,各干旱指数差异较为稳定;周尺度下DSI的干旱频率为其他指数的1.1~1.8倍;月尺度下SMDI干旱频率为其他指数的1.2~1.6倍,且在不同尺度和土壤层条件下SMDI平均干旱持续时间最长。4)各指数在敏感性与稳定性上各具优势,DSI综合性能较优,在类似气候与土壤条件下可作为主要识别指标;SSMI稳健,虚警率最低;SMDI敏感性最高,适用于早期预警;SMP敏感性相对较低。
结论
2
土壤干旱指数在农业干旱监测中的适用性受指数构建方法、时间尺度和土壤层次差异的共同影响,单一指数难以兼顾稳定性与敏感性,多指数联合应用有助于降低干旱识别的不确定性。
Objective
2
Taking Heilongjiang Province as the study area, this study analyzes the differences and uncertainties among various soil drought indices in characterizing drought features under different temporal scales and soil layer conditions, aiming to provide a basis for the selection and application of soil drought indices in agricultural drought monitoring.
Methods
2
Based on ERA5-Land reanalysis data, the Standardized Soil Moisture Index (SSMI), Soil Moisture Deficit Index (SMDI), Soil Moisture Percentile (SMP), and Drought Severity Index (DSI) were constructed at weekly and monthly temporal scales for shallow (0-28 cm) and middle (28-100 cm) soil layers. The indices were comparatively analyzed using the Mann-Kendall trend test, correlation analysis, and run theory.
Results
2
1) SMDI exhibited the largest annual change rate (approximately -0.025/a), while DSI showed the smallest (approximately 0.001/a). Seasonal differences among indices were most pronounced in spring: SMDI was sensitive to local mild drought alleviation, whereas the area identified as significantly intensifying drought by DSI was 1.5-2.0 times that of other indices. 2) The highest consistency in drought identification was observed for the SSMI-SMP (0.883-1.000) and SSMI-DSI (0.879-1.000) index combinations, and consistency increased with drought intensity. 3) Across soil layers, differences among indices remained relatively stable; at the weekly scale, the drought frequency identified by DSI was 1.1-1.8 times that of other indices, while at the monthly scale, that identified by SMDI was 1.2-1.6 times that of other indices. Moreover, SMDI exhibited the longest mean drought duration across different time scales and soil layers. 4) Each index demonstrated distinct advantages in sensitivity and stability: DSI showed relatively better overall performance and can be recommended as a primary indicator under similar climatic and soil conditions; SSMI was the most robust with the lowest false alarm rate; SMDI exhibited the highest sensitivity and is suitable for early warning; SMP showed relatively lower sensitivity.
Conclusion
2
The applicability of soil drought indices in agricultural drought monitoring is influenced by index formulation, temporal scale, and soil layer differences. A single index cannot simultaneously achieve high stability and sensitivity, whereas the combined use of multiple indices can reduce uncertainty in drought identification.
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