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Article(id=1312009532151267725, tenantId=1146029695717560320, journalId=1311385839672066169, issueId=1312009474789958403, articleNumber=null, orderNo=null, doi=10.13870/j.cnki.stbcxb.2026.04.033, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1766764800000, receivedDateStr=2025-12-27, revisedDate=1771776000000, revisedDateStr=2026-02-23, acceptedDate=1774972800000, acceptedDateStr=2026-04-01, onlineDate=1790737048423, onlineDateStr=2026-09-30, pubDate=1787846400000, pubDateStr=2026-08-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790737048423, onlineIssueDateStr=2026-09-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790737048423, creator=13701087609, updateTime=1790737048423, updator=13701087609, issue=Issue{id=1312009474789958403, tenantId=1146029695717560320, journalId=1311385839672066169, year='2026', volume='40', issue='4', pageStart='1', pageEnd='488', issueExtLink='null', onlineDate='null', pubDate='1787846400000', pubDateStr='2026-08-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1790737034746, creator='13701087609', updateTime=1790739471092, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1312019693662204413, tenantId=1146029695717560320, journalId=1311385839672066169, issueId=1312009474789958403, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1312019693662204414, tenantId=1146029695717560320, journalId=1311385839672066169, issueId=1312009474789958403, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=152, endPage=162, ext={EN=ArticleExt(id=1312009532319039886, articleId=1312009532151267725, tenantId=1146029695717560320, journalId=1311385839672066169, language=EN, title=Responses of Water Storage of Gully Heads to Rainfall in Black Soil Region of Northeast China, columnId=1312009477243626245, journalTitle=Journal of Soil and Water Conservation, columnName=Basic Research, runingTitle=null, highlight=null, articleAbstract=

Objective This study investigates the response characteristics of water storage at gully heads to rainfall in the black soil region of Northeast China， reveals the variation patterns of water storage at gully heads before and after rainfall， and establishes a quantitative prediction method for its changes before and after rainfall. Methods Four gully heads with similar developmental stages and scales in three study areas （Jiusan， Binxian and Jiutai） were selected as research objects. Differences in soil hydraulic parameters， decay coefficients of water storage， and variation patterns of water storage before and after rainfall were investigated through transient water release and imbibition method （TRIM）， numerical fitting， and prediction model construction. Results Obvious hysteresis effects were observed in soil-water characteristic curves （SWCC） of soils at gully heads， with the intensity ranking as gully 1 ≈ gully 2 < gully 3 < gully 4. After rainfall， water storage decayed exponentially over time， showing rapid decline in the initial stage and slower decline in the later stage. The decay coefficient （Kd） of water storage decreased progressively with increasing soil depth. Model simulations showed that water storage changes at 85.7 % of the monitoring sites were best predicted using 1 h maximum rainfall intensity （I1 h） as the rainfall input parameter， whereas 14.3 % of the sites were better simulated using 2 h average maximum continuous rainfall intensity （I2 h） as input. Therefore， in predicting soil water storage changes， I1 h could be selected as the rainfall input parameter for sites with good infiltration performance， such as gully heads or severely eroded sites. However， I2 h should be selected as the rainfall input parameter for sites with poor infiltration performance or strong water redistribution. Conclusion The evolution of water storage at gully heads after rainfall in the black soil region of Northeast China can be effectively characterized using exponential decay patterns and short-duration rainfall indices. The constructed model can accurately and quantitatively predict short-duration water storage changes at gully heads at the event scale， which provides methodological support for prediction and early warning of gully erosion processes.

, authors=Wenqi Wang, Chao Ma, authorsList=Wenqi Wang, Chao Ma, authorCompany=null, correspAuthors=Chao Ma, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1312009535489933725, articleId=1312009532151267725, tenantId=1146029695717560320, journalId=1311385839672066169, language=CN, title=东北黑土区切沟沟头储水量对降雨的响应, columnId=1312009477407204103, journalTitle=水土保持学报, columnName=基础研究, runingTitle=null, highlight=null, articleAbstract=

目的 为探究东北黑土区切沟沟头储水量对降雨的响应特征，揭示降雨前后沟头储水量的变化规律，建立降雨前后储水量变化的定量预测方法。 方法 以九三、宾县和九台3个研究区发育阶段及规模相近的4个切沟沟头为研究对象，通过瞬态脱湿-吸湿试验、数值拟合和储水量预测模型构建，深入探究不同切沟土壤水力学参数差异、储水量衰减系数差异和储水量在降雨前后的变化规律。 结果 沟头土壤土水特征曲线存在明显滞后效应，滞后效应强弱排序为沟1≈沟2<沟3<沟4。降雨后储水量随时间呈指数衰减，初期消退快、后期变缓。储水量衰减系数（Kd）随土层深度依次减小。模型模拟表明，85.7%的点位储水量变化与以最大1 h雨强为降雨输入参数的预测结果最吻合，14.3%的点位以最大连续2 h平均雨强输入更优。因此，在开展土壤储水量预测时，入渗性能好的点位可选取I1 h为降雨输入参数，如沟头或受侵蚀严重的点位；而入渗性能差或有强烈水分再分配点位应选取I2 h为降雨输入参数。 结论 东北黑土区切沟沟头降雨后储水量演化可通过指数衰减规律及短历时降雨指标加以有效表征，所构建模型可较准确地实现事件尺度下沟头短期储水量变化的定量预测，为沟蚀过程预测预警提供方法支撑。

, authors=王文起, 马超, authorsList=王文起, 马超, authorCompany=null, correspAuthors=马超, authorNote=

王文起（2000—），男，硕士研究生，主要从事土壤侵蚀与水土保持研究。E-mail：

, correspAuthorsNote=
马超（1986—），男，博士，教授，主要从事山地灾害成灾动力研究。E-mail：
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王文起（2000—），男，硕士研究生，主要从事土壤侵蚀与水土保持研究。E-mail：

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Soil physicochemical properties and roots promoted preferential flow development after vegetation restoration［J］.Journal of Hydrology，2025，659：e133349., articleTitle=Soil physicochemical properties and roots promoted preferential flow development after vegetation restoration, refAbstract=null), Reference(id=1312009549440188919, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, doi=null, pmid=null, pmcid=null, year=2025, volume=17, issue=8, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[29], rfOrder=43, authorNames=Ji Chenlin, Wang Tianyi, Bao Han, journalName=Water, refType=null, unstructuredReference=Ji Chenlin， Wang Tianyi， Bao Han， et al. 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Soil infiltration characteristics and simulation of different eroded degrees in the black soil region of Northeast China［J］.Science of Soil and Water Conservation，2024，22（2）：17-24., articleTitle=null, refAbstract=null)], funds=[Fund(id=1312009540929946059, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, awardId=2024YFD1501201-3, language=CN, fundingSource=国家重点研发计划项目(2024YFD1501201-3), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1312009535691260318, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, xref=null, ext=[AuthorCompanyExt(id=1312009535699648927, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, companyId=1312009535691260318, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Soil and Water Conservation，Beijing Forestry University，Beijing 100083，China), 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articleId=1312009532151267725, language=EN, label=Fig.7, caption=1∶1 validation, figureFileSmall=2zWExDwGTmmgSvUGEJVdeQ==, figureFileBig=K0QEjlqIGj90+gdAFVGPCg==, tableContent=null), ArticleFig(id=1312009540032364992, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, language=CN, label=图7, caption=1∶1检验, figureFileSmall=2zWExDwGTmmgSvUGEJVdeQ==, figureFileBig=K0QEjlqIGj90+gdAFVGPCg==, tableContent=null), ArticleFig(id=1312009540099473857, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, language=EN, label=Table 1, caption=

Data types and collection times of monitored gullies

, figureFileSmall=null, figureFileBig=null, tableContent=

数据

类型

具体

指标

监测

切沟

年份数据采集时间（月-日）

观测

数据

含水率

及雨量

沟1202207-14—09-30
沟3202507-29—09-30
沟4202507-15—09-30

实测

数据

（验证）

含水率沟2202407-29、08-03、08-06、08-11、08-18
沟3202507-16、07-27、07-30、08-03
沟4202507-08、07-11、07-21、07-28
), ArticleFig(id=1312009540166582722, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, language=CN, label=表1, caption=

监测切沟数据类型及采集时间

, figureFileSmall=null, figureFileBig=null, tableContent=

数据

类型

具体

指标

监测

切沟

年份数据采集时间（月-日）

观测

数据

含水率

及雨量

沟1202207-14—09-30
沟3202507-29—09-30
沟4202507-15—09-30

实测

数据

（验证）

含水率沟2202407-29、08-03、08-06、08-11、08-18
沟3202507-16、07-27、07-30、08-03
沟4202507-08、07-11、07-21、07-28
), ArticleFig(id=1312009540229497283, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, language=EN, label=Table 2, caption=

Comparison of basic physical properties of soils

, figureFileSmall=null, figureFileBig=null, tableContent=

监测

切沟

土壤体积质量/

（g·cm-3）

孔隙度/%级配
黏粒/%粉粒/%砂粒/%
沟11.6230.8265.9512.7421.31
沟21.5544.1470.525.8023.68
), ArticleFig(id=1312009540321771972, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, language=CN, label=表2, caption=

土壤基础物理性质对比

, figureFileSmall=null, figureFileBig=null, tableContent=

监测

切沟

土壤体积质量/

（g·cm-3）

孔隙度/%级配
黏粒/%粉粒/%砂粒/%
沟11.6230.8265.9512.7421.31
沟21.5544.1470.525.8023.68
), ArticleFig(id=1312009540397269445, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, language=EN, label=Table 3, caption=

Soil hydraulic parameters inverted by Hydrus-1D

, figureFileSmall=null, figureFileBig=null, tableContent=

监测

切沟

残余含水率饱和含水率进气值的倒数孔径分布参数饱和渗透性系数
（θr）/%θsd/%θsw/%αd/kPa-1αw/kPa-1ndnwKsd/（cm·s-1）Ksw/（cm·s-1）
沟1［22］2.6257.0053.004.20×10-30.021.691.954.73×10-62.64×10-5
沟2［22］2.7957.0053.004.00×10-30.021.741.985.64×10-62.75×10-5
沟31.3251.8832.292.35×10-30.131.941.917.22×10-61.68×10-6
沟44.0159.3851.532.97×10-30.381.972.101.47×10-51.89×10-5
), ArticleFig(id=1312009540481155526, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, language=CN, label=表3, caption=

Hydrus-1D反演出的土壤水力学参数

, figureFileSmall=null, figureFileBig=null, tableContent=

监测

切沟

残余含水率饱和含水率进气值的倒数孔径分布参数饱和渗透性系数
（θr）/%θsd/%θsw/%αd/kPa-1αw/kPa-1ndnwKsd/（cm·s-1）Ksw/（cm·s-1）
沟1［22］2.6257.0053.004.20×10-30.021.691.954.73×10-62.64×10-5
沟2［22］2.7957.0053.004.00×10-30.021.741.985.64×10-62.75×10-5
沟31.3251.8832.292.35×10-30.131.941.917.22×10-61.68×10-6
沟44.0159.3851.532.97×10-30.381.972.101.47×10-51.89×10-5
), ArticleFig(id=1312009540560847303, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, language=EN, label=Table 4, caption=

Fitting values of water storage decay coefficient （Kd）

, figureFileSmall=null, figureFileBig=null, tableContent=
土层深度/cm沟1沟3沟4
KdR2KdR2KdR2
0~200.0540.950.0820.760.0360.98
20~400.0230.880.0100.940.0100.94
40~600.0170.860.0070.960.0100.96
60~800.0100.930.0060.910.0060.97
0~40 （验证）0.0350.920.0280.840.0190.97
), ArticleFig(id=1312009540653121992, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, language=CN, label=表4, caption=

储水量衰减系数（Kd）拟合值

, figureFileSmall=null, figureFileBig=null, tableContent=
土层深度/cm沟1沟3沟4
KdR2KdR2KdR2
0~200.0540.950.0820.760.0360.98
20~400.0230.880.0100.940.0100.94
40~600.0170.860.0070.960.0100.96
60~800.0100.930.0060.910.0060.97
0~40 （验证）0.0350.920.0280.840.0190.97
), ArticleFig(id=1312009540732813769, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, language=EN, label=Table 5, caption=

Mean absolute error （MAE） at monitoring sites

, figureFileSmall=null, figureFileBig=null, tableContent=
MAE/ mm沟2沟3沟4
点1点2点3点4点5点6点1点2点3点4点1点2点3点4
I1 h6.54.08.34.64.46.27.17.710.46.015.54.05.42.9
I2 h12.98.614.49.25.34.429.426.826.025.06.821.222.615.2
I3 h15.611.417.312.18.15.640.237.636.835.813.628.029.422.0
I4 h17.313.219.113.89.97.145.843.242.441.518.132.533.926.4
), ArticleFig(id=1312009540812505546, tenantId=1146029695717560320, journalId=1311385839672066169, articleId=1312009532151267725, language=CN, label=表5, caption=

实测点平均绝对误差

, figureFileSmall=null, figureFileBig=null, tableContent=
MAE/ mm沟2沟3沟4
点1点2点3点4点5点6点1点2点3点4点1点2点3点4
I1 h6.54.08.34.64.46.27.17.710.46.015.54.05.42.9
I2 h12.98.614.49.25.34.429.426.826.025.06.821.222.615.2
I3 h15.611.417.312.18.15.640.237.636.835.813.628.029.422.0
I4 h17.313.219.113.89.97.145.843.242.441.518.132.533.926.4
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东北黑土区切沟沟头储水量对降雨的响应
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王文起 , 马超
水土保持学报 | 基础研究 2026,40(4): 152-162
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水土保持学报 |基础研究 2026 , 40 (4) : 152 -162
东北黑土区切沟沟头储水量对降雨的响应
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王文起（2000—），男，硕士研究生，主要从事土壤侵蚀与水土保持研究。E-mail：

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王文起 , 马超
作者信息
  • 北京林业大学水土保持学院，北京 100083
通讯作者:
马超（1986—），男，博士，教授，主要从事山地灾害成灾动力研究。E-mail：
作者简介:

王文起（2000—），男，硕士研究生，主要从事土壤侵蚀与水土保持研究。E-mail：

Responses of Water Storage of Gully Heads to Rainfall in Black Soil Region of Northeast China
Wenqi Wang , Chao Ma
Affiliations
  • School of Soil and Water Conservation，Beijing Forestry University，Beijing 100083，China
出版时间: 2026-08-28 doi: 10.13870/j.cnki.stbcxb.2026.04.033
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目的 为探究东北黑土区切沟沟头储水量对降雨的响应特征，揭示降雨前后沟头储水量的变化规律，建立降雨前后储水量变化的定量预测方法。 方法 以九三、宾县和九台3个研究区发育阶段及规模相近的4个切沟沟头为研究对象，通过瞬态脱湿-吸湿试验、数值拟合和储水量预测模型构建，深入探究不同切沟土壤水力学参数差异、储水量衰减系数差异和储水量在降雨前后的变化规律。 结果 沟头土壤土水特征曲线存在明显滞后效应，滞后效应强弱排序为沟1≈沟2<沟3<沟4。降雨后储水量随时间呈指数衰减，初期消退快、后期变缓。储水量衰减系数（Kd）随土层深度依次减小。模型模拟表明，85.7%的点位储水量变化与以最大1 h雨强为降雨输入参数的预测结果最吻合，14.3%的点位以最大连续2 h平均雨强输入更优。因此，在开展土壤储水量预测时，入渗性能好的点位可选取I1 h为降雨输入参数，如沟头或受侵蚀严重的点位；而入渗性能差或有强烈水分再分配点位应选取I2 h为降雨输入参数。 结论 东北黑土区切沟沟头降雨后储水量演化可通过指数衰减规律及短历时降雨指标加以有效表征，所构建模型可较准确地实现事件尺度下沟头短期储水量变化的定量预测，为沟蚀过程预测预警提供方法支撑。

东北黑土  /  切沟  /  储水量  /  衰减系数

Objective This study investigates the response characteristics of water storage at gully heads to rainfall in the black soil region of Northeast China， reveals the variation patterns of water storage at gully heads before and after rainfall， and establishes a quantitative prediction method for its changes before and after rainfall. Methods Four gully heads with similar developmental stages and scales in three study areas （Jiusan， Binxian and Jiutai） were selected as research objects. Differences in soil hydraulic parameters， decay coefficients of water storage， and variation patterns of water storage before and after rainfall were investigated through transient water release and imbibition method （TRIM）， numerical fitting， and prediction model construction. Results Obvious hysteresis effects were observed in soil-water characteristic curves （SWCC） of soils at gully heads， with the intensity ranking as gully 1 ≈ gully 2 < gully 3 < gully 4. After rainfall， water storage decayed exponentially over time， showing rapid decline in the initial stage and slower decline in the later stage. The decay coefficient （Kd） of water storage decreased progressively with increasing soil depth. Model simulations showed that water storage changes at 85.7 % of the monitoring sites were best predicted using 1 h maximum rainfall intensity （I1 h） as the rainfall input parameter， whereas 14.3 % of the sites were better simulated using 2 h average maximum continuous rainfall intensity （I2 h） as input. Therefore， in predicting soil water storage changes， I1 h could be selected as the rainfall input parameter for sites with good infiltration performance， such as gully heads or severely eroded sites. However， I2 h should be selected as the rainfall input parameter for sites with poor infiltration performance or strong water redistribution. Conclusion The evolution of water storage at gully heads after rainfall in the black soil region of Northeast China can be effectively characterized using exponential decay patterns and short-duration rainfall indices. The constructed model can accurately and quantitatively predict short-duration water storage changes at gully heads at the event scale， which provides methodological support for prediction and early warning of gully erosion processes.

black soil region in Northeast China  /  gully  /  water storage  /  decay coefficient
王文起, 马超. 东北黑土区切沟沟头储水量对降雨的响应. 水土保持学报, 2026 , 40 (4) : 152 -162 . DOI: 10.13870/j.cnki.stbcxb.2026.04.033
Wenqi Wang, Chao Ma. Responses of Water Storage of Gully Heads to Rainfall in Black Soil Region of Northeast China[J]. Journal of Soil and Water Conservation, 2026 , 40 (4) : 152 -162 . DOI: 10.13870/j.cnki.stbcxb.2026.04.033
正文
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东北黑土区是我国最重要的商品粮生产基地，被誉为中国粮食的“压舱石”［1］。然而，近年来，东北黑土区的水土流失日益严重，水土流失面积占区域总面积的18.95%［2］。其中沟蚀的危害尤为突出，其危害性强、潜在威胁性大、治理紧迫性高的特征，严重威胁东北黑土区的粮食安全，阻碍现代农业的发展［3］。
沟蚀是东北黑土区农田土壤流失的主要形式之一，其发生和发展受降雨特征和土壤水分状况的共同制约［4-6］。沟蚀的形成通常需要达到一定的降雨阈值并具备汇流条件，即当降雨强度和历时超过土壤入渗能力时，汇集的地表径流便会冲刷出侵蚀沟［7］。在此过程中，前期土壤含水量与降雨入渗共同影响产流阈值与径流强度，进而使沟蚀降雨阈值随地形、土壤性质及土壤水分状况而变化［8］。沟头常出现在坡度较陡、汇水面积大的部位［9］，作为汇流集中与沟道演化的重要部分，其水分状态与稳定性直接影响沟道延伸与扩张。侵蚀沟形成后，沟头持续向上游侵蚀使沟长延伸，沟底下切加深、沟壁坍塌拓宽使沟道进一步扩大［10］。杨丽娟等［11］、黄萌等［12］研究表明，降雨条件对沟蚀影响极大。年降雨量偏高时沟蚀明显加剧，多雨年沟蚀体积增量可较常年高出数倍，极端湿润年的侵蚀量甚至占10 a总量的1/2以上［13］。强降雨事件可促使浅沟在雨季内快速发育，单次强降雨过程造成的土壤流失可占总侵蚀量的29%~45%［14］。不同降雨指标对不同部位沟蚀过程的影响有所差异：谷底沟的侵蚀与最大降雨量关系最为密切，而坡面沟侵蚀则与降雪量、产流降雨侵蚀力、最大降雨量的复合指标相关性更显著［15］。Ma等［16］研究表明，在沟底下切、沟壁拓宽的过程中，土体储水量是连接降雨入渗、产流与力学响应的关键控制量。储水量较低时，可削弱地表产流，但雨后高含水状态与孔隙水压力升高降低土体抗剪强度，易诱发沟壁坍塌从而促进沟道加宽；当储水量接近饱和时，超渗产流增强，沟底水力剪切力随之升高，从而加剧沟底冲刷下切及沟头溯源退缩。目前，针对东北黑土区切沟沟头关键侵蚀源区，沟头土体储水量对短历时降雨的动态响应及雨后衰减规律仍缺乏可参数化的系统认识，限制沟蚀过程的定量预测与预警。
为探究东北黑土区切沟沟头储水量对降雨的响应特征，揭示降雨前后沟头储水量的变化规律，本研究在3处典型黑土小流域内选取4个切沟沟头作为研究对象。布设仪器进行连续监测获取气象水文数据。开展瞬态脱湿-吸湿试验获取水力学参数，计算土壤储水量。使用指数衰减模型，拟合不同深度条件下储水量的衰减系数。最后，构建出基于短历时降雨指标的日尺度储水量预测模型，以期为切沟土壤侵蚀预测预报提供理论支撑。
1 材料与方法
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1.1 研究区概况
研究区位于黑龙江省嫩江市鹤山农场鹤北流域、黑龙江省哈尔滨市宾县郭万有屯小流域和吉林省长春市九台区梁家沟小流域（图1）。鹤北流域（48°59′34″~49°02′36″N，125°15′46″~125°20′47″E）地形为漫岗丘陵，坡度为1°~6°。属大陆性季风气候，多年平均降雨量为463 mm，多年平均气温为0 ℃。郭万有屯小流域（45°52′12″~45°58′10″N，127°33′30″~127°38′21″E）为漫岗丘陵地形，地势平缓，坡度为1°~7°。属寒温带大陆季风气候，年平均降雨量为550 mm，年平均气温为3.9 ℃。梁家沟小流域（44°17′31.35″~44°18′45″N，126°06′25″~126°06′30″E）地貌类型为丘陵，地形起伏明显。属中温带大陆季风气候，年平均降水量为580~600 mm，年平均气温为4.7~7.8 ℃。3个小流域土壤均以典型黑土为主，降雨集中在6~8月，占全年降雨的70%~90%。
图2为研究区内选取的典型黑土切沟示意图，4条切沟的发育阶段及规模相近。切沟（a）横穿林带，沟头侧壁土体成分较为一致，记为沟1；切沟（b）位于农田内部，土体成分均一且结构较为紧实，颜色呈黑褐色，记为沟2；切沟（c）位于农田内部，周围作物为玉米，切沟一侧靠近林带，颜色呈黑褐色，记为沟3；切沟（d）位于农田内部，周围作物为玉米，靠近主沟，颜色呈黄褐色，记为沟4。
1.2 研究方法
为阐明切沟沟头土壤对降雨过程的入渗蓄水响应，并建立日尺度的储水量预测模型。研究通过获取的数据进行参数拟合，根据所得参数构建模型，最后进行可靠性检验。具体步骤为：首先在3处典型黑土小流域选择发育阶段与规模相近的4个切沟沟头布设监测仪器，获取降雨与分层含水率连续序列；其次采集沟头土样开展瞬态脱湿-吸湿试验，并以VG-Mualem函数为基础借助Hydrus-1D反演水力学参数；随后计算储水量，通过指数模型反演储水量衰减系数Kd，在此基础上，基于漏桶模型构建日尺度储水量预测模型，其中降雨输入参数（Ii h）采用最大1 h雨强及最大连续2~4 h平均雨强以表征短历时降雨过程的峰值特征；最后，利用独立实测含水率数据对模型进行验证，通过统计学指标评价模型精度。
1.2.1 数据获取
所用数据分为观测数据和实测数据。从表1可以看出，观测数据包括土壤含水率及雨量数据。土壤含水率测定通过智能含水率传感器获取，传感器安装在切沟沟头1.5 m处，可测定0~20、20~40、40~60、60~80 cm土层体积含水率，数据采集时间间隔为2 h。雨量数据通过压电式雨量计获取，雨量计安装在沟域范围内居民家中，数据采集时间间隔为1 h。
实测数据分为实测土壤含水率数据及土壤样品。实测土壤含水率数据获取方式为雨后使用手持式土壤温度湿度检测仪在切沟沟头附近的沟壁处测量，测量深度为20 cm，平行采集3次取平均值作为该处实测值，其中沟2选定6个实测点，沟3和沟4均选定4个实测点，数据采集时间见表1。使用环刀采集土壤样品以测定土壤水力学参数。于沟头处距表层0~40 cm的沟壁位置，铲除外层扰动土，打入高（H）25.4 mm、直径（D）61.8 mm的环刀取样，平行采集3~4个样品为1组。
基于沟1、沟3、沟4的观测数据，首先通过瞬态脱湿-吸湿试验获取各沟头水力学参数，随后通过计算得到储水量序列，拟合得到储水量衰减系数（Kd）。为检验储水量预测模型的准确性，采用实测数据作为独立验证数据开展对比验证。由于沟1缺乏实测数据，本文选取实测数据完整的沟2作为对照验证点参与验证。基于表2的数据对比，沟1与沟2土壤体积质量分别为1.62/1.55 g/cm³，颗粒级配均以黏粒为主（65.95%、70.52%），砂粒含量接近（21.31%、23.68%），表明两沟土体组成相近。最终选取沟2、沟3、沟4的实测数据对模型预测的储水量进行精度评估，从而保证模型可靠性。
1.2.2 数据处理
土壤水力学参数测定：采用瞬态脱湿吸湿试验装置（transient water release and imbibition method，TRIM）对4条切沟的土壤样品进行测定以获取关键水力学参数；随后以Van Genuchten土水特征函数［17］与Mualem导水率函数［18］为理论基础，借助Hydrus-1D对脱湿与吸湿阶段观测数据开展反演分析，相关计算公式为：
θ-θrθs-θr=11+αhn1-1n
K=Ks1-αhn-11+αhn1n-11+αhn12-12n
式中：θ为实测含水率；θr为残余含水率；θs为饱和含水率；α为进气值的倒数，/kPa；h为基质吸力（或压力水头）；n为孔径分布相关的形状参数；K为非饱和渗透系数，cm/s；Ks 为饱和渗透系数，cm/s。
雨量数据处理：降雨强度是控制土壤水分入渗补给与产流过程的重要因子［19］。为在日尺度储水量预测中保留降雨过程的日内峰值信息，以当日08：00至次日08：00为当日降雨数据，在1次降雨过程中，把降雨量按连续i h为单位划分，计算每个i h内的平均雨强。其中最大数值为最大连续i h平均雨强。计算最大1 h雨强、最大连续2 h平均雨强、最大连续3 h平均雨强和最大连续4 h平均雨强，并记为I1 h、I2 h、I3 h和I4 h，作为降雨输入参数。
观测含水率数据处理：为将观测含水率转换为日尺度代表值，使其反映当日主导过程。当日有降雨时，土壤含水率受入渗补给影响呈上升趋势并在降雨后达到峰值，故取当日含水率最大值记为当日含水率数据，以表征降雨引起的最大增湿效应；当日无降雨时，土壤含水率受蒸散与重力排水控制呈衰减趋势，故取当日含水率最小值记为当日含水率数据，以表征当日衰减后的低值状态。
土壤储水量可通过土层深度及有效饱和度来评估，计算公式为：
S=θ-θrθsd-θr×h
式中：S为土壤储水量，mm；θ为实测体积含水率；θr为残余含水率；θsd为脱湿条件下的饱和含水率；h为土层深度，取200 mm。
1.2.3 参数拟合
为表征降雨后储水量的消退特征，本文采用指数衰减模型对0~20、20~40、40~60、60~80 cm土层的储水量衰减系数进行反演。计算公式为：
St=S0×e-Kdt
式中：S0为消退段起始时刻的储水量，mm；Kd为储水量衰减系数，/d；t为相对天数。
基于沟1、沟3和沟4的观测含水率数据，计算不同深度储水量。以0~20 cm作为参考层，识别降雨后储水量连续下降的时段作为消退段。为确保不同层位的参数具有可比性，各层位均在相同的消退时段内估计Kd。参数估计采用遍历搜索方式在预设范围Kd∈［0.001，0.999］内寻找使总体拟合偏差最小的Kd，从而获得该层位在多个消退过程下的统一衰减特征。拟合优度以决定系数R2进行评价，用于衡量指数消退模型对观测消退过程的解释能力。最终得到沟1、沟3和沟4在0~20、20~40、40~60、60~80 cm深度的储水量衰减系数。
1.2.4 模型构建
为描述储水量在给定时段内的变化规律，基于漏桶模型［20-21］，构建日尺度的储水量预测模型：
St=S0×e-Kdt+Ii·hKd1-e-Kdt
式中：St 为t时刻的储水量，mm；S0为起始时刻的储水量，mm；Kd为储水量衰减系数，用于表征储水量衰减的快慢，Kd越大，储水量消退越快，/d；Ii h为该时段内的降雨输入参数，用于表征降雨引起的水分补给，mm/d。
从结构上看，该模型可分解为消退项和输入项2部分，前者随时间按指数规律衰减，后者因降雨输入而累积。
1.2.5 模型检验
用距离表层20 cm处采集到的实测含水率数据进行模型精度检验。首先，将实测含水率数据代入公式（3）得到起始时刻储水量S0，其次将S0、0~40 cm的储水量衰减系数Kd及不同降雨输入参数Ii h同时代入公式（5），然后用平均绝对误差判断最优的水分补给强度参数。最后用最优水分补给强度得出储水量预测值与实测值进行1∶1检验，并用统计指标来判断模型可靠性。
均方根误差（root mean square error，RMSE）：
RMSE=1n∑i=1ny^i-yi2
平均绝对误差（mean absolute error，MAE）：
MAE=1n∑i=1ny^i-yi
平均绝对百分比误差（mean absolute percentage error，MAPE）：
MAPE=100%n∑i=1ny^i-yiyi
式中：yi 为第i个样本的实测值；ŷi 为其对应的预测值；n为样本数量。
2 结果与分析
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2.1 土水特征曲线
表3为基于Hydrus-1D反演得到的土壤水力学参数。利用参数绘制观测含水量范围内的整个土体的土水特征曲线（soil-water characteristic curve，SWCC）及水力传导函数曲线（hydraulic conductivity function，HCF）（图3），从而表达土体在变饱和条件下的储水-排水过程及导水能力在不同含水率状态下的变化特征。图3a~图3d分别为沟1、沟2、沟3、沟4的SWCC及HCF。在VG-Mualem模型中，饱和含水率（θs）与残余含水率（θr）分别是含水率的上下边界。θs表征土体接近饱和时的储水上限。当其他参数相近时，θs越大，土体越能储水。θr 表征在高基质吸力下仍难以排出的束缚水，是SWCC在高基质吸力端的渐近下限。θr 越大，土体在干燥阶段越能维持含水状态，反映出更强的持水能力。参数α控制曲线在吸力尺度上的位置。当其他参数不变时，α越小，在相同含水率下基质吸力越大，表明持水能力越强。孔径分布参数（n）主要调节SWCC过渡段的陡缓程度，n越小对应过渡段越平缓，孔径分布越分散。饱和渗透性系数（Ks）表示近饱和条件下导水能力的上限，Ks越大意味着导水通道连通性越好或大孔隙贡献越显著，从而使饱和与近饱和阶段的水分传输越迅速。
进气压力代表空气进入饱和土壤并开始排水的临界值。对比脱湿阶段的进气值可知，沟1与沟2的进气值近似相同，二者均低于沟4进气值，且明显低于沟3进气值。表明沟1与沟2更容易达到启动排水的条件，更容易进入脱饱和排水阶段；而沟3与沟4需在更高基质吸力条件下才开始排水，相对不容易达到启动排水条件。SWCC的滞后效应体现在脱湿与吸湿曲线在相同含水率状态下对应基质吸力的差距［23］。具体来看，沟1和沟2滞后效应弱于沟3和沟4。沟1沟2进气值在脱湿条件下为238~250 kPa，吸湿约50 kPa，脱湿吸湿间约为4~5倍差异，且饱和含水率在2条路径间仅小幅降低，由57%降至53%；沟3和沟4进气值在脱湿条件下为337~426 kPa，而吸湿进气值降至2.63~7.69 kPa，脱湿与吸湿间相差约55~128倍。已有研究［24］指出，滞后效应与孔隙结构及颗粒级配相关，当细颗粒含量较高、大孔隙不足时，孔隙水迁移速率降低，脱湿-吸湿过程的路径依赖性更强，从而表现出更强的滞后效应。滞后效应越强，土壤在相同基质吸力下的保水能力越强，表现为雨后含水率与储水量消退过程较缓、衰减系数较小，对降雨事件的响应相对滞后。从分析结果来看，滞后效应强弱呈现沟1≈沟2<沟3<沟4的总体趋势。与SWCC的滞后效应相同，HCF显示非饱和渗透系数随含水率升高快速增大，在相同含水率下吸湿路径总体高于脱湿路径。
2.2 含水率衰减规律
沟1（图4a、图4b）的监测期为2022年7月14日至9月30日，累计降雨量296.03 mm，降雨日数35 d。降雨过程主要集中于7月底至8月上旬，其中7月26日—28日为主要降雨过程，累计降雨76.74 mm；7月28日出现最大日降雨量40.13 mm，且7月27日记录到监测期最大雨强 18.83 mm/h。8月4日—5日亦发生强降雨过程，累计降雨量为 50.87 mm。沟3（图4c、图4d）的监测期为2025年7月29日至9月30日，累计降雨量154.57 mm，降雨日数27 d。该时段降雨以间歇性过程为主，其中8月2日出现最大日降雨量33.67 mm，并同步出现最大雨强17.71 mm/h。沟4（图4e、图4f）的监测期为2025年7月15日至9月30日，累计降雨量250.79 mm，降雨日数40 d。在7月22日—27日发生持续性降雨过程，累计降雨量达102.83 mm，其中7月26日出现最大日降雨量44.96 mm。
沟1、沟3和沟4的体积含水率的变化呈现表层含水率响应强而深层响应弱，雨后表层含水率快速下降而深层含水率缓慢变化的规律。该规律是从降雨补给到水分再分配再到排水与蒸散消耗的典型过程［25］。含水率对降雨的响应随土层深度增加而减弱，以代表性降雨事件为例，沟3在8月2日的降雨过程中，0~20 cm土层含水率的最大日增幅为8.66%，而20~40、40~60、60~80 cm土层含水率最大日增幅分别为3.21%、1.82%、2.90%，呈现随土层深度增加而减小的特征。降雨结束后，表层含水率的下降速率普遍高于深层，其原因可能在于表层主要受快速排水与蒸散过程共同控制，而深层更多体现为土体储水释放及缓慢排水的影响。
2.3 储水量衰减系数
沟1、沟3和沟4在0~20、20~40、40~60、60~80 cm土层的储水量递减段拟合结果（图5）可以看出，降雨结束后储水量（S）随相对天数（t）呈持续衰减趋势，且指数模型（公式4）能够较好地描述该衰减过程。该指数衰减形态表明，降雨后水分进入以重力排水与水分再分配为主导的消退阶段。初期土体含水状态较高、连通水通道较充分，水分下渗及侧向排水与再分配速率较快。随时间推移，土体逐渐脱湿，排水驱动力与连通水通道同步减弱，储水量下降速率随之放缓，从而呈先快后慢的衰减特征。
3处切沟的储水量衰减均表现出一致的垂直分异规律（表4），Kd随土层深度的增加而减小。沟1储水量衰减系数由0~20 cm的0.054递减至60~80 cm的0.010；沟3由0.082递减至0.006；沟4由0.036递减至0.006。表明随着土层深度加深，储水量的消退速度整体减缓。从过程上看，深层土体对降雨扰动的响应更平缓：一方面，水分向下或向侧向排出的路径更长，驱动水分迁移的梯度相对减弱，使得水分外排速度降低；另一方面，降雨结束后缓慢的水分再分配与持续性排水过程的叠加，使得深层土体储水量的日尺度波动较小，从而缓慢消退。各切沟对比显示，20~40 cm及更深深度，沟1的Kd整体高于沟3、沟4，说明沟1深层的储水量消退更快，而沟3在除表层外各深度的储水量衰减系数（Kd）都最小，表现为更缓慢的水分消退过程。
2.4 储水量预测模型及验证
通过日尺度的储水量预测模型计算储水量（图6），沟2（a~f）、沟3（g~j）、沟4（k~n）均表现出相同规律，即储水量在降雨补给作用下发生抬升，随后以指数形式消退，体现出从降雨补给到排水消退的典型事件响应。由于起始时刻的储水量（S0）由实测值直接赋值，该时刻4种降雨输入参数的预测值相同，纳入误差统计将人为降低误差并掩盖差异。因此，在逐点位误差评价中将其剔除，仅在剩余记录上计算储水量实测值与预测值的平均绝对误差，并以平均绝对误差最小者判定该点位更接近的储水量预测线。表5结果表明，在14个实测点位中，85.7%的点位最优降雨输入参数为I1 h，仅有14.3%的点位最优降雨输入参数为I2 h。
由图7可知，沟2、沟3和沟4储水量预测值与实测值进行1∶1检验结果。总体上，模型在3组数据上的相对误差为5.6%~6.5%，整体相对精度表现较稳定、误差水平可控。其中沟2绝对误差最小、稳定性最好；沟3平均绝对误差偏大；沟4均方根误差偏高，说明存在少量较大误差点需进一步优化。经检验，该模型能够在事件尺度上再现降雨后短期储水量的演化趋势。部分点位出现偏离，表明储水量的实际变化除受Kd与Ii h控制外，还可能受到初始含水状态差异、降雨历时结构与过程内分配等因素的共同影响。总体而言，该预测模型以Kd表征储水量的消退、以Ii h表征降雨输入，实现对降雨后储水量短期演化的参数化描述。
3 讨 论
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3.1 土壤水分滞后与衰减特性
SWCC曲线滞后效应强弱呈沟1≈沟2<沟3<沟4的总体趋势，表明沟3和沟4土体在脱湿吸湿过程中具有更强的路径依赖性。在切沟沟头区域，基质吸力深刻影响着土体稳定性。而SWCC的滞后效应使沟头水分呈显著的吸湿-脱湿过程路径依赖。降雨开始时，常表现为吸力快速衰减而含水量增长相对滞后，导致基质吸力短时间内显著降低，使沟头陡坎更易塌陷。雨停后水分状态并不沿原路径迅速恢复，基质吸力恢复与含水量回落具有明显时滞，使沟头失稳风险在降雨结束后仍可持续或进一步发展。在日尺度建模中，本文通过有雨日取含水率最大值，无雨日取含水率最小值的含水率处理方式区别吸湿和脱湿路径及在雨后储水量消退段上反演储水量衰减系数（Kd），从而实现对滞后效应的隐式表征。雨后沟头土壤储水量随时间呈指数型衰减，土壤储水量在初期下降迅速而后期趋缓，表现为饱和带排水过程由重力驱动向毛管束缚主导的转变。该衰减规律与Horton［26］入渗模型假定的土壤入渗能力随时间指数下降的理论一致。储水量衰减系数随土层深度增加而减小，且在20~80 cm土层内沟1储水量衰减系数显著大于沟3和沟4，此现象可能与东北黑土区耕作层与犁地层的剖面结构及土壤优先流有关［27-28］。沟1横穿林带，根系及腐根根孔易形成连通生物孔隙并触发优先流，使降雨入渗后的深层补给与重力排水更充分，因而在20~80 cm土层表现为更快的储水量消退。沟3、沟4位于农田内部，长期耕作可能在耕作层底部形成致密犁底层，导致水分入渗困难，深层水分衰退。拟合结果表明，沟头0~20 cm土层Kd高于其他3种深度土层Kd，佐证了深层土壤蓄水消退更缓慢、长时间保持较高含水率的认识［29］，且与侵蚀黑土的土层厚度和紧实度显著影响入渗性能，表层饱和含水量和渗透速率均高于深层土壤的试验结果［30］一致。因此，Kd值的垂直变化可作为评判土壤内部水力连通性的重要指标。
3.2 储水量预测模型及其验证
通过构建日尺度的沟头储水量预测模型，以储水量初值（S0）、衰减系数（Kd）及降雨输入参数（Ii h）为参数，实现对降雨事件后土壤储水量变化的模拟。从实测点平均误差分析可知，不同监测点的降雨输入参数存在差异。该差异可能与地形汇流条件和侵蚀扰动程度影响下，各点位有效入渗能力不同有关。沟头附近或受侵蚀严重的点位，地形汇流与土壤结构扰动可能入渗更快，使土壤储水量对峰值雨强更为敏感，该位置采用I1 h作为降雨输入参数能更准确地预测储水量。而在沟2点位6，沟4点位1区域，短时峰值雨强被坡面入渗和水分再分配作用而削弱，该位置采用I2 h作为降雨输入参数能更准确地预测储水量。因此，在开展土壤储水量预测时，入渗性能好的点位应选取I1 h为降雨输入参数，如沟头或受侵蚀严重的点位；而入渗性能差或有强烈水分再分配点位应选取I2 h为降雨输入参数，得到的预测值更接近真实值。对模型所得的储水量预测值与实测值进行1∶1检验，用统计学指标验证模型有效性。结果显示，储水量预测值与实测值的相对误差为5.6%~6.5%，表明模型能够较好地再现降雨后短期土壤储水量的演化过程。
4 结 论
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1）通过对比脱湿阶段进气值发现，启动脱饱和排水难易程度呈沟1≈沟2<沟4<沟3的趋势。SWCC曲线滞后效应强弱趋势为沟1≈沟2<沟3<沟4一致。滞后效应越强，排水时同一基质吸力下保水能力更强，表现为储水量衰减缓慢、衰减系数偏小，对降雨响应更迟缓。
2）降雨结束后沟头储水量随相对天数呈持续指数衰减趋势，表明降雨后水分进入以重力排水与水分再分配为主导的消退阶段逐渐转变为毛管束缚、导水率降低的缓慢消退阶段。3处切沟的储水量衰减均表现出一致的垂直分异规律：Kd随土层深度增加而减小。
3）日尺度储水量预测模型能够较好地再现降雨后短期储水量演化，预测值与实测值的相对误差为5.6%~6.5%。在降雨输入参数选取上，85.7%的点位以I1 h匹配最佳，14.3%的点位以I2 h匹配最佳；其中，入渗性能好的点位宜采用I1 h，入渗性能差或水分再分配强烈的点位宜采用I2 h。
基金
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  • 国家重点研发计划项目(2024YFD1501201-3)
文献
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doi: 10.13870/j.cnki.stbcxb.2026.04.033
  • 接收时间：2025-12-27
  • 首发时间：2026-09-30
  • 出版时间：2026-08-28
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  • 收稿日期：2025-12-27
  • 修回日期：2026-02-23
  • 录用日期：2026-04-01
基金
国家重点研发计划项目(2024YFD1501201-3)
作者信息
    北京林业大学水土保持学院，北京 100083

通讯作者:

马超（1986—），男，博士，教授，主要从事山地灾害成灾动力研究。E-mail：
参考文献
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https://castjournals.cast.org.cn/joweb/stbcxb/CN/10.13870/j.cnki.stbcxb.2026.04.033
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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