Assessment of soil erosion in the Irga watershed on the eastern edge of the Chota Nagpur Plateau,India

Human activities to improve the quality of life have accelerated the natural rate of soil erosion.In turn,these natural disasters have taken a great impact on humans.Human activities,particularly the conversion of vegetated land into agricultural land and built-up area,stand out as primary contributors to soil erosion.The present study investigated the risk of soil erosion in the Irga watershed located on the eastern fringe of the Chota Nagpur Plateau in Jharkhand,India,which is dominated by sandy loam and sandy clay loam soil with low soil organic carbon(SOC)content.The study used the Revised Universal Soil Loss Equation(RUSLE)and Geographical Information System(GIS)technique to determine the rate of soil erosion.The five parameters(rainfall-runoff erosivity(R)factor,soil erodibility(K)factor,slope length and steepness(LS)factor,cover-management(C)factor,and support practice(P)factor)of the RUSLE were applied to present a more accurate distribution characteristic of soil erosion in the Irga watershed.The result shows that the R factor is positively correlated with rainfall and follows the same distribution pattern as the rainfall.The K factor values in the northern part of the study area are relatively low,while they are relatively high in the southern part.The mean value of the LS factor is 2.74,which is low due to the flat terrain of the Irga watershed.There is a negative linear correlation between Normalized Difference Vegetation Index(NDVI)and the C factor,and the high values of the C factor are observed in places with low NDVI.The mean value of the P factor is 0.210,with a range from 0.000 to 1.000.After calculating all parameters,we obtained the average soil erosion rate of 1.43 t/(hm^(2)•a),with the highest rate reaching as high as 32.71 t/(hm^(2)•a).Therefore,the study area faces a low risk of soil erosion.However,preventative measures are essential to avoid future damage to productive and constructive activities caused by soil erosion.This study also identifies the spatial distribution of soil erosion rate,which will help policy-makers to implement targeted soil erosion control measures.

Evaluation of soil erosion vulnerability in Hubei Province of China using RUSLE model and combination weighting method

Soil erosion has been recognized as a critical environmental issue worldwide.While previous studies have primarily focused on watershed-scale soil erosion vulnerability from a natural factor perspective,there is a notable gap in understanding the intricate interplay between natural and socio-economic factors,especially in the context of spatial heterogeneity and nonlinear impacts of human-land interactions.To address this,our study evaluates the soil erosion vulnerability at a provincial scale,taking Hubei Province as a case study to explore the combined effects of natural and socio-economic factors.We developed an evaluation index system based on 15 indicators of soil erosion vulnerability:exposure,sensitivity,and adaptability.In addition,the combination weighting method was applied to determine index weights,and the spatial interaction was analyzed using spatial autocorrelation,geographical temporally weighted regression and geographical detector.The results showed an overall decreasing soil erosion intensity in Hubei Province during 2000 and 2020.The soil erosion vulnerability increased before 2000 and then.The areas with high soil erosion vulnerability were mainly confined in the central and southern regions of Hubei Province(Xiantao,Tianmen,Qianjiang and Ezhou)with obvious spatial aggregation that intensified over time.Natural factors(habitat quality index)had negative impacts on soil erosion vulnerability,whereas socio-economic factors(population density)showed substantial spatial variability in their influences.There was a positive correlation between soil erosion vulnerability and erosion intensity,with the correlation coefficients ranging from-0.41 and 0.93.The increase of slope was found to enhance the positive correlation between soil erosion vulnerability and intensity.

Changes in Climate Factors and Their Impacts on Wind Erosion Climatic Erosivity in Farming-pastoral Zone of Northern China

Climate change can affect wind erosion power and hence induce changes in wind erosion rates.In this study,the wind erosion climate factor(C-factor),proposed by the Food and Agriculture Organization of the United Nations,was used to assess the impact of changes in climate on wind erosion climatic erosivity.The Mann-Kendall test was employed to detect trends in the C-factor during the period of 1961–2017 in the farming-pastoral zone of northern China.Sensitivity analysis was used to determine the sensitivity of the C-factor to changes in key climate factors.Furthermore,a comparison of the contributions of different climate factors was carried out to understand their impact on changes in the C-factor.The results indicated that most of the surveyed region exhibited decreasing trends in wind speed at a confidence level of 90%,while maximum and minimum temperatures showed increasing trends throughout the study area.As a consequence of decreasing wind speed,the annual C-factor exhibited significant decreasing trends,with a mean slope of–0.58/yr.Seasonal analysis revealed that in most regions,the changes in the C-factor had significant decreasing trends in spring,winter,and autumn,while in more than two-thirds of the study area,no significant change trends in the C-factor were detected in summer at a confidence level of 90%.Sensitivity analysis showed that the C-factor was most sensitive to wind speed,and that the sensitivity coefficients from July to September were much higher than those in other months.Contribution analysis revealed that,for most stations,wind speed(with greater values of sensitivity coefficients)was the dominant factor in the change of C-factor,while for some stations,the minimum temperature made the most contribution to the C-factor’s change due to its dramatic changes during the study period.Although the minimum temperature sensitivity coefficient was the lowest of all the sensitivity coefficients,it is urgent to evaluate the expected impact of minimum temperature due to its possible changes in the future.

Gully erosion spatial modelling: Role of machine learning algorithms in selection of the best controlling factors and modelling process

This investigation assessed the efficacy of 10 widely used machine learning algorithms(MLA)comprising the least absolute shrinkage and selection operator(LASSO),generalized linear model(GLM),stepwise generalized linear model(SGLM),elastic net(ENET),partial least square(PLS),ridge regression,support vector machine(SVM),classification and regression trees(CART),bagged CART,and random forest(RF)for gully erosion susceptibility mapping(GESM)in Iran.The location of 462 previously existing gully erosion sites were mapped through widespread field investigations,of which 70%(323)and 30%(139)of observations were arbitrarily divided for algorithm calibration and validation.Twelve controlling factors for gully erosion,namely,soil texture,annual mean rainfall,digital elevation model(DEM),drainage density,slope,lithology,topographic wetness index(TWI),distance from rivers,aspect,distance from roads,plan curvature,and profile curvature were ranked in terms of their importance using each MLA.The MLA were compared using a training dataset for gully erosion and statistical measures such as RMSE(root mean square error),MAE(mean absolute error),and R-squared.Based on the comparisons among MLA,the RF algorithm exhibited the minimum RMSE and MAE and the maximum value of R-squared,and was therefore selected as the best model.The variable importance evaluation using the RF model revealed that distance from rivers had the highest significance in influencing the occurrence of gully erosion whereas plan curvature had the least importance.According to the GESM generated using RF,most of the study area is predicted to have a low(53.72%)or moderate(29.65%)susceptibility to gully erosion,whereas only a small area is identified to have a high(12.56%)or very high(4.07%)susceptibility.The outcome generated by RF model is validated using the ROC(Receiver Operating Characteristics)curve approach,which returned an area under the curve(AUC)of 0.985,proving the excellent forecasting ability of the model.The GESM prepared using the RF algorithm can aid decision-makers in targeting remedial actions for minimizing the damage caused by gully erosion.

Risk factors for proton pump inhibitor refractoriness in Chinese patients with non-erosive reflux disease

AIM:To analyze risk factors for refractoriness to proton pump inhibitors(PPIs) in patients with non-erosive reflux disease(NERD).METHODS:A total of 256 NERD patients treated with the PPI esomeprazole were enrolled.They were classified into symptom-free and residual symptoms groups according to Quality of Life in Reflux and Dyspepsia(QolRad) scale.All subjects completed questionnaires on psychological status(self-rating anxiety scale;selfrating depression scale) and quality of life scale(Short Form 36).Multivariate analysis was used to determine the predictive factors for PPI responses.RESULTS:According to QolRad,97 patients were confirmed to have residual reflux symptoms,and the remaining 159 patients were considered symptom free.There were no significant differences between the two groups in lifestyle factors(smoking and alcohol consumption),age,Helicobacter pylori infection,and hiatal hernia.There were significant differences between the two groups in relation to sex,psychological distress including anxiety and depression,body mass index(BMI),and irritable bowel syndrome(IBS)(P < 0.05).Logistic regression analysis found that BMI < 23,comorbid IBS,anxiety,and depression were major risk factors for PPI resistance.Symptomatic patients had a lower quality of life compared with symptom-free patients.CONCLUSION:Some NERD patients are refractory to PPIs and have lower quality of life.Residual symptoms are associated with psychological distress,intestinal disorders,and low BMI.

Quantitative Analysis of Factors Influencing Soil Erosion and Construction of Conceptual Model

[Objective] The aim was to research soil erosion in boundary areas of Dongchuan City and Huize County in Yunnan Province through quantitative analysis on factors influencing soil erosion and establishment of conceptual model, providing method for land use and treatment of soil erosion. [Method] Based on Universal Soil Loss Equation （USLE）, quantitative indices determined and the conceptual model of of six factors influencing soil erosion were soil erosion was established. In addition. pixel-loss map was obtained through multiplication and soil erosive areas and the treatment schemes were proposed through statistical work of pixel-loss map and soil erosion map. [Result] In the research, annual loss modulus averaged 5 962 t/hm2, indicating the area was heavily eroded; from soil erosion map, it can be concluded that the heavily erosive area was near rivers, where wasteland and bare land dominated with slope of 30°-40° and without protective measures. [Conclusion] The research indicated that land use in the area is unreasonable erosive region should be paid more attention. In addition, the to be changed into terrace cultivation. and 51.6% of heavily wasteland is suggested to be changed into terrace cultivation.

Soil erosion and its causes in high-filling body:A case study of a valley area on the Loess Plateau,China

Large-scale land consolidation projects(LCPs)have been carried out on the Loess Plateau to increase the area of agriculture land.The newly created land is prone to soil erosion under the effects of water and gravity.Taking a typical high-filling body(HFB)formed by LCPs in Yan’an,China as the subject,this study comprehensively investigated the types and causes of soil erosion with multiple methods of field investigation,on-site monitoring and laboratory tests.Results showed that the HFB presented a composite pattern of soil erosion with multiple types mainly including underground erosion,mixed water-gravity erosion,seepage erosion,and scouring erosion.The type of erosion varied spatially in different parts of the HFB depending on the dominant factors,mainly including the groundwater state,rainfall,runoff,gravity action,topography,and soil erodibility.The underground erosion mainly occurred at the positions with higher groundwater level and larger hydraulic gradient,while scouring erosion mainly occurred at the positions with extensive interactions of surface runoff,channel slope gradient and soil properties.And near the leading edge of the top of the slope,a band of mixed watergravity erosion occurred owing to the effects of water and gravity.In addition,nearly saturated soils at the toe of HFB displayed groundwater exfiltration and slope-face slumping.Based on our findings on the causes and variation of soil erosion for the HFB,we proposed the following erosion prevention and control measures to protect the LCPs on the Loess Plateau:to construct drainage ditches and blind ditches to form a complete drainage system,plant alfalfa on the top platform to increase rainfall interception and reduce surface runoff,set seepage ditches and plant deep-rooted plants at the toe of the slope to improve slope toe stability,monitor groundwater level and slope deformation to learn the erosion dynamics and slope stability,and optimize the geometry of HFB such as the slope gradient and slope steps to reduce soil erosion.

Coastal erosion risk assessment of Hainan Island, China

Coastal erosion on islands is increasing due to sea level rise,frequent extreme events,and anthropogenic activities.However,studies on the multifactorial coastal erosion risk and the vulnerability of islands are limited.In this study,the Coastal Erosion Risk Assessment(CERA)method was applied for the first time to the study area in China to assess the erosion risk on the coast of Hainan Island;to explore the effects of coastal ocean dynamics,sediment movement characteristics,and anthropogenic construction;and to discuss the suitability of the method and countermeasures for coastal protection.The results show that the coast of Hainan Island shows high sensitivity,high value,low exposure,and moderate erosion.The whole island showed high vulnerability but low erosion risk,with the eastern region being more affected by erosion,particularly the eastern side of Wulong Port and Yalin Bay in Wenchang,and the shore section of Yalong Bay in Sanya,having a very high risk of coastal erosion.In addition,Monte Carlo simulation was used to check the applicability of the CERA method,and it was found that the rate of shoreline change,population density,and number of storms significantly contributed to coastal erosion,but only the short-term effects of sea level rise were considered.The effects of sea level rise and sediment grain size were primarily analyzed as influencing factors.The effects of sea level rise continue to strengthen,with coastal retreat expected to be greater than 2 m by the mid-21st century.Moreover,Hainan Island is primarily composed of the fine and medium sand types,which have little resistance to coastal erosion.Currently,the impact of sediment grain size is rarely considered in coastal erosion risk assessment studies.However,it can be incorporated into the indicator system in the future,and the spatial variation of indicators can be fully considered to strengthen the refinement study.

Driving forces and their interactions of soil erosion in soil and water conservation regionalization at the county scale with a high cultivation rate

Soil erosion control based on county scale Soil and Water Conservation Regionalization(SWCR)is an essential component of China's ecological civilization construction.In SWCR,the quantitative analysis of the spatial heterogeneity and driving factors of soil erosion among different regions is still lacking.It is of great significance for soil erosion control to deeply examine the factors contributing to soil erosion(natural,land use,and socioeconomic factors)and their interaction at the county and regional levels.This study focused on a highly cultivated area,Hechuan District of Chongqing in the Sichuan Basin.The district(with 30 townships)was divided into four soil and water conservation regions(Ⅰ-Ⅳ)using principal component and hierarchical cluster analysis.The driving factors of soil erosion were identified using the geographical detector model.The results showed thatⅰ)the high cultivation rate was a prominent factor of soil erosion,and the sloping farmland accounted for 78.4%of the soil erosion in the study area;ⅱ)land use factors demonstrated the highest explanatory power in soil erosion,and the average interaction of land use factors explained 60.1%of soil erosion in the study area;ⅲ)the interaction between natural factors,socioeconomic factors,and land use factors greatly contributes to regional soil erosion through nonlinear-enhancement of double-factor enhancement.This study highlights the importance of giving special attention to the effects of land use factors on soil erosion at the county scale,particularly in mountainous and hilly areas with extensive sloping farmland and a high cultivation rate.

1980—2016年中国北方风蚀气候侵蚀力的变化

随着修订风蚀方程(RWEQ)的提出,采用增加了冻结因子的气候因子(WF)表达风蚀气候侵蚀力更具有科学性和必要性。基于中国北方风蚀区157个气象站1980—2016年的观测数据,逐月计算了各站点气候因子,并探讨了气候因子时空分布变化特征及影响因素。结果表明:①1980—1997年,年气候因子值表现为快速下降,从940.46 kg/m下降到273.03 kg/m;而1998—2016年,年气候因子值表现相对稳定,在139.81~398.85 kg/m范围内波动。②春季气候因子值约占全年63%,其变化也显著高于其它季节,这也是土壤风蚀发生在春季的主要原因。③气候因子的高值区分布在新疆东部、青海西部、40°N以北的内蒙古中西部,这与气压中心和高大山体地形分布有关。

基于2次全国制图的土壤可蚀性因子变化趋势

2011年第1次全国水利普查水土保持专项普查基于全国各省(区、市)土壤类型图和土种志剖面数据,制作首张全国土壤可蚀性因子分布图(简称2011版K值)。为了提高土壤侵蚀评价的准确性和可信度,2022年利用全国土系调查数据和随机森林制图方法对中国土壤可蚀性因子分布图进行更新(简称2022版K值)。以全国水蚀区2011版和2022版的土壤可蚀性因子(简称K值)为研究对象,分别在流域尺度和不同土壤类型下对K值大小及空间分布进行研究。结果表明:2022版全国平均K值(0.0298 t·hm^(2)·h/(MJ·mm·hm^(2)))略低于2011版K值(0.0323 t·hm^(2)·h/(MJ·mm·hm^(2))),说明全国水土流失治理发展状况有向好的趋势。其中栗钙土、暗棕壤、盐碱土等土壤类型K值的降低幅度最大,潮土、褐土、黄壤等土壤类型的K值则有所升高。K值降低主要与退耕还林、土壤改良等政策措施的出台和布设有关,升高则与集约化耕作及坡地侵蚀有关。该结果可为水土流失动态监测及治理成效评价提供科学依据。

三峡库区水土流失遥感监测及治理研究

三峡库区是长江流域生态环境系统的重要环节,库区生态环境问题备受关注。水土流失是影响三峡库区生态安全、制约库区发挥生态屏障功能的关键环境问题之一。2020—2022年,水利部水土保持监测中心的三峡库区水土流失遥感监测站组织实施了基于遥感技术的三峡库区水土流失动态监测,结合野外考察和数值模拟等手段,对库区土壤侵蚀因子与侵蚀模数进行计算,并对水土流失防治效益进行评价。结果显示:(1)林地和耕地是水土流失发生的主要区域;(2)在相同的土地利用模式下,地形较陡的区域更易发生强度较大的水蚀;(3)2020—2022年,库区水土流失面积呈减少趋势,减少速率约为264 km^(2)/年,水土保持措施面积则以865 km^(2)/年的速率增加,取得较好治理效果。在进一步工作中,可针对性地在坡度较大的水蚀区进行合理的水保措施布设,以进一步提高库区水土流失治理成效。本研究可为三峡库区水土流失治理和水保措施规划以及长江流域生态系统建设提供科学依据。

托法替布对类风湿关节炎患者的干预效果分析

目的:探讨与分析托法替布对类风湿关节炎患者的干预效果.方法:选择2021年6月—2023年1月我院收治的80例类风湿关节炎患者作为研究对象,根据随机数字表法分为托法替布组与对照组,各40例.对照组给予甲氨蝶呤治疗,托法替布组在对照组治疗的基础上给予托法替布治疗,2组均治疗观察12周,比较2组患者的滑膜增生程度与骨侵蚀变化情况、肌骨超声半定量评分、生活质量评分及治疗期间不良反应发生率.结果:2组治疗12周后的骨侵蚀评分、滑膜增生评分均低于治疗前,且托法替布组治疗12周后骨侵蚀评分、滑膜增生评分均低于对照组,差异均有统计学意义(P<0.05).2组治疗期间恶心呕吐、嗜睡、静脉血栓、白细胞减少等不良反应发生率对比,差异无统计学意义(P>0.05).2组治疗12周后的肌骨超声半定量评分均低于治疗前,且托法替布组治疗12周后的肌骨超声半定量评分低于对照组,差异均有统计学意义(P<0.05).托法替布组治疗12周后的功能状况、情感状况、社会功能状况、生理功能状况等生活质量评分均高于对照组,组间差异有统计学意义(P<0.05).结论:托法替布在类风湿关节炎患者的应用能缓解滑膜增生程度与骨侵蚀程度,且不会增加不良反应的发生,还可降低患者的肌骨超声半定量评分,提高患者的生活质量,从而持续改善患者的预后.

非糜烂性胃食管反流病与食管胃结合部黏膜病变的相关性研究及其危险因素分析

目的:探讨非糜烂性胃食管反流病(NERD)与食管胃结合部黏膜隆起性病变的相关性,为NERD内镜下诊断提供证据;同时分析NERD的危险因素。方法:前瞻性收入2022年01月至2022年12月在我院行胃镜检查的患者,符合纳入标椎的患者纳入NERD组,同期无症状于我院体检行胃镜检查的患者纳入对照组。对比两组患者的一般人口学因素及内镜下因素,分析NERD与食管胃结合部黏膜隆起性病变的关系。结果:单因素分析显示,NERD组与对照组的性别、年龄、BMI、饮食习惯、饮酒、服用NSAIDs、胃食管阀瓣分级、食管胃结合部黏膜隆起性病变、胆汁反流及HP感染比较差异有统计学意义(P<0.05);经Logistic回归分析,女性、高BMI、不良饮食习惯、饮酒、服用NSAIDs、胃食管阀瓣松弛(Ⅲ+Ⅳ级)、食管胃结合部黏膜隆起性病变、胆汁反流及HP感染是影响NERD的相关因素;食管胃结合部黏膜隆起性病变对NERD判断的灵敏度为45.83%,特异度为86.27%。结论:食管胃结合部黏膜隆起性病变与NERD有着明显的关系,可将其作为NERD的一项支持性诊断证据,提高诊断的可靠性。女性、高BMI、饮酒、服用NSAIDs、不良饮食习惯、胃食管阀瓣松弛(Ⅲ+Ⅳ级)、胆汁反流等是影响NERD的独立危险因素;HP感染是NERD的保护因素。

典型水蚀区坡耕地黑土质量的空间分异特征及影响因素

[目的]为明确侵蚀—沉积在黑土坡耕地土壤质量空间分异格局中的塑造作用。[方法]以东北典型水蚀区坡耕地为研究对象,利用110个样点的土壤属性,采用基于最小数据集的土壤质量指数(SQI)指标,评价坡面尺度土壤质量的空间分异特征,并利用广义线性模型(GLM)明确坡度、坡位、土层深度等因子对土壤质量的贡献。[结果](1)坡耕地土壤养分含量和空间特征在耕作层和亚表层间呈相反规律。对于大部分养分指标,耕作层的含量显著高于亚表层,但是,其空间异质性及土壤养分含量间的相关性低于亚表层(p<0.05);(2)侵蚀沉积作用影响坡耕地土壤质量的空间分布特征。SQI在强烈侵蚀的坡中显著低于轻度侵蚀的坡上和沉积区的坡下(p<0.05),与坡上相比,坡中SQI在耕作层和亚表层分别降低26.2%和31.6%,沉积作用并不一定提高强烈侵蚀坡耕地沉积区的土壤质量,坡下和坡上耕作层的土壤质量无显著差异(p>0.05);(3)土层深度、坡位和坡度是坡耕地SQI变异的主要影响因素。GLM结果显示,对于同一个土壤层次,坡度、坡位及其交互作用对SQI变异的解释度达95%,其中,坡位和坡度的解释度分别为68%和22%;考虑土壤深度因素,在0—40 cm土层,土层深度、坡位和坡度对SQI变异的解释度分别为39%,31%和10%。[结论]采用SQI和GLM相结合的方法,明确侵蚀—沉积过程在坡耕地黑土质量空间分异中的塑造作用,研究成果可为典型水蚀区侵蚀退化黑土地质量评价和管理提供技术支撑。

Effect of Different Vegetation Types on Soil Erosion by Water

The C factor in Universal Soil loss Equation reflecting the effect of vegetation on soil erosion by water is one of the important parameters for estimating soil erosion rate and selecting appropriate land use patterns. In this study, the C factor for nine types of grassland and woodland was estimated from 195 plot-year observation data of six groups of soil erosion experiments on Loess Plateau. The result indicates that the effects of woodland and grassland on soil erosion keep approximately uniform after two or three years' growth. The estimated woodland C factor ranges from 0.004 to 0.164, and the grassland C factor ranges from 0.071 to 0.377, showing that the effect of woodland and grassland on soil conservation is greatly better than that of cropland. The study results can be used to compare or estimate the soil loss from land with different vegetation cover, and are the useful references for land use pattern selection and the project of returning cropland to forest or grassland.

Dynamics of Slope Runoff and Soil Erosion of Different Forest Types in Karst Depression

[Objective] The research was aimed to study the dynamics of slope runoff and soil erosion in different forest types in karst depression.[Method] Precipitation observation sites at the bottom of karst depression and runoff observation sites in different forest types were established to monitor regularly the main indices changes of runoff and soil erosion at fixed position in 4 years.[Result] The surface runoff of different forest types appeared singer peak from February to November,with lowest valley from June to July.The runoff coefficient appeared double peaks from February to May and from July to September.The changing coefficient of runoff appeared three peaks from March to April,from July to August and from September to November.The silt concentration appeared one peak from March to May and The erosion modulus appeared double peaks from March to May and from June to August.Runoff showed annually reduced trend with the growth of forests and the development of vegetation layer＇s structure.There was a positive correlation between the runoff and its silt concentration in different forest types.Precipitation and evaporation had notable positive correlation with the runoff,and similar correlation but not marked with silt concentration.The fitting analysis results of surface runoff and erosion modulus showed that rocky desertification intensified the unevenness of surface runoff and increased the surface runoff and erosion modulus.The penetrability of surface soil in new planted forest was lower than that in young forest,and that in surface soil of different forest types was higher than in bottom soil.[Conclusion] The research provided theoretical basis for the biological management technologies of water and soil conservation and the control of karst rocky desertification in karst regions.

1980—2020年延河甘谷驿流域土壤侵蚀评价与驱动因子分析

采用日降雨量、DEM、土壤类型、泥沙含量及多期NDVI等数据,基于修正通用土壤流失方程(RUSLE)和地理探测器,研究了国家生态退耕还林还草工程实施前后近41年延河甘谷驿流域土壤侵蚀动态与驱动因子。结果表明,1980—2020年研究区土壤侵蚀强度总体呈波动变化趋势,1980年、1990年、2000年、2010年和2020年平均侵蚀模数分别为6 746.30、5 740.28、6 389.56、5 450.46、5 480.56 t/(km~2·年)。1980—2000年研究区整体侵蚀强度逐渐增强,强烈及以上等级侵蚀面积占比逐渐增加,表现为“增蚀升级”的特点;2000年后研究区内土壤侵蚀强度开始降低,强烈及以上等级的侵蚀面积减少,总体表现为“减蚀降级”的特点。研究区土壤侵蚀强度随着坡度的升高而加剧,同时发现海拔1 000~1 200 m和1 200~1 400 m是研究区内侵蚀发生的主要高程带。2020年土地利用类型因子解释力最为突出,表明退耕还林还草工程实施效果显著,大面积的耕地向林草地转换是使得研究区2000年后土壤侵蚀强度降低的最主要原因。土壤侵蚀各影响因子的协同作用明显强于单一因子的影响。

Analysis on Status and Development Trend of Wind Erosion in Black Earth Region of Northeast China

In this paper,areas and main factors of wind erosion in black earth region of Northeast China were systematically analyzed,as well as the development trend of wind erosion in black earth region of Northeast China.In addition,development trend of wind erosion in black earth region of Northeast China was analyzed from the aspects of the geographic position,climatic change law in recent 40 years and effects of northeast sand land desertification on wind erosion in black earth region,which had provided references for the research and prevention of wind erosion in soil of black earth region of Northeast China.

1960-2020年东北黑土区水蚀动力因子时空格局及其对主要大气海洋环流模式的响应

[目的]研究东北黑土区水蚀动力因子的时空格局及其对大气海洋环流模式的响应,对区域极端降水事件诱发的土壤侵蚀防治有重要意义。[方法]选用降雨侵蚀力(R)、暴雨雨量(R 50p)、极端强降水量(R 95p)、连续5日最大降水量(R 5d)表征水蚀动力因子,基于1960-2020年逐日降雨数据,采用滑动平均、小波分析、Sen斜率估计法、Mann-Kendall检验方法,分析1960-2020年东北黑土区水蚀动力因子的时空格局,解析水蚀动力因子对大气海洋环流模式的响应。[结果](1)东北黑土区的年降雨侵蚀力(R)为1145.36~3575.94(MJ·mm)/(hm^(2)·h·a),暴雨雨量(R 50p)为73.17~197.86 mm,极端强降水量(R 95p)为265.81~566.35 mm;连续5日最大降水量(R 5d)为69.67~124.95 mm。(2)东北黑土区4个水蚀动力因子在1960-2000年均呈不显著上升趋势,且均未发生整体突变,但2015年后上升趋势明显,表明研究区发生降雨侵蚀的潜在可能性增加。4个水蚀动力因子均存在以约44年为主周期,29年为小周期的周期性变化特征,并经历高低交替2次振荡过程。(3)各水蚀动力因子的空间分布均呈现南高北低,东西两侧低中部高的特征,各指标的最大值出现在长白山-完达山山地丘陵区,最小值出现在呼伦贝尔丘陵平原区。(4)东亚夏季风指数(EASMI)是对东北黑土区水蚀动力因子影响最显著的单一环流模式,北极涛动(AO)和多元ENSO-南方涛动指数(MEI)可以通过影响东亚夏季风间接影响水蚀动力因子。东亚夏季风指数-南海夏季风指数叠加(EASMI-SCSSMI)对各水蚀动力因子的影响均为最显著(ΔPSAC>5%);而东亚夏季风指数、南海夏季风指数和多元ENSO-南方涛动的大气海洋环流模式仅对降雨侵蚀力(R)影响显著(ΔPSAC>5%)。[结论]东北黑土区水蚀动力时空格局的影响因素主要包括地形、东亚夏季风和南亚夏季风等,需关注2014年后水蚀动力增强带来的潜在水蚀危害。