广东省1960～2007年降雨侵蚀力变化趋势分析

降雨侵蚀力反映由降雨引起的土壤侵蚀的潜在能力.本文利用广东省25个站点48年(1960～2007)的日雨量资料计算了各站的降雨侵蚀力,并用Mann-Kendall(M-K)非参数检验和克里格空间插值法分析了降雨侵蚀力的时空变化规律.结果表明:广东省降雨侵蚀力的空间分布呈沿海向内陆逐渐递减的趋势.全省大部分地区的年降雨侵蚀力呈现不明显上升趋势,且存在较明显的年代际和年际变化.降雨侵蚀力的年内分布特征和降雨量分布类似,呈"双峰型",主要集中在4～9月的雨季.对于季节序列,冬季、春季和夏季大部分地区的降雨侵蚀力有不同程度的上升,秋季全省几乎所有地区呈下降趋势.汛期的降雨侵蚀力变化特征与年降雨侵蚀力相似.     

TRMM3B42降雨数据在渭河流域的应用分析

运用渭河流域24个气象站点日降雨数据对2001~2012年热带测雨卫星(TRMM)3B42数据在不同子流域、不同降雨强度以及不同时间尺度的精度进行了对比验证,并对比分析了基于TRMM和站点数据的渭河流域降雨时空分布特征。结果显示:在不同子流域的日TRMM数据比站点观测数据对低值降雨更为敏感,而在极大值降雨数据观测上两者差距较大,月尺度TRMM站点观测数据确定性系数在0.89到0.96之间;两种数据在流域降雨的时空分布上表现一致性,在年内6月中旬~10月初为湿润多雨期,其余月份降雨较少,空间分布呈东南部大,西北部小的格局。     

祁连山石羊河上游山区土壤侵蚀的环境因子特征分析

在GIS技术支持下, 运用通用水土流失方程USLE, 对祁连山北坡东段的哈溪林区的土壤侵蚀量及空间分布进行了模拟运算, 并定量分析了各种环境因子与土壤侵蚀之间的关系. 结果显示: 研究区平均土壤侵蚀模数为25.1 t·hm^-2·a^-1, 微度和轻度侵蚀面积占总面积的80%, 而强度到剧烈侵蚀产生的侵蚀量占78.3%; 各土地类型土壤侵蚀模数由高到低依次是裸地>草地>农田>灌丛>乔木林, 裸地侵蚀量占到总侵蚀量的54.9%; 乔木林和灌木林95%以上侵蚀面积属微度侵蚀区, 农田中度到剧烈侵蚀的面积比例达到35.9%, 高于草地和其他植被类型, 而草地剧烈侵蚀面积比例高于农田. 海拔高度范围与土壤流失量之间的关系与植被的海拔分布范围明显相关; 土壤平均侵蚀模数随坡度的增加而增大, 土壤侵蚀量主要分布在15°～45°的坡度范围, 不同植被覆盖下土壤流失随坡度变化的趋势可在一定程度上反映该类植被对土壤流失的防止作用.     

珠江流域降水集中度时空变化特征及成因分析

基于珠江流域内43个常规气象站点1960~2012年的逐日降水资料,计算了流域内各站点长期降水集中度(LCI)和逐年降水集中度(ACI);采用Mann-Kendall趋势检验法和Sen’s坡度检验法检测ACI时间上的变化趋势;同时采用反距离权重插值法(IDW)对LCI的区域特征和ACI的变化趋势进行空间插值以分析降水集中度的时空分布规律;采用随机森林(RF)算法对降水集中度的影响因子进行重要度分析。结果表明:(1)珠江流域逐年降水集中度ACI的年际变化不明显,东南部呈上升趋势,西北部呈下降趋势;(2)珠江流域西北部长期降水集中度LCI值偏小,即降水分布较平均;东南部长期降水集中度LCI值偏大,即降水较集中,表明该地区降水极值情况发生的几率相对较高,该空间分布趋势可能是受距离海洋的远近及海拔的影响;(3)众多气候影响因子中,东亚夏季季风(EASMI)对珠江流域的降水集中度影响最明显。     

降雨侵蚀力对露天矿排土场边坡水土流失的影响研究

降雨侵蚀力反应降雨引起的土壤侵蚀潜在能力,是水土保持研究中的主要指标之一。以露天煤矿排土场不同覆盖类型边坡为研究对象,分析了日降雨侵蚀力与边坡侵蚀的关系。结果表明,从控制坡面径流深来看,降雨侵蚀力的作用受到了乔灌草和灌草配置的显著影响,其产生的坡面径流仅为对照区的42.9%和52.6%。从控制坡面侵蚀量来看,三种植物配置措施都具有显著减少功能,土壤侵蚀量仅为对照区的2.3%~6.7%。降雨侵蚀力与边坡水土流失量存在线性正相关,其中坡面径流深对降雨侵蚀力的响应快于土壤侵蚀量。     

基于被动微波遥感反演雪深的时间序列分析我国积雪时空变化特征

利用1978-2005年逐日中国积雪深度数据集,分析了我国积雪空间分布特征和季节时空分布特征,并运用趋势线分析方法和均方根差模拟了积雪深度和积雪日数的变化趋势及异常空间变化特征.结果表明:青藏高原东南、青藏高原西部和南部、新疆北部和东北山区为我国积雪空间分布四大高值区.近28 a来,积雪深度和积雪日数呈增加趋势,20世纪80年代青藏高原明显增加和明显减少趋势并存,90年代整体明显增加,2000-2005年整体基本不变.青藏高原中东部、新疆北部以及东北山区为积雪深度异常变化敏感区,而青藏高原西部则为积雪日数异常变化敏感区.     

塔里木河流域水文气象要素时空变化特征及其影响因素分析

本文首先应用非参数Mann—Kendall检验法和线性趋势统计检验法对塔里木河流域各水文气象要素的时间序列变化趋势进行显著性检验。根据Mann-Kendall计算的倾斜度值分析了该流域水文气象要素的空间变化趋势，进而探讨了研究区水文气象要素的时空分布特征。然后采用非参数Z统计量检验法分析其时空变化特点，特别是对降雨、径流、日照时数和平均气温变化趋势的对比分析。判识了影响塔里木河流域水文气象要素时空变化规律的主导因素。研究结果表明：流域内降水、平均气温呈较为明显的上升趋势，径流量则表现出明显的减少趋势，说明人类活动的影响在部分水文气象要素的变化趋势中可能占据了主导地位。     

祁连山及河西走廊地表干湿变化的时空分布

利用20个气象站1960-2006年的逐日气象资料, 采用FAO Penman-Monteith模型, 计算出祁连山及河西走廊各气象站的月潜在蒸发量, 在此基础上计算各气象站的月湿润指数, 然后进行季节、年地表湿润指数的统计, 进而对研究区地表干湿状况的时空变化进行分析.结果表明: 祁连山及河西走廊在20世纪80年代之前地表相对干旱, 之后相对湿润, 自60年代以来地表湿润指数有逐年增大的趋势; 年地表湿润指数的年际变化率为0.001 4 a-1, 相关系数为0.428 1, 通过了0.01的置信度检验, 表明地表湿润状况有明显改善, 其中春季和冬季增加趋势明显, 夏季增加趋势和秋季减小趋势不太明显.地表干湿变化趋势在空间上有差异, 东部表现为东西差异, 自东向西逐渐变湿, 乌鞘岭以东呈变干趋势, 其他大部分地区显著变湿, 中部大部分地区呈不明显的变干趋势, 而托来南山以北地区显著变干, 张掖绿洲显著变湿, 西部除敦煌以西呈不显著的变湿趋势, 其他大部分地区显著变湿.      

白龙江流域不同降雨侵蚀力模型对比研究

降雨侵蚀力不仅是评价土壤流失、输沙量和水质模型的重要参数,也是气候环境变化模拟中的重要参量。基于白龙江流域5个气象站点逐日降雨观测资料,利用Renard等8个降雨侵蚀力模型分别计算白龙江流域降雨侵蚀力,并分析各模型之间的差异。结果表明Renard-Lo年降雨侵蚀力模型误差最大为76.2%,周伏建月降雨侵蚀力模型误差最小为2.1%,月降雨侵蚀力模型计算结果在白龙江流域优于年雨量和日雨量模型结果。白龙江流域年平均侵蚀性降雨占年降雨量的34.5%~46.0%。年降雨量与年平均降雨侵蚀力之间呈现高度相关,可以用幂函数拟合,各站相关系数均超过0.98。     

基于分布式水文模型的长江上游水资源时空变异性分析

本文首先分析了长江流域内154个气象站降水量和26个干支流水文站流量在1950～2000年期间的变化趋势。为定量分析长江上游地区降水量时空变化对水资源量的影响,构建了基于物理机理的分布式水文模型,模拟再现了天然河道条件下的水文过程。有别于传统的河道径流性水资源评价方法,本文尝试用径流深的空间变化来探讨水资源分布及演变态势。并以渠江罗渡溪水文站为个案,剖析了90年代秋季流量大幅减少的主要缘由。结果表明:受降水在时空分布上存在变异的影响,长江上游局部地区夏季径流深比率呈增加趋势,而秋季则相反;导致嘉陵江渠江水系秋季流量减少的主要原因是降雨,其次才是人为因素。     

桂江流域土壤侵蚀估算及其时空特征分析

桂江流域的水土流失现状研究对珠江三角洲的水生态安全有重要的现实意义。采用修正的通用土壤流失方程（RUSLE）估算了桂江流域的土壤侵蚀模数与年侵蚀总量,分析流域内土壤侵蚀的时空分布特征,探讨了影响该区域土壤侵蚀强度的自然与人文因素。结果表明,桂江流域51.8%的地表都在发生不同程度的土壤侵蚀。从全流域平均土壤侵蚀强度来看,属于中度侵蚀。从土壤侵蚀面积来看,约85%的地表处于微度、轻度与中度侵蚀。4-6月的全流域平均土壤侵蚀强度最大,侵蚀总量也是最大的。流域的土壤侵蚀主要发生在高程在30~600m的低山丘陵-高地地貌区内的林地与耕地中。流域内岩溶区的土壤侵蚀强度随着石漠化程度从无到中度逐渐增加,轻、中度石漠化区的土壤侵蚀强度达到强度侵蚀等级。      

http://www.sciencedirect.com/science/article/pii/S1674987111001034

A comprehensive methodology that integrates Revised Universal Soil Loss Equation（RUSLE） model and Geographic Information System（GIS） techniques was adopted to determine the soil erosion vulnerability of a forested mountainous sub-watershed in Kerala,India.The spatial pattern of annual soil erosion rate was obtained by integrating geo-environmental variables in a raster based GIS method.GIS data layers including,rainfall erosivity（R）,soil erodability（K）,slope length and steepness（LS）,cover management （C） and conservation practice（P） factors were computed to determine their effects on average annual soil loss in the area.The resultant map of annual soil erosion shows a maximum soil loss of 17.73 t h^-1 y^-1 with a close relation to grass land areas,degraded forests and deciduous forests on the steep side-slopes（with high LS ）.The spatial erosion maps generated with RUSLE method and GIS can serve as effective inputs in deriving strategies for land planning and management in the environmentally sensitive mountainous areas.     

Evaluation of rainfall erosivity and its temporal variation in the Yanhe River catchment of the Chinese Loess Plateau

The potential of rain to generate soil erosion is known as the rainfall erosivity (R), and its estimation is fundamental for a better understanding of the erosive ability of certain rainfall events. In this paper, we investigated the temporal variations of rainfall erosivity using common daily rainfall data from four meteorological stations during 1956 to 1989 and 2008 to 2010 periods in the Yanhe River catchment of the Chinese Loess Plateau. The adaptability of several simplified calculation models for R was evaluated and compared with the results of previous studies. An exponential model based on the modified Fournier index (MFI) was considered as the optimum for our study area. By considering the monthly distribution and coefficient of variation of annual precipitation, equations based on two indices, the MFI and its modification F _F , produced a higher calculation accuracy than mean annual precipitation. The rainfall erosivity in the Yanhe River catchment has a remarkable interannual difference, with a seasonality index ranging from 0.69 to 1.05 and a precipitation concentration index from 14.51 to 27.46. In addition to the annual rainfall amounts, the extreme wave of monthly rainfall distribution also has an effect on the magnitude and temporal variation of rainfall erosivity, especially interannual variation. For long time series of rainfall erosivity, a trend coefficient r of ?0.07 indicated a slight decline in erosivity in the Yanhe River catchment from 1956 to 2010.     

西南喀斯特区土壤侵蚀研究进展

西南喀斯特区土层浅薄、成土速率低等特点决定了其允许土壤流失量小,土壤一旦流失,极难恢复,土壤侵蚀及其造成的石漠化现象已成为制约该区可持续发展最严重的生态环境问题。文章首先明晰西南喀斯特区土壤侵蚀特征,从坡面、小流域和区域三个尺度上系统概括西南喀斯特区土壤侵蚀的相关研究进展。针对当前喀斯特区土壤侵蚀研究野外径流小区、小流域及区域空间尺度数据缺少和相关研究模型限制性强等不足,建议从不同尺度深入研究喀斯特区土壤侵蚀发生发展规律及时空演化格局,并结合高新遥感、地球物理探测技术及模型,同步监测坡面—小流域—区域土壤流失,对土壤侵蚀进行定量评估,结合不同空间尺度土壤侵蚀特征构建系统性水土保持生态恢复治理模式和监测系统评价体系。      

Evaluation of soil loss change after Grain for Green Project in the Loss Plateau: a case study of Yulin,China

Soil erosion is one of the serious and urgent issues in the Loss Plateau of China. Chinese government has implemented Grain for Green Project to restore the ecological environment since 1999. In order to explore the spatiotemporal evolution of erosion and sediment yield before and after Grain for Green Project in the Loss Plateau, annual soil loss of Yulin from 2000 to 2013 is estimated by Chinese Water Erosion on Hillslope Prediction Model in conjunction with Remote Sensing and Geographic Information Systems. This model has the characteristics of a simple algorithm and can be applied to predict erosion in the Loss Plateau. The result shows that vegetation cover increased significantly after Grain for Green Project, and the annual average value of NDVI increased from 0.20 to 0.33. The spatiotemporal variations of soil erosion are largely related to rainfall erosion distribution, slope, and land use type. The overall soil erosion categories in the south region are higher than those of the northwest. Mid slopes and valleys are the major topographic contributors to soil erosion. With the growth of slope gradient, soil erosion significantly increased. The soil loss has a decreasing tendency after Grain for Green Project. Although the rainfall of 2002 and 2013 is similar, the soil loss decreased from 5192.86 to 3598.94 t/(km² a), decreasing by 30.33%. It is also expressed that soil loss appears a reducing trend in the same degree of slope and elevation in 2002, 2007, and 2013. Under the simulation of the maximum and the minimum rainfall, soil erosion amount in 2013 decreased by 29.16 and 30.88%. The study proved that GFG has already achieved conservation of water and soil. The results indicate that the vegetation restoration as part of the Grain for Green Project on the Loss Plateau is effective.     

Spatio-temporal changes in rate of soil loss and erosion vulnerability of selected region in the tropical forests of Borneo during last three decades

An attempt has been made to analyze the spatial-temporal characteristics of soil erosion vulnerability and soil loss from the forested region in the north-eastern Borneo, Sarawak, Malaysia during the last three decades (1991–2015) using the revised universal soil loss equation (RUSLE) and geographical information systems (GIS). The components of RUSLE such as rainfall erosivity (R), soil erodibility (K), slope-length and steepness (LS), cover management (C) and conservation practice (P) factors were grouped into two categories by keeping one set as temporally changing and others as static. Among them the R and C factors are calculated for the years 1991, 2001 and 2015 whereas the K and LS factors are considered for the single time frame. Because of the forested nature of the study area, the P factor is kept constant for the whole analysis. The R factor and C factor is shown changes in values and its distribution over the years, which reflected in the final soil loss and erosion vulnerability map as a change in the rate of erosion and spatial domain. The analysis of three time slices has shown that the maximum value of the soil loss per unit area i.e. at erosion hotspots, is relatively similar throughout at around 1636 to 1744 t/ha/y. This is the result of maximum values of R factor and C factor i.e. high rainfall erosivity combined with lack of vegetation cover in those hotspots, which are generally steeply sloping terrain. The reclassification of annual soil loss map into erosion vulnerability zones indicated a major increase in the spatial spread of erosion vulnerability from the year 1991 to 2015 with a significant increase in the high and critical erosion areas from 2.3% (1991) to 31.5% (2015). In 1991, over 84% of the study area was under low erosion vulnerability class but by the year 2015 only 12% was under low erosion vulnerability class. Moreover, a dynamic nature in the erosion pattern was found from the year 1991 to 2015 with more linear areas of land associated with higher rate of soil loss and enhanced erosion vulnerability. The linearity in the spatial pattern is correlated with the development of logging roads and logging activities which has been confirmed by the extraction of exposed areas from satellite images of different years of analysis. The findings of the present study has quantified the changes in vegetation cover from dense, thick tropical forest to open mixed type landscapes which provide less protection against erosion and soil loss during the severe rainfall events which are characteristic of this tropical region.     

Soil erosion and sediment yield modeling using RS and GIS techniques: a case study, Iran

Water erosion is a serious and continuous environmental problem in many parts of the world. The need to quantify the amount of erosion, sediment delivery, and sediment yield in a spatially distributed form has become essential at the watershed scale and in the implementation of conservation efforts. In this study, an effort to predict potential annual soil loss and sediment yield is conducted by using the Revised Universal Soil Loss Equation (RUSLE) model with adaptation in a geographic information system (GIS). The rainfall erosivity, soil erosivity, slope length, steepness, plant cover, and management practice and conservation support practice factors are among the basic factors that are obtained from monthly and annual rainfall data, soil map of the region, 50-m digital elevation model, remote sensing (RS) techniques (with use of Normalized Difference Vegetation Index), and GIS, respectively. The Ilam dam watershed which is located southeast part of Ilam province in western Iran is considered as study area. The study indicates that the slope length and steepness of the RUSLE model are the most effective factors controlling soil erosion in the region. The mean annual soil loss and sediment yield are also predicted. Moreover, the results indicated that 45.25%, 12.18%, 12.44%, 10.79%, and 19.34% of the study area are under minimal, low, moderate, high, and extreme actual erosion risks, respectively. Since 30.13% of the region is under high and extreme erosion risk, adoption of suitable conservation measures seems to be inevitable. So, the RUSLE model integrated with RS and GIS techniques has a great potential for producing accurate and inexpensive erosion and sediment yield risk maps in Iran.     

"5·12" 地震后汶川县泥石流特征与演化分析

2008年“5·12”汶川地震极大地改变了震区泥石流的特征,不仅增强了泥石流的活动性,同时也使得震区在相当长的时间内都要面临泥石流的威胁。本文基于前人大量的研究成果,并利用遥感解译结合现场调查等手段,分析了汶川县泥石流沟道纵坡降、沟壑密度、两岸坡度等基本发育特征;进而分析了地震前后汶川县降雨分布及泥石流相关降雨参数变化特征。结果显示,流域内泥石流沟的沟壑密度在0.2~4之间,属于微度土壤侵蚀区域,泥石流的沟床纵坡降偏大,有利于泥石流的发生;泥石流流域内斜坡坡度多为30°~40°,有利于灾害的发生;震后汶川县年均降雨量增加了5.17%,降雨多集中在7~9月份,降雨量由南及北逐渐降低;震后泥石流的降雨阈值在2008~2013年呈现缓慢回升的趋势,但2019年又有所下降,预计恢复到震前水平尚需要一定时间;同时震后汶川县泥石流物源丰富,震后物源量呈现“震荡式衰减”的演化趋势,但体量仍然很大,对泥石流仍需坚持监测预警工作。