苏北花岗片麻岩地区USLE模型的试验研究

针对苏北花岗片麻岩地区水土流失的自然状况,建立了6种径流小区,进行试验研究。通过对364次降雨径流与土壤流失量的相关分析,得出适合本地区降雨侵蚀力因子R值的简便算式,确定了USLE模型中其他诸因子的取值。运用USLE模型计算的土壤侵蚀量与实测值进行偏差分析,结果表明,准确率达90％以上。该项研究为本地区水土流失预报与监测提供了科学简便的方法,其研究成果为本地区或同类型地区的小流域综合治理及水土保持规划提供了科学的依据。     

苏北花岗片麻岩地区USLE模型的试验研究

针对苏北花岗片麻岩地区水土流失的自然状况.建立了6种径流小区进行试验研究,通过对各小区364次降雨径流与土壤流失量的相关分析,得出适合本地区降雨侵蚀力因子R值的简便算式,确定了USLE模型中其它诸因子的取值.运用USLE模型计算各小区的土壤侵蚀量与实测值进行偏差分析,偏差为-3.5%～9.9%.可信度达90%以上.在实际应用检验中,梯田偏差5.64%,坡耕地偏差12.36%,可信度达87%以上.由此说明,USLE模型及其诸因子的取值方法在该地区的土壤侵蚀定量分析中具有很好的适用性.该项试验研究成果为该地区的水土流失预报与监测、水土保持规划及小流域综合治理提供了科学的依据.     

石灰岩山区工程建设对水土流失的影响研究

从对影响石炭岩山区土壤侵蚀的因素分析入手,获取有关可蚀性因子信息,利用变径流系数经验公式和通用水土流失方程（USLE）对住宅工程建设前后的建设期间的地表径流损失量和土壤流失量进行计算和预测,最后总结工程开发建设对石灰岩山区水土流失的影响特点。     

平凉纸坊沟流域水土流失影响因素及其相关关系分析

为了深入探讨黄土高原沟壑地区小流域水沙运动及水土流失规律,采用平凉市纸坊沟流域50a的降水、径流、泥沙观测资料和成果,建立数据库,采取数理统计、矩阵计算、分段对比、相关分析等方法对黄土高原沟壑区典型小流域纸坊沟流域的水沙特性及水土流失特点进行了分析,研究了流域降水、径流、泥沙基本特性及其变化规律和水土流失主要影响因素及其相互关系,建立了流域土壤侵蚀流失量与主要影响因素间的单因子数学模型,为同类地区小流域水土流失状况分析和径流、泥沙及水土流失量估算分析确立了简便方式。该文从其研究成果中提炼出了纸坊沟流域水土流失主要影响因子及其变化对土壤侵蚀流失量减少的影响程度以及土壤侵蚀流失量与主要影响因素间的单因子数学模型。     

基于GIS的南四湖沿岸农业面源氮磷负荷估算研究

以济宁市沿南四湖县区乡镇为主要研究区,根据降雨径流和土壤侵蚀量,运用遥感(RS)影像和地理信息系统(GIS),确定土壤通用流失方程(USLE)各参数,运用USLE对南四湖沿岸氮磷流失模数进行定量估算,为南四湖沿岸农业氮磷流失的消减与控制提供科学依据。结果表明:USLE模型计算的氮磷流失量主要集中在湖西区域,以喻屯镇、王鲁镇和唐口镇的流失量居于前列,最高的喻屯镇氮、磷流失量分别达439.9t/a和271t/a;湖东区域,石桥镇、马坡镇、欢城镇和韩庄镇的氮磷流失量居于前列,最高的石桥镇氮和磷流失分别为174t/a和120.6t/a。农田实际调查的氮和磷的流失量与模型计算值趋势较一致,两者呈极显著线性正相关(p<0.01)。氮的模型计算流失量略低于实际调查流失量,而磷的模型计算流失量远远高于实际调查流失量。主要是因为南四湖沿岸农田氮的流失是氮的主要流失形式,远高于畜禽养殖和生活排污的氮流失。而磷的流失主要来自畜禽养殖,其次才是农田流失磷。     

径流场监测结果在武汉黄陂区水土流失预测中的应用

基于武汉市黄陂区野佛沟径流场监测的径流和泥沙数据,通过类比法建立土壤流失量的预测模型,完成了从土壤流失监测到土壤流失预测研究的重大突破,为该类型区生产建设项目水土流失背景值的预测提供依据。同时对径流场监测的径流和泥沙数据进行统计分析,结果表明:土壤流失量的大小与降雨强度有着密切关系,其值的大小受环境因素的影响远比径流深度的影响复杂。     

北京市密云水库上游坡地水土流失监测系统的建立及应用

以北京市密云水库上游为示范监测区,利用遥感及地理信息系统,通过坡度、土地利用和植被覆盖度专题图形制作、交叉分析和土壤侵蚀强度判别,进行流域自然状况及水土流失面积调查;根据坡地土壤侵蚀区分布及坡地水土保持治理情况布设坡地径流小区,观测各类型区水土流失量及污染物流失量;分析计算全流域的水土流失量、污染物流失量及治理措施的水土保持效益。     

黑土区三江平原水土流失变化趋势研究

三江平原是我国东北黑土区重要的商品粮基地。基于GIS和RS,结合美国通用土壤流失方程(USLE),获得了三江平原1954、1976、1986、2000年4个时期的土壤流失量,并据此了解该区土壤侵蚀现状,分析水土流失变化趋势,为该区开展水土保持工作和政府宏观决策提供了科学依据。     

植被因子算式在土壤侵蚀定量监测中的应用研究

植被覆盖度与植被因子作为水土保持学科上的一个重要指标,历来受到众多的研究人员重视,作为美国通用流失量方程USLE中的一个参数因子,必须将它加以量化计算,本文以南安市水土流失定量遥感监测为例,具体叙述了在南安市进行水土流失遥感定量监测过程中,植被因子C值的求算过程,并叙述其主要步骤,最后得到了植被因子的C值,为水土流失监测系统提供基础资料或作为反映地表植被覆盖状况的一个“量”的指标。     

GIS技术在通用土壤流失方程中的应用

通用土壤流失方程（USLE）传入我国后，国内各级研究机构加以深放研究与适用性探索。结合遥感（RS）与地理信息系统（GIS）技术，实现以USLE为构式的区域土壤流失遥感监测，已在我国多处地区进行了尝试应用与实际应用。基于泉州市1996年度水土流失遥感监测所采用的技术路线，阐述了USLE方程因子的GIS生成以及土壤流失量的GIS实现依据。     

Erodibility of agricultural soils on the Loess Plateau of China

Soil erodibility is thought of as the ease with which soil is detached by splash during rainfall or by surface flow. Soil erodibility is an important factor in determining the rate of soil loss. In the universal soil loss equation (USLE) and the revised universal soil loss equation (RUSLE), soil erodibility is represented by an erodibility factor (K). The K factor was defined as the mean rate of soil loss per unit rainfall erosivity index from unit runoff plots. Although high rate of soil loss from the Loess Plateau in China is well known and widely documented, it is remarkable that there is little systematic attempt to develop and validate an erodibility index for soils on the Loess Plateu for erosion prediction. Field experimental data from four sites on the Loess Plateau were analyzed to determine the K factor for USLE/RUSLE and to compare with another erodibility index based on soil loss and runoff commonly used for the region. The data set consists of event erosivity index, runoff, and soil loss for 17 runoff plots with slope ranging from 8.7 to 60.1%. Results indicate that the K factor for USLE/RULSE is more appropriate for agricultural soils on the Loess Plateau than the erodibility index developed locally. Values of the K factor for loessial soils range from 0.0096 to 0.0269 t h/(MJ mm). The spatial distribution of the K value in the study area follows a simple pattern showing high values in areas with low clay content. For the four sites investigated, the K factor was significantly related to the clay content, (K=0.031−0.0013 Cl, r²=0.75), where Cl is the clay content in percent. The measured values of the K factor are systematically lower than the nomograph-based estimates by a factor of 3.3–8.4. This implies that use of the nomograph method to estimate soil erodibility would considerably over-predict the rate of soil loss, and local relationship between soil property and the K factor is required for soil erosion prediction for the region.     

Applying the USLE Family of Models at the Sparacia (South Italy) Experimental Site

Soil erosion is a key process to understand the land degradation, and modelling of soil erosion will help to understand the process and to foresee its impacts. The applicability of the Universal Soil Loss Equation (USLE) at event scale is affected by the fact that USLE rainfall erosivity factor does not take into account runoff explicitly. USLE‐M and USLE‐MM, including the effect of runoff in the event rainfall–runoff erosivity factor, are characterized by a better capacity to predict event soil loss. The specific objectives of this paper were (i) to determine the suitable parameterization of USLE, USLE‐M and USLE‐MM by using the dataseries of Sparacia experimental site and (ii) to evaluate their performances at both event and annual scale. The measurements allowed to establish the relationships for calculating the factors of USLE, USLE‐M and USLE‐MM usable at the Sparacia experimental area. At first, for slope‐length values greater than 33 m, the calibration of USLE model at event scale pointed out that sediment delivery processes, that is processes involving deposition of the transported eroded soil particles, occur. The analysis showed that USLE and USLE‐M tend to overestimate low event soil losses, while for USLE‐MM, this tendency is less pronounced. However, the USLE‐MM performed better than USLE and USLE‐M and was able to reproduce better than other two models the highest soil loss values that are the most interesting from a practical point of view. The results obtained at annual scale were generally consistent with those obtained at event scale. Copyright © 2016 John Wiley & Sons, Ltd.     

长江上游紫色土坡耕地水土流失特征及其防治对策

 紫色土是长江上游最重要的土地资源之一,严重的水土流失引发了一系列问题。在对紫色土坡面产流特征进行分析的基础上,研究紫色土坡面产流特征对水土流失的作用机制以及紫色土坡耕地水土流失防治对策。结果表明:紫色土坡耕地产流模式以蓄满产流为主,壤中流在坡面径流总量中所占比例较大;紫色土坡耕地土壤侵蚀导致土壤粗骨沙化,土壤养分流失途径与营养元素的溶解性有关,易溶的N、K主要以溶解态流失,易被土壤固定的P主要随土壤颗粒流失;壤中流是紫色土坡耕地水土流失的重要外营力之一,进行水土流失治理必须对其加以干预。提出长江上游紫色土坡耕地水土流失治理策略与"增渗防冲、排水保土,先排后蓄、蓄以为用"的治理措施。     

Field Evaluation of Selected Soil Erosion Models for Catchment Management in Indonesia

Three models, viz., areal non-point source watershed environment response simulation (ANSWERS), universal soil loss equation (USLE) and adapted universal soil loss equation (AUSLE) are evaluated for their performance under the field conditions of the Riam Kanan catchment in South Kalimantan province of Indonesia. While ANSWERS is evaluated for its accuracy to predict both runoff and soil loss, USLE and AUSLE are evaluated for soil loss only. The study was carried out in the context of sedimentation concerns for the Muhammad Nur Reservoir—an important source of drinking and irrigation water supply for the catchment. The models are evaluated using field data collected under four different land uses and during 2 years of field experiments. The land uses considered are cropland with minimum tillage, cropland with conventional tillage, grassland and areas reforested with rubber trees. The ANSWERS model in general has a tendency to overpredict runoff values. The ANSWERS model also was relatively better for predicting soil loss followed by the AUSLE and USLE models. Overall, the ANSWERS model proved superior for predicting soil loss in the Riam Kanan catchment. However, given that the AUSLE model produced sufficiently reliable results and is relatively easy to use, the AUSLE model would also appear to be a useful tool for predicting soil erosion in the catchment.     

南方丘陵紫色页岩地区土壤可蚀性因子K值的确定——以湖南衡阳为例

通过2003~2004年两年的径流小区试验,运用反推法和经验公式确定土壤可蚀性因子(K)的取值,并对两种结果进行比较分析得出衡阳紫色页岩地区的土壤可蚀性因子(K)的取值范围在0.34~0.37之间,为正确认识当地土壤特性从而提出有效减小水土流失危害的对策提供科学依据。     

Modelling runoff and soil erosion in logged forests: Scope and application of some existing models

Predictive erosion models are useful tools for evaluating the impact of land-use practices on soil and water properties, and as often used by environmental protection authorities, for setting guidelines and standards for regulation purposes. This study examines the application of three erosion models of varying complexity and design for predicting runoff and soil erosion from logged forest compartments in south eastern Australia. These are: the Universal Soil Loss Equation (USLE), the Water Erosion Prediction Project (WEPP), and TOPOG, a physically based hydrologic modelling package. Data on rates of soil loss and redistribution collected during a series of large-scale rainfall simulator experiments were used as model input parameters and validation. The models were evaluated in terms of general ease of use, input data requirements and accuracy of process understanding and prediction. Results suggest that in this application the USLE overestimated soil loss, and have the limitation that it does not predict sediment yield or sediment redistribution for specific storm events. When used at the hillslope scale, WEPP and TOPOG have predicted runoff and soil loss reasonably well, particularly on disturbed surfaces such as skid trails. On less disturbed surfaces such as the general harvesting area, both models performed less accurately, generally under-predicting soil loss and sediment yield, notably on sites with low observed values. The complexity and data requirements of WEPP and TOPOG limit their usability as a general-purpose, erosion hazard predicting tool. In terms of process understanding, none of the existing models accurately depict the nature and extent of sediment redistribution quantified in the rainfall simulator experiments. In order to advance the application and accuracy of modelling tools in forestry environments, this redistribution process should be considered integral to the refinement and redevelopment of future models.     

USLE用于估算工程建设项目水土流失量的讨论

USLE是适用于估算缓坡农耕地多年平均土壤侵蚀量的模型 ,由于工程建设项目水土流失预测的时段及范围与USLE的适用条件有较大差别 ,经工程建设施工扰动的土体结构与农耕地的土壤结构有较大差异 ,因此工程项目施工引起的水土流失不能直接用USLE进行估算。     

基于DEM和SCS模型的四川盆地丘陵区局地径流研究

人类活动对产流的影响是水文科学研究的热点,如何采取有效的方法利用表面径流成为解决水资源危机的关键问题。以重庆市忠县拔山镇3个村为研究区,基于土地利用、土壤、降雨等信息,应用SCS模型对四川盆地丘陵区局地径流进行计算和分析。研究区径流空间分布与下垫面土地利用类型和土壤类型密切相关,下垫面单一的水域和裸地所形成的径流量大,而有作物的水田和旱地所形成的径流量较小;研究区径流年内分配相对集中,主要产生在4月至10月,占全年的90%以上,但整体上看,径流与降雨呈现一致性趋势;研究区年际径流量分布不均,呈现丰、枯水年交替变化的现象,年径流变差系数Cv值较小。研究结果还表明:SCS模型所需参数较少,并考虑了径流与土壤特性和土地利用情况的关系,是一种简洁且实用的径流计算方法;利用GIS软件,可使局地径流数据图像化,这使径流等水文过程更加简明和直观。因此,利用GIS等软件分析研究各个集水区径流的时空变化等规律,可为研究各个集水区内农业水资源布局等提供方法和参考,实用性和可操作性强。