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1.
Development and application of a simple hydrologic model simulation for a Brazilian headwater basin 总被引：1，自引：0，他引：1
Physically based hydrologic models for watersheds are important tools to support water resources management and predict hydrologic impacts produced by land-use change. Grande River Basin is located in southern Minas Gerais State, and the Grande River is the main tributary of Basin which has 2080 km2 draining into the Camargos Hydropower Plant Reservoir (CEMIG — “Minas Gerais State Energy Company”). The objectives of this work were: 1) to create a semi-physically based hydrologic model in semi-distributed to sub-basins approach and based on GIS and Remote Sensing tools and, 2) to simulate the hydrologic responses of the Grande River Basin, thus creating an important tool for management and planning of water resources for region. The hydrologic model is based on the SCS Curve Number (SCS-CN) and MGB/IPH models, and structured into three hydrologic components: estimation of the flow components (quick runoff, hortonian and base flows), propagation into the respective soil reservoirs (surface, sub-surface and shallow saturated zone) and propagation into the channels. Precipitation and discharge data sets were obtained from the Brazilian National Water Agency (ANA). Reference evapotranspiration (ETo) data were obtained from the Brazilian National Meteorological Institute (INMET). In order to estimate actual evapotranspiration, crop coefficient, soil moisture and satellite image interpretation of actual land-use were applied. The long-term hydrologic data series were structured for period between 1990 and 2003. The calibration and validation process was carried out by evaluating the behavior of the Nash–Sutcliffe Coefficient (CNS), obtained from three different combinations of calibration and validation years. This allowed us to evaluate the model performance to simulate years in which El Niño (EN) and La Niña (LN) events were registered (1997–1998 and 1999–2000, respectively). The combinations of calibration and validation years were: the first 7 years to calibrate and remaining 6 years to validate; the first 9 years to calibrate and remaining 4 years to validate; and first 11 years to calibrate and the last 2 years to validate. The statistical precision showed that the model was able to simulate the hydrologic impacts, including years of EN and LN events, with CNS scores greater than 0.70 in both situations. The evaluation of the CNS scores showed small variation in the coefficient as the years of validation decreased. In addition, the model was also able to simulate the hydrologic impacts of land-use change in the Grande River Basin, based on the CNS scores of 0.80 for different combinations of validation periods. The hydrologic impacts in Grande River Basin produced from grassland area converted to eucalyptus under three specific scenarios were evaluated, which predicted annual runoff mean reductions of up to 17.8%, due to an increase in evapotranspiration rate for the eucalyptus plantation. 相似文献
2.
《CATENA》2009,76(3):235-247
Physically based hydrologic models for watersheds are important tools to support water resources management and predict hydrologic impacts produced by land-use change. Grande River Basin is located in southern Minas Gerais State, and the Grande River is the main tributary of Basin which has 2080 km2 draining into the Camargos Hydropower Plant Reservoir (CEMIG — “Minas Gerais State Energy Company”). The objectives of this work were: 1) to create a semi-physically based hydrologic model in semi-distributed to sub-basins approach and based on GIS and Remote Sensing tools and, 2) to simulate the hydrologic responses of the Grande River Basin, thus creating an important tool for management and planning of water resources for region. The hydrologic model is based on the SCS Curve Number (SCS-CN) and MGB/IPH models, and structured into three hydrologic components: estimation of the flow components (quick runoff, hortonian and base flows), propagation into the respective soil reservoirs (surface, sub-surface and shallow saturated zone) and propagation into the channels. Precipitation and discharge data sets were obtained from the Brazilian National Water Agency (ANA). Reference evapotranspiration (ETo) data were obtained from the Brazilian National Meteorological Institute (INMET). In order to estimate actual evapotranspiration, crop coefficient, soil moisture and satellite image interpretation of actual land-use were applied. The long-term hydrologic data series were structured for period between 1990 and 2003. The calibration and validation process was carried out by evaluating the behavior of the Nash–Sutcliffe Coefficient (CNS), obtained from three different combinations of calibration and validation years. This allowed us to evaluate the model performance to simulate years in which El Niño (EN) and La Niña (LN) events were registered (1997–1998 and 1999–2000, respectively). The combinations of calibration and validation years were: the first 7 years to calibrate and remaining 6 years to validate; the first 9 years to calibrate and remaining 4 years to validate; and first 11 years to calibrate and the last 2 years to validate. The statistical precision showed that the model was able to simulate the hydrologic impacts, including years of EN and LN events, with CNS scores greater than 0.70 in both situations. The evaluation of the CNS scores showed small variation in the coefficient as the years of validation decreased. In addition, the model was also able to simulate the hydrologic impacts of land-use change in the Grande River Basin, based on the CNS scores of 0.80 for different combinations of validation periods. The hydrologic impacts in Grande River Basin produced from grassland area converted to eucalyptus under three specific scenarios were evaluated, which predicted annual runoff mean reductions of up to 17.8%, due to an increase in evapotranspiration rate for the eucalyptus plantation. 相似文献
3.
[目的]分析南汀河流域坡面土壤侵蚀的时空分异特征,为流域水土保持和边疆生态环境建设提供科学参考。[方法]基于通用土壤流失方程(USLE),运用RS和GIS技术计算南汀河流域1990,2000及2010年3个时段的土壤侵蚀模数。[结果]3个时段内研究区侵蚀模数呈现先升后降的趋势,年均侵蚀模数从24.75t/(hm2·a)升到30.05t/(hm2·a),然后降为25.87t/(hm2·a)。3个时段内,流域内强烈侵蚀及其以上的侵蚀面积仅占总侵蚀面积的19.94%,但对流域总侵蚀量的贡献高达73.56%。1990—2000年,强烈及强烈以下侵蚀面积减少了1 059.85km2,强烈侵蚀以上的侵蚀面积则增加了112.29km2;2000—2010年,微度侵蚀面积有小幅增加,其余侵蚀等级的侵蚀面积都有所下降。当坡度小于20°时,侵蚀模数随着坡度的增加而增加,坡度超过20°后,侵蚀模数有降低的趋势;从海拔上看,高侵蚀模数区域主要位于海拔500~2 000m范围。[结论]流域内的土壤侵蚀治理已初见成效,但在局部地区,土壤侵蚀仍有加剧现象。 相似文献
4.
Decline in global surface water quality around the world is closely linked to excess sediment and nutrient inputs. This study examined sediment and phosphorus fluxes in Aquia Creek, a fourth-order sub-watershed of the Chesapeake Bay located in Stafford, Virginia. The Revised Universal Soil Loss Equation (RUSLE), sediment delivery ratio (SDR), field sediment traps, bank erosion pins, and LIDAR data, combined with historical aerial images, were used in quantifying rill and inter-rill erosion from the basin, as well as internally generated sediments. Stream water and stream bank soils were analyzed for phosphorus. RUSLE/SDR modeling estimates a basin total sediment flux of 25,247 tons year?1. The greatest calculated soil losses were in deciduous forests and cropland areas, whereas medium and high-intensity developed areas had the least soil loss. Cut-bank erosion ranged from 0.2 to 27.4 cm year?1, and annual bank sediment fluxes were estimated at 1444 Mg, with a corresponding annual mass of phosphorous of 13,760 kg year?1. The highest bank loss estimates were incurred along reaches draining urban areas. Stream water total phosphorous levels ranged from 0.054 μg g?1 during low flows to 134.94 μg g?1 during high discharge periods in autumn and spring. These results show that stormwater management practices in urban areas are limiting runoff water and soil contact, reducing surficial soil loss. However, the runoff acceleration due to expansion of impervious surfaces is progressively increasing the significance of intrinsic sediment and phosphorous sources by exacerbating stream bank erosion and resuspension of internally stored sediments. 相似文献
5.
基于GIS/RS和USLE鄱阳湖流域土壤侵蚀变化 总被引：26，自引：7，他引：19
将空间信息技术（RS和GIS）和通用土壤流失方程（USLE）相结合对鄱阳湖流域土壤侵蚀量进行计算。分别利用1990年和2000年TM/ETM+影像分类得到两期土地利用/覆盖类型图,结合鄱阳湖流域数字高程模型（DEM）、土壤类型分布图和流域降雨资料分别获取USLE模型中各因子值的空间分布,最后计算流域2个年份的土壤侵蚀空间分布图。研究表明：鄱阳湖流域土壤侵蚀区域主要分布在赣江上游,信江上游,抚河上中游和修水上游地区;鄱阳湖流域1990年和2000年大范围土地经受着Ⅰ级微度与Ⅱ级轻度侵蚀,其侵蚀面积之和分别占流域面积的97.38%和97.30%;而流域产沙主要来源于Ⅱ级轻度侵蚀和Ⅲ级中度侵蚀,所占土壤侵蚀总量分别为58.16%和51.20%,其中中度以上等级的侵蚀对产沙量的贡献是不可忽视的;从1990年到2000年土壤侵蚀等级变化呈现了由中等级侵蚀（Ⅱ级轻度侵蚀和Ⅲ级中度侵蚀）向低等级（Ⅰ级微度侵蚀）和高等级侵蚀（Ⅴ级极强度和Ⅵ级剧烈侵蚀）的2个极端演化的趋势。鄱阳湖流域土壤侵蚀量从1990年到2000年增长幅度达6.3%;土壤平均侵蚀模数都约为1 100 t/(km2·a),属于Ⅱ级轻度侵蚀。分析2个年份的土地利用/覆盖变化,发现鄱阳湖流域湿地和农田面积减少,建筑用地增加均是造成土壤侵蚀量增加的因素,而降雨侵蚀力因子空间格局也对土壤侵蚀空间分布具有重要影响,最后提出了鄱阳湖流域水土保持规划措施。 相似文献
6.
Miguel L. Villarreal Robert H. Webb Laura M. Norman Jennifer L. Psillas Abigail S. Rosenberg Shinji Carmichael Roy E. Petrakis Philip E. Sparks 《Land Degradation \u0026amp; Development》2016,27(4):1106-1121
Decades of intensive off‐road vehicle use for border security, immigration, smuggling, recreation, and military training along the USA–Mexico border have prompted concerns about long‐term human impacts on sensitive desert ecosystems. To help managers identify areas susceptible to soil erosion from anthropogenic activities, we developed a series of erosion potential models based on factors from the Universal Soil Loss Equation (USLE). To better express the vulnerability of soils to human disturbances, we refined two factors whose categorical and spatial representations limit the application of the USLE for non‐agricultural landscapes: the C‐factor (vegetation cover) and the P‐factor (support practice/management). A soil compaction index (P‐factor) was calculated as the difference in saturated hydrologic conductivity (Ks) between disturbed and undisturbed soils, which was then scaled up to maps of vehicle disturbances digitized from aerial photography. The C‐factor was improved using a satellite‐based vegetation index, which was better correlated with estimated ground cover (r2 = 0·77) than data derived from land cover (r2 = 0·06). We identified 9,780 km of unauthorized off‐road tracks in the 2,800‐km2 study area. Maps of these disturbances, when integrated with soil compaction data using the USLE, provided landscape‐scale information on areas vulnerable to erosion from both natural processes and human activities and are detailed enough for adaptive management and restoration planning. The models revealed erosion potential hotspots adjacent to the border and within areas managed as critical habitat for the threatened flat‐tailed horned lizard and endangered Sonoran pronghorn. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
7.
基于USLE模型的大小凉山地区土壤侵蚀定量研究 总被引：3，自引：1，他引：2
[目的]对四川省凉山地区土壤水力侵蚀状况进行定量研究,为该区水土流失调查提供数据支持。[方法]利用四川省地理国情普查数据,基于对USLE模型的本土化研究成果进行分析和研究。[结果]凉山彝族自治州平均土壤侵蚀模数为1 207.67t/(km2·a),土壤侵蚀面积为15 221km2,占该区土地总面积的25.19%。从空间分布上看其中金沙江沿岸是凉山彝族自治州土壤侵蚀最为严重的地区,其次是安宁河流域和黑水河流域。[结论]凉山州目前水土流失面积较大,水土流失治理的形势依然严峻。 相似文献
8.
Nadine Konz Monika Schaub Volker Prasuhn Dominik Baenninger Christine Alewell 《植物养料与土壤学杂志》2009,172(5):615-622
Data on quantification of erosion rates in alpine grasslands remain scarce but are urgently needed to estimate soil degradation. We determined soil‐erosion rates based on 137Cs in situ measurements. The method integrates soil erosion over the last 22 y (time after the Chernobyl accident). Measured erosion rates were compared with erosion rates modeled with the Universal Soil Loss Equation (USLE). The comparison was done in order to find out if the USLE is a useful tool for erosion prediction in steep mountainous grassland systems. Three different land‐use types were investigated: hayfields, pasture with dwarf shrubs, and pasture without dwarf shrubs. Our test plots are situated in the Urseren Valley (Central Switzerland) with a mean slope steepness of 37°. Mean annual soil‐erosion rates determined with 137Cs of the investigated sites ranged between the minimum of 4.7 t ha–1 y–1 for pastures with dwarf shrubs to >30 t ha–1 y–1 at hayfields and pastures without dwarf shrubs. The determined erosion rates are 10 to 20 times higher compared to previous measurements in alpine regions. Our measurements integrated over the last 22 y, including extreme rainfall events as well as winter processes, whereas previous studies mostly reported erosion rates based on summer time and short‐term rainfall simulation experiments. These results lead to the assumption that heavy‐rainfall events as well as erosion processes during winter time and early spring do have a considerable influence on the high erosion amounts that were measured. The latter can be confirmed by photographs of damaged plots after snowmelt. Erosion rates based on the USLE are in the same order of magnitude compared to 137Cs‐based results for the land‐use type “pasture with dwarf shrubs”. However, erosion amounts on hayfields and pasture without dwarf shrubs are underestimated by the USLE compared to 137Cs‐based erosion rates. We assume that the underestimation is due to winter processes that cause soil erosion on sites without dwarf shrubs that is not considered by the USLE. Dwarf shrubs may possibly prevent from damage of soil erosion through winter processes. The USLE is not able to perform well on the affected sites. Thus, a first attempt was done to create an alpine factor for the USLE based on the measured data. 相似文献
9.
Field Evaluation of Selected Soil Erosion Models for Catchment Management in Indonesia 总被引：1，自引：1，他引：1
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. 相似文献
10.
青海湖流域土壤保持量动态变化 总被引：3，自引：1，他引：3
[目的]对青海湖流域近24a的土壤保持量进行评估,揭示其时空变化规律,为定量评估青海湖流域土壤保持功能和区域土壤保持的重要性提供理论支撑。[方法]利用通用土壤流失方程(USLE)和GIS技术,评估和揭示1987—2010年青海湖流域土壤保持量的时空动态变化。[结果]近24a来青海湖流域土壤保持量平均为4.68×108 t/a;单位面积土壤保持量高值区分布在青海湖流域主要河流的河源区及中部地区,低值区主要集中分布在青海湖周围、河谷以及青海湖流域西北部地区。在各生态系统中,高寒草甸的土壤保持量最大,平均为2.68×108 t/a。近24a来青海湖流域土壤保持量呈先增加后减小的变化趋势,并在2005年达到最大,相比于1987年,2010年其土壤保持总量共计增加了2.17×108 t,其中,高寒草甸的土壤保持量增加最多,增加了1.20×108 t。[结论]近24a来,青海湖流域土壤保持功能在不断增强,土壤侵蚀程度不断减弱,表明青海湖流域的生态环境在不断改善。 相似文献
11.
黑土区典型小流域土壤侵蚀空间格局模拟研究 总被引：3，自引：1，他引：2
利用校正后的基于GIS的USLE模型预测了黑土区域土壤侵蚀量的空间分布格局。研究结果表明,研究区小流域年侵蚀量值范围在0~60t/(hm2 a),无侵蚀、轻度侵蚀、中度侵蚀和强度侵蚀面积分别占研究区总面积的28.7%,56.2%,18.6%和0.1%。研究区坡顶土壤侵蚀量较少〔0~5t/(hm2 a)〕,坡肩和坡背侵蚀量较大〔3~15t/(hm2 a)〕。基于GIS的USLE不能够很好地模拟黑土区坡麓和坡足区域土壤沉积和侵蚀沟的空间分布格局,但可以较好地模拟坡顶、坡肩和坡背处的土壤流失状况。 相似文献
12.
为摸清东北黑土区土壤侵蚀与泥沙输移特征,以松花江流域为研究对象,选取不同侵蚀类型区8个水文站控制区,利用RUSLE模型,结合水文站实测输沙数据,分析了不同侵蚀类型区泥沙输移比的时空变化特征。结果表明:（1）松花江流域各侵蚀类型区均以微度侵蚀和轻度侵蚀为主,而草地、旱地和裸地侵蚀模数均呈现依次增大趋势,且大于该区容许土壤流失量,特别是松岭站、碾子山站、大石寨站和大山咀子站水文站控制区裸地土壤侵蚀模数均大于20 000 t/（km2·a）,达到剧烈侵蚀程度。不同侵蚀类型区之间侵蚀模数表现为丘陵沟壑区Ⅰ > 丘陵沟壑区Ⅱ > 天然林区 > 漫川漫岗区。（2）松花江流域不同侵蚀类型区泥沙输移比总体上表现为漫川漫岗区 > 丘陵沟壑区Ⅱ > 丘陵沟壑区Ⅰ > 天然林区。（3）同一侵蚀类型区不同年际间泥沙输移比波动起伏,而从20世纪60年代到80年代,人类活动影响较小的天然林区和丘陵沟壑区Ⅱ不同时期平均泥沙输移比相差不大,人类活动剧烈的漫川漫岗区和丘陵沟壑区Ⅰ平均泥沙输移比则表现为波动式递增。研究结果对于了解东北黑土区土壤侵蚀和泥沙输移规律,明确该区域土壤侵蚀机理和治理目标具有指导意义。 相似文献
13.
We applied the Revised Soil Loss Equation (RUSLE) to assess levels of soil loss in a Geographic Information System (GIS). In this study, we used the k-NN technique to estimate vegetation cover by integrating Landsat ETM+ scenes and field data with optimal parameters. We evaluated the root mean square errors and significance of biases at the pixel level in order to determine the optimal parameters. The accuracy of vegetation cover estimation by the k-NN technique was compared to that predicted by a regression function using Landsat ETM+ bands and field measurements as well as to that predicted by the Normalized Difference Vegetation Index (NDVI). We used a regression equation to calculate the cover management (C) factor of the RUSLE from vegetation cover data. On the basis of the quantitative model of soil erosion, we explored the relationship between soil loss and its influencing factors, and identified areas at high erosion risk. The results showed that the k-NN method can predict vegetation cover more accurately for image pixels at the landscape level than can the other two methods examined in this study. Of those factors, the C-factor is one of the most important affecting soil erosion in the region. Scenarios with different vegetation cover on high-risk areas showed that greater vegetation cover can considerably reduce the loss of soil erosion. The k-NN technique provides a new method to estimate the C-factor for RUSLE erosion mapping. The quantitative model of different vegetation cover scenarios provides information on how vegetation restoration could reduce erosion. 相似文献
14.
GIS/RS集成技术在叙利亚滨海土壤侵蚀评价和模拟研究上的应用 总被引：6，自引：0，他引：6
An integrated remote sensing(RS) and geographic informtion system(GIS) technique was employed to characterize the spatial distribution of the risk of soil erosion by water on Lakaia district ,Syria,The universal soil loss equation(USLE)was used to calculate the annual soil loss rates for Latakia soils ,Mainly,remote sensing data soil survey,land use inventory,elevation data and climatic atlases are used as resource data sets to generate USLE facto values ,The results revealed that integration of GIS/RS with USLE was a practical and effective approach for monitoring soil erosion over large areas. 相似文献
15.
黄土丘陵沟壑区不同空间尺度流域泥沙输移比研究 总被引：1，自引：1，他引：0
泥沙输移比是定量表征流域内侵蚀产沙-河道输沙特征的重要指标。探讨了不同尺度流域泥沙输移比计算的可能性与方法,以黄土丘陵沟壑区的径流小区、小流域、水文站实测资料为基础,利用径流小区观测资料和单元小流域侵蚀模数2种方法,对4种空间尺度流域的泥沙输移比进行了估算。结果表明:(1)对于面积在10~100km2的小流域,利用2种方法计算的泥沙输移比结果非常接近,说明在没有小区观测资料时,用单元小流域计算流域泥沙输移比是可行的。(2)对于土壤侵蚀类型单一的水文站控制流域,在没有面积>1km2单元小流域资料的情况下,可以用面积1~10km2小流域或面积10~100km2小流域作为单元小流域来计算泥沙输移比而对于侵蚀类型不同的支流其误差范围有些偏大。(3)流域治理措施的实施对于泥沙输移比的减少具有明显的效果,但治理措施减沙效应的发挥具有一定的滞后性。 相似文献
16.
17.
Development of improved soil erosion and sediment yield prediction technology is required to provide catchment stakeholders with the tools they need to evaluate the impact of various management strategies on soil loss and sediment yield in order to plan for the optimal use of the land. In this paper, a newly developed approach is presented to predict the sources of sediment reaching the stream network within Masinga, a large‐scale rural catchment in Kenya. The study applies the revised universal soil loss equation (RUSLE) and a developed hillslope sediment delivery distributed (HSDD) model embedded in a geographical information system (GIS). The HSDD model estimates the sediment delivery ratio (SDR) on a cell‐by‐cell basis using the concept of runoff travel time as a function of catchment characteristics. The model performance was verified by comparing predicted and measured plot runoff and sediment yield. The results show a fairly good relationship between predicted and measured sediment yield (R2=0·82). The predicted results show that the developed modelling approach can be used as a major tool to estimate spatial soil erosion and sediment yield at a catchment scale. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
18.
[目的] 通过分析十大孔兑水土流失面积、强度及水土流失动态变化,为流域综合治理提供参考依据。[方法] 基于全国土壤侵蚀遥感调查结果和全国水土流失动态监测成果,对比分析流域水土流失及其分布、动态变化。[结果] 十大孔兑流域植被面积占流域面积的63.97%,以中低覆盖和低覆盖为主,分别占植被覆盖面积的48.85%和36.54%。2021年水土流失面积为4374.98 km2,占流域面积的40.63%;与2020年、1999年和1985年相比,2021年水土流失分别减少46.32,3 664.50,4 958.03 km2,水土流失主要分布在草地、林地、耕地和其他土地4个地类上,占水土流失总面积的96.69%。[结论] 十大孔兑依然是黄河流域水土流失治理的难点地区,高强度侵蚀减少与年度监测成果未考虑沟道侵蚀有关;该区应坚持以“以沙棘种植为主的植被建设,以淤地坝建设为重点的工程布局,以锁边固沙为前提的治沙方针,大力推进拦沙换水试点工程”的流域综合治理策略。 相似文献
19.
地形因子计算方法对土壤侵蚀评价的影响 总被引：2，自引：0，他引：2
选取嫩江县、怀来县、吴起县、开州区、长汀县5个区域1∶1万地形图,生成5 m分辨率的DEM作为数据源。分别用分段坡长法和汇流面积法计算了坡长坡度因子,并用中国土壤流失方程(CSLE)计算了土壤侵蚀模数,评价了土壤侵蚀强度,对比分析了分段坡长法和汇流面积法对坡长因子及水土流失面积的影响。结果表明:采用汇流面积法提取的坡长因子值和空间分布差异比分段坡长法更大,2种方法的低值区差异较小,高值区差异较大。2种方法计算水土流失面积比例差异不大,而在计算土壤侵蚀强度上显示出明显的差异。研究结果为不同地形区土壤侵蚀的地形因子和土壤侵蚀评价提供了数据支撑和理论基础。 相似文献
20.
陕西省耕地土壤可蚀性因子 总被引：3，自引：0，他引：3
[目的]土壤可蚀性因子是计算土壤侵蚀的一个重要因子,对陕西省耕地土壤可蚀性因子展开研究,可为陕西地区的耕地土壤侵蚀计算及评价提供科学依据。[方法]以陕西省9个地区的耕地土壤实测数据为基础,利用通用土壤流失方程USLE(universal soil loss equation)、修订土壤流失方程RUSLE2(revised universal soil loss equation version 2)、侵蚀生产力影响模型EPIC(erosion productivity impact calculator)中可蚀性因子K值的计算公式以及几何平均粒径公式和几何平均粒径—有机质Dg-OM公式,计算不同耕地土壤质地条件下的土壤可蚀性因子。[结果]RUSLE2的极细砂粒转换公式在陕西黄土丘陵沟壑区平均低约14.53%,在陕南地区平均高约32.91%,使用修正公式后平均误差分别为7.81%和13.14%;对比分析K值的估算值与实测值,子洲县实测K值为0.002 69〔(t·hm2·h)/(hm2·MJ·mm)〕,Dg-OM模拟计算均值为0.0297〔(t·hm2·h)/(hm2·MJ·mm)〕;水蚀预报模型WEPP(water erosion prediction project)中的细沟间可蚀性(Ki)和细沟可蚀性(Kr),与USLE的K值相关系数分别为0.738 6和0.607 4。[结论]极细砂粒转换修正公式的计算误差小于RUSLE2模型;Dg-OM模型适合陕西黄土丘陵沟壑区及长武县、杨凌区和安康市典型耕地土壤;WEPP中Ki和Kr,当土壤砂粒含量小于30%,USLE的K值与WEPP的Ki和Kr值有强相关性。 相似文献