江苏省生产建设项目水土流失特点

基于江苏省191个部、省级大中型工程水土流失观测和调查数据,对江苏省点、线式工程水土流失的主要特点进行了分析、结果表明,点、线式工程施工期水土流失量均占到了总水土流失量的90%左右,线式工程水土流失强度(200.00 t/hm²)大于点式工程的水土流失强度(151.37 t/hm²);点、线式工程土壤侵蚀强度均在强度及以上等级;两类工程占地面积与施工期水土流失量均存在线性正相关关系(R_点²=0.9318,R_线²=0.9439),且两类工程扰动后土壤侵蚀模数与单位土石方填挖量均存在正相关关系(R_点²=0.9595,R_线²线=0.9324)。     

南方红壤区典型水土流失治理小流域的洪水径流泥沙特征

为探究南方红壤区经长期水土流失治理小流域的水沙特征,该研究收集长汀县朱溪河小流域2017—2020年降雨及洪水水沙数据,通过冗余分析、多元逐步回归方程、含沙量-流量滞回曲线等方法进行分析。结果显示：（1）流域年洪水径流深和泥沙量分别为282.30～892.50 mm和35.80～179.50 t/km²,洪水事件的产沙模数集中在0～20.0 t/km²,但总泥沙量由大于5.0 t/km²的少数事件决定;（2）降雨量、30 mim的最大雨强和降雨侵蚀力是影响洪水径流泥沙的主要降雨特征,对径流、泥沙变化的解释度分别为68.99%和49.28%,通过主要径流特征估算泥沙量、平均含沙量和最大含沙量,拟合优度达0.624～0.870;（3）洪水事件共出现6种含沙量-流量滞回关系,其中线型出现频率（55%）最高,该类事件中含沙量随流量的变化具有分阶段特征,临界含沙量约为0.1 g/L。经过长期的水土流失治理,红壤区小流域的洪水泥沙量普遍较低,且主要受径流量影响,洪水事件的滞回关系表明流域的泥沙供应通常处于持续少量的状态,研究结果有助于揭示红壤区土壤侵蚀的发展趋势。     

Effect of land management on runoff and soil losses from two small watersheds in St Lucia

The influence of land use on runoff and soil loss was assessed on two small watersheds in the Eastern Caribbean island of St Lucia, under contrasting land management regimes. The data generated from these watersheds revealed that the soil losses from an intensively cultivated agricultural watershed were 20‐times higher in magnitude than that of a forested watershed both for peak rainfall event and for total duration of analysis. This was due to higher surface runoff rates and exposure of soil to direct raindrop impact within cultivated areas. Whereas the forest canopy cover in combination with higher infiltration capacities of the forested land reduced the erosive runoff from the forest watershed and thus the soil loss. Moreover, the energy intensities of large storms in excess of 40 mm were estimated and found to range between 400 MJ mm ha⁻¹ h⁻¹ and 1834 MJ mm ha⁻¹ h⁻¹. 1

1 Megajoules‐millimeters per hectare‐hour.

Soil loss from the agricultural watershed was strongly correlated (R² = 0·85) to storm energy‐intensity (EI₃₀). However, the correlation of soil loss with the EI₃₀ (R² = 0·71) was poor for the forest watershed due to the effect of canopy vegetation, which significantly reduced the energy of raindrop impact. Over the study period, cumulative soil losses were 10·0 t ha⁻¹ for the agricultural site and 0·5 t ha⁻¹ for the forest site. 2

2 Metric tons per hectare.

The largest storm observed during the study period resulted in erosion losses of 3·78 t ha⁻¹ and 0·2 t ha⁻¹ from the agricultural and forest sites respectively. The regression models were developed using the measured data for prediction of runoff and soil loss over the watersheds of St Lucia under similar conditions. This study contributed towards efficient watershed management planning and implementation of suitable water conservation measures in St Lucia. Copyright © 2005 John Wiley & Sons, Ltd.     

作物覆盖度对土壤侵蚀的影响

为研究传统耕作模式下坡耕地作物覆盖度对土壤侵蚀的影响,利用冬小麦不同的种植密度和生长期来模拟作物不同的覆盖度情况。采用人工模拟降雨方法测定0,150万,250万,350万,450万株/hm² 5种不同密度处理在不同生育期的覆盖度、地表径流和土壤侵蚀,分析作物覆盖度对土壤侵蚀的影响。结果表明：(1)坡耕地作物种植密度的不同导致覆盖度产生差异,对土壤侵蚀有明显的影响,作物覆盖度一般随种植密度的增加而增加,但如果密度过大,由于生长状况不佳,覆盖度反而变小,表现为7.5万株/hm²时覆盖度最大,种植密度最大的9万株/hm²的覆盖度却不是最大;(2)侵蚀量和径流量与作物覆盖均呈较好的指数函数关系,分别为Y=44.37e^-0.09x(p<0.01),Y=1089.19e^-0.02x(p<0.01),即随作物覆盖度的增加,径流量和侵蚀量减少;(3)土壤侵蚀和地表径流之间存在显著的指数函数关系(R²=0.96)。研究...     

Assessment of soil erosion at large watershed scale using RUSLE and GIS: a case study in the Loess Plateau of China

Soil erosion is a serious problem in the Loess Plateau of China, and assessment of soil erosion at large watershed scale is urgently need. This study used RUSLE and GIS to assess soil loss in the Yanhe watershed. All factors used in the RUSLE were calculated for the watershed using local data. RUSLE‐factor maps were made. The mean values of the R‐factor, K‐factor, LS‐factor, C‐factor and P‐factor were 970 209 MJ km⁻² h⁻¹ a⁻¹, 0·0195 Mg h MJ⁻¹ mm⁻¹, 10·27, 0·33359 and 0·2135 respectively. The mean value of the annual average soil loss was found to be 14 458 Mg km⁻² per year, and the soil loss rate in most areas was between 5000 and 20 000 Mg km⁻² per year. There is more erosion in the centre and southeast than in the northwest of Yanhe watershed. Because of the limitations of the RUSLE and spatial heterogeneity, more work should be done on the RUSLE‐factor accuracy, scale effects, etc. Furthermore, it is necessary to apply some physical models in the future, to identify the transport and deposition processes of sediment at a large scale. Copyright © 2005 John Wiley & Sons, Ltd.     

冻融条件下土壤侵蚀阻力影响因素

为揭示季节性冻融区土壤侵蚀阻力的变化机制，确定影响土壤侵蚀阻力主控因子，通过室内冻融模拟、水槽冲刷和土壤抗剪试验，对黄绵土(SM粉质壤土)、风沙土(WS砂壤土)和黑土(KS黏壤土)侵蚀阻力影响因素进行研究。结果表明：(1)随着冻融循环次数增加，细沟可蚀性值逐渐升高，而临界剪切力降低。经历10次冻融循环后，SM粉质壤土、WS砂壤土和KS黏壤土的细沟可蚀性分别增加76%,63%,11%,临界剪切力分别减小37%,13%,91%。(2)细沟可蚀性随土壤抗剪强度、黏聚力和内摩擦角增大而减小，临界剪切力则呈相反趋势。与内摩擦角相比，黏聚力更适合用来表征土壤侵蚀阻力。采用黏聚力对SM粉质壤土、WS砂壤土和KS黏壤土的细沟可蚀性进行预测，决定系数(R²)分别为0.42,0.78,0.50,平均为0.57;对临界剪切力的预测效果较差，决定系数(R²)分别为0.16,0.14,0.18,平均仅为0.16。(3)根据皮尔逊相关分析结果，基于土壤的初始含水率、冻融循环次数、力学特性以及土壤参数等分别建立细沟可蚀性(R²=0.85)和临界剪切力...     

小麦秸秆粉碎还田配施氮肥与多酚对土壤侵蚀阻力的影响

小麦秸秆粉碎还田可改变土壤性质,进而影响土壤侵蚀阻力。以北方土石山区褐土为研究对象,利用L_9(3~4)正交表对秸秆长度(2,5,8 cm)、秸秆还田量(2 000,4 000,8 000 kg/hm~2)、纯氮施加量(100,140,180 kg/hm~2)及纯多酚施加量(0,40,80 kg/hm~2)4因素3水平进行正交设计,加空白对照共计10个处理。采用JET土壤侵蚀阻力测定仪测定土壤可蚀性和临界剪切力,分析秸秆粉碎还田对土壤侵蚀阻力的影响。结果表明:与对照相比,秸秆粉碎还田后各处理土壤临界剪切力均有所增大,但差异不显著(P0.05),氮肥量对土壤临界剪切力影响显著,随氮肥量增加土壤临界剪切力先增加后减小。秸秆长度、还田量、氮肥量和多酚量对土壤可蚀性均具有显著影响,其中秸秆还田量和多酚量的影响贡献率较大,分别为50.61%和23.84%,其影响分别为负效应和正效应。秸秆粉碎还田条件下,土壤可蚀性可用土壤饱和含水量、0.25 mm团聚体含量进行线性拟合(R~2=0.81,P0.01);0.25 mm水稳性团聚体含量与土壤可蚀性能较好地模拟土壤临界剪切力(R~2=0.76,P0.05)。研究结果有助于理解秸秆粉碎还田后土壤侵蚀阻力变化与机制,并可为模型模拟提供数据支持。     

模拟降雨条件下金银花对片麻岩坡地土壤侵蚀的影响

通过室内人工模拟降雨的方法,研究不同树龄金银花对片麻岩坡地土壤侵蚀的影响。结果表明:种植金银花能明显减缓雨水对片麻岩坡地的土壤侵蚀。金银花能延迟初始产流时间,降低径流模数和输沙模数,且随树龄的增加效果明显增加。相比裸地,种植1,3,6年树龄金银花分别延迟产流时间0.71%,23.33%和39.20%;6年金银花降低径流模数和径流深分别达75%和51%,降低输沙模数为23.42%～57.60%。金银花能提高土壤抗侵蚀能力,相比裸地,种植1,3,6年树龄金银花坡面WAS_0.25分别提高11.52%,19.37%和24.35%。在近根区,相比1年树龄金银花根系生物量,种植3,6年金银花依次增加82.67%和191.26%。根系生物量与金银花坡面的总减流率和总减沙率呈极显著正相关,其相关系数(R^2)分别为0.801和0.911。总体上,金银花能够控制片麻岩坡地土壤侵蚀,并在一定程度上提高土壤抗侵蚀能力。     

基于降雨量和降雨时间的月降雨侵蚀力简易算法——以陕北黄土丘陵沟壑区为例

 降雨侵蚀力简易算法是较大尺度应用USLE/RUSLE进行土壤侵蚀评价研究的必要内容。基于降雨量和降雨时间建立月降雨侵蚀力计算模型,并以陕北黄土丘陵沟壑区为例,进行模型的拟合。结果表明:随着自变量中降雨量和降雨时间表示方式的改变,模型的拟合优度表现出明显的差异;对于不同因变量而言,以ΣEI30(或lg(ΣEI30))和以ΣEI10(或lg(ΣEI10))为因变量的模型拟合优度在整体上比较接近甚至相同,而以ΣE60I10(或lg(ΣE60I10))为因变量的模型拟合优度在整体上略低;就尺度效应而言,在时间尺度上,整个汛期的模型拟合优度低于1个月份或多个月份模型的拟合优度,在空间尺度上,区域模型中的拟合优度低于至少1个流域的模型拟合优度;在实际应用中,可以选择以ΣEI30为因变量的月降雨侵蚀力公式对该区域进行土壤侵蚀评价。     

基于RUSLE模型的湟水流域土壤侵蚀时空变化

研究黄河上游土壤侵蚀的时空变化对于维持黄河上游生态系统服务功能、保护黄河上游水塔具有重要意义。以黄河上游典型区域湟水流域为研究区,采用RUSLE模型定量评估了该流域2000—2015年土壤侵蚀的时空变化特征,并分析了有无梯田措施下土壤侵蚀的空间变化,从而量化了梯田建设对防治坡面土壤侵蚀的影响。结果表明:2000—2015年,湟水流域的土壤侵蚀强度整体呈现减小趋势,侵蚀模数由1 183 t/(km~2·a)降低至940 t/(km~2·a),减少幅度为20.54%。不同土地利用类型以及不同坡度下的土壤侵蚀强度均有所降低,其中耕地上的减幅最大为20.58%。15°～20°坡度区间的侵蚀模数减幅最显著,为23.11%。通过有无梯田措施情景模拟发现,湟水流域2015年土壤侵蚀模数由940 t/(km~2·a)降低至有梯田的837 t/(km~2·a),减少11.00%。研究结果可为流域的水土流失防治和生态环境保护提供科学依据。     

我国水蚀区坡耕地土壤分离能力的空间分布与影响因素

我国水蚀区不同区域自然地理环境和土壤理化性质存在巨大差异,可能会引起土壤分离能力(Dc)的差异。然而目前大尺度上(如水蚀区)Dc的空间分布及其影响因素的研究尚未见报道。在水蚀区依据土壤类型和土壤质地不同布设了36个采样点,用扰动土(代表新耕坡耕地)测定其Dc并分析其影响因素。结果表明,水蚀区沙漠风沙土Dc最大,红壤Dc最小,Dc呈强度空间变异。西北黄土高原地区和南方山地丘陵区Dc最大。黏粒和砂粒含量适中的土壤质地Dc最大。水流剪切力与水流功率在模拟Dc方面无显著差异。Dc与粉粒、土壤粒径参数、阳离子交换量和土壤有机质存在显著的负相关关系,与砂粒、中值粒径、平均几何粒径和交换性纳百分比存在显著的正相关关系。水蚀区Dc可用水流剪切力、粉粒、阳离子交换量和土壤有机质很好地模拟(R^2=0.71,NSE=0.71)。     

Investigating soil physical properties and yield response in a grassland field using a dual‐sensor penetrometer and EM38

Precision‐farming applications are mainly based on site‐specific information of soil properties at the field scale. For this purpose, a number of novel sensor techniques have been developed but not intensively tested under different field conditions. This study presents a combined application of a self‐developed dual‐sensor vertical penetrometer (DVP) for measuring volumetric soil water content (VSWC) and cone index (CI), and an EM38 for soil apparent electrical conductivity (EC_a) in a pasture (1.4 ha). To verify the feasibility of the DVP for interpreting the depth‐specific information in the field, not only the soil physical properties and their geographical coordinates were measured, but also geo‐referenced yield data were collected. We found that the yield pattern was quite similar to the soil water‐content pattern of each layer (layer‐1: 5–15 cm; layer‐2: 15–25 cm, layer‐3: 25–35 cm) and EC_a pattern. Using the map‐based comparisons in conjunction with the statistical analyses, the effect of each measured soil physical property (VSWC, CI, and EC_a) on the yield was investigated. The regression between the yield and VSWC at each layer fitted a quadratic equation (R² = 0.515 at 5–15 cm; R² = 0.623, at 15–25 cm; R² = 0.406 at 25–35 cm). The negative correlation between yield and CI at each layer fitted a linear model with R² ≥ 0.510.     

Spatial Estimation of Soil Erosion Risk by Land‐cover Change in the Andes OF Southern Ecuador

Ecuador has the highest deforestation rate in South America, causing large‐scale soil erosion. Inter‐Andean watersheds are especially affected by a rapid increase of the population leading to the conversion of large areas of montane forest into pasture and cropland. In this study, we estimate soil erosion risk in a small mixed land‐use watershed in the southern Andes of Ecuador. Soil loss was estimated at a spatial resolution of 30 m, using the Revised Universal Soil Loss Equation (RUSLE) where the RUSLE factors were estimated on the basis of limited public available data. Land‐cover maps for 1976, 2008 and 2040 were created assuming increasing deforestation rates over the ensuing decades. Greater erosion rates are estimated for succession areas with agricultural cropland and pasture with maximum values of 936 Mg ha⁻¹ y⁻¹, where slopes and precipitation amounts are the greatest. Under natural forest vegetation, the estimated soil erosion rates are negligible (1·5 to 40 Mg ha⁻¹ y⁻¹) even at steep slopes and higher elevations where rainfall amounts and intensities are generally higher. When the entire watershed has undergone substantial deforestation in 2040, erosion values may reach 2,021 Mg ha⁻¹ y⁻¹. Vegetation cover is the most important factor for potential soil erosion. Secondary factors are related to rainfall (R‐factor) and topography (LS factors). Although the spatial predictions of potential soil erosion have only limited meaning for erosion risk, this method provides an important screening tool for land management and assessment of land‐cover change. Copyright © 2013 John Wiley & Sons, Ltd.     

修正的通用土壤流失方程中各因子单位的确定

[目的]明确和规范修正的通用土壤流失方程(RUSLE)中各因子的单位,使得RUSLE在中国具体应用过程中更加科学和便捷。[方法]通过对国内外RUSLE应用实践的总结和对比研究,并分析其科学合理性,找出最为普遍应用的、准确的RUSLE各因子的单位,明确不同单位类型之间的转化系数。[结果]国内RUSLE的应用,大部分是通过各地区建立的各因子统计模型转换成国际制单位系统,最后相乘得到的是以国际制单位表示的土壤侵蚀量,另一部分则是通过相应的各因子统计模型计算得到各个因子以美制单位系统表示的计算结果,最后再乘以224.2将土壤侵蚀量转换为国际制单位。国内主流侵蚀估计中使用的单位焦耳系统,单位面积有两种即km^2和hm^2。土壤流失量A常用的国际制单位为t/hm^2或t/km^2;降雨侵蚀力因子R常用的国际制单位为(MJ·mm)/(hm^2·h·a)或(MJ·mm)/(km^2·h·a);土壤可蚀性因子K的常用国际制单位为(t·hm^2·h)/(hm^2·MJ·mm)或(t·km^2·h)/(km^2·MJ·mm)。不同地区建立的计算方法通过相应的转换系数转换成国际制单位。最后,R和K因子的单位系统的一致性是RUSLE应用的关键步骤。[结论]R和K因子通过相应的单位转换系数转换为国际制单位以及两者的单位一致性是土壤侵蚀评估的重要基础。     

Soil and nutrient losses due to root crops harvesting: a case study from southwestern Iran

Although root crops are widely cultivated in Iran, little is known about soil loss due to crop harvesting (SLCH). We assessed the annual exported soil, soil organic matter (SOM) and nutrients from 47 farms under root crops in southwestern Iran. Soil losses for garlic, potato, sugar beet, radish and beetroot were estimated as 6.27, 2.52, 2.26, 4.10 and 6.95, Mg ha^?1, respectively, which on average was of the order of soil losses by water erosion in the watershed basins of Iran. Total N, P₂O₅ and K₂O losses were estimated as 36.61, 1.10 and 31.50 kg ha^?1 and their costs as 18.24, 0.74 and 19.93 USAlthough root crops are widely cultivated in Iran, little is known about soil loss due to crop harvesting (SLCH). We assessed the annual exported soil, soil organic matter (SOM) and nutrients from 47 farms under root crops in southwestern Iran. Soil losses for garlic, potato, sugar beet, radish and beetroot were estimated as 6.27, 2.52, 2.26, 4.10 and 6.95, Mg ha^?1, respectively, which on average was of the order of soil losses by water erosion in the watershed basins of Iran. Total N, P₂O₅ and K₂O losses were estimated as 36.61, 1.10 and 31.50 kg ha^?1 and their costs as 18.24, 0.74 and 19.93 US$ ha^?1, respectively. For the whole country, total soil, N, P₂O₅, K₂O and SOM losses for garlic, potato and sugar beet were estimated as 731.7 × 10³, 836, 27, 476 and 14.5 × 10³ Mg, respectively (radish and beetroot were excluded due to no reliable data on their planted areas). Correlation analysis showed no significant relationship between soil properties and SLCH (except soil moisture content for radish and clay content for beetroot). The findings indicated that the exported soil, SOM and nutrients were at such levels that SLCH should be considered in soil erosion studies.     

黄土丘陵区典型沟道侵蚀诱发的CO2通量估算

以黄土丘陵区典型侵蚀沟道为对象,基于沟道剖面有机碳和¹³⁷Cs数据,采用碳库重分布模型估算了典型沟道侵蚀诱发的CO₂通量,并通过检验模型预测效率、解析影响因子,提出了模型校正的思路。结果表明:(1)在长期侵蚀作用下,沟道侵蚀区和沉积区均表现为剧烈的侵蚀效应,侵蚀区侵蚀速率介于30.99~46.44 mm/a,沉积区侵蚀速率介于34.20~37.88 mm/a,沉积区土壤流失速率略小于侵蚀区;(2)碳库重分布模型估算显示,侵蚀区与沉积区均表现为较强烈的碳源效应,侵蚀区CO₂通量介于18.41~28.44 g/(m²·a),沉积区CO₂通量介于22.19~29.25 g/(m²·a);(3)侵蚀部位、土壤容重、有机碳含量、侵蚀量、沟道平均坡度、植被地上部与地下部生物量共同解释了碳库重分布模型预测效率的变异特征(R²=0.68),其中侵蚀部位、侵蚀量、有机碳含量、土壤容重、植被地下部对预测效率有强驱动效应;(4)引入被忽略的植被新输入有机碳库参数,有望校正碳库重分布模型,提升模型预测效率。该研究结果明确了碳库重分布模型在沟道侵蚀区相比沉积区有更高的CO₂通量预测效率,为进一步提高模型的预测精度,可以考虑引入植被输入有机碳库作为校正参数。     

基于不同风蚀模型的区域土壤风蚀变化及影响因素研究——以内蒙古自治区为例

基于遥感数据、气象数据等,利用RWEQ模型和风蚀预报模型对内蒙古自治区2000—2017年土壤风蚀进行评估并分析其驱动因素。结果表明：（1） RWEQ模型（R²=0.85,P<0.01）和风蚀预报模型（R²=0.43,P<0.01）的预测值与¹³⁷Cs示踪技术风蚀的值具有较好的相关性,其中RWEQ模型预测精度更好。（2）时间上,RWEQ和风蚀预报模型模拟的结果均表明2000—2017年内蒙古自治区土壤风蚀呈下降的趋势,下降趋势分别为0.73,1.18 t/（hm²·a）,2个模型模拟的土壤风蚀模数在2011年均达到最低值。空间上,2000—2017年,2个模型的模拟结果均表明内蒙古自治区土壤风蚀以微度和轻度侵蚀为主,其中剧烈侵蚀在整个研究区的占比较小（RWEQ 1.79%,风蚀预报模型5.45%）,主要分布于北方风沙区的西南部。趋势上,89.74%（RWEQ）和72.05%（风蚀预报模型）的土壤风蚀模数呈下降趋势,其中显著降低的区域主要分布于北方风沙区的巴丹吉林沙漠和乌兰布和沙漠。（3）大风天数对土壤风蚀具有显著影响,随着大风天数的增多,土壤风蚀呈显著上升趋势,植被覆盖度和降水量的增长在一定程度上可抑制土壤风蚀的进程。     

Is Nitrous Oxide Reduction Primarily Regulated by the Fungi-to-Bacteria Abundance Ratio in Fertilized Soils?

The production of nitrous oxide (N₂O) is a widespread trait in fungi and is of interest because denitrifying fungi lack the N₂O reductase gene (nosZ) that regulates N₂O reduction to nitrogen gas (N₂). The adaptive ability of soil fungi is better than that of bacteria in acidic soils. We investigated the N₂O reduction potential, described by the N₂O product ratio (R_N2O), N₂O/(N₂O+N₂), in soils of different types of fields under crop cultivation with different fertilizer inputs and a bare fallow field with no fertilization as a control. The fungi-to-bacteria abundance ratio (R_F/B) was negatively correlated (P < 0.01) with the natural pH of the soil; however, the high value of R_F/B measured in vineyards was due to the large inputs of manure. When the denitrification potential was measured at natural pH values of soils, R_N2O was negatively correlated (P < 0.01) with soil pH. When the denitrification potential was measured after short-term modifications of soil pH, however, no significant correlation was found between R_N2O and the modified pH. Based on stepwise multiple regression analysis, soil pH and residual nitrate (NO₃^-) were the key factors regulating N₂O reduction in soils at natural pH values (R²=0.88, P < 0.001), whereas the key factor was the soil residual NO₃^- alone (R²=0.83, P < 0.001) when the soil pH was modified. When the effect of the soil chemical properties was weakened, a high R_F/B value had the potential (P < 0.01) to affect N₂O reduction; however, the role of fungi was offset by the presence of denitrifying bacteria. These results provide evidence that compared to the indirect effects of R_F/B, the direct effects of the soil chemical properties have a greater effect on N₂O reduction in fertilized soils.     

Prediction of soil and water conservation structure impacts on runoff and erosion processes using SWAT model in the northern Ethiopian highlands

Purpose

Land degradation due to soil erosion is a serious threat to the highlands of Ethiopia. Various soil and water conservation (SWC) strategies have been in use to tackle soil erosion. However, the effectiveness of SWC measures on runoff dynamics and sediment load in terms of their medium- and short-term effects has not been sufficiently studied.

Materials and methods

A study was conducted in 2011 to 2015 in the Gumara-Maksegnit watershed to study the impacts of SWC structures on runoff and soil erosion processes using the soil and water analysis tool (SWAT) model. The study was conducted in two adjacent watersheds where in one of the watersheds, SWC structures were constructed (treated watershed (TW)) in 2011, while the other watershed was a reference watershed without SWC structures (untreated watershed (UW)). For both watersheds, separate SWAT and SWAT-CUP (SWAT calibration and uncertainty procedure) projects were set up for daily runoff and sediment yield. The SWAT-CUP program was applied to optimize the parameters of the SWAT using daily observed runoff and sediment yield data.

Results and discussion

The runoff simulations indicated that SWAT can reproduce the hydrological regime for both watersheds. The daily runoff calibration (2011–2013) results for the TW and UW showed good correlation between the predicted and the observed data (R ²?=?0.78 for the TW and R ²?=?0.77 for the UW). The validation (2014–2015) results also showed good correlation with R ² values of 0.72 and 0.70 for the TW and UW, respectively. However, sediment yield calibration and validation results showed modest correlation between the predicted and observed sediment yields with R ² values of 0.65 and 0.69 for the TW and UW for the calibration and R ² values of 0.55 and 0.65 for the TW and UW for the validation, respectively.

Conclusions

The model results indicated that SWC structures considerably reduced soil loss by as much as 25–38% in the TW. The study demonstrated that SWAT performed well for both watersheds and can be a potential instrument for upscaling and assessing the impact of SWC structures on sediment loads in the highlands of Ethiopia.

     

典型黑土小流域侵蚀强度时空变化特征——以海伦市光荣小流域为例

为了系统反映黑土区典型水蚀小流域土壤侵蚀特征，基于连续的Landsat TM/OLI影像计算NDVI,并基于优化后的土壤和土地利用参数，结合实地调查，利用中国土壤流失方程(CSLE)、基于单位流量加权侵蚀沉积模型(USPED)分别模拟了海伦市光荣小流域2000—2021年间平均土壤侵蚀模数和侵蚀沉积分布格局，并通过融雪侵蚀模型(SHI)模拟了2017年春季融雪侵蚀空间分布，综合分析了小流域的侵蚀格局成因。结果表明：2000—2021年间CSLE模拟发现，小流域平均土壤侵蚀模数为5.57 t/(hm²·a),平均土壤流失量为0.55 mm/a,坡上侵蚀量较少[0～2 t/(hm²·a)],为微度侵蚀，坡中处于极强烈侵蚀和剧烈侵蚀等级，侵蚀贡献主要来自坡度2°～6°区域，占总侵蚀量的79.56%;USPED模拟发现，小流域78.11%面积发生侵蚀或沉积，其中侵蚀面积占流域面积24.89%,平均侵蚀模数为9.40 t/(hm²·a),且多集中在坡中和坡底侵蚀沟位置；沉积面积占流域面积的53.22%,平均沉积模数为-4.39 t...