International Soil and Water Conservation Research最新文献

Utilizing geodetectors to identify conditioning factors for gully erosion risk in the black soil region of northeast China 利用地质探测器识别中国东北黑土区沟壑侵蚀风险的条件因素

IF 7.3 1区农林科学 Q1 ENVIRONMENTAL SCIENCES

International Soil and Water Conservation Research

Pub Date : 2024-07-31 DOI: 10.1016/j.iswcr.2024.07.004

Donghao Huang , Xinrui Zhao , Zhe Yin , Wei Qin

In the black soil region of Northeast China, the issue of gully erosion persists as a significant threat, resulting in extensive damage to farmland, severe degradation of the black soil, and decreased productivity. It is therefore of utmost importance to accurately identify areas that are susceptible to gully erosion to effectively prevent and control its negative impact. This study tried to utilize geographical detectors (geodetectors) as a means to identify the factors that contribute to the distribution of gullies and assess the risk of gully erosion (GER) in five catchments within the region, with areas ranging from approximately 80 km²–200 km². By employing the geodetectors method, fourteen geo-environmental factors were analyzed, including topographic attributes (such as aspect, catchment area, convergence index, elevation, plan curvature, profile curvature, slope length, slope, stream power index, and topographic wetness index), channel network distance, vegetation index (NDVI and EVI), as well as land use/land cover (LULC). The modeling of GER was conducted using the random forest algorithm (RFA). Out of the fourteen examined geo-environmental factors, only a subset, comprising less than or equal to 50%, demonstrated a significant (p < 0.05) influence on the spatial distribution of gullies. These selected factors were sufficient in assessing GER, with LULC (mean q-value = 0.270) and elevation (mean q-value = 0.113) identified as the two most important factors. Furthermore, the RFA exhibited satisfactory performance across all catchments, achieving AUC values ranging from 0.712 to 0.933 (mean = 0.863) in predicting GER. Overall, the catchment areas were classified into high, moderate, low, and very low-risk levels, representing 9.67%–15.95%, 19.28%–26.08%, 24.59%–30.55%, and 30.54%–39.08% of the total area, respectively. Importantly, a significant positive linear relationship (r² = 0.722, p < 0.05) was observed between the proportion of cropland area and the occurrence of high-level GER. Although the primary risk levels were categorized as low and very low, the proportion of high-risk levels exceeded the existing gully coverage (0.34%–3.69%). These findings highlight the substantial potential for gully erosion and underscore the necessity for intensified efforts in the prevention and control of gully erosion within the black soil region of Northeast China.

在中国东北黑土区，沟壑水土流失问题一直是一个重大威胁，造成农田大面积破坏、黑土地严重退化和生产力下降。因此，准确识别沟蚀易发区，有效预防和控制沟蚀的负面影响至关重要。本研究试图利用地理探测器（geodetectors）来确定导致沟壑分布的因素，并评估该地区五个集水区的沟壑侵蚀风险（GER），这些集水区的面积约为 80 平方公里至 200 平方公里。通过采用地质探测器方法，分析了 14 个地质环境因素，包括地形属性（如纵向、流域面积、汇聚指数、海拔高度、平面曲率、剖面曲率、坡长、坡度、溪流动力指数和地形湿润指数）、沟道网络距离、植被指数（NDVI 和 EVI）以及土地利用/土地覆盖（LULC）。采用随机森林算法（RFA）对 GER 进行建模。在所研究的 14 个地理环境因子中，只有一个子集（小于或等于 50%）对沟壑的空间分布有显著影响（p < 0.05）。这些选定因素足以评估 GER，其中 LULC（平均 q 值 = 0.270）和海拔（平均 q 值 = 0.113）被认为是两个最重要的因素。此外，RFA 在所有流域都表现出令人满意的性能，在预测 GER 方面的 AUC 值介于 0.712 到 0.933 之间（平均值 = 0.863）。总体而言，集水区被划分为高、中、低和极低风险等级，分别占总面积的 9.67%-15.95%、19.28%-26.08%、24.59%-30.55% 和 30.54%-39.08%。重要的是，在耕地面积比例与高级别 GER 发生率之间观察到了明显的正线性关系（r2 = 0.722，p <0.05）。虽然主要风险等级被划分为低和极低，但高风险等级的比例超过了现有的沟壑覆盖率（0.34%-3.69%）。这些发现凸显了沟蚀的巨大潜力，并强调了在中国东北黑土区加强沟蚀防治工作的必要性。

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引用次数: 0

Automated quantification of contouring as support practice for improved soil erosion estimation considering ridges 自动量化等高线，作为改进山脊土壤侵蚀估算的辅助方法

IF 7.3 1区农林科学 Q1 ENVIRONMENTAL SCIENCES

International Soil and Water Conservation Research

Pub Date : 2024-07-20 DOI: 10.1016/j.iswcr.2024.07.001

Dominik Scholand, Britta Schmalz

Using soil conservation practices such as contouring are able to reduce soil loss on arable land parcels. In the empirical model of the Universal Soil Loss Equation (USLE), these measures are taken into account by the P-factor for support practice management. In the context of application, there is usually a lack of sufficient data or suitable methodology to accurately determine the P-factor within a plot-specific analysis. In this study, we demonstrate the effort and benefit of deriving an individual P-factor for each land parcel within a typical application scale. For this purpose, we apply the Fast Line Detector algorithm to open remote sensing data of Google Earth from May 2016 in German low mountain range. The algorithm detects lines from tire tracks and seed rows, which allows to determine an individual main cultivation direction for each land parcel. The success rate was 94.9 % for 2495 land parcels with 26 different crops. The results show a major time advantage for the automated method when considering a large number of parcels. Subsequently, we used the detailed information obtained to calculate the P-factor under regional German conditions using the German standard DIN 19708 and, secondly, an approach based on revised USLE. It is apparent that the current German standard cannot be applied with the necessary level of detail for 78.1 % of all land parcels in this low mountain range study due to unsuitable equations and validity ranges for slope steepness and length and a non-consideration of ridges and off-grade contouring and therefore needs to be revised to avoid being restricted in its application.

采用等高耕作等水土保持措施可以减少耕地的土壤流失。在通用土壤流失方程（USLE）的经验模型中，这些措施都被考虑在支持实践管理的 P 因子中。在应用过程中，通常缺乏足够的数据或合适的方法来准确确定具体地块分析中的 P 系数。在本研究中，我们展示了在典型应用范围内为每个地块推导单独 P 因子所需的工作和益处。为此，我们将快速线条检测算法应用于 2016 年 5 月谷歌地球在德国低山地区的开放式遥感数据。该算法从轮胎痕迹和种子行中检测出线条，从而确定每个地块的主要耕作方向。在 26 种不同作物的 2495 块土地上，成功率为 94.9%。结果表明，在考虑大量地块时，自动方法在时间上有很大优势。随后，我们利用获得的详细信息，采用德国 DIN 19708 标准计算了德国地区条件下的 P 系数，其次还采用了基于修订的 USLE 方法。很明显，由于坡度和坡长的计算公式和有效范围不合适，且未考虑山脊和偏离地面的等高线，现行德国标准无法以必要的详细程度适用于本次低山脉研究中 78.1% 的地块，因此需要对其进行修订，以避免在应用中受到限制。

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引用次数: 0

Three-dimensional spatiotemporal variation of soil organic carbon and its influencing factors at the basin scale 流域尺度上土壤有机碳的三维时空变化及其影响因素

IF 7.3 1区农林科学 Q1 ENVIRONMENTAL SCIENCES

International Soil and Water Conservation Research

Pub Date : 2024-05-16 DOI: 10.1016/j.iswcr.2024.05.001

The variability of soil organic carbon (SOC) extends across three dimensions. However, quantitative analyses of the factors influencing spatiotemporal variations of SOC in various soil depth is scarce. This study leverages legacy data from two soil surveys conducted in the Dongting Lake Basin during the 1980s and the 2010s, employing Random Forest models to generate three-dimensional SOC maps. Through correlation analysis and permutation importance, we identified the primary factors driving temporal and spatial changes of SOC. The results showed that in the 2010s, SOC storage up to a depth of 1 m in the Dongting Lake Basin was approximately 2.95 Pg, increasing at an average rate of 0.0047 Pg C per year since the 1980s. Regions with higher average SOC contents were predominantly found in the western, southern, and eastern parts of the basin, despite significant losses over the 30-year period. In contrast, the central and northern areas, which initially had lower SOC contents in the 1980s, exhibited increases by the 2010s. Soil depth was the most influential predictor of SOC patterns in both the 1980s and 2010s. Meanwhile, relief and organism factors were primarily responsible for spatial variations in SOC, with the influence of organism factors diminishing by the 2010s. The temporal variations of SOC were chiefly attributed to changes in soil conservation practices, extreme precipitation events, and grain production. Consequently, it is imperative to prioritize ecological restoration and conservation tillage practices to mitigate the impacts of extreme weather conditions and safeguard food security.

土壤有机碳（SOC）的变化跨越三个维度。然而，对不同土壤深度 SOC 时空变化影响因素的定量分析却很少。本研究利用 20 世纪 80 年代和 2010 年代在洞庭湖流域开展的两次土壤调查的遗留数据，采用随机森林模型生成三维 SOC 地图。通过相关性分析和置换重要性分析，我们确定了驱动 SOC 时空变化的主要因素。结果表明，2010 年代洞庭湖流域 1 米深以内的 SOC 储量约为 2.95 Pg，自 20 世纪 80 年代以来平均每年增加 0.0047 Pg C。平均 SOC 含量较高的区域主要分布在盆地的西部、南部和东部，尽管在 30 年间损失巨大。与此相反，20 世纪 80 年代 SOC 含量较低的中部和北部地区，到 2010 年代出现了上升。在 20 世纪 80 年代和 2010 年代，土壤深度是对 SOC 模式影响最大的预测因素。同时，地形和生物因素是 SOC 空间变化的主要原因，到 2010 年代，生物因素的影响逐渐减弱。SOC 的时间变化主要归因于土壤保护措施、极端降水事件和粮食生产的变化。因此，必须优先考虑生态恢复和保护性耕作实践，以减轻极端天气条件的影响，保障粮食安全。

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引用次数: 0

Can hydraulic-energy-indices be effectively used to describe the saturated hydraulic conductivity? 水能指数能否有效用于描述饱和导水性？

IF 7.3 1区农林科学 Q1 ENVIRONMENTAL SCIENCES

International Soil and Water Conservation Research

Pub Date : 2024-05-15 DOI: 10.1016/j.iswcr.2024.05.002

The saturated hydraulic conductivity (K_s) and water retention curve (SWRC) parameters are important properties for simulating soil hydrological processes and characterizing soil conservation around the world. Therefore, K_s and SWRC are related with the soil physical quality (SPQ) and several SPQ indices can be derived from SWRC, such as the pore size distribution, relative field capacity, plant available water, drainable porosity, and soil hydraulic-energy indices (SHEI). It is well known that the soil structure can be assessed by using SHEI, but a possible physical relationship between K_s and SHEI was not examined yet. Therefore, the objective of this study was to investigate the behavior of K_s as function of SHEI for several soil textural classes. If this relationship be proved, then SHEI might be applied to improve the K_s prediction by PTF models. In this work, a data set of 395 measured SWRC's were fitted to the vG equation to obtain the SHEI to verify whether they are statistically correlated and physically dependent on K_s. The resulting parametric and non-parametric correlation results were split up according to six textural classes. The significant influence of K_s on at least one of the absolute SHEI (A_a or WR_a) was verified on the numerical scale when all textures were grouped and on numerical and pF scales for clayey and silty textures. K_s showed significant impact on A_a and WR_a indices in four textural classes. Furthermore, K_s had influence on the sum A_a + WR_a denoted in pF scale for five of the six textural classes, with a significant linear correlation in the clayey texture when log (A_a + WR_a) was applied. The significant and high correlation of K_s on the ratios WR_a/AWC and A_a/φ_D was also observed in four of the six classes, and therefore the use of these indices is recommended for the development of PTFs for K_s prediction.

饱和导水系数（Ks）和保水曲线（SWRC）参数是模拟土壤水文过程和描述世界各地土壤保持状况的重要参数。因此，Ks 和 SWRC 与土壤物理质量（SPQ）有关，而且可以根据 SWRC 得出多种 SPQ 指数，如孔径分布、相对田间容重、植物可用水量、可排水孔隙度和土壤水能指数（SHEI）。众所周知，使用 SHEI 可以评估土壤结构，但尚未研究 Ks 与 SHEI 之间可能存在的物理关系。因此，本研究的目的是调查 Ks 与几种土壤质地等级的 SHEI 之间的函数关系。如果这种关系得到证实，那么 SHEI 就有可能用于改进 PTF 模型对 Ks 的预测。在这项工作中，对 395 个测量的 SWRC 数据集进行了 vG 方程拟合，以获得 SHEI，从而验证它们是否与 Ks 存在统计相关性和物理依赖性。得出的参数和非参数相关结果按六个质地类别进行了划分。在对所有纹理进行分组时，Ks 对至少一种绝对 SHEI（Aa 或 WRa）的重要影响在数值尺度上得到了验证，在粘土和淤泥纹理的数值和 pF 尺度上也得到了验证。在四个质地类别中，Ks 对 Aa 和 WRa 指数有明显影响。此外，Ks 对六个质地类别中五个类别的 pF 表示的 Aa + WRa 总和也有影响，在粘土质地中，当采用对数（Aa + WRa）时，Ks 具有显著的线性相关关系。Ks 与 WRa/AWC 和 Aa/φD 的比率也在六个等级中的四个等级中呈现出明显的高度相关性，因此建议使用这些指数来开发用于 Ks 预测的 PTF。

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引用次数: 0

National variability in soil organic carbon stock predictions: Impact of bulk density pedotransfer functions 土壤有机碳储量预测的全国差异：体积密度 Pedotransfer 函数的影响

IF 7.3 1区农林科学 Q1 ENVIRONMENTAL SCIENCES

International Soil and Water Conservation Research

Pub Date : 2024-05-03 DOI: 10.1016/j.iswcr.2024.04.002

Accurate soil organic carbon storage (SOCS) estimation is crucial for sustaining ecosystem health and mitigating climate change impacts. This study investigated the accuracy and variability of SOCS predictions, focusing on the role of pedotransfer functions (PTFs) in estimating soil bulk density (BD). Utilizing a comprehensive dataset from the Korean Rural Development Administration (RDA database), which includes 516 soil horizons, we evaluated 36 widely-used BD PTFs, well-established formulas that estimate BD by considering soil properties, including soil organic carbon (SOC), soil organic matter (OM), sand, gravel, silt, and clay. These PTFs demonstrated varying levels of precision, with root mean squared errors (RMSE) ranging from 0.177 to 0.377 Mg m⁻³ and coefficients of determination (R²) from 0.176 to 0.658; hence, the PTFs have been classified into excellent, moderate, and poor-performing groups for predicting BD. Further, a novel PTF based on an exponential function of SOC was developed, showing superior predictive power (R² = 0.73) compared to existing PTFs, using an independent validation dataset. Our findings reveal significant differences in SOCS predictions and observations among the PTFs, with a p-value <0.05. The highest concentrations of SOCS were noted in forest soils, considerably above the national average, highlighting the importance of tailored soil management practices to enhance carbon sequestration. These findings are crucial for refining PTF precision to improve the accuracy of national SOCS estimates, supporting effective land management and climate change mitigation strategies.

准确估算土壤有机碳储量（SOCS）对于维持生态系统健康和减轻气候变化影响至关重要。本研究调查了土壤有机碳储量预测的准确性和可变性，重点关注 pedotransfer 函数（PTF）在估算土壤容重（BD）中的作用。利用韩国农村发展局（RDA 数据库）包含 516 个土壤层的综合数据集，我们评估了 36 个广泛使用的容重 PTF，这些成熟的公式通过考虑土壤特性（包括土壤有机碳 (SOC)、土壤有机质 (OM)、砂、砾石、粉土和粘土）来估算容重。这些 PTF 的精确度各不相同，均方根误差 (RMSE) 从 0.177 到 0.377 Mg m-3 不等，判定系数 (R2) 从 0.176 到 0.658 不等；因此，这些 PTF 在预测 BD 方面的表现被分为优、中、差三类。此外，我们还开发了一种基于 SOC 指数函数的新型 PTF，与现有的 PTF 相比，该 PTF 在使用独立验证数据集时显示出更高的预测能力（R2 = 0.73）。我们的研究结果表明，SOCS 的预测结果与 PTF 之间的观测结果存在明显差异，P 值为 0.05。森林土壤中的 SOCS 浓度最高，大大高于全国平均水平，这凸显了有针对性的土壤管理措施对提高碳固存的重要性。这些发现对于改进 PTF 精确度以提高国家 SOCS 估算的准确性、支持有效的土地管理和气候变化减缓战略至关重要。

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引用次数: 0

Divergent behaviour of soil nutrients imprinted by different land management practices in the Three Gorges Reservoir Area, China 中国三峡库区不同土地管理方式下土壤养分的差异表现

IF 7.3 1区农林科学 Q1 ENVIRONMENTAL SCIENCES

International Soil and Water Conservation Research

Pub Date : 2024-04-01 DOI: 10.1016/j.iswcr.2024.03.003

Soil nutrients are essentially regulated by land management practices via modulating biotic element input and metabolism. The Three Gorges Reservoir Area in China was dominated by a farming landscape, but land management has become diversified over recent decades. How these restorative management practices may have affected soil nutrients is not completely understood. In this study, a space-time substitution approach was applied to evaluate soil nutrients and their stoichiometric changes in response to post-farming land management practices. Soil samples (0–10 cm, 10–20 cm, and 20–40 cm) were collected from present-day croplands, cypress plantations, eucalyptus plantations, abandoned croplands, and citrus plantations. Soil organic matter, soil organic carbon, total nitrogen, alkaline hydrolyzed nitrogen, total phosphorus, and available phosphorus were determined. The results showed that soil organic matter and total nitrogen in abandoned croplands, cypress plantations, eucalyptus plantations and citrus plantations were increased by 186% and 190%, 184% and 107%, 45% and 33%, 45% and 54%, respectively, in comparison with those of present-day croplands. Soil nutrients except for total phosphorus decreased with soil depth by exclusion of tillage mixing. Comprehensive soil nutrient index showed that abandoned croplands (0.90) and cypress plantations (0.72) exhibited favorable nutrient recovery capacity. Soil C:P and N:P ratios increased in abandoned croplands, cypress plantations, and eucalyptus plantations. Phosphorus may become a limiting factor for plant growth with prolonged recovery in abandoned croplands, cypress plantations, and eucalyptus plantations, while soil organic matter and total nitrogen deficiencies were exacerbated in citrus plantations and present-day croplands. Therefore, cropland abandonment and reforestation (particularly cypress trees plantation) are recommended options for restoring soil nutrients in the Three Gorges Reservoir Area.

土壤养分基本上是由土地管理方法通过调节生物元素输入和新陈代谢来调节的。中国三峡库区曾以农耕景观为主，但近几十年来，土地管理变得多样化。这些恢复性管理措施如何影响土壤养分尚不完全清楚。本研究采用时空置换法评估土壤养分及其化学计量变化对耕作后土地管理措施的响应。土壤样本（0-10 厘米、10-20 厘米和 20-40 厘米）采集自现今的耕地、柏树种植园、桉树种植园、废弃耕地和柑橘种植园。测定了土壤有机质、土壤有机碳、全氮、碱性水解氮、全磷和可利用磷。结果表明，与现在的耕地相比，废弃耕地、柏树种植园、桉树种植园和柑橘种植园的土壤有机质和全氮分别增加了 186% 和 190%、184% 和 107%、45% 和 33%、45% 和 54%。除总磷外，土壤养分随着耕作深度的增加而减少。土壤养分综合指数显示，废弃耕地（0.90）和柏树种植园（0.72）表现出良好的养分恢复能力。废弃耕地、柏树种植园和桉树种植园的土壤碳：磷和氮：磷比率均有所上升。在废弃的耕地、柏树种植园和桉树种植园中，磷可能会成为植物生长的限制因素，并随着时间的延长而恢复，而在柑橘种植园和现在的耕地中，土壤有机质和全氮的缺乏会加剧。因此，废弃耕地和植树造林（尤其是柏树种植）是恢复三峡库区土壤养分的推荐方案。

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引用次数: 0

Modeling gully initiation by two codeless nonlinear methods: A case study in a small watershed on the Tibetan Plateau 用两种无码非线性方法模拟沟谷的形成：青藏高原小流域案例研究

IF 7.3 1区农林科学 Q1 ENVIRONMENTAL SCIENCES

International Soil and Water Conservation Research

Pub Date : 2024-03-29 DOI: 10.1016/j.iswcr.2024.03.002

Land and soil resources are scarce in the Tibetan Plateau, and the region is facing ecological pressure from climate warming and increasing human activities. As a major ecological problem, gully erosion is destroying land and soil resources on the Tibetan Plateau, but related research is limited, and susceptibility areas and influencing factors are unclear. Machine learning methods are often applied to study gully initiation susceptibility, but they require a programming foundation. Therefore, the Redui watershed on the southern Tibetan Plateau with severe gully erosion was selected to evaluate the susceptibility and influencing factors of gully initiation through 12 influencing factors including topography, human activity, and underlying surface conditions, and all 2310 gully headcut sites. Two non-code nonlinear modeling methods, the categorical Regression (CATREG) and geographical detector (Geodetector) methods, were first used in the spatial modeling of gully initiation susceptibility. The results showed that the gully initiation susceptibility of the hillslope around the alluvial fan was highest. The very high susceptibility areas of the CATREG model and Geodetector model account for 18.2% and 16% of the total, respectively. The main influencing factors of gully initiation were elevation, relief, and soil type recognized by CATREG, and elevation, human footprint, and soil type recognized by Geodetector. Elevation is the primary factor controlling downstream susceptibility in both models. The primary factors in the upper and middle reaches are soil type and relief identified by CATREG. Human footprint, soil type, and distance to road are primary factors in the upper and middle reaches identified by Geodetector. The explanatory power of elevation, elevation-relief interaction, Geodetector model and CATREG model were 39%, 54%, 46.4% and 73.8%, respectively, at extremely significant levels (P < 0.001), which means that the influencing factors were well considered and that the methods have great application potential in the future.

青藏高原的土地和土壤资源稀缺，该地区正面临着气候变暖和人类活动增加所带来的生态压力。作为一个主要的生态问题，沟壑侵蚀正在破坏青藏高原的土地和土壤资源，但相关研究有限，易发区和影响因素不明确。机器学习方法通常被用于研究沟壑的易发性，但需要一定的编程基础。因此，选择了青藏高原南部冲沟侵蚀严重的红堆流域，通过地形地貌、人类活动、地表基础条件等 12 个影响因素和全部 2310 个沟头切迹点，评估了冲沟形成的易感性和影响因素。首先使用了两种非编码非线性建模方法，即分类回归法（CATREG）和地理检测器法（Geodetector），对冲沟形成的敏感性进行了空间建模。结果表明，冲积扇周围山坡的成沟易感性最高。CATREG 模型和 Geodetector 模型的极高易发区分别占总易发区的 18.2% 和 16%。沟谷形成的主要影响因素是 CATREG 识别的海拔、地势和土壤类型，以及 Geodetector 识别的海拔、人类足迹和土壤类型。在这两个模型中，海拔都是控制下游易发性的主要因素。中上游的主要因素是 CATREG 识别的土壤类型和地形。人类足迹、土壤类型和与道路的距离是 Geodetector 确定的上游和中游的主要因素。高程、高程-地形交互作用、Geodetector 模型和 CATREG 模型的解释力分别为 39%、54%、46.4% 和 73.8%，均达到极显著水平（P < 0.001），这说明影响因素考虑周全，这些方法在未来有很大的应用潜力。

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引用次数: 0

Challenges and constraints of conservation agriculture adoption in smallholder farms in sub-Saharan Africa: A review 撒哈拉以南非洲小农农场采用保护性农业的挑战和制约因素：综述

IF 7.3 1区农林科学 Q1 ENVIRONMENTAL SCIENCES

International Soil and Water Conservation Research

Pub Date : 2024-03-20 DOI: 10.1016/j.iswcr.2024.03.001

Common farming practices in sub-Saharan Africa (SSA) such as intensive and repeated tillage, complete crop residue removal, and biomass burning create risks of soil degradation. To reduce these risks, conservation agriculture (CA) uses minimal soil disturbance, crop residue retention, and crop rotation in order to reduce soil erosion, improve soil quality and crop production, and facilitate climate change mitigation and adaptation. Nevertheless, CA adoption in SSA is extremely low. This paper aims to review current practices, challenges, and constraints to the adoption of CA in SSA. Our analyses show that CA is practiced in only about 1.25% of the total cultivated area in SSA, despite two decades of efforts to promote CA adoption among smallholder farmers. Specific difficulties in CA adoption by smallholder farmers in SSA may be attributed to i) lack of locally adaptable CA systems, particularly those integrating the needs of livestock production; ii) lack of adequate crop residues for surface mulch; iii) inconsistent and low crop yields; iv) lack of smallholder CA equipment for direct sowing; v) limited availability, high cost, and inadequate knowledge associated with the use of appropriate fertilizer and herbicides; and vi) lack of CA knowledge and training. Other problems relate to the management of specific soil orders, e.g., CA implementation on steeply sloping land and poorly drained soils such as Vertisols. CA adoption by smallholder farmers is also obstructed by socio-economic factors due to smallholder farmers’ focus on short term yield increases and their lack of access to markets, loans, and education. To facilitate wider adoption by smallholder farmers in SSA, CA approaches should be downscaled to fit the existing tillage tools and the specific agroecological and socio-economic farm settings.

撒哈拉以南非洲地区（SSA）的常见耕作方式，如密集和重复耕作、完全清除作物残留物和焚烧生物质，都会造成土壤退化的风险。为了降低这些风险，保护性农业（CA）采用了尽量减少土壤扰动、保留作物残茬和轮作的方法，以减少土壤侵蚀、提高土壤质量和作物产量，并促进减缓和适应气候变化。然而，撒哈拉以南非洲地区对 CA 的采用率极低。本文旨在回顾撒哈拉以南非洲地区采用 CA 的当前实践、挑战和制约因素。我们的分析表明，尽管二十年来一直在努力促进小农户采用 CA，但在 SSA，CA 的种植面积仅占总种植面积的 1.25%。撒南非洲小农在采用 CA 方面遇到的具体困难可归因于：i) 缺乏适应当地情况的 CA 系统，特别是那些结合畜牧业生产需求的系统；ii) 缺乏足够的作物残茬用于地表覆盖；iii) 作物产量不稳定且较低；iv) 缺乏直接播种的小农 CA 设备；v) 与使用适当肥料和除草剂相关的可用性有限、成本高且知识不足；以及 vi) 缺乏 CA 知识和培训。其他问题与特定土壤的管理有关，例如在陡坡地和排水不良的土壤（如 Vertisols）上实施 CA。小农户采用 CA 还受到社会经济因素的阻碍，因为小农户注重短期增产，缺乏进入市场、获得贷款和接受教育的机会。为促进撒哈拉以南非洲地区的小农更广泛地采用 CA 方法，应缩小规模，以适应现有的耕作工具以及特定的农业生态和社会经济农场环境。

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引用次数: 0

Agroecology-based land use/land cover change detection, prediction and its implications for land degradation: A case study in the Upper Blue Nile Basin 基于农业生态学的土地利用/土地覆被变化检测、预测及其对土地退化的影响：青尼罗河上游盆地案例研究

IF 7.3 1区农林科学 Q1 ENVIRONMENTAL SCIENCES

International Soil and Water Conservation Research

Pub Date : 2024-02-17 DOI: 10.1016/j.iswcr.2024.02.002

This study examined land use/land cover (LULC) changes in Chemoga watershed of the Upper Blue Nile Basin, comprising four distinct agroecological regions: Wet Wurch, Moist Dega, Moist Weyna Dega, and Moist Kolla. We used multi-temporal Landsat images from 1985 to 2020, a hybrid classification method and the Cellular Automata-Markov model to analyze historical and predict future (2020–2060) LULC changes under business-as-usual (BAU) and land conservation (LC) scenarios. Magnitudes and patterns of spaciotemporal LULC changes were analyzed using intensity analysis. Cropland expanded across all agroecologies from 1985 to 2020, with Moist Kolla experiencing the highest increase at the expense of woodland, due the introduction of commercial farming to this hotter, less populated and inaccessible area. Moist Dega exhibited the highest allocation changes within cropland and forest, attributable to farmers’ adoption of rotational land use to rehabilitate extensively degraded cultivated lands. Under the BAU scenario, projections suggest further cropland expansion at expense of woodland in Moist Kolla and built-up areas at the expense of cropland and grassland in Moist Dega. Under the LC scenario, forest cover is expected to increase at the expense of cropland across all agroecologies. The historical and projected BAU LULC change scenario substantially increased soil erosion and reduced ecosystem services. These effects can be minimized if LC scenario is properly implemented. The agroecology-based LULC intensity analysis reveals local drivers of change and associated impacts, providing vital insights for targeted land use planning in this study watershed and other watersheds facing similar challenges.

本研究考察了青尼罗河上游流域 Chemoga 流域的土地利用/土地覆被 (LULC) 变化情况，该流域由四个不同的农业生态区组成：湿润的 Wurch、湿润的 Dega、湿润的 Weyna Dega 和湿润的 Kolla。我们利用 1985 年至 2020 年的多时相大地遥感卫星图像、混合分类方法和细胞自动机-马尔可夫模型分析了历史上的 LULC 变化，并预测了在一切照旧（BAU）和土地保护（LC）情景下未来（2020-2060 年）的 LULC 变化。利用强度分析法分析了 LULC 空间时空变化的幅度和模式。从 1985 年到 2020 年，所有农业生态区域的耕地面积都有所扩大，其中湿润科拉（Moist Kolla）地区的耕地面积增幅最大，但林地面积却减少了，原因是在这一较炎热、人口较少且交通不便的地区引入了商业化耕作。德加湿润地区的耕地和林地分配变化最大，原因是农民采用轮作方式恢复大面积退化的耕地。在 "一切照旧 "情景下，预测结果表明，在 Moist Kolla，耕地面积进一步扩大，但林地面积却减少了；在 Moist Dega，建筑区面积扩大，但耕地和草地面积却减少了。在低碳经济情景下，预计所有农业生态的森林覆盖率都将增加，但耕地面积将减少。历史和预测的 BAU LULC 变化情景大大增加了土壤侵蚀，减少了生态系统服务。如果适当实施低碳方案，这些影响可以降到最低。基于农业生态的 LULC 强度分析揭示了当地的变化驱动因素和相关影响，为本研究流域和其他面临类似挑战的流域进行有针对性的土地利用规划提供了重要见解。

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引用次数: 0

VIS-NIR spectroscopy and environmental factors coupled with PLSR models to predict soil organic carbon and nitrogen 利用 VIS-NIR 光谱和环境因素以及 PLSR 模型预测土壤有机碳和氮

IF 7.3 1区农林科学 Q1 ENVIRONMENTAL SCIENCES

International Soil and Water Conservation Research

Pub Date : 2024-02-14 DOI: 10.1016/j.iswcr.2024.02.001

Soil profile organic carbon (OC) and total nitrogen (TN) are influenced by topographic attributes, and land use. The visible and near-infrared (Vis-NIR) spectroscopy method can be used for the prediction of OC and TN because it is reliable, nondestructive, fast, and cost-effective. VIS-NIR soil spectral and environmental data were combined with the Partial least squares regression (PLSR) model to examine the effect of topography attributes and land use on topsoil and subsoil OC and TN stocks. After this, based on the soil depth, 114 soil samples were collected from 0 to 20 cm (topsoil) and 20–50 cm (subsoil) under three land uses, as well as OC and TN, along with several soil properties including soil particles (sand, silt, clay), pH, and bulk density in both topsoil and subsoil samples were measured. A DEM with a resolution of 30 m was used to derive the topography factors and remote sensing data was used to calculate the vegetation index. Soils (0–50 cm) under orchard land use had the highest stock of SOC (7.4 kg m⁻²) as well as TN (2.4 kg m⁻²). There was a significant increase in the organic matter stock of soils located on the south aspect (8.3 kg m⁻²) compared to soils located on other aspects, particularly on the north aspect (3.9% increase). Soils on the south aspect contain higher soil-water contents and lower temperatures, resulting in a decrease in the decomposition of soil organic matter. A strong positive correlation was demonstrated between topography wetness index (0.57–0.63) and topography TN stocks (0.54–0.66) as well as the highest loading score among terrain attributes, suggesting that topography is the primary factor controlling SOC stocks, particularly subsoil stocks. Additionally, we found that soils on the south-facing aspects (N aspects) had the highest spectra. Additionally, the PLSR, which showed an R² of 0.82, a RMSE of 0.15 %, and a RPD of 0.39 indicated excellent prediction capabilities for the OC content. We concluded that the PLSR model coupled with Vis-NIR spectroscopy is able to predict topsoil and subsoil OC and N content under different aspect slopes.

土壤剖面有机碳（OC）和总氮（TN）受地形属性和土地利用的影响。可见光和近红外（Vis-NIR）光谱法具有可靠、无损、快速和成本效益高的特点，可用于预测有机碳和全氮。将 VIS-NIR 土壤光谱和环境数据与偏最小二乘回归（PLSR）模型相结合，研究了地形属性和土地利用对表土和底土 OC 和 TN 储量的影响。随后，根据土壤深度，采集了三种土地用途下 0 至 20 厘米（表土）和 20 至 50 厘米（底土）的 114 个土壤样本，并测量了表土和底土样本中的 OC 和 TN 以及土壤颗粒（沙、粉土、粘土）、pH 值和容重等多种土壤特性。使用分辨率为 30 米的 DEM 得出地形系数，并使用遥感数据计算植被指数。果园用地土壤（0-50 厘米）中的 SOC（7.4 千克/平方米）和 TN（2.4 千克/平方米）含量最高。南面土壤的有机质储量（8.3 千克/平方米-2）比其他面的土壤明显增加，尤其是北面（增加 3.9%）。南面的土壤含水量较高，温度较低，导致土壤有机物分解减少。地形湿润指数（0.57-0.63）与地形 TN 储量（0.54-0.66）之间存在很强的正相关性，并且在地形属性中负荷分值最高，这表明地形是控制 SOC 储量（尤其是底土储量）的主要因素。此外，我们还发现朝南的土壤（北向）具有最高的光谱。此外，PLSR 的 R2 为 0.82，RMSE 为 0.15 %，RPD 为 0.39，表明其对 OC 含量具有出色的预测能力。我们的结论是，结合可见光-近红外光谱的 PLSR 模型能够预测不同坡度下表土和底土的 OC 和 N 含量。

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引用次数: 0