Assessing geopedological soil mapping approach by statistical and geostatistical methods: A case study in the Borujen region,Central Iran

Geopedology, using geomorphologic and supervised classification bases, has been proposed as a soil surveying method. It undertakes a systematic approach to map soilscapes. This approach tries to reduce the budget of accomplishing soil surveys as well as increasing the purity of mapping units. But to what extent it has been succeeded is the question. The main objective of this research was to validate the geopedological mapping methodology by statistical and geostatistical methods in the Borujen region, Central Iran. After a primary interpretation of the study area on air photos (1:20 000 scale), 94 pedons were excavated on a 125 m square sampling grid in the sample area for geostatistical studies. To achieve the statistical aims, a geomorphic unit which encompassed the maximum surface of the sample area (and also the study area) was selected and the biggest delineation of this unit with 19 pedons was considered. The credibility of generalizing the results of the geopedological approach for the studied unit was tested by comparison with 15 pedons in a similar unit outside the sample area, named the validation area. Properties of the soils, including percentage of clay, rock fragments (2–75 mm) and total carbonates in the soil family control section, percentage of organic matter in the A horizon and its thickness, were selected for statistical and geostatistical analyses. Univariate and multivariate statistical analyses obtained from the units in the sample and the validation areas, showed that the means of soil variables were similar. A high difference between A horizon thickness variances in the sample area and the validation area affected the significance of the variation test in the univariate and multivariate results. Our study demonstrated that, when comparing the same factors from sample and validation areas, the spatial distribution and spatial dependency level of soil attributes were different. Therefore, although the geopedological approach tries to distinguish more homogeneous soil mapping units, it is still not able to fully define and represent the real variability of soil properties and show the chaotic behavior or nature of the soils. We recommend further investigations on different techniques of stratifying the landscape in order to better analyze and understand the soil-forming processes and the nature of soil variability and to improve sampling and mapping approaches. We suggest that the additional determination of the phases of landforms and phases of soil series will improve mapping in the future.     

结合多等级代表性采样和模糊隶属度的区域土壤制图方法

High-resolution and detailed regional soil spatial distribution information is increasingly needed for ecological modeling and land resource management. For areas with no point data, regional soil mapping includes two steps: soil sampling and soil mapping. Because sampling over a large area is costly, efficient sampling strategies are required. A multi-grade representative sampling strategy, which designs a small number of representative samples with different representative grades to depict soil spatial variations at different scales,could be a potentially efficient sampling strategy for regional soil mapping. Additionally, a suitable soil mapping approach is needed to map regional soil variations based on a small number of samples. In this study, the multi-grade representative sampling strategy was applied and a fuzzy membership-weighted soil mapping approach was developed to map soil sand percentage and soil organic carbon(SOC) at 0–20 and 20–40 cm depths in a study area of 5 900 km2 in Anhui Province of China. First, geographical sub-areas were delineated using a parent lithology data layer. Next, fuzzy c-means clustering was applied to two climate and four terrain variables in each stratum. The clustering results(environmental cluster chains) were used to locate representative samples. Evaluations based on an independent validation sample set showed that the addition of samples with lower representativeness generally led to a decrease of root mean square error(RMSE). The declining rates of RMSE with the addition of samples slowed down for 20–40 cm depth, but fluctuated for 0–20 cm depth. The predicted SOC maps based on the representative samples exhibited higher accuracy, especially for soil depth 20–40 cm, as compared to those based on legacy soil data. Multi-grade representative sampling could be an effective sampling strategy at a regional scale. This sampling strategy, combined with the fuzzy membership-based mapping approach, could be an optional effective framework for regional soil property mapping. A more detailed and accurate soil parent material map and the addition of environmental variables representing human activities would improve mapping accuracy.     

Distribution of large soil invertebrates as related to soil parameters

The study of three types of forest soils has shown virtually no reliable relationships between the distribution of large soil invertebrates and the soil parameters (the stone content, pH, litter thickness, etc.) when the sample area has a size of 76 cm². However, an increase in the size of the observation plots by two to four times (depending on the particular soil type) makes it possible to find statistically significant coefficients of correlation between the studied parameters. Thus, the size of the sample area influences our assessment of the relationships between the abundance of large invertebrates and the soil parameters. In each of the studied types of forest soils, the heterogeneity of the soil structure is manifested at different scales. A correct forecast of the effect of the factors of the soil on the population of large invertebrates depends on the spatial distribution of these factors.     

Occurrence and hydrological effects of water repellency in different soil and land use types in Mexican volcanic highlands

Little is known on the hydrological behavior of the volcanic ash soils, which are characterized by extremely high porosities and hydraulic conductivities. In this study the occurrence and hydrological effects of water repellency were investigated at a plot scale for different types of land use and volcanic soils in Mexican volcanic highlands from Michoacan, Mexico: [1] fir, pine and oak mixed forest soils developed from lavas, [2] soils developed from volcanic ashes and pyroclastic sediments under sparse fir, pine and oak forest and shrubland, [3] pine and oak forested soils developed from lavas and pyroclastic sediments, and [4] bare soils on recent ash sediments in plain surfaces. Soil water repellency was assessed using the water drop penetration time test and rainfall simulations were performed on circular plots (50 cm in diameter) during 30 min and at an intensity of 90 mm h^− 1 in order to study the hydrological response of each area. The return period for storms with a similar intensity in the area is 10 years. The shape and depth of the wetting front after simulated rainfall was also analyzed. Soil water repellency showed a high variability among the different studied zones. Organic matter content, soil texture and acidity were the most important factors for developing hydrophobicity. A wide range of soil water repellency classes (hydrophilic to severely water-repellent soils) has been found in soils under dense fir, pine and oak mixed forests or shrubland, while inexistent or slight water repellency has been observed in soils under sparse forest or at bare ash-covered areas. At a plot scale, marked differences in the hydrological behavior of the studied land use and soil zones were observed after the rainfall simulations. Soil water repellency contributes to fast ponding and runoff generation during the first stages of rainstorms. Runoff was enhanced in water-repellent forested soils (average runoff coefficients between 15.7 and 19.9%), in contrast to hydrophilic or slightly water-repellent soils, where runoff rates were lower (between 1.0 and 11.7%). Shallow and irregular wetting fronts were observed at water-repellent zones, reducing the soil water storage capacity. The implications of soil water repellency in soil hydrology and erosion risk in the area shed light on the soil hydrology of the studied ecosystems, and can contribute to develop better management policies.     

基于支持向量机的典型冻土区土壤制图研究

基于青藏高原大片连续多年冻土分布的东部边缘,青海省兴海县温泉地区的野外调查数据,通过对研究区遥感数据的分析,开展了土壤制图方法的探讨。以成土因素学说和土壤-景观模型理论为基础,筛选土壤分类潜在变量,在不同的变量组合下运用支持向量机(SVM)的方法建立土壤-景观模型,对整个研究区进行预测性分类。为了更好地检验该方法的有效性,采用五折交叉方式进行结果的验证。并通过对比不同变量组合的交叉验证结果和分布模拟结果图,确定了适合典型冻土区土壤分类的环境变量组合,以较少的样本知识较好地预测该区土壤类型的空间分布。     

Experience in digital mapping of soil cover patterns

Methodological problems of large-scale soil mapping with the use of digital mapping technologies are discussed. Two variants of obtaining the maps of soil combinations for a test polygon (30 km²) in the area of soddy-podzolic soils with 996 studied soil pits are described. In the first variant, the initial state of soils at studied points was characterized by the taxonomic name of the soil (at the level of soil subtypes); the probability of occurrence of different subtypes within operation cells of the digital map was estimated, and the most probable soil subtypes were assigned to them. This approach was tested for the first time. In the second variant, the initial state of soils at studied points was described with the help of the grades of ecologically meaningful features of soil morphology; the degree of soil gleying and the degree of soil erosion or aggradation were indicated. The integral digital map represented the areas of different agroecological groups of soil combinations. The maps obtained with the help of these two approaches show a satisfactory agreement with the maps of soil cover patterns compiled by traditional methods earlier.     

Proximal sensor-enhanced soil mapping in complex soil-landscape areas of Brazil

Portable X-ray fluorescence (pXRF) spectrometry and magnetic susceptibility (MS) via magnetometer have been increasingly used with terrain variables for digital soil mapping. However, this methodology is still emerging in many countries with tropical soils. The objective of this study was to use proximal soil sensor data associated with terrain variables at varying spatial resolutions to predict soil classes using the Random Forest (RF) algorithm. The study was conducted on a 316-ha area featuring highly variable soil classes and complex soil-landscape relationships in Minas Gerais State, Brazil. The overall accuracy and Kappa index were evaluated using soils that were classified at 118 sites, with 90 being used for modeling and 28 for validation. Digital elevation models (DEMs) were created at 5-, 10-, 20-, and 30-m resolutions using contour lines from two sources. The resulting DEMs were processed to generate 12 terrain variables. Total Fe, Ti, and SiO₂ contents were obtained using pXRF, with MS determined via a magnetometer. Soil class prediction was performed using the RF algorithm. The quality of the soil maps improved when using only the five most important covariates and combining proximal sensor data with terrain variables at different spatial resolutions. The finest spatial resolution did not always provide the most accurate maps. The high soil complexity in the area prevented highly accurate predictions. The most important variables influencing the soil mapping were MS, Fe, and Ti. Proximal sensor data associated with terrain information were successfully used to map Brazilian soils at variable spatial resolutions.     

Automated updating of medium-scale soil maps

An approach towards an automated updating of medium-scale soil maps via imitation of traditional mapping technologies is suggested. It is based on formulation of the rules of mapping in the form of classification trees for separating different soil cover patterns and on creation of the maps of soil-forming factors with the use of satellite data. Algorithms for mapping alluvial soils (Fluvisols), eroded (abraded), and anthropogenically transformed soils are presented. This approach was tested for the southern (Trans-Oka) part of Moscow oblast. The model for an automated soil mapping was realized using ILWIS software. The polygons of alluvial soils were mapped with a higher accuracy via the automated separation of floodplains according to the digital terrain model. The total area of alluvial soils shown on the medium-scale soil map decreased from 373 to 340 km². Calculations of slope angles according to digital terrain models allowed us to localize soil cover patterns with participation of eroded soils with a higher accuracy; their area decreased insignificantly: from 791 to 781 km². Anthropogenically transformed soils of building areas were mapped for the territory of Moscow oblast on the basis of satellite data for the first time. Their areas were delineated taking into account land use types and comprised 551 km², i.e., 15.4% of the total area (3570 km²) of the Trans-Oka part of Moscow oblast.     

Bodengesellschaften von geomorphen Einheiten unter Berücksichtigung des Gefügestils im Stormarner Jungmoränengebiet (Brandenburger Stadium) in Nordwestdeutschland

Soil associations of different geomorpholocical units of a younger‐moraine area in Schleswig‐Holstein (NW Germany) considering matter fluxes As result of a detailed mapping work, the soil association of different geomorpholocical units of a younger‐moraine area (“Stormarner Jungmoränengebiet”) in Schleswig‐Holstein (NW Germany) is analyzed taking into account soil development in vertical and horizontal direction. The consequences for classification of soil types and soil associations are discussed. We distinguished between different patterns of matter fluxes (unilateral coupling, mutual coupling, no coupling of soils). By morphometric analysis of the relief, five geomorpholocical units were distinguished: till‐plains with dead‐ice kettles (I), tongue‐like basin with moraine slopes (II), terminal‐push moraine (III), moraine slopes with gutter valley (IV), und terminal‐push moraine valley with steep slopes (V). In the examination area with its intense agricultural land use, the regular sequence of erosion and accumulation of soils is a typical consequence of unilateral water‐flow direction. Thus, the truncated Stagnic Luvisols/Anthrosols association is dominating. We suggest to classify the truncated Luvisol with a Bt horizon exposed directly to the surface at the level of soil subtypes in the German soil‐classification system. Additionally soils in depressions such as Calcic Gleysols, Histosols and “subhydric soils”, which are influenced by solute and solid‐matter input, are frequently encountered. Within the till‐plains, a compensation of the relief by (historical) soil erosion took place, recognizable by the high percentage of Anthrosols (20 %). Therefore, no recent lateral transport of solid material can be found. The steep moraine slopes partly already show Regosols, thus indicating a high erosion potential (erosion rate for geomorphical unit IV: 13 t ha^–1 y^–1). In the depressions intersected with small streams, the afflux caused by mills led to an additional peat development.     

Combined use of compost and wood scraps to increase carbon stock and improve soil quality in intensive farming systems

Intensive agricultural systems negatively affect soil quality principally because of a reduction in soil organic matter (OM). Sustainable practices providing organic amendments could be useful to maintain or increase OM content in agricultural soils, preserving and improving soil fertility. In this study, biomass with a large C:N ratio was applied to intensively farmed agricultural soils to maximize the increase of soil OM and hence chemical and biochemical fertility. In particular, 30 and 60 t ha^?1 of two mixtures of compost and scraps from poplar pruning, A1 and A2, with different C:N ratios (15 and 25, respectively), were applied to soils of two farms (F1 and F2) in a Mediterranean area (southern Italy) on an annual basis for two consecutive years. An effective, long‐lasting increase of soil OM, on average of 60 and 55% in F1 and F2 soils, respectively, was reached at the end of the experiment. As well as a progressive increase in the C:N ratio, total N and available P also increased with organic amendments, with positive effects on soil microbial activity as demonstrated by the enhancement of the seven studied enzymatic activities. Principal component analysis demonstrated different responses to various organic amendments between F1 and F2 soils because of their geopedological diversity. The results indicate that the C:N ratio of the mixture is an important factor, but what is the best rate of addition to use is still not obvious. The use of a smaller amount (30 t ha^?1) of the A1 mixture (10:1 compost:wood) appears, in these types of soils, to be the most suitable strategy to produce significant benefits.     

Comparing mapping approaches at subcatchment scale in northern Thailand with emphasis on the Maximum Likelihood approach

This study compares different soil mapping approaches in three different petrographic areas in order to test their suitability for regional mapping in northern Thailand. Sampling was based on transects or grid-based randomization. Maps were created based on expert knowledge (eye fitting) or using Classification Tree (CART algorithm) or the Maximum Likelihood approach. In addition, local knowledge-based-soil maps were created. Validation was performed using soil reference maps and independent sampling points. The mapping approaches based on transects and grid-based randomization showed a very high correspondence with the respective reference soil map and a very high degree of matching with independent sampling points. Both methods are best suited for sub-watershed scale. Mapping larger areas is difficult due to the inaccessibility of the mountainous regions. The soil maps based on Maximum Likelihood showed a high correlation with the respective reference soil maps and the individual sampling points. Maximum Likelihood maps and Classification Tree maps showed similar levels of accuracy. The Maximum Likelihood approach is applicable to upscaling procedures; therefore, a calibration area is required which represents the target area. Local knowledge-based-soil mapping is very cheap and fast, but is restricted to village areas where classification often varies even within a village. Despite this, local knowledge is very useful for soil reconnaissance surveys, as well as to acquire an overview of the major distribution of soils and their properties. Upscaling of local knowledge due to its inherent inconsistency is not realistic.     

河南省多级地貌特征及与土壤多样性的关系

从土壤多样性向地多样性发展符合土壤地理学的研究趋势,选择河南省作为研究区,将地貌这一主要的地学要素加入到土壤多样性的研究中,并用改进的仙农熵公式对多级地貌空间分布多样性及其与土壤多样性的相关性进行探讨。首先,对河南省1︰175万地貌类型图进行矢量化得到地貌类型等级系统;然后,对地貌和土壤的构成组分多样性和2种不同分类体系的分支率进行计算并分析其特征;最后,在3 km×3 km网格尺度下分析地貌和土壤多样性间的相关性。研究表明:河南省共有3个一级地貌,12个二级地貌和37个三级地貌;随着土壤和地貌分类的等级细化,其分类个数和构成组分多样性值均呈上升趋势,即土壤和地貌所有分类单元在数量构成上的均匀程度越来越高;两种分类系统中,土壤分类较地貌分类有更详细的分类体系,且分支率有较大范围的变化;河南省一级地貌、二级地貌和三级地貌的空间分布多样性值和面积值均最大的类型分别是流水地貌、冲积平原和泛滥平坦地,是不同级别的优势地貌类型;一级地貌类型与土类、亚类和土属多样性间存在紧密的相关关系,且以流水地貌与土壤多样性间的相关性最强。     

基于水量平衡的红壤丘岗坡地利用结构拟合

以集雨区水量平衡为基础,从分析坡地水文过程入手,以坡地不同生态系统雨水分配、降雨过程地表径流产量、径流过程的土壤及养分流失量为参数,以生产灌溉对集雨的要求、坡地不同生态系统对雨水侵蚀的承载力、坡地雨水运移过程对环境和区域洪涝灾害的影响为约束条件,拟合出红壤丘岗坡地农林复合生态系统构建适宜的土地利用结构:人工林占30%,人工草地占15%,果药茶园占30%,耕地占20%,自然保护区占5%。该用地比例(结构)既满足于地貌单元(集雨区)生态系统利用坡地集雨维持系统水循环平衡的要求,也满足于坡地农林复合生态系统的可持续性保护的要求。     

Zonal,provincial, lithological,and geomorphic features of soil salinization in the Southern federal okrug of Russia

The relationships between soil salinization and the zonal and provincial bioclimatic conditions, the lithological composition of the sediments, and the geomorphic features of the territory have been analyzed for the Southern federal okrug of Russia. It is shown that the lithological and geomorphic conditions (relief, salinity of parent materials, degree of drainage, and the depth of saline groundwater) play an important role in the distribution of salt-affected soils against the background of the more general regularities specified by the climate. The participation of salt-affected soils in the soil cover of the Southern federal okrug increases in the eastward direction from the forest-steppe zone to the semidesert zone in agreement with an increase in the aridity and continentality of the climate. The chemical composition of soil salts also changes: the sulfate and soda-sulfate types predominate in the forest-steppe zone; the sulfate type or the sulfate type with the participation of soda, in the steppe zone; the sulfate-chloride type, in the dry steppe zone; and the chloride type, in the semidesert zone. The lithological and geomorphic conditions within the particular zones and provinces affect the distribution pattern of the salt-affected soils and the degree and chemistry of the soil salinization. The areas of salt-affected soils were calculated with the use of a digital version of the Map of Salt-Affected Soils of Russia (1: 2.5 M scale) with due account for the participation of these soils in the soil cover of the particular delineations and the data on the depth of the upper boundary of the salt-bearing horizons, the degree and chemistry of the soil salinization, and the area of solonetzes and solonetzic soils.     

对全国第二次土壤普查中土类、亚类划分及其调查制图的辨析

按照中国发生分类对新采集的68个北京市山区的土壤剖面进行了分类命名,并与剖面点所在土壤普查图上的分类名称进行比较,结果是只有18个剖面的分类名称一致。造成分类名称不一致的原因:1发生分类以区域典型土壤剖面分类命名,而区域内很多土壤不同于典型土壤剖面;2发生分类往往以现代生物气候带为主要分类标准命名区域土壤,而不是根据土壤性质;3分类不一致的最大原因可能是制图精度不够。研究认为,土壤分类必须依据土壤性质本身,而不是土壤形成因素;采取野外单土壤性质调查制图,室内叠加单土壤性质图形成多属性图斑,根据分类系统对它们进行综合分类,以提高分类制图精度。     

土系划分方法研究——以江苏省新沂样区为例

作为土壤系统分类的基层分类单元,土系的划分必须经过实地调查,重视控制层段和特征土层的设立,并选择合适的分异特性作为分类指标。本文选择样区内不同景观单元中的10个土壤剖面,根据中国土壤系统分类的要求,探讨了样区内土壤诊断层、诊断特性及其在中国土壤系统分类中的归属;并在有关土系认识的基础上,探讨了土系划分的原则、依据和具体划分方法,确立了研究区土壤所具有的特征土层,依据①特征土层的种类、排列、厚度,②土壤质地和③土壤有机质含量这三类指标,把样区土壤划分为10个土系。     

Mapping contemporary magnetic mineral concentrations in peat soils using fine-resolution digital terrain data

Small-scale spatial variability in the concentration of magnetic minerals in peat soils has been explained by differences in the deposition and interception of magnetic minerals at the soil surface and the retention of magnetic minerals within the soil. Each of these processes is controlled by topographic conditions. Recent advances in the field of digital terrain analysis and the availability of fine-resolution digital elevation models means that the relationship between the concentration of magnetic minerals in peat soils and topography can be explored using quantitative methods. Alport Moor is an ombrotrophic peat moorland in the Peak District National Park, UK. 24 peat cores were collected from Alport Moor covering an area of 0.1 km². Each core was analysed for mass specific magnetic susceptibility. Three topographic attributes (topographic wetness index, difference from mean elevation and elevation as a percentage of elevation range) were extracted from a high resolution LiDAR digital elevation model of Alport Moor. Stepwise multiple regression analyses show that topographic wetness index and difference from mean elevation are excellent predictors of variation in peak magnetic susceptibility and total magnetic susceptibility inventories for peat soils of this upland area. The results demonstrate that the contemporary concentration of magnetic minerals in the peat soils of Alport Moor is controlled by micro- and local-scale variations in water table position. The results also suggest that the contemporary level of magnetic minerals in the peat soils of Alport Moor is controlled by the retention of such particles in the soil environment. Differences in the deposition and interception of magnetic minerals play a secondary role in controlling magnetic mineral concentrations. Spatial maps of magnetic susceptibility reveal that peat soils adjacent to gully edges at Alport Moor have the highest concentration of magnetic minerals. The mapping approach used in this study could be applied to other peatland environments.     

Effect of spatial scale of soil data on estimates of soil ecosystem services: Case study in 100 km2 area in France

Over the last decade, the ecosystem services (ESs) framework has been increasingly used to support mapping and assessment studies for sustainable land management purposes. Previous analysis of practical applications has revealed the significance of the spatial scale at which input data are obtained. This issue is particularly problematic with soil data that are often unavailable or available only at coarse scales or resolutions in various part of the world. In this context, four soil-based ecosystem services, namely biomass provision, water provision, global climate regulation, and water quality regulation, are assessed using three conventional soil maps at the 1:1,000,000, 1:250,000 and 1:50,000 scales. The resulting individual and joint ES maps are then compared to examine the effects of changing the spatial scale of soil data on the ES levels and spatial patterns. ES levels are finally aggregated to landforms, land use, or administrative levels in order to try to identify the determinants of the sensitivity of ES levels to change in the scale of input soil data. Whereas the three soil maps turn out to be equally useful whenever ESs levels averaged over the whole 100 km² territory are needed, the maps at the 1:1,000,000 and 1:250,000 induced biases in the assessment of ESs levels over spatial units smaller than 100 and 10 km², respectively. The simplification of the diversity and spatial distribution of soils at the two coarsest scales indeed resulted in local differences in ES levels ranging from several 10 to several 100%. Identification of the optimal representation of soil diversity and distribution to obtain a reliable representation of ESs spatial distribution is not straightforward. The ESs sensitivity to scale effect is indeed context-specific, variable among individual ESs, and not directly or simply linked with the soil typological diversity represented in soil maps. Forested and natural lands in the study area appear particularly sensitive to soil data scales as they occupy marginal soils showing very specific ESs signatures.     

The ConMap approach for terrain-based digital soil mapping

We present a new digital terrain analysis framework for digital soil mapping, referred to as contextual elevation mapping (ConMap). In contrast to common regression approaches based on features from digital terrain analysis, ConMap is not based on standard terrain attributes, but on elevation differences from the centre pixel to each pixel in circular neighbourhoods only. These differences are used as features in random forest regressions. We applied and validated the framework by predicting topsoil silt content in a loess region of 1150 km² in Rhineland-Palatinate and Hesse, Germany. Three hundred and forty-two samples and a 20-m resolution digital elevation model were used for this illustration and validation. We compared ConMap with standard and multi-scale terrain analysis approaches as well as with ordinary kriging interpolations. Cross-validation root mean square error ( RMSE) decreased from 16.1 when the standard digital terrain analysis was used to 11.2 when ConMap was used. This corresponds to an increase in variance explained ( R ²) from 15 to 61%. Even though ordinary kriging out-performed standard terrain analysis as well, the variance explained was 6% smaller compared with that using ConMap. The results show that the geomorphic settings in the study area must have induced the spatial trend, which can be accounted for by ConMap over different scales. We conclude that ConMap shows great potential for digital soil mapping studies.     

Soil reflectance as a generic tool for assessing infiltration rate induced by structural crust for heterogeneous soils

Raindrop energy disintegrates soil aggregates and rearranges soil particles to form a structural crust on the upper soil layer. The structural crust affects the physical properties of the soil, which can be observed by significant colour changes on the soil surface. Spectral differences observed in the structural crust are caused by rearrangement of the soil surface texture, mainly an increase in the clay fraction. Previous studies conducted on crusted soils using reflectance spectroscopy were limited to a certain soil type or area and seemed to be strongly dependent on the small range of soil types. In the current study, the influence of raindrop energy on the NIR‐SWIR spectral reflectance (1200–2400 nm) of heterogeneous soils was evaluated and used in combination with partial least squares (PLS) regression to construct a model that correlates the infiltration rate (IR) with its reflectance. Four soils from Israel and three soils from the USA were studied to provide a single data set. A relatively small root mean square error of cross‐validation (RMSECV) of 15.2% was found. A ratio of prediction to deviation (RPD) value of 1.98 indicates a promising generic model. Additionally, PLS models were run on different combinations of soil types (RPD values ranging between 2.4 and 3.2). For all models, whether all soils were run in one cross‐validation data set, or run for different combinations of soils, the best assessment of IR was achieved when using reduced wavelength range (selected wavelengths based on Martens’ significance test selection). These results allowed us to conclude that a generic approach aimed at assessing the structural crust for a variety of soils is feasible. A generic model using the suggested spectral approach has the potential to provide NIR‐SWIR spectral soil IR predictions with either a local or global data base of soils worldwide and may contribute to improved protection of crusted soils from erosion or water loss by runoff.