Regional Soil Maps Research Articles

Estimated stocks of circumpolar permafrost carbon with quantified uncertainty ranges and identified data gaps

Abstract. Soils and other unconsolidated deposits in the northern circumpolar permafrost region store large amounts of soil organic carbon (SOC). This SOC is potentially vulnerable to remobilization following soil warming and permafrost thaw, but SOC stock estimates were poorly constrained and quantitative error estimates were lacking. This study presents revised estimates of permafrost SOC stocks, including quantitative uncertainty estimates, in the 0–3 m depth range in soils as well as for sediments deeper than 3 m in deltaic deposits of major rivers and in the Yedoma region of Siberia and Alaska. Revised estimates are based on significantly larger databases compared to previous studies. Despite this there is evidence of significant remaining regional data gaps. Estimates remain particularly poorly constrained for soils in the High Arctic region and physiographic regions with thin sedimentary overburden (mountains, highlands and plateaus) as well as for deposits below 3 m depth in deltas and the Yedoma region. While some components of the revised SOC stocks are similar in magnitude to those previously reported for this region, there are substantial differences in other components, including the fraction of perennially frozen SOC. Upscaled based on regional soil maps, estimated permafrost region SOC stocks are 217 ± 12 and 472 ± 27 Pg for the 0–0.3 and 0–1 m soil depths, respectively (±95% confidence intervals). Storage of SOC in 0–3 m of soils is estimated to 1035 ± 150 Pg. Of this, 34 ± 16 Pg C is stored in poorly developed soils of the High Arctic. Based on generalized calculations, storage of SOC below 3 m of surface soils in deltaic alluvium of major Arctic rivers is estimated as 91 ± 52 Pg. In the Yedoma region, estimated SOC stocks below 3 m depth are 181 ± 54 Pg, of which 74 ± 20 Pg is stored in intact Yedoma (late Pleistocene ice- and organic-rich silty sediments) with the remainder in refrozen thermokarst deposits. Total estimated SOC storage for the permafrost region is ∼1300 Pg with an uncertainty range of ∼1100 to 1500 Pg. Of this, ∼500 Pg is in non-permafrost soils, seasonally thawed in the active layer or in deeper taliks, while ∼800 Pg is perennially frozen. This represents a substantial ∼300 Pg lowering of the estimated perennially frozen SOC stock compared to previous estimates.

Putting regional digital soil mapping into practice in Tropical Northern Australia

Tropical Northern Australia is a vast region dominated by extensive cattle grazing. Australia is seeking opportunities to intensify land use in this region through irrigation. We describe a digital soil mapping (DSM) approach for the Flinders and Gilbert catchments (combined area, 155,000km2) in north Queensland to supply soil property (i.e. target variable) maps for an eventual crop-specific irrigation suitability assessment.We applied a statistically-based survey design to identify new soil sampling sites. This data was merged with legacy soil data to produce a combined dataset of 1951 soil sites used in our DSM approach to map 16 soil target variables. Our mapping relied on the RuleFit3 analytical toolset and environmental correlation employing 13 predictors from terrain analysis, mapping and remote sensing. We present prediction and evaluation for three categories of target variables, namely: numeric, binary and categorical using the examples of surface pH (H2O) (numeric), rocky/non-rocky (binary) and permeability (categorical).Prediction quality was evaluated using internal cross-validation, independent validation, and non-parametric bootstrapping. Under internal cross-validation the models achieved R-squared of 0.49 for surface pH (H2O) (numerical), 76% classification accuracy for rocky/non-rocky (binary) and 56% classification accuracy for soil permeability (categorical). Under independent validation the target variables achieved a R-squared of 0.67 for surface pH (H2O), and accuracy of 93% for rocky/non-rocky accuracy of 63% for soil permeability. Non-parametric bootstrapping conducted on the surface pH (H2O) estimation showed the most reliable predictions to be in the pH range of 6–7.Despite the practical pressures imposed on the project (i.e. short project duration, and study area remoteness, size and difficult access), our DSM approach delivered the soil data within required specifications for the crop-specific irrigation suitability assessment. The approach gives a working framework of other soil mapping exercises sharing similar practical (i.e. environmental, logistical, data) constraints.

Shifting carbon pools along a plant cover gradient in woody encroached savannas of central Argentina

Woody plant encroachment is a widespread process of land cover change driven by a combination of local land use practices and regional to global environmental changes. Increases in woody plant cover alter the distribution of carbon in the ecosystem and can affect water and nutrient cycling. Although semiarid rangelands comprise almost half of the global land surface, our understanding on the effects of woody plant encroachment on carbon stocks in these ecosystems is uncertain – studies have found both net C gains and losses. We measured, for the first time in South American semiarid savannas, ecosystem C stocks along a gradient of woody plant density across 30,000km2 of the Caldenal in central Argentina. We characterized changes in C stocks in live biomass (woody and herbaceous, above- and belowground), litter, and soil organic carbon (to 1.5m depth) pools along a woody plant cover gradient (0–94%). We found a significant increase in ecosystem C stocks with increasing woody cover, with mean values of 4.5, 8.4, 12.4, and 16.5kgCm−2 for grasslands, shrublands, open and closed forests, respectively. Using dendrochronological data we estimated the average C accrual rate to be 104gCm−2yr−1 at the ecosystem (plant+soil) level. Woody plant cover and soil silt content were the two primary factors accounting for the variability of ecosystem C. We developed simple regression models that reliably predict soil, tree and ecosystem C stocks from basic field measurements of woody plant cover and soil silt content. These models could prove to be valuable tools for broad scale estimation if linked to regional soil maps and remotely sensed data, allowing for precise and spatially explicit estimation of C stocks and change at regional scales.

Measurements of riverbed hydraulic conductivity in a semi-arid lowland river system (Murray–Darling Basin, Australia)

Riverbed hydraulic conductivity (Kr) was measured along one river reach in four tributaries of the Murray–Darling Basin (MDB) in south-eastern Australia. Two techniques were trialled: in-river falling-head tests in high Kr sediments, and laboratory evaporation tests on intact riverbed cores for low Kr sediments. In-river falling-head tests were conducted using two types of permeameter: a steel-base permeameter or a stand-pipe permeameter. Kr was found to range from 10–10 to 10–3 m s–1, corresponding to a range in riverbed sediment textures from clay to silty gravels, respectively. Although the within-reach variability in Kr was also large, in general the river reaches could be divided in two groups, those with a low Kr (<10–8 m s–1) or a high Kr (>10–5 m s–1). The low Kr reach (Billabong Creek) was a clay-lined bed, whereas the others had silty sand or silty gravel beds. Thus, regional-scale assessments of Kr in the MDB could be made using a stratified sampling process in which reaches would be first classified into low or high Kr classes, and then Kr measurements made in a subsample of low and high Kr reaches. This would be an improvement over the current practice whereby riverbed Kr is estimated either from regional soil maps or through the calibration of groundwater models.

Estimating carbon stocks at a regional level using soil information and easily accessible auxiliary variables

One of the most important challenges of digital soil mapping is the development of methods that allow the characterisation of large areas with a high-resolution. Surface soils, forming the largest pool of terrestrial organic carbon, may be able to sequester atmospheric carbon and thus mitigate climate change. However, this remains controversial, largely due to insufficient information on SOC stocks worldwide. One reason for this is the generally limited number of available data points, especially when large areas are considered, while another reason lies on the accuracy of interpolation techniques used for SOC mapping. The study was performed in Laos, a 230,566 km 2 area mostly forested and with steep slopes, and where soil data from 2806 pits is available. Our objective was to estimate SOC stocks to a depth of 1 m over the whole country while improving regional digital soil mapping (RDSM). SOC mapping by using purely spatial approaches of ordinary kriging (OK), inverse distance weighting (IDW) and regularized spline with tension (RST) was compared with the use of additional information on relief, climate and soils through co-kriging (OCK). The generation and validation data sets were composed of 2665 and 141 data points respectively. Overall, OCK using a multiple correlation with elevation above sea level, compound topographic index, mean slope gradient, average annual rainfall, and soil clay content ( R 2 = 0.42; P level < 0.001) as covariate, yielded the most accurate predictions (19.7 kg C m − 2 with standard error of ± 3.2 kg C m − 2 ; and 4.54 ± 0.74 billion tons of SOC for Laos). The pure interpolation techniques were less accurate with 4.51 ± 1.02 billion tons of SOC for OK and 4.88 ± 0.94 billion tons of SOC for RST. Besides providing nationwide estimates of SOC stocks these results indicate that using collectively soil punctual information on SOC stocks and their inter-relationships with controlling factors which are easy to gather might be an efficient way to improve RDSM.

Derivation of Soil Line Influence on Two-Band Vegetation Indices and Vegetation Isolines

This paper introduces derivations of soil line influences on two-band vegetation indices (VIs) and vegetation isolines in the red and near infra-red reflectance space. Soil line variations are described as changes in the soil line parameters (slope and offset) and the red reflectance of the soil surface. A general form of a VI model equation written as a ratio of two linear functions (e.g., NDVI and SAVI) was assumed. It was found that relative VI variations can be approximated by a linear combination of the three soil parameters. The derived expressions imply the possibility of estimating and correcting for soil-induced bias errors in VIs and their derived biophysical parameters, caused by the assumption of a general soil line, through the use of external data sources such as regional soil maps.

Drought deaths in Eucalyptus globulus (Labill.) plantations in relation to soils, geomorphology and climate

The occurrence of tree deaths in young, 3 to 6 year old Eucalyptus globulus plantations established on farmland in south-western Australia was found to be strongly related to factors indicative of poor soil water storage capacity. Seven years after planting tree survival was significantly less on soils 2 m deep (22% vs 70%). This is due to the limited ability of some soils to store a sufficient proportion of the annual rainfall within the root-zone to meet the plant water demand in a region with a recurrent annual summer drought. There are practical difficulties in routinely surveying soils to depths in excess of 2 m over broad areas, to predict the likelihood of tree death. On the granitic basement rocks of south-west Western Australia, the occurrence of ferricrete gravels provides a useful surrogate indicator for the presence of deeper soils. In this region the distribution of soil depth and soil fertility has a geomorphic basis, being related to previous patterns of deep weathering and regolith stripping. Soils have developed on various horizons of deeply weathered profiles, formed from granites and gneisses. These materials have been stripped to a variable extent by erosion, leading to a range of soil depths. The original weathered profiles, which correspond to the soils with ferricrete gravels, comprise the deepest soil/regolith materials (~30-50 m deep); whereas along drainage lines the regolith has been completely stripped, the soils are shallow and plantations are most susceptible to drought. Knowledge of the relationship between soil depth and plantation performance allows regional indications of drought risk to be developed from regional soil mapping and the production of more efficient sampling designs for site assessment.

History of geological mapping of the Holocene Rhine-Meuse delta, the Netherlands

AbstractA brief overview is given of the history of geological mapping of the Holocene Rhine-Meuse delta. The first accurate map of the delta, based on field observations, was made by Vink (1926). The geological map of the Netherlands, scale 1 : 50,000, made by the ‘Geologische Stichting’ (1927 – 1938) under the supervision of P. Tesch totally neglected Vink’s work, and was a step backwards with regard to the mapping of the Holocene delta. Between 1940 and 1965, the Wageningen group of soil scientists produced detailed regional soil maps, that had a strong ‘geogenetic’ component. In the 1960’s a revolutionary ‘profile type legend’ was introduced by the Netherlands’ Geological Survey. This allowed to map not only the outcropping sediments, but the whole Holocene succession, which gave more insight into the geological history. Over the past 30 years, the Rhine-Meuse delta has been studied extensively by students of physical geography at Utrecht University. More than 250,000 borehole descriptions, 1500 14C dates and over 36,000 archeological artifacts with associated ages (collected by the National Service for Archaeological Heritage) have accumulated, resulting in the largest database of a delta in the world. The production of detailed maps has been crucial to the solution of many scientific problems. The use of GIS has greatly enhanced geological and geomorphological mapping, and subsequently, understanding of the evolution of the Holocene Rhine-Meuse delta. A new detailed digital elevation map of the Netherlands, based on very accurate laser-altimetry data, will enable us to map larger areas in greater detail, with greater accuracy, and in a much shorter period of time.

EDAPHIC CHARACTERISTICS OF OLIVE-TREE AREAS IN THE TRÁ-OS-MONTES REGION (PORTUGAL): A MAP-BASED APPROACH

In the Tras-os-Montes Region (Northeastern Portugal), olive tree plantations cover an area of more than 70 thousand ha (near the 6 % of the regional territory), mostly planted and cultivated under traditional non-mechanised cultural systems. It is fully recognised that the olive sector contributes significantly to the regional agroeconomy, as well as to the conservation of certain typical landscapes. The purposes of this study were (i) to draw a general picture of the olive-tree plantations spatial distribution in the Tras-os-Montes Region and (ii) to identify the main soil characteristics and land qualities of areas where olive-trees are the dominant land use. Information provided by regional soil, land use and land suitability maps (1:100 000) was selected, interpreted and treated in order to achieve those objectives. Due to the small scale of maps, results have only a reconnaissance level of detail. However, they allow conclusions on the main soil/land constraints of olivetree cultivation in the region. Development of olive-tree plantations and improvement of actual management techniques have to cope with the identified constraints. For that, research contributions are of primary importance, mainly on the fields of mechanisation, soil and water conservation and soil fertility.

A regional scale soil mapping approach using integrated AVHRR and DEM data

There is an increasing need for reasonably accurate small-scale soil databases. The compilation of a continental or global-scale soil database requires a lot of spatially and thematically accurate soil data. The aim of this study was to test a method for small-scale soil mapping in Italy using Advanced Very High Resolution Radiometer (AVHRR) and digital elevation data. This method was employed in an earlier study in Hungary for a much smaller area and a significantly different soil-forming environment. An integrated, 45-layer AVHRR-terrain database was used for the study, including a digital elevation model (DEM), slope, curvature, aspect, potential drainage density, and the five bands of AVHRR data for eight different dates. The data were processed using the Discriminant Analysis Feature Extraction (DAFE) function, which is based on a canonical analysis procedure. Two types of images (basic and transformed) were classified using the maximum likelihood classifier. Two training sets were chosen that have identical geographic coverage, but differ in the level of soil classification. One set was based on the soil units (SU) of the FAO-revised legend, while the other set represented major soil groupings (MSG). The best 10, 15, 20, 25, 30, 35, 40 and 45 layers were selected using the Bhattachryya feature selection method and were then classified. The results of the different sets were compared. The performance of the purely AVHRR and purely terrain-data-based images, respectively, were also interpreted. The results indicate that the terrain descriptors alone are not sufficient for soil classification. However, the feature selection algorithms always selected the DEM and its derivatives among the first ones, highlighting their importance for soil-landscape characterization. When using AVHRR data alone, test class performances of 49.8 percent (MSG) and 48.6 percent (SU) were achieved. Integration of terrain data into the AVHRR database produced relatively small improvements (4.6 and 2.8 percent). The best test class performances were achieved when all available channels were used for the classification, namely 51.4 for the FAO's SUs and 54.4 for the MSGs on the basic image, and 51.7 and 54.4 respectively on the DAFE-transformed images. The most informative AVHRR bands were found to be from the spring period (April-May), while the most abundant bands were the visible-red (band 1) and bands 3 and 4.

Use of combined digital elevation model and satellite radiometric data for regional soil mapping

Previous reports demonstrated that data from air- and spaceborne sensors are appropriate for delineation of soil patterns. Also, many attempts have been made to use digital elevation model (DEM) for deriving soil information. However, little is known about the potential use of low spatial resolution satellite and digital elevation data in small-scale soil mapping. A case study was conducted to assess the use of integrated terrain and Advanced Very High Resolution Radiometer (AVHRR) databases for small-scale soil pattern delineation. The main objective was to test the effect of the addition of terrain descriptor data to the AVHRR data set on the classification results. Two database were used for the study. The first one was purely AVHRR data and contained the five basic AVHRR channels and the normalized difference vegetation index (NDVI) of five different dates, while in the second database the AVHRR data was complemented with a DEM, a curvature, a slope, an aspect and the potential drainage density layers. The performance of these two databases when employed to derive soil information was compared. These databases were then further processed using the Discriminant Analysis Feature Extraction (DAFE) function (which is based on a canonical analysis procedure), and were then classified using the Fisher linear discriminant, and the ECHO spectral–spatial classifiers. Based on the results, it was concluded that the two reflective bands, the middle infrared, the two thermal bands and the NDVI provided a relatively wide range of detectable soil information. The use of single images or small dimensional AVHRR data sets (less then 10 layers) does not result in acceptable performances, while the use of multispectral and multitemporal databases improved the classification performance very significantly. However, the purely AVHRR-based model could not always delineate soil variations related to terrain differences, and resulted in an overall classification performance of 49.1%. Digital elevation and terrain descriptor data were essential in the model for achieving acceptable results. In the second part of the study an integrated AVHRR-terrain database was used, where five terrain layers were added to the 30 AVHRR channels. Two different spatial resolutions were compared, 500 m and 1 km, respectively. The use of elevation, slope, aspect and curvature as differentiating criteria often lead to a satisfactory result in terrain characterization, particularly in large-scale mapping. However, with those variables extracted from DEM of physiographically complex areas, e.g., — where plain areas and mountainous/hilly regions occur together in the same study — often lose their ability to delineate soil variations of the level lands. Beyond these terrain descriptors we implemented a new function, called potential drainage density (PDD) to improve the performance of the model on the plain areas. The classification accuracy of the integrated AVHRR-terrain database was improved significantly over the case when only AVHRR data was in the model. The classification performances of the three different resolution images were 87.3% for the 500-m resolution image and 70.1% for the 1-km resolution image.

Investigations of BOREAS spatial data in support of regional ecosystem modeling

Simulation models are commonly used to scale up water, energy, and trace gas flux estimates from study plots to an entire region or biome, such as the North American boreal forest. As a means to validate ecosystem model predictions at the scale of the typical experimental area (100 m2 to 1 km2), it is necessary to quantify potential errors in spatial data layers used as model inputs, independently from prediction errors resulting from incorrect model design or flawed process algorithms. Our analysis of land cover, hydrology, and soil maps generated as part of the Boreal Ecosystem‐Atmosphere Study (BOREAS) suggests that coverages for plant functional types, derived from a combination of Landsat Thematic Mapper and the advanced very high resolution radiometer (AVHRR) satellite images, provide the highest quality information to define spatial model parameters. This information is critical for boreal ecosystem simulations of small patch types (e.g., dry conifer, fen, and disturbed sites), which are frequently obscured at 1‐km pixel resolution. We find that soil property information for the dominant class, as contained in the regional BOREAS soil maps, does not appear to be a highly consistent indicator of hydrologic dynamics for fen and other boreal wetlands at the study area level. It appears instead that accurate regional modeling analyses for methane and other biogenic trace gas fluxes will depend largely on relatively fine scale remote sensing to resolve the high level of undifferentiated pixel mixing seen among boreal forest types and fen/bog areas in aggregated 1‐km AVHRR land cover data.

A review of soil and geological maps of the Nepean River terraces, NSW

SUMMARY The Nepean River terraces are a sequence of Tertiary and Quaternary alluvial deposits to the west of Sydney, NSW. In the last 85 years over 20 soil and geological maps covering the area have been produced. Errors and interpretations introduced in early regional scale maps were perpetuated for over 40 years despite numerous new editions. Regional scale geological maps in the 1950s and 1960s failed to take account of good detailed work by geographers, soil surveyors and geology students. Detailed geological and soil stratigraphic mapping in the past 10 years drew attention to these problems and has highlighted the important contributions made by the earlier detailed studies. New interpretations can now be tested against a substantial body of data. Contemporary regional soil and geological maps have taken account of these detailed studies and so present a more consistent approach than in the past.

Possible applications of photogeology to the study of rock mechanics

Summary Photogeology may provide useful general information in some spheres of rock mechanics, particularly in the very earliest stages of an investigation before ground is broken. Possible aspects for study are hydrogeology, major fracture systems, broad changes in rock character, structure and regional stress, soil mapping and natural slope failures. Much research is still needed in some of these fields, and suggestions for this are given. Some types of detailed ground based rock mechanics research would be helped by using the methods of ground photogrammetry, and by photogeological interpretation of ground stereoscopic photographs.