Soil - landscape relationships of downlands soils formed from loess, eastern South Island, New Zealand

Soil Research ◽  
1997 ◽  
Vol 35 (4) ◽  
pp. 827 ◽  
Author(s):  
T. H. Webb ◽  
S. J. Burgham

The Timaru and Claremont soil series occupy >145 000 ha of loess-mantled downlands of the South Island. The soils are mapped in large map delineations and the accompanying soil reports provide very generalised descriptions and definitions of the units. Almost no information is recorded on the nature and causes of soil variability. In this study soil variability is described along transects at 12 locations. The sites selected encompass a range of aspect (sunny and shady), topography (easy rolling to strongly rolling terrain), and land use (non-ploughed, pastoral, and mixed cropping). The definitions of the Timaru and Claremont series are refined and the variability in soil morphology is related to landscape features. Morphological data from the transects are collated into generalised soil–landscape models. Similar arrays of soils occur within the Timaru and Claremont soil–landscape models. The models vary mainly in the occurrence and depth to reducing conditions. The soil–landscape models provide a framework within which to derive soil attribute values for use in predictive models and land-use interpretations, and provide a baseline from which future studies may assess the impacts of land-use practices. In both soil series, the thickness of topsoils, depth to reducing conditions, and depth to fragipans are greatest on footslopes and generally decrease to shoulderslopes. Penetration resistance is lowest on footslopes and increases to shoulderslopes. In cultivated land, footslope sites have markedly over-thickened topsoils. Relocation of topsoil material from upper to lower slopes is attributed mainly to the effects of cultivation, either directly, through mechanical movement of soil material during cultivation operations, or indirectly, through the promotion of soil erosion. Variations in depth of soil materials are expected to have attendant affects on potential productivity.

1986 ◽  
Vol 66 (1) ◽  
pp. 37-44 ◽  
Author(s):  
J. A. McKEAGUE ◽  
G. C. TOPP

Soil drainage groups assigned on the basis of soil survey information were evaluated against measured saturated hydraulic conductivity (Ksat) data for nine soils in Ontario. The drainage groups used in the drainage guide for Ontario, are based mainly on assumed relationships between soil texture and the capacity of the soil to transmit water.Measured Ksat values were incompatible with the drainage groups assigned to at least four of the nine soils. For the soils tested, there was very little relationship between texture and Ksat. Structure, including porosity, had a major influence on Ksat, and near-surface structure is influenced greatly by land use. Thus, general interpretations of the drainage characteristics of soil series have serious limitations. The usefulness of soil survey information for interpretation of soil drainage could be increased by improved description of soil morphology and by reliable estimates of Ksat during mapping. Such estimates can be based on morphology if they are regularly recalibrated by measurement. Key words: Hydraulic conductivity, tile drainage, texture, soil morphology


1986 ◽  
Vol 66 (1) ◽  
pp. 21-30 ◽  
Author(s):  
C. WANG ◽  
J. A. McKEAGUE

Pedons were described, sampled and classified at 5-m intervals along a 130-m transect in an area typical of the southern Laurentian Highlands in order to assess short-range soil variability. Orthic Ferro-Humic Podzol was the dominant subgroup (25 of 27 sites). Differences in depth to bedrock and in soil water regime resulted in four soil families; bedrock was exposed at one site. At 21 of the 27 sites, however, the pedons were classified in one family: Orthic Ferro-Humic Podzol, coarse loamy, cold, humid. Differences in thicknesses and sequences of horizons resulted in a total of at least nine soil series. At scales of 1:20 000 or somewhat smaller, the soils of map units in the area would be most appropriately indicated as slope phases (10–40% slopes) of families. The dominant family would be the one indicated above with inclusions of shallow to extremely shallow phases and bedrock outcrops. Key words: Soil variability, Podzolic soils, classification of pedons


Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2661 ◽  
Author(s):  
Vincent Smets ◽  
Boud Verbeiren ◽  
Martin Hermy ◽  
Ben Somers

Due to changing precipitation patterns induced by climate change, urban planners are confronted with new challenges to effectively mitigate rainfall runoff. An important knowledge gap that needs to be addressed before tackling these challenges is how and to which extent street/drainage grid density and spatial land use configuration influence the amount of runoff. Therefore, a virtual experiment was conducted to assess the influence of grid density and spatial land use configuration on the functional runoff connectivity (Fc), which is a measure of the easiness by which water flows through the landscape. Through the use of a design of experiments approach in combination with the SCS—Curve Number runoff model, a wide variety of neutral landscape models with a fixed percentage of pervious- and impervious cover were generated that maximized the variance of Fc. Correlations between landscape metrics and neutral landscape models were calculated. Our results indicated that, out of the 17 landscape metrics tested, the average impervious cluster area, the number of impervious clusters, the standard deviation of the cluster size, two proximity indexes and the effective impervious area were strongly correlated with Fc throughout all grid scenarios. The relationship between Fc on the one hand and the average impervious cluster area and the effective impervious area on the other hand, was modelled. The average impervious cluster area models showed a relationship with Fc that closely approximated a logarithmic function (R2: 0.49–0.73), while the effective impervious area models were found to have a linear relationship with Fc (R2: 0.63–0.99). A dense grid was shown to cause a strong increase in Fc, demonstrating the effectiveness of an urban grid in channeling and removing runoff. Our results further indicate that fine-grained landscapes with a lot of small impervious clusters are preferred over course-grained landscapes when the goal is to reduce Fc. In highly urbanized landscapes, where the percentage of impervious area is high, small changes in landscape pattern could significantly reduce Fc. By using a downward hydrological modeling approach this research aims to bring more clarity to the underlying variables influencing Fc, rather than trying to generate realistic prediction values.


Soil Research ◽  
1994 ◽  
Vol 32 (5) ◽  
pp. 889 ◽  
Author(s):  
E Fritsch ◽  
RW Fitzpatrick

A pedo-hydrological method which involves interpreting features in soils that result from both ancient and modern processes along toposequences in a subcatchment of the Mt Lofty Ranges, South Australia, is used to construct conceptual soil-water-landscape models. This method links soil-landscape features to soil-water processes with strong emphasis on: (i) soil water-flow systems and (ii) soil-forming and soil-change processes. The conceptual model illustrates the interactions between soil processes acting in soil water-flow systems. This model is able to predict future modes of soil-landscape evolution under changing environmental conditions. As well, it may be used by land and water supply managers to develop more efficient management strategies under conditions of increasing land degradation (e.g. erosion and water pollution). A typical Palexeralf-Natraqualf hydro-toposequence of soils (i.e. catena consisting of red-yellow-grey duplex soils) is used as an example to illustrate this new approach. The landscape selected is undergoing severe soil degradation (i.e. waterlogging, dryland salinity, erosion and water pollution). The constructed conceptual soil-water-landscape model is the result of detailed pedo-hydrological investigations along toposequences in a representative subcatchment in the high rainfall zone (>600 mm) of the Mount Lofty Ranges, South Australia. The model illustrates in graphic form interactions between three soil water-flow systems (freely drained red soil system, hydromorphic topsoil system, hydromorphic subsoil system) and eight soil processes (saprolitization, ferralitization, glaebulization, redoximorphism, eluviation/illuviation, salinization/solonization, sulfidization/sulfuricization and water erosion). The study demonstrates that this whole ecosystem has been placed into disequilibrium thereby developing severe land degradation problems as a result of rising saline sulfatic ground watertables and perched watertables due to land-clearing since European settlement. The purpose of this paper is to provide a methodology framework and overall summary for other papers in a series dealing essentially with detailed field and laboratory investigations of individual soil-water processes.


Author(s):  
M. Grodzynskyi

Series (succession sequences) of soils that change each other over time and within the landscape units are proper objects for landscape mapping. The soil series give an idea of both retrospective state of a soil before its anthropogenic transformations and of tendencies of soil development in landscape complexes of various types. The names of soils as they are appeared in soil nomenclature of Soil science should not be duplicated in the legends of landscape maps. "Landscape" names for soils have to stress on their features and attributes that are of primary importance for vegetation, water, thermal and other ecological regimes of landscapes. The "landscape" names for different types of Albeluvisols and Phaeozems of Ukraine are suggested. Key words: soil, landscape, landscape map, landscape science.


2019 ◽  
Author(s):  
W. Marijn van der Meij ◽  
Arnaud J. A. M. Temme ◽  
Jakob Wallinga ◽  
Michael Sommer

Abstract. Humans have substantially altered soil and landscape patterns and properties due to agricultural use, with severe impacts on biodiversity, carbon sequestration and food security. These impacts are difficult to quantify, because we lack data on long-term changes in soils in natural and agricultural settings and available simulation methods are not suitable to reliably predict future development of soils under projected changes in climate and land management. To help overcome these challenges, we developed the HydroLorica soil-landscape evolution model, that simulates soil development by explicitly modelling the spatial water balance as driver of soil and landscape forming processes. We simulated 14500 years of soil – formation under natural conditions for three scenarios of different rainfall inputs. For each scenario we added a 500-year period of intensive agricultural land use, where we introduced tillage erosion and changed vegetation type. Our results show substantial differences between natural soil patterns under different rainfall input. With higher rainfall, soil patterns become more heterogeneous due to increased tree throw and water erosion. Agricultural patterns differ substantially from the natural patterns, with higher variation of soil properties over larger distances and larger correlations with terrain position. In the natural system, rainfall is the dominant factor influencing soil variation, while for agricultural soil patterns landform explains most of the variation simulated. The cultivation of soils thus changed the dominant factors and processes influencing soil formation, and thereby also increased predictability of soil patterns. Our study highlights the potential of soil-landscape evolution modelling for simulating past and future developments of soil and landscape patterns. Our results confirm that humans have become the dominant soil forming factor in agricultural landscapes.


2020 ◽  
Vol 63 (3) ◽  
pp. 731-740
Author(s):  
Dagbegnon Clement Sohoulande Djebou ◽  
Liwang Ma ◽  
Ariel A. Szogi ◽  
Gilbert C. Sigua ◽  
Kenneth C. Stone ◽  
...  

Highlights This study addressed the inclusion of field-scale soil variability in nitrogen (N) management for corn production. RZWQM2 was calibrated for corn yield and N dynamics on four sandy soil series under supplemental irrigation. Multi-year simulations of corn production under high and low N application rates were analyzed. Results showed room to reduce N use and N leaching without affecting corn production on Coastal Plain sandy soils. Abstract. Nitrogen (N) fertilization contributes significantly to maintain high yields in corn (Zea mays L.) production. In the Southeastern Coastal Plain of the U.S. where soils are sandy with poor water and nutrient holding capacity, a fraction of the N applied to corn fields is often leached from the root zone and becomes unavailable to plants. As these soils belong to various taxonomic classes, research has shown significant corn yield differences among soil series. However, few studies have focused on integrating field-scale soil variability, N leaching, and corn production. To address this knowledge gap, this study used the Root Zone Water Quality Model (RZWQM2) to simulate different N management scenarios in corn production for four sandy soil series under supplemental irrigation. The calibrated model was used to simulate nine consecutive years of corn production under four N management scenarios, including two high rates of N application (rate A = 224 kg N ha-1 with 25 kg N ha-1 at preplant; rate A' = 224 kg N ha-1 without preplant N), and two low rates of N application (rate B = 157 kg N ha-1 with 25 kg N ha-1 at preplant; rate B' = 157 kg N ha-1 without preplant N). Simulation results showed that without preplant N application, N leaching was reduced by up to 17% with no significant impact on corn yield, depending on the soil series. Hence, consideration of field-scale soil variability could help improve N management by reducing N use and N leaching without impacting corn production. Keywords: Corn yield components, Growing season, Modeling, Nitrogen dynamics, RZWQM2, Soil variability.


2002 ◽  
Vol 18 (3) ◽  
pp. 157-163 ◽  
Author(s):  
Sonneveld M.P.W.* ◽  
J. Bouma ◽  
A. Veldkamp

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