Mapping the spatial distribution of subsurface saline material in the Darling River valley

Triantafilis, John; Buchanan, Sam

doi:10.1016/j.jappgeo.2009.12.003

Cited by 26 publications

(11 citation statements)

References 29 publications

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“…Selection of the calibration sites is described elsewhere (Triantafilis & Buchanan, ). Briefly, a total of 50 cores (See Figure c) were selected and based on the EM34‐20 EC a data, which covered the small (0–100 mS/m), intermediate (100–200 mS/m) and large (200–300 mS/m) EC a (See Figure c).…”

Section: Methodsmentioning

confidence: 99%

“…Increasingly, digital soil mapping (DSM) methods are revolutionizing how natural resource information is being provided and interrogated, including the use of remote and proximal sensed ancillary data to give added value to soil data, such as the electrical conductivity of a saturated soil paste extract (EC e ). For example, Triantafilis & Buchanan () correlated EM34 data and used this to map subsurface (6–12 m) EC e . This approach was also used to map deep drainage (Woodforth et al ., ), groundwater height (Buchanan & Triantafilis, ) and texture (Huang et al ., ) when coupled with gamma‐ray ( γ ‐ray) spectrometry and digital elevation models (DEMs).…”

Section: Introductionmentioning

confidence: 99%

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Salinity risk assessment using fuzzy multiple criteria evaluation

Buchanan

Huang

2016

Soil Use and Management

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For agricultural productivity, primary salinity constitutes a hazard. Understanding the risk of secondary salinization is also important and it is necessary to map all these hazards and the overall risk. One approach is digital soil mapping. We have developed hazard maps of root zone (0-2 m) and subsurface (6-12 m) salinity, as well as groundwater height, using empirical best linear unbiased prediction using proximal and remotely sensed ancillary data. To convert the hazards into salinity risk maps and account for some uncertainty, fuzzy membership functions (FMF) were used in conjunction with semantic import models that consider the vulnerability of agricultural crops. Therefore, we developed memberships (l) to three salinity risk classes and created maps of each, including root zone (l RSR ) and subsurface (l SSR ) salinity, and depth to groundwater (l GTR ). To estimate groundwater (l GSR ) and overall salinity risk (l OSR ), fuzzy multiple criteria evaluation was undertaken. To account for l GSR , the l SSR and l GTR were combined using a t-norm operator, and l OSR was accounted for by combining l RSR and l GSR using a t-conorm operator. The approach was applied to an area growing irrigated cotton. Cross-validation shows predicted l OSR was good, with an agreement rate of 70.6%. The predicted l OSR was consistent with that of many areas affected by point-source salinity. The method provides an effective way of mapping salinity hazard and risk. Incorporation of FMF provides a meaningful continuum of membership and allows the incorporation of uncertainty. Salinity risk can be calculated relative to any vegetation community and locations where management actions to moderate soil salinization can be identified.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Salinity risk assessment using fuzzy multiple criteria evaluation

Buchanan

Huang

2016

Soil Use and Management

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“…More recently, attempts have therefore been made to extrapolate environmental features for entire data sets from specific measurements taken only in a subsample of plots (e.g. soil conditions) by relying on more readily available/observed spatial information, such as aerial images, imaging spectroscopy, electromagnetic (EM) data, canopy reflectance, topographic data or distance from the coastline (Schloeder et al 2001; Wilson & Ference 2001; Strachan et al 2002; Boggs et al 2003; Tilley et al 2003; Kooistra et al 2004; Schmidtlein & Sassin 2004; Schmidtlein 2005; Reich et al 2008; Triantafilis & Buchanan 2010). These approaches take advantage of regression relationships, co‐kryging or other modelling techniques to impute the value of the variable of interest in all plots of the database from inter‐correlated variables.…”

Section: Introductionmentioning

confidence: 99%

Dealing with scarce data to understand how environmental gradients and propagule pressure shape fine-scale alien distribution patterns on coastal dunes

Carboni

Santoro

Acosta

2011

Journal of Vegetation Science

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Questions: On sandy coastal habitats, factors related to substrate and to wind action vary along the sea–inland ecotone, forming a marked directional disturbance and stress gradient. Further, input of propagules of alien plant species associated to touristic exploitation and development is intense. This has contributed to establishment and spread of aliens in coastal systems. Records of alien species in databases of such heterogeneous landscapes remain scarce, posing a challenge for statistical modelling. We address this issue and attempt to shed light on the role of environmental stress/disturbance gradients and propagule pressure on invasibility of plant communities in these typical model systems. Location: Sandy coasts of Lazio (Central Italy). Methods: We proposed an innovative methodology to deal with low prevalence of alien occurrence in a data set and high cost of field‐based sampling by taking advantage, through predictive modelling, of the strong interrelation between vegetation and abiotic features in coastal dunes. We fitted generalized additive models to analyse (1) overall patterns of alien occurrence and spread and (2) specific patterns of the most common alien species recorded. Conclusion: Even in the presence of strong propagule pressure, variation in local abiotic conditions can explain differences in invasibility within a local environment, and intermediate levels of natural disturbance and stress offer the best conditions for spread of alien species. However, in our model system, propagule pressure is actually the main determinant of alien species occurrence and spread. We demonstrated that extending the information of environmental features measured in a subsample of vegetation plots through predictive modelling allows complex questions in invasion biology to be addressed without requiring disproportionate funding and sampling effort.

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“…The transition to the Cotton CRC saw continued work on both the surveying of salinity in various locations and the development of models to more accurately predict EC depth functions using different EM devices. In the Bourke Irrigation District, Odeh and Onus (2008) conducted a field survey and then mapped topsoil EC using regression kriging, while Triantafilis and Buchanan (2010) estimated the spatial distribution of saline soil layers to a depth of 12 m using EM34 data acquired from across the district. A series of papers were also published Monteiro Santos 2009, 2010;Monteiro Santos et al 2010;Triantafilis et al 2013b) detailing methods of…”

Section: Salinity and Sodicitymentioning

confidence: 99%

A review of the soil science research legacy of the triumvirate of cotton CRC

Cattle

Field

2013

Crop Pasture Sci.

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For nearly two decades (1994–2012) a series of three consecutive Cooperative Research Centres (CRC) dealing with cotton production provided the impetus and financial support for a substantial body of soil science research in eastern and northern Australia. Focusing on the most commonly utilised soil for irrigated crop production, the Vertosol, CRC-affiliated soil researchers undertook detailed soil inventories of cotton-growing valleys in New South Wales, and tackled a range of applied soil research questions that faced the entire Australian cotton industry. Across the broad categories of soil mapping and characterisation, soil physical condition, salinity and sodicity, soil chemical fertility, and soil carbon and biota, some 120 CRC-affiliated research papers were published in peer-reviewed journals during the years of the CRC. Findings from this body of research were fed back to the industry through conferences, extension workshops and materials, and to a lesser extent, the peer-reviewed publications. In certain cases, underpinning basic research was carried out concurrently with the more applied research, meaning that the cotton CRC were effectively supporting advances in the discipline of soil science, as well as in sustainable cotton production. A feature of the soil research portfolio over the span of the three cotton CRC was that priorities shifted according to the interplay of three factors; the natural maturation of research topics and the concomitant evolution of cotton farming systems, the rising importance of environmental implications of agricultural land use, and the emergence of carbon as a national research priority. Furthermore, the commitment of the CRC to education resulted in the involvement of undergraduate and postgraduate university students in all aspects of the soil research effort. A legacy of the triumvirate of cotton CRC is a wide-ranging body of both applied and basic knowledge regarding the physical, chemical and biological attributes of Australian Vertosols used for irrigated agriculture.

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Mapping the spatial distribution of subsurface saline material in the Darling River valley

Cited by 26 publications

References 29 publications

Salinity risk assessment using fuzzy multiple criteria evaluation

Salinity risk assessment using fuzzy multiple criteria evaluation

Dealing with scarce data to understand how environmental gradients and propagule pressure shape fine-scale alien distribution patterns on coastal dunes

A review of the soil science research legacy of the triumvirate of cotton CRC

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