Academic literature on the topic 'Soil moisture Australia Measurement'

The amount of water that can be stored in soil and evaporated or actively used by plants is a key parameter in hydrologic models and is important for crop and pasture production. Often, the active soil moisture store is estimated from laboratory measurements of soil properties. An alternative approach, described in this paper, is to estimate the extractable soil moisture capacity from direct measurements of soil moisture content in the field. A time series of soil moisture values, over the depth of the soil, shows the actual changes in water content. The difference between the wettest and driest profiles is an estimate of the extractable soil moisture storage. We have gathered data on extractable soil water capacity for 180 locations over Australia and have compared our values with published results from the Atlas of Australian Soils (AAS), derived from profile descriptions and pedo-transfer functions. Our results show that data from the AAS provide a useful lower bound for measured extractable soil moisture storage, but of the sites examined, 42% had values >2 times those in the AAS. In part, this was because total soil depths were underestimated in the AAS results compared with the active depths from the measured data. Active depths are strongly related to vegetation type.

Measurement of the moisture variation in soils is required for geotechnical design and research because soil properties and behavior can vary as moisture content changes. The neutron probe, which was developed more than 40 years ago, is commonly used to monitor soil moisture variation in the field. This study reports a full-scale field monitoring of soil moisture using a neutron moisture probe for a period of more than 2 years in the Melbourne (Australia) region. On the basis of soil types available in the Melbourne region, 23 sites were chosen for moisture monitoring down to a depth of 1500 mm. The field calibration method was used to develop correlations relating the volumetric moisture content and neutron counts. Observed results showed that the deepest “wetting front” during the wet season was limited to the top 800 to 1000 mm of soil whilst the top soil layer down to about 550 mm responded almost immediately to the rainfall events. At greater depths (550 to 800 mm and below 800 mm), the moisture variations were relatively low and displayed predominantly periodic fluctuations. This periodic nature was captured with Fourier analysis to develop a cyclic moisture model on the basis of an analytical solution of a one-dimensional moisture flow equation for homogeneous soils. It is argued that the model developed can be used to predict the soil moisture variations as applicable to buried structures such as pipes.

Soil moisture reanalysis products can provide soil water information for the surface and root zone soil layers, which are significant for understanding the water cycle and climate change. However, the accuracy of multi-layer soil moisture datasets obtained from reanalysis products remains unclear in some areas. In this study, we evaluated the root zone soil moisture of the ERA-Interim soil moisture product, as well as the surface soil moisture based on in situ measurements from the OzNet hydrological measurement network over southeast Australia. In general, the ERA-Interim soil moisture product presents good agreement with in situ soil moisture values and can nicely reflect time variations, with correlation coefficient (R) values in the range of 0.73 to 0.84 and unbiased root mean square difference (ubRMSD) values from 0.035 m3·m−3 to 0.060 m3·m−3. Although the ERA-Interim soil moisture also can reflect temporal dynamics of soil moisture at root zone layer at depths of 28–100 cm, low correlations were found in winter. In addition, the ERA-Interim soil moisture product overestimates in situ measurements at depths of 0–7 cm and 7–28 cm, whereas the product shows underestimated values compared with in situ soil moisture at the root zone of 28–100 cm. Consequently, the ERA-Interim soil moisture product has both high absolute and temporal accuracy at depths of 7–28 cm, and the ERA-Interim soil moisture product can nicely capture temporal dynamics at all the evaluated soil level depths, except for the depth of 28–100 cm during the winter months. The contributions of terrain, vegetation cover, and soil texture to the model error were addressed by feature importance estimations using the random forest (RF) algorithm. Results indicate that terrain features may have an impact on the model errors. It is clear that the accuracy of the ERA-Interim soil moisture can be improved by adjusting the assimilation scheme, and the results of this study are expected to provide a comprehensive understanding of the model errors and references for optimizing the model.

Abstract. The lack of direct measurement of root-zone soil moisture poses a challenge to the large-scale prediction of ecosystem response to variation in soil water. Microwave remote sensing capability is limited to measuring moisture content in the uppermost few centimetres of soil. The GRACE (Gravity Recovery and Climate Experiment) mission detected the variability in storage within the total water column. However, root-zone soil moisture cannot be separated from GRACE-observed total water storage anomalies without ancillary information on surface water and groundwater changes. In this study, GRACE total water storage anomalies and SMOS near-surface soil moisture observations were jointly assimilated into a hydrological model globally to better estimate the impact of changes in root-zone soil moisture on vegetation vigour. Overall, the accuracy of root-zone soil moisture estimates through the joint assimilation of surface soil moisture and total water storage retrievals showed improved consistency with ground-based soil moisture measurements and satellite-observed greenness when compared to open-loop estimates (i.e. without assimilation). For example, the correlation between modelled and in situ measurements of root-zone moisture increased by 0.1 (from 0.48 to 0.58) and 0.12 (from 0.53 to 0.65) on average for grasslands and croplands, respectively. Improved correlations were found between vegetation greenness and soil water storage on both seasonal variability and anomalies over water-limited regions. Joint assimilation results show a more severe deficit in soil water anomalies in eastern Australia, southern India and eastern Brazil over the period of 2010 to 2016 than the open-loop, consistent with the satellite-observed vegetation greenness anomalies. The assimilation of satellite-observed water content contributes to more accurate knowledge of soil water availability, providing new insights for monitoring hidden water stress and vegetation conditions.

Salinity, sodicity, acidity, and phytotoxic concentrations of chloride (Cl–) in soil are major constraints to crop production in many soils of north-eastern Australia. Soil constraints vary both spatially across the landscape and vertically within the soil profile. Identification of the spatial variability of these constraints will allow farmers to tune management to the potential of the land, which will, in turn, bring economic benefit. For three cropping fields in Australia’s northern grains region, we used electromagnetic induction with an EM38, which measures apparent electrical conductivity of the soil (ECa) and soil sampling to identify potential management classes. Soil Cl– and soluble Na+ concentrations, EC of the saturated extract (ECse), and soil moisture were the principal determinants of the variation of ECa, measured both at the drained upper limit of moisture (UL) and at the lower limit (LL) of moisture extracted by the crop. Grain yield showed a strong negative relation with ECa at both UL and LL, although it was stronger for the latter. We arrive at a framework to estimate the monetary value of site-specific management options, through: (i) identification of potential management classes formed from ECa at LL; (ii) measurement of soil attributes generally associated with soil constraints in the region; (iii) grain yield monitoring; and (iv) simple on-farm experiments. Simple on-farm experiments suggested that, for constrained areas, matching fertiliser application to realistic yield potential, coupled to gypsum amelioration, could potentially benefit growers by AU$14–46/ha.year (fertiliser) and $207/ha.3 years (gypsum).

Abstract. Interactions between soil moisture and terrestrial evaporation affect water cycle behaviour and responses between the land surface and the atmosphere across scales. With strong heterogeneities at the land surface, the inherent spatial variability in soil moisture makes its representation via point-scale measurements challenging, resulting in scale mismatch when compared to coarser-resolution satellite-based soil moisture or evaporation estimates. The Cosmic Ray Neutron Probe (CRNP) was developed to address such issues in the measurement and representation of soil moisture at intermediate scales. Here, we present a study to assess the utility of CRNP soil moisture observations in validating model evaporation estimates. The CRNP soil moisture product from a pasture in the semi-arid central west region of New South Wales, Australia, was compared to evaporation derived from three distinct approaches, including the Priestley–Taylor (PT-JPL), Penman–Monteith (PM-Mu), and Surface Energy Balance System (SEBS) models, driven by forcing data from local meteorological station data and remote sensing retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson's correlations, quantile–quantile (Q–Q) plots, and analysis of variance (ANOVA) were used to qualitatively and quantitatively evaluate the temporal distributions of soil moisture and evaporation over the study site. The relationships were examined against nearly 2 years of observation data, as well as for different seasons and for defined periods of analysis. Results highlight that while direct correlations of raw data were not particularly instructive, the Q–Q plots and ANOVA illustrate that the root-zone soil moisture represented by the CRNP measurements and the modelled evaporation estimates reflect similar distributions under most meteorological conditions. The PT-JPL and PM-Mu model estimates performed contrary to expectation when high soil moisture and cold temperatures were present, while SEBS model estimates displayed a disconnect from the soil moisture distribution in summers with long dry spells. Importantly, no single evaporation model matched the statistical distribution of the measured soil moisture for the entire period, highlighting the challenges in effectively capturing evaporative flux response within changing landscapes. One of the outcomes of this work is that the analysis points to the feasibility of using intermediate-scale soil moisture measurements to evaluate gridded estimates of evaporation, exploiting the independent, yet physically linked nature of these hydrological variables.

Persistence is an important feature of soil moisture, which affects many important processes such as land–air interaction and ecohydrological processes. Soil moisture datasets from reanalysis, remote-sensing observations and land surface models have been widely used in various ecohydrological studies, however, due to the complexity of hydrological processes, the essential features of soil moisture such as spatial-temporal characteristics and persistence still need to be further quantified. This study focused on the Australia region and used in situ observation from fourteen International Soil Moisture Network sites to evaluate soil moisture from six gridded products, including satellite remote-sensing records (ESA CCI), output of reanalysis (ERA5-Land) and land surface models (GLDAS and GLEAM). High correlation coefficients between observations and the other soil moisture datasets were gotten. Regional averaged inter-annual variations of soil moisture were relatively large with some dry periods (2002–2010, 2013–2016) and wet periods (2011–2012) indicated by these gridded products. General coherent spatial patterns were found in long-term soil moisture with large differences in the lateral inflow area of the Great Artesian Basin. The coefficient of variation of these soil moisture datasets generally decreased from northwest to southeast, but the enhanced vegetation index coefficient of variation was larger in the southwest corner, northeast (non-coastal areas) and the lateral inflow area. Persistence calculated from various soil moisture datasets had quite large differences compared with measurements. Meanwhile, little coherence was gotten among different surface soil moisture datasets, the persistence of deep soil moisture seemed to be significantly overestimated. Therefore, models still need to improve the temporal characteristics with the persistence rather than the correlation coefficient.

Abstract. Currently, no extensive, near real time, global soil moisture observation network exists. Therefore, the Met Office global soil moisture analysis scheme has instead used observations of screen temperature and humidity. A number of new space-borne remote sensing systems, operating at microwave frequencies, have been developed that provide a more direct retrieval of surface soil moisture. These systems are attractive since they provide global data coverage and the horizontal resolution is similar to weather forecasting models. Several studies show that measurements of normalised backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) on the meteorological operational (MetOp) satellite contain good quality information about surface soil moisture. This study describes methods to convert ASCAT surface soil wetness measurements to volumetric surface soil moisture together with bias correction and quality control. A computationally efficient nudging scheme is used to assimilate the ASCAT volumetric surface soil moisture data into the Met Office global soil moisture analysis. This ASCAT nudging scheme works alongside a soil moisture nudging scheme that uses observations of screen temperature and humidity. Trials, using the Met Office global Unified Model, of the ASCAT nudging scheme show a positive impact on forecasts of screen temperature and humidity for the tropics, North America and Australia. A comparison with in-situ soil moisture measurements from the US also indicates that assimilation of ASCAT surface soil wetness improves the soil moisture analysis. Assimilation of ASCAT surface soil wetness measurements became operational during July 2010.

Abstract. Currently, no extensive global soil moisture observation network exists. Therefore, the Met Office global soil moisture analysis scheme has instead used observations of screen temperature and humidity. A number of new space-borne remote sensing systems, operating at microwave frequencies, have been developed that provide a more direct retrieval of surface soil moisture. These systems are attractive since they provide global data coverage and the horizontal resolution is similar to weather forecasting models. Several studies show that measurements of normalised backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) on the meteorological operational (MetOp) satellite contain good quality information about surface soil moisture. This note describes methods to convert ASCAT surface soil wetness measurements to volumetric surface soil moisture together with bias correction and quality control. A computationally efficient nudging scheme is used to assimilate the ASCAT volumetric surface soil moisture data into the Met Office global soil moisture analysis. This ASCAT nudging scheme works alongside a soil moisture nudging scheme that uses observations of screen temperature and humidity. Trials, using the Met Office global Unified Model, of the ASCAT nudging scheme show a positive impact on forecasts of screen temperature and humidity for the tropics, North America and Australia. A comparison with in-situ soil moisture measurements from the US also indicates that assimilation of ASCAT surface soil wetness improves the soil moisture analysis. Assimilation of ASCAT surface soil wetness measurements became operational during July 2010.

Space-borne soil moisture (SM) satellite products such as those available from Soil Moisture Active Passive (SMAP) offer unique opportunities for global and frequent monitoring of SM and also to understand its spatiotemporal variability. The present study investigates the performance of the SMAP L4 SM product at selected experimental sites across four continents, namely North America, Europe, Asia and Australia. This product provides global scale SM estimates at 9 km × 9 km spatial resolution at daily intervals. For the product evaluation, co-orbital in situ SM measurements were used, acquired at 14 test sites in North America, Europe, and Australia belonging to the International Soil Moisture Network (ISMN) and local networks in India. The satellite SM estimates of up to 0–5 cm soil layer were compared against collocated ground measurements using a series of statistical scores. Overall, the best performance of the SMAP product was found in North America (RMSE = 0.05 m3/m3) followed by Australia (RMSE = 0.08 m3/m3), Asia (RMSE = 0.09 m3/m3) and Europe (RMSE = 0.14 m3/m3). Our findings provide important insights into the spatiotemporal variability of the specific operational SM product in different ecosystems and environments. This study also furnishes an independent verification of this global product, which is of international interest given its suitability for a wide range of practical and research applications.

Soil moisture information can be used accurately in determining the timing and amount of irrigation applied to plants. Pan and Pan et al. proposed a robust and simple daily diagnostic equation for estimating daily soil moisture. The diagnostic equation evaluates the relationship between the soil moisture loss function and the summation weighted average of precipitation. The loss function uses the sinusoidal wave function which employs day of the year (DOY) to evaluate the seasonal variation in soil moisture loss for a given year. This was incorporated into the daily diagnostic equation to estimate the daily soil moisture for a location. Solar radiation is an energy source that drives the energy and water exchanges between vegetation and the atmosphere (i.e., evapotranspiration), and thus impacts the soil moisture dry-down. In this paper, two parameters (the actual solar radiation and the clear sky solar radiation) are introduced into loss function coefficient to improve the estimation of soil moisture. After the Introduction of the solar radiation data into soil moisture loss function, a slight improvement was observed in the estimated daily soil moisture. Pan observed that generally the correlation coefficient between the estimated and the observed soil moisture is above 0.75 and the root mean square error is below 5.0 (%v/v). The introduction solar radiation data (i.e. clear sky solar radiation and actual solar) improve the correlation coefficient average for all the sites evaluated by 0.03 when the root mean square error is generally below 4.5(%v/v) for the entire root zone.

Thesis (MScAgric)--University of Stellenbosch, 2004.
ENGLISH ABSTRACT: Irrigation scheduling is one of the most important cultural practices in irrigated vineyards. Water holding capacity of soil is arguably therefore one of the most important characteristics of a soil as it determines how much water can be made available to the plant. The measurement of water holding capacity of soils is time consuming and costly. In situ determinations are often impractical to determine. For routine determinations, water holding capacity is therefore determined on disturbed samples. Such a method for example is the rubber ring method. A great deal of criticism surrounds this rubber ring method and results are often questioned. The objectives of this study were therefore to determine what the relationship was between undisturbed and disturbed samples and to determine whether compacted samples could give a more accurate representation of the water holding capacity of soil. Soil textural factors influencing the volumetric water content of undisturbed, rubber ring and compacted samples at 5, 10 and 100 kPa were investigated. In addition, soil textural properties influencing water holding capacity of the respective samples between 5 and 100 kPa and 10 and 100 kPa were investigated. The final objective of the study was to develop simple models to predict the volumetric water content and water holding capacity of soil. Undisturbed and disturbed soil samples were taken at various localities to ensure a wide range of textures. Water holding capacity of undisturbed and disturbed samples was determined at ARC Infruitec-Nietvoorbij using the standard air pressure and ceramic plate technique and the routine rubber ring method respectively. Soil samples were also compacted to a bulk density of approximately 1.5 g.cm-3 as a further treatment for determination of water holding capacity using the air pressure and ceramic plate technique. To investigate aspects of soil texture that could possibly influence volumetric water content of the soil, correlations were done between different texture components and volumetric water content of undisturbed, rubber ring and compacted samples at 5, 10 and 100 kPa. In order to determine the effect of texture on water holding capacity of the soil, correlations were drawn between texture components and water holding capacity of undisturbed, rubber ring and compacted samples between matric potential ranges 5 and 100 kPa and 10 and 100 kPa. The results from this study were used to develop models to predict volumetric soil water content and water holding capacity of soils for a range of soils. Volumetric water content of rubber ring samples at 5 kPa was more than the volumetric water content of undisturbed samples at 5 kPa. The volumetric water content of rubber ring samples at 5 kPa and the volumetric water content of undisturbed samples at 5 kPa was correlated by 87%. Volumetric water content of compacted samples at 5 kPa had a 85% degree of correlation with the volumetric water content of undisturbed samples. At 10 kPa, the correlation between volumetric water content determined using rubber ring samples and undisturbed samples was 77%. This was identical to the correlation between volumetric water content of compacted samples at 10 kPa and undisturbed samples. At 100 kPa, most of the rubber ring samples' volumetric water content fell below the 1:1 line of volumetric water content of undisturbed samples. The volumetric water content of all the compacted samples was higher than that of the undisturbed samples. Water holding capacity of all the rubber ring samples between 5 and 100 kPa was greater than the water holding capacity of the undisturbed samples between 5 and 100 kPa. Rubber ring samples therefore generally overestimated the water holding capacity of the soil. The water holding capacity of most of the rubber ring samples between 10 and 100 kPa was greater than the water holding capacity of the undisturbed samples. In contrast, the water holding capacity of compacted samples between 5 and 100 kPa was less than the water holding capacity of undisturbed samples between 5 and 100 kPa. Water holding capacity of compacted samples was therefore underestimated. The results from this study confirmed that the influence of clay and silt content on volumetric water content of undisturbed, rubber ring and compacted samples increased as the suction on the respective samples is increased. The influence of fine sand content on volumetric water content of undisturbed, rubber ring and compacted samples decreased with an increase in matric potential to 100 kPa. Medium sand content of undisturbed, rubber ring and compacted samples had the greatest influence of all the textural components on the volumetric water content of the respective samples at 5 kPa and 10 kPa. Water holding capacity of undisturbed, rubber ring and compacted samples between 5 and 100 kPa was greatly influenced by the fine sand content of the samples. Medium sand content of the samples also had an influence on the water holding capacity thereof. To predict the volumetric water content of undisturbed samples at 5, 10 and 100 kPa, the independent variables were fine sand content, square root of medium sand content and In of medium sand content. In the case of models to predict the volumetric water content of rubber ring samples at 5, 10 and 100 kPa, the same variables were used as independent variables. Additional variables such as silt content, the In of silt content, square root of clay plus silt content and the medium sand content. To predict the volumetric water content of compacted samples at 5, 10 and 100 kPa the terms used were silt content, clay plus silt content, the e-clay plus silt content. medium sand content and the square root of medium sand content. The models to predict volumetric water content of rubber ring samples gave the best correlation with the actual volumetric water content of rubber ring samples. The final models to predict the water holding capacity of all the samples between 5 and 100 kPa and 10 and 100 kPa used only fine and medium sand parameters as independent variables. Soil textural components do play an important role in determining the volumetric water content of undisturbed, rubber ring and compacted samples at 5, 10 and 100 kPa. The magnitude of the water holding capacity between 5 and 100 kPa and 10 and 100 kPa is also influenced by soil texture. The models developed to predict the volumetric water content of samples at 5, 10 and 100 kPa and the magnitude of the water holding capacity between 5 and 100 kPa and 10 and 100 kPa could be very useful. Both time and money can potentially be saved. Models that can be highly recommended are the models generated for the undisturbed samples. These are: At 5 kPa, VWCu = 0.47259 - 0.04712 medium sando.s At 10 kPa, VWCu = 0.41292 - 0.04221 medium sandos At 100 kPa, VWCu = 0.48080 - 0.00254 fine sand - 0.0865 In medium sand Between 5 and 100 kPa, WHCu = -29.523 + 3.394 fine sand Between 10 and 100 kPa, WHCu = -891.794 + 232.326 In fine sand + 38.006 In medium sand
AFRIKAANSE OPSOMMING: Besproeiingskedulering is een van die belangrikste wingerdverbouingspraktyke. Waterhouvermoë bepaal hoeveel water beskikbaar gestel kan word aan die plant en daarom is dit een van die belangrikste eienskappe van 'n grond. Die meting van waterhouvermoë van grond is tydsaam en duur. Boonop is in situ bepalings dikwels onprakties om te bepaal. Waterhouvermoë word dus bepaal op versteurde monsters vir roetine ontledings. 'n Voorbeeld van so 'n metode is die rubberring metode. Daar bestaan groot kritiek teenoor hierdie rubberring metode en resultate word dikwels betwyfel deur die landboubedryf. Die doel van hierdie studie was dus om te bepaal wat die verwantskap is tussen onversteurde monsters en rubberring monsters asook om te bepaal of gekompakteerde monsters 'n meer akkurate aanduiding sou gee as onversteurde monsters van die waterhouvermoë van die grond. Grondtekstuur faktore wat die volumetriese waterinhoud van onversteurde monsters, rubberring monsters en gekompakteerde monsters by 5, 10 and 100 kPa beïnvloed, was ondersoek. Grondtekstuur faktore wat waterhouvermoë van die onderskeie monsters tussen 5 en 100 kPa en tussen 10 en 100 kPa beïnvloed, was ook ondersoek. Die finale doelwit van die studie was om eenvoudige modelle te ontwikkel vir die voorspelling van volumetriese waterinhoud en waterhouvermoë van grond. Onversteurde grond monsters en grond vir versteurde monsters is by verskeie lokaliteite geneem om 'n wye reeks teksture te verkry. Waterhouvermoë van onversteurde monsters is bepaal by LNR Infruitec- Nietvoorbij met die standaard drukplaat tegniek. Waterhouvermoë van versteurde grond is bepaal met die roetine rubberring metode van LNR Infruitec-Nietvoorbij. Grond was ook gekompakteer tot 'n bulkdigtheid van ongeveer 1.5 g.cm-3 en daarna is die waterhouvermoë bepaal by die LNR Infruitec- Nietvoorbij met die standaard drukplaat tegniek. Om aspekte van grondtekstuur, wat moontlik die volumetriese waterinhoud van grond kan beïnvloed te ondersoek, is korrelasies tussen verskeie tekstuur komponente en die volumetriese waterinhoud van onversteurde monsters, rubberring monsters en gekompakteerde monsters by 5, 10 en 100 kPa bepaal. Om te bepaal watter tekstuur komponente waterhouvermoë van die grond kan bepaal, is korrelasies getrek tussen tekstuur komponente en waterhouvermoë van onversteurde monsters, rubberring monsters en gekompakteerde monsters tussen 5 en 100 kPa en tussen 10 en 100 kPa. Die data is verwerk met die SAS uitgawe 6.12 (SAS, 1990) om modelle vir die voorspelling van volumetriese waterinhoud en waterhouvermoë van grond met behulp van maklik kwantifiseerbare grondtekstuur veranderlikes te ontwikkel. Die volumetriese waterinhoud van rubberring monsters by 5 kPa was meer as die volumetriese waterinhoud van onversteurde monsters by 5 kPa. Die volumetriese waterinhoud van rubberring monsters by 5 kPa en die volumetriese waterinhoud van onversteurde monsters by 5 kPa is gekorreleerd met 87%. Die volumetriese waterinhoud van gekompakteerde monsters by 5 kPa het 'n korrelasie van 85% met volumetriese waterinhoud van onversteurde monsters getoon. By 10 kPa, was die graad van korrelasie tussen volumetriese waterinhoud bepaal met rubberring monsters en onversteurde monsters, 77%. Dit was omtrent dieselfde as die graad van korrelasie tussen volumetriese waterinhoud van gekompakteerde monsters en onversteurde monsters by 10 kPa. By 100 kPa het die meeste van die rubberring monsters se volumetriese waterinhoud onderkant die 1:1 lyn van die volumetriese waterinhoud by 100 kPa van al die onversteurde monsters. Die volumetriese waterinhoud van al die gekompakteerde monsters was hoër as die van die onversteurde monsters. Die waterhouvermoë van al die rubberring monsters tussen 5 en 100 kPa was groter as die van die onversteurde monsters tussen 5 en 100 kPa. Die rubberring monsters het dus oor die algemeen die grootte van die waterhouvermoë oorskry. Die waterhouvermoë van die meeste van die rubberring monsters tussen 10 en 100 kPa was groter as die waterhouvermoë van die onversteurde monsters. Die waterhouvermoë van gekompakteerde monsters tussen 5 en 100 kPa was minder as die waterhouvermoë van die onversteurde monsters tussen 5 en 100 kPa. Die waterhouvermoë van gekompakteerde grondmonsters is dus onderskat. Die resultate van hierdie studie het die invloed van klei- en slik- inhoud op die volumetriese waterinhoud van onversteurde monsters, rubberring monsters en gekompakteerde monsters bevestig. Die invloed van klei en sand op die volumetriese waterinhoud van onversteurde monsters, rubberring monsters en gekompakteerde monsters het toegeneem soos die matriks potensiaal op die onderskeie monsters toegeneem het. Die invloed van fynsand op die volumetriese waterinhoud van onversteurde monsters, rubberring monsters en gekompakteerde monsters was die grootste by 5 kPa en het afgeneem tot by 100 kPa. Die mediumsand inhoud van onversteurde monsters, rubberring monsters en gekompakteerde monsters het van al die tekstuur komponente die grootste invloed op die volumetriese waterinhoud van al die monsters by 5 kPa en 10 kPa gehad. Die waterhouvermoë van onversteurde monsters, rubberring monsters en gekompakteerde monsters tussen 5 en 100 kPa is grootliks beinvloed deur die fynsand inhoud van die monsters. Die mediumsand inhoud van die monsters het ook 'n invloed gehad op die waterhouvermoë daarvan. Om die volumetriese waterinhoud van onversteurde monsters by 5, 10 en 100 kPa te voorspel, is onafhanklike veranderlikes soos fynsand inhoud, vierkantswortel van mediumsand inhoud en In van mediumsand inhoud bepaal. In die geval van modelle om die volumetriese waterinhoud van rubberring monsters by 5, 10 en 100 kPa te voorspel, is dieselfde veranderlikes gebruik as onafhanklike veranderlikes. Addisionele veranderlikes soos slik inhoud, In van slik inhoud, die vierkantswortel van die klei plus slik inhoud en die mediumsand inhoud is ook gebruik. Om die volumetriese waterinhoud van gekompakteerde monsters by 5, 10 en 100 kPa te voorspel, is die terme slik inhoud, klei plus slik inhoud, e-klei plus slik inhoud, mediumsand inhoud en vierkantswortel van mediumsand inhoud gebruik. Die modelle om volumetriese waterinhoud van rubberring samples te voorspel het die akkuraatste voorspellings gegee. Die finale modelle, om waterhouvermoë van alle monsters tussen 5 en 100 kPa en tussen 10 en 100 kPa te bepaal, het slegs fyn en mediumsand as onafhanklike veranderlikes gebruik. Grondtekstuur komponente speel dus 'n belangrike rol in die volumetriese waterinhoud van onversteurde monsters, rubberring monsters en gekompakteerde monsters by 5, 10 en 100 kPa. Die grootte van die waterhouvermoë tussen 5 en 100 kPa en tussen 10 en 100 kPa is ook beinvloed deur die grondtekstuur. Die modelle wat ontwikkel is om die volumetriese waterinhoud van monsters by 5, 10 en 100 kPa en die grootte van die waterhouvermoë tussen 5 en 100 kPa en tussen 10 and 100 kPa te voorspel, kan baie waardevol wees. Tyd en geld kan potensieel bespaar word. Die modelle wat hoogs aanbevole is, is die modelle vir onversteurde monsters. Die modele is: By 5 kPa, VWlo = 0.47259 - 0.04712 rnedlumsand?" By 10 kPa, VWlo = 0.41292 - 0.04221 mediumsando.s By 100 kPa, VWlo = 0.48080 - 0.00254 fynsand - 0.0865 In mediumsand Tussen 5 en 100 kPa, WHVo = -29.523 + 3.394 fynsand Tussen 10 en 100 kPa, WHVo = -891.794 + 232.326 In fynsand + 38.006 In mediumsand

Drought is the most severe disaster compared to other disasters in human civilization and their impacts are serious which can cause hungur, thrist, food shortages, loss of livestock directly effects the human life. The main objective of this project is to develop an early warning system (EWS) [3] for drought indices by using wireless sensor networks (WSNs) which is the only way forward for an on-site monitoring and validation of locally defined drought indices [3].The designed wireless sensor network (WSN) consisting of a sensor unit, a master unit and a sensor power management unit (PMU). The sensor unit measures the moisture of the soil and transmitt the measured data through ZigBee module to the master unit. A real time clock (RTC) is also used in the sensor unit which records the information of second, minute, hour, day, month of day and year about when or what time the measurement taken. The master unit consisting of a SD-card and Bluetooth module. SD-card is used to store measured data from other sensor units and it is possible to take out the reading of measured data from the master unit by accessing the SD-card via Bluetooth inside the master unit to a PC or a smartphone mobile.To manage the power in the sensor unit and to make sensor alive for several years, the power management unit (PMU) manages the power level between two energy storage buffers (i.e., a supercapacitor and a Li+ ion battery) for a sensor node.

Unsaturated hydraulic conductivity was measured using four different methods. Tension permeameters were used to measure unsaturated hydraulic conductivity in the field, using a single disc method, which depends on the measurements of sorptivity, steady state flow rate, initial and final water content (White and Perroux, 1987, 1989). Also, a double disc method was used which utilizes Wooding's (1968) equation for two different disc radii at the same tension for steady state flow rates. Undisturbed and disturbed soil cores were used to measure unsaturated hydraulic conductivity in the lab, using water retention curves with van Genuchten's equations. There were no significant differences in the mean of hydraulic conductivity between single and double disc methods in all the tensions used (0, 5, 10 and 15 cm). There were significant differences between the field methods and undisturbed soil cores in zero cm tension, and disturbed soil cores in 10 and 15 cm tension. The effect of land preparation on the unsaturated hydraulic conductivity was studied using the double disc method. Tilling has significant effects on the unsaturated hydraulic conductivity at all tensions used. The spatial variation of unsaturated hydraulic conductivity and steady state flow in different tensions using the double disc method was studied. We found exponential variogram models for unsaturated hydraulic conductivity at 5, 10 and 15 cm tensions and a random model for zero cm tension. Also, exponential models were best fitted for steady state flow corresponding to pores radii of 0.03 - 0.015 cm, 0.015 - 0.010 cm and steady state flow at 10 cm tension. A Michaelis-Menton model was used for steady state flow at 5 cm and 15 cm tension. Disc permeameters were also used to add 5 cm depth of water, bromide and dye solution at 0, 5, 10 and 15 cm tensions with three replicates. A comparison was made between field data and simulated model under the same boundary and initial conditions as in the field. Results showed that the water and bromide move deeper than the prediction of the simulated model in all tensions used. The differences were larger between simulated model and field data for both water and bromide concentrations in the lower tension and smaller in the higher tension as a result of elimination of some preferential flow paths. An equation was developed for cumulative infiltration valid for both small and large time. The parameters calculated using the developed equation closely matched the measured infiltration, and fit better than a three term series similar to the Philip equation for one-dimensional flow.

The feasibility of synthesizing distributed fields of remotely-sensed soil moisture by the novel application of four-dimensional data assimilation applied in a hydrological model was explored in this study. Six Push Broom Microwave Radiometer images gathered over Walnut Gulch, Arizona were assimilated into the TOPLATS hydrological model. Several alternative assimilation procedures were implemented, including a method that adjusted the statistics of the modeled field to match those in the remotely sensed image, and the more sophisticated, traditional methods of statistical interpolation and Newtonian nudging. The high observation density characteristic of remotely-sensed imagery poses a massive computational burden when used with statistical interpolation, necessitating observation reduction through subsampling or averaging. For Newtonian nudging, the high observation density compromises the conventional weighting assumptions, requiring modified weighting procedures. Remotely-sensed soil moisture images were found to contain horizontal correlations that change with time and have length scales of several tens of kilometers, presumably because they are dependent on antecedent precipitation patterns. Such correlation therefore has a horizontal length scale beyond the remotely sensed region that approaches or exceeds the catchment scale. This suggests that remotely-sensed information can be advected beyond the image area and across the whole catchment. The remotely-sensed data was available for a short period providing limited opportunity to investigate the effectiveness of surface-subsurface coupling provided by alternative assimilation procedures. Surface observations were advected into the subsurface using incomplete knowledge of the surface-subsurface correlation measured at only 2 sites. It is perceived that improved vertical correlation specification will be a need for optimal soil moisture assimilation. Based on direct measurement comparisons and the plausibility of synthetic soil moisture patterns, Newtonian nudging assimilation procedures were preferred because they preserved the observed patterns within the sampled region, while also calculating plausible patterns in unmeasured regions. Statistical interpolation reduced to the trivial limit of direct data insertion in the sampled region and gave less plausible patterns outside this region. Matching the statistics of the modeled fields to those observed provided plausible patterns, but the observed patterns within sampled area were largely lost.

In Chapter 1, a numerical computer technique is developed to determine radiation view factors between planar surfaces whose geometry is sufficiently regular so as to be defined by algebraic equations. This technique does not require spherical, cylindrical or rectangular symmetry, although such symmetries may be exploited when they exist. Once the essential geometric problem is formulated, enough generality can be built into the solutions so that certain "new" configurations, derived from translations or rotations of one surface relative to the other, can be solved as a matter of course. In Chapter 2, a model of bare soil evaporation is tested against measured flux from lysimeters obtained in the Peace River region of British Columbia and Alberta. Hydraulic diffusivity characteristics, measured from separate, adjacent field samples, were used in the model. Certain procedural difficulties in the measurement of hydraulic diffusivity are examined in detail, and recommendations for improvement are made. The degree to which evaporation simulation agrees with measured flux is discussed.
Land and Food Systems, Faculty of
Graduate

This project objective evaluated the potential of improving linked weather-and-mobility model predictions by blending soil moisture observations from a Cosmic-ray Soil Moisture Observing System (COSMOS) sensor with weather-informed predictions of soil moisture and soil strength from the Geospatial Weather-Affected Terrain Conditions and Hazards (GeoWATCH). Assimilating vehicle-borne COSMOS observations that measure local effects model predictions of soil moisture offered potential to produce more accurate soil strength and vehicle mobility forecast was the hypothesis. This project compared soil moisture observations from a COSMOS mobile sensor driven around an area near Iowa Falls, IA, with both GeoWATCH soil moisture predictions and in situ probe observations. The evaluation of the COSMOS rover data finds that the soil moisture measurements contain a low measurement bias while the GeoWATCH estimates more closely matched the in situ data. The COSMOS rover captured a larger dynamic range of soil moisture conditions as compared to GeoWATCH, capturing both very wet and very dry soil conditions, which may better flag areas of high risk for mobility considerations. Overall, more study of the COSMOS rover is needed to better understand sensor performance in a variety of soil conditions to determine the feasibility of assimilating the COSMOS rover estimates into GeoWATCH.

A soil moisture retrieval method is proposed, in the absence of ground-based auxiliary measurements, by deriving the soil moisture content relationship from the satellite vegetation index-based evapotranspiration fraction and soil moisture physical properties of a soil type. A temperature–vegetation dryness index threshold value is also proposed to identify water bodies and underlying saturated areas. Verification of the retrieved growing season soil moisture was performed by comparative analysis of soil moisture obtained by observed conventional in situ point measurements at the 239-km2 Reynolds Creek Experimental Watershed, Idaho, USA (2006–2009), and at the US Climate Reference Network (USCRN) soil moisture measurement sites in Sundance, Wyoming (2012–2015), and Lewistown, Montana (2014–2015). The proposed method best represented the effective root zone soil moisture condition, at a depth between 50 and 100 cm, with an overall average R2 value of 0.72 and average root mean square error (RMSE) of 0.042.

Drip irrigation has the potential of high water use efficiency, but actual water measurement is difficult because of the limited wetted volume. Two long-term experiments in orchards in Israel and in California and several field crop studies supported by this project have demonstrated the feasibility of precise monitoring of soil water distribution for drip irrigation in spite of the limited soil wetting. Time Domain Reflectometry (TDR) enables in situ measurement of soil water content of well defined small volumes. Several approaches were tried in monitoring the soil water balance in the field during drip irrigation. These also facilitated the estimation of water uptake: 1. The use of multilevel moisture probe TDR system. This approach proved to be of limited value because of the extremely small diameter of measurement. 2. The placement of 20 cm long TDR probes at predetermined distances from the drippers in citrus orchards. 3. Heavy instrumentation with neutron scattering access tubes and tensiometers of a single drip irrigated almond tree. 4. High resolution spatial and temporal measurements (0.1m x 0.1m grid) of water content by TDR in corn irrigated by surface and subsurface drip. The latter approach was accompanied by parametric modelling of water uptake intensity patterns by corn roots and superimposed with analytical solutions for water flow from point and line sources. All this lead to general and physically based suggestions for the placement of soil water sensors for scheduling drip irrigation.

The underlying similarity between soils, grains, fertilizers, concentrated animal feed, pellets, and mixtures is that they are all granular materials used in agriculture. Modeling such materials is a complex process due to the spatial variability of such media, the origin of the material (natural or biological), the nonlinearity of these materials, the contact phenomenon and flow that occur at the interface zone and between these granular materials, as well as the dynamic effect of the interaction process. The lack of a tool for studying such materials has limited the understanding of the phenomena relevant to them, which in turn has led to energy loss and poor quality products. The objective of this study was to develop a reliable prediction simulation tool for cohesive agricultural particle materials using Discrete Element Modeling (DEM). The specific objectives of this study were (1) to develop and verify a 3D cohesionless agricultural soil-tillage tool interaction model that enables the prediction of displacement and flow in the soil media, as well as forces acting on various tillage tools, using the discrete element method; (2) to develop a micro model for the DEM formulation by creating a cohesive contact model based on liquid bridge forces for various agriculture materials; (3) to extend the model to include both plastic and cohesive behavior of various materials, such as grain and soil structures (e.g., compaction level), textures (e.g., clay, loam, several grains), and moisture contents; (4) to develop a method to obtain the parameters for the cohesion contact model to represent specific materials. A DEM model was developed that can represent both plastic and cohesive behavior of soil. Soil cohesive behavior was achieved by considering tensile force between elements. The developed DEM model well represented the effect of wedge shape on soil behavior and reaction force. Laboratory test results showed that wedge penetration resistance in highly compacted soil was two times greater than that in low compacted soil, whereas DEM simulation with parameters obtained from the test of low compacted soil could not simply be extended to that of high compacted soil. The modified model took into account soil failure strength that could be changed with soil compaction. A three dimensional representation composed of normal displacement, shear failure strength and tensile failure strength was proposed to design mechanical properties between elements. The model based on the liquid bridge theory. An inter particle tension force measurement tool was developed and calibrated A comprehensive study of the parameters of the contact model for the DEM taking into account the cohesive/water-bridge was performed on various agricultural grains using this measurement tool. The modified DEM model was compared and validated against the test results. With the newly developed model and procedure for determination of DEM parameters, we could reproduce the high compacted soil behavior and reaction forces both qualitatively and quantitatively for the soil conditions and wedge shapes used in this study. Moreover, the effect of wedge shape on soil behavior and reaction force was well represented with the same parameters. During the research we made use of the commercial PFC3D to analyze soil tillage implements. An investigation was made of three different head drillers. A comparison of three commonly used soil tillage systems was completed, such as moldboard plow, disc plow and chisel plow. It can be concluded that the soil condition after plowing by the specific implement can be predicted by the DEM model. The chisel plow is the most economic tool for increasing soil porosity. The moldboard is the best tool for soil manipulation. It can be concluded that the discrete element simulation can be used as a reliable engineering tool for soil-implement interaction quantitatively and qualitatively.

Bulk quantitative mineralogy of regolith is a useful indicator of lithological precursor (protolith), degree of weathering, and soil properties affecting various potential landuse decisions. To date, no national-scale maps of regolith mineralogy are available in Australia. Catchment outlet sediments collected over 80% of the continent as part of the National Geochemical Survey of Australia (NGSA) afford a unique opportunity to rapidly and cost-effectively determine regolith mineralogy using the archived sample material. This report releases mineralogical data and metadata obtained as part of a feasibility study in a selected pilot area for such a national regolith mineralogy database and atlas. The area chosen for this study is within the Darling-Curnamona-Delamerian (DCD) region of southeastern Australia. The DCD region was selected as a ‘deep-dive’ data acquisition and analysis by the Exploration for the Future (2020-2024) federal government initiative managed at Geoscience Australia. One hundred NGSA sites from the DCD region were prepared for X-Ray Diffraction (XRD) analysis, which consisted of qualitative mineral identification of the bulk samples (i.e., ‘major’ minerals), qualitative clay mineral identification of the <2 µm grain-size fraction, and quantitative analysis of both ‘major’ and clay minerals of the bulk sample. The identified mineral phases were quartz, plagioclase, K-feldspar, calcite, dolomite, gypsum, halite, hematite, goethite, rutile, zeolite, amphibole, talc, kaolinite, illite (including muscovite and biotite), palygorskite (including interstratified illite-smectite and vermiculite), smectite (including interstratified illite-smectite), vermiculite, and chlorite. Poorly diffracting material (PDM) was also quantified and reported as ‘amorphous’. Mineral identification relied on the EVA® software, whilst quantification was performed using Siroquant®. Resulting mineral abundances are reported with a Chi-squared goodness-of-fit between the actual diffractogram and a modelled diffractogram for each sample, as well as an estimated standard error (esd) measurement of uncertainty for each mineral phase quantified. Sensitivity down to 0.1 wt% (weight percent) was achieved, with any mineral detection below that threshold reported as ‘trace’. Although detailed interpretation of the mineralogical data is outside the remit of the present data release, preliminary observations of mineral abundance patterns suggest a strong link to geology, including proximity to fresh bedrock, weathering during sediment transport, and robust relationships between mineralogy and geochemistry. The mineralogical data generated by this study are presented in Appendix A of this report and are downloadable as a .csv file. Mineral abundance or presence/absence maps are shown in Appendices B and C to document regional mineralogical patterns.