http://nova.newcastle.edu.au/vital/access/services/Feed ${session.getAttribute("locale")} 5 http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:10806 It is well documented that capacitance-based soil moisture sensor measurements are particularly influenced by particle size distribution, density, salinity, and temperature of a soil, in addition to its moisture content. Moreover, the equations provided by manufacturers of soil moisture sensors are often only applicable to a limited number of soil types, thus yielding significant errors when compared with gravimetric measurements for observations in real soils. This limitation makes site-specific calibrations of such sensors necessary. Consequently, development of a general equation provides the possibility to derive the needed parameters from information such as soil type or particle size distribution. This paper describes the development of a general equation for the Campbell Scientific CS616 Water Content Reflectometers using data from sensors installed throughout the Goulburn River experimental catchment. It is subsequently tested using monitoring sites in the Murrumbidgee Soil Moisture Monitoring Network, which were not part of the original development; both monitoring networks are located in south-eastern Australia. Previously developed equations for temperature correction and soil moisture estimation using the Campbell Scientific CS615 Water Content Reflectometer are adapted to the new CS616 sensor. Moreover, relationships between readily available soil properties and the parameters of the general equations are derived. It is shown that the general equations developed here can be applied to data collected in the field using only information on the soil particle size distribution with an RMSE of around 6% m³/m³ (<1% m³/m³ under laboratory conditions; which is a significant improvement in comparison to 14% m³/m³ when using the manufacturer’s equations). 2012-05-16T04:40:03.889Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:7149 Soil moisture will be mapped globally by the European Soil Moisture and Ocean Salinity (SMOS) mission to be launched in 2009. The expected soil moisture accuracy will be 4.0 %v/v. The core component of the SMOS soil moisture retrieval algorithm is the L-band Microwave Emission of the Biosphere (L-MEB) model which simulates the microwave emission at L-band from the soil–vegetation layer. The model parameters have been calibrated with data acquired by tower mounted radiometer studies in Europe and the United States, with a typical footprint size of approximately 10 m. In this study, aircraft L-band data acquired during the National Airborne Field Experiment (NAFE) intensive campaign held in South-eastern Australia in 2005 are used to perform the first evaluation of the L-MEB model and its proposed parameterization when applied to coarser footprints (62.5 m). The model could be evaluated across large areas including a wide range of land surface conditions, typical of the Australian environment. Soil moisture was retrieved from the aircraft brightness temperatures using L-MEB and ground measured ancillary data (soil temperature, soil texture, vegetation water content and surface roughness) and subsequently evaluated against ground measurements of soil moisture. The retrieval accuracy when using the L-MEB ‘default’ set of model parameters was found to be better than 4.0 %v/v only over grassland covered sites. Over crops the model was found to underestimate soil moisture by up to 32 %v/v. After site specific calibration of the vegetation and roughness parameters, the retrieval accuracy was found to be equal or better than 4.8 %v/v for crops and grasslands at 62.5-m resolution. It is suggested that the proposed value of roughness parameter HR for crops is too low, and that variability of HR with soil moisture must be taken into consideration to obtain accurate retrievals at these scales. The analysis presented here is a crucial step towards validating the application of L-MEB for soil moisture retrieval from satellite observations in an operational context. 2011-02-02T23:10:21.552Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:6225 Revegetation is the preferred method for rehabilitating degraded riparian lands by government agencies, landcare groups and landowners across Australia. Increased scientific involvement is necessary because most revegetation works rely on ad-hoc recipes, while the interaction of riparian vegetation with flow and sediment in rivers is an area of growing interest in fluvial geomorphology. This paper compares bare, partial and fully vegetated streambanks in order to make recommendations for bank protection works using vegetation, as well as examining the effect of reach scale variations in vegetation coverage on flow dynamics. Experiments are conducted using a reduced scale model of a natural river undergoing vegetative rehabilitation. Our hypothesis is that partial coverage can offer a similar level of protection to a fully vegetated bank face. A comparative analysis of each experiment is presented which includes depth average velocities and bed shear stresses as indicators of erosion potential. With the current emphasis on vegetative rehabilitation techniques the experiments offer potentially useful insights into more effective planting. 2010-05-11T04:20:20.096Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:1426 Source control measures include rainwater tanks, infiltration trenches, grassed swales, detention basins and constructed wetlands that can be used in housing allotments and subdivisions. A methodology for evaluating the regional economic benefits due to implementation of source control measures is presented and illustrated for two case studies in the Lower Hunter and Central Coast regions of New South Wales, Australia. It is demonstrated that use of rainwater tanks to supplement mains water supply for toilet, hot water and outdoor uses can very significantly reduce demand on mains water supply. Reductions in regional water demand will enable deferment of water supply headworks augmentation, while reductions in peak mains water demand will extend the life of water supply distribution infrastructure. In addition, substantial reduction of stormwater discharge from allotments can be realised. For the Lower Hunter region with an urban population of about 450,000 it is shown that construction of new water supply headworks infrastructure can be delayed by up to 34 years. Compared with the traditional provision of mains water and stormwater disposal, the use of rainwater tanks along with other source control measures can produce present worth savings to the Lower Hunter region conservatively estimated to be up to $67 million. Similar results were found for the Central Coast region. 2010-04-27T06:50:33.235Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:863 The Kalman filter data assimilation technique is applied to a distributed three-dimensional soil moisture model for retrieval of the soil moisture profile in a 6 ha catchment using near-surface soil moisture measurements. A simplified Kalman filter covariance forecasting methodology is developed based on forecasting of the state correlations and imposed state variances. This covariance forecasting technique, termed the modified Kalman filter, was then used in a 1 month three-dimensional field application. Two updating scenarios were tested: (1) updating every 2 to 3 days and (2) a single update. The data used were from the Nerrigundah field site, near Newcastle, Australia. This study demonstrates the feasibility of data assimilation in a quasi three-dimensional distributed soil moisture model, provided simplified covariance forecasting techniques are used. It also identifies that (1) the soil moisture profile cannot be retrieved from near-surface soil moisture measurements when the near-surface and deep soil layers become decoupled, such as during extreme drying events; (2) if simulation of the soil moisture profile is already good, the assimilation can result in a slight degradation, but if the simulation is poor, assimilation can yield a significant improvement; (3) soil moisture profile retrieval results are independent of initial conditions; and (4) the required update frequency is a function of the errors in model physics and forcing data. 2010-04-27T06:23:11.197Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:862 The Kalman filter assimilation technique is applied to a simplified soil moisture model for retrieval of the soil moisture profile from near-surface soil moisture measurements. First, the simplified soil moisture model is developed, based on an approximation to the Buckingham–Darcy equation. This model is then used in a 12-month one-dimensional field application, with updating at 1-, 5-, 10-, and 20-day intervals. The data used are for the Nerrigundah field site, New South Wales, Australia. This study has identified (i) the importance of knowing the depth over which the near-surface soil moisture measurements are representative (i.e., observation depth), (ii) soil porosity and residual soil moisture content as the most important soil parameters for correct retrieval of the soil moisture profile, (iii) the importance of a soil moisture model that represents the dominant soil physical processes correctly, and (iv) an appropriate forecasting model as far more important than the temporal resolution of near-surface soil moisture measurements. Although the soil moisture model developed here is a good approximation to the Richards equation, it requires a root water uptake term or calibration to an extreme drying event to model extremely dry periods at the field site correctly. 2010-04-27T06:23:06.401Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:2580 Figtree Place is a water sensitive urban redevelopment consisting of 27 residential units located in Hamilton, an inner suburb of Newcastle, NSW, Australia. The site uses rainwater stored in tanks to supply hot water and toilet flushing demand. A two-year monitoring program for roofwater, tanks and hot water systems revealed that water quality improves in the roof to tank to hot water system treatment chain. Analysis of water quality from hot water systems and rainwater tanks showed compliance with the Australian Drinking Water Guidelines. 2010-04-27T06:18:01.061Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:160 [1] The water table fluctuation method for determining recharge from precipitation and water table measurements was originally developed on an event basis. Here a new multievent time series approach is presented for inferring groundwater recharge from longterm water table and precipitation records. Additional new features are the incorporation of a variable specific yield based upon the soil moisture retention curve, proper accounting for the Lisse effect on the water table, and the incorporation of aquifer drainage so that recharge can be detected even if the water table does not rise. A methodology for filtering noise and non- rainfall- related water table fluctuations is also presented. The model has been applied to 2 years of field data collected in the Tomago sand beds near Newcastle, Australia. It is shown that gross recharge estimates are very sensitive to time step size and specific yield. Properly accounting for the Lisse effect is also important to determining recharge. 2010-04-27T05:56:50.101Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:308 In order to assess performance and to improve predictions, land surface models are routinely calibrated against measurements of either latent heat or sensible heat fluxes. Generally, little regard is given to the multi-output nature of these models, resulting in a model evaluation that is inherently biased towards the calibration variable. In this paper, an assessment strategy that accounts for multiple outputs is explored and an examination of incorporating alternative sources of information to assess performance is undertaken. The benefits of such a multi-objective calibration framework are illustrated through comparison with traditional single objective calibration. Results indicate that combining different observation data streams for calibration purposes assists in producing a more robust process model and provides improved surface flux predictions. Further, the utility of using correlated, if not commensurate, sources of data, is demonstrated through analysis of a time series of surface temperature measurements. (C) 2004 Elsevier B.V. All rights reserved. 2010-04-27T05:49:05.176Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:3481 A number of automated techniques for point measurement of soil moisture content have been developed to an operational level over the past few decades. While each of those techniques have been individually evaluated by the thermogravimetric (oven drying and weighing) method, typically under laboratory conditions, there have been few studies which have made a direct comparison between the various techniques, particularly under field conditions. This paper makes an inter-comparison of the Virrib®, Campbell Scientific CS615 reflectometer, Soil Moisture Equipment Corporation TRASE® buriable- and connector-type time domain reflectometry (TDR) soil moisture sensors, and a comparison of the connector-type TDR sensor with thermogravimetric measurements for data collected during a 2-year field study. Both qualitative and quantitative comparisons between the techniques are made, and comparisons made with results from a simple water balance 'bucket' model and a Richards equation based model. It was found that the connector-type TDR sensors produced soil moisture measurements within the ±2.5% v/v accuracy specification of the manufacturer as compared to thermogravimetric data when using the manufacturer's calibration relationship. However, comparisons with the water balance model showed that Virrib and buriable-type TDR sensors yielded soil moisture changes that exceeded rainfall amounts during infiltration events. It was also found that the CS615 reflectometer yielded physically impossible soil moisture measurements (greater than the soil porosity) during periods of saturation. Moreover, the buriable-type TDR measurements of soil moisture content were systematically less than the Virrib measurements by approximately 10% v/v. In addition to the good agreement with thermogravimetric measurements, the connector-type TDR soil moisture measurements yielded the best agreement with Richards equation based model predictions of soil moisture content, with Virrib sensors yielding a poor agreement in the deeper layers. This study suggests that connector-type TDR sensors give the most accurate measurements of soil moisture content out of the sensor types tested. 2010-04-27T05:29:14.423Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:4400 The National Airborne Field Experiment 2005 (NAFE'05) and the Campaign for validating the Operation of Soil Moisture and Ocean Salinity (CoSMOS) were undertaken in November 2005 in the Goulburn River catchment, which is located in southeastern Australia. The objective of the joint campaign was to provide simulated Soil Moisture and Ocean Salinity (SMOS) observations using airborne L-band radiometers supported by soil moisture and other relevant ground data for the following: (1) the development of SMOS soil moisture retrieval algorithms; (2) developing approaches for downscaling the low-resolution data from SMOS; and (3) testing its assimilation into land surface models for root zone soil moisture retrieval. This paper describes the NAFE'05 and CoSMOS airborne data sets together with the ground data collected in support of both aircraft campaigns. The airborne L-band acquisitions included 40 km times 40 km coverage flights at 500-m and 1-km resolution for the simulation of a SMOS pixel, multiresolution flights with ground resolution ranging from 1 km to 62.5 m, multiangle observations, and specific flights that targeted the vegetation dew and sun glint effect on L-band soil moisture retrieval. The L-band data were accompanied by airborne thermal infrared and optical measurements. The ground data consisted of continuous soil moisture profile measurements at 18 monitoring sites throughout the 40 km times 40 km study area and extensive spatial near-surface soil moisture measurements concurrent with airborne monitoring. Additionally, data were collected on rock coverage and temperature, surface roughness, skin and soil temperatures, dew amount, and vegetation water content and biomass. These data are available at www.nafe.unimelb.edu.au. 2010-04-27T05:27:50.380Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:5131 The National Airborne Field Experiment 2006 (NAFE'06) was conducted during a three week period of November 2006 in the Murrumbidgee River catchment, located in southeastern Australia. One objective of NAFE'06 was to explore the suitability of the area for SMOS (Soil Moisture and Ocean Salinity) calibration/validation and develop downscaling and assimilation techniques for when SMOS does come on line. Airborne L-band brightness temperature was mapped at 1 km resolution 11 times (every 1-3 days) over a 40 by 55 km area in the Yanco region and 3 times over a 40 by 50 km area that includes Kyeamba Creek catchment. Moreover, multi-resolution, multi-angle and multi-spectral airborne data including surface temperature, surface reflectance (green, read and near infrared), lidar data and aerial photos were acquired over selected areas to develop downscaling algorithms and test multi-angle and multi-spectral retrieval approaches. The near-surface soil moisture was measured extensively on the ground in eight sampling areas concurrently with aircraft flights, and the soil moisture profile was continuously monitored at 41 sites. Preliminary analyses indicate that (i) the uncertainty of a single ground measurement was typically less than 5% vol. (ii) the spatial variability of ground measurements at 1 km resolution was up to 10% vol. and (iii) the validation of 1 km resolution L-band data is facilitated by selecting pixels with a spatial soil moisture variability lower than the point-scale uncertainty. The sensitivity of passive microwave and thermal data is also compared at 1 km resolution to illustrate the multi-spectral synergy for soil moisture monitoring at improved accuracy and resolution. The data described in this paper are available at www.nafe.unimelb.edu.au. 2010-04-27T04:41:45.826Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:5300 This paper reviews methods for estimating evaporation from landscapes, regions and larger geographic extents, with remotely sensed surface temperatures, and highlights uncertainties and limitations associated with those estimation methods. Particular attention is given to the validation of such approaches against ground based flux measurements. An assessment of some 30 published validations shows an average root mean squared error value of about 50 W m⁻² and relative errors of 15–30%. The comparison also shows that more complex physical and analytical methods are not necessarily more accurate than empirical and statistical approaches. While some of the methods were developed for specific land covers (e.g. irrigation areas only) we also review methods developed for other disciplines, such as hydrology and meteorology, where continuous estimates in space and in time are needed, thereby focusing on physical and analytical methods as empirical methods are usually limited by in situ training data. This review also provides a discussion of temporal and spatial scaling issues associated with the use of thermal remote sensing for estimating evaporation. Improved temporal scaling procedures are required to extrapolate instantaneous estimates to daily and longer time periods and gap-filling procedures are needed when temporal scaling is affected by intermittent satellite coverage. It is also noted that analysis of multi-resolution data from different satellite/sensor systems (i.e. data fusion) will assist in the development of spatial scaling and aggregation approaches, and that several biological processes need to be better characterized in many current land surface models. 2010-04-27T04:33:21.848Z ]]>