Experimental Design and Initial Results from the Mahurangi River Variability Experiment: MARVEX

Woods, Ross; Grayson, Rodger B.; Western, Andrew W.; Duncan, Maurice J.; Wilson, David J.; Young, R.; Ibbitt, Richard P.; Henderson, Roddy; McMahon, TA

doi:10.1029/ws003p0201

Cited by 40 publications

(48 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Soil Moisture Patterns At Mahurangimentioning

confidence: 99%

“…The total catchment drains 50 km 2 of steep hills and gently rolling lowlands located 70 km north of Auckland [121]. ''Satellite Station'' is a sub-catchment of approximately 1 km 2 in area, covered largely by pasture and is one of several intensively monitored areas within the MARVEX (see Woods et al [121] for details of the experimental set up). Six soil moisture patterns were collected over the top 30 cm of soil (the root zone for this vegetation) on a 40m Â 40 m grid using the TDR equipped all terrain vehicle discussed above [25,96,110].…”

Section: Soil Moisture Patterns At Mahurangimentioning

confidence: 99%

“…[96]). This approach has been used at a number of locations including the 10 ha Tarrawarra catchment in Australia [110], the 50 km 2 Mahurangi catchment in New Zealand [121], at Nerrigundah in Australia [108], at Weiherbach in Germany [4,24,69], at Dartmoor, England [76] and sampling associated with the Southern Great Plains experiments in the United States [77]. Also, the general interest in spatial patterns, and availability of rapid position fixing via GPS, has made it more common to collect patterns of even ''traditional'' data such as snow depth or snow density.…”

Section: Lots Of Pointsmentioning

confidence: 99%

See 2 more Smart Citations

Advances in the use of observed spatial patterns of catchment hydrological response

Grayson

Blöschl

Western

et al. 2002

Advances in Water Resources

214

181

View full text Add to dashboard Cite

Section: Soil Moisture Patterns At Mahurangimentioning

confidence: 99%

Section: Soil Moisture Patterns At Mahurangimentioning

confidence: 99%

Section: Lots Of Pointsmentioning

confidence: 99%

See 1 more Smart Citation

Advances in the use of observed spatial patterns of catchment hydrological response

Grayson

Blöschl

Western

et al. 2002

Advances in Water Resources

214

181

View full text Add to dashboard Cite

“…[3] While there have been several studies on the spatial and temporal variability of soil moisture, these have been either large-scale intensive experiments for short periods (weeks) of time, such as the Southern Great Plains (SGP) [e.g., Famiglietti et al, 1999] and Soil Moisture Experiments (SMEX) series [e.g., Jacobs et al, 2004a] experiments, or medium-term (years) detailed studies of small areas, such as the Tarrawarra [Western et al, 1999], Nerrigundah [Walker et al, 2001], and Mahurangi experiments [Woods et al, 2001]. What has been missing to date is a long-term detailed experiment for a large area encapsulating a range of land cover, land use, and soil type conditions.…”

Section: Introductionmentioning

confidence: 99%

Goulburn River experimental catchment data set

Rüdiger

Hancock

Hemakumara

et al. 2007

Water Resources Research

View full text Add to dashboard Cite

This paper describes the data set from the 6540‐km2 Goulburn River experimental catchment in New South Wales, Australia. Data have been archived from this experimental catchment since its inception in September 2002. Land use in the northern half of the catchment is predominantly cropping and grazing on basalt‐derived soils, with the south being cattle and sheep grazing on sandstone‐derived soils; only the floodplains are cleared of trees in the south. Monitoring sites are mainly concentrated in the nested Merriwa (651 km2) and Krui (562 km2) subcatchments in the northern half of this experimental catchment with a few monitoring sites located in the south. The data set comprises soil temperature and moisture profile measurements from 26 locations; meteorological data from two automated weather stations (data from a further three stations are available from other sources) including precipitation, atmospheric pressure, air temperature and relative humidity, wind speed and direction, soil heat flux, and up‐ and down‐welling short‐ and long‐wave radiation; streamflow observations at five nested locations (data from a further three locations are available from other sources); a total of three surface soil moisture maps across a 40 km × 50 km region in the north from ∼200 measurement locations during intensive field campaigns; and a high‐resolution digital elevation model (DEM) of a 175‐ha microcatchment in the Krui catchment. These data are available on the World Wide Web at http://www.sasmas.unimelb.edu.au.

show abstract

“…The climate is warm and humid with an average annual precipitation of 160 cm and an average annual PET of 130 cm. The soil at Satellite Station can be up to a meter deep and varies in texture from the hillslopes to the valley bottoms (Woods et al, 2001). The soil on the hillslopes is silty clay loam, while the soil in the valley bottoms is predominately clay.…”

Section: Catchment Descriptionsmentioning

confidence: 99%

Evaluation of sampling techniques to characterize topographically-dependent variability for soil moisture downscaling

Werbylo

Niemann

2014

Journal of Hydrology

View full text Add to dashboard Cite

EVALUATION OF SAMPLING TECHNIQUES TO CHARACTERIZE TOPOGRAPHICALLY-DEPENDENT VARIABILITY FOR SOIL MOISTURE DOWNSCALINGSoil moisture patterns are an important consideration in many catchment-scale hydrologic applications. Unfortunately, estimating soil moisture patterns at resolutions that are appropriate for these applications (e.g., grid cells with a linear dimension of 10 to 50 m) is difficult. Downscaling methods can be used to estimate catchment-scale soil moisture patterns from coarser resolution estimates or spatial average soil moisture values. These methods usually infer the fine-scale variability in soil moisture using variations in ancillary variables like topographic attributes that have relationships to soil moisture. Previously, such relationships have been observed in catchments using soil moisture observations taken on uniform grids at hundreds of locations on multiple dates, but collecting data in this manner limits the applicability of this approach. The objective of this paper is to evaluate the effectiveness of two strategic sampling techniques for characterizing the relationships between topographic attributes and soil moisture for the purpose of constraining downscaling methods. The strategic sampling methods considered are conditioned Latin hypercube sampling (cLHS) and stratified random sampling (SRS). Each sampling method is used to select a limited number of locations and/or dates for soil moisture monitoring at three catchments with detailed soil moisture datasets (Tarrawarra, Satellite Station, and Cache la Poudre). These samples are then used to calibrate two available downscaling methods, and the effectiveness of the sampling methods is evaluated by the ability iii of the downscaling methods to reproduce the known soil moisture patterns at the catchments.The results show that cLHS and SRS can characterize the relationships between soil moisture and ancillary topographic variables with many fewer locations and dates than previously used.

show abstract

Experimental Design and Initial Results from the Mahurangi River Variability Experiment: MARVEX

Cited by 40 publications

References 13 publications

Advances in the use of observed spatial patterns of catchment hydrological response

Advances in the use of observed spatial patterns of catchment hydrological response

Goulburn River experimental catchment data set

Evaluation of sampling techniques to characterize topographically-dependent variability for soil moisture downscaling

Contact Info

Product

Resources

About