Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors

Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the "rover", offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 x 36 km at 9 km resolution) and intensive (10 x 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models

Modelling Sub-daily Latent Heat Fluxes from a Small Reservoir

Abstract Accurate methods of latent heat flux quantification are essential for water management and for use in hydrological and meteorological models. Currently the effect of small lakes in most numerical weather prediction modelling systems is either entirely ignored or crudely parameterized. In order to test methods for modelling hourly latent heat flux from small water bodies, this study compares results from several modelling approaches to values measured by the eddy covariance method at an agricultural reservoir in southeast Queensland, Australia. Mass transfer estimates of LE calculated using the theoretical mass transfer model and using the Tanny et al

Modelling sub-daily latent heat fluxes from a small reservoir

Accurate methods of latent heat flux quantification are essential for water management and for use in hydrological and meteorological models. Currently the effect of small lakes in most numerical weather prediction modelling systems is either entirely ignored or crudely parameterized. In order to test methods for modelling hourly latent heat flux from small water bodies, this study compares results from several modelling approaches to values measured by the eddy covariance method at an agricultural reservoir in southeast Queensland, Australia. Mass transfer estimates of LE calculated using the theoretical mass transfer model and using the Tanny et al. (2008) and Sacks et al. (1994) bulk transfer coefficients showed the best relationship with measured values under a range of meteorological conditions. The theoretical model showed the strongest correlation with measured values, while the Tanny et al. (2008) and Sacks et al. (1994) models had regression equation slopes with the closest proximity to 1. Latent heat fluxes estimated using the Granger and Hedstrom (2011) evaporation model, that was specifically developed for use at small reservoirs, showed a poor relationship with measured values, particularly in stable atmospheric conditions. The 1-dimensional hydrodynamics model, DYRESM, was used to obtain predictions of hourly latent heat flux without the use of water surface temperature measurements. DYRESM estimates of latent heat flux showed a slightly worse relationship with measured values than those predicted using the traditional mass transfer models (which used measurements of water surface temperature). However, DYRESM performed considerably better than the Granger and Hedstrom (2011) model

Comment on ‘Examining the variation of soil moisture from cosmic‑ray neutron probes footprint: experimental results from a COSMOS‑UK site’ by Howells, O.D., Petropoulos, G.P., et al., Environ Earth Sci 82, 41 (2023)

The published article by Howells et al. (2023) attempts to empirically derive the lateral footprint for a single cosmic-ray neutron sensor (CRNS), which is part of the COSMOS-UK network (Evans et al. 2016). The main result is the “true” footprint to be 50 m in radius, substantially smaller than previously published estimates. Their conclusion contradicts more than 15 peer-reviewed studies and more than a decade of research on the subject conducted by various international research groups, and thus, it would be considered as a ground-breaking finding if the methods were scientifically sound. However, the methods and arguments presented by the authors have major errors and the presented conclusions are consequently wrong

Thermal and asphyxia exposure risk to freshwater fish in feral-pig-damaged tropical wetlands

Acute thermal and asphyxia exposure risks for freshwater fish occupying three tropical wetland typologies were examined. Field water‐quality data revealed that fish in wetlands grazed by pigs had the highest exposure risks, because they are shallow and heavily damaged by pig activities. In contrast, with the exception is dissolved oxygen (which still reached critical conditions because of aquatic vegetation respiration), deeper permanent and pig‐managed wetlands provides the best opportunity for the same fish species to survive in a heavily pig‐modified tropical landscape

Surface water numerical modelling for the Clarence-Moreton bioregion. Product 2.6.1 from the Clarence-Moreton Bioregional Assessment

No abstract available

Surface water numerical modelling for the Clarence-Moreton bioregion. Product 2.6.1 from the Clarence-Moreton Bioregional Assessment

No abstract available

Tropical montane cloud forest: Environmental drivers of vegetation structure and ecosystem function

Abstract:Tropical montane cloud forests (TMCF) are characterized by short trees, often twisted with multiple stems, with many stems per ground area, a large stem diameter to height ratio, and small, often thick leaves. These forests exhibit high root to shoot ratio, with a moderate leaf area index, low above-ground production, low leaf nutrient concentrations and often with luxuriant epiphytic growth. These traits of TMCF are caused by climatic conditions not geological substrate, and are particularly associated with frequent or persistent fog and low cloud. There are several reasons why fog might result in these features. Firstly, the fog and clouds reduce the amount of light received per unit area of ground and as closed-canopy forests absorb most of the light that reaches them the reduction in the total amount of light reduces growth. Secondly, the rate of photosynthesis per leaf area declines in comparison with that in the lowlands, which leads to less carbon fixation. Nitrogen supply limits growth in several of the few TMCFs where it has been investigated experimentally. High root : shoot biomass and production ratios are common in TMCF, and soils are often wet which may contribute to N limitation. Further study is needed to clarify the causes of several key features of TMCF ecosystems including high tree diameter : height ratio.This is the author accepted manuscript. The final version is available from Cambridge University Press via http://dx.doi.org/10.1017/S026646741500017