An Operational In Situ Soil Moisture & Soil Temperature Monitoring Network for West Wales, UK: The WSMN Network

In situ, incubations of intact soil cores were carried out to identify factors controlling nitrogen (N) mineralisation and its spatial variability under field conditions. The analysed factors were soil moisture, temperature, and the content of light-fraction (density ≤ 2 Mg/m3) organic carbon (LC) contained in the soil. The error associated with the estimate of in situ N mineralisation was analysed using undisturbed samples in laboratory incubations. The coefficient of variation of in situ N mineralisation ranged from 58 to 234%. Nitrogen and LC mineralisation in the field showed a similar temporal pattern. The major factor affecting this pattern was soil temperature, soil moisture being near the optimum level throughout the experiment. The rate of N mineralisation during an incubation period was correlated with the content of LC at the beginning of the period; this factor explained 40–50% of the variation in N mineralisation. At a low rate of N mineralisation, a large proportion of the spatial variability was attributed to the error of estimation. From the relationship between N mineralisation and LC content, we estimated the rate constant k which could be expressed as a function of soil temperature. Within the observed temperature range (daily mean average 11–17°C), the Q10 (temperature coefficient) of in situ N mineralisation was 1.5. Negative values of N mineralisation were associated with the lower LC content of each period, indicating the presence of an immobilisation process, or that a proportion of LC was not involved in N mineralisation.

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Evaluating the potential of Sentinel-1 images for the estimation of soil moisture on an alluvial Fan

10.5194/egusphere-egu2020-19614 ◽

2020 ◽

Author(s):

Abhilash Singh ◽

Kumar Gaurav ◽

Shashi Kumar

Keyword(s):

Surface Roughness ◽

Soil Moisture ◽

Soil Temperature ◽

Alluvial Fan ◽

Soil Survey ◽

Volumetric Soil Moisture ◽

The North ◽

S Model ◽

Time Domain Reflectometer

We evaluate the potential of Sentinel-1A & 1B satellite images to estimate the volumetric soil moisture content over an alluvial fan of the Kosi River in the North Bihar, India. Over this region, only dual polarised images (VH and VV) are available. However, the existing backscattering models (i.e., Dubois, Oh and IEM models) uses quad polarised (VV, VH, HH and HV) images for the estimation of soil permittivity and surface roughness over the bareland. To overcome the constraint of dual polarised data, we eliminated one of the unknown (i.e. surface roughness) by developing a regression model between the in-situ measured surface roughness and the ratio of backscatter values (VH/VV) in dB. &#160;In a field campaign in the Kosi Fan from December 10-21, 2019, we have measured surface roughness, soil temperature, soil pH and soil moisture at 78 different location using the pin-meter, soil survey instrument (soil temperature and pH), and Time Domain Reflectometer (TDR) respectively. The average surface roughness and soil moisture varies between (0.61 - 5.45) cm and (0.12-0.53) m3/m3 respectively in the study area.Further, using the surface roughness we modify the Dubois, Oh and IEM models. This reduces the number of unknowns in the models from two to one; the soil permittivity. We compute the soil permittivity from the inversion of the existing backscattering models. Finally, we use the permittivity values in the Top&#8217;s model to estimate the volumetric soil moisture in the study area. Our initial results exhibit a good correlation (R2 = 0.85) to the in-situ measured soil moisture.

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Measurements of soil respiration and simple models dependent on moisture and temperature for an Amazonian southwest tropical forest

Biogeosciences Discussions ◽

10.5194/bgd-6-6147-2009 ◽

2009 ◽

Vol 6 (3) ◽

pp. 6147-6177 ◽

Cited By ~ 1

Author(s):

F. B. Zanchi ◽

H. R. da Rocha ◽

H. C. de Freitas ◽

B. Kruijt ◽

M. J. Waterloo ◽

...

Keyword(s):

Soil Moisture ◽

Soil Respiration ◽

Soil Temperature ◽

Field Measurements ◽

Dry Season ◽

Wet Season ◽

Hourly Data ◽

Fresh Litter ◽

Favorable Conditions

Abstract. Soil respiration plays a significant role in the carbon cycle of Amazonian tropical forests, although in situ measurements have only been poorly reported and the dependence of soil moisture and soil temperature also weakly understood. This work investigates the temporal variability of soil respiration using field measurements, which also included soil moisture, soil temperature and litterfall, from April 2003 to January 2004, in a southwest Brazilian tropical rainforest near Ji-Paraná, Rondônia. The experimental design deployed five automatic (static, semi-opened) soil chambers connected to an infra-red CO2 gas analyzer. The mean half-hourly soil respiration showed a large scattering from 0.6 to 18.9 μmol CO2 m−2 s−1 and the average was 8.0±3.4 μmol CO2 m−2 s−1. Soil respiration varied seasonally, being lower in the dry season and higher in the wet season, which generally responded positively to the variation of soil moisture and temperature year round. The peak was reached in the dry-to-wet season transition (September), this coincided with increasing sunlight, evapotranspiration and ecosystem productivity. Litterfall processes contributed to meet very favorable conditions for biomass decomposition in early wet season, especially the fresh litter on the forest floor accumulated during the dry season. We attempted to fit three models with the data: the exponential Q10 model, the Reichstein model, and the log-soil moisture model. The models do not contradict the scattering of observations, but poorly explain the variance of the half-hourly data, which is improved when the lag-time days averaging is longer. The observations suggested an optimum range of soil moisture, between 0.115

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Interannual Variability of Atmospheric CH4 and Its Driver Over South Korea Captured by Integrated Data in 2019

Remote Sensing ◽

10.3390/rs13122266 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2266

Author(s):

Samuel Kenea ◽

Hae-Young Lee ◽

Sang-Won Joo ◽

Shan-Lan Li ◽

Lev Labzovskii ◽

...

Keyword(s):

Growth Rate ◽

Soil Moisture ◽

Soil Temperature ◽

Interannual Variability ◽

Statistical Significance ◽

Regional Distribution ◽

High Growth ◽

Surface Model ◽

Annual Growth Rate

Understanding the temporal variability of atmospheric methane (CH4) and its potential drivers can advance the progress toward mitigating changes to the climate. To comprehend interannual variability and spatial characteristics of anomalous CH4 mole fractions and its drivers, we used integrated data from different platforms such as in situ measurements and satellites (TROPOspheric Monitoring Instrument (TROPOMI) and Greenhouse Gases Observing SATellite (GOSAT)) retrievals. A pronounced change of annual growth rate was detected at Anmyeondo (AMY), Republic of Korea, ranging from −16.8 to 31.3 ppb yr−1 as captured in situ through 2015–2020 and 3.9 to 16.4 ppb yr−1 detected by GOSAT through 2014–2019, respectively. High growth rates were discerned in 2016 (31.3 ppb yr−1 and 13.4 ppb yr−1 from in situ and GOSAT, respectively) and 2019 (27.4 ppb yr−1 and 16.4 ppb yr−1 from in situ and GOSAT, respectively). The high growth in 2016 was essentially explained by the strong El Niño event in 2015–2016, whereas the large growth rate in 2019 was not related to ENSO. We suggest that the growth rate that appeared in 2019 was related to soil temperature according to the Noah Land Surface Model. The stable isotopic composition of 13C/12C in CH4 (δ13-CH4) collected by flask-air sampling at AMY during 2014–2019 supported the soil methane hypothesis. The intercept of the Keeling plot for summer and autumn were found to be −53.3‰ and −52.9‰, respectively, which suggested isotopic signature of biogenic emissions. The isotopic values in 2019 exhibited the strongest depletion compared to other periods, which suggests even a stronger biogenic signal. Such changes in the biogenic signal were affected by the variations of soil temperature and soil moisture. We looked more closely at the variability of XCH4 and the relationship with soil properties. The result indicated a spatial distribution of interannual variability, as well as the captured elevated anomaly over the southwest of the domain in autumn 2019, up to 70 ppb, which was largely explained by the combined effect of soil temperature and soil moisture changes, indicating a pixel-wise correlation of XCH4 anomaly with those parameters in the range of 0.5–0.8 with a statistical significance (p < 0.05). This implies that the soil-associated drivers are able to exert a large-scale influence on the regional distribution of CH4 in Korea.

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Regional soil moisture monitoring network in the Raam catchment in the Netherlands

10.5194/essd-2017-50 ◽

2017 ◽

Cited By ~ 1

Author(s):

Harm-Jan F. Benninga ◽

Coleen D. U. Carranza ◽

Michiel Pezij ◽

Pim van Santen ◽

Martine J. van der Ploeg ◽

...

Keyword(s):

Soil Moisture ◽

The Netherlands ◽

Soil Temperature ◽

Meteorological Data ◽

Monitoring Network ◽

Water Shortage ◽

First Year ◽

Moisture Profile ◽

Groundwater Levels ◽

Extreme Precipitation Events

Abstract. We have established a soil moisture profile monitoring network in the 223 km2 Raam Catchment, a tributary of the Meuse River in the Netherlands. This catchment faces water shortage during summers and excess of water during winters and after extreme precipitation events. Water management can benefit from reliable information on the soil water availability in the unsaturated zone. In situ measurements provide a direct source of information on which water managers can base their decisions. Moreover, these measurements are commonly used as a reference for calibration and validation of soil moisture products derived from earth observations or obtained by model simulations. Distributed over the Raam Catchment, we have equipped 14 agricultural fields and one natural grass field with soil moisture and soil temperature monitoring instrumentation, consisting of Decagon 5TM sensors installed at depths of 5 cm, 10 cm, 20 cm, 40 cm and 80 cm. Soil-specific calibration functions that have been developed for the 5TM sensors under laboratory conditions lead to an accuracy of 0.02 m3 m−3. The first set of measurements has been retrieved for the period 5 April 2016–4 April 2017. In this paper, we describe the Raam monitoring network and instrumentation, the soil-specific calibration of the sensors, the first year of measurements, and additional measurements (soil temperature, phreatic groundwater levels and meteorological data) and information (elevation, soil texture, land cover, and geohydrological model) available for performing scientific research. The data is available at http://dx.doi.org/10.4121/uuid:2411bbb8-2161-4f31-985f-7b65b8448bc9.

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Hyperresolution Land Surface Modeling in the Context of SMAP Cal–Val

Journal of Hydrometeorology ◽

10.1175/jhm-d-15-0070.1 ◽

2015 ◽

Vol 17 (1) ◽

pp. 345-352 ◽

Cited By ~ 11

Author(s):

Camille Garnaud ◽

Stéphane Bélair ◽

Aaron Berg ◽

Tracy Rowlandson

Keyword(s):

Soil Moisture ◽

Soil Temperature ◽

Land Surface ◽

Large Scale ◽

Initial Conditions ◽

Surface Condition ◽

Soil Conditions ◽

Small Scale ◽

In Situ Observations

Abstract This study explores the performance of Environment Canada’s Surface Prediction System (SPS) in comparison to in situ observations from the Brightwater Creek soil moisture observation network with respect to soil moisture and soil temperature. To do so, SPS is run at hyperresolution (100 m) over a small domain in southern Saskatchewan (Canada) during the summer of 2014. It is shown that with initial conditions and surface condition forcings based on observations, SPS can simulate soil moisture and soil temperature evolution over time with high accuracy (mean bias of 0.01 m3 m−3 and −0.52°C, respectively). However, the modeled spatial variability is generally much weaker than observed. This is likely related to the model’s use of uniform soil texture, the lack of small-scale orography, as well as a predefined crop growth cycle in SPS. Nonetheless, the spatial averages of simulated soil conditions over the domain are very similar to those observed, suggesting that both are representative of large-scale conditions. Thus, in the context of the National Aeronautics and Space Administration’s (NASA) Soil Moisture Active Passive (SMAP) project, this study shows that both simulated and in situ observations can be upscaled to allow future comparison with upcoming satellite data.

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The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) for quantifying uncertainties in coarse resolution satellite and model products

Hydrology and Earth System Sciences ◽

10.5194/hess-15-2303-2011 ◽

2011 ◽

Vol 15 (7) ◽

pp. 2303-2316 ◽

Cited By ~ 159

Author(s):

Z. Su ◽

J. Wen ◽

L. Dente ◽

R. van der Velde ◽

L. Wang ◽

...

Keyword(s):

Soil Moisture ◽

Tibetan Plateau ◽

Soil Temperature ◽

Land Surface ◽

Regional Scale ◽

The Tibetan Plateau ◽

Humid Climate ◽

Coarse Resolution ◽

Reference Networks

Abstract. A plateau scale soil moisture and soil temperature observatory is established on the Tibetan Plateau for quantifying uncertainties in coarse resolution satellite and model products of soil moisture and soil temperature. The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) consists of three regional scale in-situ reference networks, including the Naqu network in a cold semiarid climate, the Maqu network in a cold humid climate and the Ngari network in a cold arid climate. These networks provide a representative coverage of the different climate and land surface hydrometeorological conditions on the Tibetan plateau. In this paper the details of the Tibet-Obs are reported. To demonstrate the uniqueness of the Tibet-Obs in quantifying and explaining soil moisture uncertainties in existing coarse satellite products, an analysis is carried out to assess the reliability of several satellite products for the Naqu and the Maqu network areas. It is concluded that global coarse resolution soil moisture products are useful but exhibit till now unreported uncertainties in cold and semiarid regions – use of them would be critically enhanced if uncertainties can be quantified and reduced using in-situ measurements.

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Estimating in-situ soil moisture dynamics from soil thermal dependencies

10.5194/egusphere-egu2020-13852 ◽

2020 ◽

Author(s):

Svenja Hoffmeister ◽

Sibylle Haßler ◽

Mirko Mälicke ◽

Erwin Zehe

Keyword(s):

Time Series ◽

Soil Moisture ◽

Phase Shift ◽

Soil Temperature ◽

Soil Water ◽

Coupled Model ◽

Soil Moisture Dynamics ◽

Amplitude Attenuation ◽

Moisture Dynamics

Soil moisture plays an important role for the understanding of hydrological processes due to its influence on water and energy fluxes between the soil surface and the atmosphere. Knowledge of soil water dynamics is especially critical in water-scarce areas. In agroforestry systems, for instance, excessive competition for water between the trees and crops might outweigh the benefits of the system, thus preventing a successful implementation. Several techniques exist for measuring soil moisture and commercial devices vary widely in cost, reliability and efficiency. An alternative approach could be to estimate soil moisture dynamics from soil thermal dependencies. Similar approaches are already being used in remote sensing, as soil moisture influences the soil thermal properties and thus the surface energy balance and soil heat transfer. However, few studies have tested the feasibility of estimating in-situ soil moisture dynamics from soil temperature dynamics within a soil profile. Temperature sensors are cheaper, smaller and technically robust and could thus provide an interesting alternative to available commercial soil moisture sensors. In this study, we quantify the effect of soil moisture on phase shift and amplitude attenuation of soil temperature to estimate soil moisture content. We investigate these relationships from two different angles. Firstly, we use virtual measurements in coupled model simulations of soil water and soil heat dynamics to infer the general feasibility and precision of the method in an idealized error-free world. A sensitivity analysis can give insights on how the parametrization of the thermal diffusivity affects the precision and feasibility. Secondly, we compare findings from these simulations to results from analyzing time series of both soil moisture and soil temperature measured in an agroforestry field site in South Africa. A tentative analysis of these time series reveals that the amplitude attenuation and phase shift in the daily temperature signal is clearly sensitivity to changes in soil moisture. Finally, we aim to setup a coupled model for the study site based on the available soil hydraulic and textural data and compare simulated with observed phase shifts and attenuations at different depths.

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A plateau scale soil moisture and soil temperature observatory for quantifying uncertainties in coarse resolution satellite products

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-8-243-2011 ◽

2011 ◽

Vol 8 (1) ◽

pp. 243-276 ◽

Cited By ~ 1

Author(s):

Z. Su ◽

J. Wen ◽

L. Dente ◽

R. van der Velde ◽

L. Wang ◽

...

Keyword(s):

Soil Moisture ◽

Tibetan Plateau ◽

Soil Temperature ◽

In Situ Measurements ◽

Winter Period ◽

The Tibetan Plateau ◽

Monsoon Period ◽

Coarse Resolution ◽

Mean And Variance

Abstract. A plateau scale soil moisture and soil temperature observatory is established on the Tibetan Plateau for quantifying uncertainties in coarse resolution satellite products of soil moisture and soil temperature. The observatory consists of three regional networks across the Tibetan Plateau and provides reliable measurements of mean and variance in soil moisture and soil temperature of representative areas comparable in size to coarse satellite footprints. Using these in-situ measurements, a analysis is carried out to assess the reliability of several satellite products derived from AMSR-E and ASCAT data by three retrieval algorithms (henceforth the AMSR-E products, the ASCAT-L2 products and the ITC-model retrievals) for the first time. For the cold semiarid Naqu area, AMSR-E and ASCAT-L2 products overestimate significantly the regional soil moisture in the monsoon seasons. The ITC-model retrievals are closer to the in-situ measurements but the dynamics in the retrieved time series needs further investigation. The use of these datasets is therefore not recommended for cold semiarid conditions on the Tibetan Plateau. For the cold humid Maqu network area AMSR-E and ASCAT-L2 products have comparable accuracy as reported by previous studies in the humid monsoon period. AMSR-E products significantly overestimate and ASCAT-L2 products underestimate the soil moisture in the winter period. The ITC-model retrievals underestimate the soil moisture in general. It is concluded that global coarse resolution soil moisture products are useful but exhibit till now unreported uncertainties in cold and semiarid regions – use of them would be critically enhanced if uncertainties can be quantified and reduced using in-situ measurements.

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