scholarly journals Analyzing the Potential Impacts of Soil Moisture on the Observed and Model-Simulated Australian Surface Temperature Variations

2004 ◽  
Vol 17 (21) ◽  
pp. 4190-4212 ◽  
Author(s):  
Huqiang Zhang
Keyword(s):  
Soil Moisture ◽  
Climate Variability ◽  
Surface Temperature ◽  
Soil Water ◽  
Land Surface ◽  
Water Movement ◽  
Water Evaporation ◽  
Linear Regression Method ◽  
Temperature Variations ◽  
Partial Correlations

Abstract Based on observational and modeling analyses, this study aims to assess the potential influence of land surface conditions (soil moisture, in particular) on the Australian surface temperature variations. At first, a simple linear regression method is used to largely remove the ENSO influence from 50-yr observational surface temperature and precipitation datasets. Then, lag and partial correlations of the residuals are analyzed. The impacts of precipitation on the forthcoming surface temperature variations are largely attributed to the soil storage of precipitation water and the slow-varying soil moisture process. Results from partial correlations between precipitation and temperature variations suggest that when responding to anomalous atmospheric forcing, the land surface can introduce some slow-varying processes that can in turn affect the mean state of the atmosphere at monthly or longer scales and increase the predictability of the climate system. Following the observational analysis, results from 16 Atmospheric Model Intercomparison Project Phase 2 (AMIP2) AGCM simulations are analyzed to assess whether land surface modeling can affect the model-simulated climate variability. Lag-correlation analysis reveals that “climatic memory” of soil moisture has different features in the 16 models. Models with simple bucket-type schemes tend to have a rapid decay rate in the retention of soil moisture anomalies and show rapid feedback between land surface and the overlying atmosphere, with a much weaker influence of soil moisture conditions on surface climate variations. In contrast, most models using nonbucket schemes in which more physical processes are introduced in simulating soil water evaporation and soil water movement tend to show slow-varying soil moisture processes, affecting the model integrations at longer time scales. Different characteristics for translating soil moisture memory into climate variability and predictability are seen across the models, and more detailed studies are needed to further explore how land surface processes affect climate variability and predictability.

Effect of integrating straw into agricultural soils on soil infiltration and evaporation

2012 ◽  
Vol 65 (12) ◽  
pp. 2213-2218 ◽  
Author(s):  
Jiansheng Cao ◽  
Changming Liu ◽  
Wanjun Zhang ◽  
Yunlong Guo
Keyword(s):  
Soil Water ◽  
Water Conservation ◽  
Land Surface ◽  
Water Movement ◽  
Soil Depth ◽  
Soil Column ◽  
Conservation Strategies ◽  
Water Evaporation ◽  
Soil Infiltration ◽  
Straw Mulching

Soil water movement is a critical consideration for crop yield in straw-integrated fields. This study used an indoor soil column experiment to determine soil infiltration and evaporation characteristics in three forms of direct straw-integrated soils (straw mulching, straw mixing and straw inter-layering). Straw mulching is covering the land surface with straw. Straw mixing is mixing straw with the top 10 cm surface soil. Then straw inter-layering is placing straw at the 20 cm soil depth. There are generally good correlations among the mulch integration methods at p < 0.05, and with average errors/biases <10%. Straw mixing exhibited the best effect in terms of soil infiltration, followed by straw mulching. Due to over-burden weight-compaction effect, straw inter-layering somehow retarded soil infiltration. In terms of soil water evaporation, straw mulching exhibited the best effect. This was followed by straw mixing and then straw inter-layering. Straw inter-layering could have a long-lasting positive effect on soil evaporation as it limited the evaporative consumption of deep soil water. The responses of the direct straw integration modes to soil infiltration and evaporation could lay the basis for developing efficient water-conservation strategies. This is especially useful for water-scarce agricultural regions such as the arid/semi-arid regions of China.

scholarly journals Summer temperature response to extreme soil water conditions in the Mediterranean transitional climate regime

2021 ◽  
Author(s):  
Stefano Materia ◽  
Constantin Ardilouze ◽  
Chloé Prodhomme ◽  
Markus G. Donat ◽  
Marianna Benassi ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Soil Water ◽  
Land Surface ◽  
Heat Waves ◽  
Climate Regime ◽  
Seasonal Forecasts ◽  
Near Surface ◽  
Surface Temperatures ◽  
The Mediterranean

AbstractLand surface and atmosphere are interlocked by the hydrological and energy cycles and the effects of soil water-air coupling can modulate near-surface temperatures. In this work, three paired experiments were designed to evaluate impacts of different soil moisture initial and boundary conditions on summer temperatures in the Mediterranean transitional climate regime region. In this area, evapotranspiration is not limited by solar radiation, rather by soil moisture, which therefore controls the boundary layer variability. Extremely dry, extremely wet and averagely humid ground conditions are imposed to two global climate models at the beginning of the warm and dry season. Then, sensitivity experiments, where atmosphere is alternatively interactive with and forced by land surface, are launched. The initial soil state largely affects summer near-surface temperatures: dry soils contribute to warm the lower atmosphere and exacerbate heat extremes, while wet terrains suppress thermal peaks, and both effects last for several months. Land-atmosphere coupling proves to be a fundamental ingredient to modulate the boundary layer state, through the partition between latent and sensible heat fluxes. In the coupled runs, early season heat waves are sustained by interactive dry soils, which respond to hot weather conditions with increased evaporative demand, resulting in longer-lasting extreme temperatures. On the other hand, when wet conditions are prescribed across the season, the occurrence of hot days is suppressed. The land surface prescribed by climatological precipitation forcing causes a temperature drop throughout the months, due to sustained evaporation of surface soil water. Results have implications for seasonal forecasts on both rain-fed and irrigated continental regions in transitional climate zones.

A laboratory study of the effect of soil-water dynamics on the migration of gases from subsurface sources

2021 ◽  
Author(s):  
Ana M. C. Ilie ◽  
Tissa H. Illangasekare ◽  
Kenichi Soga ◽  
William R. Whalley
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Sandy Soil ◽  
Land Surface ◽  
Soil Gas ◽  
Water Dynamics ◽  
Gas Migration ◽  
Soil Water Dynamics ◽  
Scale Test ◽  
Properties Of Soil

<p>Understanding the soil-gas migration in unsaturated soil is important in a number of problems that include carbon loading to the atmosphere from the bio-geochemical activity and leakage of gases from subsurface sources from carbon storage unconventional energy development. The soil water dynamics in the vadose zone control the soil-gas pathway development and, hence, the gas flux's spatial and temporal distribution at the soil surface. The spatial distribution of soil-water content depends on soil water characteristics. The dynamics are controlled by the water flux at the land surface and water table fluctuations. Physical properties of soil give a better understanding of the soil gas dynamics and migration from greater soil depths. The fundamental process of soil gas migration under dynamic water content was investigated in the laboratory using an intermediate-scale test system under controlled conditions that is not possible in the field. The experiments focus on observing the methane gas migration in relation to the physical properties of soil and the soil moisture patterns. A 2D soil tank with dimensions of 60 cm × 90 cm × 5.6 cm (height × length × width) was used.  The tank was heterogeneously packed with sandy soil along with a distributed network of soil moisture, temperature, and electrical conductivity sensors. The heterogeneous soil configuration was designed using nine uniform silica sands with the effective sieve numbers #16, #70, #8, #40/50, #110, #30/40, #50, and #20/30 (Accusands, Unimin Corp., Ottawa, MN), and a porosity ranging in values from 0.31 to 0.42. Four methane infrared gas sensors and a Flame Ionization detector (HFR400 Fast FID) were used for the soil gas sampling at different depths within the soil profiles and at the land surface.  A complex transient soil moisture distribution and soil gas migration patterns were observed in the 2D tank. These processes were successfully captured by the sensors. These preliminary experiments helped us to understand the mechanism of soil moisture sensor response and methane gas migration into a heterogeneous sandy soil with a view to developing a large-scale test in a 3D tank (4.87 m × 2.44 m × 0.40 m) and finally transition to field deployment.</p>

Characterizing waste disposal sites by using multi-spectral satellite imagery

2021 ◽  
Author(s):  
Gaetana Ganci ◽  
Annalisa Cappello ◽  
Giuseppe Bilotta ◽  
Giuseppe Pollicino ◽  
Luigi Lodato
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Waste Disposal ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
The State ◽  
Dump Site ◽  
Temperature State ◽  
Surrounding Areas

<p>The application of remote sensing for monitoring, detecting and analysing the spatial and extents and temporal changes of waste dumping sites and landfills could become a cost-effective and powerful solution. Multi-spectral satellite images, especially in the thermal infrared, can be exploited to characterize the state of activity of a landfill.  Indeed, waste disposal sites, during the period of activity, can show differences in surface temperature (LST, Land Surface Temperature), state of vegetation (estimated through NDVI, Normalized Difference Vegetation Index) or soil moisture (estimated through NDWI, Normalized Difference Water Index) compared to neighboring areas. Landfills with organic waste typically show higher temperatures than surrounding areas due to exothermic decomposition activities. In fact, the biogas, in the absence or in case of inefficiency of the conveying plants, rises through the layers of organic matter and earth (landfill body) until it reaches the surface at a temperature of over 40 ° C. Moreover, in some cases, leachate contamination of the aquifers can be identified by analyzing the soil moisture, through the estimate of the NDWI, and the state of suffering of the vegetation surrounding the site, through the estimate of the NDVI. This latter can also be an indicator of soil contamination due to the presence of toxic and potentially dangerous waste when buried or present nearby. To take into account these facts, we combine the LST, NDVI and NDWI indices of the dump site and surrounding areas in order to characterize waste disposal sites. Preliminary results show how this approach can bring out the area and level of activity of known landfill sites. This could prove particularly useful for the definition of intervention priorities in landfill remediation works.</p>

scholarly journals An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data

2019 ◽  
Author(s):  
Bouchra Ait Hssaine ◽  
Olivier Merlin ◽  
Jamal Ezzahar ◽  
Nitu Ojha ◽  
Salah Er-raki ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Energy Balance ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Wide Range ◽  
The Mean

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1 km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1 km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014–2018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014–2018). The field was seeded for the 2014–2015 (S1), 2016–2017 (S2) and 2017–2018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015–2016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated αPT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved αPT remains at a mostly constant value (∼ 0.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181 W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62 W/m2 for S1, S2, S3 and B1 respectively.

scholarly journals Earth Observations-Based Evapotranspiration in Northeastern Thailand

2019 ◽  
Vol 11 (2) ◽  
pp. 138 ◽  
Author(s):  
Chaolei Zheng ◽  
Li Jia ◽  
Guangcheng Hu ◽  
Jing Lu
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Microwave Remote Sensing ◽  
Spatiotemporal Pattern ◽  
Monsoon Climate ◽  
Thermal Remote Sensing ◽  
Clear Sky

Thailand is characterized by typical tropical monsoon climate, and is suffering serious water related problems, including seasonal drought and flooding. These issues are highly related to the hydrological processes, e.g., precipitation and evapotranspiration (ET), which are helpful to understand and cope with these problems. It is critical to study the spatiotemporal pattern of ET in Thailand to support the local water resource management. In the current study, daily ET was estimated over Thailand by ETMonitor, a process-based model, with mainly satellite earth observation datasets as input. One major advantage of the ETMonitor algorithm is that it introduces the impact of soil moisture on ET by assimilating the surface soil moisture from microwave remote sensing, and it reduces the dependence on land surface temperature, as the thermal remote sensing is highly sensitive to cloud, which limits the ability to achieve spatial and temporal continuity of daily ET. The ETMonitor algorithm was further improved in current study to take advantage of thermal remote sensing. In the improved scheme, the evaporation fraction was first obtained by land surface temperature—vegetation index triangle method, which was used to estimate ET in the clear days. The soil moisture stress index (SMSI) was defined to express the constrain of soil moisture on ET, and clear sky SMSI was retrieved according to the estimated clear sky ET. Clear sky SMSI was then interpolated to cloudy days to obtain the SMSI for all sky conditions. Finally, time-series ET at daily resolution was achieved using the interpolated spatio-temporal continuous SMSI. Good agreements were found between the estimated daily ET and flux tower observations with root mean square error ranging between 1.08 and 1.58 mm d−1, which showed better accuracy than the ET product from MODerate resolution Imaging Spectroradiometer (MODIS), especially for the forest sites. Chi and Mun river basins, located in Northeast Thailand, were selected to analyze the spatial pattern of ET. The results indicate that the ET had large fluctuation in seasonal variation, which is predominantly impacted by the monsoon climate.

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