Surprisingly robust projections of soil temperature and moisture for North American drylands in the 21st century

NASA Astrophysics Data System (ADS)

Bradford, J. B.; Schlaepfer, D.; Palmquist, K. A.; Lauenroth, W.

2017-12-01

Climate projections for western North America suggest temperature increases that are relatively consistent across climate models. However, precipitation projections are less consistent, especially in the Southwest, promoting uncertainty about the future of soil moisture and drought. We utilized a daily time-step ecosystem water balance model to characterize soil temperature and moisture patterns at a 10-km resolution across western North America for historical (1980-2010), mid-century (2020-2050), and late century (2070-2100). We simulated soil moisture and temperature under two representative concentration pathways and eleven climate models (selected strategically to represent the range of variability in projections among the full set of models in the CMIP5 database and perform well in hind-cast comparisons for the region), and we use the results to identify areas with robust projections, e.g. areas where the large majority of models agree in the direction of change in long-term average soil moisture or temperature. Rising air temperatures will increase average soil temperatures across western North America and expand the area of mesic and thermic soil temperature regimes while decreasing the area of cryic and frigid regimes. Future soil moisture conditions are relatively consistent across climate models for much of the region, including many areas with variable precipitation trajectories. Consistent projections for drier soils are expected in most of Arizona and New Mexico, similar to previous studies. Other regions with projections for declining soil moisture include the central and southern U.S. Great Plains and large parts of southern British Columbia. By contrast, areas with robust projections for increasing soil moisture include northeastern Montana, southern Alberta and Saskatchewan, and many areas in the intermountain west dominated by big sagebrush. In addition, seasonal moisture patterns in much of the western US drylands are expected to shift toward cool-season water availability, with potentially important consequences for ecosystem structure and function. These results provide a framework for coping with variability in climate projections and assessing climate change impacts on dryland ecosystems.

Agriculture intensifies soil moisture decline in Northern China

DOE PAGES

Liu, Yaling; Pan, Zhihua; Zhuang, Qianlai; ...

2015-07-09

Northern China is one of the most densely populated regions in the world. Agricultural activities have intensified since the 1980s to provide food security to the country. However, this intensification has likely contributed to an increasing scarcity in water resources, which may in turn be endangering food security. Based on in-situ measurements of soil moisture collected in agricultural plots during 1983–2012, we find that topsoil (0–50 cm) volumetric water content during the growing season has declined significantly (p<0.01), with a trend of -0.011 to -0.015 m3 m-3 per decade. Observed discharge declines for the three large river basins are consistentmore » with the effects of agricultural intensification, although other factors (e.g. dam constructions) likely have contributed to these trends. Practices like fertilizer application have favoured biomass growth and increased transpiration rates, thus reducing available soil water. In addition, the rapid proliferation of water-expensive crops (e.g., maize) and the expansion of the area dedicated to food production have also contributed to soil drying. Adoption of alternative agricultural practices that can meet the immediate food demand without compromising future water resources seem critical for the sustainability of the food production system.« less

Agriculture intensifies soil moisture decline in Northern China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yaling; Pan, Zhihua; Zhuang, Qianlai

Northern China is one of the most densely populated regions in the world. Agricultural activities have intensified since the 1980s to provide food security to the country. However, this intensification has likely contributed to an increasing scarcity in water resources, which may in turn be endangering food security. Based on in-situ measurements of soil moisture collected in agricultural plots during 1983–2012, we find that topsoil (0–50 cm) volumetric water content during the growing season has declined significantly (p<0.01), with a trend of -0.011 to -0.015 m3 m-3 per decade. Observed discharge declines for the three large river basins are consistentmore » with the effects of agricultural intensification, although other factors (e.g. dam constructions) likely have contributed to these trends. Practices like fertilizer application have favoured biomass growth and increased transpiration rates, thus reducing available soil water. In addition, the rapid proliferation of water-expensive crops (e.g., maize) and the expansion of the area dedicated to food production have also contributed to soil drying. Adoption of alternative agricultural practices that can meet the immediate food demand without compromising future water resources seem critical for the sustainability of the food production system.« less

Agriculture intensifies soil moisture decline in Northern China

PubMed Central

Liu, Yaling; Pan, Zhihua; Zhuang, Qianlai; Miralles, Diego G.; Teuling, Adriaan J.; Zhang, Tonglin; An, Pingli; Dong, Zhiqiang; Zhang, Jingting; He, Di; Wang, Liwei; Pan, Xuebiao; Bai, Wei; Niyogi, Dev

2015-01-01

Northern China is one of the most densely populated regions in the world. Agricultural activities have intensified since the 1980s to provide food security to the country. However, this intensification has likely contributed to an increasing scarcity in water resources, which may in turn be endangering food security. Based on in-situ measurements of soil moisture collected in agricultural plots during 1983–2012, we find that topsoil (0–50 cm) volumetric water content during the growing season has declined significantly (p < 0.01), with a trend of −0.011 to −0.015 m3 m−3 per decade. Observed discharge declines for the three large river basins are consistent with the effects of agricultural intensification, although other factors (e.g. dam constructions) likely have contributed to these trends. Practices like fertilizer application have favoured biomass growth and increased transpiration rates, thus reducing available soil water. In addition, the rapid proliferation of water-expensive crops (e.g., maize) and the expansion of the area dedicated to food production have also contributed to soil drying. Adoption of alternative agricultural practices that can meet the immediate food demand without compromising future water resources seem critical for the sustainability of the food production system. PMID:26158774

Projections of Declining Surface-Water Availability for the Southwestern United States

NASA Technical Reports Server (NTRS)

Seager, Richard; Ting, Mingfang; Li, Cuihua; Naik, Naomi; Cook, Benjamin; Nakamura, Jennifer; Liu, Haibo

2012-01-01

Global warming driven by rising greenhouse-gas concentrations is expected to cause wet regions of the tropics and mid to high latitudes to get wetter and subtropical dry regions to get drier and expand polewards. Over southwest North America, models project a steady drop in precipitation minus evapotranspiration, P -- E, the net flux of water at the land surface, leading to, for example, a decline in Colorado River flow. This would cause widespread and important social and ecological consequences. Here, using new simulations from the Coupled Model Intercomparison Project Five, to be assessed in Intergovernmental Panel on Climate Change Assessment Report Five, we extend previous work by examining changes in P, E, runoff and soil moisture by season and for three different water resource regions. Focusing on the near future, 2021-2040, the new simulations project declines in surface-water availability across the southwest that translate into reduced soil moisture and runoff in California and Nevada, the Colorado River headwaters and Texas.

Belowground Response to Drought in a Tropical Forest Soil. II. Change in Microbial Function Impacts Carbon Composition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bouskill, Nicholas J.; Wood, Tana E.; Baran, Richard

Climate model projections for tropical regions show clear perturbation of precipitation patterns leading to increased frequency and severity of drought in some regions. Previous work has shown declining soil moisture to be a strong driver of changes in microbial trait distribution, however, the feedback of any shift in functional potential on ecosystem properties related to carbon cycling are poorly understood. Here we show that drought-induced changes in microbial functional diversity and activity shape, and are in turn shaped by, the composition of dissolved and soil-associated carbon. We also demonstrate that a shift in microbial functional traits that favor the productionmore » of hygroscopic compounds alter the efflux of carbon dioxide following soil rewetting. Under drought the composition of the dissolved organic carbon pool changed in a manner consistent with a microbial metabolic response. We hypothesize that this microbial ecophysiological response to changing soil moisture elevates the intracellular carbon demand stimulating extracellular enzyme production, that prompts the observed decline in more complex carbon compounds (e.g., cellulose and lignin). Furthermore, a metabolic response to drought appeared to condition (biologically and physically) the soil, notably through the production of polysaccharides, particularly in experimental plots that had been pre-exposed to a short-term drought. This hysteretic response, in addition to an observed drought-related decline in phosphorus concentration, may have been responsible for a comparatively modest CO 2 efflux following wet-up in drought plots relative to control plots.« less

Belowground Response to Drought in a Tropical Forest Soil. II. Change in Microbial Function Impacts Carbon Composition

PubMed Central

Bouskill, Nicholas J.; Wood, Tana E.; Baran, Richard; Hao, Zhao; Ye, Zaw; Bowen, Ben P.; Lim, Hsiao Chien; Nico, Peter S.; Holman, Hoi-Ying; Gilbert, Benjamin; Silver, Whendee L.; Northen, Trent R.; Brodie, Eoin L.

2016-01-01

Climate model projections for tropical regions show clear perturbation of precipitation patterns leading to increased frequency and severity of drought in some regions. Previous work has shown declining soil moisture to be a strong driver of changes in microbial trait distribution, however, the feedback of any shift in functional potential on ecosystem properties related to carbon cycling are poorly understood. Here we show that drought-induced changes in microbial functional diversity and activity shape, and are in turn shaped by, the composition of dissolved and soil-associated carbon. We also demonstrate that a shift in microbial functional traits that favor the production of hygroscopic compounds alter the efflux of carbon dioxide following soil rewetting. Under drought the composition of the dissolved organic carbon pool changed in a manner consistent with a microbial metabolic response. We hypothesize that this microbial ecophysiological response to changing soil moisture elevates the intracellular carbon demand stimulating extracellular enzyme production, that prompts the observed decline in more complex carbon compounds (e.g., cellulose and lignin). Furthermore, a metabolic response to drought appeared to condition (biologically and physically) the soil, notably through the production of polysaccharides, particularly in experimental plots that had been pre-exposed to a short-term drought. This hysteretic response, in addition to an observed drought-related decline in phosphorus concentration, may have been responsible for a comparatively modest CO2 efflux following wet-up in drought plots relative to control plots. PMID:27014243

Belowground Response to Drought in a Tropical Forest Soil. II. Change in Microbial Function Impacts Carbon Composition

DOE PAGES

Bouskill, Nicholas J.; Wood, Tana E.; Baran, Richard; ...

2016-03-15

Climate model projections for tropical regions show clear perturbation of precipitation patterns leading to increased frequency and severity of drought in some regions. Previous work has shown declining soil moisture to be a strong driver of changes in microbial trait distribution, however, the feedback of any shift in functional potential on ecosystem properties related to carbon cycling are poorly understood. Here we show that drought-induced changes in microbial functional diversity and activity shape, and are in turn shaped by, the composition of dissolved and soil-associated carbon. We also demonstrate that a shift in microbial functional traits that favor the productionmore » of hygroscopic compounds alter the efflux of carbon dioxide following soil rewetting. Under drought the composition of the dissolved organic carbon pool changed in a manner consistent with a microbial metabolic response. We hypothesize that this microbial ecophysiological response to changing soil moisture elevates the intracellular carbon demand stimulating extracellular enzyme production, that prompts the observed decline in more complex carbon compounds (e.g., cellulose and lignin). Furthermore, a metabolic response to drought appeared to condition (biologically and physically) the soil, notably through the production of polysaccharides, particularly in experimental plots that had been pre-exposed to a short-term drought. This hysteretic response, in addition to an observed drought-related decline in phosphorus concentration, may have been responsible for a comparatively modest CO 2 efflux following wet-up in drought plots relative to control plots.« less

Effects of slash, machine passes, and soil moisture on penetration resistance in a cut-to-length harvesting

Treesearch

Han-Sup Han; Debbie Page-Dumroese; Sang-Kyun Han; Joanne Tirocke

2006-01-01

Multiple entries into forest stands are often needed for fire hazard reduction and ecosystem restoration treatments in the Inland-Northwest U.S.A. region. However, soil compaction occurring from mechanized harvesting operations often remains for many years and may contribute to a decline in long-term site productivity. A controlled experiment on a silt loam soil was...

Evaluation of soil and vegetation response to drought using SMOS soil moisture satellite observations

NASA Astrophysics Data System (ADS)

Piles, Maria; Sánchez, Nilda; Vall-llossera, Mercè; Ballabrera, Joaquim; Martínez, Justino; Martínez-Fernández, José; Camps, Adriano; Font, Jordi

2014-05-01

Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA's Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth's surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (< 1km) soil moisture estimates, which permits extending the applicability of the data to regional and local studies. Fine-scale soil moisture maps are currently limited to the Iberian Peninsula but the algorithm is dynamic and can be transported to any region. Soil moisture maps are generated in a near real-time fashion at BEC facilities and are used by Barcelona's fire prevention services to detect extremely dry soil and vegetation conditions posing a risk of fire. Recently, they have been used to explain drought-induced tree mortality episodes and forest decline in the Catalonia region. These soil moisture products can also be a useful tool to monitor the effectiveness of land restoration management practices. The aim of this work is to demonstrate the feasibility of using SMOS soil moisture maps for monitoring drought and water-stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be in close relationship with well-known drought indices (the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index). In this work, SSMA have been calculated for the period 2010-2013 in representative arid, semi-arid, sub-humid and humid areas across global land biomes. The SSMA reflect the cumulative precipitation anomalies and is known to provide 'memory' in the climate and hydrological system; the water retained in the soil after a rainfall event is temporally more persistent than the rainfall event itself, and has a greater persistence during periods of low precipitation. Besides, the Normalized Difference Vegetation Index (NDVI) from MODIS is used as an indicator of vegetation activity and growth. The NDVI time series are expected to reflect the changes in surface vegetation density and status induced by water-deficit conditions. Understanding the relationships between SSMA and NDVI concurrent time series should provide new insight about the sensitivity of land biomes to drought.

Arbuscular Mycorrhiza Alleviates Restrictions to Substrate Water Flow and Delays Transpiration Limitation to Stronger Drought in Tomato.

PubMed

Bitterlich, Michael; Sandmann, Martin; Graefe, Jan

2018-01-01

Arbuscular mycorrhizal fungi (AMF) proliferate in soil pores, on the surface of soil particles and affect soil structure. Although modifications in substrate moisture retention depend on structure and could influence plant water extraction, mycorrhizal impacts on water retention and hydraulic conductivity were rarely quantified. Hence, we asked whether inoculation with AMF affects substrate water retention, water transport properties and at which drought intensity those factors become limiting for plant transpiration. Solanum lycopersicum plants were set up in the glasshouse, inoculated or not with Funneliformis mosseae , and grown for 35 days under ample water supply. After mycorrhizal establishment, we harvested three sets of plants, one before (36 days after inoculation) and the second (day 42) and third (day 47) within a sequential drying episode. Sampling cores were introduced into pots before planting. After harvest, moisture retention and substrate conductivity properties were assessed and water retention and hydraulic conductivity models were fitted. A root water uptake model was adopted in order to identify the critical substrate moisture that induces soil derived transpiration limitation. Neither substrate porosity nor saturated water contents were affected by inoculation, but both declined after substrates dried. Drying also caused a decline in pot water capacity and hydraulic conductivity. Plant available water contents under wet (pF 1.8-4.2) and dry (pF 2.5-4.2) conditions increased in mycorrhizal substrates and were conserved after drying. Substrate hydraulic conductivity was higher in mycorrhizal pots before and during drought exposure. After withholding water from pots, higher substrate drying rates and lower substrate water potentials were found in mycorrhizal substrates. Mycorrhiza neither affected leaf area nor root weight or length. Consistently with higher substrate drying rates, AMF restored the plant hydraulic status, and increased plant transpiration when soil moisture declined. The water potential at the root surface and the resistance to water flow in the rhizosphere were restored in mycorrhizal pots although the bulk substrate dried more. Finally, substrates colonized by AMF can be more desiccated before substrate water flux quantitatively limits transpiration. This is most pronounced under high transpiration demands and complies with a difference of over 1,000 hPa in substrate water potential.

Towards Generating Long-term AMSR-based Soil Moisture Data Record

NASA Astrophysics Data System (ADS)

Mladenova, I. E.; Jackson, T. J.; Bindlish, R.; Cosh, M. H.

2014-12-01

Research done over the past couple of years, such as Jung et al. (Nature, 2010) among others, demonstrates the potential for using soil moisture as an indicator and parameter for identifying long-term changes in climate trends. The study mentioned links the reduction in global evapotranspiration observed after the 1998 El Nino to decline in moisture supplies in the soil profile. Due to its crucial role in the terrestrial cycles and the demonstrated strong feedback with other climate variables, soil moisture has been recognized by the Global Climate Observing System as one of the 50 Essential Climate Variables (ECVs). The most cost and time effective way of monitoring soil moisture at global scale on routine basis, which is one of the requirements for ECVs, is using satellite technologies. AMSR-E was the first satellite mission to include soil moisture as an operational product. AMSR-E provided us with almost a decade of soil moisture data that are now extended by AMSR2, allowing the generation of a consistent and continuous global soil moisture data record. AMSR-E and AMSR2 are technically alike, thus, they are expected to have similar performance and accuracy, which needs to be confirmed and this the main focus of our research. AMSR-E stopped operating at its optimal rotational speed about 6 months before the launch of AMSR2, which complicates the direct inter-comparison and assessment of AMSR2 performance relative to AMSR-E. The AMSR-E and AMSR2 brightness temperature data and the corresponding soil moisture retrievals derived using the Single Channel Approach were evaluated separately at several ground validation sides located in the US. Brightness temperature inter-comparisons were done using monthly climatology and the low spin AMSR-E data acquired at 2 rpm. Both analyses showed very high agreement between the two instruments and revealed a constant positive bias at all locations in the AMSR2 observations relative to AMSR-E. Removal of this bias is essential in order to ensure consistency between both instruments. The corresponding soil moisture retrievals from AMSR-E and AMSR2 demonstrated reasonable agreement relative to in situ data. A detailed discussion that focuses on this analysis as well as possible approaches for removing the observed bias in the brightness temperature observations will be presented.

Future soil moisture and temperature extremes imply expanding suitability for rainfed agriculture in temperate drylands

USGS Publications Warehouse

Bradford, John B.; Schlaepfer, Daniel R.; Lauenroth, William K.; Yackulic, Charles B.; Duniway, Michael C.; Hall, Sonia A.; Jia, Gensuo; Jamiyansharav, Khishigbayar; Munson, Seth M.; Wilson, Scott D.; Tietjen, Britta

2017-01-01

The distribution of rainfed agriculture is expected to respond to climate change and human population growth. However, conditions that support rainfed agriculture are driven by interactions among climate, including climate extremes, and soil moisture availability that have not been well defined. In the temperate regions that support much of the world’s agriculture, these interactions are complicated by seasonal temperature fluctuations that can decouple climate and soil moisture. Here, we show that suitability to support rainfed agriculture can be effectively represented by the interactive effects of just two variables: suitability increases where warm conditions occur with wet soil, and suitability decreases with extreme high temperatures. 21st century projections based on ecohydrological modeling of downscaled climate forecasts imply geographic shifts and overall increases in the area suitable for rainfed agriculture in temperate regions, especially at high latitudes, and pronounced, albeit less widespread, declines in suitable areas in low latitude drylands, especially in Europe. These results quantify the integrative direct and indirect impact of rising temperatures on rainfed agriculture.

Temperature and moisture effects on greenhouse gas emissions from deep active-layer boreal soils

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bond-Lamberty, Ben; Smith, A. Peyton; Bailey, Vanessa L.

Rapid climatic changes, rising air temperatures, and increased fires are expected to drive permafrost degradation and alter soil carbon (C) cycling in many high-latitude ecosystems. How these soils will respond to changes in their temperature, moisture, and overlying vegetation is uncertain but critical to understand given the large soil C stocks in these regions. We used a laboratory experiment to examine how temperature and moisture control CO 2 and CH 4 emissions from mineral soils sampled from the bottom of the annual active layer, i.e., directly above permafrost, in an Alaskan boreal forest. Gas emissions from 30 cores, subjected tomore » two temperatures and either field moisture conditions or experimental drought, were tracked over a 100-day incubation; we also measured a variety of physical and chemical characteristics of the cores. Gravimetric water content was 0.31 ± 0.12 (unitless) at the beginning of the incubation; cores at field moisture were unchanged at the end, but drought cores had declined to 0.06 ± 0.04. Daily CO 2 fluxes were positively correlated with incubation chamber temperature, core water content, and percent soil nitrogen. They also had a temperature sensitivity ( Q 10) of 1.3 and 1.9 for the field moisture and drought treatments, respectively. Daily CH 4 emissions were most strongly correlated with percent nitrogen, but neither temperature nor water content was a significant first-order predictor of CH 4 fluxes. The cumulative production of C from CO 2 was over 6 orders of magnitude higher than that from CH 4; cumulative CO 2 was correlated with incubation temperature and moisture treatment, with drought cores producing 52–73 % lower C. Cumulative CH 4 production was unaffected by any treatment. These results suggest that deep active-layer soils may be sensitive to changes in soil moisture under aerobic conditions, a critical factor as discontinuous permafrost thaws in interior Alaska. Furthermore, deep but unfrozen high-latitude soils have been shown to be strongly affected by long-term experimental warming, and these results provide insight into their future dynamics and feedback potential with future climate change.« less

Temperature and moisture effects on greenhouse gas emissions from deep active-layer boreal soils

DOE PAGES

Bond-Lamberty, Ben; Smith, A. Peyton; Bailey, Vanessa L.

2016-12-21

Rapid climatic changes, rising air temperatures, and increased fires are expected to drive permafrost degradation and alter soil carbon (C) cycling in many high-latitude ecosystems. How these soils will respond to changes in their temperature, moisture, and overlying vegetation is uncertain but critical to understand given the large soil C stocks in these regions. We used a laboratory experiment to examine how temperature and moisture control CO 2 and CH 4 emissions from mineral soils sampled from the bottom of the annual active layer, i.e., directly above permafrost, in an Alaskan boreal forest. Gas emissions from 30 cores, subjected tomore » two temperatures and either field moisture conditions or experimental drought, were tracked over a 100-day incubation; we also measured a variety of physical and chemical characteristics of the cores. Gravimetric water content was 0.31 ± 0.12 (unitless) at the beginning of the incubation; cores at field moisture were unchanged at the end, but drought cores had declined to 0.06 ± 0.04. Daily CO 2 fluxes were positively correlated with incubation chamber temperature, core water content, and percent soil nitrogen. They also had a temperature sensitivity ( Q 10) of 1.3 and 1.9 for the field moisture and drought treatments, respectively. Daily CH 4 emissions were most strongly correlated with percent nitrogen, but neither temperature nor water content was a significant first-order predictor of CH 4 fluxes. The cumulative production of C from CO 2 was over 6 orders of magnitude higher than that from CH 4; cumulative CO 2 was correlated with incubation temperature and moisture treatment, with drought cores producing 52–73 % lower C. Cumulative CH 4 production was unaffected by any treatment. These results suggest that deep active-layer soils may be sensitive to changes in soil moisture under aerobic conditions, a critical factor as discontinuous permafrost thaws in interior Alaska. Furthermore, deep but unfrozen high-latitude soils have been shown to be strongly affected by long-term experimental warming, and these results provide insight into their future dynamics and feedback potential with future climate change.« less

Temperature and moisture effects on greenhouse gas emissions from deep active-layer boreal soils

NASA Astrophysics Data System (ADS)

Bond-Lamberty, Ben; Smith, A. Peyton; Bailey, Vanessa

2016-12-01

Rapid climatic changes, rising air temperatures, and increased fires are expected to drive permafrost degradation and alter soil carbon (C) cycling in many high-latitude ecosystems. How these soils will respond to changes in their temperature, moisture, and overlying vegetation is uncertain but critical to understand given the large soil C stocks in these regions. We used a laboratory experiment to examine how temperature and moisture control CO2 and CH4 emissions from mineral soils sampled from the bottom of the annual active layer, i.e., directly above permafrost, in an Alaskan boreal forest. Gas emissions from 30 cores, subjected to two temperatures and either field moisture conditions or experimental drought, were tracked over a 100-day incubation; we also measured a variety of physical and chemical characteristics of the cores. Gravimetric water content was 0.31 ± 0.12 (unitless) at the beginning of the incubation; cores at field moisture were unchanged at the end, but drought cores had declined to 0.06 ± 0.04. Daily CO2 fluxes were positively correlated with incubation chamber temperature, core water content, and percent soil nitrogen. They also had a temperature sensitivity (Q10) of 1.3 and 1.9 for the field moisture and drought treatments, respectively. Daily CH4 emissions were most strongly correlated with percent nitrogen, but neither temperature nor water content was a significant first-order predictor of CH4 fluxes. The cumulative production of C from CO2 was over 6 orders of magnitude higher than that from CH4; cumulative CO2 was correlated with incubation temperature and moisture treatment, with drought cores producing 52-73 % lower C. Cumulative CH4 production was unaffected by any treatment. These results suggest that deep active-layer soils may be sensitive to changes in soil moisture under aerobic conditions, a critical factor as discontinuous permafrost thaws in interior Alaska. Deep but unfrozen high-latitude soils have been shown to be strongly affected by long-term experimental warming, and these results provide insight into their future dynamics and feedback potential with future climate change.

Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

NASA Astrophysics Data System (ADS)

Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

2017-12-01

Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

Soil moisture and fungi affect seed survival in California grassland annual plants.

PubMed

Mordecai, Erin A

2012-01-01

Survival of seeds in the seed bank is important for the population dynamics of many plant species, yet the environmental factors that control seed survival at a landscape level remain poorly understood. These factors may include soil moisture, vegetation cover, soil type, and soil pathogens. Because many soil fungi respond to moisture and host species, fungi may mediate environmental drivers of seed survival. Here, I measure patterns of seed survival in California annual grassland plants across 15 species in three experiments. First, I surveyed seed survival for eight species at 18 grasslands and coastal sage scrub sites ranging across coastal and inland Santa Barbara County, California. Species differed in seed survival, and soil moisture and geographic location had the strongest influence on survival. Grasslands had higher survival than coastal sage scrub sites for some species. Second, I used a fungicide addition and exotic grass thatch removal experiment in the field to tease apart the relative impact of fungi, thatch, and their interaction in an invaded grassland. Seed survival was lower in the winter (wet season) than in the summer (dry season), but fungicide improved winter survival. Seed survival varied between species but did not depend on thatch. Third, I manipulated water and fungicide in the laboratory to directly examine the relationship between water, fungi, and survival. Seed survival declined from dry to single watered to continuously watered treatments. Fungicide slightly improved seed survival when seeds were watered once but not continually. Together, these experiments demonstrate an important role of soil moisture, potentially mediated by fungal pathogens, in driving seed survival.

Shallow snowpack inhibits soil respiration in sagebrush steppe through multiple biotic and abiotic mechanisms

DOE PAGES

Tucker, Colin L.; Tamang, Shanker; Pendall, Elise; ...

2016-05-01

In sagebrush steppe, snowpack may govern soil respiration through its effect on multiple abiotic and biotic factors. Across the Intermountain West of the United States, snowpack has been declining for decades and is projected to decline further over the next century, making the response of soil respiration to snowpack a potentially important factor in the ecosystem carbon cycle. In this study, we evaluated the direct and indirect roles of the snowpack in driving soil respiration in sagebrush steppe ecosystems by taking advantage of highway snowfences in Wyoming to manipulate snowpack. An important contribution of this study is the use ofmore » Bayesian modeling to quantify the effects of soil moisture and temperature on soil respiration across a wide range of conditions from frozen to hot and dry, while simultaneously accounting for biotic factors (e.g., vegetation cover, root density, and microbial biomass and substrate-use diversity) affected by snowpack. Elevated snow depth increased soil temperature (in the winter) and moisture (winter and spring), and was associated with reduced vegetation cover and microbial biomass carbon. Soil respiration showed an exponential increase with temperature, with a temperature sensitivity that decreased with increasing seasonal temperature (Q 10 = 4.3 [winter], 2.3 [spring], and 1.7 [summer]); frozen soils were associated with unrealistic Q 10 approximate to 7989 due to the liquid-to-ice transition of soil water. Soil respiration was sensitive to soil water content; predicted respiration under very dry conditions was less than 10% of respiration under moist conditions. While higher vegetation cover increased soil respiration, this was not due to increased root density, and may reflect differences in litter inputs. Microbial substrate-use diversity was negatively related to reference respiration (i.e., respiration rate at a reference temperature and optimal soil moisture), although the mechanism remains unclear. Lastly, this study indicates that soil respiration is inhibited by shallow snowpack through multiple mechanisms; thus, future decreases in snowpack across the sagebrush steppe have the potential to reduce losses of soil C, potentially affecting regional carbon balance.« less

Shallow snowpack inhibits soil respiration in sagebrush steppe through multiple biotic and abiotic mechanisms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tucker, Colin L.; Tamang, Shanker; Pendall, Elise

In sagebrush steppe, snowpack may govern soil respiration through its effect on multiple abiotic and biotic factors. Across the Intermountain West of the United States, snowpack has been declining for decades and is projected to decline further over the next century, making the response of soil respiration to snowpack a potentially important factor in the ecosystem carbon cycle. In this study, we evaluated the direct and indirect roles of the snowpack in driving soil respiration in sagebrush steppe ecosystems by taking advantage of highway snowfences in Wyoming to manipulate snowpack. An important contribution of this study is the use ofmore » Bayesian modeling to quantify the effects of soil moisture and temperature on soil respiration across a wide range of conditions from frozen to hot and dry, while simultaneously accounting for biotic factors (e.g., vegetation cover, root density, and microbial biomass and substrate-use diversity) affected by snowpack. Elevated snow depth increased soil temperature (in the winter) and moisture (winter and spring), and was associated with reduced vegetation cover and microbial biomass carbon. Soil respiration showed an exponential increase with temperature, with a temperature sensitivity that decreased with increasing seasonal temperature (Q 10 = 4.3 [winter], 2.3 [spring], and 1.7 [summer]); frozen soils were associated with unrealistic Q 10 approximate to 7989 due to the liquid-to-ice transition of soil water. Soil respiration was sensitive to soil water content; predicted respiration under very dry conditions was less than 10% of respiration under moist conditions. While higher vegetation cover increased soil respiration, this was not due to increased root density, and may reflect differences in litter inputs. Microbial substrate-use diversity was negatively related to reference respiration (i.e., respiration rate at a reference temperature and optimal soil moisture), although the mechanism remains unclear. Lastly, this study indicates that soil respiration is inhibited by shallow snowpack through multiple mechanisms; thus, future decreases in snowpack across the sagebrush steppe have the potential to reduce losses of soil C, potentially affecting regional carbon balance.« less

Forest productivity varies with soil moisture more than temperature in a small montane watershed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Liang; Zhou, Hang; Link, Timothy E

Mountainous terrain creates variability in microclimate, including nocturnal cold air drainage and resultant temperature inversions. Driven by the elevational temperature gradient, vapor pressure deficit (VPD) also varies with elevation. Soil depth and moisture availability often increase from ridgetop to valley bottom. These variations complicate predictions of forest productivity and other biological responses. We analyzed spatiotemporal air temperature (T) and VPD variations in a forested, 27-km 2 catchment that varied from 1000 to 1650 m in elevation. Temperature inversions occurred on 76% of mornings in the growing season. The inversion had a clear upper boundary at midslope (~1370 m a.s.l.). Vapormore » pressure was relatively constant across elevations, therefore VPD was mainly controlled by T in the watershed. Here, we assessed the impact of microclimate and soil moisture on tree height, forest productivity, and carbon stable isotopes (δ 13C) using a physiological forest growth model (3-PG). Simulated productivity and tree height were tested against observations derived from lidar data. The effects on photosynthetic gas-exchange of dramatic elevational variations in T and VPD largely cancelled as higher temperature (increasing productivity) accompanies higher VPD (reducing productivity). Although it was not measured, the simulations suggested that realistic elevational variations in soil moisture predicted the observed decline in productivity with elevation. Therefore, in this watershed, the model parameterization should have emphasized soil moisture rather than precise descriptions of temperature inversions.« less

Forest productivity varies with soil moisture more than temperature in a small montane watershed

DOE PAGES

Wei, Liang; Zhou, Hang; Link, Timothy E; ...

2018-05-16

Mountainous terrain creates variability in microclimate, including nocturnal cold air drainage and resultant temperature inversions. Driven by the elevational temperature gradient, vapor pressure deficit (VPD) also varies with elevation. Soil depth and moisture availability often increase from ridgetop to valley bottom. These variations complicate predictions of forest productivity and other biological responses. We analyzed spatiotemporal air temperature (T) and VPD variations in a forested, 27-km 2 catchment that varied from 1000 to 1650 m in elevation. Temperature inversions occurred on 76% of mornings in the growing season. The inversion had a clear upper boundary at midslope (~1370 m a.s.l.). Vapormore » pressure was relatively constant across elevations, therefore VPD was mainly controlled by T in the watershed. Here, we assessed the impact of microclimate and soil moisture on tree height, forest productivity, and carbon stable isotopes (δ 13C) using a physiological forest growth model (3-PG). Simulated productivity and tree height were tested against observations derived from lidar data. The effects on photosynthetic gas-exchange of dramatic elevational variations in T and VPD largely cancelled as higher temperature (increasing productivity) accompanies higher VPD (reducing productivity). Although it was not measured, the simulations suggested that realistic elevational variations in soil moisture predicted the observed decline in productivity with elevation. Therefore, in this watershed, the model parameterization should have emphasized soil moisture rather than precise descriptions of temperature inversions.« less

Hydrologic control on redox and nitrogen dynamics in a peatland soil.

PubMed

Rubol, Simonetta; Silver, Whendee L; Bellin, Alberto

2012-08-15

Soils are a dominant source of nitrous oxide (N(2)O), a potent greenhouse gas. However, the complexity of the drivers of N(2)O production and emissions has hindered our ability to predict the magnitude and spatial dynamics of N(2)O fluxes. Soil moisture can be considered a key driver because it influences oxygen (O(2)) supply, which feeds back on N(2)O sources (nitrification versus denitrification) and sinks (reduction to dinitrogen). Soil water content is directly linked to O(2) and redox potential, which regulate microbial metabolism and chemical transformations in the environment. Despite its importance, only a few laboratory studies have addressed the effects of hydrological transient dynamics on nitrogen (N) cycling in the vadose zone. To further investigate these aspects, we performed a long term experiment in a 1.5 m depth soil column supplemented by chamber experiments. With this experiment, we aimed to investigate how soil moisture dynamics influence redox sensitive N cycling in a peatland soil. As expected, increased soil moisture lowered O(2) concentrations and redox potential in the soil. The decline was more severe for prolonged saturated conditions than for short events and at deep than at the soil surface. Gaseous and dissolved N(2)O, dissolved nitrate (NO(3)(-)) and ammonium (NH(4)(+)) changed considerably along the soil column profile following trends in soil O(2) and redox potential. Hot spots of N(2)O concentrations corresponded to high variability in soil O(2) in the upper and lower parts of the column. Results from chamber experiments confirmed high NO(3)(-) reduction potential in soils, particularly from the bottom of the column. Under our experimental conditions, we identified a close coupling of soil O(2) and N(2)O dynamics, both of which lagged behind soil moisture changes. These results highlight the relationship among soil hydrologic properties, redox potential and N cycling, and suggest that models working at a daily scale need to consider soil O(2) dynamics in addition to soil moisture dynamics to accurately predict patterns in N(2)O fluxes. Copyright © 2012 Elsevier B.V. All rights reserved.

Nitrous oxide fluxes from a claypan soil overlying nitrate-enriched glacial drift

USGS Publications Warehouse

Pomes, M.L.; Wilkison, D.H.; McMahon, P.B.

1998-01-01

The closed chamber method was used to assess nitrous oxide (N2O) fluxes from corn (Zea mays, L.) fields during the 1995 growing season. The study area was characterized by a claypan soil overlying a nitrate (NO31-)-enriched glacial-drift aquifer. Denitrification produced N2O fluxes of 0.2-6.9 g ha-1 hr-1 early in the growing season. Fluxes increased with increasing soil temperature, soil water potential, and soil saturation. However, greatly diminished N2O fluxes (0.001-0.09 gha-1 hr-1) occurred when soil saturation increased to 94 percent. Losses of N2O increased linearly during the day and decreased at night, probably because of declining soil temperatures. Declines in soil saturation (less than 80 percent) and soil moisture potential (less than -10 kPa) produced late season N2O fluxes (0.03-0.8 g ha-1 hr-1) attributable to nitrification. Results indicate that denitrification would not significantly reduce claypan soil NO31- concentrations.

Topographic soil wetness index derived from combined Alaska-British Columbia datasets for the Gulf of Alaska region

NASA Astrophysics Data System (ADS)

D'Amore, D. V.; Biles, F. E.

2016-12-01

The flow of water is often highlighted as a priority in land management planning and assessments related to climate change. Improved measurement and modeling of soil moisture is required to develop predictive estimates for plant distributions, soil moisture, and snowpack, which all play important roles in ecosystem planning in the face of climate change. Drainage indexes are commonly derived from GIS tools with digital elevation models. Soil moisture classes derived from these tools are useful digital proxies for ecosystem functions associated with the concentration of water on the landscape. We developed a spatially explicit topographically derived soil wetness index (TWI) across the perhumid coastal temperate rainforest (PCTR) of Alaska and British Columbia. Developing applicable drainage indexes in complex terrain and across broad areas required careful application of the appropriate DEM, caution with artifacts in GIS covers and mapping realistic zones of wetlands with the indicator. The large spatial extent of the model has facilitated the mapping of forest habitat and the development of water table depth mapping in the region. A key element of the TWI is the merging of elevation datasets across the US-Canada border where major rivers transect the international boundary. The unified TWI allows for seemless mapping across the international border and unified ecological applications. A python program combined with the unified DEM allows end users to quickly apply the TWI to all areas of the PCTR. This common platform can facilitate model comparison and improvements to local soil moisture conditions, generation of streamflow, and ecological site conditions. In this presentation we highlight the application of the TWI for mapping risk factors related to forest decline and the development of a regional water table depth map. Improved soil moisture maps are critical for deriving spatial models of changes in soil moisture for both plant growth and streamflow across future climate conditions.

Biogeochemistry of a treeline watershed, northwestern Alaska

USGS Publications Warehouse

Stottlemyer, R.

2001-01-01

Since 1950, mean annual temperatures in northwestern Alaska have increased. Change in forest floor and soil temperature or moisture could alter N mineralization rates, production of dissolved organic carbon (DOC) and organic nitrogen (DON), and their export to the aquatic ecosystem. In 1990, we began study of nutrient cycles in the 800-ha Asik watershed, located at treeline in the Noatak National Preserve, northwestern Alaska. This paper summarizes relationships between topographic aspect, soil temperature and moisture, inorganic and organic N pools, C pools, CO2 efflux, growing season net N mineralization rates, and stream water chemistry. Forest floor (O2) C/N ratios, C pools, temperature, and moisture were greater on south aspects. More rapid melt of the soil active layer (zone of annual freeze-thaw) and permafrost accounted for the higher moisture. The O2 C and N content were correlated with moisture, inorganic N pools, CO2 efflux, and inversely with temperature. Inorganic N pools were correlated with temperature and CO2 efflux. Net N mineralization rates were positive in early summer, and correlated with O2 moisture, temperature, and C and N pools. Net nitrification rates were inversely correlated with moisture, total C and N. The CO2 efflux increased with temperature and moisture, and was greater on south aspects. Stream ion concentrations declined and DOC increased with discharge. Stream inorganic nitrogen (DIN) output exceeded input by 70%. Alpine stream water nitrate (NO-3) and DOC concentrations indicated substantial contributions to the watershed DIN and DOC budgets.

Biogeochemistry of a treeline watershed, northwestern Alaska.

PubMed

Stottlemyer, R

2001-01-01

Since 1950, mean annual temperatures in northwestern Alaska have increased. Change in forest floor and soil temperature or moisture could alter N mineralization rates, production of dissolved organic carbon (DOC) and organic nitrogen (DON), and their export to the aquatic ecosystem. In 1990, we began study of nutrient cycles in the 800-ha Asik watershed, located at treeline in the Noatak National Preserve, northwestern Alaska. This paper summarizes relationships between topographic aspect, soil temperature and moisture, inorganic and organic N pools, C pools, CO2 efflux, growing season net N mineralization rates, and stream water chemistry. Forest floor (O2) C/N ratios, C pools, temperature, and moisture were greater on south aspects. More rapid melt of the soil active layer (zone of annual freeze-thaw) and permafrost accounted for the higher moisture. The O2 C and N content were correlated with moisture, inorganic N pools, CO2 efflux, and inversely with temperature. Inorganic N pools were correlated with temperature and CO2 efflux. Net N mineralization rates were positive in early summer, and correlated with O2 moisture, temperature, and C and N pools. Net nitrification rates were inversely correlated with moisture, total C and N. The CO2 efflux increased with temperature and moisture, and was greater on south aspects. Stream ion concentrations declined and DOC increased with discharge. Stream inorganic nitrogen (DIN) output exceeded input by 70%. Alpine stream water nitrate (NO3-) and DOC concentrations indicated substantial contributions to the watershed DIN and DOC budgets.

Scaling Soil Microbe-Water Interactions from Pores to Ecosystems

NASA Astrophysics Data System (ADS)

Manzoni, S.; Katul, G. G.

2014-12-01

The spatial scales relevant to soil microbial activity are much finer than scales relevant to whole-ecosystem function and biogeochemical cycling. On the one hand, how to link such different scales and develop scale-aware biogeochemical and ecohydrological models remains a major challenge. On the other hand, resolving these linkages is becoming necessary for testing ecological hypotheses and resolving data-theory inconsistencies. Here, the relation between microbial respiration and soil moisture expressed in water potential is explored. Such relation mediates the water availability effects on ecosystem-level heterotrophic respiration and is of paramount importance for understanding CO2 emissions under increasingly variable rainfall regimes. Respiration has been shown to decline as the soil dries in a remarkably consistent way across climates and soil types (open triangles in Figure). Empirical models based on these respiration-moisture relations are routinely used in Earth System Models to predict moisture effects on ecosystem respiration. It has been hypothesized that this consistency in microbial respiration decline is due to breakage of water film continuity causing in turn solute diffusion limitations in dry conditions. However, this hypothesis appears to be at odds with what is known about soil hydraulic properties. Water film continuity estimated from soil water retention (SWR) measurements at the 'Darcy' scale breaks at far less negative water potential (<-0.1 MPa) levels than where microbial respiration ceases (approximately -15 MPa) as shown in the Figure (violet frequency distribution). Also, this threshold point inferred from SWR shows strong texture dependence, in contrast to the respiration curves. Employing theoretical tools from percolation theory, it is demonstrated that hydrological measurements can be spatially downscaled at a micro-level relevant to microbial activity. Such downscaling resolves the inconsistency between respiration thresholds and hydrological thresholds. This result, together with observations of residual microbial activity well below -15 MPa (dashed back curve in Figure), lends support to the hypothesis that soil microbes are substrate-limited in dry conditions.

Accounting for sap flow from different parts of the root system improves the prediction of xylem ABA concentration in plants grown with heterogeneous soil moisture.

PubMed

Dodd, Ian C; Egea, Gregorio; Davies, William J

2008-01-01

When soil moisture is heterogeneous, sap flow from, and ABA status of, different parts of the root system impact on leaf xylem ABA concentration ([X-ABA]leaf). The robustness of a model for predicting [X-ABA]leaf was assessed. 'Two root-one shoot' grafted sunflower (Helianthus annuus L.) plants received either deficit irrigation (DI, each root system received the same irrigation volumes) or partial rootzone drying (PRD, only one root system was watered and the other dried the soil). Irrespective of whether relative sap flow was assessed using sap flow sensors in vivo or by pressurization of de-topped roots, each root system contributed similarly to total sap flow during DI, while sap flow from roots in drying soil declined linearly with soil water potential (Psisoil) during PRD. Although Psisoil of the irrigated pot determined the threshold Psisoil at which sap flow from roots in drying soil decreased, the slope of this decrease was independent of the wet pot Psisoil. Irrespective of whether sap was collected from the wet or dry root system of PRD plants, or a DI plant, root xylem ABA concentration increased as Psisoil declined. The model, which weighted ABA contributions of each root system according to the sap flow from each, almost perfectly explained [X-ABA] immediately above the graft union. That the model overestimated measured [X-ABA]leaf may result from changes in [X-ABA] along the transport pathway or an artefact of collecting xylem sap from detached leaves. The implications of declining sap flow through partially dry roots during PRD for the control of stomatal behaviour and irrigation scheduling are discussed.

Arbuscular Mycorrhiza Alleviates Restrictions to Substrate Water Flow and Delays Transpiration Limitation to Stronger Drought in Tomato

PubMed Central

Bitterlich, Michael; Sandmann, Martin; Graefe, Jan

2018-01-01

Arbuscular mycorrhizal fungi (AMF) proliferate in soil pores, on the surface of soil particles and affect soil structure. Although modifications in substrate moisture retention depend on structure and could influence plant water extraction, mycorrhizal impacts on water retention and hydraulic conductivity were rarely quantified. Hence, we asked whether inoculation with AMF affects substrate water retention, water transport properties and at which drought intensity those factors become limiting for plant transpiration. Solanum lycopersicum plants were set up in the glasshouse, inoculated or not with Funneliformis mosseae, and grown for 35 days under ample water supply. After mycorrhizal establishment, we harvested three sets of plants, one before (36 days after inoculation) and the second (day 42) and third (day 47) within a sequential drying episode. Sampling cores were introduced into pots before planting. After harvest, moisture retention and substrate conductivity properties were assessed and water retention and hydraulic conductivity models were fitted. A root water uptake model was adopted in order to identify the critical substrate moisture that induces soil derived transpiration limitation. Neither substrate porosity nor saturated water contents were affected by inoculation, but both declined after substrates dried. Drying also caused a decline in pot water capacity and hydraulic conductivity. Plant available water contents under wet (pF 1.8–4.2) and dry (pF 2.5–4.2) conditions increased in mycorrhizal substrates and were conserved after drying. Substrate hydraulic conductivity was higher in mycorrhizal pots before and during drought exposure. After withholding water from pots, higher substrate drying rates and lower substrate water potentials were found in mycorrhizal substrates. Mycorrhiza neither affected leaf area nor root weight or length. Consistently with higher substrate drying rates, AMF restored the plant hydraulic status, and increased plant transpiration when soil moisture declined. The water potential at the root surface and the resistance to water flow in the rhizosphere were restored in mycorrhizal pots although the bulk substrate dried more. Finally, substrates colonized by AMF can be more desiccated before substrate water flux quantitatively limits transpiration. This is most pronounced under high transpiration demands and complies with a difference of over 1,000 hPa in substrate water potential. PMID:29503655

Invasion of a semi-arid shrubland by annual grasses increases autotrophic and heterotrophic soil respiration rates due to altered soil moisture and temperature patterns

NASA Astrophysics Data System (ADS)

Mauritz, M.; Hale, I.; Lipson, D.

2010-12-01

Shrub <-> grassland conversions are a globally occurring phenomenon altering habitat structure, quality and nutrient cycling. Grasses and shrubs differ in their above and belowground biomass allocation, root architecture, phenology, litter quality and quantity. Conversion affects soil microbial communities, soil moisture and temperature and carbon (C) allocation patterns. However, the effect of conversion on C storage is regionally variable and there is no consistent direction of change. In Southern California invasion by annual grasses is a major threat to native shrub communities and it has been proposed that grass invasion increases NPP and ecosystem C storage (Wolkovich et al, 2009). In order to better understand how this shrub <-> grassland conversion changes ecosystem C storage it is important to understand the partitioning of soil respiration into autotrophic and heterotrophic components. Respiration was measured in plots under shrubs and grasses from February when it was cold and wet to July when it was hot and dry, capturing seasonal transitions in temperature and water availability. Roots were excluded under shrubs and grasses with root exclusion cores to quantify heterotrophic respiration. Using total soil respiration (Rt) = autotrophic respiration (root) (Ra)+ heterotrophic respiration (microbial) (Rh) the components contributing to total soil respiration can be evaluated. Respiration, soil moisture and temperature were measured daily at four hour intervals using Licor 8100 automated chamber measurements. Throughout the measurement period, Rt under grasses exceeded Rt under shrubs. Higher Rt levels under grasses were mainly due to higher Ra in grasses rather than changes in Rh. On average grass Ra was almost double shrub Ra. Higher grass respiration levels are partially explained by differences in soil moisture and temperature between shrubs and grasses. Respiration rates responded similarly to seasonal transitions regardless of treatment although Ra had a much stronger seasonal response. Across all months changes in respiration rates are explained by changes in soil moisture. However, within wet periods respiration rates increase with temperature. From February to April the soil was wet and respiration levels gradually increased as day time soil temperatures increased. From April onwards absence of precipitation events and rising soil temperatures caused the soils to rapidly dry out. As a result Rt rates declined and gradually converged with Rh levels. As soils dried, grass Ra declined more gradually than shrub Ra. This was contrary to our expectation that shrub roots would respire longer into the dry season because they have deeper roots and can access water. The high late-season levels of respiration observed in the grass community are possibly due to the presence of invasive forbs which have deep tap roots and continue to grow after the grasses have senesced. Conversion from native shrubs to annual invasive grasses increased both Rt and Rh which indicates changes in plant C allocation and decomposition rates of soil C. The continued encroachment of grasses on shrubland has important implications for the future of C storage in this system.

Application of time-lapse ERT to characterize soil-water-disease interactions of young citrus trees

NASA Astrophysics Data System (ADS)

Peddinti, S. R.; Kbvn, D. P.; Ranjan, S.; R M, P. G.

2016-12-01

Vidarbha region in Maharashtra, India is witnessing a continuous decrease in orange crop due to the propagation of `Phytopthora root rot', a water mold disease. Under favorable conditions, the disease causing bacteria can attack the plant root system and propagates to the surface (where first visual impression is made), making difficult to regain the plant health. This research aims at co-relating eco-hydrological fluxes with disease sensing parameters of orange trees. Two experimental plots around a healthy-young and declined-young orange trees were selected for our analysis. A 3-dimentional electrical resistivity tomography (ERT) (Figure) was carried at each plot to quantify the soil moisture distribution at a vadose zone. Pedo-electric relations were obtained considering modified Archie's law parameters. ERT derived moisture data was validated with time domain reflectometry (TDR) point observations. Soil moisture profiles derived from ERT were observed to be differ marginally between the two plots. Disease quantification was done by estimating the density of Phytopthora spp. inoculum in soils sampled along the root zone. Identification of Phytopthora spp. was done in the laboratory using taxonomic and morphologic criteria of the colonies. Spatio-temporal profiles of soil moisture and inoculum density were then co-related to comment on the eco-hydrological fluxes contributing to the health propagation of root rot in orange tree for implementing effective water management practices.

High temperature causes negative whole-plant carbon balance under mild drought.

PubMed

Zhao, Junbin; Hartmann, Henrik; Trumbore, Susan; Ziegler, Waldemar; Zhang, Yiping

2013-10-01

Theoretically, progressive drought can force trees into negative carbon (C) balance by reducing stomatal conductance to prevent water loss, which also decreases C assimilation. At higher temperatures, negative C balance should be initiated at higher soil moisture because of increased respiratory demand and earlier stomatal closure. Few data are available on how these theoretical relationships integrate over the whole plant. We exposed Thuja occidentalis to progressive drought under three temperature conditions (15, 25, and 35°C), and measured C and water fluxes using a whole-tree chamber design. High transpiration rates at higher temperatures led to a rapid decline in soil moisture. During the progressive drought, soil moisture-driven changes in photosynthesis had a greater impact on the whole-plant C balance than respiration. The soil moisture content at which whole-plant C balance became negative increased with temperature, mainly as a result of higher respiration rates and an earlier onset of stomatal closure under a warmer condition. Our results suggest that the effect of drought on whole-plant C balance is highly temperature-dependent. High temperature causes a negative C balance even under mild drought and may increase the risk of C starvation. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Linkages Between Terrestrial Carbon Uptake and Interannual Climate Variability over the Texas-northern Mexico High Plains

NASA Astrophysics Data System (ADS)

Parazoo, N.; Barnes, E. A.; Worden, J.; Harper, A. B.; Bowman, K. W.; Frankenberg, C.

2014-12-01

The Texas-northern Mexico high plains experienced record drought conditions in 2011 during strong negative phases of ENSO and the NAO. Given predictions of increased frequency and severity of drought under projected climate change [e.g., Reichstein et al., 2013] and recent findings of CO2 growth rate sensitivity to interannual variability of carbon uptake in semi-arid ecosystems [Poulter et al., 2014], we investigate the response of carbon uptake in the Texas high plains to interannual climate variability with the goal of improved mechanistic understanding of climate-carbon cycle links. Specifically, we examine (1) observed tendencies in regional scale carbon uptake and soil moisture from 2010 to 2011 using satellite observations of gross primary production (GPP) (from plant fluorescence) from GOSAT and soil moisture from SMOS, and (2) the interannual relationship between GPP and ENSO & NAO variability using terrestrial biosphere simulations from 1950-2012. Observations reveal widespread decline of GPP in 2011 (0.42 +/- 0.04 Pg C yr-1) correlated with negative soil moisture tendencies (r = 0.85 +/- 0.21) which leads to corresponding declines in net carbon uptake and transpiration (according to model simulations). Further examination of model results over the period 1950-2012 indicates that negative GPP anomalies are linked systematically to winter and spring precipitation deficits associated with overlapping negative phases of winter NAO and ENSO, with increasing magnitude of negative anomalies in strong La Niña years. Furthermore, the strongest decline of GPP, carbon uptake, and transpiration on record occurred during the 2011 drought and were associated with extreme negative phases of ENSO and NAO, with 2011 being the only year since 1950 that both indices exceeded 1 σ standard deviation.

Forest restoration as a strategy to mitigate climate impacts on wildfire, vegetation, and water in semi-arid forests of the southwestern U.S.

NASA Astrophysics Data System (ADS)

O'Donnell, F. C.; Flatley, W. T.; Masek Lopez, S.; Fulé, P. Z.; Springer, A. E.

2017-12-01

Climate change and fire suppression are interacting to reduce forest health, drive high-intensity wildfires, and potentially reduce water quantity and quality in high-elevation forests of the southwestern US. Forest restoration including thinning and prescribed fire, is a management approach that reduces fire risk. It may also improve forest health by increasing soil moisture through the combined effects of increased snow pack and reduced evapotranspiration (ET), though the relative importance of these mechanisms is unknown. It is also unclear how small-scale changes in the hydrologic cycle will scale-up to influence watershed dynamics. We conducted field and modeling studies to investigate these issues. We measured snow depth, snow water equivalent (SWE), and soil moisture at co-located points in paired restoration-control plots near Flagstaff, AZ. Soil moisture was consistently higher in restored plots across all seasons. Snow depth and SWE were significantly higher in restored plots immediately after large snow events with no difference one week after snowfall, suggesting that restoration leads to both increased accumulation and sublimation. At the point scale, there was a small (ρ=0.28) but significant correlation between fall-to-spring soil moisture increase and peak SWE during the winter. Consistent with previous studies, soil drying due to ET was more rapid in recently restored sites than controls, but there was no difference 10 years after restoration. In addition to the small role played by snow and ET, we also observed more rapid soil moisture loss in the 1-2 days following rain or rapid snowmelt in control than in restoration plots. We hypothesize that this is due to a loss of macropores when woody plants are replaced by herbaceous vegetation and warrants further study. To investigate watershed-scale dynamics, we combined spatially-explicit vegetation and fire modeling with statistical water and sediment yield models for a large forested landscape on the Kaibab Plateau, AZ. Our results predicted that climate-induced vegetation changes will result in annual runoff declines of 2%-10% in the next century, but that restoration reversed these declines. We also predict that restoration treatments will protect water quality by reducing the incidence of high severity fire and the associated erosion.

Fine scale climatic and soil variability effects on plant species cover along the Front Range of Colorado, USA

NASA Astrophysics Data System (ADS)

Cumming, William Frank Preston

Fine scale studies are rarely performed to address landscape level responses to microclimatic variability. Is it the timing, distribution, and magnitude of soil temperature and moisture that affects what species emerge each season and, in turn, their resilience to fluctuations in microclimate. For this dissertation research, I evaluated the response of vegetation change to microclimatic variability within two communities over a three year period (2009-2012) utilizing 25 meter transects at two locations along the Front Range of Colorado near Boulder, CO and Golden, CO respectively. To assess microclimatic variability, spatial and temporal autocorrelation analyses were performed with soil temperature and moisture. Species cover was assessed along several line transects and correlated with microclimatic variability. Spatial and temporal autocorrelograms are useful tools in identifying the degree of dependency of soil temperature and moisture on the distance and time between pairs of measurements. With this analysis I found that a meter spatial resolution and two-hour measurements are sufficient to capture the fine scale variability in soil properties throughout the year. By comparing this to in situ measurements of soil properties and species percent cover I found that there are several plant functional types and/or species origin in particular that are more sensitive to variations in temperature and moisture than others. When all seasons, locations, correlations, and regional climate are looked at, it is the month of March that stands out in terms of significance. Additionally, of all of the vegetation types represented at these two sites C4, C3, native, non-native, and forb species seem to be the most sensitive to fluctuations in soil temperature, moisture, and regional climate in the spring season. The steady decline in percent species cover the study period and subsequent decrease in percent species cover and size at both locations may indicate that certain are unable to respond to continually higher temperatures and lower moisture availability that is inevitable with future climatic variability.

Drought effects on soil carbon dioxide production in two ecosystems in Central Sulawesi, Indonesia

NASA Astrophysics Data System (ADS)

van Straaten, Oliver

2010-05-01

Drought response on soil CO2 production dynamics were examined in two tropical ecosystems in central Sulawesi, Indonesia. Large-scale throughfall displacement roofs were built in a cacao (Theobroma cacao) / Gliricidia sepium agroforestry plantation (560 m.a.s.l.) and in a sub-montane tropical rainforest (1050 m.a.s.l.) to simulate drought conditions. At each site, ecosystem drought responses from three roof plots were compared to three undisturbed control plots. Soil CO2 production was measured spatially at the soil surface and vertically within the soil profile to 2.5 m depth every two weeks. 1. The cacao / Gliricidia ecosystem exhibited a mild drought response. Here, soil CO2 production decreased by 13% in comparison to the control plots during the 13 month induced drought. The mild drought response is attributed to two reasons. First, soil CO2 efflux exhibited an inverse parabolic relationship with soil moisture (R2 = 0.32): soil CO2 efflux peaked at intermediate moisture conditions, but was low when soil conditions became dry (in the induced drought plots), and when the soil became water saturated (in the control plots). This means that respiration differences between control and roof plots may have been masked when soil moisture conditions were saturated in the control and concurrently dry in roof plots. Secondly, the shallow rooted cacao understory grown next to the deeper rooted Gliricidia overstory created a favourable set of site conditions that enabled the ecosystem to mitigate serious drought stress. The experiment had a CO2 neutral effect overall: emissions were initially reduced during the induced drought period but rebounded and surpassed the control during the five month rewetting phase, thus compensating for earlier declines. 2. In contrast, the sub-montane tropical rainforest experienced a severe decrease in soil CO2 production. Here, soil CO2 efflux decreased by an average of 39% in comparison to the control during the 24 month induced drought period. Soil moisture, the main variable controlling CO2, exhibited a strong positive linear relationship with soil CO2 production (R2 = 0.72). A two phase ecosystem drought response was observed. During the first phase, which lasted nine months, leaf litter respiration declined while the total respiration from autotrophic and belowground heterotrophic sources remained relatively unchanged, although an upward shift from the subsoil to the soil surface was measured. During the second phase of the experiment, when drought conditions intensified further (the next 16 months), belowground CO2 production from heterotrophic and autotrophic sources decreased at all soil depths. Leaf litter respiration remained negligible. Recuperation after the drought was slow in this ecosystem and did not rebound to control plot levels. In this ecosystem, the simulated drought resulted in a reduction in overall CO2 emission.

The Rocky Mountain Epidemic of Bark Beetles and Blue Stain Fungi Cause Cascading Effects on Coupled Water, C and N cycles

NASA Astrophysics Data System (ADS)

Ewers, B. E.; Pendall, E.; Norton, U.; Reed, D.; Franks, J.; Aston, T.; Whitehouse, F.; Barnard, H. R.; Brooks, P. D.; Angstmann, J.; Massman, W. J.; Williams, D. G.; Harpold, A. A.; Biederman, J.; Edburg, S. L.; Meddens, A. J.; Gochis, D. J.; Hicke, J. A.

2010-12-01

The ongoing epidemic of bark beetles and their associated xylem blocking blue-stain fungi is unprecedented in Rocky Mountain subalpine forests. As this epidemic continues, we seek to improve our predictive understanding of coupled water, C and N cycles by quantifying how these cycles may become uncoupled in response to the outbreak. Our specific questions are 1) how does the rapid drop in individual tree transpiration impact the temporal and spatial extent of evapotranspiration and 2) how does the subsequent increase in soil moisture and lower C inputs and N uptake impact soil C and N fluxes? We address these questions in two forest ecosystems using eddy covariance, sap flux, leaf gas exchange, plant hydraulic conductance, vegetation characteristics and soil trace gas measurements. We applied two sampling designs 1) subdivide the lodgepole pine forest spatially into varying degrees of bark beetle and blue stain infection and 2) follow the fluxes as the outbreak continues at a point in space encompassing the range of spatial variability in mortality. The first order impact of the bark beetle and blue stain fungi is dramatic in all tree species with a greater than 50% reduction in transpiration per tree within a month of infection. This change occurs even before the characteristic red tinge occurs in the needles or before the sapwood is stained blue. Leaf stomatal conductance declines more than either the biochemical or light harvesting components of photosynthesis immediately after infestation. The annual C sink at the spruce/fir forest has declined from -2.88 to -0.57 Mg C ha-1 yr-1 from 2006 to 2009. Annual evapotranspiration (ET) over the last five years at the spruce/fir forest now has an inverse relationship with precipitation because the last two years have seen a dramatic decrease (from 73 to 59 cm/year) in ET while precipitation has increased (from ~100 to 140 cm/year). Soil moisture in both forests has increased up to 100% within one growing season in lodgepole pine stands with high mortality. At the spruce/fir forest, July soil moisture has increased more than 30% over the last five years. Soil respiration has declined likely from lower labile C inputs while CH4 consumption has decreased due to higher soil moisture. N2O fluxes have increased with mineral N availability. Our results suggest that C, N and water cycles have become decoupled within two years of infestation. However, these soil impacts are not yet as dramatic when scaled up to the eddy covariance footprint which includes uninfested areas. We test these mechanisms at larger scales and investigate C and N cycles as succession occurs using the Community Land Model (CLM).

Seasonal and diurnal gas exchange differences in ozone-sensitive common milkweed (Asclepias syriaca L.) in relation to ozone uptake.

PubMed

Bergweiler, Chris; Manning, William J; Chevone, Boris I

2008-03-01

Stomatal conductance and net photosynthesis of common milkweed (Asclepias syriaca L.) plants in two different soil moisture regimes were directly quantified and subsequently modeled over an entire growing season. Direct measurements captured the dynamic response of stomatal conductance to changing environmental conditions throughout the day, as well as declining gas exchange and carbon assimilation throughout the growth period beyond an early summer maximum. This phenomenon was observed in plants grown both with and without supplemental soil moisture, the latter of which should theoretically mitigate against harmful physiological effects caused by exposure to ozone. Seasonally declining rates of stomatal conductance were found to be substantial and incorporated into models, making them less susceptible to the overestimations of effective exposure that are an inherent source of error in ozone exposure indices. The species-specific evidence presented here supports the integration of dynamic physiological processes into flux-based modeling approaches for the prediction of ozone injury in vegetation.

Carbon exchange in biological soil crust communities under differential temperatures and soil water contents: implications for global change

USGS Publications Warehouse

Grote, Edmund E.; Belnap, Jayne; Housman, David C.; Sparks, Jed P.

2010-01-01

Biological soil crusts (biocrusts) are an integral part of the soil system in arid regions worldwide, stabilizing soil surfaces, aiding vascular plant establishment, and are significant sources of ecosystem nitrogen and carbon. Hydration and temperature primarily control ecosystem CO2 flux in these systems. Using constructed mesocosms for incubations under controlled laboratory conditions, we examined the effect of temperature (5-35 1C) and water content (WC, 20-100%) on CO2 exchange in light cyanobacterially dominated) and dark cyanobacteria/lichen and moss dominated) biocrusts of the cool Colorado Plateau Desert in Utah and the hot Chihuahuan Desert in New Mexico. In light crusts from both Utah and New Mexico, net photosynthesis was highest at temperatures 430 1C. Net photosynthesis in light crusts from Utah was relatively insensitive to changes in soil moisture. In contrast, light crusts from New Mexico tended to exhibit higher rates of net photosynthesis at higher soil moisture. Dark crusts originating from both sites exhibited the greatest net photosynthesis at intermediate soil water content (40-60%). Declines in net photosynthesis were observed in dark crusts with crusts from Utah showing declines at temperatures 425 1C and those originating from New Mexico showing declines at temperatures 435 1C. Maximum net photosynthesis in all crust types from all locations were strongly influenced by offsets in the optimal temperature and water content for gross photosynthesis compared with dark respiration. Gross photosynthesis tended to be maximized at some intermediate value of temperature and water content and dark respiration tended to increase linearly. The results of this study suggest biocrusts are capable of CO2 exchange under a wide range of conditions. However, significant changes in the magnitude of this exchange should be expected for the temperature and precipitation changes suggested by current climate models.

The Fate of Aspen in a World with Diminishing Snowpacks

NASA Astrophysics Data System (ADS)

Kavanagh, K.; Link, T. E.; Seyfried, M. S.; Kemp, K. B.

2010-12-01

Aspen (Populus tremuloides) productivity is tightly coupled with soil moisture. In the mountainous regions of the western USA, annual replenishment of soil moisture commonly occurs during snowmelt. Therefore, snow pack depth and duration can play an important role in sustaining aspen productivity. The presence of almost 50 years of detailed climate data across an elevational transect in the Reynolds Creek Experimental Watershed (RCEW) in southwestern Idaho offers a novel opportunity to better understand the role of shifting precipitation patterns on aspen productivity. Over the past 50 years, the proportion of the precipitation falling in the form of snow decreased by almost a factor of 2 at mid to low elevations in the RCEW, coupled with a roughly four week advance of snow ablation, and decline of large snow drifts that release moisture into the early summer. Results from growth ring increment, stable isotope analysis, sapflux and a process model (Biome BGC), will be used to determine the impact of shifting precipitation patterns on tree productivity along this transect over the past 50 years. Aspen trees located on moist microsites continue to transpire water and maintain high stomatal conductance 21 days later in the growing season relative to individuals on drier microsites. Predictions of net primary productivity (NPP) in aspen are very sensitive to precipitation patterns. NPP becomes negative as early as day 183 (90 days post budbreak) for years with little winter and spring precipitation whereas, in years with ample winter and spring precipitation, NPP remains positive until day 260 when leaf fall occurs. These results give unique insight into the conditions that deciduous tree species will encounter in a warming climate where snow water equivalent continues to diminish and soil moisture declines soon after budbreak occurs.

Potential nitrogen fixation activity of different aged biological soil crusts from rehabilitated grasslands of the hilly Loess Plateau, China

USGS Publications Warehouse

Zhao, Y.; Xu, M.; Belnap, J.

2010-01-01

Biological soil crusts (biocrusts) cover up to 60–70% of the soil surface in grasslands rehabilitated during the "Grain for Green" project implemented in the hilly Loess Plateau region in 1999. As biocrusts fix nitrogen (N), they are an important part of restoring soil fertility. We measured nitrogenase activity (NA) in biocrusts from sites rehabilitated at six different time periods to estimate 1) the effects of moisture content and temperature on NA in biocrusts of different ages and 2) the potential N contribution from biocrusts to soils and plants in this region. Results show that NA in the biocrusts was mostly controlled by the species composition, as the activity of biocrusts dominated by free-living soil cyanobacteria was significantly higher than that of moss-dominated biocrusts. Nitrogenase activity was also influenced by soil moisture content and ambient temperature, with a significant decline in activity when moisture levels were decreased to 20% field water-holding capacity. The optimal temperature for NA was 35–40 °C and 30–40 °C for cyanobacteria- and moss-dominated biocrusts, respectively. Biocrust fixed N is likely an important source of N in this ecosystem, as we estimated annual potential N inputs per hectare in these grasslands to be up to 13 kg N ha-1 and 4 kg N ha-1 for cyanobacteria- and moss-dominated biocrusts, respectively.

Soil moisture depletion under simulated drought in the Amazon: impacts on deep root uptake.

PubMed

Markewitz, Daniel; Devine, Scott; Davidson, Eric A; Brando, Paulo; Nepstad, Daniel C

2010-08-01

*Deep root water uptake in tropical Amazonian forests has been a major discovery during the last 15 yr. However, the effects of extended droughts, which may increase with climate change, on deep soil moisture utilization remain uncertain. *The current study utilized a 1999-2005 record of volumetric water content (VWC) under a throughfall exclusion experiment to calibrate a one-dimensional model of the hydrologic system to estimate VWC, and to quantify the rate of root uptake through 11.5 m of soil. *Simulations with root uptake compensation had a relative root mean square error (RRMSE) of 11% at 0-40 cm and < 5% at 350-1150 cm. The simulated contribution of deep root uptake under the control was c. 20% of water demand from 250 to 550 cm and c. 10% from 550 to 1150 cm. Furthermore, in years 2 (2001) and 3 (2002) of throughfall exclusion, deep root uptake increased as soil moisture was available but then declined to near zero in deep layers in 2003 and 2004. *Deep root uptake was limited despite high VWC (i.e. > 0.30 cm(3) cm(-3)). This limitation may partly be attributable to high residual water contents (theta(r)) in these high-clay (70-90%) soils or due to high soil-to-root resistance. The ability of deep roots and soils to contribute increasing amounts of water with extended drought will be limited.

Effects of Climate and Social Change on Pasture Productivity and Area in the Alay Valley, Kyrgyzstan

NASA Astrophysics Data System (ADS)

Zhang, L.; Smithwick, E. A. H.

2017-12-01

The high elevation Alay Valley, located in the central Asian country of Kyrgyzstan, has experienced substantial socio-political and environmental changes in recent decades, resulting from the collapse of the Soviet Union and an increase in average annual temperature from 1.8 C to 2.7 C between 1990 and 2014. However, the consequences of these changes on pastureland productivity and area has not been previously assessed, despite the critical cultural and economic importance of pasturelands for sustaining livelihoods in this region. We assessed spatial and temporal patterns of soil moisture, pasture productivity and pasture area in the Alay Valley. Supervised classification was performed on Landsat imagery over the study region to distinguish pastures and agricultural land in order to relate changes in soil moisture to specific land classes. Root Zone Soil Moisture (RZSM) was estimated between May 2015 and June 2017 from Soil Moisture Active Passive L4 RZSM product. Average monthly NDVI for 2016 was calculated to obtain seasonal patterns in productivity of the pasturelands in the region. Results show that annual RZSM trends closely matched those of precipitation, as RZSM peaks during May (the wettest month) and decreases during the dry summer. The NDVI trend is also notable as it peaks very early in June before declining due to limited precipitation and grazing practices. There has been a sharp increase in pasturelands encompassing the bank of the Kyzyl Suu river from 1993 to 2016. Likely due to turmoil from collapse of the USSR, the area of pasturelands decreased slightly from 59.98 to 55.99 km^2 from 1993-1994, corresponding with a decline in livestock count and GDP per capita. The area of pasturelands has since recovered and is hovering around 104.47 - 107.95 km^2 between 2009-2016. Overall results highlight both sensitivity and resilience of high elevation pasture to coupled socio-environmental drivers.

Spatial distribution of tree species governs the spatio-temporal interaction of leaf area index and soil moisture across a forested landscape.

PubMed

Naithani, Kusum J; Baldwin, Doug C; Gaines, Katie P; Lin, Henry; Eissenstat, David M

2013-01-01

Quantifying coupled spatio-temporal dynamics of phenology and hydrology and understanding underlying processes is a fundamental challenge in ecohydrology. While variation in phenology and factors influencing it have attracted the attention of ecologists for a long time, the influence of biodiversity on coupled dynamics of phenology and hydrology across a landscape is largely untested. We measured leaf area index (L) and volumetric soil water content (θ) on a co-located spatial grid to characterize forest phenology and hydrology across a forested catchment in central Pennsylvania during 2010. We used hierarchical Bayesian modeling to quantify spatio-temporal patterns of L and θ. Our results suggest that the spatial distribution of tree species across the landscape created unique spatio-temporal patterns of L, which created patterns of water demand reflected in variable soil moisture across space and time. We found a lag of about 11 days between increase in L and decline in θ. Vegetation and soil moisture become increasingly homogenized and coupled from leaf-onset to maturity but heterogeneous and uncoupled from leaf maturity to senescence. Our results provide insight into spatio-temporal coupling between biodiversity and soil hydrology that is useful to enhance ecohydrological modeling in humid temperate forests.

Mechanisms control the soil organic carbon loss with grassland degradation in the Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

Peng, Fei; Xian, Xue; You, Quangang; Huang, Cuihua; Dong, Siyang; Liao, Jie; Duan, Hanchen; Wang, Tao

2017-04-01

Grassland in the Qinghai-Tibet Plateau (QTP) provides tremendous carbon (C) sinks and is the important ground for grazing. Grassland degradation, the loss of plant coverage and the emergence of sand activities, results in substantial reduction in soil organic carbon (SOC). To demonstrate the specific degradation pattern of SOC and elucidate underlying mechanisms, a sequence of five degradation stages over the whole grassland in the QTP were investigated. The survey and laboratory data were analyzed by three structural equation modeling (SEM) analysis. One of the analysis focused on the biological processes while the other two included both the biological and physical processes. Soil temperature had no significant change but soil moisture decreased in all layers. The above and the below-ground plant production decreased and the dominant plant functional group shifted from sedge and grass to forbs. The SOC concentration declined about 40-50% in the very severely degraded comparing with intact alpine grassland.All the three models were successfully fitted with R2 about 0.50. Three biological processes can explain the SOC change. The decrease in soil moisture suppressed C output through soil respiration (Rs) thus lower the SOC loss with land degradation. Decline in the plant production due to a decrease in coverage or to the change in relative abundance of sedge, forbs and grass directly or indirectly reduce the C input and finally lead to the 40-50% loss in SOC. The significant pathways from soil microclimate and soil properties to SOC in the black box model, only one significant pathway from soil properties to SOC indicate that physical processes like the wind and water erosion might control the SOC loss with land degradation in the alpine grassland in the QTP.

Interactive effects of wildfire and permafrost on microbial communities and soil processes in an Alaskan black spruce forest

USGS Publications Warehouse

Waldrop, M.P.; Harden, J.W.

2008-01-01

Boreal forests contain significant quantities of soil carbon that may be oxidized to CO2 given future increases in climate warming and wildfire behavior. At the ecosystem scale, decomposition and heterotrophic respiration are strongly controlled by temperature and moisture, but we questioned whether changes in microbial biomass, activity, or community structure induced by fire might also affect these processes. We particularly wanted to understand whether postfire reductions in microbial biomass could affect rates of decomposition. Additionally, we compared the short-term effects of wildfire to the long-term effects of climate warming and permafrost decline. We compared soil microbial communities between control and recently burned soils that were located in areas with and without permafrost near Delta Junction, AK. In addition to soil physical variables, we quantified changes in microbial biomass, fungal biomass, fungal community composition, and C cycling processes (phenol oxidase enzyme activity, lignin decomposition, and microbial respiration). Five years following fire, organic surface horizons had lower microbial biomass, fungal biomass, and dissolved organic carbon (DOC) concentrations compared with control soils. Reductions in soil fungi were associated with reductions in phenol oxidase activity and lignin decomposition. Effects of wildfire on microbial biomass and activity in the mineral soil were minor. Microbial community composition was affected by wildfire, but the effect was greater in nonpermafrost soils. Although the presence of permafrost increased soil moisture contents, effects on microbial biomass and activity were limited to mineral soils that showed lower fungal biomass but higher activity compared with soils without permafrost. Fungal abundance and moisture were strong predictors of phenol oxidase enzyme activity in soil. Phenol oxidase enzyme activity, in turn, was linearly related to both 13C lignin decomposition and microbial respiration in incubation studies. Taken together, these results indicate that reductions in fungal biomass in postfire soils and lower soil moisture in nonpermafrost soils reduced the potential of soil heterotrophs to decompose soil carbon. Although in the field increased rates of microbial respiration can be observed in postfire soils due to warmer soil conditions, reductions in fungal biomass and activity may limit rates of decomposition. ?? 2008 The Authors Journal compilation ?? 2008 Blackwell Publishing.

Assessing the Factors of Regional Growth Decline of Sugar Maple

NASA Astrophysics Data System (ADS)

Bishop, D. A.; Beier, C. M.; Pederson, N.; Lawrence, G. B.; Stella, J. C.; Sullivan, T. J.

2014-12-01

Sugar maple (Acer saccharum Marsh) is among the most ecologically, economically and culturally important trees in North America, but has experienced a decline disease across much of its range. We investigated the climatic and edaphic factors associated with A. saccharum growth in the Adirondack Mountains (USA) using a well-replicated tree-ring network incorporating a range of soil fertility (base cation availability). We found that nearly 3 in 4 A. saccharum trees exhibited declining growth rates during the last several decades, regardless of tree age or size. Although diameter growth was consistently higher on base-rich soils, the negative trends in growth were largely consistent across the soil chemistry gradient. Sensitivity of sugar maple growth to climatic variability was overall weaker than expected, but were also non-stationary during the 20th century. We observed increasingly positive responses to late-winter precipitation, increasingly negative responses to growing season temperatures, and strong positive responses to moisture availability during the 1960s drought that became much weaker during the recent pluvial. Further study is needed of these factors and their interactions as potential mechanisms for sugar maple growth decline.

Tree rings provide early warning signals of jack pine mortality across a moisture gradient in the southern boreal forest

NASA Astrophysics Data System (ADS)

Mamet, S. D.; Chun, K. P.; Metsaranta, J. M.; Barr, A. G.; Johnstone, J. F.

2015-08-01

Recent declines in productivity and tree survival have been widely observed in boreal forests. We used early warning signals (EWS) in tree ring data to anticipate premature mortality in jack pine (Pinus banksiana)—an extensive and dominant species occurring across the moisture-limited southern boreal forest in North America. We sampled tree rings from 113 living and 84 dead trees in three soil moisture regimes (subxeric, submesic, subhygric) in central Saskatchewan, Canada. We reconstructed annual increments of tree basal area to investigate (1) whether we could detect EWS related to mortality of individual trees, and (2) how water availability and tree growth history may explain the mortality warning signs. EWS were evident as punctuated changes in growth patterns prior to transition to an alternative state of reduced growth before dying. This transition was likely triggered by a combination of severe drought and insect outbreak. Higher moisture availability associated with a soil moisture gradient did not appear to reduce tree sensitivity to stress-induced mortality. Our results suggest tree rings offer considerable potential for detecting critical transitions in tree growth, which are linked to premature mortality.

Hydrometeorological conditions preceding wildfire, and the subsequent burning of a fen watershed in Fort McMurray, Alberta, Canada

NASA Astrophysics Data System (ADS)

Elmes, Matthew C.; Thompson, Dan K.; Sherwood, James H.; Price, Jonathan S.

2018-01-01

The destructive nature of the ˜ 590 000 ha Horse river wildfire in the Western Boreal Plain (WBP), northern Alberta, in May of 2016 motivated the investigation of the hydrometeorological conditions that preceded the fire. Historical climate and field hydrometeorological data from a moderate-rich fen watershed were used to (a) identify whether the spring 2016 conditions were outside the range of natural variability for WBP climate cycles, (b) explain the observed patterns in burn severity across the watershed, and (c) identify whether fall and winter moisture signals observed in peatlands and lowland forests in the region are indicative of wildfire. Field hydrometeorological data from the fen watershed confirmed the presence of cumulative moisture deficits prior to the fire. Hydrogeological investigations highlighted the susceptibility of fen and upland areas to water table and soil moisture decline over rain-free periods (including winter), due to the watershed's reliance on supply from localized flow systems originating in topographic highs. Subtle changes in topographic position led to large changes in groundwater connectivity, leading to greater organic soil consumption by fire in wetland margins and at high elevations. The 2016 spring moisture conditions measured prior to the ignition of the fen watershed were not illustrated well by the Drought Code (DC) when standard overwintering procedures were applied. However, close agreement was found when default assumptions were replaced with measured duff soil moisture recharge and incorporated into the overwintering DC procedure. We conclude that accumulated moisture deficits dating back to the summer of 2015 led to the dry conditions that preceded the fire. The infrequent coinciding of several hydrometeorological conditions, including low autumn soil moisture, a modest snowpack, lack of spring precipitation, and high spring air temperatures and winds, ultimately led to the Horse river wildfire spreading widely and causing the observed burn patterns. Monitoring soil moisture at different land classes and watersheds would aid management strategies in the production of more accurate overwintered DC calculations, providing fire management agencies early warning signals ahead of severe spring wildfire seasons.

Soil respiration at the Amargosa Desert Research site: A section in U.S. Geological Survey Toxic Substances Hydrology Program: Proceedings of the technical meeting, Charleston, South Carolina, March 8-12, 1999: Volume 3 (Part C) (WRI 99-4018C)

USGS Publications Warehouse

Riggs, Alan C.; Striegl, Robert G.; Maestas, Florentino B.; Morganwalp, David W.; Buxton, Herbert T.

1999-01-01

Automated opaque flux-chamber measurements of soil carbon dioxide (CO2) flux (soil respiration) into the atmosphere at the Amargosa Desert Research Site show seasonal and diel cycles of soil respiration that are closely linked with soil temperature and soil moisture. During 1998, soil respiration increased with soil warming through spring, reaching a maximum rate (not counting anomalously high values scattered through the record) of about 0.055 moles CO2 m-2 day-1 around Julian Day 120. Respiration rates then declined along with volumetric soil moisture content, tending to stay at or below about 0.02 moles CO2 per square meter per day (m-2 day -1) for the rest of the year, except after summer rainfalls when respiration sharply increased for short periods. The diel respiration pattern during dry spells is marked by a sharp rise in CO2 flux coincident with steeply rising soil temperatures in the morning, then dropping back to low levels about the time of maximum soil temperature. The reason for this pattern in unclear.

Evaluation of Assimilated SMOS Soil Moisture Data for US Cropland Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

Yang, Zhengwei; Sherstha, Ranjay; Crow, Wade; Bolten, John; Mladenova, Iva; Yu, Genong; Di, Liping

2016-01-01

Remotely sensed soil moisture data can provide timely, objective and quantitative crop soil moisture information with broad geospatial coverage and sufficiently high resolution observations collected throughout the growing season. This paper evaluates the feasibility of using the assimilated ESA Soil Moisture Ocean Salinity (SMOS)Mission L-band passive microwave data for operational US cropland soil surface moisture monitoring. The assimilated SMOS soil moisture data are first categorized to match with the United States Department of Agriculture (USDA)National Agricultural Statistics Service (NASS) survey based weekly soil moisture observation data, which are ordinal. The categorized assimilated SMOS soil moisture data are compared with NASSs survey-based weekly soil moisture data for consistency and robustness using visual assessment and rank correlation. Preliminary results indicate that the assimilated SMOS soil moisture data highly co-vary with NASS field observations across a large geographic area. Therefore, SMOS data have great potential for US operational cropland soil moisture monitoring.

Woody riparian vegetation response to different alluvial water table regimes

USGS Publications Warehouse

Shafroth, P.B.; Stromberg, J.C.; Patten, D.T.

2000-01-01

Woody riparian vegetation in western North American riparian ecosystems is commonly dependent on alluvial groundwater. Various natural and anthropogenic mechanisms can cause groundwater declines that stress riparian vegetation, but little quantitative information exists on the nature of plant response to different magnitudes, rates, and durations of groundwater decline. We observed groundwater dynamics and the response of Populus fremontii, Salix gooddingii, and Tamarix ramosissima saplings at 3 sites between 1995 and 1997 along the Bill Williams River, Arizona. At a site where the lowest observed groundwater level in 1996 (-1.97 m) was 1.11 m lower than that in 1995 (-0.86 m), 92-100% of Populus and Salix saplings died, whereas 0-13% of Tamarix stems died. A site with greater absolute water table depths in 1996 (-2.55 m), but less change from the 1995 condition (0.55 m), showed less Populus and Salix mortality and increased basal area. Excavations of sapling roots suggest that root distribution is related to groundwater history. Therefore, a decline in water table relative to the condition under which roots developed may strand plant roots where they cannot obtain sufficient moisture. Plant response is likely mediated by other factors such as soil texture and stratigraphy, availability of precipitation-derived soil moisture, physiological and morphological adaptations to water stress, and tree age. An understanding of the relationships between water table declines and plant response may enable land and water managers to avoid activities that are likely to stress desirable riparian vegetation.

Surface Soil Moisture Estimates Across China Based on Multi-satellite Observations and A Soil Moisture Model

NASA Astrophysics Data System (ADS)

Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo

2017-04-01

Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE < 0.1 and r > 0.8).

Regional seasonal warming anomalies and land-surface feedbacks

NASA Astrophysics Data System (ADS)

Coffel, E.; Horton, R. M.

2017-12-01

Significant seasonal variations in warming are projected in some regions, especially central Europe, the southeastern U.S., and central South America. Europe in particular may experience up to 2°C more warming during June, July, and August than in the annual mean, enhancing the risk of extreme summertime heat. Previous research has shown that heat waves in Europe and other regions are tied to seasonal soil moisture variations, and that in general land-surface feedbacks have a strong effect on seasonal temperature anomalies. In this study, we show that the seasonal anomalies in warming are also due in part to land-surface feedbacks. We find that in regions with amplified warming during the hot season, surface soil moisture levels generally decline and Bowen ratios increase as a result of a preferential partitioning of incoming energy into sensible vs. latent. The CMIP5 model suite shows significant variability in the strength of land-atmosphere coupling and in projections of future precipitation and soil moisture. Due to the dependence of seasonal warming on land-surface processes, these inter-model variations influence the projected summertime warming amplification and contribute to the uncertainty in projections of future extreme heat.

Topographical controls on soil moisture distribution and runoff response in a first order alpine catchment

NASA Astrophysics Data System (ADS)

Penna, Daniele; Gobbi, Alberto; Mantese, Nicola; Borga, Marco

2010-05-01

Hydrological processes driving runoff generation in mountain basins depend on a wide number of factors which are often strictly interconnected. Among them, topography is widely recognized as one of the dominant controls influencing soil moisture distribution in the root zone, depth to water table and location and extent of saturated areas possibly prone to runoff production. Morphological properties of catchments are responsible for the alternation between steep slopes and relatively flat areas which have the potentials to control the storage/release of water and hence the hydrological response of the whole watershed. This work aims to: i) identify the role of topography as the main factor controlling the spatial distribution of near-surface soil moisture; ii) evaluate the possible switch in soil moisture spatial organization between wet and relatively dry periods and the stability of patterns during triggering of surface/subsurface runoff; iii) assess the possible connection between the develop of an ephemeral river network and the groundwater variations, examining the influence of the catchment topographical properties on the hydrological response. Hydro-meteorological data were collected in a small subcatchment (Larch Creek Catchment, 0.033 km²) of Rio Vauz basin (1.9 km²), in the eastern Italian Alps. Precipitation, discharge, water table level over a net of 14 piezometric wells and volumetric soil moisture at 0-30 cm depth were monitored continuously during the late spring-early autumn months in 2007 and 2008. Soil water content at 0-6 and 0-20 cm depth was measured manually during 22 field surveys in summer 2007 over a 44-sampling point experimental plot (approximately 3000 m²). In summer 2008 the sampling grid was extended to 64 points (approximately 4500 m²) and 28 field surveys were carried out. The length of the ephemeral stream network developed during rainfall events was assessed by a net of 24 Overland Flow Detectors (OFDs), which are able to detect the presence/absence of surface runoff. Results show a significant correlation between plot-averaged soil moisture at 0-20 cm depth, local slope and local curvature, while poor correlations were found with aspect and solar radiation: this suggests a sharp control of the catchment topological architecture (likely coupled with soil properties) on soil moisture distribution. This was also confirmed by the visual inspection of interpolated maps which reveal the persistence of high values of soil moisture in hollow areas and, conversely, of low values over the hillslopes. Moreover, a strong correlation between plot-averaged soil moisture patterns over time, with no decline after rainfall events, indicates a good temporal stability of water content distribution and its independence from the triggering of surface flow and transient lateral subsurface flow during wet conditions. The analysis of the time lag between storm centroid and piezometric peak shows an increasing delay of water table reaction with increasing distance from the stream, revealing different groundwater dynamics between the near-stream and the hillslope zone. Furthermore, the significant correlation between groundwater time lag monitored for the net of piezometers and the local slope suggests a topographical influence on the temporal and spatial variability of subsurface runoff. Finally, the extent of the ephemeral stream network was clearly dependent on the amount of precipitation but a different percentage of active OFDs and piezometers for the same rainfall event suggests a decoupling between patterns of surface and subsurface flows in the study area. Key words: topographical controls, soil moisture patterns, groundwater level, overland flow.

Response of water use efficiency to summer drought in a boreal Scots pine forest in Finland

NASA Astrophysics Data System (ADS)

Gao, Yao; Markkanen, Tiina; Aurela, Mika; Mammarella, Ivan; Thum, Tea; Tsuruta, Aki; Yang, Huiyi; Aalto, Tuula

2017-09-01

The influence of drought on plant functioning has received considerable attention in recent years, however our understanding of the response of carbon and water coupling to drought in terrestrial ecosystems still needs to be improved. A severe soil moisture drought occurred in southern Finland in the late summer of 2006. In this study, we investigated the response of water use efficiency to summer drought in a boreal Scots pine forest (Pinus sylvestris) on the daily time scale mainly using eddy covariance flux data from the Hyytiälä (southern Finland) flux site. In addition, simulation results from the JSBACH land surface model were evaluated against the observed results. Based on observed data, the ecosystem level water use efficiency (EWUE; the ratio of gross primary production, GPP, to evapotranspiration, ET) showed a decrease during the severe soil moisture drought, while the inherent water use efficiency (IWUE; a quantity defined as EWUE multiplied with mean daytime vapour pressure deficit, VPD) increased and the underlying water use efficiency (uWUE, a metric based on IWUE and a simple stomatal model, is the ratio of GPP multiplied with a square root of VPD to ET) was unchanged during the drought. The decrease in EWUE was due to the stronger decline in GPP than in ET. The increase in IWUE was because of the decreased stomatal conductance under increased VPD. The unchanged uWUE indicates that the trade-off between carbon assimilation and transpiration of the boreal Scots pine forest was not disturbed by this drought event at the site. The JSBACH simulation showed declines of both GPP and ET under the severe soil moisture drought, but to a smaller extent compared to the observed GPP and ET. Simulated GPP and ET led to a smaller decrease in EWUE but a larger increase in IWUE because of the severe soil moisture drought in comparison to observations. As in the observations, the simulated uWUE showed no changes in the drought event. The model deficiencies exist mainly due to the lack of the limiting effect of increased VPD on stomatal conductance during the low soil moisture condition. Our study provides a deeper understanding of the coupling of carbon and water cycles in the boreal Scots pine forest ecosystem and suggests possible improvements to land surface models, which play an important role in the prediction of biosphere-atmosphere feedbacks in the climate system.

Assessment of Multi-frequency Electromagnetic Induction for Determining Soil Moisture Patterns at the Hillslope Scale

NASA Astrophysics Data System (ADS)

Tromp-van Meerveld, I.; McDonnell, J.

2009-05-01

We present an assessment of electromagnetic induction (EM) as a potential rapid and non-invasive method to map soil moisture patterns at the Panola (GA, USA) hillslope. We address the following questions regarding the applicability of EM measurements for hillslope hydrological investigations: (1) Can EM be used for soil moisture measurements in areas with shallow soils?; (2) Can EM represent the temporal and spatial patterns of soil moisture throughout the year?; and (3) can multiple frequencies be used to extract additional information content from the EM approach and explain the depth profile of soil moisture? We found that the apparent conductivity measured with the multi-frequency GEM-300 was linearly related to soil moisture measured with an Aqua-pro capacitance sensor below a threshold conductivity and represented the temporal patterns in soil moisture well. During spring rainfall events that wetted only the surface soil layers the apparent conductivity measurements explained the soil moisture dynamics at depth better than the surface soil moisture dynamics. All four EM frequencies (7290, 9090, 11250, and 14010 Hz) were highly correlated and linearly related to each other and could be used to predict soil moisture. This limited our ability to use the four different EM frequencies to obtain a soil moisture profile with depth. The apparent conductivity patterns represented the observed spatial soil moisture patterns well when the individually fitted relationships between measured soil moisture and apparent conductivity were used for each measurement point. However, when the same (master) relationship was used for all measurement locations, the soil moisture patterns were smoothed and did not resemble the observed soil moisture patterns very well. In addition, the range in calculated soil moisture values was reduced compared to observed soil moisture. Part of the smoothing was likely due to the much larger measurement area of the GEM-300 compared to the Aqua-pro soil moisture measurements.

Assimilation of Passive and Active Microwave Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Draper, C. S.; Reichle, R. H.; DeLannoy, G. J. M.; Liu, Q.

2012-01-01

Root-zone soil moisture is an important control over the partition of land surface energy and moisture, and the assimilation of remotely sensed near-surface soil moisture has been shown to improve model profile soil moisture [1]. To date, efforts to assimilate remotely sensed near-surface soil moisture at large scales have focused on soil moisture derived from the passive microwave Advanced Microwave Scanning Radiometer (AMSR-E) and the active Advanced Scatterometer (ASCAT; together with its predecessor on the European Remote Sensing satellites (ERS. The assimilation of passive and active microwave soil moisture observations has not yet been directly compared, and so this study compares the impact of assimilating ASCAT and AMSR-E soil moisture data, both separately and together. Since the soil moisture retrieval skill from active and passive microwave data is thought to differ according to surface characteristics [2], the impact of each assimilation on the model soil moisture skill is assessed according to land cover type, by comparison to in situ soil moisture observations.

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

NASA Astrophysics Data System (ADS)

McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross

2017-12-01

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 × 36 km at 9 km resolution) and intensive (10 × 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.

[Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].

PubMed

Zheng, Xiao-po; Sun, Yue-jun; Qin, Qi-ming; Ren, Hua-zhong; Gao, Zhong-ling; Wu, Ling; Meng, Qing-ye; Wang, Jin-liang; Wang, Jian-hua

2015-08-01

Soil is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, moisture, microbes, et al. Among its complex compositions, soil moisture varies greatly. Therefore, the fast and accurate inversion of soil moisture by using remote sensing is very crucial. In order to reduce the influence of soil type on the retrieval of soil moisture, this paper proposed a normalized spectral slope and absorption index named NSSAI to estimate soil moisture. The modeling of the new index contains several key steps: Firstly, soil samples with different moisture level were artificially prepared, and soil reflectance spectra was consequently measured using spectroradiometer produced by ASD Company. Secondly, the moisture absorption spectral feature located at shortwave wavelengths and the spectral slope of visible wavelengths were calculated after analyzing the regular spectral feature change patterns of different soil at different moisture conditions. Then advantages of the two features at reducing soil types' effects was synthesized to build the NSSAI. Thirdly, a linear relationship between NSSAI and soil moisture was established. The result showed that NSSAI worked better (correlation coefficient is 0.93) than most of other traditional methods in soil moisture extraction. It can weaken the influences caused by soil types at different moisture levels and improve the bare soil moisture inversion accuracy.

Evaluation of Long-term Soil Moisture Proxies in the U.S. Great Plains

NASA Astrophysics Data System (ADS)

Yuan, S.; Quiring, S. M.

2016-12-01

Soil moisture plays an important role in land-atmosphere interactions through both surface energy and water balances. However, despite its importance, there are few long-term records of observed soil moisture for investigating long-term spatial and temporal variations of soil moisture. Hence, it is necessary to find suitable approximations of soil moisture observations. 5 drought indices will be compared with simulated and observed soil moisture over the U.S. Great Plains during two time periods (1980 - 2012 and 2003 - 2012). Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), Palmer Z Index (zindex) and Crop Moisture Index (CMI) will be calculated by PRISM data. The soil moisture simulations will be derived from NLDAS. In situ soil moisture will be obtained from North American Soil Moisture Database. The evaluation will focus on three main aspects: trends, variations and persistence. The results will support further research investigating long-term variations in soil moisture-climate interactions.

Utilization of point soil moisture measurements for field scale soil moisture averages and variances in agricultural landscapes

USDA-ARS?s Scientific Manuscript database

Soil moisture is a key variable in understanding the hydrologic processes and energy fluxes at the land surface. In spite of new technologies for in-situ soil moisture measurements and increased availability of remotely sensed soil moisture data, scaling issues between soil moisture observations and...

Assessment of multi-frequency electromagnetic induction for determining soil moisture patterns at the hillslope scale

NASA Astrophysics Data System (ADS)

Tromp-van Meerveld, H. J.; McDonnell, J. J.

2009-04-01

SummaryHillslopes are fundamental landscape units, yet represent a difficult scale for measurements as they are well-beyond our traditional point-scale techniques. Here we present an assessment of electromagnetic induction (EM) as a potential rapid and non-invasive method to map soil moisture patterns at the hillslope scale. We test the new multi-frequency GEM-300 for spatially distributed soil moisture measurements at the well-instrumented Panola hillslope. EM-based apparent conductivity measurements were linearly related to soil moisture measured with the Aqua-pro capacitance sensor below a threshold conductivity and represented the temporal patterns in soil moisture well. During spring rainfall events that wetted only the surface soil layers the apparent conductivity measurements explained the soil moisture dynamics at depth better than the surface soil moisture dynamics. All four EM frequencies (7.290, 9.090, 11.250, and 14.010 kHz) were highly correlated and linearly related to each other and could be used to predict soil moisture. This limited our ability to use the four different EM frequencies to obtain a soil moisture profile with depth. The apparent conductivity patterns represented the observed spatial soil moisture patterns well when the individually fitted relationships between measured soil moisture and apparent conductivity were used for each measurement point. However, when the same (master) relationship was used for all measurement locations, the soil moisture patterns were smoothed and did not resemble the observed soil moisture patterns very well. In addition the range in calculated soil moisture values was reduced compared to observed soil moisture. Part of the smoothing was likely due to the much larger measurement area of the GEM-300 compared to the soil moisture measurements.

Seasonal photosynthetic responses of European oaks to drought and elevated daytime temperature.

PubMed

Arend, M; Brem, A; Kuster, T M; Günthardt-Goerg, M S

2013-01-01

Oaks are commonly considered as drought- and heat-tolerant trees that might benefit from a warmer and drier climate. Their tolerance to drought has been frequently studied in the past, whereas studies dealing with elevated temperature or its combination with drought are very limited in number. In this study we investigated seasonal photosynthetic patterns in three European oak species (Quercus robur, Q. petraea, Q. pubescens) exposed in lysimeter-based open-top chambers (OTC) to elevated daytime temperature, drought and their combination. Stomatal and non-stomatal traits of photosynthesis were followed over an entire growing season and related to changes in daytime temperature, soil moisture and pre-dawn leaf water potential (Ψ(PD) ). Elevated daytime temperature enhanced net photosynthesis (P(N) ) in a season-dependent manner, with higher mid-summer rates than in controls exposed to ambient temperature. Drought imposed in early and mid-summer reduced the soil moisture content and caused a gradual decline in Ψ(PD) , stomatal conductance (g(S) ) and P(N) . Drought effects on Ψ(PD) and P(N) were exacerbated when drought was combined with elevated daytime temperature. In general, P(N) tended to be more affected by low soil moisture content or low Ψ(PD) in Q. robur than in Q. petraea and Q. pubescens. Non-stomatal limitations may have contributed to the drought-induced decline of P(N) in Q. robur, as indicated by a down-regulation of PSII photochemistry (F(V) /F(M) ) and decreased chlorophyll content. Taken together, our findings show that European oaks may benefit from elevated temperature, but detrimental effects can be expected when elevated temperature occurs simultaneously with drought. © 2012 German Botanical Society and The Royal Botanical Society of the Netherlands.

Estimation of hectare-scale soil-moisture characteristics from aquifer-test data

USGS Publications Warehouse

Moench, A.F.

2003-01-01

Analysis of a 72-h, constant-rate aquifer test conducted in a coarse-grained and highly permeable, glacial outwash deposit on Cape Cod, Massachusetts revealed that drawdowns measured in 20 piezometers located at various depths below the water table and distances from the pumped well were significantly influenced by effects of drainage from the vadose zone. The influence was greatest in piezometers located close to the water table and diminished with increasing depth. The influence of the vadose zone was evident from a gap, in the intermediate-time zone, between measured drawdowns and drawdowns computed under the assumption that drainage from the vadose zone occurred instantaneously in response to a decline in the elevation of the water table. By means of an analytical model that was designed to account for time-varying drainage, simulated drawdowns could be closely fitted to measured drawdowns regardless of the piezometer locations. Because of the exceptional quality and quantity of the data and the relatively small aquifer heterogeneity, it was possible by inverse modeling to estimate all relevant aquifer parameters and a set of three empirical constants used in the upper-boundary condition to account for the dynamic drainage process. The empirical constants were used to define a one-dimensional (ID) drainage versus time curve that is assumed to be representative of the bulk material overlying the water table. The curve was inverted with a parameter estimation algorithm and a ID numerical model for variably saturated flow to obtain soil-moisture retention curves and unsaturated hydraulic conductivity relationships defined by the Brooks and Corey equations. Direct analysis of the aquifer-test data using a parameter estimation algorithm and a two-dimensional, axisymmetric numerical model for variably saturated flow yielded similar soil-moisture characteristics. Results suggest that hectare-scale soil-moisture characteristics are different from core-scale predictions and even relatively small amounts of fine-grained material and heterogeneity can dominate the large-scale soil-moisture characteristics and aquifer response. ?? 2003 Elsevier B.V. All rights reserved.

Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

2011-01-01

The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

Constraint of soil moisture on CO2 efflux from tundra lichen, moss, and tussock in Council, Alaska using a hierarchical Bayesian model

NASA Astrophysics Data System (ADS)

Kim, Y.; Nishina, K.; Chae, N.; Park, S.; Yoon, Y.; Lee, B.

2014-04-01

The tundra ecosystem is quite vulnerable to drastic climate change in the Arctic, and the quantification of carbon dynamics is of significant importance in response to thawing permafrost, changes in the snow-covered period and snow and shrub community extent, and the decline of sea ice in the Arctic. Here, CO2 efflux measurements using a manual chamber system within a 40 m × 40 m (5 m interval; 81 total points) plot were conducted in dominant tundra vegetation on the Seward Peninsula of Alaska, during the growing seasons of 2011 and 2012, for the assessment of the driving parameters of CO2 efflux. We applied a hierarchical Bayesian (HB) model - which is a function of soil temperature, soil moisture, vegetation type and thaw depth - to quantify the effect of environmental parameters on CO2 efflux, and to estimate growing season CO2 emission. Our results showed that average CO2 efflux in 2011 is 1.4-fold higher than in 2012, resulting from the distinct difference in soil moisture between the two years. Tussock-dominated CO2 efflux is 1.4 to 2.3 times higher than those measured in lichen and moss communities, reflecting tussock as a significant CO2 source in the Arctic, with wide area distribution on a circumpolar scale. CO2 efflux followed soil temperature nearly exponentially from both the observed data and the posterior medians of the HB model. This reveals soil temperature as the most important parameter in regulating CO2 efflux, rather than soil moisture and thaw depth. Obvious changes in soil moisture during the growing seasons of 2011 and 2012 resulted in an explicit difference in CO2 efflux - 742 and 539 g CO2 m-2 period-1 in 2011 and 2012, respectively, suggesting that the 2012 CO2 emission rate was constrained by 27% (95% credible interval: 17-36%) compared to 2011, due to higher soil moisture from severe rain. Estimated growing season CO2 emission rate ranged from 0.86 Mg CO2 period-1 in 2012 to 1.2 Mg CO2 period-1 in 2011 within a 40 m × 40 m plot, corresponding to 86% and 80% of the annual CO2 emission rates within the Alaska western tundra ecosystem. Therefore, the HB model can be readily applied to observed CO2 efflux, as it demands only four environmental parameters and can also be effective for quantitatively assessing the driving parameters of CO2 efflux.

Stochastic Analysis and Probabilistic Downscaling of Soil Moisture

NASA Astrophysics Data System (ADS)

Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.

2017-12-01

Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture patterns with more realistic statistical properties than the deterministic model. Additionally, the results suggest that the variance and spatial correlation of the stochastic soil-moisture variations do not vary consistently with the spatial-average soil moisture.

Response of deep soil moisture to land use and afforestation in the semi-arid Loess Plateau, China

NASA Astrophysics Data System (ADS)

Yang, Lei; Wei, Wei; Chen, Liding; Mo, Baoru

2012-12-01

SummarySoil moisture is an effective water source for plant growth in the semi-arid Loess Plateau of China. Characterizing the response of deep soil moisture to land use and afforestation is important for the sustainability of vegetation restoration in this region. In this paper, the dynamics of soil moisture were quantified to evaluate the effect of land use on soil moisture at a depth of 2 m. Specifically, the gravimetric soil moisture content was measured in the soil layer between 0 and 8 m for five land use types in the Longtan catchment of the western Loess Plateau. The land use types included traditional farmland, native grassland, and lands converted from traditional farmland (pasture grassland, shrubland and forestland). Results indicate that the deep soil moisture content decreased more than 35% after land use conversion, and a soil moisture deficit appeared in all types of land with introduced vegetation. The introduced vegetation decreased the soil moisture content to levels lower than the reference value representing no human impact in the entire 0-8 m soil profile. No significant differences appeared between different land use types and introduced vegetation covers, especially in deeper soil layers, regardless of which plant species were introduced. High planting density was found to be the main reason for the severe deficit of soil moisture. Landscape management activities such as tillage activities, micro-topography reconstruction, and fallowed farmland affected soil moisture in both shallow and deep soil layers. Tillage and micro-topography reconstruction can be used as effective countermeasures to reduce the soil moisture deficit due to their ability to increase soil moisture content. For sustainable vegetation restoration in a vulnerable semi-arid region, the plant density should be optimized with local soil moisture conditions and appropriate landscape management practices.

State of the Art in Large-Scale Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.;

Reconstructions of Soil Moisture for the Upper Colorado River Basin Using Tree-Ring Chronologies

NASA Astrophysics Data System (ADS)

Tootle, G.; Anderson, S.; Grissino-Mayer, H.

2012-12-01

Soil moisture is an important factor in the global hydrologic cycle, but existing reconstructions of historic soil moisture are limited. Tree-ring chronologies (TRCs) were used to reconstruct annual soil moisture in the Upper Colorado River Basin (UCRB). Gridded soil moisture data were spatially regionalized using principal components analysis and k-nearest neighbor techniques. Moisture sensitive tree-ring chronologies in and adjacent to the UCRB were correlated with regional soil moisture and tested for temporal stability. TRCs that were positively correlated and stable for the calibration period were retained. Stepwise linear regression was applied to identify the best predictor combinations for each soil moisture region. The regressions explained 42-78% of the variability in soil moisture data. We performed reconstructions for individual soil moisture grid cells to enhance understanding of the disparity in reconstructive skill across the regions. Reconstructions that used chronologies based on ponderosa pines (Pinus ponderosa) and pinyon pines (Pinus edulis) explained increased variance in the datasets. Reconstructed soil moisture was standardized and compared with standardized reconstructed streamflow and snow water equivalent from the same region. Soil moisture reconstructions were highly correlated with streamflow and snow water equivalent reconstructions, indicating reconstructions of soil moisture in the UCRB using TRCs successfully represent hydrologic trends, including the identification of periods of prolonged drought.

Downscaling soil moisture over East Asia through multi-sensor data fusion and optimization of regression trees

NASA Astrophysics Data System (ADS)

Park, Seonyoung; Im, Jungho; Park, Sumin; Rhee, Jinyoung

2017-04-01

Soil moisture is one of the most important keys for understanding regional and global climate systems. Soil moisture is directly related to agricultural processes as well as hydrological processes because soil moisture highly influences vegetation growth and determines water supply in the agroecosystem. Accurate monitoring of the spatiotemporal pattern of soil moisture is important. Soil moisture has been generally provided through in situ measurements at stations. Although field survey from in situ measurements provides accurate soil moisture with high temporal resolution, it requires high cost and does not provide the spatial distribution of soil moisture over large areas. Microwave satellite (e.g., advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR2), the Advanced Scatterometer (ASCAT), and Soil Moisture Active Passive (SMAP)) -based approaches and numerical models such as Global Land Data Assimilation System (GLDAS) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) provide spatial-temporalspatiotemporally continuous soil moisture products at global scale. However, since those global soil moisture products have coarse spatial resolution ( 25-40 km), their applications for agriculture and water resources at local and regional scales are very limited. Thus, soil moisture downscaling is needed to overcome the limitation of the spatial resolution of soil moisture products. In this study, GLDAS soil moisture data were downscaled up to 1 km spatial resolution through the integration of AMSR2 and ASCAT soil moisture data, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and Moderate Resolution Imaging Spectroradiometer (MODIS) data—Land Surface Temperature, Normalized Difference Vegetation Index, and Land cover—using modified regression trees over East Asia from 2013 to 2015. Modified regression trees were implemented using Cubist, a commercial software tool based on machine learning. An optimization based on pruning of rules derived from the modified regression trees was conducted. Root Mean Square Error (RMSE) and Correlation coefficients (r) were used to optimize the rules, and finally 59 rules from modified regression trees were produced. The results show high validation r (0.79) and low validation RMSE (0.0556m3/m3). The 1 km downscaled soil moisture was evaluated using ground soil moisture data at 14 stations, and both soil moisture data showed similar temporal patterns (average r=0.51 and average RMSE=0.041). The spatial distribution of the 1 km downscaled soil moisture well corresponded with GLDAS soil moisture that caught both extremely dry and wet regions. Correlation between GLDAS and the 1 km downscaled soil moisture during growing season was positive (mean r=0.35) in most regions.

Recent decline in the global land evapotranspiration trend due to limited moisture supply.

PubMed

Jung, Martin; Reichstein, Markus; Ciais, Philippe; Seneviratne, Sonia I; Sheffield, Justin; Goulden, Michael L; Bonan, Gordon; Cescatti, Alessandro; Chen, Jiquan; de Jeu, Richard; Dolman, A Johannes; Eugster, Werner; Gerten, Dieter; Gianelle, Damiano; Gobron, Nadine; Heinke, Jens; Kimball, John; Law, Beverly E; Montagnani, Leonardo; Mu, Qiaozhen; Mueller, Brigitte; Oleson, Keith; Papale, Dario; Richardson, Andrew D; Roupsard, Olivier; Running, Steve; Tomelleri, Enrico; Viovy, Nicolas; Weber, Ulrich; Williams, Christopher; Wood, Eric; Zaehle, Sönke; Zhang, Ke

2010-10-21

More than half of the solar energy absorbed by land surfaces is currently used to evaporate water. Climate change is expected to intensify the hydrological cycle and to alter evapotranspiration, with implications for ecosystem services and feedback to regional and global climate. Evapotranspiration changes may already be under way, but direct observational constraints are lacking at the global scale. Until such evidence is available, changes in the water cycle on land−a key diagnostic criterion of the effects of climate change and variability−remain uncertain. Here we provide a data-driven estimate of global land evapotranspiration from 1982 to 2008, compiled using a global monitoring network, meteorological and remote-sensing observations, and a machine-learning algorithm. In addition, we have assessed evapotranspiration variations over the same time period using an ensemble of process-based land-surface models. Our results suggest that global annual evapotranspiration increased on average by 7.1 ± 1.0 millimetres per year per decade from 1982 to 1997. After that, coincident with the last major El Niño event in 1998, the global evapotranspiration increase seems to have ceased until 2008. This change was driven primarily by moisture limitation in the Southern Hemisphere, particularly Africa and Australia. In these regions, microwave satellite observations indicate that soil moisture decreased from 1998 to 2008. Hence, increasing soil-moisture limitations on evapotranspiration largely explain the recent decline of the global land-evapotranspiration trend. Whether the changing behaviour of evapotranspiration is representative of natural climate variability or reflects a more permanent reorganization of the land water cycle is a key question for earth system science.

A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture

NASA Astrophysics Data System (ADS)

Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.

2017-12-01

Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.

Carbon use efficiency (CUE) and biomass turnover of soil microbial communities as affected by bedrock, land management and soil temperature and moisture

NASA Astrophysics Data System (ADS)

Zheng, Qing; Hu, Yuntao; Richter, Andreas; Wanek, Wolfgang

2017-04-01

Soil microbial carbon use efficiency (CUE), defined as the proportion of organic C taken up that is allocated to microbial growth, represents an important synthetic representation of microbial community C metabolism that describes the flux partitioning between microbial respiration and growth. Therefore, studying microbial CUE is critical for the understanding of soil C cycling. Microbial CUE is thought to vary with environmental conditions (e.g. temperature and soil moisture). Microbial CUE is thought to decrease with increasing temperature and declining soil moisture, as the latter may trigger stress responses (e.g. the synthesis of stress metabolites), which may consequently lower microbial community CUE. However, these effects on microbial CUE have not been adequately measured so far due to methodological restrictions. The most widely used methods for microbial CUE estimation are based on tracing 13C-labeled substrates into microbial biomass and respiratory CO2, approaches that are known to overestimate microbial CUE of native organic matter in soil. Recently, a novel substrate-independent approach based on the measurement of (i) respiration rates and (ii) the incorporation rates of 18O from labelled water into newly formed microbial DNA has been developed in our laboratory for measuring microbial CUE. This approach overcomes the shortcomings of previously used methods and has already been shown to yield realistic estimations of soil microbial CUE. This approach can also be applied to concurrently measure microbial biomass turnover rates, which also influence the sequestration of soil organic C. Microbial turnover rates are also thought to be impacted by environmental factors, but rarely have been directly measured so far. Here, we aimed at determining the short-term effects of environmental factors (soil temperature and soil moisture) on microbial CUE and microbial biomass turnover rates based on the novel 18O approach. Soils from three land-use types (arable fields, pasture and forest) sampled from two geologies (silicate versus limestone) in the same region in Austria were incubated at three temperatures (5, 15 and 25 ˚ C) for 1 day and at three moisture levels (30, 60, 90% water-holding capacity) for 7 days in the laboratory, respectively. We will present the results and discuss major effects of environmental factors as well as of land management and geology on microbial growth, respiration, microbial CUE and microbial biomass turnover, and set those in relation to microbial community composition.

Estimating Soil Moisture at High Spatial Resolution with Three Radiometric Satellite Products: A Study from a South-Eastern Australian Catchment

NASA Astrophysics Data System (ADS)

Senanayake, I. P.; Yeo, I. Y.; Tangdamrongsub, N.; Willgoose, G. R.; Hancock, G. R.; Wells, T.; Fang, B.; Lakshmi, V.

2017-12-01

Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions ( several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.

High resolution change estimation of soil moisture and its assimilation into a land surface model

NASA Astrophysics Data System (ADS)

Narayan, Ujjwal

Near surface soil moisture plays an important role in hydrological processes including infiltration, evapotranspiration and runoff. These processes depend non-linearly on soil moisture and hence sub-pixel scale soil moisture variability characterization is important for accurate modeling of water and energy fluxes at the pixel scale. Microwave remote sensing has evolved as an attractive technique for global monitoring of near surface soil moisture. A radiative transfer model has been tested and validated for soil moisture retrieval from passive microwave remote sensing data under a full range of vegetation water content conditions. It was demonstrated that soil moisture retrieval errors of approximately 0.04 g/g gravimetric soil moisture are attainable with vegetation water content as high as 5 kg/m2. Recognizing the limitation of low spatial resolution associated with passive sensors, an algorithm that uses low resolution passive microwave (radiometer) and high resolution active microwave (radar) data to estimate soil moisture change at the spatial resolution of radar operation has been developed and applied to coincident Passive and Active L and S band (PALS) and Airborne Synthetic Aperture Radar (AIRSAR) datasets acquired during the Soil Moisture Experiments in 2002 (SMEX02) campaign with root mean square error of 10% and a 4 times enhancement in spatial resolution. The change estimation algorithm has also been used to estimate soil moisture change at 5 km resolution using AMSR-E soil moisture product (50 km) in conjunction with the TRMM-PR data (5 km) for a 3 month period demonstrating the possibility of high resolution soil moisture change estimation using satellite based data. Soil moisture change is closely related to precipitation and soil hydraulic properties. A simple assimilation framework has been implemented to investigate whether assimilation of surface layer soil moisture change observations into a hydrologic model will potentially improve it performance. Results indicate an improvement in model prediction of near surface and deep layer soil moisture content when the update is performed to the model state as compared to free model runs. It is also seen that soil moisture change assimilation is able to mitigate the effect of erroneous precipitation input data.

Soil moisture variations in remotely sensed and reanalysis datasets during weak monsoon conditions over central India and central Myanmar

NASA Astrophysics Data System (ADS)

Shrivastava, Sourabh; Kar, Sarat C.; Sharma, Anu Rani

2017-07-01

Variation of soil moisture during active and weak phases of summer monsoon JJAS (June, July, August, and September) is very important for sustenance of the crop and subsequent crop yield. As in situ observations of soil moisture are few or not available, researchers use data derived from remote sensing satellites or global reanalysis. This study documents the intercomparison of soil moisture from remotely sensed and reanalyses during dry spells within monsoon seasons in central India and central Myanmar. Soil moisture data from the European Space Agency (ESA)—Climate Change Initiative (CCI) has been treated as observed data and was compared against soil moisture data from the ECMWF reanalysis-Interim (ERA-I) and the climate forecast system reanalysis (CFSR) for the period of 2002-2011. The ESA soil moisture correlates rather well with observed gridded rainfall. The ESA data indicates that soil moisture increases over India from west to east and from north to south during monsoon season. The ERA-I overestimates the soil moisture over India, while the CFSR soil moisture agrees well with the remotely sensed observation (ESA). Over Myanmar, both the reanalysis overestimate soil moisture values and the ERA-I soil moisture does not show much variability from year to year. Day-to-day variations of soil moisture in central India and central Myanmar during weak monsoon conditions indicate that, because of the rainfall deficiency, the observed (ESA) and the CFSR soil moisture values are reduced up to 0.1 m3/m3 compared to climatological values of more than 0.35 m3/m3. This reduction is not seen in the ERA-I data. Therefore, soil moisture from the CFSR is closer to the ESA observed soil moisture than that from the ERA-I during weak phases of monsoon in the study region.

Validation of soil moisture ocean salinity (SMOS) satellite soil moisture products

USDA-ARS?s Scientific Manuscript database

The surface soil moisture state controls the partitioning of precipitation into infiltration and runoff. High-resolution observations of soil moisture will lead to improved flood forecasts, especially for intermediate to large watersheds where most flood damage occurs. Soil moisture is also key in d...

On the assimilation of satellite derived soil moisture in numerical weather prediction models

NASA Astrophysics Data System (ADS)

Drusch, M.

2006-12-01

Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

Evaluation of the validated soil moisture product from the SMAP radiometer

USDA-ARS?s Scientific Manuscript database

In this study, we used a multilinear regression approach to retrieve surface soil moisture from NASA’s Soil Moisture Active Passive (SMAP) satellite data to create a global dataset of surface soil moisture which is consistent with ESA’s Soil Moisture and Ocean Salinity (SMOS) satellite retrieved sur...

NASA Soil Moisture Data Products and Their Incorporation in DREAM

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette

2005-01-01

NASA provides soil moisture data products that include observations from the Advanced Microwave Scanning Radiometer on the Earth Observing System Aqua satellite, field measurements from the Soil Moisture Experiment campaigns, and model predictions from the Land Information System and the Goddard Earth Observing System Data Assimilation System. Incorporation of the NASA soil moisture products in the Dust Regional Atmospheric Model is possible through use of the satellite observations of soil moisture to set initial conditions for the dust simulations. An additional comparison of satellite soil moisture observations with mesoscale atmospheric dynamics modeling is recommended. Such a comparison would validate the use of NASA soil moisture data in applications and support acceptance of satellite soil moisture data assimilation in weather and climate modeling.

Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann; Shi, J. C.

2011-01-01

The objectives of the SMAP (Soil Moisture Active Passive) mission are global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolution, respectively. SMAP will provide soil moisture with a spatial resolution of 10 km with a 3-day revisit time at an accuracy of 0.04 m3/m3 [1]. In this paper we contribute to the development of the Level 2 soil moisture algorithm that is based on passive microwave observations by exploiting Soil Moisture Ocean Salinity (SMOS) satellite observations and products. SMOS brightness temperatures provide a global real-world, rather than simulated, test input for the SMAP radiometer-only soil moisture algorithm. Output of the potential SMAP algorithms will be compared to both in situ measurements and SMOS soil moisture products. The investigation will result in enhanced SMAP pre-launch algorithms for soil moisture.

Sensitivity of stomatal conductance to soil moisture: implications for tropospheric ozone

NASA Astrophysics Data System (ADS)

Anav, Alessandro; Proietti, Chiara; Menut, Laurent; Carnicelli, Stefano; De Marco, Alessandra; Paoletti, Elena

2018-04-01

Soil moisture and water stress play a pivotal role in regulating stomatal behaviour of plants; however, in the last decade, the role of water availability has often been neglected in atmospheric chemistry modelling studies as well as in integrated risk assessments, despite the fact that plants remove a large amount of atmospheric compounds from the lower troposphere through stomata. The main aim of this study is to evaluate, within the chemistry transport model CHIMERE, the effect of soil water limitation on stomatal conductance and assess the resulting changes in atmospheric chemistry testing various hypotheses of water uptake by plants in the rooting zone. Results highlight how dry deposition significantly declines when soil moisture is used to regulate the stomatal opening, mainly in the semi-arid environments: in particular, over Europe the amount of ozone removed by dry deposition in one year without considering any soil water limitation to stomatal conductance is about 8.5 TgO3, while using a dynamic layer that ensures that plants maximize the water uptake from soil, we found a reduction of about 10 % in the amount of ozone removed by dry deposition ( ˜ 7.7 TgO3). Although dry deposition occurs from the top of canopy to ground level, it affects the concentration of gases remaining in the lower atmosphere, with a significant impact on ozone concentration (up to 4 ppb) extending from the surface to the upper troposphere (up to 650 hPa). Our results shed light on the importance of improving the parameterizations of processes occurring at plant level (i.e. from the soil to the canopy) as they have significant implications for concentration of gases in the lower troposphere and resulting risk assessments for vegetation or human health.

Precipitation pulse dynamics of carbon sequestration and efflux in highly weatherable soils

NASA Astrophysics Data System (ADS)

Barron-Gafford, G.; Minor, R.; Van Haren, J. L.; Dontsova, K.; Troch, P. A.

2013-12-01

Soils are the primary pool for terrestrial carbon on Earth, and loss of that carbon to the atmosphere or hydrosphere represents a significant efflux that can impact a host of other downstream processes. Soil respiration (Rsoil), the efflux of CO2 to the atmosphere, represents the major pathway by which carbon is lost from the soil system in more weathered soils. However, in newly formed soils, chemical weathering can significantly deplete soil CO2 concentrations. As vegetation colonizes these soils, multiple interacting and contradictory pathways evolve such that soil CO2 concentrations increase in response to plant inputs but are decreased through chemical reactions. Furthermore, abiotic drivers of soil temperature and moisture likely differentially affect these processes. Understanding the bio-geo-chemical drivers and feedbacks associated with soil CO2 production and efflux in the critical zone necessitates an integrated science approach, drawing on input from plant physiologists, bio- and geochemists, and hydrologists. Here, we created a series of 1-meter deep mesocosms filled with granular basalt that supported either a woody mesquite shrub, a bunchgrass, or was left as bare soil. Use of multiple plant functional types allowed us to explore the impacts of plant structure (primarily rooting profiles) on critical zone function in terms of water and carbon exchange surrounding precipitation pulse dynamics. Each mesocosm was outfitted with an array of soil moisture, temperature, water potential, and CO2 concentration sensors at the near-surface, 30, 55, and 80cm depths to quantify patterns of soil moisture and respiratory CO2 efflux in response to rainfall events of varying magnitude and intervening periods of drought. Five replicates of each were maintained under current ambient or projected (+4oC) air temperatures. In addition, we used minirhizotrons to quantify the response of roots to episodic rainfall and confirm differences among plant types and collected soils solution samples to quantify dissolved inorganic carbon (DIC), pH, and other solute concentrations. Importantly, we found Rsoil dynamics to be nearly in direct contrast to our classic understanding of patterns of soil CO2 efflux after rain events. Rsoil rates declined immediately upon wetting and gradually increased to pre-rain rates as the soils dried. Investigation into soil CO2 profile data showed that CO2 concentrations just below the surface declined significantly from near-ambient levels to near ~50ppm, which would directly impact rates of Rsoil. We detected differences among plant functional types in terms of rooting depth, water use, photosynthetic uptake, base rates of Rsoil, the time required to return to pre-rain rates of Rsoil, and the rates of soil weathering. Combining aboveground measurements of carbon uptake with these belowground estimates of carbon pools and efflux will allow us to make much more informed projections of carbon dynamics within highly weatherable soils across a range of global climate change projections and plant functional types.

Diurnal and seasonal patterns of ecosystem CO{sub 2} efflux from upland tundra in the foothills of the Brooks Range, Alaska, U.S.A.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oberbauer, S.F.; Gillespie, C.T.; Cheng, Weixin

1996-08-01

Carbon dioxide efflux and soil microenvironment were measured in three upland tundra communities in the foothills of the Brooks Range in arctic Alaska to determine the magnitude of CO{sub 2} efflux rates and the relative importance of the belowground factors that influence them. Gas exchange and soil microenvironment measurements were made weekly between 14 June and 31 July 1990. The study communities included lichen-heath, a sparse community vegetated by lichens and dwarf ericaceous shrubs on rocky soils, moist Cassiope dwarf-shrub heath tundra, dominated by Carex and evergreen and deciduous shrubs on relatively deep organic soils, and dry Cassiope dwarf-shrub heathmore » of stone-stripe areas, which was of intermediate character. Rates of CO{sub 2} efflux were similar for the three communities until mid-season when they peaked at rates between 4.9 and 5.9 g m{sup {minus}2} d{sup {minus}1}. Following the mid-season peak, the rates in all three communities declined, particularly in the lichen-heath. Seasonal patterns of CO{sub 2} efflux, soil temperature, and soil moisture suggest changing limitations to CO{sub 2} efflux, soil temperature, and soil moisture suggest changing limitations to CO{sub 2} efflux over the course of the season. Rates of carbon dioxide efflux followed changes in soil temperature early in the season when soil moisture was highest. Mid-season efflux appeared to be limited by soil, moss, and lichen hydration until the end of July, when temperature again limited efflux. Differences between the communities were related to microenvironmental differences and probable differences in carbon quality. The presence of peat-forming mosses is suggested to play an important role in differences in efflux and micro-environment among the communities. 32 refs., 3 figs., 4 tab.« less

Validation and Scaling of Soil Moisture in a Semi-Arid Environment: SMAP Validation Experiment 2015 (SMAPVEX15)

NASA Technical Reports Server (NTRS)

Colliander, Andreas; Cosh, Michael H.; Misra, Sidharth; Jackson, Thomas J.; Crow, Wade T.; Chan, Steven; Bindlish, Rajat; Chae, Chun; Holifield Collins, Chandra; Yueh, Simon H.

2017-01-01

The NASA SMAP (Soil Moisture Active Passive) mission conducted the SMAP Validation Experiment 2015 (SMAPVEX15) in order to support the calibration and validation activities of SMAP soil moisture data products. The main goals of the experiment were to address issues regarding the spatial disaggregation methodologies for improvement of soil moisture products and validation of the in situ measurement upscaling techniques. To support these objectives high-resolution soil moisture maps were acquired with the airborne PALS (Passive Active L-band Sensor) instrument over an area in southeast Arizona that includes the Walnut Gulch Experimental Watershed (WGEW), and intensive ground sampling was carried out to augment the permanent in situ instrumentation. The objective of the paper was to establish the correspondence and relationship between the highly heterogeneous spatial distribution of soil moisture on the ground and the coarse resolution radiometer-based soil moisture retrievals of SMAP. The high-resolution mapping conducted with PALS provided the required connection between the in situ measurements and SMAP retrievals. The in situ measurements were used to validate the PALS soil moisture acquired at 1-km resolution. Based on the information from a dense network of rain gauges in the study area, the in situ soil moisture measurements did not capture all the precipitation events accurately. That is, the PALS and SMAP soil moisture estimates responded to precipitation events detected by rain gauges, which were in some cases not detected by the in situ soil moisture sensors. It was also concluded that the spatial distribution of the soil moisture resulted from the relatively small spatial extents of the typical convective storms in this region was not completely captured with the in situ stations. After removing those cases (approximately10 of the observations) the following metrics were obtained: RMSD (root mean square difference) of0.016m3m3 and correlation of 0.83. The PALS soil moisture was also compared to SMAP and in situ soil moisture at the 36-km scale, which is the SMAP grid size for the standard product. PALS and SMAP soil moistures were found to be very similar owing to the close match of the brightness temperature measurements and the use of a common soil moisture retrieval algorithm. Spatial heterogeneity, which was identified using the high-resolution PALS soil moisture and the intensive ground sampling, also contributed to differences between the soil moisture estimates. In general, discrepancies found between the L-band soil moisture estimates and the 5-cm depth in situ measurements require methodologies to mitigate the impact on their interpretations in soil moisture validation and algorithm development. Specifically, the metrics computed for the SMAP radiometer-based soil moisture product over WGEW will include errors resulting from rainfall, particularly during the monsoon season when the spatial distribution of soil moisture is especially heterogeneous.

Initializing numerical weather prediction models with satellite-derived surface soil moisture: Data assimilation experiments with ECMWF's Integrated Forecast System and the TMI soil moisture data set

NASA Astrophysics Data System (ADS)

Drusch, M.

2007-02-01

Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.

Impact of SMOS soil moisture data assimilation on NCEP-GFS forecasts

NASA Astrophysics Data System (ADS)

Zhan, X.; Zheng, W.; Meng, J.; Dong, J.; Ek, M.

2012-04-01

Soil moisture is one of the few critical land surface state variables that have long memory to impact the exchanges of water, energy and carbon between the land surface and atmosphere. Accurate information about soil moisture status is thus required for numerical weather, seasonal climate and hydrological forecast as well as for agricultural production forecasts, water management and many other water related economic or social activities. Since the successful launch of ESA's soil moisture ocean salinity (SMOS) mission in November 2009, about 2 years of soil moisture retrievals has been collected. SMOS is believed to be the currently best satellite sensors for soil moisture remote sensing. Therefore, it becomes interesting to examine how the collected SMOS soil moisture data are compared with other satellite-sensed soil moisture retrievals (such as NASA's Advanced Microwave Scanning Radiometer -AMSR-E and EUMETSAT's Advanced Scatterometer - ASCAT)), in situ soil moisture measurements, and how these data sets impact numerical weather prediction models such as the Global Forecast System of NOAA-NCEP. This study implements the Ensemble Kalman filter in GFS to assimilate the AMSR-E, ASCAT and SMOS soil moisture observations after a quantitative assessment of their error rate based on in situ measurements from ground networks around contiguous United States. in situ soil moisture measurements from ground networks (such as USDA Soil Climate Analysis network - SCAN and NOAA's U.S. Climate Reference Network -USCRN) are used to evaluate the GFS soil moisture simulations (analysis). The benefits and uncertainties of assimilating the satellite data products in GFS are examined by comparing the GFS forecasts of surface temperature and rainfall with and without the assimilations. From these examinations, the advantages of SMOS soil moisture data products over other satellite soil moisture data sets will be evaluated. The next step toward operationally assimilating soil moisture and other land observations into GFS will also be discussed.

Diagnosis of nutrient imbalances with vector analysis in agroforestry systems.

PubMed

Isaac, Marney E; Kimaro, Anthony A

2011-01-01

Agricultural intensification has had unintended environmental consequences, including increased nutrient leaching and surface runoff and other agrarian-derived pollutants. Improved diagnosis of on-farm nutrient dynamics will have the advantage of increasing yields and will diminish financial and environmental costs. To achieve this, a management support system that allows for site-specific rapid evaluation of nutrient production imbalances and subsequent management prescriptions is needed for agroecological design. Vector diagnosis, a bivariate model to depict changes in yield and nutritional response simultaneously in a single graph, facilitates identification of nutritional status such as growth dilution, deficiency, sufficiency, luxury uptake, and toxicity. Quantitative data from cocoa agroforestry systems and pigeonpea intercropping trials in Ghana and Tanzania, respectively, were re-evaluated with vector analysis. Relative to monoculture, biomass increase in cocoa ( L.) under shade (35-80%) was accompanied by a 17 to 25% decline in P concentration, the most limiting nutrient on this site. Similarly, increasing biomass with declining P concentrations was noted for pigeonpea [ (L). Millsp.] in response to soil moisture availability under intercropping. Although vector analysis depicted nutrient responses, the current vector model does not consider non-nutrient resource effects on growth, such as ameliorated light and soil moisture, which were particularly active in these systems. We revisit and develop vector analysis into a framework for diagnosing nutrient and non-nutrient interactions in agroforestry systems. Such a diagnostic technique advances management decision-making by increasing nutrient precision and reducing environmental issues associated with agrarian-derived soil contamination. American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.

Soil moisture variability across different scales in an Indian watershed for satellite soil moisture product validation

NASA Astrophysics Data System (ADS)

Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra B.

2016-05-01

Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA's Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected at two nested scale extents (0.5 km and 3 km) to understand the trend of soil moisture variability across these scales. This ground-based soil moisture sampling was conducted in the 500 km2 Rana watershed situated in eastern India. The study area is characterized as sub-humid, sub-tropical climate with average annual rainfall of about 1456 mm. Three 3x3 km square grids were sampled intensively once a day at 49 locations each, at a spacing of 0.5 km. These intensive sampling locations were selected on the basis of different topography, soil properties and vegetation characteristics. In addition, measurements were also made at 9 locations around each intensive sampling grid at 3 km spacing to cover a 9x9 km square grid. Intensive fine scale soil moisture sampling as well as coarser scale samplings were made using both impedance probes and gravimetric analyses in the study watershed. The ground-based soil moisture samplings were conducted during the day, concurrent with the SMAP descending overpass. Analysis of soil moisture spatial variability in terms of areal mean soil moisture and the statistics of higher-order moments, i.e., the standard deviation, and the coefficient of variation are presented. Results showed that the standard deviation and coefficient of variation of measured soil moisture decreased with extent scale by increasing mean soil moisture.

Modeling soil moisture memory in savanna ecosystems

NASA Astrophysics Data System (ADS)

Gou, S.; Miller, G. R.

2011-12-01

Antecedent soil conditions create an ecosystem's "memory" of past rainfall events. Such soil moisture memory effects may be observed over a range of timescales, from daily to yearly, and lead to feedbacks between hydrological and ecosystem processes. In this study, we modeled the soil moisture memory effect on savanna ecosystems in California, Arizona, and Africa, using a system dynamics model created to simulate the ecohydrological processes at the plot-scale. The model was carefully calibrated using soil moisture and evapotranspiration data collected at three study sites. The model was then used to simulate scenarios with various initial soil moisture conditions and antecedent precipitation regimes, in order to study the soil moisture memory effects on the evapotranspiration of understory and overstory species. Based on the model results, soil texture and antecedent precipitation regime impact the redistribution of water within soil layers, potentially causing deeper soil layers to influence the ecosystem for a longer time. Of all the study areas modeled, soil moisture memory of California savanna ecosystem site is replenished and dries out most rapidly. Thus soil moisture memory could not maintain the high rate evapotranspiration for more than a few days without incoming rainfall event. On the contrary, soil moisture memory of Arizona savanna ecosystem site lasts the longest time. The plants with different root depths respond to different memory effects; shallow-rooted species mainly respond to the soil moisture memory in the shallow soil. The growing season of grass is largely depended on the soil moisture memory of the top 25cm soil layer. Grass transpiration is sensitive to the antecedent precipitation events within daily to weekly timescale. Deep-rooted plants have different responses since these species can access to the deeper soil moisture memory with longer time duration Soil moisture memory does not have obvious impacts on the phenology of woody plants, as these can maintain transpiration for a longer time even through the top soil layer dries out.

Using satellite image data to estimate soil moisture

NASA Astrophysics Data System (ADS)

Chuang, Chi-Hung; Yu, Hwa-Lung

2017-04-01

Soil moisture is considered as an important parameter in various study fields, such as hydrology, phenology, and agriculture. In hydrology, soil moisture is an significant parameter to decide how much rainfall that will infiltrate into permeable layer and become groundwater resource. Although soil moisture is a critical role in many environmental studies, so far the measurement of soil moisture is using ground instrument such as electromagnetic soil moisture sensor. Use of ground instrumentation can directly obtain the information, but the instrument needs maintenance and consume manpower to operation. If we need wide range region information, ground instrumentation probably is not suitable. To measure wide region soil moisture information, we need other method to achieve this purpose. Satellite remote sensing techniques can obtain satellite image on Earth, this can be a way to solve the spatial restriction on instrument measurement. In this study, we used MODIS data to retrieve daily soil moisture pattern estimation, i.e., crop water stress index (cwsi), over the year of 2015. The estimations are compared with the observations at the soil moisture stations from Taiwan Bureau of soil and water conservation. Results show that the satellite remote sensing data can be helpful to the soil moisture estimation. Further analysis can be required to obtain the optimal parameters for soil moisture estimation in Taiwan.

A Hydraulic Model Is Compatible with Rapid Changes in Leaf Elongation under Fluctuating Evaporative Demand and Soil Water Status1[C][W][OPEN

PubMed Central

Caldeira, Cecilio F.; Bosio, Mickael; Parent, Boris; Jeanguenin, Linda; Chaumont, François; Tardieu, François

2014-01-01

Plants are constantly facing rapid changes in evaporative demand and soil water content, which affect their water status and growth. In apparent contradiction to a hydraulic hypothesis, leaf elongation rate (LER) declined in the morning and recovered upon soil rehydration considerably quicker than transpiration rate and leaf water potential (typical half-times of 30 min versus 1–2 h). The morning decline of LER began at very low light and transpiration and closely followed the stomatal opening of leaves receiving direct light, which represent a small fraction of leaf area. A simulation model in maize (Zea mays) suggests that these findings are still compatible with a hydraulic hypothesis. The small water flux linked to stomatal aperture would be sufficient to decrease water potentials of the xylem and growing tissues, thereby causing a rapid decline of simulated LER, while the simulated water potential of mature tissues declines more slowly due to a high hydraulic capacitance. The model also captured growth patterns in the evening or upon soil rehydration. Changes in plant hydraulic conductance partly counteracted those of transpiration. Root hydraulic conductivity increased continuously in the morning, consistent with the transcript abundance of Zea maize Plasma Membrane Intrinsic Protein aquaporins. Transgenic lines underproducing abscisic acid, with lower hydraulic conductivity and higher stomatal conductance, had a LER declining more rapidly than wild-type plants. Whole-genome transcriptome and phosphoproteome analyses suggested that the hydraulic processes proposed here might be associated with other rapidly occurring mechanisms. Overall, the mechanisms and model presented here may be an essential component of drought tolerance in naturally fluctuating evaporative demand and soil moisture. PMID:24420931

Using Remotely Sensed Soil Moisture to Estimate Fire Risk in Tropical Peatlands

NASA Astrophysics Data System (ADS)

Dadap, N.; Cobb, A.; Hoyt, A.; Harvey, C. F.; Konings, A. G.

2017-12-01

Tropical peatlands in Equatorial Asia have become more vulnerable to fire due to deforestation and peatland drainage over the last 30 years. In these regions, water table depth has been shown to play an important role in mediating fire risk as it serves as a proxy for peat moisture content. However, water table depth observations are sparse and expensive. Soil moisture could provide a more direct indicator of fire risk than water table depth. In this study, we use new soil moisture retrievals from the Soil Moisture Active Passive (SMAP) satellite to demonstrate that - contrary to popular wisdom - remotely sensed soil moisture observations are possible over most Southeast Asian peatlands. Soil moisture estimation in this region was previously thought to be impossible over tropical peatlands because of dense vegetation cover. We show that vegetation density is sufficiently low across most Equatorial Asian peatlands to allow soil moisture estimation, and hypothesize that deforestation and other anthropogenic changes in land cover have combined to reduce overall vegetation density sufficient to allow soil moisture estimation. We further combine burned area estimates from the Global Fire Emissions Database and SMAP soil moisture retrievals to show that soil moisture provides a strong signal for fire risk in peatlands, with fires occurring at a much greater rate over drier soils. We will also develop an explicit fire risk model incorporating soil moisture with additional climatic, land cover, and anthropogenic predictor variables.

A microwave systems approach to measuring root zone soil moisture

NASA Technical Reports Server (NTRS)

Newton, R. W.; Paris, J. F.; Clark, B. V.

1983-01-01

Computer microwave satellite simulation models were developed and the program was used to test the ability of a coarse resolution passive microwave sensor to measure soil moisture over large areas, and to evaluate the effect of heterogeneous ground covers with the resolution cell on the accuracy of the soil moisture estimate. The use of realistic scenes containing only 10% to 15% bare soil and significant vegetation made it possible to observe a 60% K decrease in brightness temperature from a 5% soil moisture to a 35% soil moisture at a 21 cm microwave wavelength, providing a 1.5 K to 2 K per percent soil moisture sensitivity to soil moisture. It was shown that resolution does not affect the basic ability to measure soil moisture with a microwave radiometer system. Experimental microwave and ground field data were acquired for developing and testing a root zone soil moisture prediction algorithm. The experimental measurements demonstrated that the depth of penetration at a 21 cm microwave wavelength is not greater than 5 cm.

The international soil moisture network: A data hosting facility for global in situ soil moisture measurements

USDA-ARS?s Scientific Manuscript database

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land co...

An analysis of soil moisture and vegetation conditions during a period of rapid subseasonal oscillations between drought and pluvials over Texas during 2015

NASA Astrophysics Data System (ADS)

Hunt, E. D.; Otkin, J.; Zhong, Y.

2017-12-01

Flash drought, characterized by the rapid onset of abnormally warm and dry weather conditions that leads to the rapid depletion of soil moisture and rapid deteriorations in vegetation health. Flash recovery, on the other hand, is characterized by a period(s) of intense precipitation where drought conditions are quickly eradicated and may be replaced by saturated soils and flooding. Both flash drought and flash recovery are closely tied to the rapid depletion or recharge of root zone soil moisture; therefore, soil moisture observations are very useful for monitoring their evolution. However, in-situ soil moisture observations tend to be concentrated over small regions and thus other methods are needed to provide a spatially continuous depiction of soil moisture conditions. One option is to use top soil moisture retrievals from the Soil Moisture Active Passive (SMAP) sensor. SMAP provides routine coverage of surface soil moisture (0-5 cm) over most of the globe, including the timespan (2015) and region of interest (Texas) that are the focus of our study. This region had an unusual sequence of flash recovery-flash drought-flash recovery during an six-month period during 2015 that provides a valuable case study of rapid transitions between extreme soil moisture conditions. During this project, SMAP soil moisture retrievals are being used in combination with in-situ soil moisture observations and assimilated into the Land Information System (LIS) to provide information about soil moisture content. LIS also provides greenness vegetation fraction data over large regions. The relationship between soil moisture and vegetation conditions and the response of the vegetation to the rapidly changing conditions are also assessed using the satellite thermal infrared based Evaporative Stress Index (ESI) that depicts anomalies in evapotranspiration, along with other vegetation datasets (leaf area index, greenness fraction) derived using MODIS observations. Preliminary results with the Noah land surface model (inside of LIS) shows that it broadly captured the soil moisture evolution during the 2015 sequence but tended to underestimate the magnitude of soil moisture anomalies. The ESI also showed negative anomalies during the drought. These and other results will be presented at the annual meeting.

Evaluation of a Soil Moisture Data Assimilation System Over West Africa

NASA Astrophysics Data System (ADS)

Bolten, J. D.; Crow, W.; Zhan, X.; Jackson, T.; Reynolds, C.

2009-05-01

A crucial requirement of global crop yield forecasts by the U.S. Department of Agriculture (USDA) International Production Assessment Division (IPAD) is the regional characterization of surface and sub-surface soil moisture. However, due to the spatial heterogeneity and dynamic nature of precipitation events and resulting soil moisture, accurate estimation of regional land surface-atmosphere interactions based sparse ground measurements is difficult. IPAD estimates global soil moisture using daily estimates of minimum and maximum temperature and precipitation applied to a modified Palmer two-layer soil moisture model which calculates the daily amount of soil moisture withdrawn by evapotranspiration and replenished by precipitation. We attempt to improve upon the existing system by applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA soil moisture model. This work aims at evaluating the utility of merging satellite-retrieved soil moisture estimates with the IPAD two-layer soil moisture model used within the DBMS. We present a quantitative analysis of the assimilated soil moisture product over West Africa (9°N- 20°N; 20°W-20°E). This region contains many key agricultural areas and has a high agro- meteorological gradient from desert and semi-arid vegetation in the North, to grassland, trees and crops in the South, thus providing an ideal location for evaluating the assimilated soil moisture product over multiple land cover types and conditions. A data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing assimilated soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.

Assessing the uncertainty of soil moisture impacts on convective precipitation using a new ensemble approach

NASA Astrophysics Data System (ADS)

Henneberg, Olga; Ament, Felix; Grützun, Verena

2018-05-01

Soil moisture amount and distribution control evapotranspiration and thus impact the occurrence of convective precipitation. Many recent model studies demonstrate that changes in initial soil moisture content result in modified convective precipitation. However, to quantify the resulting precipitation changes, the chaotic behavior of the atmospheric system needs to be considered. Slight changes in the simulation setup, such as the chosen model domain, also result in modifications to the simulated precipitation field. This causes an uncertainty due to stochastic variability, which can be large compared to effects caused by soil moisture variations. By shifting the model domain, we estimate the uncertainty of the model results. Our novel uncertainty estimate includes 10 simulations with shifted model boundaries and is compared to the effects on precipitation caused by variations in soil moisture amount and local distribution. With this approach, the influence of soil moisture amount and distribution on convective precipitation is quantified. Deviations in simulated precipitation can only be attributed to soil moisture impacts if the systematic effects of soil moisture modifications are larger than the inherent simulation uncertainty at the convection-resolving scale. We performed seven experiments with modified soil moisture amount or distribution to address the effect of soil moisture on precipitation. Each of the experiments consists of 10 ensemble members using the deep convection-resolving COSMO model with a grid spacing of 2.8 km. Only in experiments with very strong modification in soil moisture do precipitation changes exceed the model spread in amplitude, location or structure. These changes are caused by a 50 % soil moisture increase in either the whole or part of the model domain or by drying the whole model domain. Increasing or decreasing soil moisture both predominantly results in reduced precipitation rates. Replacing the soil moisture with realistic fields from different days has an insignificant influence on precipitation. The findings of this study underline the need for uncertainty estimates in soil moisture studies based on convection-resolving models.

Moisture-strength-constructability guidelines for subgrade foundation soils found in Indiana.

DOT National Transportation Integrated Search

2016-09-01

Soil moisture is an important indicator of constructability in the field. Construction activities become difficult when the soil moisture content is excessive, especially in fine-grained soils. Change orders caused by excessive soil moisture during c...

A New Approach for Validating Satellite Estimates of Soil Moisture Using Large-Scale Precipitation: Comparing AMSR-E Products

NASA Astrophysics Data System (ADS)

Tuttle, S. E.; Salvucci, G.

2012-12-01

Soil moisture influences many hydrological processes in the water and energy cycles, such as runoff generation, groundwater recharge, and evapotranspiration, and thus is important for climate modeling, water resources management, agriculture, and civil engineering. Large-scale estimates of soil moisture are produced almost exclusively from remote sensing, while validation of remotely sensed soil moisture has relied heavily on ground truthing, which is at an inherently smaller scale. Here we present a complementary method to determine the information content in different soil moisture products using only large-scale precipitation data (i.e. without modeling). This study builds on the work of Salvucci [2001], Saleem and Salvucci [2002], and Sun et al. [2011], in which precipitation was conditionally averaged according to soil moisture level, resulting in moisture-outflow curves that estimate the dependence of drainage, runoff, and evapotranspiration on soil moisture (i.e. sigmoidal relations that reflect stressed evapotranspiration for dry soils, roughly constant flux equal to potential evaporation minus capillary rise for moderately dry soils, and rapid drainage for very wet soils). We postulate that high quality satellite estimates of soil moisture, using large-scale precipitation data, will yield similar sigmoidal moisture-outflow curves to those that have been observed at field sites, while poor quality estimates will yield flatter, less informative curves that explain less of the precipitation variability. Following this logic, gridded ¼ degree NLDAS precipitation data were compared to three AMSR-E derived soil moisture products (VUA-NASA, or LPRM [Owe et al., 2001], NSIDC [Njoku et al., 2003], and NSIDC-LSP [Jones & Kimball, 2011]) for a period of nine years (2001-2010) across the contiguous United States. Gaps in the daily soil moisture data were filled using a multiple regression model reliant on past and future soil moisture and precipitation, and soil moisture was then converted to a ranked wetness index, in order to reconcile the wide range and magnitude of the soil moisture products. Generalized linear models were employed to fit a polynomial model to precipitation, given wetness index. Various measures of fit (e.g. log likelihood) were used to judge the amount of information in each soil moisture product, as indicated by the amount of precipitation variability explained by the fitted model. Using these methods, regional patterns appear in soil moisture product performance.

A spatial scaling relationship for soil moisture in a semiarid landscape, using spatial scaling relationships for pedology

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.

2013-12-01

In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.

PubMed

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F; Li, Lin; Seely, Mary K

2016-01-01

Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months' continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert

PubMed Central

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.

2016-01-01

Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert. PMID:27764203

Linking the soil moisture distribution pattern to dynamic processes along slope transects in the Loess Plateau, China.

PubMed

Wang, Shuai; Fu, Bojie; Gao, Guangyao; Zhou, Ji; Jiao, Lei; Liu, Jianbo

2015-12-01

Soil moisture pulses are a prerequisite for other land surface pulses at various spatiotemporal scales in arid and semi-arid areas. The temporal dynamics and profile variability of soil moisture in relation to land cover combinations were studied along five slopes transect on the Loess Plateau during the rainy season of 2011. Within the 3 months of the growing season coupled with the rainy season, all of the soil moisture was replenished in the area, proving that a type stability exists between different land cover soil moisture levels. Land cover combinations disturbed the trend determined by topography and increased soil moisture variability in space and time. The stability of soil moisture resulting from the dynamic processes could produce stable patterns on the slopes. The relationships between the mean soil moisture and vertical standard deviation (SD) and coefficient of variation (CV) were more complex, largely due to the fact that different land cover types had distinctive vertical patterns of soil moisture. The spatial SD of each layer had a positive correlation and the spatial CV exhibited a negative correlation with the increase in mean soil moisture. The soil moisture stability implies that sampling comparisons in this area can be conducted at different times to accurately compare different land use types.

Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture

NASA Astrophysics Data System (ADS)

Sure, A.; Dikshit, O.

2017-12-01

Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.

Persistence of glyphosate and aminomethylphosphonic acid in loess soil under different combinations of temperature, soil moisture and light/darkness.

PubMed

Bento, Célia P M; Yang, Xiaomei; Gort, Gerrit; Xue, Sha; van Dam, Ruud; Zomer, Paul; Mol, Hans G J; Ritsema, Coen J; Geissen, Violette

2016-12-01

The dissipation kinetics of glyphosate and its metabolite aminomethylphosphonic acid (AMPA) were studied in loess soil, under biotic and abiotic conditions, as affected by temperature, soil moisture (SM) and light/darkness. Nonsterile and sterile soil samples were spiked with 16mgkg -1 of glyphosate, subjected to three SM contents (20% WHC, 60% WHC, saturation), and incubated for 30days at 5°C and 30°C, under dark and light regimes. Glyphosate and AMPA dissipation kinetics were fit to single-first-order (SFO) or first-order-multicompartment (FOMC) models, per treatment combination. AMPA kinetic model included both the formation and decline phases. Glyphosate dissipation kinetics followed SFO at 5°C, but FOMC at 30°C. AMPA followed SFO dissipation kinetics for all treatments. Glyphosate and AMPA dissipation occurred mostly by microbial activity. Abiotic processes played a negligible role for both compounds. Under biotic conditions, glyphosate dissipation and AMPA formation/dissipation were primarily affected by temperature, but also by SM. Light regimes didn't play a significant role. Glyphosate DT50 varied between 1.5 and 53.5days, while its DT90 varied between 8.0 and 280days, depending on the treatment. AMPA persisted longer in soil than glyphosate, with its DT50 at 30°C ranging between 26.4 and 44.5days, and its DT90 between 87.8 and 148days. The shortest DT50/DT90 values for both compounds occurred at 30°C and under optimal/saturated moisture conditions, while the largest occurred at 5°C and reaching drought stress conditions. Based on these results, we conclude that glyphosate and AMPA dissipate rapidly under warm and rainy climate conditions. However, repeated glyphosate applications in fallows or winter crops in countries where cold and dry winters normally occur could lead to on-site soil pollution, with consequent potential risks to the environment and human health. To our knowledge, this study is the first evaluating the combined effect of temperature, soil moisture and light/dark conditions on AMPA formation/dissipation kinetics and behaviour. Copyright © 2016 Elsevier B.V. All rights reserved.

Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas; Cosh, Michael; Zhao, Tianjie; O'Neil, Peggy

2015-01-01

Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = -0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

Soil moisture and soil temperature variability among three plant communities in a High Arctic Lake Basin

NASA Astrophysics Data System (ADS)

Davis, M. L.; Konkel, J.; Welker, J. M.; Schaeffer, S. M.

2017-12-01

Soil moisture and soil temperature are critical to plant community distribution and soil carbon cycle processes in High Arctic tundra. As environmental drivers of soil biochemical processes, the predictability of soil moisture and soil temperature by vegetation zone in High Arctic landscapes has significant implications for the use of satellite imagery and vegetation distribution maps to estimate of soil gas flux rates. During the 2017 growing season, we monitored soil moisture and soil temperature weekly at 48 sites in dry tundra, moist tundra, and wet grassland vegetation zones in a High Arctic lake basin. Soil temperature in all three communities reflected fluctuations in air temperature throughout the season. Mean soil temperature was highest in the dry tundra community at 10.5±0.6ºC, however, did not differ between moist tundra and wet grassland communities (2.7±0.6 and 3.1±0.5ºC, respectively). Mean volumetric soil moisture differed significantly among all three plant communities with the lowest and highest soil moisture measured in the dry tundra and wet grassland (30±1.2 and 65±2.7%), respectively. For all three communities, soil moisture was highest during the early season snow melt. Soil moisture in wet grassland remained high with no significant change throughout the season, while significant drying occurred in dry tundra. The most significant change in soil moisture was measured in moist tundra, ranging from 61 to 35%. Our results show different gradients in soil moisture variability within each plant community where: 1) soil moisture was lowest in dry tundra with little change, 2) highest in wet grassland with negligible change, and 3) variable in moist tundra which slowly dried but remained moist. Consistently high soil moisture in wet grassland restricts this plant community to areas with no significant drying during summer. The moist tundra occupies the intermediary areas between wet grassland and dry tundra and experiences the widest range of soil moisture variability. As climate projections predict wetter summers in the High Arctic, expansion of areas with seasonally inundated soils and increased soil moisture variability could result in an expansion of wet grassland and moist tundra communities with a commensurate decrease in dry tundra area.

Response of spectral vegetation indices to soil moisture in grasslands and shrublands

USGS Publications Warehouse

Zhang, Li; Ji, Lei; Wylie, Bruce K.

2011-01-01

The relationships between satellite-derived vegetation indices (VIs) and soil moisture are complicated because of the time lag of the vegetation response to soil moisture. In this study, we used a distributed lag regression model to evaluate the lag responses of VIs to soil moisture for grasslands and shrublands at Soil Climate Analysis Network sites in the central and western United States. We examined the relationships between Moderate Resolution Imaging Spectroradiometer (MODIS)-derived VIs and soil moisture measurements. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) showed significant lag responses to soil moisture. The lag length varies from 8 to 56 days for NDVI and from 16 to 56 days for NDWI. However, the lag response of NDVI and NDWI to soil moisture varied among the sites. Our study suggests that the lag effect needs to be taken into consideration when the VIs are used to estimate soil moisture.

Soil Moisture Project Evaluation Workshop

NASA Technical Reports Server (NTRS)

Gilbert, R. H. (Editor)

1980-01-01

Approaches planned or being developed for measuring and modeling soil moisture parameters are discussed. Topics cover analysis of spatial variability of soil moisture as a function of terrain; the value of soil moisture information in developing stream flow data; energy/scene interactions; applications of satellite data; verifying soil water budget models; soil water profile/soil temperature profile models; soil moisture sensitivity analysis; combinations of the thermal model and microwave; determing planetary roughness and field roughness; how crust or a soil layer effects microwave return; truck radar; and truck/aircraft radar comparison.

The Temporal Dynamics of Spatial Patterns of Observed Soil Moisture Interpreted Using the Hydrus 1-D Model

NASA Astrophysics Data System (ADS)

Chen, M.; Willgoose, G. R.; Saco, P. M.

2009-12-01

This paper investigates the soil moisture dynamics over two subcatchments (Stanley and Krui) in the Goulburn River in NSW during a three year period (2005-2007) using the Hydrus 1-D unsaturated soil water flow model. The model was calibrated to the seven Stanley microcatchment sites (1 sqkm site) using continuous time surface 30cm and full profile soil moisture measurements. Soil type, leaf area index and soil depth were found to be the key parameters changing model fit to the soil moisture time series. They either shifted the time series up or down, changed the steepness of dry-down recessions or determined the lowest point of soil moisture dry-down respectively. Good correlations were obtained between observed and simulated soil water storage (R=0.8-0.9) when calibrated parameters for one site were applied to the other sites. Soil type was also found to be the main determinant (after rainfall) of the mean of modelled soil moisture time series. Simulations of top 30cm were better than those of the whole soil profile. Within the Stanley microcatchment excellent soil moisture matches could be generated simply by adjusting the mean of soil moisture up or down slightly. Only minor modification of soil properties from site to site enable good fits for all of the Stanley sites. We extended the predictions of soil moisture to a larger spatial scale of the Krui catchment (sites up to 30km distant from Stanley) using soil and vegetation parameters from Stanley but the locally recorded rainfall at the soil moisture measurement site. The results were encouraging (R=0.7~0.8). These results show that it is possible to use a calibrated soil moisture model to extrapolate the soil moisture to other sites for a catchment with an area of up to 1000km2. This paper demonstrates the potential usefulness of continuous time, point scale soil moisture (typical of that measured by permanently installed TDR probes) in predicting the soil wetness status over a catchment of significant size.

Harnessing long-term flux records to better understand ecosystem response to drought

NASA Astrophysics Data System (ADS)

Novick, K. A.; Ficklin, D. L.; Stoy, P. C.; Williams, C. A.; Bohrer, G.; Oishi, A. C.; Papuga, S. A.; Blanken, P.; Noormets, A.; Scott, R. L.; Wang, L.; Roman, D. T.; Yi, K.; Sulman, B. N.; Phillips, R.

2016-12-01

While ongoing climate change affects a number of meteorological drivers relevant to plant functioning, the predicted increase in the frequency and severity of droughts may ultimately have the biggest impact on ecosystem carbon cycling. Because it is difficult to experimentally manipulate all of the meteorological drivers that change during drought (including precipitation, light, temperature, and humidity), our understanding of the mechanisms by which plants respond to drought is generally limited to an understanding of how plants respond to variable soil moisture. As flux tower records grow in length and number, they permit us to harness natural spatial and temporal variability in hydrologic condition to better understand how ecosystems respond to the full suite of meteorological drivers that change during drought stress. Here, a series of case studies are presented that illustrate how long term flux data can be used to disentangle limitations to ecosystem functioning imposed by declining soil moisture as compared to rising atmospheric demand for water during drought. At the site-level, we pair observations from the Morgan-Monroe State Forest Ameriflux tower (active since 1999) with eco-physiological datasets collected during the severe 2012 Midwestern drought. We show that vapor pressure deficit (VPD) limits ecosystem carbon uptake and transpiration as much as soil moisture, but that individual species vary in their sensitivity to these drivers. We then present results from two cross-site Ameriflux syntheses that quantify how VPD as compared to soil moisture limitations to carbon and water cycling vary across broad climate gradients spanning semi-arid to mesic biomes. Informed by these results, we end by highlighting ways that flux network data may be leveraged together with other eco-physiological networks and databases to further expand our understanding of the mechanisms determining ecosystem response to drought.

Response of dominant grass and shrub species to water manipulation: an ecophysiological basis for shrub invasion in a Chihuahuan Desert grassland.

PubMed

Throop, Heather L; Reichmann, Lara G; Sala, Osvaldo E; Archer, Steven R

2012-06-01

Increases in woody vegetation and declines in grasses in arid and semi-arid ecosystems have occurred globally since the 1800s, but the mechanisms driving this major land-cover change remain uncertain and controversial. Working in a shrub-encroached grassland in the northern Chihuahuan Desert where grasses and shrubs typically differ in leaf-level nitrogen allocation, photosynthetic pathway, and root distribution, we asked if differences in leaf-level ecophysiology could help explain shrub proliferation. We predicted that the relative performance of grasses and shrubs would vary with soil moisture due to the different morphological and physiological characteristics of the two life-forms. In a 2-year experiment with ambient, reduced, and enhanced precipitation during the monsoon season, respectively, the encroaching C(3) shrub (honey mesquite Prosopis glandulosa) consistently and substantially outperformed the historically dominant C(4) grass (black grama Bouteloua eriopoda) in terms of photosynthetic rates while also maintaining a more favorable leaf water status. These differences persisted across a wide range of soil moisture conditions, across which mesquite photosynthesis was decoupled from leaf water status and moisture in the upper 50 cm of the soil profile. Mesquite's ability to maintain physiologically active leaves for a greater fraction of the growing season than black grama potentially amplifies and extends the importance of physiological differences. These physiological and phenological differences may help account for grass displacement by shrubs in drylands. Furthermore, the greater sensitivity of the grass to low soil moisture suggests that grasslands may be increasingly susceptible to shrub encroachment in the face of the predicted increases in drought intensity and frequency in the desert of the southwestern USA.

Discrimination of soil hydraulic properties by combined thermal infrared and microwave remote sensing

NASA Technical Reports Server (NTRS)

Vandegriend, A. A.; Oneill, P. E.

1986-01-01

Using the De Vries models for thermal conductivity and heat capacity, thermal inertia was determined as a function of soil moisture for 12 classes of soil types ranging from sand to clay. A coupled heat and moisture balance model was used to describe the thermal behavior of the top soil, while microwave remote sensing was used to estimate the soil moisture content of the same top soil. Soil hydraulic parameters are found to be very highly correlated with the combination of soil moisture content and thermal inertia at the same moisture content. Therefore, a remotely sensed estimate of the thermal behavior of the soil from diurnal soil temperature observations and an independent remotely sensed estimate of soil moisture content gives the possibility of estimating soil hydraulic properties by remote sensing.

Improved Prediction of Quasi-Global Vegetation Conditions Using Remotely-Sensed Surface Soil Moisture

NASA Technical Reports Server (NTRS)

Bolten, John; Crow, Wade

2012-01-01

The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.

Pre-exposure to drought increases the resistance of tropical forest soil bacterial communities to extended drought

PubMed Central

Bouskill, Nicholas J; Lim, Hsiao Chien; Borglin, Sharon; Salve, Rohit; Wood, Tana E; Silver, Whendee L; Brodie, Eoin L

2013-01-01

Global climate models project a decrease in the magnitude of precipitation in tropical regions. Changes in rainfall patterns have important implications for the moisture content and redox status of tropical soils, yet little is known about how these changes may affect microbial community structure. Specifically, does exposure to prior stress confer increased resistance to subsequent perturbation? Here we reduced the quantity of precipitation throughfall to tropical forest soils in the Luquillo Mountains, Puerto Rico. Treatments included newly established throughfall exclusion plots (de novo excluded), plots undergoing reduction for a second time (pre-excluded) and ambient control plots. Ten months of throughfall exclusion led to a small but statistically significant decline in soil water potential and bacterial populations clearly adapted to increased osmotic stress. Although the water potential decline was small and microbial biomass did not change, phylogenetic diversity in the de novo-excluded plots decreased by ∼40% compared with the control plots, yet pre-excluded plots showed no significant change. On the other hand, the relative abundances of bacterial taxa in both the de novo-excluded and pre-excluded plots changed significantly with throughfall exclusion compared with control plots. Changes in bacterial community structure could be explained by changes in soil pore water chemistry and suggested changes in soil redox. Soluble iron declined in treatment plots and was correlated with decreased soluble phosphorus concentrations, which may have significant implications for microbial productivity in these P-limited systems. PMID:23151641

The SWEX at the area of Eastern Poland: Comparison of soil moisture obtained from ground measurements and SMOS satellite data*

NASA Astrophysics Data System (ADS)

Usowicz, J. B.; Marczewski, W.; Usowicz, B.; Lukowski, M. I.; Lipiec, J.; Slominski, J.

2012-04-01

Soil moisture, together with soil and vegetation characteristics, plays an important role in exchange of water and energy between the land surface and the atmospheric boundary layer. Accurate knowledge of current and future spatial and temporal variation in soil moisture is not well known, nor easy to measure or predict. Knowledge of soil moisture in surface and root zone soil moisture is critical for achieving sustainable land and water management. The importance of SM is so high that this ECV is recommended by GCOS (Global Climate Observing System) to any attempts of evaluating of effects the climate change, and therefore it is one of the goals for observing the Earth by the ESA SMOS Mission (Soil Moisture and Ocean Salinity), globally. SMOS provides its observations by means of the interferometric radiometry method (1.4 GHz) from the orbit. In parallel, ten ground based stations are kept by IA PAN, in area of the Eastern Wall in Poland, in order to validate SMOS data and for other ground based agrophysical purposes. Soil moisture measurements obtained from ground and satellite measurements from SMOS were compared using Bland-Altman method of agreement, concordance correlation coefficient (CCC) and total deviation index (TDI). Observed similar changes in soil moisture, but the values obtained from satellite measurements were lower. Minor differences between the compared data are at higher moisture contents of soil and they grow with decreasing soil moisture. Soil moisture trends are maintained in the individual stations. Such distributions of soil moisture were mainly related to soil type. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO3275.

A multiyear study of soil moisture patterns across agricultural and forested landscapes

NASA Astrophysics Data System (ADS)

Georgakakos, C. B.; Hofmeister, K.; O'Connor, C.; Buchanan, B.; Walter, T.

2017-12-01

This work compares varying spatial and temporal soil moisture patterns in wet and dry years between forested and agricultural landscapes. This data set spans 6 years (2012-2017) of snow-free soil moisture measurements across multiple watersheds and land covers in New York State's Finger Lakes region. Due to the relatively long sampling period, we have captured fluctuations in soil moisture dynamics across wetter, dryer, and average precipitation years. We can therefore analyze response of land cover types to precipitation under varying climatic and hydrologic conditions. Across the study period, mean soil moisture in forest soils was significantly drier than in agricultural soils, and exhibited a smaller range of moisture conditions. In the drought year of 2016, soil moisture at all sites was significantly drier compared to the other years. When comparing the effects of land cover and year on soil moisture, we found that land cover had a more significant influence. Understanding the difference in landscape soil moisture dynamics between forested and agricultural land will help predict watershed responses to changing precipitation patterns in the future.

A comparative study of the SMAP passive soil moisture product with existing satellite-based soil moisture products

USDA-ARS?s Scientific Manuscript database

NASA Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015 to provide global mapping of high-resolution soil moisture and freeze thaw state every 2-3 days using an L-band (active) radar and an L-band (passive) radiometer. The radiometer-only soil moisture product (L2...

Prediction of Root Zone Soil Moisture using Remote Sensing Products and In-Situ Observation under Climate Change Scenario

NASA Astrophysics Data System (ADS)

Singh, G.; Panda, R. K.; Mohanty, B.

2015-12-01

Prediction of root zone soil moisture status at field level is vital for developing efficient agricultural water management schemes. In this study, root zone soil moisture was estimated across the Rana watershed in Eastern India, by assimilation of near-surface soil moisture estimate from SMOS satellite into a physically-based Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble Kalman filter (EnKF) technique coupled with SWAP model was used for assimilating the satellite soil moisture observation at different spatial scales. The universal triangle concept and artificial intelligence techniques were applied to disaggregate the SMOS satellite monitored near-surface soil moisture at a 40 km resolution to finer scale (1 km resolution), using higher spatial resolution of MODIS derived vegetation indices (NDVI) and land surface temperature (Ts). The disaggregated surface soil moisture were compared to ground-based measurements in diverse landscape using portable impedance probe and gravimetric samples. Simulated root zone soil moisture were compared with continuous soil moisture profile measurements at three monitoring stations. In addition, the impact of projected climate change on root zone soil moisture were also evaluated. The climate change projections of rainfall were analyzed for the Rana watershed from statistically downscaled Global Circulation Models (GCMs). The long-term root zone soil moisture dynamics were estimated by including a rainfall generator of likely scenarios. The predicted long term root zone soil moisture status at finer scale can help in developing efficient agricultural water management schemes to increase crop production, which lead to enhance the water use efficiency.

Empirical Soil Moisture Estimation with Spaceborne L-band Polarimetric Radars: Aquarius, SMAP, and PALSAR-2

NASA Astrophysics Data System (ADS)

Burgin, M. S.; van Zyl, J. J.

2017-12-01

Traditionally, substantial ancillary data is needed to parametrize complex electromagnetic models to estimate soil moisture from polarimetric radar data. The Soil Moisture Active Passive (SMAP) baseline radar soil moisture retrieval algorithm uses a data cube approach, where a cube of radar backscatter values is calculated using sophisticated models. In this work, we utilize the empirical approach by Kim and van Zyl (2009) which is an optional SMAP radar soil moisture retrieval algorithm; it expresses radar backscatter of a vegetated scene as a linear function of soil moisture, hence eliminating the need for ancillary data. We use 2.5 years of L-band Aquarius radar and radiometer derived soil moisture data to determine two coefficients of a linear model function on a global scale. These coefficients are used to estimate soil moisture with 2.5 months of L-band SMAP and L-band PALSAR-2 data. The estimated soil moisture is compared with the SMAP Level 2 radiometer-only soil moisture product; the global unbiased RMSE of the SMAP derived soil moisture corresponds to 0.06-0.07 cm3/cm3. In this study, we leverage the three diverse L-band radar data sets to investigate the impact of pixel size and pixel heterogeneity on soil moisture estimation performance. Pixel sizes range from 100 km for Aquarius, over 3, 9, 36 km for SMAP, to 10m for PALSAR-2. Furthermore, we observe seasonal variation in the radar sensitivity to soil moisture which allows the identification and quantification of seasonally changing vegetation. Utilizing this information, we further improve the estimation performance. The research described in this paper is supported by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Copyright 2017. All rights reserved.

The moisture response of soil heterotrophic respiration: Interaction with soil properties.

USDA-ARS?s Scientific Manuscript database

Soil moisture-respiration functions are used to simulate the various mechanisms determining the relations between soil moisture content and carbon mineralization. Soil models used in the simulation of global carbon fluxes often apply simplified functions assumed to represent an average moisture-resp...

SMAP Radiometer Captures Views of Global Soil Moisture

NASA Image and Video Library

2015-05-06

These maps of global soil moisture were created using data from the radiometer instrument on NASA Soil Moisture Active Passive SMAP observatory. Evident are regions of increased soil moisture and flooding during April, 2015.

Arbuscular mycorrhizal fungi associated with Populus-Salix stands in a semiarid riparian ecosystem

USGS Publications Warehouse

Beauchamp, Vanessa B.; Stromberg, J.C.; Stutz, J.C.

2006-01-01

??? This study examined the activity, species richness, and species composition of the arbuscular mycorrhizal fungal (AMF) community of Populus-Salix stands on the Verde River (Arizona, USA), quantified patterns of AMF richness and colonization along complex floodplain gradients, and identified environmental variables responsible for structuring the AMF community. ??? Samples from 61 Populus-Salix stands were analyzed for AMF and herbaceous composition, AMF colonization, gravimetric soil moisture, soil texture, per cent organic matter, pH, and concentrations of nitrate, bicarbonate phosphorus and exchangeable potassium. ??? AMF species richness declined with stand age and distance from and elevation above the channel and was positively related to perennial species cover and richness and gravimetric soil moisture. Distance from and elevation above the active channel, forest age, annual species cover, perennial species richness, and exchangeable potassium concentration all played a role in structuring the AMF community in this riparian area. ??? Most AMF species were found across a wide range of soil conditions, but a subset of species tended to occur more often in hydric areas. This group of riparian affiliate AMF species includes several not previously encountered in the surrounding Sonoran desert. ?? New Phytologist (2006).

Investigating local controls on soil moisture temporal stability using an inverse modeling approach

NASA Astrophysics Data System (ADS)

Bogena, Heye; Qu, Wei; Huisman, Sander; Vereecken, Harry

2013-04-01

A better understanding of the temporal stability of soil moisture and its relation to local and nonlocal controls is a major challenge in modern hydrology. Both local controls, such as soil and vegetation properties, and non-local controls, such as topography and climate variability, affect soil moisture dynamics. Wireless sensor networks are becoming more readily available, which opens up opportunities to investigate spatial and temporal variability of soil moisture with unprecedented resolution. In this study, we employed the wireless sensor network SoilNet developed by the Forschungszentrum Jülich to investigate soil moisture variability of a grassland headwater catchment in Western Germany within the framework of the TERENO initiative. In particular, we investigated the effect of soil hydraulic parameters on the temporal stability of soil moisture. For this, the HYDRUS-1D code coupled with a global optimizer (DREAM) was used to inversely estimate Mualem-van Genuchten parameters from soil moisture observations at three depths under natural (transient) boundary conditions for 83 locations in the headwater catchment. On the basis of the optimized parameter sets, we then evaluated to which extent the variability in soil hydraulic conductivity, pore size distribution, air entry suction and soil depth between these 83 locations controlled the temporal stability of soil moisture, which was independently determined from the observed soil moisture data. It was found that the saturated hydraulic conductivity (Ks) was the most significant attribute to explain temporal stability of soil moisture as expressed by the mean relative difference (MRD).

Constraint of soil moisture on CO2 efflux from tundra lichen, moss, and tussock in Council, Alaska, using a hierarchical Bayesian model

NASA Astrophysics Data System (ADS)

Kim, Y.; Nishina, K.; Chae, N.; Park, S. J.; Yoon, Y. J.; Lee, B. Y.

2014-10-01

The tundra ecosystem is quite vulnerable to drastic climate change in the Arctic, and the quantification of carbon dynamics is of significant importance regarding thawing permafrost, changes to the snow-covered period and snow and shrub community extent, and the decline of sea ice in the Arctic. Here, CO2 efflux measurements using a manual chamber system within a 40 m × 40 m (5 m interval; 81 total points) plot were conducted within dominant tundra vegetation on the Seward Peninsula of Alaska, during the growing seasons of 2011 and 2012, for the assessment of driving parameters of CO2 efflux. We applied a hierarchical Bayesian (HB) model - a function of soil temperature, soil moisture, vegetation type, and thaw depth - to quantify the effects of environmental factors on CO2 efflux and to estimate growing season CO2 emissions. Our results showed that average CO2 efflux in 2011 was 1.4 times higher than in 2012, resulting from the distinct difference in soil moisture between the 2 years. Tussock-dominated CO2 efflux is 1.4 to 2.3 times higher than those measured in lichen and moss communities, revealing tussock as a significant CO2 source in the Arctic, with a wide area distribution on the circumpolar scale. CO2 efflux followed soil temperature nearly exponentially from both the observed data and the posterior medians of the HB model. This reveals that soil temperature regulates the seasonal variation of CO2 efflux and that soil moisture contributes to the interannual variation of CO2 efflux for the two growing seasons in question. Obvious changes in soil moisture during the growing seasons of 2011 and 2012 resulted in an explicit difference between CO2 effluxes - 742 and 539 g CO2 m-2 period-1 for 2011 and 2012, respectively, suggesting the 2012 CO2 emission rate was reduced to 27% (95% credible interval: 17-36%) of the 2011 emission, due to higher soil moisture from severe rain. The estimated growing season CO2 emission rate ranged from 0.86 Mg CO2 in 2012 to 1.20 Mg CO2 in 2011 within a 40 m × 40 m plot, corresponding to 86 and 80% of annual CO2 emission rates within the western Alaska tundra ecosystem, estimated from the temperature dependence of CO2 efflux. Therefore, this HB model can be readily applied to observed CO2 efflux, as it demands only four environmental factors and can also be effective for quantitatively assessing the driving parameters of CO2 efflux.

Value of Available Global Soil Moisture Products for Agricultural Monitoring

NASA Astrophysics Data System (ADS)

Mladenova, Iliana; Bolten, John; Crow, Wade; de Jeu, Richard

2016-04-01

The first operationally derived and publicly distributed global soil moil moisture product was initiated with the launch of the Advanced Scanning Microwave Mission on the NASA's Earth Observing System Aqua satellite (AMSR-E). AMSR-E failed in late 2011, but its legacy is continued by AMSR2, launched in 2012 on the JAXA Global Change Observation Mission-Water (GCOM-W) mission. AMSR is a multi-frequency dual-polarization instrument, where the lowest two frequencies (C- and X-band) were used for soil moisture retrieval. Theoretical research and small-/field-scale airborne campaigns, however, have demonstrated that soil moisture would be best monitored using L-band-based observations. This consequently led to the development and launch of the first L-band-based mission-the ESA's Soil Moisture Ocean Salinity (SMOS) mission (2009). In early 2015 NASA launched the second L-band-based mission, the Soil Moisture Active Passive (SMAP). These satellite-based soil moisture products have been demonstrated to be invaluable sources of information for mapping water stress areas, crop monitoring and yield forecasting. Thus, a number of agricultural agencies routinely utilize and rely on global soil moisture products for improving their decision making activities, determining global crop production and crop prices, identifying food restricted areas, etc. The basic premise of applying soil moisture observations for vegetation monitoring is that the change in soil moisture conditions will precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop condition change. Here this relationship was evaluated across multiple microwave frequencies by examining the lag rank cross-correlation coefficient between the soil moisture observations and the Normalized Difference Vegetation Index (NDVI). A main goal of our analysis is to evaluate and inter-compare the value of the different soil moisture products derived using L-band (SMOS) versus C-/X-band (AMSR2) observations. The soil moisture products analyzed here were derived using the Land Parameter Retrieval Model.

Evaluation of gravimetric ground truth soil moisture data collected for the agricultural soil moisture experiment, 1978 Colby, Kansas, aircraft mission

NASA Technical Reports Server (NTRS)

Arya, L. M.; Phinney, D. E. (Principal Investigator)

1980-01-01

Soil moisture data acquired to support the development of algorithms for estimating surface soil moisture from remotely sensed backscattering of microwaves from ground surfaces are presented. Aspects of field uniformity and variability of gravimetric soil moisture measurements are discussed. Moisture distribution patterns are illustrated by frequency distributions and contour plots. Standard deviations and coefficients of variation relative to degree of wetness and agronomic features of the fields are examined. Influence of sampling depth on observed moisture content an variability are indicated. For the various sets of measurements, soil moisture values that appear as outliers are flagged. The distribution and legal descriptions of the test fields are included along with examinations of soil types, agronomic features, and sampling plan. Bulk density data for experimental fields are appended, should analyses involving volumetric moisture content be of interest to the users of data in this report.

Converting Soil Moisture Observations to Effective Values for Improved Validation of Remotely Sensed Soil Moisture

NASA Technical Reports Server (NTRS)

Laymon, Charles A.; Crosson, William L.; Limaye, Ashutosh; Manu, Andrew; Archer, Frank

2005-01-01

We compare soil moisture retrieved with an inverse algorithm with observations of mean moisture in the 0-6 cm soil layer. A significant discrepancy is noted between the retrieved and observed moisture. Using emitting depth functions as weighting functions to convert the observed mean moisture to observed effective moisture removes nearly one-half of the discrepancy noted. This result has important implications in remote sensing validation studies.

Effects of soil moisture on dust emission from 2011 to 2015 observed over the Horqin Sandy Land area, China

NASA Astrophysics Data System (ADS)

Ju, Tingting; Li, Xiaolan; Zhang, Hongsheng; Cai, Xuhui; Song, Yu

2018-06-01

Using the observational data of dust concentrations and meteorological parameters from 2011 to 2015, the effects of soil moisture and air humidity on dust emission were studied at long (monthly) and short (several days or hours) time scales over the Horqin Sandy Land area, Inner Mongolia of China. The results show that the monthly mean dust concentrations and dust fluxes within the near-surface layer had no obvious relationship with the monthly mean soil moisture content but had a slightly negative correlation with monthly mean air relative humidity from 2011 to 2015. The daily mean soil moisture exhibited a significantly negative correlation with the daily mean dust concentrations and dust fluxes, as soil moisture changed obviously. However, such negative correlation between soil moisture and dust emission disappeared on dust blowing days. Additionally, the effect of soil moisture on an important parameter for dust emission, the threshold friction velocity (u∗t), was investigated during several saltation-bombardment and/or aggregation-disintegration dust emission (SADE) events. Under dry soil conditions, the values of u∗t were not influenced by soil moisture content; however, when the soil moisture content was high, the values of u∗t increased with increasing soil moisture content.

Relation Between the Rainfall and Soil Moisture During Different Phases of Indian Monsoon

NASA Astrophysics Data System (ADS)

Varikoden, Hamza; Revadekar, J. V.

2018-03-01

Soil moisture is a key parameter in the prediction of southwest monsoon rainfall, hydrological modelling, and many other environmental studies. The studies on relationship between the soil moisture and rainfall in the Indian subcontinent are very limited; hence, the present study focuses the association between rainfall and soil moisture during different monsoon seasons. The soil moisture data used for this study are the ESA (European Space Agency) merged product derived from four passive and two active microwave sensors spanning over the period 1979-2013. The rainfall data used are India Meteorological Department gridded daily data. Both of these data sets are having a spatial resolution of 0.25° latitude-longitude grid. The study revealed that the soil moisture is higher during the southwest monsoon period similar to rainfall and during the pre-monsoon period, the soil moisture is lower. The annual cycle of both the soil moisture and rainfall has the similitude of monomodal variation with a peak during the month of August. The interannual variability of soil moisture and rainfall shows that they are linearly related with each other, even though they are not matched exactly for individual years. The study of extremes also exhibits the surplus amount of soil moisture during wet monsoon years and also the regions of surplus soil moisture are well coherent with the areas of high rainfall.

Hydrologic downscaling of soil moisture using global data without site-specific calibration

USDA-ARS?s Scientific Manuscript database

Numerous applications require fine-resolution (10-30 m) soil moisture patterns, but most satellite remote sensing and land-surface models provide coarse-resolution (9-60 km) soil moisture estimates. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales soil moistu...

New Physical Algorithms for Downscaling SMAP Soil Moisture

NASA Astrophysics Data System (ADS)

Sadeghi, M.; Ghafari, E.; Babaeian, E.; Davary, K.; Farid, A.; Jones, S. B.; Tuller, M.

2017-12-01

The NASA Soil Moisture Active Passive (SMAP) mission provides new means for estimation of surface soil moisture at the global scale. However, for many hydrological and agricultural applications the spatial SMAP resolution is too low. To address this scale issue we fused SMAP data with MODIS observations to generate soil moisture maps at 1-km spatial resolution. In course of this study we have improved several existing empirical algorithms and introduced a new physical approach for downscaling SMAP data. The universal triangle/trapezoid model was applied to relate soil moisture to optical/thermal observations such as NDVI, land surface temperature and surface reflectance. These algorithms were evaluated with in situ data measured at 5-cm depth. Our results demonstrate that downscaling SMAP soil moisture data based on physical indicators of soil moisture derived from the MODIS satellite leads to higher accuracy than that achievable with empirical downscaling algorithms. Keywords: Soil moisture, microwave data, downscaling, MODIS, triangle/trapezoid model.

Validation of the Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval in an Arctic tundra environment

NASA Astrophysics Data System (ADS)

Wrona, Elizabeth; Rowlandson, Tracy L.; Nambiar, Manoj; Berg, Aaron A.; Colliander, Andreas; Marsh, Philip

2017-05-01

This study examines the Soil Moisture Active Passive soil moisture product on the Equal Area Scalable Earth-2 (EASE-2) 36 km Global cylindrical and North Polar azimuthal grids relative to two in situ soil moisture monitoring networks that were installed in 2015 and 2016. Results indicate that there is no relationship between the Soil Moisture Active Passive (SMAP) Level-2 passive soil moisture product and the upscaled in situ measurements. Additionally, there is very low correlation between modeled brightness temperature using the Community Microwave Emission Model and the Level-1 C SMAP brightness temperature interpolated to the EASE-2 Global grid; however, there is a much stronger relationship to the brightness temperature measurements interpolated to the North Polar grid, suggesting that the soil moisture product could be improved with interpolation on the North Polar grid.

Methods of measuring soil moisture in the field

USGS Publications Warehouse

Johnson, A.I.

1962-01-01

For centuries, the amount of moisture in the soil has been of interest in agriculture. The subject of soil moisture is also of great importance to the hydrologist, forester, and soils engineer. Much equipment and many methods have been developed to measure soil moisture under field conditions. This report discusses and evaluates the various methods for measurement of soil moisture and describes the equipment needed for each method. The advantages and disadvantages of each method are discussed and an extensive list of references is provided for those desiring to study the subject in more detail. The gravimetric method is concluded to be the most satisfactory method for most problems requiring onetime moisture-content data. The radioactive method is normally best for obtaining repeated measurements of soil moisture in place. It is concluded that all methods have some limitations and that the ideal method for measurement of soil moisture under field conditions has yet to be perfected.

Linking carbon and water limitations to drought-induced mortality of Pinus flexilis seedlings

USGS Publications Warehouse

Reinhardt, Keith; Germino, Matthew J.; Kueppers, Lara M.; Domec, Jean-Christophe; Mitton, Jeffry

2015-01-01

Survival of tree seedlings at high elevations has been shown to be limited by thermal constraints on carbon balance, but it is unknown if carbon relations also limit seedling survival at lower elevations, where water relations may be more important. We measured and modeled carbon fluxes and water relations in first-year Pinus flexilis seedlings in garden plots just beyond the warm edge of their natural range, and compared these with dry-mass gain and survival across two summers. We hypothesized that mortality in these seedlings would be associated with declines in water relations, more so than with carbon-balance limitations. Rather than gradual declines in survivorship across growing seasons, we observed sharp, large-scale mortality episodes that occurred once volumetric soil-moisture content dropped below 10%. By this point, seedling water potentials had decreased below −5 MPa, seedling hydraulic conductivity had decreased by 90% and seedling hydraulic resistance had increased by >900%. Additionally, non-structural carbohydrates accumulated in aboveground tissues at the end of both summers, suggesting impairments in phloem-transport from needles to roots. This resulted in low carbohydrate concentrations in roots, which likely impaired root growth and water uptake at the time of critically low soil moisture. While photosynthesis and respiration on a leaf area basis remained high until critical hydraulic thresholds were exceeded, modeled seedling gross primary productivity declined steadily throughout the summers. At the time of mortality, modeled productivity was insufficient to support seedling biomass-gain rates, metabolism and secondary costs. Thus the large-scale mortality events that we observed near the end of each summer were most directly linked with acute, episodic declines in plant hydraulic function that were linked with important changes in whole-seedling carbon relations.

Multi-site assimilation of a terrestrial biosphere model (BETHY) using satellite derived soil moisture data

NASA Astrophysics Data System (ADS)

Wu, Mousong; Sholze, Marko

2017-04-01

We investigated the importance of soil moisture data on assimilation of a terrestrial biosphere model (BETHY) for a long time period from 2010 to 2015. Totally, 101 parameters related to carbon turnover, soil respiration, as well as soil texture were selected for optimization within a carbon cycle data assimilation system (CCDAS). Soil moisture data from Soil Moisture and Ocean Salinity (SMOS) product was derived for 10 sites representing different plant function types (PFTs) as well as different climate zones. Uncertainty of SMOS soil moisture data was also estimated using triple collocation analysis (TCA) method by comparing with ASCAT dataset and BETHY forward simulation results. Assimilation of soil moisture to the system improved soil moisture as well as net primary productivity(NPP) and net ecosystem productivity (NEP) when compared with soil moisture derived from in-situ measurements and fluxnet datasets. Parameter uncertainties were largely reduced relatively to prior values. Using SMOS soil moisture data for assimilation of a terrestrial biosphere model proved to be an efficient approach in reducing uncertainty in ecosystem fluxes simulation. It could be further used in regional an global assimilation work to constrain carbon dioxide concentration simulation by combining with other sources of measurements.

Surface soil moisture retrieval using the L-band synthetic aperture radar onboard the Soil Moisture Active Passive satellite and evaluation at core validation sites

USDA-ARS?s Scientific Manuscript database

This paper evaluates the retrieval of soil moisture in the top 5-cm layer at 3-km spatial resolution using L-band dual-copolarized Soil Moisture Active Passive (SMAP) synthetic aperture radar (SAR) data that mapped the globe every three days from mid-April to early July, 2015. Surface soil moisture ...

Using repeat electrical resistivity surveys to assess heterogeneity in soil moisture dynamics under contrasting vegetation types

NASA Astrophysics Data System (ADS)

Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris

2018-04-01

As the relationship between vegetation and soil moisture is complex and reciprocal, there is a need to understand how spatial patterns in soil moisture influence the distribution of vegetation, and how the structure of vegetation canopies and root networks regulates the partitioning of precipitation. Spatial patterns of soil moisture are often difficult to visualise as usually, soil moisture is measured at point scales, and often difficult to extrapolate. Here, we address the difficulties in collecting large amounts of spatial soil moisture data through a study combining plot- and transect-scale electrical resistivity tomography (ERT) surveys to estimate soil moisture in a 3.2 km2 upland catchment in the Scottish Highlands. The aim was to assess the spatio-temporal variability in soil moisture under Scots pine forest (Pinus sylvestris) and heather moorland shrubs (Calluna vulgaris); the two dominant vegetation types in the Scottish Highlands. The study focussed on one year of fortnightly ERT surveys. The surveyed resistivity data was inverted and Archie's law was used to calculate volumetric soil moisture by estimating parameters and comparing against field measured data. Results showed that spatial soil moisture patterns were more heterogeneous in the forest site, as were patterns of wetting and drying, which can be linked to vegetation distribution and canopy structure. The heather site showed a less heterogeneous response to wetting and drying, reflecting the more uniform vegetation cover of the shrubs. Comparing soil moisture temporal variability during growing and non-growing seasons revealed further contrasts: under the heather there was little change in soil moisture during the growing season. Greatest changes in the forest were in areas where the trees were concentrated reflecting water uptake and canopy partitioning. Such differences have implications for climate and land use changes; increased forest cover can lead to greater spatial variability, greater growing season temporal variability, and reduced levels of soil moisture, whilst projected decreasing summer precipitation may alter the feedbacks between soil moisture and vegetation water use and increase growing season soil moisture deficits.

Drive by Soil Moisture Measurement: A Citizen Science Project

NASA Astrophysics Data System (ADS)

Senanayake, I. P.; Willgoose, G. R.; Yeo, I. Y.; Hancock, G. R.

2017-12-01

Two of the common attributes of soil moisture are that at any given time it varies quite markedly from point to point, and that there is a significant deterministic pattern that underlies this spatial variation and which is typically 50% of the spatial variability. The spatial variation makes it difficult to determine the time varying catchment average soil moisture using field measurements because any individual measurement is unlikely to be equal to the average for the catchment. The traditional solution to this is to make many measurements (e.g. with soil moisture probes) spread over the catchment, which is very costly and manpower intensive, particularly if we need a time series of soil moisture variation across a catchment. An alternative approach, explored in this poster is to use the deterministic spatial pattern of soil moisture to calibrate one site (e.g. a permanent soil moisture probe at a weather station) to the spatial pattern of soil moisture over the study area. The challenge is then to determine the spatial pattern of soil moisture. This poster will present results from a proof of concept project, where data was collected by a number of undergraduate engineering students, to estimate the spatial pattern. The approach was to drive along a series of roads in a catchment and collect soil moisture measurements at the roadside using field portable soil moisture probes. This drive was repeated a number of times over the semester, and the time variation and spatial persistence of the soil moisture pattern were examined. Provided that the students could return to exactly the same location on each collection day there was a strong persistent pattern in the soil moisture, even while the average soil moisture varied temporally as a result of preceding rainfall. The poster will present results and analysis of the student data, and compare these results with several field sites where we have spatially distributed permanently installed soil moisture probes. The poster will also outline an experimental design, based on our experience, that will underpin a proposed citizen science project involving community environment and farming groups, and high school students.

Responses of ecosystem CO 2 fluxes to short-term experimental warming and nitrogen enrichment in an Alpine meadow, northern Tibet Plateau.

PubMed

Zong, Ning; Shi, Peili; Jiang, Jing; Song, Minghua; Xiong, Dingpeng; Ma, Weiling; Fu, Gang; Zhang, Xianzhou; Shen, Zhenxi

2013-01-01

Over the past decades, the Tibetan Plateau has experienced pronounced warming, yet the extent to which warming will affect alpine ecosystems depends on how warming interacts with other influential global change factors, such as nitrogen (N) deposition. A long-term warming and N manipulation experiment was established to investigate the interactive effects of warming and N deposition on alpine meadow. Open-top chambers were used to simulate warming. N addition, warming, N addition × warming, and a control were set up. In OTCs, daytime air and soil temperature were warmed by 2.0°C and 1.6°C above ambient conditions, but soil moisture was decreased by 4.95 m(3) m(-3). N addition enhanced ecosystem respiration (Reco); nevertheless, warming significantly decreased Reco. The decline of Reco resulting from warming was cancelled out by N addition in late growing season. Our results suggested that N addition enhanced Reco by increasing soil N availability and plant production, whereas warming decreased Reco through lowering soil moisture, soil N supply potential, and suppression of plant activity. Furthermore, season-specific responses of Reco indicated that warming and N deposition caused by future global change may have complicated influence on carbon cycles in alpine ecosystems.

Responses of Ecosystem CO2 Fluxes to Short-Term Experimental Warming and Nitrogen Enrichment in an Alpine Meadow, Northern Tibet Plateau

PubMed Central

Shi, Peili; Jiang, Jing; Song, Minghua; Xiong, Dingpeng; Ma, Weiling; Fu, Gang; Zhang, Xianzhou; Shen, Zhenxi

2013-01-01

Over the past decades, the Tibetan Plateau has experienced pronounced warming, yet the extent to which warming will affect alpine ecosystems depends on how warming interacts with other influential global change factors, such as nitrogen (N) deposition. A long-term warming and N manipulation experiment was established to investigate the interactive effects of warming and N deposition on alpine meadow. Open-top chambers were used to simulate warming. N addition, warming, N addition × warming, and a control were set up. In OTCs, daytime air and soil temperature were warmed by 2.0°C and 1.6°C above ambient conditions, but soil moisture was decreased by 4.95 m3 m−3. N addition enhanced ecosystem respiration (Reco); nevertheless, warming significantly decreased Reco. The decline of Reco resulting from warming was cancelled out by N addition in late growing season. Our results suggested that N addition enhanced Reco by increasing soil N availability and plant production, whereas warming decreased Reco through lowering soil moisture, soil N supply potential, and suppression of plant activity. Furthermore, season-specific responses of Reco indicated that warming and N deposition caused by future global change may have complicated influence on carbon cycles in alpine ecosystems. PMID:24459432

Inter-Comparison of SMAP, SMOS and GCOM-W Soil Moisture Products

NASA Astrophysics Data System (ADS)

Bindlish, R.; Jackson, T. J.; Chan, S.; Burgin, M. S.; Colliander, A.; Cosh, M. H.

2016-12-01

The Soil Moisture Active Passive (SMAP) mission was launched on Jan 31, 2015. The goal of the SMAP mission is to produce soil moisture with accuracy better than 0.04 m3/m3 with a revisit frequency of 2-3 days. The validated standard SMAP passive soil moisture product (L2SMP) with a spatial resolution of 36 km was released in May 2016. Soil moisture observations from in situ sensors are typically used to validate the satellite estimates. But, in situ observations provide ground truth for limited amount of landcover and climatic conditions. Although each mission will have its own issues, observations by other satellite instruments can be play a role in the calibration and validation of SMAP. SMAP, SMOS and GCOM-W missions share some commonnalities because they are currently providing operational brightness temperature and soil moisture products. SMAP and SMOS operate at L-band but GCOM-W uses X-band observations for soil moisture estimation. All these missions use different ancillary data sources, parameterization and algorithm to retrieve soil moisture. Therefore, it is important to validate and to compare the consistency of these products. Soil moisture products from the different missions will be compared with the in situ observations. SMAP soil moisture products will be inter-compared at global scales with SMOS and GCOM-W soil moisture products. The major contribution of satellite product inter-comparison is that it allows the assessment of the quality of the products over wider geographical and climate domains. Rigorous assessment will lead to a more reliable and accurate soil moisture product from all the missions.

Estimating the soil moisture profile by assimilating near-surface observations with the ensemble Kalman filter (EnKF)

NASA Astrophysics Data System (ADS)

Zhang, Shuwen; Li, Haorui; Zhang, Weidong; Qiu, Chongjian; Li, Xin

2005-11-01

The paper investigates the ability to retrieve the true soil moisture profile by assimilating near-surface soil moisture into a soil moisture model with an ensemble Kaiman filter (EnKF) assimilation scheme, including the effect of ensemble size, update interval and nonlinearities in the profile retrieval, the required time for full retrieval of the soil moisture profiles, and the possible influence of the depth of the soil moisture observation. These questions are addressed by a desktop study using synthetic data. The “true” soil moisture profiles are generated from the soil moisture model under the boundary condition of 0.5 cm d-1 evaporation. To test the assimilation schemes, the model is initialized with a poor initial guess of the soil moisture profile, and different ensemble sizes are tested showing that an ensemble of 40 members is enough to represent the covariance of the model forecasts. Also compared are the results with those from the direct insertion assimilation scheme, showing that the EnKF is superior to the direct insertion assimilation scheme, for hourly observations, with retrieval of the soil moisture profile being achieved in 16 h as compared to 12 days or more. For daily observations, the true soil moisture profile is achieved in about 15 days with the EnKF, but it is impossible to approximate the true moisture within 18 days by using direct insertion. It is also found that observation depth does not have a significant effect on profile retrieval time for the EnKF. The nonlinearities have some negative influence on the optimal estimates of soil moisture profile but not very seriously.

Accomplishments of the NASA Johnson Space Center portion of the soil moisture project in fiscal year 1981

NASA Technical Reports Server (NTRS)

Paris, J. F.; Arya, L. M.; Davidson, S. A.; Hildreth, W. W.; Richter, J. C.; Rosenkranz, W. A.

1982-01-01

The NASA/JSC ground scatterometer system was used in a row structure and row direction effects experiment to understand these effects on radar remote sensing of soil moisture. Also, a modification of the scatterometer system was begun and is continuing, to allow cross-polarization experiments to be conducted in fiscal years 1982 and 1983. Preprocessing of the 1978 agricultural soil moisture experiment (ASME) data was completed. Preparations for analysis of the ASME data is fiscal year 1982 were completed. A radar image simulation procedure developed by the University of Kansas is being improved. Profile soil moisture model outputs were compared quantitatively for the same soil and climate conditions. A new model was developed and tested to predict the soil moisture characteristic (water tension versus volumetric soil moisture content) from particle-size distribution and bulk density data. Relationships between surface-zone soil moisture, surface flux, and subsurface moisture conditions are being studied as well as the ways in which measured soil moisture (as obtained from remote sensing) can be used for agricultural applications.

Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen

2016-04-01

Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under different hydrologic conditions and the factors controlling the temporal variability of the ECa-soil moisture relationship. The approach provided valuable insight into the time-varying contribution of local and nonlocal factors to the characteristic spatial patterns of soil moisture and the transition mechanisms. The spatial organization of soil moisture was controlled by different processes in different soil horizons, and the topsoil's moisture did not mirror processes that take place within the soil profile. Results show that, for the Schäfertal hillslope site which is presumed to be representative for non-intensively managed soils with moderate clay content, local soil properties (e.g., soil texture and porosity) are the major control on the spatial pattern of ECa. In contrast, the ECa-soil moisture relationship is small and varies over time indicating that ECa is not a good proxy for soil moisture estimation at the investigated site.Occasionally observed stronger correlations between ECa and soil moisture may be explained by background dependencies of ECa to other state variables such as pore water electrical conductivity. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented sites, as well as to constrain the use of EMI-based ECa data for hydrological applications.

Soil moisture and properties estimation by assimilating soil temperatures using particle batch smoother: A new perspective for DTS

NASA Astrophysics Data System (ADS)

Dong, J.; Steele-Dunne, S. C.; Ochsner, T. E.; Van De Giesen, N.

2015-12-01

Soil moisture, hydraulic and thermal properties are critical for understanding the soil surface energy balance and hydrological processes. Here, we will discuss the potential of using soil temperature observations from Distributed Temperature Sensing (DTS) to investigate the spatial variability of soil moisture and soil properties. With DTS soil temperature can be measured with high resolution (spatial <1m, and temporal < 1min) in cables up to kilometers in length. Soil temperature evolution is primarily controlled by the soil thermal properties, and the energy balance at the soil surface. Hence, soil moisture, which affects both soil thermal properties and the energy that participates the evaporation process, is strongly correlated to the soil temperatures. In addition, the dynamics of the soil moisture is determined by the soil hydraulic properties.Here we will demonstrate that soil moisture, hydraulic and thermal properties can be estimated by assimilating observed soil temperature at shallow depths using the Particle Batch Smoother (PBS). The PBS can be considered as an extension of the particle filter, which allows us to infer soil moisture and soil properties using the dynamics of soil temperature within a batch window. Both synthetic and real field data will be used to demonstrate the robustness of this approach. We will show that the proposed method is shown to be able to handle different sources of uncertainties, which may provide a new view of using DTS observations to estimate sub-meter resolution soil moisture and properties for remote sensing product validation.

Soil Nutrient Depletion Is Associated with the Presence of Burkholderia pseudomallei.

PubMed

Hantrakun, Viriya; Rongkard, Patpong; Oyuchua, Malinee; Amornchai, Premjit; Lim, Cherry; Wuthiekanun, Vanaporn; Day, Nicholas P J; Peacock, Sharon J; Limmathurotsakul, Direk

2016-12-15

Burkholderia pseudomallei is a soil-dwelling bacterium and the cause of melioidosis, which kills an estimated 89,000 people per year worldwide. Agricultural workers are at high risk of infection due to repeated exposure to the bacterium. Little is known about the soil physicochemical properties associated with the presence or absence of the organism. Here, we evaluated the soil physicochemical properties and presence of B. pseudomallei in 6,100 soil samples collected from 61 rice fields in Thailand. The presence of B. pseudomallei was negatively associated with the proportion of clay, proportion of moisture, level of salinity, percentage of organic matter, presence of cadmium, and nutrient levels (phosphorus, potassium, calcium, magnesium, and iron). The presence of B. pseudomallei was not associated with the level of soil acidity (P = 0.54). In a multivariable logistic regression model, the presence of B. pseudomallei was negatively associated with the percentage of organic matter (odds ratio [OR], 0.06; 95% confidence interval [CI], 0.01 to 0.47; P = 0.007), level of salinity (OR, 0.06; 95% CI, 0.01 to 0.74; P = 0.03), and percentage of soil moisture (OR, 0.81; 95% CI, 0.66 to 1.00; P = 0.05). Our study suggests that B. pseudomallei thrives in rice fields that are nutrient depleted. Some agricultural practices result in a decline in soil nutrients, which may impact the presence and amount of B. pseudomallei bacteria in affected areas. Burkholderia pseudomallei is an environmental Gram-negative bacillus and the cause of melioidosis. Humans acquire the disease following skin inoculation, inhalation, or ingestion of the bacterium in the environment. The presence of B. pseudomallei in soil defines geographic regions where humans and livestock are at risk of melioidosis, yet little is known about the soil properties associated with the presence of the organism. We evaluated the soil properties and presence of B. pseudomallei in 61 rice fields in East, Central, and Northeast Thailand. We demonstrated that the organism was more commonly found in soils with lower levels of organic matter and nutrients, including phosphorus, potassium, calcium, magnesium, and iron. We also demonstrated that crop residue burning after harvest, which can reduce soil nutrients, was not uncommon. Some agricultural practices result in a decline in soil nutrients, which may impact the presence and amount of B. pseudomallei bacteria in affected areas. Copyright © 2016 Hantrakun et al.

Evaluation of fine soil moisture data from the IFloodS (NASA GPM) Ground Validation campaign using a fully-distributed ecohydrological model

NASA Astrophysics Data System (ADS)

Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.

2014-12-01

The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.

Remote Sensing Soil Moisture Analysis by Unmanned Aerial Vehicles Digital Imaging

NASA Astrophysics Data System (ADS)

Yeh, C. Y.; Lin, H. R.; Chen, Y. L.; Huang, S. Y.; Wen, J. C.

2017-12-01

In recent years, remote sensing analysis has been able to apply to the research of climate change, environment monitoring, geology, hydro-meteorological, and so on. However, the traditional methods for analyzing wide ranges of surface soil moisture of spatial distribution surveys may require plenty resources besides the high cost. In the past, remote sensing analysis performed soil moisture estimates through shortwave, thermal infrared ray, or infrared satellite, which requires lots of resources, labor, and money. Therefore, the digital image color was used to establish the multiple linear regression model. Finally, we can find out the relationship between surface soil color and soil moisture. In this study, we use the Unmanned Aerial Vehicle (UAV) to take an aerial photo of the fallow farmland. Simultaneously, we take the surface soil sample from 0-5 cm of the surface. The soil will be baking by 110° C and 24 hr. And the software ImageJ 1.48 is applied for the analysis of the digital images and the hue analysis into Red, Green, and Blue (R, G, B) hue values. The correlation analysis is the result from the data obtained from the image hue and the surface soil moisture at each sampling point. After image and soil moisture analysis, we use the R, G, B and soil moisture to establish the multiple regression to estimate the spatial distributions of surface soil moisture. In the result, we compare the real soil moisture and the estimated soil moisture. The coefficient of determination (R2) can achieve 0.5-0.7. The uncertainties in the field test, such as the sun illumination, the sun exposure angle, even the shadow, will affect the result; therefore, R2 can achieve 0.5-0.7 reflects good effect for the in-suit test by using the digital image to estimate the soil moisture. Based on the outcomes of the research, using digital images from UAV to estimate the surface soil moisture is acceptable. However, further investigations need to be collected more than ten days (four times a day) data to verify the relation between the image hue and the soil moisture for reliable moisture estimated model. And it is better to use the digital single lens reflex camera to prevent the deformation of the image and to have a better auto exposure. Keywords: soil, moisture, remote sensing

Effects of shifting seasonal rainfall patterns on net primary productivity and carbon storage in tropical seasonally dry ecosystems

NASA Astrophysics Data System (ADS)

Rohr, T.; Manzoni, S.; Feng, X.; Menezes, R.; Porporato, A. M.

2013-12-01

Although seasonally dry ecosystems (SDEs), identified by prolonged drought followed by a short, but intense, rainy season, cover large regions of the tropics, their biogeochemical response to seasonal rainfall and soil carbon (C) sequestration potential are not well characterized. Both productivity and soil respiration are positively affected by seasonal soil moisture availability, creating a delicate balance between C deposition through litterfall and C losses through heterotrophic respiration. As climate change projections for the tropics predict decreased annual rainfall and increased dry season length, it is critical to understand how variations in seasonal rainfall distributions control this balance. To address this question, we develop a minimal model linking the seasonal behavior of the ensemble soil moisture, plant productivity, the related soil C inputs through litterfall, and soil C dynamics. The model is parameterized for a case study from a drought-deciduous caatinga ecosystem in northeastern Brazil. Results indicate that when altering the seasonal rainfall patterns for a fixed annual rainfall, both plant productivity and soil C sequestration potential are largely, and nonlinearly, dependent on wet season duration. Moreover, total annual rainfall plays a dominant role in describing this relationship, leading at times to the emergence of distinct optima in both primary production and C sequestration. Examining these results in the context of climate-driven changes to wet season duration and mean annual precipitation indicate that the initial hydroclimatic regime of a particular ecosystem is an important factor to predict both the magnitude and direction of the effects of shifting seasonal distributions on productivity and C storage. Although highly productive ecosystems will likely experience declining C storage with predicted climate shifts, those currently operating well below peak production can potentially see improved C stocks with the onset of declining rainfall due to reduced soil respiration. a) Annual average net primary productivity and b) the temporally averaged ensemble soil carbon concentration <(C_yr )> are plotted against the length of the wet season T_W, for six annual rainfall rates (m yr-1).

Examination of Soil Moisture Retrieval Using SIR-C Radar Data and a Distributed Hydrological Model

NASA Technical Reports Server (NTRS)

Hsu, A. Y.; ONeill, P. E.; Wood, E. F.; Zion, M.

1997-01-01

A major objective of soil moisture-related hydrological-research during NASA's SIR-C/X-SAR mission was to determine and compare soil moisture patterns within humid watersheds using SAR data, ground-based measurements, and hydrologic modeling. Currently available soil moisture-inversion methods using active microwave data are only accurate when applied to bare and slightly vegetated surfaces. Moreover, as the surface dries down, the number of pixels that can provide estimated soil moisture by these radar inversion methods decreases, leading to less accuracy and, confidence in the retrieved soil moisture fields at the watershed scale. The impact of these errors in microwave- derived soil moisture on hydrological modeling of vegetated watersheds has yet to be addressed. In this study a coupled water and energy balance model operating within a topographic framework is used to predict surface soil moisture for both bare and vegetated areas. In the first model run, the hydrological model is initialized using a standard baseflow approach, while in the second model run, soil moisture values derived from SIR-C radar data are used for initialization. The results, which compare favorably with ground measurements, demonstrate the utility of combining radar-derived surface soil moisture information with basin-scale hydrological modeling.

Method for evaluating moisture tensions of soils using spectral data

NASA Technical Reports Server (NTRS)

Peterson, John B. (Inventor)

1982-01-01

A method is disclosed which permits evaluation of soil moisture utilizing remote sensing. Spectral measurements at a plurality of different wavelengths are taken with respect to sample soils and the bidirectional reflectance factor (BRF) measurements produced are submitted to regression analysis for development therefrom of predictable equations calculated for orderly relationships. Soil of unknown reflective and unknown soil moisture tension is thereafter analyzed for bidirectional reflectance and the resulting data utilized to determine the soil moisture tension of the soil as well as providing a prediction as to the bidirectional reflectance of the soil at other moisture tensions.

A Methodology for Soil Moisture Retrieval from Land Surface Temperature, Vegetation Index, Topography and Soil Type

NASA Astrophysics Data System (ADS)

Pradhan, N. R.

2015-12-01

Soil moisture conditions have an impact upon hydrological processes, biological and biogeochemical processes, eco-hydrology, floods and droughts due to changing climate, near-surface atmospheric conditions and the partition of incoming solar and long-wave radiation between sensible and latent heat fluxes. Hence, soil moisture conditions virtually effect on all aspects of engineering / military engineering activities such as operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, peaking factor analysis in dam design etc. Like other natural systems, soil moisture pattern can vary from completely disorganized (disordered, random) to highly organized. To understand this varying soil moisture pattern, this research utilized topographic wetness index from digital elevation models (DEM) along with vegetation index from remotely sensed measurements in red and near-infrared bands, as well as land surface temperature (LST) in the thermal infrared bands. This research developed a methodology to relate a combined index from DEM, LST and vegetation index with the physical soil moisture properties of soil types and the degree of saturation. The advantage in using this relationship is twofold: first it retrieves soil moisture content at the scale of soil data resolution even though the derived indexes are in a coarse resolution, and secondly the derived soil moisture distribution represents both organized and disorganized patterns of actual soil moisture. The derived soil moisture is used in driving the hydrological model simulations of runoff, sediment and nutrients.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

NASA Astrophysics Data System (ADS)

Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig

2008-08-01

SummaryThis research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

USGS Publications Warehouse

Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Kvien, Craig

2008-01-01

This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.

Characterization of Soil Moisture Level for Rice and Maize Crops using GSM Shield and Arduino Microcontroller

NASA Astrophysics Data System (ADS)

Gines, G. A.; Bea, J. G.; Palaoag, T. D.

2018-03-01

Soil serves a medium for plants growth. One factor that affects soil moisture is drought. Drought has been a major cause of agricultural disaster. Agricultural drought is said to occur when soil moisture is insufficient to meet crop water requirements, resulting in yield losses. In this research, it aimed to characterize soil moisture level for Rice and Maize Crops using Arduino and applying fuzzy logic. System architecture for soil moisture sensor and water pump were the basis in developing the equipment. The data gathered was characterized by applying fuzzy logic. Based on the results, applying fuzzy logic in validating the characterization of soil moisture level for Rice and Maize crops is accurate as attested by the experts. This will help the farmers in monitoring the soil moisture level of the Rice and Maize crops.

Soil Moisture Memory in Climate Models

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, Max J.; Zukor, Dorothy J. (Technical Monitor)

2000-01-01

Water balance considerations at the soil surface lead to an equation that relates the autocorrelation of soil moisture in climate models to (1) seasonality in the statistics of the atmospheric forcing, (2) the variation of evaporation with soil moisture, (3) the variation of runoff with soil moisture, and (4) persistence in the atmospheric forcing, as perhaps induced by land atmosphere feedback. Geographical variations in the relative strengths of these factors, which can be established through analysis of model diagnostics and which can be validated to a certain extent against observations, lead to geographical variations in simulated soil moisture memory and thus, in effect, to geographical variations in seasonal precipitation predictability associated with soil moisture. The use of the equation to characterize controls on soil moisture memory is demonstrated with data from the modeling system of the NASA Seasonal-to-Interannual Prediction Project.

Soil moisture and vegetation patterns in northern California forests

Treesearch

James R. Griffin

1967-01-01

Twenty-nine soil-vegetation plots were studied in a broad transect across the southern Cascade Range. Variations in soil moisture patterns during the growing season and in soil moisture tension values are discussed. Plot soil moisture values for 40- and 80-cm. depths in August and September are integrated into a soil drought index. Vegetation patterns are described in...

Effect of land-use practice on soil moisture variability for soils covered with dense forest vegetation of Puerto Rico

NASA Technical Reports Server (NTRS)

Tsegaye, T.; Coleman, T.; Senwo, Z.; Shaffer, D.; Zou, X.

1998-01-01

Little is known about the landuse management effect on soil moisture and soil pH distribution on a landscape covered with dense tropical forest vegetation. This study was conducted at three locations where the history of the landuse management is different. Soil moisture was measured using a 6-cm three-rod Time Domain Reflectometery (TDR) probe. Disturbed soil samples were taken from the top 5-cm at the up, mid, and foothill landscape position from the same spots where soil moisture was measured. The results showed that soil moisture varies with landscape position and depth at all three locations. Soil pH and moisture variability were found to be affected by the change in landuse management and landscape position. Soil moisture distribution usually expected to be relatively higher in the foothill (P3) area of these forests than the uphill (P1) position. However, our results indicated that in the Luquillo and Guanica site the surface soil moisture was significantly higher for P1 than P3 position. These suggest that the surface and subsurface drainage in these two sites may have been poor due to the nature of soil formation and type.

A comparison of soil-moisture loss from forested and clearcut areas in West Virginia

Treesearch

Charles A. Troendle

1970-01-01

Soil-moisture losses from forested and clearcut areas were compared on the Fernow Experimental Forest. As expected, hardwood forest soils lost most moisture while revegetated clearcuttings, clearcuttings, and barren areas lost less, in that order. Soil-moisture losses from forested soils also correlated well with evapotranspiration and streamflow.

Spatial-temporal variability of soil moisture and its estimation across scales

NASA Astrophysics Data System (ADS)

Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.

2010-02-01

The soil moisture is a quantity of paramount importance in the study of hydrologic phenomena and soil-atmosphere interaction. Because of its high spatial and temporal variability, the soil moisture monitoring scheme was investigated here both for soil moisture retrieval by remote sensing and in view of the use of soil moisture data in rainfall-runoff modeling. To this end, by using a portable Time Domain Reflectometer, a sequence of 35 measurement days were carried out within a single year in seven fields located inside the Vallaccia catchment, central Italy, with area of 60 km2. Every sampling day, soil moisture measurements were collected at each field over a regular grid with an extension of 2000 m2. The optimization of the monitoring scheme, with the aim of an accurate mean soil moisture estimation at the field and catchment scale, was addressed by the statistical and the temporal stability. At the field scale, the number of required samples (NRS) to estimate the field-mean soil moisture within an accuracy of 2%, necessary for the validation of remotely sensed soil moisture, ranged between 4 and 15 for almost dry conditions (the worst case); at the catchment scale, this number increased to nearly 40 and it refers to almost wet conditions. On the other hand, to estimate the mean soil moisture temporal pattern, useful for rainfall-runoff modeling, the NRS was found to be lower. In fact, at the catchment scale only 10 measurements collected in the most "representative" field, previously determined through the temporal stability analysis, can reproduce the catchment-mean soil moisture with a determination coefficient, R2, higher than 0.96 and a root-mean-square error, RMSE, equal to 2.38%. For the "nonrepresentative" fields the accuracy in terms of RMSE decreased, but similar R2 coefficients were found. This insight can be exploited for the sampling in a generic field when it is sufficient to know an index of soil moisture temporal pattern to be incorporated in conceptual rainfall-runoff models. The obtained results can address the soil moisture monitoring network design from which a reliable soil moisture temporal pattern at the catchment scale can be derived.

Examining diel patterns of soil and xylem moisture using electrical resistivity imaging

NASA Astrophysics Data System (ADS)

Mares, Rachel; Barnard, Holly R.; Mao, Deqiang; Revil, André; Singha, Kamini

2016-05-01

The feedbacks among forest transpiration, soil moisture, and subsurface flowpaths are poorly understood. We investigate how soil moisture is affected by daily transpiration using time-lapse electrical resistivity imaging (ERI) on a highly instrumented ponderosa pine and the surrounding soil throughout the growing season. By comparing sap flow measurements to the ERI data, we find that periods of high sap flow within the diel cycle are aligned with decreases in ground electrical conductivity and soil moisture due to drying of the soil during moisture uptake. As sap flow decreases during the night, the ground conductivity increases as the soil moisture is replenished. The mean and variance of the ground conductivity decreases into the summer dry season, indicating drier soil and smaller diel fluctuations in soil moisture as the summer progresses. Sap flow did not significantly decrease through the summer suggesting use of a water source deeper than 60 cm to maintain transpiration during times of shallow soil moisture depletion. ERI captured spatiotemporal variability of soil moisture on daily and seasonal timescales. ERI data on the tree showed a diel cycle of conductivity, interpreted as changes in water content due to transpiration, but changes in sap flow throughout the season could not be interpreted from ERI inversions alone due to daily temperature changes.

Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring

NASA Astrophysics Data System (ADS)

Crow, W. T.; Bolten, J. D.

2014-12-01

Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Such systems, however, are prone to random error associated with: incorrect process model physics, poor parameter choices and noisy meteorological inputs. The presentation will describe attempts to remediate these sources of error via the assimilation of remotely-sensed surface soil moisture retrievals from satellite-based passive microwave sensors into a global soil water balance model. Results demonstrate the ability of satellite-based soil moisture retrieval products to significantly improve the global characterization of root-zone soil moisture - particularly in data-poor regions lacking adequate ground-based rain gage instrumentation. This success has lead to an on-going effort to implement an operational land data assimilation system at the United States Department of Agriculture's Foreign Agricultural Service (USDA FAS) to globally monitor variations in root-zone soil moisture availability via the integration of satellite-based precipitation and soil moisture information. Prospects for improving the performance of the USDA FAS system via the simultaneous assimilation of both passive and active-based soil moisture retrievals derived from the upcoming NASA Soil Moisture Active/Passive mission will also be discussed.

The Contribution of Soil Moisture Information to Forecast Skill: Two Studies

NASA Technical Reports Server (NTRS)

Koster, Randal

2010-01-01

This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.

Evaluation of Remote Sensing and Hydrological Model Based Soil Moisture Datasets in Drought Perspective

NASA Astrophysics Data System (ADS)

Hüsami Afşar, M.; Bulut, B.; Yilmaz, M. T.

2017-12-01

Soil moisture is one of the fundamental parameters of the environment that plays a major role in carbon, energy, and water cycles. Spatial distribution and temporal changes of soil moisture is one of the important components in climatic, ecological and natural hazards at global, regional and local levels scales. Therefore retrieval of soil moisture datasets has a great importance in these studies. Given soil moisture can be retrieved through different platforms (i.e., in-situ measurements, numerical modeling, and remote sensing) for the same location and time period, it is often desirable to evaluate these different datasets to assign the most accurate estimates for different purposes. During last decades, efforts have been given to provide evaluations about different soil moisture products based on various statistical analysis of the soil moisture time series (i.e., comparison of correlation, bias, and their error standard deviation). On the other hand, there is still need for the comparisons of the soil moisture products in drought analysis context. In this study, LPRM and NOAH Land Surface Model soil moisture datasets are investigated in drought analysis context using station-based watershed average datasets obtained over four USDA ARS watersheds as ground truth. Here, the drought analysis are performed using the standardized soil moisture datasets (i.e., zero mean and one standard deviation) while the droughts are defined as consecutive negative anomalies less than -1 for longer than 3 months duration. Accordingly, the drought characteristics (duration and severity) and false alarm and hit/miss ratios of LPRM and NOAH datasets are validated using station-based datasets as ground truth. Results showed that although the NOAH soil moisture products have better correlations, LPRM based soil moisture retrievals show better consistency in drought analysis. This project is supported by TUBITAK Project number 114Y676.

Is the Pearl River basin, China, drying or wetting? Seasonal variations, causes and implications

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Li, Jianfeng; Gu, Xihui; Shi, Peijun

2018-07-01

Soil moisture plays crucial roles in the hydrological cycle and is also a critical link between land surface and atmosphere. The Pearl River basin (PRb) is climatically subtropical and tropical and is highly sensitive to climate changes. In this study, seasonal soil moisture changes across the PRb were analyzed using the Variable Infiltration Capacity (VIC) model forced by the gridded 0.5° × 0.5° climatic observations. Seasonal changes of soil moisture in both space and time were investigated using the Mann-Kendall trend test method. Potential influencing factors behind seasonal soil moisture changes such as precipitation and temperature were identified using the Maximum Covariance Analysis (MCA) technique. The results indicated that: (1) VIC model performs well in describing changing properties of soil moisture across the PRb; (2) Distinctly different seasonal features of soil moisture can be observed. Soil moisture in spring decreased from east to west parts of the PRb. In summer however, soil moisture was higher in east and west parts but was lower in central parts of the PRb; (3) A significant drying trend was identified over the PRb in autumn, while no significant drying trends can be detected in other seasons; (4) The increase/decrease in precipitation can generally explain the wetting/drying tendency of soil moisture. However, warming temperature contributed significantly to the drying trends and these drying trends were particularly evident during autumn and winter; (5) Significant decreasing precipitation and increasing temperature combined to trigger substantially decreasing soil moisture in autumn. In winter, warming temperature is the major reason behind decreased soil moisture although precipitation is in slightly decreasing tendency. Season variations of soil moisture and related implications for hydro-meteorological processes in the subtropical and tropical river basins over the globe should arouse considerable human concerns.

Data Assimilation using observed streamflow and remotely-sensed soil moisture for improving sub-seasonal-to-seasonal forecasting

NASA Astrophysics Data System (ADS)

Arumugam, S.; Mazrooei, A.; Lakshmi, V.; Wood, A.

2017-12-01

Subseasonal-to-seasonal (S2S) forecasts of soil moisture and streamflow provides critical information for water and agricultural systems to support short-term planning and mangement. This study evaluates the role of observed streamflow and remotely-sensed soil moisture from SMAP (Soil Moisture Active Passive) mission in improving S2S streamflow and soil moisture forecasting using data assimilation (DA). We first show the ability to forecast soil moisture at monthly-to-seaasonal time scale by forcing climate forecasts with NASA's Land Information System and then compares the developed soil moisture forecast with the SMAP data over the Southeast US. Our analyses show significant skill in forecasting real-time soil moisture over 1-3 months using climate information. We also show that the developed soil moisture forecasts capture the observed severe drought conditions (2007-2008) over the Southeast US. Following that, we consider both SMAP data and observed streamflow for improving S2S streamflow and soil moisture forecasts for a pilot study area, Tar River basin, in NC. Towards this, we consider variational assimilation (VAR) of gauge-measured daily streamflow data in improving initial hydrologic conditions of Variable Infiltration Capacity (VIC) model. The utility of data assimilation is then assessed in improving S2S forecasts of streamflow and soil moisture through a retrospective analyses. Furthermore, the optimal frequency of data assimilation and optimal analysis window (number of past observations to use) are also assessed in order to achieve the maximum improvement in S2S forecasts of streamflow and soil moisture. Potential utility of updating initial conditions using DA and providing skillful forcings are also discussed.

Hydrological Storage Length Scales Represented by Remote Sensing Estimates of Soil Moisture and Precipitation

NASA Astrophysics Data System (ADS)

Akbar, Ruzbeh; Short Gianotti, Daniel; McColl, Kaighin A.; Haghighi, Erfan; Salvucci, Guido D.; Entekhabi, Dara

2018-03-01

The soil water content profile is often well correlated with the soil moisture state near the surface. They share mutual information such that analysis of surface-only soil moisture is, at times and in conjunction with precipitation information, reflective of deeper soil fluxes and dynamics. This study examines the characteristic length scale, or effective depth Δz, of a simple active hydrological control volume. The volume is described only by precipitation inputs and soil water dynamics evident in surface-only soil moisture observations. To proceed, first an observation-based technique is presented to estimate the soil moisture loss function based on analysis of soil moisture dry-downs and its successive negative increments. Then, the length scale Δz is obtained via an optimization process wherein the root-mean-squared (RMS) differences between surface soil moisture observations and its predictions based on water balance are minimized. The process is entirely observation-driven. The surface soil moisture estimates are obtained from the NASA Soil Moisture Active Passive (SMAP) mission and precipitation from the gauge-corrected Climate Prediction Center daily global precipitation product. The length scale Δz exhibits a clear east-west gradient across the contiguous United States (CONUS), such that large Δz depths (>200 mm) are estimated in wetter regions with larger mean precipitation. The median Δz across CONUS is 135 mm. The spatial variance of Δz is predominantly explained and influenced by precipitation characteristics. Soil properties, especially texture in the form of sand fraction, as well as the mean soil moisture state have a lesser influence on the length scale.

Variation in microbial activity in histosols and its relationship to soil moisture.

PubMed

Tate, R L; Terry, R E

1980-08-01

Microbial biomass, dehydrogenase activity, carbon metabolism, and aerobic bacterial populations were examined in cropped and fallow Pahokee muck (a lithic medisaprist) of the Florida Everglades. Dehydrogenase activity was two- to sevenfold greater in soil cropped to St. Augustinegrass (Stenotaphrum secundatum (Walt) Kuntz) compared with uncropped soil, whereas biomass ranged from equivalence in the two soils to a threefold stimulation in the cropped soil. Biomass in soil cropped to sugarcane (Saccharum spp. L) approximated that from the grass field, whereas dehydrogenase activities of the cane soil were nearly equivalent to those of the fallow soil. Microbial biomass, dehydrogenase activity, aerobic bacterial populations, and salicylate oxidation rates all correlated with soil moisture levels. These data indicate that within the moisture ranges detected in the surface soils, increased moisture stimulated microbial activity, whereas within the soil profile where moisture ranges reached saturation, increased moisture inhibited aerobic activities and stimulated anaerobic processes.

Variation in Microbial Activity in Histosols and Its Relationship to Soil Moisture †

PubMed Central

Tate, Robert L.; Terry, Richard E.

1980-01-01

Microbial biomass, dehydrogenase activity, carbon metabolism, and aerobic bacterial populations were examined in cropped and fallow Pahokee muck (a lithic medisaprist) of the Florida Everglades. Dehydrogenase activity was two- to sevenfold greater in soil cropped to St. Augustinegrass (Stenotaphrum secundatum (Walt) Kuntz) compared with uncropped soil, whereas biomass ranged from equivalence in the two soils to a threefold stimulation in the cropped soil. Biomass in soil cropped to sugarcane (Saccharum spp. L) approximated that from the grass field, whereas dehydrogenase activities of the cane soil were nearly equivalent to those of the fallow soil. Microbial biomass, dehydrogenase activity, aerobic bacterial populations, and salicylate oxidation rates all correlated with soil moisture levels. These data indicate that within the moisture ranges detected in the surface soils, increased moisture stimulated microbial activity, whereas within the soil profile where moisture ranges reached saturation, increased moisture inhibited aerobic activities and stimulated anaerobic processes. PMID:16345610

Empirical relationships between soil moisture, albedo, and the planetary boundary layer height: a two-layer bucket model approach

NASA Astrophysics Data System (ADS)

Sanchez-Mejia, Z. M.; Papuga, S. A.

2013-12-01

In semiarid regions, where water resources are limited and precipitation dynamics are changing, understanding land surface-atmosphere interactions that regulate the coupled soil moisture-precipitation system is key for resource management and planning. We present a modeling approach to study soil moisture and albedo controls on planetary boundary layer height (PBLh). We used data from the Santa Rita Creosote Ameriflux site and Tucson Airport atmospheric sounding to generate empirical relationships between soil moisture, albedo and PBLh. We developed empirical relationships and show that at least 50% of the variation in PBLh can be explained by soil moisture and albedo. Then, we used a stochastically driven two-layer bucket model of soil moisture dynamics and our empirical relationships to model PBLh. We explored soil moisture dynamics under three different mean annual precipitation regimes: current, increase, and decrease, to evaluate at the influence on soil moisture on land surface-atmospheric processes. While our precipitation regimes are simple, they represent future precipitation regimes that can influence the two soil layers in our conceptual framework. For instance, an increase in annual precipitation, could impact on deep soil moisture and atmospheric processes if precipitation events remain intense. We observed that the response of soil moisture, albedo, and the PBLh will depend not only on changes in annual precipitation, but also on the frequency and intensity of this change. We argue that because albedo and soil moisture data are readily available at multiple temporal and spatial scales, developing empirical relationships that can be used in land surface - atmosphere applications are of great value.

Climate Prediction Center - United States Drought Information

Science.gov Websites

• Crop Moisture Indices • Soil Moisture Percentiles (based on NLDAS) • Standardized Runoff Index (based /Minimum • Mean Surface Hydrology (based on NLDAS) • Total Soil Moisture • Total SM Change • MOSAIC Soil Moisture Profile • NOAH Soil Moisture Profile • NOAH Soil T Profile • Evaporation • E-P Â

An overview of the measurements of soil moisture and modeling of moisture flux in FIFE

NASA Technical Reports Server (NTRS)

Wang, J. R.

1992-01-01

Measurements of soil moisture and calculations of moisture transfer in the soil medium and at the air-soil interface were performed over a 15-km by 15-km test site during FIFE in 1987 and 1989. The measurements included intensive soil moisture sampling at the ground level and surveys at aircraft altitudes by several passive and active microwave sensors as well as a gamma radiation device.

Evaluation of AMSR2 soil moisture products over the contiguous United States using in situ data from the International Soil Moisture Network

NASA Astrophysics Data System (ADS)

Wu, Qiusheng; Liu, Hongxing; Wang, Lei; Deng, Chengbin

2016-03-01

High quality soil moisture datasets are required for various environmental applications. The launch of the Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the Global Change Observation Mission 1-Water (GCOM-W1) in May 2012 has provided global near-surface soil moisture data, with an average revisit frequency of two days. Since AMSR2 is a new passive microwave system in operation, it is very important to evaluate the quality of AMSR2 products before widespread utilization of the data for scientific research. In this paper, we provide a comprehensive evaluation of the AMSR2 soil moisture products retrieved by the Japan Aerospace Exploration Agency (JAXA) algorithm. The evaluation was performed for a three-year period (July 2012-June 2015) over the contiguous United States. The AMSR2 soil moisture products were evaluated by comparing ascending and descending overpass products to each other as well as comparing them to in situ soil moisture observations of 598 monitoring stations obtained from the International Soil Moisture Network (ISMN). The accuracy of AMSR2 soil moisture product was evaluated against several types of monitoring networks, and for different land cover types and ecoregions. Three performance metrics, including mean difference (MD), root mean squared difference (RMSD), and correlation coefficient (R), were used in our accuracy assessment. Our evaluation results revealed that AMSR2 soil moisture retrievals are generally lower than in situ measurements. The AMSR2 soil moisture retrievals showed the best agreement with in situ measurements over the Great Plains and the worst agreement over forested areas. This study offers insights into the suitability and reliability of AMSR2 soil moisture products for different ecoregions. Although AMSR2 soil moisture retrievals represent useful and effective measurements for some regions, further studies are required to improve the data accuracy.

Reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cui, Y.; Long, D.; Hong, Y.; Zeng, C.; Han, Z.

2016-12-01

Reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau Yaokui Cui, Di Long, Yang Hong, Chao Zeng, and Zhongying Han State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China Abstract: Soil moisture is a key variable in the exchange of water and energy between the land surface and the atmosphere, especially over the Tibetan Plateau (TP) which is climatically and hydrologically sensitive as the world's third pole. Large-scale consistent and continuous soil moisture datasets are of importance to meteorological and hydrological applications, such as weather forecasting and drought monitoring. The Fengyun-3B Microwave Radiation Imager (FY-3B/MWRI) soil moisture product is one of relatively new passive microwave products. The FY-3B/MWRI soil moisture product is reconstructed using the back-propagation neural network (BP-NN) based on reconstructed MODIS products, i.e., LST, NDVI, and albedo using different gap-filling methods. The reconstruction method of generating the soil moisture product not only considers the relationship between the soil moisture and the NDVI, LST, and albedo, but also the relationship between the soil moisture and the four-dimensional variation using the longitude, latitude, DEM and day of year (DOY). Results show that the soil moisture could be well reconstructed with R2 larger than 0.63, and RMSE less than 0.1 cm3 cm-3 and bias less than 0.07 cm3 cm-3 for both frozen and unfrozen periods, compared with in-situ measurements in the central TP. The reconstruction method is subsequently applied to generate spatially consistent and temporally continuous surface soil moisture over the TP. The reconstructed FY-3B/MWRI soil moisture product could be valuable in studying meteorology, hydrology, and agriculture over the TP. Keywords: FY-3B/MWRI; Soil moisture; Reconstruction; Tibetan Plateau

An inversion method for retrieving soil moisture information from satellite altimetry observations

NASA Astrophysics Data System (ADS)

Uebbing, Bernd; Forootan, Ehsan; Kusche, Jürgen; Braakmann-Folgmann, Anne

2016-04-01

Soil moisture represents an important component of the terrestrial water cycle that controls., evapotranspiration and vegetation growth. Consequently, knowledge on soil moisture variability is essential to understand the interactions between land and atmosphere. Yet, terrestrial measurements are sparse and their information content is limited due to the large spatial variability of soil moisture. Therefore, over the last two decades, several active and passive radar and satellite missions such as ERS/SCAT, AMSR, SMOS or SMAP have been providing backscatter information that can be used to estimate surface conditions including soil moisture which is proportional to the dielectric constant of the upper (few cm) soil layers . Another source of soil moisture information are satellite radar altimeters, originally designed to measure sea surface height over the oceans. Measurements of Jason-1/2 (Ku- and C-Band) or Envisat (Ku- and S-Band) nadir radar backscatter provide high-resolution along-track information (~ 300m along-track resolution) on backscatter every ~10 days (Jason-1/2) or ~35 days (Envisat). Recent studies found good correlation between backscatter and soil moisture in upper layers, especially in arid and semi-arid regions, indicating the potential of satellite altimetry both to reconstruct and to monitor soil moisture variability. However, measuring soil moisture using altimetry has some drawbacks that include: (1) the noisy behavior of the altimetry-derived backscatter (due to e.g., existence of surface water in the radar foot-print), (2) the strong assumptions for converting altimetry backscatters to the soil moisture storage changes, and (3) the need for interpolating between the tracks. In this study, we suggest a new inversion framework that allows to retrieve soil moisture information from along-track Jason-2 and Envisat satellite altimetry data, and we test this scheme over the Australian arid and semi-arid regions. Our method consists of: (i) deriving time-invariant spatial patterns (base-functions) by applying principal component analysis (PCA) to simulated soil moisture from a large-scale land surface model. (ii) Estimating time-variable soil moisture evolution by fitting these base functions of (i) to the along-track retracked backscatter coefficients in a least squares sense. (iii) Combining the estimated time-variable amplitudes and the pre-computed base-functions, which results in reconstructed (spatio-temporal) soil moisture information. We will show preliminary results that are compared to available high-resolution soil moisture model data over the region (the Australian Water Resource Assessment, AWRA model). We discuss the possibility of using altimetry-derived soil moisture estimations to improve the simulation skill of soil moisture in the Global Land Data Assimilation System (GLDAS) over Australia.

Downscaled soil moisture from SMAP evaluated using high density observations

USDA-ARS?s Scientific Manuscript database

Recently, a soil moisture downscaling algorithm based on a regression relationship between daily temperature changes and daily average soil moisture was developed to produce an enhanced spatial resolution on soil moisture product for the Advanced Microwave Scanning Radiometer–EOS (AMSR-E) satellite ...

Data assimilation to extract soil moisture information from SMAP observations

USDA-ARS?s Scientific Manuscript database

This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP) observations. Neural Network(NN) and physically-based SMAP soil moisture retrievals were assimilated into the NASA Catchment model over the contiguous United Sta...

Soil moisture status estimation over Three Gorges area with Landsat TM data based on temperature vegetation dryness index

NASA Astrophysics Data System (ADS)

Xu, Lina; Niu, Ruiqing; Li, Jiong; Dong, Yanfang

2011-12-01

Soil moisture is the important indicator of climate, hydrology, ecology, agriculture and other parameters of the land surface and atmospheric interface. Soil moisture plays an important role on the water and energy exchange at the land surface/atmosphere interface. Remote sensing can provide information on large area quickly and easily, so it is significant to do research on how to monitor soil moisture by remote sensing. This paper presents a method to assess soil moisture status using Landsat TM data over Three Gorges area in China based on TVDI. The potential of Temperature- Vegetation Dryness Index (TVDI) from Landsat TM data in assessing soil moisture was investigated in this region. After retrieving land surface temperature and vegetation index a TVDI model based on the features of Ts-NDVI space is established. And finally, soil moisture status is estimated according to TVDI. It shows that TVDI has the advantages of stability and high accuracy to estimating the soil moisture status.

Evaluating Land-Atmosphere Interactions with the North American Soil Moisture Database

NASA Astrophysics Data System (ADS)

Giles, S. M.; Quiring, S. M.; Ford, T.; Chavez, N.; Galvan, J.

2015-12-01

The North American Soil Moisture Database (NASMD) is a high-quality observational soil moisture database that was developed to study land-atmosphere interactions. It includes over 1,800 monitoring stations the United States, Canada and Mexico. Soil moisture data are collected from multiple sources, quality controlled and integrated into an online database (soilmoisture.tamu.edu). The period of record varies substantially and only a few of these stations have an observation record extending back into the 1990s. Daily soil moisture observations have been quality controlled using the North American Soil Moisture Database QAQC algorithm. The database is designed to facilitate observationally-driven investigations of land-atmosphere interactions, validation of the accuracy of soil moisture simulations in global land surface models, satellite calibration/validation for SMOS and SMAP, and an improved understanding of how soil moisture influences climate on seasonal to interannual timescales. This paper provides some examples of how the NASMD has been utilized to enhance understanding of land-atmosphere interactions in the U.S. Great Plains.

NASA Giovanni: A Tool for Visualizing, Analyzing, and Inter-Comparing Soil Moisture Data

NASA Technical Reports Server (NTRS)

Teng, William; Rui, Hualan; Vollmer, Bruce; deJeu, Richard; Fang, Fan; Lei, Guang-Dih

2012-01-01

There are many existing satellite soil moisture algorithms and their derived data products, but there is no simple way for a user to inter-compare the products or analyze them together with other related data (e.g., precipitation). An environment that facilitates such inter-comparison and analysis would be useful for validation of satellite soil moisture retrievals against in situ data and for determining the relationships between different soil moisture products. The latter relationships are particularly important for applications users, for whom the continuity of soil moisture data, from whatever source, is critical. A recent example was provided by the sudden demise of EOS Aqua AMSR-E and the end of its soil moisture data production, as well as the end of other soil moisture products that had used the AMSR-E brightness temperature data. The purpose of the current effort is to create an environment, as part of the NASA Giovanni family of portals, that facilitates inter-comparisons of soil moisture algorithms and their derived data products.

Microwave remote sensing and its application to soil moisture detection

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Experimental measurements were utilized to demonstrate a procedure for estimating soil moisture, using a passive microwave sensor. The investigation showed that 1.4 GHz and 10.6 GHz can be used to estimate the average soil moisture within two depths; however, it appeared that a frequency less than 10.6 GHz would be preferable for the surface measurement. Average soil moisture within two depths would provide information on the slope of the soil moisture gradient near the surface. Measurements showed that a uniform surface roughness similar to flat tilled fields reduced the sensitivity of the microwave emission to soil moisture changes. Assuming that the surface roughness was known, the approximate soil moisture estimation accuracy at 1.4 GHz calculated for a 25% average soil moisture and an 80% degree of confidence, was +3% and -6% for a smooth bare surface, +4% and -5% for a medium rough surface, and +5.5% and -6% for a rough surface.

[Biological soil crust nitrogenase activity and its responses to hydro-thermic factors in different erosion regions on the Loess Plateau, China].

PubMed

Ming, Jiao; Zhao, Yun-Ge; Xu, Ming-Xiang; Yang, Li-Na; Wang, Ai-Guo

2013-07-01

Based on field survey, the biological soil crusts at their stable development stage were collected from the water erosion region, water-wind erosion region, and wind erosion region on the Loess Plateau, aimed to study the effects of the variations of moisture and temperature on the crusts nitrogenase activity (NA). The NA of the crusts in the erosion regions decreased in the order of water erosion region (127.7 micromol x m(-2) x h(-1)) > water-wind erosion region (34.6 micromol x m(-2) x h(-1)) > wind erosion region (6.0 micromol x m(-2) x h(-1)), and the optimal temperature for the crust nitrogen fixation was 35 degrees C, 25 degrees C, and 15 degrees C, respectively. At the optimal temperature and 100% -40% field water-holding capacity, the NA of the crusts from the water erosion and water-wind erosion regions had no significant difference. The NA of the crusts from the wind erosion region was more sensitive to the variation of moisture, showing a dramatic decline when the moisture decreased to 80% field water-holding capacity, and totally lost when the moisture decreased to 20% field water-holding capacity. The differences in the NA of the crusts from the three erosion regions and the responses of the NA to the variations of moisture and temperature were likely associated with the climate, environment, and the crust species composition.

Estimating Surface Soil Moisture in Simulated AVIRIS Spectra

NASA Technical Reports Server (NTRS)

Whiting, Michael L.; Li, Lin; Ustin, Susan L.

2004-01-01

Soil albedo is influenced by many physical and chemical constituents, with moisture being the most influential on the spectra general shape and albedo (Stoner and Baumgardner, 1981). Without moisture, the intrinsic or matrix reflectance of dissimilar soils varies widely due to differences in surface roughness, particle and aggregate sizes, mineral types, including salts, and organic matter contents. The influence of moisture on soil reflectance can be isolated by comparing similar soils in a study of the effects that small differences in moisture content have on reflectance. However, without prior knowledge of the soil physical and chemical constituents within every pixel, it is nearly impossible to accurately attribute the reflectance variability in an image to moisture or to differences in the physical and chemical constituents in the soil. The effect of moisture on the spectra must be eliminated to use hyperspectral imagery for determining minerals and organic matter abundances of bare agricultural soils. Accurate soil mineral and organic matter abundance maps from air- and space-borne imagery can improve GIS models for precision farming prescription, and managing irrigation and salinity. Better models of soil moisture and reflectance will also improve the selection of soil endmembers for spectral mixture analysis.

4.4 Development of a 30-Year Soil Moisture Climatology for Situational Awareness and Public Health Applications

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Zavodsky, Bradley T.; White, Kristopher D.; Bell, Jesse E.

2015-01-01

This paper provided a brief background on the work being done at NASA SPoRT and the CDC to create a soil moisture climatology over the CONUS at high spatial resolution, and to provide a valuable source of soil moisture information to the CDC for monitoring conditions that could favor the development of Valley Fever. The soil moisture climatology has multi-faceted applications for both the NOAA/NWS situational awareness in the areas of drought and flooding, and for the Public Health community. SPoRT plans to increase its interaction with the drought monitoring and Public Health communities by enhancing this testbed soil moisture anomaly product. This soil moisture climatology run will also serve as a foundation for upgrading the real-time (currently southeastern CONUS) SPoRT-LIS to a full CONUS domain based on LIS version 7 and incorporating real-time GVF data from the Suomi-NPP Visible Infrared Imaging Radiometer Suite (Vargas et al. 2013) into LIS-Noah. The upgraded SPoRT-LIS run will serve as a testbed proof-of-concept of a higher-resolution NLDAS-2 modeling member. The climatology run will be extended to near real-time using the NLDAS-2 meteorological forcing from 2011 to present. The fixed 1981-2010 climatology shall provide the soil moisture "normals" for the production of real-time soil moisture anomalies. SPoRT also envisions a web-mapping type of service in which an end-user could put in a request for either an historical or real-time soil moisture anomaly graph for a specified county (as exemplified by Figure 2) and/or for local and regional maps of soil moisture proxy percentiles. Finally, SPoRT seeks to assimilate satellite soil moisture data from the current Soil Moisture Ocean Salinity (SMOS; Blankenship et al. 2014) and the recently-launched NASA Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010) missions, using the EnKF capability within LIS. The 9-km combined active radar and passive microwave retrieval product from SMAP (Das et al. 2011) has the potential to provide valuable information about the near-surface soil moisture state for improving land surface modeling output.

Long-Term Evaluation of the AMSR-E Soil Moisture Product Over the Walnut Gulch Watershed, AZ

NASA Astrophysics Data System (ADS)

Bolten, J. D.; Jackson, T. J.; Lakshmi, V.; Cosh, M. H.; Drusch, M.

2005-12-01

The Advanced Microwave Scanning Radiometer -Earth Observing System (AMSR-E) was launched aboard NASA's Aqua satellite on May 4th, 2002. Quantitative estimates of soil moisture using the AMSR-E provided data have required routine radiometric data calibration and validation using comparisons of satellite observations, extended targets and field campaigns. The currently applied NASA EOS Aqua ASMR-E soil moisture algorithm is based on a change detection approach using polarization ratios (PR) of the calibrated AMSR-E channel brightness temperatures. To date, the accuracy of the soil moisture algorithm has been investigated on short time scales during field campaigns such as the Soil Moisture Experiments in 2004 (SMEX04). Results have indicated self-consistency and calibration stability of the observed brightness temperatures; however the performance of the moisture retrieval algorithm has been poor. The primary objective of this study is to evaluate the quality of the current version of the AMSR-E soil moisture product for a three year period over the Walnut Gulch Experimental Watershed (150 km2) near Tombstone, AZ; the northern study area of SMEX04. This watershed is equipped with hourly and daily recording of precipitation, soil moisture and temperature via a network of raingages and a USDA-NRCS Soil Climate Analysis Network (SCAN) site. Surface wetting and drying are easily distinguished in this area due to the moderately-vegetated terrain and seasonally intense precipitation events. Validation of AMSR-E derived soil moisture is performed from June 2002 to June 2005 using watershed averages of precipitation, and soil moisture and temperature data from the SCAN site supported by a surface soil moisture network. Long-term assessment of soil moisture algorithm performance is investigated by comparing temporal variations of moisture estimates with seasonal changes and precipitation events. Further comparisons are made with a standard soil dataset from the European Centre for Medium-Range Weather Forecasts. The results of this research will contribute to a better characterization of the low biases and discrepancies currently observed in the AMSR-E soil moisture product.

Data documentation for the bare soil experiment at the University of Arkansas

NASA Technical Reports Server (NTRS)

Waite, W. P.; Scott, H. D. (Principal Investigator); Hancock, G. D.

1980-01-01

The reflectivities of several controlled moisture test plots were investigated. These test plots were of a similar soil texture which was clay loam and were prepared to give a desired initial soil moisture and density profile. Measurements were conducted on the plots as the soil water redistributed for both long term and diurnal cycles. These measurements included reflectivity, gravimetric and volumetric soil moisture, soil moisture potential, and soil temperature.

Soil moisture dynamics and smoldering combustion limits of pocosin soils in North Carolina, USA

Treesearch

James Reardon; Gary Curcio; Roberta Bartlette

2009-01-01

Smoldering combustion of wetland organic soils in the south-eastern USA is a serious management concern. Previous studies have reported smoldering was sensitive to a wide range of moisture contents, but studies of soil moisture dynamics and changing smoldering combustion potential in wetland communities are limited. Linking soil moisture measurements with estimates of...

The soil moisture active passive experiments (SMAPEx): Towards soil moisture retrieval from the SMAP mission

USDA-ARS?s Scientific Manuscript database

NASA’s Soil Moisture Active Passive (SMAP) mission, scheduled for launch in 2014, will carry the first combined L-band radar and radiometer system with the objective of mapping near surface soil moisture and freeze/thaw state globally at near-daily time step (2-3 days). SMAP will provide three soil ...

Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns

NASA Astrophysics Data System (ADS)

Dong, Jingnuo; Ochsner, Tyson E.

2018-03-01

Soil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (˜1-100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic-ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12-32 km, 13-20 km, and 14-45 km, respectively. Soil moisture was more strongly correlated with sand content (r = -0.536 to -0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.

Sensitivity of Polygonum aviculare Seeds to Light as Affected by Soil Moisture Conditions

PubMed Central

Batlla, Diego; Nicoletta, Marcelo; Benech-Arnold, Roberto

2007-01-01

Background and Aims It has been hypothesized that soil moisture conditions could affect the dormancy status of buried weed seeds, and, consequently, their sensitivity to light stimuli. In this study, an investigation is made of the effect of different soil moisture conditions during cold-induced dormancy loss on changes in the sensitivity of Polygonum aviculare seeds to light. Methods Seeds buried in pots were stored under different constant and fluctuating soil moisture environments at dormancy-releasing temperatures. Seeds were exhumed at regular intervals during storage and were exposed to different light treatments. Changes in the germination response of seeds to light treatments during storage under the different moisture environments were compared in order to determine the effect of soil moisture on the sensitivity to light of P. aviculare seeds. Key Results Seed acquisition of low-fluence responses during dormancy release was not affected by either soil moisture fluctuations or different constant soil moisture contents. On the contrary, different soil moisture environments affected seed acquisition of very low fluence responses and the capacity of seeds to germinate in the dark. Conclusions The results indicate that under field conditions, the sensitivity to light of buried weed seeds could be affected by the soil moisture environment experienced during the dormancy release season, and this could affect their emergence pattern. PMID:17430979

Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

NASA Technical Reports Server (NTRS)

Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.

2013-01-01

Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

Multifrequency remote sensing of soil moisture. [Guymon, Oklahoma and Dalhart, Texas

NASA Technical Reports Server (NTRS)

Theis, S. W.; Mcfarland, M. J.; Rosenthal, W. D.; Jones, C. L. (Principal Investigator)

1982-01-01

Multifrequency sensor data collected at Guymon, Oklahoma and Dalhart, Texas using NASA's C-130 aircraft were used to determine which of the all-weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. In comparison to other active and passive microwave sensors the L-band radiometer (1) was influenced least by ranges in surface roughness; (2) demonstrated the most sensitivity to soil moisture differences in terms of the range of return from the full range of soil moisture; and (3) was less sensitive to errors in measurement in relation to the range of sensor response. L-band emissivity related more strongly to soil moisture when moisture was expressed as percent of field capacity. The perpendicular vegetation index as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture.

Evaluation of soil pH and moisture content on in-situ ozonation of pyrene in soils.

PubMed

Luster-Teasley, S; Ubaka-Blackmoore, N; Masten, S J

2009-08-15

In this study, pyrene spiked soil (300 ppm) was ozonated at pH levels of 2, 6, and 8 and three moisture contents. It was found that soil pH and moisture content impacted the effectiveness of PAH oxidation in unsaturated soils. In air-dried soils, as pH increased, removal increased, such that pyrene removal efficiencies at pH 6 and pH 8 reached 95-97% at a dose of 2.22 mg O(3)/mg pyrene. Ozonation at 16.2+/-0.45 mg O(3)/ppm pyrene in soil resulted in 81-98% removal of pyrene at all pH levels tested. Saturated soils were tested at dry, 5% or 10% moisture conditions. The removal of pyrene was slower in moisturized soils, with the efficiency decreasing as the moisture content increased. Increasing the pH of the soil having a moisture content of 5% resulted in improved pyrene removals. On the contrary, in the soil having a moisture content of 10%, as the pH increased, pyrene removal decreased. Contaminated PAH soils were stored for 6 months to compare the efficiency of PAH removal in freshly contaminated soil and aged soils. PAH adsorption to soil was found to increase with longer exposure times; thus requiring much higher doses of ozone to effectively oxidize pyrene.

Predicting Soil Salinity with Vis–NIR Spectra after Removing the Effects of Soil Moisture Using External Parameter Orthogonalization

PubMed Central

Liu, Ya; Pan, Xianzhang; Wang, Changkun; Li, Yanli; Shi, Rongjie

2015-01-01

Robust models for predicting soil salinity that use visible and near-infrared (vis–NIR) reflectance spectroscopy are needed to better quantify soil salinity in agricultural fields. Currently available models are not sufficiently robust for variable soil moisture contents. Thus, we used external parameter orthogonalization (EPO), which effectively projects spectra onto the subspace orthogonal to unwanted variation, to remove the variations caused by an external factor, e.g., the influences of soil moisture on spectral reflectance. In this study, 570 spectra between 380 and 2400 nm were obtained from soils with various soil moisture contents and salt concentrations in the laboratory; 3 soil types × 10 salt concentrations × 19 soil moisture levels were used. To examine the effectiveness of EPO, we compared the partial least squares regression (PLSR) results established from spectra with and without EPO correction. The EPO method effectively removed the effects of moisture, and the accuracy and robustness of the soil salt contents (SSCs) prediction model, which was built using the EPO-corrected spectra under various soil moisture conditions, were significantly improved relative to the spectra without EPO correction. This study contributes to the removal of soil moisture effects from soil salinity estimations when using vis–NIR reflectance spectroscopy and can assist others in quantifying soil salinity in the future. PMID:26468645

Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture

NASA Astrophysics Data System (ADS)

Martens, B.; Miralles, D.; Lievens, H.; Fernández-Prieto, D.; Verhoest, N. E. C.

2016-06-01

Terrestrial evaporation is an essential variable in the climate system that links the water, energy and carbon cycles over land. Despite this crucial importance, it remains one of the most uncertain components of the hydrological cycle, mainly due to known difficulties to model the constraints imposed by land water availability on terrestrial evaporation. The main objective of this study is to assimilate satellite soil moisture observations from the Soil Moisture and Ocean Salinity (SMOS) mission into an existing evaporation model. Our over-arching goal is to find an optimal use of satellite soil moisture that can help to improve our understanding of evaporation at continental scales. To this end, the Global Land Evaporation Amsterdam Model (GLEAM) is used to simulate evaporation fields over continental Australia for the period September 2010-December 2013. SMOS soil moisture observations are assimilated using a Newtonian Nudging algorithm in a series of experiments. Model estimates of surface soil moisture and evaporation are validated against soil moisture probe and eddy-covariance measurements, respectively. Finally, an analogous experiment in which Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture is assimilated (instead of SMOS) allows to perform a relative assessment of the quality of both satellite soil moisture products. Results indicate that the modelled soil moisture from GLEAM can be improved through the assimilation of SMOS soil moisture: the average correlation coefficient between in situ measurements and the modelled soil moisture over the complete sample of stations increased from 0.68 to 0.71 and a statistical significant increase in the correlations is achieved for 17 out of the 25 individual stations. Our results also suggest a higher accuracy of the ascending SMOS data compared to the descending data, and overall higher quality of SMOS compared to AMSR-E retrievals over Australia. On the other hand, the effect of soil moisture data assimilation on the evaporation fields is very mild, and difficult to assess due to the limited availability of eddy-covariance data. Nonetheless, our continental-scale simulations indicate that the assimilation of soil moisture can have a substantial impact on the estimated dynamics of evaporation in water-limited regimes. Progressing towards our goal of using satellite soil moisture to increase understanding of global land evaporation, future research will focus on the global application of this methodology and the consideration of multiple evaporation models.

Spatial variability and its main controlling factors of the permafrost soil-moisture on the northern-slope of Bayan Har Mountains in Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

Cao, W.; Sheng, Y.

2017-12-01

The soil moisture movement is an important carrier of material cycle and energy flow among the various geo-spheres in the cold regions. It is very critical to protect the alpine ecology and hydrologic cycle in Qinghai-Tibet Plateau. Especially, it becomes one of the key problems to reveal the spatial-temporal variability of soil moisture movement and its main influence factors in earth system science. Thus, this research takes the north slope of Bayan Har Mountains in Qinghai-Tibet Plateau as a case study. The present study firstly investigates the change of permafrost moisture in different slope positions and depths. Based on this investigation, this article attempts to investigate the spatial variability of permafrost moisture and identifies the key influence factors in different terrain conditions. The method of classification and regression tree (CART) is adopted to identify the main controlling factors influencing the soil moisture movement. And the relationships between soil moisture and environmental factors are revealed by the use of the method of canonical correspondence analysis (CCA). The results show that: 1) the change of the soil moisture on the permafrost slope is divided into 4 stages, including the freezing stability phase, the rapid thawing phase, the thawing stability phase and the fast freezing phase; 2) this greatly enhances the horizontal flow in the freezing period due to the terrain slope and the freezing-thawing process. Vertical migration is the mainly form of the soil moisture movement. It leads to that the soil-moisture content in the up-slope is higher than that in the down-slope. On the contrary, the soil-moisture content in the up-slope is lower than that in the down-slope during the melting period; 3) the main environmental factors which affect the slope-permafrost soil-moisture are elevation, soil texture, soil temperature and vegetation coverage. But there are differences in the impact factors of the soil moisture in different freezing-thawing stages; 4) the main factors that affect the slope-permafrost soil-moisture at the shallow depth of 0-20cm are slope, elevation and vegetation coverage. And the main factors influencing the soil moisture at the middle and lower depth are complex.

Soil moisture observations using L-, C-, and X-band microwave radiometers

NASA Astrophysics Data System (ADS)

Bolten, John Dennis

The purpose of this thesis is to further the current understanding of soil moisture remote sensing under varying conditions using L-, C-, and X-band. Aircraft and satellite instruments are used to investigate the effects of frequency and spatial resolution on soil moisture sensitivity. The specific objectives of the research are to examine multi-scale observed and modeled microwave radiobrightness, evaluate new EOS Aqua Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperature and soil moisture retrievals, and examine future satellite-based technologies for soil moisture sensing. The cycling of Earth's water, energy and carbon is vital to understanding global climate. Over land, these processes are largely dependent on the amount of moisture within the top few centimeters of the soil. However, there are currently no methods available that can accurately characterize Earth's soil moisture layer at the spatial scales or temporal resolutions appropriate for climate modeling. The current work uses ground truth, satellite and aircraft remote sensing data from three large-scale field experiments having different land surface, topographic and climate conditions. A physically-based radiative transfer model is used to simulate the observed aircraft and satellite measurements using spatially and temporally co-located surface parameters. A robust analysis of surface heterogeneity and scaling is possible due to the combination of multiple datasets from a range of microwave frequencies and field conditions. Accurate characterization of spatial and temporal variability of soil moisture during the three field experiments is achieved through sensor calibration and algorithm validation. Comparisons of satellite observations and resampled aircraft observations are made using soil moisture from a Numerical Weather Prediction (NWP) model in order to further demonstrate a soil moisture correlation where point data was unavailable. The influence of vegetation, spatial scaling, and surface heterogeneity on multi-scale soil moisture prediction is presented. This work demonstrates that derived soil moisture using remote sensing provides a better coverage of soil moisture spatial variability than traditional in-situ sensors. Effects of spatial scale were shown to be less significant than frequency on soil moisture sensitivity. Retrievals of soil moisture using the current methods proved inadequate under some conditions; however, this study demonstrates the need for concurrent spaceborne frequencies including L-, C, and X-band.

Incorporating an enzymatic model of effects of temperature, moisture, and substrate supply on soil respiration into an ecosystem model for two forests of northeastern USA

NASA Astrophysics Data System (ADS)

Sihi, Debjani; Davidson, Eric; Chen, Min; Savage, Kathleen; Richardson, Andrew; Keenan, Trevor; Hollinger, David

2017-04-01

Soils represent the largest terrestrial carbon (C) pool, and microbial decomposition of soil organic matter (SOM) to carbon dioxide, also called heterotrophic respiration (Rh), is an important component of the global C cycle. Temperature sensitivity of Rh is often represented with a simple Q10 function in ecosystem models and earth system models (ESMs), sometimes accompanied by an empirical soil moisture modifier. More explicit representation of the effects of soil moisture, substrate supply, and their interactions with temperature has been proposed to disentangle the confounding factors of apparent temperature sensitivity of SOM decomposition and improve performance of ecosystem models and ESMs. The objective of this work was to incorporate into an ecosystem model a more mechanistic, but still parsimonious, model of environmental factors controlling Rh. The Dual Arrhenius and Michaelis-Menten (DAMM) model simulates Rh using Michaelis-Menten, Arrhenius, and diffusion functions. Soil moisture affects Rh and its apparent temperature sensitivity in DAMM by regulating the diffusion of oxygen and soluble carbon substrates to the enzymatic reaction site. However, in its current configuration, DAMM depends on assumptions or inputs from other models regarding soil C inputs. Here we merged the DAMM soil flux model with a parsimonious ecosystem flux model, FöBAAR (Forest Biomass, Assimilation, Allocation and Respiration) by replacing FöBAAR's algorithms for Rh with those of DAMM. Classical root trenching experiments provided data to partition soil CO2 efflux into Rh (trenched plot) and root respiration (untrenched minus trenched plots). We used three years of high-frequency soil flux data from automated soil chambers (trenched and untrenched plots) and landscape-scale ecosystem fluxes from eddy covariance towers from two mid-latitude forests (Harvard Forest, MA and Howland Forest, ME) of northeastern USA to develop and validate the merged model and to quantify the uncertainties in a multiple constraints approach. The optimized DAMM-FöBAAR model better captured the seasonal dynamics of Rh compared to the FöBAAR-only model for the Harvard Forest, as indicated by lower cost functions (model-data mismatch). However, DAMM-FöBAAR showed less improvement over FöBAAR-only for the boreal transition forest at Howland. The frequency of droughts is lower at Howland, due to a shallow water table, resulting in only brief water limitation affecting Rh in some years. At both sites, the declining trend of soil respiration during drought episodes was captured by the DAMM-FöBAAR model, but not the FöBAAR-only model, which simulates Rh using only a Q10 type function. Greater confidence in model prediction resulting from the inclusion of mechanistic simulation of moisture limitation on substrate availability, an emergent property of DAMM, depends on site conditions, climate, and the temporal scale of interest. While the DAMM functions require a few more parameters than a simple Q10 function, we have demonstrated that they can be included in an ecosystem model and reduce the cost function. Moreover, the mechanistic structure of the soil moisture effects using DAMM functions should be more generalizable than other commonly used empirical functions.

Inversion of Farmland Soil Moisture in Large Region Based on Modified Vegetation Index

NASA Astrophysics Data System (ADS)

Wang, J. X.; Yu, B. S.; Zhang, G. Z.; Zhao, G. C.; He, S. D.; Luo, W. R.; Zhang, C. C.

2018-04-01

Soil moisture is an important parameter for agricultural production. Efficient and accurate monitoring of soil moisture is an important link to ensure the safety of agricultural production. Remote sensing technology has been widely used in agricultural moisture monitoring because of its timeliness, cyclicality, dynamic tracking of changes in things, easy access to data, and extensive monitoring. Vegetation index and surface temperature are important parameters for moisture monitoring. Based on NDVI, this paper introduces land surface temperature and average temperature for optimization. This article takes the soil moisture in winter wheat growing area in Henan Province as the research object, dividing Henan Province into three main regions producing winter wheat and dividing the growth period of winter wheat into the early, middle and late stages on the basis of phenological characteristics and regional characteristics. Introducing appropriate correction factor during the corresponding growth period of winter wheat, correcting the vegetation index in the corresponding area, this paper establishes regression models of soil moisture on NDVI and soil moisture on modified NDVI based on correlation analysis and compare models. It shows that modified NDVI is more suitable as a indicator of soil moisture because of the better correlation between soil moisture and modified NDVI and the higher prediction accuracy of the regression model of soil moisture on modified NDVI. The research in this paper has certain reference value for winter wheat farmland management and decision-making.

Multiscale analysis of surface soil moisture dynamics in a mesoscale catchment utilizing an integrated ecohydrological model

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2012-12-01

Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil moisture remained in contrast to the measurements very responsive to precipitation with high soil moisture after precipitation events. This behavior indicates that the soil properties might have changed due to the formation of a surface crust or seal towards the end of the growing season. Spatial soil moisture patterns were investigated using a grid resolution of 150 meter. Spatial autocorrelation was computed on a daily basis using patterns of soil texture as well as transpiration and precipitation indices as co-variables. Spatial patterns of surface soil moisture are mostly determined by the structure of the soil properties (soil type) during winter, early growing season and after harvest of all crops. Later in the growing season, after establishment of a closed canopy the dependence of the soil moisture patterns on soil texture patterns becomes smaller and diminishes quickly after precipitation events, due to differences of the transpiration rate of the different crops. When changing the spatial scale of the analysis, the highest autocorrelation values can be found on a grid cell size between 450 and 1200 meters. Thus, small scale variability of transpiration induced by the land use pattern almost averages out, leaving the larger scale structure of soil properties to explain the soil moisture patterns.

Developing Soil Moisture Profiles Utilizing Remotely Sensed MW and TIR Based SM Estimates Through Principle of Maximum Entropy

NASA Astrophysics Data System (ADS)

Mishra, V.; Cruise, J. F.; Mecikalski, J. R.

2015-12-01

Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Earlier studies show that the principle of maximum entropy (POME) can be utilized to develop vertical soil moisture profiles with accuracy (MAE of about 1% for a monotonically dry profile; nearly 2% for monotonically wet profiles and 3.8% for mixed profiles) with minimum constraints (surface, mean and bottom soil moisture contents). In this study, the constraints for the vertical soil moisture profiles were obtained from remotely sensed data. Low resolution (25 km) MW soil moisture estimates (AMSR-E) were downscaled to 4 km using a soil evaporation efficiency index based disaggregation approach. The downscaled MW soil moisture estimates served as a surface boundary condition, while 4 km resolution TIR based Atmospheric Land Exchange Inverse (ALEXI) estimates provided the required mean root-zone soil moisture content. Bottom soil moisture content is assumed to be a soil dependent constant. Mulit-year (2002-2011) gridded profiles were developed for the southeastern United States using the POME method. The soil moisture profiles were compared to those generated in land surface models (Land Information System (LIS) and an agricultural model DSSAT) along with available NRCS SCAN sites in the study region. The end product, spatial soil moisture profiles, can be assimilated into agricultural and hydrologic models in lieu of precipitation for data scarce regions.Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Previous studies have shown that the principle of maximum entropy (POME) can be utilized with minimal constraints to develop vertical soil moisture profiles with accuracy (MAE = 1% for monotonically dry profiles; MAE = 2% for monotonically wet profiles and MAE = 3.8% for mixed profiles) when compared to laboratory and field data. In this study, vertical soil moisture profiles were developed using the POME model to evaluate an irrigation schedule over a maze field in north central Alabama (USA). The model was validated using both field data and a physically based mathematical model. The results demonstrate that a simple two-constraint entropy model under the assumption of a uniform initial soil moisture distribution can simulate most soil moisture profiles within the field area for 6 different soil types. The results of the irrigation simulation demonstrated that the POME model produced a very efficient irrigation strategy with loss of about 1.9% of the total applied irrigation water. However, areas of fine-textured soil (i.e. silty clay) resulted in plant stress of nearly 30% of the available moisture content due to insufficient water supply on the last day of the drying phase of the irrigation cycle. Overall, the POME approach showed promise as a general strategy to guide irrigation in humid environments, with minimum input requirements.

Drought monitoring with soil moisture active passive (SMAP) measurements

NASA Astrophysics Data System (ADS)

Mishra, Ashok; Vu, Tue; Veettil, Anoop Valiya; Entekhabi, Dara

2017-09-01

Recent launch of space-borne systems to estimate surface soil moisture may expand the capability to map soil moisture deficit and drought with global coverage. In this study, we use Soil Moisture Active Passive (SMAP) soil moisture geophysical retrieval products from passive L-band radiometer to evaluate its applicability to forming agricultural drought indices. Agricultural drought is quantified using the Soil Water Deficit Index (SWDI) based on SMAP and soil properties (field capacity and available water content) information. The soil properties are computed using pedo-transfer function with soil characteristics derived from Harmonized World Soil Database. The SMAP soil moisture product needs to be rescaled to be compatible with the soil parameters derived from the in situ stations. In most locations, the rescaled SMAP information captured the dynamics of in situ soil moisture well and shows the expected lag between accumulations of precipitation and delayed increased in surface soil moisture. However, the SMAP soil moisture itself does not reveal the drought information. Therefore, the SMAP based SWDI (SMAP_SWDI) was computed to improve agriculture drought monitoring by using the latest soil moisture retrieval satellite technology. The formulation of SWDI does not depend on longer data and it will overcome the limited (short) length of SMAP data for agricultural drought studies. The SMAP_SWDI is further compared with in situ Atmospheric Water Deficit (AWD) Index. The comparison shows close agreement between SMAP_SWDI and AWD in drought monitoring over Contiguous United States (CONUS), especially in terms of drought characteristics. The SMAP_SWDI was used to construct drought maps for CONUS and compared with well-known drought indices, such as, AWD, Palmer Z-Index, sc-PDSI and SPEI. Overall the SMAP_SWDI is an effective agricultural drought indicator and it provides continuity and introduces new spatial mapping capability for drought monitoring. As an agricultural drought index, SMAP_SWDI has potential to capture short term moisture information similar to AWD and related drought indices.

National Centers for Environmental Prediction

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) soilm1 0-10cm soil moisture soilm2 10-40cm soil moisture soilm3 40-100cm soil moisture soilm4 100-200cm soil moisture soilt1 0-10cm soil temperature soilt2 10-40cm soil temperature soilt3 40-100cm soil temperature soilt4 100-200cm soil temperature thick700.ptype 850-700mb thickness precipitation type thick850

Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States

NASA Astrophysics Data System (ADS)

Baldwin, D.; Manfreda, S.; Keller, K.; Smithwick, E. A. H.

2017-03-01

Satellite-based near-surface (0-2 cm) soil moisture estimates have global coverage, but do not capture variations of soil moisture in the root zone (up to 100 cm depth) and may be biased with respect to ground-based soil moisture measurements. Here, we present an ensemble Kalman filter (EnKF) hydrologic data assimilation system that predicts bias in satellite soil moisture data to support the physically based Soil Moisture Analytical Relationship (SMAR) infiltration model, which estimates root zone soil moisture with satellite soil moisture data. The SMAR-EnKF model estimates a regional-scale bias parameter using available in situ data. The regional bias parameter is added to satellite soil moisture retrievals before their use in the SMAR model, and the bias parameter is updated continuously over time with the EnKF algorithm. In this study, the SMAR-EnKF assimilates in situ soil moisture at 43 Soil Climate Analysis Network (SCAN) monitoring locations across the conterminous U.S. Multivariate regression models are developed to estimate SMAR parameters using soil physical properties and the moderate resolution imaging spectroradiometer (MODIS) evapotranspiration data product as covariates. SMAR-EnKF root zone soil moisture predictions are in relatively close agreement with in situ observations when using optimal model parameters, with root mean square errors averaging 0.051 [cm3 cm-3] (standard error, s.e. = 0.005). The average root mean square error associated with a 20-fold cross-validation analysis with permuted SMAR parameter regression models increases moderately (0.082 [cm3 cm-3], s.e. = 0.004). The expected regional-scale satellite correction bias is negative in four out of six ecoregions studied (mean = -0.12 [-], s.e. = 0.002), excluding the Great Plains and Eastern Temperate Forests (0.053 [-], s.e. = 0.001). With its capability of estimating regional-scale satellite bias, the SMAR-EnKF system can predict root zone soil moisture over broad extents and has applications in drought predictions and other operational hydrologic modeling purposes.

Toward improving the representation of the water cycle at High Northern Latitudes

NASA Astrophysics Data System (ADS)

Lahoz, William; Svendby, Tove; Hamer, Paul; Blyverket, Jostein; Kristiansen, Jørn; Luijting, Hanneke

2016-04-01

The rapid warming at northern latitude regions in recent decades has resulted in a lengthening of the growing season, greater photosynthetic activity and enhanced carbon sequestration by the ecosystem. These changes are likely to intensify summer droughts, tree mortality and wildfires. A potential major climate change feedback is the release of carbon-bearing compounds from soil thawing. These changes make it important to have information on the land surface (soil moisture and temperature) at high northern latitude regions. The availability of soil moisture measurements from several satellite platforms provides an opportunity to address issues associated with the effects of climate change, e.g., assessing multi-decadal links between increasing temperatures, snow cover, soil moisture variability and vegetation dynamics. The relatively poor information on water cycle parameters for biomes at northern high latitudes make it important that efforts are expended on improving the representation of the water cycle at these latitudes. In a collaboration between NILU and Met Norway, we evaluate the soil moisture observations over Norway from the ESA satellite SMOS (Soil Moisture and Ocean Salinity) using in situ ground based soil moisture measurements, with reference to drought and flood episodes. We will use data assimilation of the quality-controlled SMOS soil moisture observations into a land surface model and a numerical weather prediction model to assess the added value from satellite observations of soil moisture for improving the representation of the water cycle at high northern latitudes. This presentation provides first results from this work. We discuss the evaluation of SMOS soil moisture data (and from other satellites) against ground-based in situ data over Norway; the performance of the SMOS soil moisture data for selected drought and flood conditions over Norway; and the first results from data assimilation experiments with land surface models and numerical weather prediction models. Analyses include information on root zone soil moisture. We provide evidence of the value of satellite soil measurements over Norway, including their fidelity, and their impact at improving the representation of the hydrological cycle over northern high latitudes. We indicate benefits from these results for multi-decadal soil moisture datasets such as that from the ESA CCI for soil moisture.

Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics

NASA Astrophysics Data System (ADS)

Xu, Y.; Wang, L.

2017-12-01

Soil moisture is important for agricultural and hydrological studies. However, ground truth soil moisture data for wide area is difficult to achieve. Microwave remote sensing such as Soil Moisture Active Passive (SMAP) can offer a solution for wide coverage. However, existing global soil moisture products only provide observations at coarse spatial resolutions, which often limit their applications in regional agricultural and hydrological studies. This paper therefore aims to generate fine scale soil moisture information and extend soil moisture spatial availability. A statistical downscaling scheme is presented that incorporates multiple fine scale geoinformation data into the downscaling of coarse scale SMAP data in the absence of ground measurement data. Geoinformation data related to soil moisture patterns including digital elevation model (DEM), land surface temperature (LST), land use and normalized difference vegetation index (NDVI) at a fine scale are used as auxiliary environmental variables for downscaling SMAP data. Generalized additive model (GAM) and regression tree are first conducted to derive statistical relationships between SMAP data and auxiliary geoinformation data at an original coarse scale, and residuals are then downscaled to a finer scale via area-to-point kriging (ATPK) by accounting for the spatial correlation information of the input residuals. The results from standard validation scores as well as the triple collocation (TC) method against soil moisture in-situ measurements show that the downscaling method can significantly improve the spatial details of SMAP soil moisture while maintain the accuracy.

SMERGE: A multi-decadal root-zone soil moisture product for CONUS

NASA Astrophysics Data System (ADS)

Crow, W. T.; Dong, J.; Tobin, K. J.; Torres, R.

2017-12-01

Multi-decadal root-zone soil moisture products are of value for a range of water resource and climate applications. The NASA-funded root-zone soil moisture merging project (SMERGE) seeks to develop such products through the optimal merging of land surface model predictions with surface soil moisture retrievals acquired from multi-sensor remote sensing products. This presentation will describe the creation and validation of a daily, multi-decadal (1979-2015), vertically-integrated (both surface to 40 cm and surface to 100 cm), 0.125-degree root-zone product over the contiguous United States (CONUS). The modeling backbone of the system is based on hourly root-zone soil moisture simulations generated by the Noah model (v3.2) operating within the North American Land Data Assimilation System (NLDAS-2). Remotely-sensed surface soil moisture retrievals are taken from the multi-sensor European Space Agency Climate Change Initiative soil moisture data set (ESA CCI SM). In particular, the talk will detail: 1) the exponential smoothing approach used to convert surface ESA CCI SM retrievals into root-zone soil moisture estimates, 2) the averaging technique applied to merge (temporally-sporadic) remotely-sensed with (continuous) NLDAS-2 land surface model estimates of root-zone soil moisture into the unified SMERGE product, and 3) the validation of the SMERGE product using long-term, ground-based soil moisture datasets available within CONUS.

Global response of the growing season to soil moisture and topography

NASA Astrophysics Data System (ADS)

Guevara, M.; Arroyo, C.; Warner, D. L.; Equihua, J.; Lule, A. V.; Schwartz, A.; Taufer, M.; Vargas, R.

2017-12-01

Soil moisture has a direct influence in plant productivity. Plant productivity and its greenness can be inferred by remote sensing with higher spatial detail than soil moisture. The objective was to improve the coarse scale of currently available satellite soil moisture estimates and identify areas of strong coupling between the interannual variability soil moisture and the maximum greenness vegetation fraction (MGVF) at the global scale. We modeled, cross-validated and downscaled remotely sensed soil moisture using machine learning and digital terrain analysis across 23 years (1991-2013) of available data. Improving the accuracy (0.69-0.87 % of cross-validated explained variance) and the spatial detail (from 27 to 15km) of satellite soil moisture, we filled temporal gaps of information across vegetated areas where satellite soil moisture does not work properly. We found that 7.57% of global vegetated area shows strong correlation with our downscaled product (R2>0.5, Fig. 1). We found a dominant positive response of vegetation greenness to topography-based soil moisture across water limited environments, however, the tropics and temperate environments of higher latitudes showed a sparse negative response. We conclude that topography can be used to effectively improve the spatial detail of globally available remotely sensed soil moisture, which is convenient to generate unbiased comparisons with global vegetation dynamics, and better inform land and crop modeling efforts.

Integrated method of RS and GPR for monitoring the changes in the soil moisture and groundwater environment due to underground coal mining

NASA Astrophysics Data System (ADS)

Bian, Zhengfu; Lei, Shaogang; Inyang, Hilary I.; Chang, Luqun; Zhang, Richen; Zhou, Chengjun; He, Xiao

2009-03-01

Mining affects the environment in different ways depending on the physical context in which the mining occurs. In mining areas with an arid environment, mining affects plants’ growth by changing the amount of available water. This paper discusses the effects of mining on two important determinants of plant growth—soil moisture and groundwater table (GWT)—which were investigated using an integrated approach involving a field sampling investigation with remote sensing (RS) and ground-penetrating radar (GPR). To calculate and map the distribution of soil moisture for a target area, we initially analyzed four models for regression analysis between soil moisture and apparent thermal inertia and finally selected a linear model for modeling the soil moisture at a depth 10 cm; the relative error of the modeled soil moisture was about 6.3% and correlation coefficient 0.7794. A comparison of mined and unmined areas based on the results of limited field sampling tests or RS monitoring of Landsat 5-thermatic mapping (TM) data indicated that soil moisture did not undergo remarkable changes following mining. This result indicates that mining does not have an effect on soil moisture in the Shendong coal mining area. The coverage of vegetation in 2005 was compared with that in 1995 by means of the normalized difference vegetation index (NDVI) deduced from TM data, and the results showed that the coverage of vegetation in Shendong coal mining area has improved greatly since 1995 because of policy input RMB¥0.4 per ton coal production by Shendong Coal Mining Company. The factor most affected by coal mining was GWT, which dropped from a depth of 35.41 m before mining to a depth of 43.38 m after mining at the Bulianta Coal Mine based on water well measurements. Ground-penetrating radar at frequencies of 25 and 50 MHz revealed that the deepest GWT was at about 43.4 m. There was a weak water linkage between the unsaturated zone and groundwater, and the decline of water table primarily resulted from the well pumping for mining safety rather than the movement of cracking strata. This result is in agreement with the measurements of the water wells. The roots of nine typical plants in the study area were investigated. Populus was found to have the deepest root system with a depth of about 26 m. Based on an assessment of plant growth demands and the effect of mining on environmental factors, we concluded that mining will have less of an effect on plant growth at those sites where the primary GWT depth before mining was deep enough to be unavailable to plants. If the primary GWT was available for plant growth before mining, especially to those plants with deeper roots, mining will have a significant effect on the growth of plants and the mechanism of this effect will include the loss of water to roots and damage to the root system.

Soil Moisture and the Persistence of North American Drought.

NASA Astrophysics Data System (ADS)

Oglesby, Robert J.; Erickson, David J., III

1989-11-01

We describe numerical sensitivity experiments exploring the effects of soil moisture on North American summertime climate using the NCAR CCMI, a 12-layer global atmospheric general circulation model. In particular. the hypothesis that reduced soil moisture may help induce and amplify warm, dry summers over midlatitude continental interiors is examined. Equilibrium climate statistics are computed for the perpetual July model response to imposed soil moisture anomalies over North America between 36° and 49°N. In addition, the persistence of imposed soil moisture anomalies is examined through use of the seasonal cycle mode of operation with use of various initial atmospheric states both equilibrated and nonequilibrated to the initial soil moisture anomaly.The climate statistics generated by thew model simulations resemble in a general way those of the summer of 1988, when extensive heat and drought occurred over much of North America. A reduction in soil moisture in the model leads to an increase in surface temperature, lower surface pressure, increased ridging aloft, and a northward shift of the jet stream. Low-level moisture advection from the Gulf of Mexico is important in determining where persistent soil moisture deficits can be maintained. In seasonal cycle simulations, it lock longer for an initially unequilibrated atmosphere to respond to the imposed soil moisture anomaly, via moisture transport from the Gulf of Mexico, than when initially the atmosphere was in equilibrium with the imposed anomaly., i.e., the initial state was obtained from the appropriate perpetual July simulation. The results demonstrate the important role of soil moisture in prolonging and/or amplifying North American summertime drought.

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. Part 1; Overview

NASA Technical Reports Server (NTRS)

Crosson, William L.; Laymon, Charles A.; Inguva, Ramarao; Schamschula, Marius; Caulfield, John

1998-01-01

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

NASA Astrophysics Data System (ADS)

Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.

2011-02-01

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status January 2011), the ISMN contains data of 16 networks and more than 500 stations located in the North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.

The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

NASA Astrophysics Data System (ADS)

Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Xaver, A.; Gruber, A.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.

2011-05-01

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.

Upscaling sparse ground-based soil moisture observations for the validation of satellite surface soil moisture products

USDA-ARS?s Scientific Manuscript database

The contrast between the point-scale nature of current ground-based soil moisture instrumentation and the footprint resolution (typically >100 square kilometers) of satellites used to retrieve soil moisture poses a significant challenge for the validation of data products from satellite missions suc...

Remote sensing of an agricultural soil moisture network in Walnut Creek, Iowa

USDA-ARS?s Scientific Manuscript database

The calibration and validation of soil moisture remote sensing products is complicated by the logistics of installing a soil moisture network for a long term period in an active landscape. Usually soil moisture sensors are added to existing precipitation networks which have as a singular requiremen...

Evaluation of SMOS soil moisture products over the CanEx-SM10 area

USDA-ARS?s Scientific Manuscript database

The Soil Moisture and Ocean Salinity (SMOS) Earth observation satellite was launched in November 2009 to provide global soil moisture and ocean salinity measurements based on L-Band passive microwave measurements. Since its launch, different versions of SMOS soil moisture products processors have be...

SMOS soil moisture validation with U.S. in situ newworks

USDA-ARS?s Scientific Manuscript database

Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors using a variety of retrieval methods. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. Since it is a new sensor u...

Potential of bias correction for downscaling passive microwave and soil moisture data

USDA-ARS?s Scientific Manuscript database

Passive microwave satellites such as SMOS (Soil Moisture and Ocean Salinity) or SMAP (Soil Moisture Active Passive) observe brightness temperature (TB) and retrieve soil moisture at a spatial resolution greater than most hydrological processes. Bias correction is proposed as a simple method to disag...

Validation of SMAP surface soil moisture products with core validation sites

USDA-ARS?s Scientific Manuscript database

The NASA Soil Moisture Active Passive (SMAP) mission has utilized a set of core validation sites as the primary methodology in assessing the soil moisture retrieval algorithm performance. Those sites provide well-calibrated in situ soil moisture measurements within SMAP product grid pixels for diver...

Evaluating soil moisture retrievals from ESA's SMOS and NASA's SMAP brightness temperature datasets

USDA-ARS?s Scientific Manuscript database

Two satellites are currently monitoring surface soil moisture (SM) from L-band observations: SMOS (Soil Moisture and Ocean Salinity), a European Space Agency (ESA) satellite that was launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration...

Estimating error cross-correlations in soil moisture data sets using extended collocation analysis

USDA-ARS?s Scientific Manuscript database

Consistent global soil moisture records are essential for studying the role of hydrologic processes within the larger earth system. Various studies have shown the benefit of assimilating satellite-based soil moisture data into water balance models or merging multi-source soil moisture retrievals int...

Precipitation estimation using L-Band and C-Band soil moisture retrievals

USDA-ARS?s Scientific Manuscript database

An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterome...

Field scale spatiotemporal analysis of surface soil moisture for evaluating point-scale in situ networks

USDA-ARS?s Scientific Manuscript database

Soil moisture is an intrinsic state variable that varies considerably in space and time. From a hydrologic viewpoint, soil moisture controls runoff, infiltration, storage and drainage. Soil moisture determines the partitioning of the incoming radiation between latent and sensible heat fluxes. Althou...

Soil moisture changes in two experimental sites in Eastern Spain. Irrigation versus rainfed orchards under organic farming

NASA Astrophysics Data System (ADS)

Azorin-Molina, Cesar; Vicente-Serrano, Sergio M.; Cerdà, Artemi

2013-04-01

Within the Soil Erosion and Degradation Research Group Experimental Stations, soil moisture is being researched as a key factor of the soil hydrology and soil erosion (Cerdà, 1995; Cerda, 1997; Cerdà 1998). This because under semiarid conditions soil moisture content plays a crucial role for agriculture, forest, groundwater recharge and soil chemistry and scientific improvement is of great interest in agriculture, hydrology and soil sciences. Soil moisture has been seeing as the key factor for plant photosynthesis, respiration and transpiration in orchards (Schneider and Childers, 1941) and plant growth (Veihmeyer and Hendrickson, 1950). Moreover, soil moisture determine the root growth and distribution (Levin et al., 1979) and the soil respiration ( Velerie and Orchard, 1983). Water content is expressed as a ratio, ranging from 0 (dry) to the value of soil porosity at saturation (wet). In this study we present 1-year of soil moisture measurements at two experimental sites in the Valencia region, Eastern Spain: one representing rainfed orchard typical from the Mediterranean mountains (El Teularet-Sierra de Enguera), and a second site corresponding to an irrigated orange crop (Alcoleja). The EC-5 soil moisture smart sensor S-SMC-M005 integrated with the field-proven ECH2O™ Sensor and a 12-bit A/D has been choosen for measuring soil water content providing ±3% accuracy in typical soil conditions. Soil moisture measurements were carried out at 5-minute intervals from January till December 2012. In addition, soil moisture was measured at two depths in each landscape: 2 and 20 cm depth - in order to retrieve a representative vertical cross-section of soil moisture. Readings are provided directly from 0 (dry) to 0.450 m3/m3 (wet) volumetric water content. The soil moisture smart sensor is conected to a HOBO U30 Station - GSM-TCP which also stored 5-minute temperature, relative humidity, dew point, global solar radiation, precipitation, wind speed and wind direction data. These complementary atmospheric measurements will serve to explain the intraannual and vertical variations observed in the soil moisture content in both experimental landscapes. This kind of study is aimed to understand the soil moisture content in two different environments such as irrigated rainfed orchards in a semi-arid region. For instance, these measurements have a direct impact on water availability for crops, plant transpiration and could have practical applications to schedule irrigation. Additionally, soil water content has also implications for erosion processes. Key Words: Water, Agriculture, Irrigation, Eastern Spain, Citrus. Acknowledgements The research projects GL2008-02879/BTE and LEDDRA 243857 supported this research. References Cerdà, A. 1995. Soil moisture regime under simulated rainfall in a three years abandoned field in Southeast Spain. Physics and Chemistry of The Earth, 20 (3-4), 271-279. Cerdà, A. 1997. Seasonal Changes of the Infiltration Rates in a Typical Mediterranean Scrubland on Limestone in Southeast Spain. Journal of Hydrology, 198 (1-4) 198-209 Cerdà, A. 1998. Effect of climate on surface flow along a climatological gradient in Israel. A field rainfall simulation approach. Journal of Arid Environments, 38, 145-159. Levin, I., Assaf, R., and Bravdo, B. 1979. Soil moisture and root distribution in an apple orchard irrigated by tricklers. Plant and Soil, 52, 31-40. Schneider, G. W. And Childers, N.F. 1941. Influence of soil moisture on photosynthesis, respiration and transpiration of apples leaves. Plant Physiol., 16, 565-583. Valerie, A. and Orchard, F.J. Cook. 1983. Relationship between soil respiration and soil moisture. Soil Biology and Biochemistry, 15, 447-453. Veihmeyer, F. J. and Hendrickson, A. H. 1950. Soil Moisture in Relation to Plant Growth. Annual Review of Plant Physiology, 1, 285-304.

Inventory of File gfs.t06z.sfluxgrbf00.grib2

Science.gov Websites

Volumetric Soil Moisture Content [Fraction] 007 0.1-0.4 m below ground SOILW analysis Volumetric Soil Volumetric Soil Moisture Content [Fraction] 068 1-2 m below ground SOILW analysis Volumetric Soil Moisture analysis Temperature [K] 071 0-0.1 m below ground SOILL analysis Liquid Volumetric Soil Moisture (non

Towards soil property retrieval from space: Proof of concept using in situ observations

NASA Astrophysics Data System (ADS)

Bandara, Ranmalee; Walker, Jeffrey P.; Rüdiger, Christoph

2014-05-01

Soil moisture is a key variable that controls the exchange of water and energy fluxes between the land surface and the atmosphere. However, the temporal evolution of soil moisture is neither easy to measure nor monitor at large scales because of its high spatial variability. This is mainly a result of the local variation in soil properties and vegetation cover. Thus, land surface models are normally used to predict the evolution of soil moisture and yet, despite their importance, these models are based on low-resolution soil property information or typical values. Therefore, the availability of more accurate and detailed soil parameter data than are currently available is vital, if regional or global soil moisture predictions are to be made with the accuracy required for environmental applications. The proposed solution is to estimate the soil hydraulic properties via model calibration to remotely sensed soil moisture observation, with in situ observations used as a proxy in this proof of concept study. Consequently, the feasibility is assessed, and the level of accuracy that can be expected determined, for soil hydraulic property estimation of duplex soil profiles in a semi-arid environment using near-surface soil moisture observations under naturally occurring conditions. The retrieved soil hydraulic parameters were then assessed by their reliability to predict the root zone soil moisture using the Joint UK Land Environment Simulator model. When using parameters that were retrieved using soil moisture observations, the root zone soil moisture was predicted to within an accuracy of 0.04 m3/m3, which is an improvement of ∼0.025 m3/m3 on predictions that used published values or pedo-transfer functions.

Soil respiration dynamics in the middle taiga of Central Siberia region

NASA Astrophysics Data System (ADS)

Makhnykina, Anastasia; Prokushkin, Anatoly; Polosukhina, Daria

2017-04-01

A large amount of carbon in soil is released to the atmosphere through soil respiration, which is the main pathway of transferring carbon from terrestrial ecosystems (Comstedt et al., 2011). Considering that boreal forests is a large terrestrial sink (Tans et al., 1990) and represent approximately 11 % of the Earth's total land area (Gower et al., 2001), even a small change in soil respiration could significantly intensify - or mitigate - current atmospheric increases of CO2, with potential feedbacks to climate change. The objectives of the present study are: (a) to study the dynamic of CO2 emission from the soil surface during summer season (from May to October); (b) to identify the reaction of soil respiration to different amount of precipitation as the main limiting factor in the region. The research was located in the pine forests in Central Siberia (60°N, 90°E), Russia. Sample plots were represented by the lichen pine forest, moss pine forest, mixed forest and anthropogenic destroyed area. We used the automated soil CO2 flux system based on the infrared gas analyzer -LI-8100 for measuring the soil efflux. Soil temperature was measured with Soil Temperature Probe Type E in three depths -5, 10, 15 cm. Volumetric soil moisture was measured with Theta Probe Model ML2. The presence and type of ground cover substantially affects the value of soil respiration fluxes. The carbon dioxide emission from the soil surface averaged 5.4 ±2.3 μmol CO2 m-2 s-1. The destroyed area without plant cover demonstrated the lowest soil respiration (0.1-5.6 μmol CO2 m-2 s-1). The lowest soil respiration among forested areas was observed in the feathermoss pine forest. The lichen pine forest was characterized by the intermediate values of soil respiration. The maximum soil respiration values and seasonal fluctuations were obtained in the mixed forest (2.3-29.3 μmol CO2 m-2 s-1). The analysis of relation between soil CO2 efflux and climatic conditions identified the parameters with highest soil efflux rates. The influence of soil temperature on the soil CO2 efflux showed that an increase of soil efflux was observed from 0 °C to 16 °C. The temperature of more than 16 °C led to the inhibition of soil respiration process. The investigation of relationship between soil CO2 efflux and soil moisture revealed that the moisture from 0 to 0.3 m-3m-3 resulted in an increase of soil efflux. The moisture of more than 0.3 m-3m-3 led to the inhibition of soil respiration. Our study suggested that the decline of the rainfall and increase of temperature due to climate change could significantly decrease the CO2 emission from the Siberian boreal forests.

Soil water dynamics during precipitation in genetic horizons of Retisol

NASA Astrophysics Data System (ADS)

Zaleski, Tomasz; Klimek, Mariusz; Kajdas, Bartłomiej

2017-04-01

Retisols derived from silty deposits dominate in the soil cover of the Carpathian Foothills. The hydrophysical properties of these are determined by the grain-size distribution of the parent material and the soil's "primary" properties shaped in the deposition process. The other contributing factors are the soil-forming processes, such as lessivage (leaching of clay particles), and the morphogenetic processes that presently shape the relief. These factors are responsible for the "secondary" differentiation of hydrophysical properties across the soil profile. Both the primary and secondary hydrophysical properties of soils (the rates of water retention, filtration and infiltration, and the moisture distribution over the soil profile) determine their ability to take in rainfall, the amount of rainwater taken in, and the ways of its redistribution. The aims of the study, carried out during 2015, were to investigate the dynamics of soil moisture in genetic horizons of Retisol derived from silty deposits and to recognize how fast and how deep water from precipitation gets into soil horizons. Data of soil moisture were measured using 5TM moisture and temperature sensor and collected by logger Em50 (Decagon Devices USA). Data were captured every 10 minutes from 6 sensors at depths: - 10 cm, 20 cm, 40 cm, 60 cm and 80 cm. Precipitation data come from meteorological station situated 50 m away from the soil profile. Two zones differing in the type of water regime were distinguished in Retisol: an upper zone comprising humic and eluvial horizons, and a lower zone consisting of illuvial and parent material horizons. The upper zone shows smaller retention of water available for plants, and relatively wide fluctuations in moisture content, compared to the lower zone. The lower zone has stable moisture content during the vegetation season, with values around the water field capacity. Large changes in soil moisture were observed while rainfall. These changes depend on the volume of the precipitation and soil moisture before the precipitation. The following changes of moisture in the soil profile during precipitation were distinguished: if soil moisture in upper zone horizons oscillates around field capacity (higher than 0.30 m3ṡm-3) there is an evident increase in soil moisture also in the lower zone horizons. If soil moisture in the upper zone horizons is much lower than the field capacity (less than 0.20 m3ṡm-3), the soil moisture in the lower zone has very little fluctuations. The range of wetting front in the soil profile depends on the volume of the precipitation and soil moisture. The heavier precipitation, the wetting front in soil profile reaches deeper horizons. The wetter the soil is, the faster soil moisture in the deeper genetic horizons increase. This Research was financed by the Ministry of Science and Higher Education of the Republic of Poland, DS No. 3138/KGiOG/2016.

Effect of soil moisture on seasonal variation in indoor radon concentration: modelling and measurements in 326 Finnish houses

PubMed Central

Arvela, H.; Holmgren, O.; Hänninen, P.

2016-01-01

The effect of soil moisture on seasonal variation in soil air and indoor radon is studied. A brief review of the theory of the effect of soil moisture on soil air radon has been presented. The theoretical estimates, together with soil moisture measurements over a period of 10 y, indicate that variation in soil moisture evidently is an important factor affecting the seasonal variation in soil air radon concentration. Partitioning of radon gas between the water and air fractions of soil pores is the main factor increasing soil air radon concentration. On two example test sites, the relative standard deviation of the calculated monthly average soil air radon concentration was 17 and 26 %. Increased soil moisture in autumn and spring, after the snowmelt, increases soil gas radon concentrations by 10–20 %. In February and March, the soil gas radon concentration is in its minimum. Soil temperature is also an important factor. High soil temperature in summer increased the calculated soil gas radon concentration by 14 %, compared with winter values. The monthly indoor radon measurements over period of 1 y in 326 Finnish houses are presented and compared with the modelling results. The model takes into account radon entry, climate and air exchange. The measured radon concentrations in autumn and spring were higher than expected and it can be explained by the seasonal variation in the soil moisture. The variation in soil moisture is a potential factor affecting markedly to the high year-to-year variation in the annual or seasonal average radon concentrations, observed in many radon studies. PMID:25899611

The Impact of Microwave-Derived Surface Soil Moisture on Watershed Hydrological Modeling

NASA Technical Reports Server (NTRS)

ONeill, P. E.; Hsu, A. Y.; Jackson, T. J.; Wood, E. F.; Zion, M.

1997-01-01

The usefulness of incorporating microwave-derived soil moisture information in a semi-distributed hydrological model was demonstrated for the Washita '92 experiment in the Little Washita River watershed in Oklahoma. Initializing the hydrological model with surface soil moisture fields from the ESTAR airborne L-band microwave radiometer on a single wet day at the start of the study period produced more accurate model predictions of soil moisture than a standard hydrological initialization with streamflow data over an eight-day soil moisture drydown.

Retrieving pace in vegetation growth using precipitation and soil moisture

NASA Astrophysics Data System (ADS)

Sohoulande Djebou, D. C.; Singh, V. P.

2013-12-01

The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and NDVI. The analysis is performed by combining both scenes 7 and 8 data. Schematic illustration of the two dimension transinformation entropy approach. T(P,SM;VI) stand for the transinformation contained in the couple soil moisture (SM)/precipitation (P) and explaining vegetation growth (VI).

Hydrology of two slopes in subarctic Yukon, Canada

NASA Astrophysics Data System (ADS)

Carey, Sean K.; Woo, Ming-Ko

1999-11-01

Two subarctic forested slopes in central Wolf Creek basin, Yukon, were studied in 1996-1997 to determine the seasonal pattern of the hydrologic processes. A south-facing slope has a dense aspen forest on silty soils with seasonal frost only and a north-facing slope has open stands of black spruce and an organic layer on top of clay sediments with permafrost. Snowmelt is advanced by approximately one month on the south-facing slope due to greater radiation receipt. Meltwater infiltrates its seasonally frozen soil with low ice content, recharging the soil moisture reservoir but yielding no lateral surface or subsurface flow. Summer evaporation depletes this recharged moisture and any additional rainfall input, at the expense of surface or subsurface flow. The north-facing slope with an ice rich substrate hinders deep percolation. Snow meltwater is impounded within the organic layer to produce surface runoff in rills and gullies, and subsurface flow along pipes and within the matrix of the organic soil. During the summer, most subsurface flows are confined to the organic layer which has hydraulic conductivities orders of magnitudes larger than the underlying boulder-clay. Evaporation on the north-facing slope declines as both the frost table and the water table descend in the summer. A water balance of the two slopes demonstrates that vertical processes of infiltration and evaporation dominate moisture exchanges on the south-facing slope, whereas the retardation of deep drainage by frost and by clayey soil on the permafrost slope promotes a strong lateral flow component, principally within the organic layer. These results have the important implication that permafrost slopes and organic horizons are the principal controls on streamflow generation in subarctic catchments.

The impact of non-isothermal soil moisture transport on evaporation fluxes in a maize cropland

NASA Astrophysics Data System (ADS)

Shao, Wei; Coenders-Gerrits, Miriam; Judge, Jasmeet; Zeng, Yijian; Su, Ye

2018-06-01

The process of evaporation interacts with the soil, which has various comprehensive mechanisms. Multiphase flow models solve air, vapour, water, and heat transport equations to simulate non-isothermal soil moisture transport of both liquid water and vapor flow, but are only applied in non-vegetated soils. For (sparsely) vegetated soils often energy balance models are used, however these lack the detailed information on non-isothermal soil moisture transport. In this study we coupled a multiphase flow model with a two-layer energy balance model to study the impact of non-isothermal soil moisture transport on evaporation fluxes (i.e., interception, transpiration, and soil evaporation) for vegetated soils. The proposed model was implemented at an experimental agricultural site in Florida, US, covering an entire maize-growing season (67 days). As the crops grew, transpiration and interception became gradually dominated, while the fraction of soil evaporation dropped from 100% to less than 20%. The mechanisms of soil evaporation vary depending on the soil moisture content. After precipitation the soil moisture content increased, exfiltration of the liquid water flow could transport sufficient water to sustain evaporation from soil, and the soil vapor transport was not significant. However, after a sufficient dry-down period, the soil moisture content significantly reduced, and the soil vapour flow significantly contributed to the upward moisture transport in topmost soil. A sensitivity analysis found that the simulations of moisture content and temperature at the soil surface varied substantially when including the advective (i.e., advection and mechanical dispersion) vapour transport in simulation, including the mechanism of advective vapour transport decreased soil evaporation rate under wet condition, while vice versa under dry condition. The results showed that the formulation of advective soil vapor transport in a soil-vegetation-atmosphere transfer continuum can affect the simulated evaporation fluxes, especially under dry condition.

Spatial and temporal variability of soil moisture on the field with and without plants*

NASA Astrophysics Data System (ADS)

Usowicz, B.; Marczewski, W.; Usowicz, J. B.

2012-04-01

Spatial and temporal variability of the natural environment is its inherent and unavoidable feature. Every element of the environment is characterized by its own variability. One of the kinds of variability in the natural environment is the variability of the soil environment. To acquire better and deeper knowledge and understanding of the temporal and spatial variability of the physical, chemical and biological features of the soil environment, we should determine the causes that induce a given variability. Relatively stable features of soil include its texture and mineral composition; examples of those variables in time are the soil pH or organic matter content; an example of a feature with strong dynamics is the soil temperature and moisture content. The aim of this study was to identify the variability of soil moisture on the field with and without plants using geostatistical methods. The soil moisture measurements were taken on the object with plant canopy and without plants (as reference). The measurements of soil moisture and meteorological components were taken within the period of April-July. The TDR moisture sensors covered 5 cm soil layers and were installed in the plots in the soil layers of 0-0.05, 0.05-0.1, 0.1-0.15, 0.2-0.25, 0.3-0.35, 0.4-0.45, 0.5-0.55, 0.8-0.85 m. Measurements of soil moisture were taken once a day, in the afternoon hours. For the determination of reciprocal correlation, precipitation data and data from soil moisture measurements with the TDR meter were used. Calculations of reciprocal correlation of precipitation and soil moisture at various depths were made for three objects - spring barley, rye, and bare soil, at the level of significance of p<0.05. No significant reciprocal correlation was found between the precipitation and soil moisture in the soil profile for any of the objects studied. Although the correlation analysis indicates a lack of correlation between the variables under consideration, observation of the soil moisture runs in particular objects and of precipitation distribution shows clearly that rainfall has an effect on the soil moisture. The amount of precipitation water that increased the soil moisture depended on the strength of the rainfall, on the hydrological properties of the soil (primarily the soil density), the status of the plant cover, and surface runoff. Basing on the precipitation distribution and on the soil moisture runs, an attempt was made at finding a temporal and spatial relationship between those variables, employing for the purpose the geostatistical methods which permit time and space to be included in the analysis. The geostatistical parameters determined showed the temporal dependence of moisture distribution in the soil profile, with the autocorrelation radius increasing with increasing depth in the profile. The highest values of the radius were observed in the plots with plant cover below the arable horizon, and the lowest in the arable horizon on the barley and fallow plots. The fractal dimensions showed a clear decrease in values with increasing depth in the plots with plant cover, while in the bare plots they were relatively constant within the soil profile under study. Therefore, they indicated that the temporal distribution of soil moisture within the soil profile in the bare field was more random in character than in the plots with plants. The results obtained and the analyses indicate that the moisture in the soil profile, its variability and determination, are significantly affected by the type and condition of plant canopy. The differentiation in moisture content between the plots studied resulted from different precipitation interception and different intensity of water uptake by the roots. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO-3275.

Ultrasound Algorithm Derivation for Soil Moisture Content Estimation

NASA Technical Reports Server (NTRS)

Belisle, W.R.; Metzl, R.; Choi, J.; Aggarwal, M. D.; Coleman, T.

1997-01-01

Soil moisture content can be estimated by evaluating the velocity at which sound waves travel through a known volume of solid material. This research involved the development of three soil algorithms relating the moisture content to the velocity at which sound waves moved through dry and moist media. Pressure and shear wave propagation equations were used in conjunction with soil property descriptions to derive algorithms appropriate for describing the effects of moisture content variation on the velocity of sound waves in soils with and without complete soil pore water volumes, An elementary algorithm was used to estimate soil moisture contents ranging from 0.08 g/g to 0.5 g/g from sound wave velocities ranging from 526 m/s to 664 m/s. Secondary algorithms were also used to estimate soil moisture content from sound wave velocities through soils with pores that were filled predominantly with air or water.

[Soil moisture dynamics of artificial Caragana microphylla shrubs at different topographical sites in Horqin sandy land].

PubMed

Huang, Gang; Zhao, Xue-yong; Huang, Ying-xin; Su, Yan-gui

2009-03-01

Based on the investigation data of vegetation and soil moisture regime of Caragana microphylla shrubs widely distributed in Horqin sandy land, the spatiotemporal variations of soil moisture regime and soil water storage of artificial sand-fixing C. microphylla shrubs at different topographical sites in the sandy land were studied, and the evapotranspiration was measured by water balance method. The results showed that the soil moisture content of the shrubs was the highest in the lowland of dunes, followed by in the middle, and in the crest of the dunes, and increased with increasing depth. No water stress occurred during the growth season of the shrubs. Soil moisture content of the shrubs was highly related to precipitation event, and the relationship of soil moisture content with precipitation was higher in deep soil layer (50-180 cm) than in shallow soil layer (0-50 cm). The variation coefficient of soil moisture content was also higher in deep layer than in shallow layer. Soil water storage was increasing in the whole growth season of the shrubs, which meant that the accumulation of soil water occurred in this area. The evapotranspiriation of the shrubs occupied above 64% of the precipitation.

An Evaluation of Soil Moisture Retrievals Using Aircraft and Satellite Passive Microwave Observations during SMEX02

NASA Technical Reports Server (NTRS)

Bolten, John D.; Lakshmi, Venkat

2009-01-01

The Soil Moisture Experiments conducted in Iowa in the summer of 2002 (SMEX02) had many remote sensing instruments that were used to study the spatial and temporal variability of soil moisture. The sensors used in this paper (a subset of the suite of sensors) are the AQUA satellite-based AMSR-E (Advanced Microwave Scanning Radiometer- Earth Observing System) and the aircraft-based PSR (Polarimetric Scanning Radiometer). The SMEX02 design focused on the collection of near simultaneous brightness temperature observations from each of these instruments and in situ soil moisture measurements at field- and domain- scale. This methodology provided a basis for a quantitative analysis of the soil moisture remote sensing potential of each instrument using in situ comparisons and retrieved soil moisture estimates through the application of a radiative transfer model. To this end, the two sensors are compared with respect to their estimation of soil moisture.

Rainfall estimation by inverting SMOS soil moisture estimates: a comparison of different methods over Australia

USDA-ARS?s Scientific Manuscript database

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) is used...

Application of triple collocation in ground-based validation of soil moisture active/passive (SMAP) level 2 data products

USDA-ARS?s Scientific Manuscript database

The validation of the soil moisture retrievals from the recently-launched NASA Soil Moisture Active/Passive (SMAP) satellite is important prior to their full public release. Uncertainty in attempts to characterize footprint-scale surface-layer soil moisture using point-scale ground observations has ...

Soil-moisture constants and their variation

Treesearch

Walter M. Broadfoot; Hubert D. Burke

1958-01-01

"Constants" like field capacity, liquid limit, moisture equivalent, and wilting point are used by most students and workers in soil moisture. These constants may be equilibrium points or other values that describe soil moisture. Their values under specific soil and cover conditions have been discussed at length in the literature, but few general analyses and...

Spatio-Temporal Analysis of Surface Soil Moisture in Evaluating Ground Truth Monitoring Sites for Remotely Sensed Observations

USDA-ARS?s Scientific Manuscript database

Soil moisture is an intrinsic state variable that varies considerably in space and time. Although soil moisture is highly variable, repeated measurements of soil moisture at the field or small watershed scale can often reveal certain locations as being temporally stable and representative of the are...

Soil moisture depletion patterns around scattered trees

Treesearch

Robert R. Ziemer

1968-01-01

Soil moisture was measured around an isolated mature sugar pine tree (Pinus lambertiana Dougl.) in the mixed conifer forest type of the north central Sierra Nevada, California, from November 1965 to October 1966. From a sequence of measurements, horizontal and vertical soil moisture profiles were developed. Estimated soil moisture depletion from the 61-foot radius plot...

Evaluation of Ku-Band Sensitivity To Soil Moisture: Soil Moisture Change Detection Over the NAFE06 Study Area

USDA-ARS?s Scientific Manuscript database

A very promising technique for spatial disaggregation of soil moisture is on the combination of radiometer and radar observations. Despite their demonstrated potential for long term large scale monitoring of soil moisture, passive and active have their disadvantages in terms of temporal and spatial ...

Calibration and validation of the COSMOS rover for surface soil moisture

USDA-ARS?s Scientific Manuscript database

The mobile COsmic-ray Soil Moisture Observing System (COSMOS) rover may be useful for validating satellite-based estimates of near surface soil moisture, but the accuracy with which the rover can measure 0-5 cm soil moisture has not been previously determined. Our objectives were to calibrate and va...

Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing

NASA Technical Reports Server (NTRS)

Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi

1998-01-01

Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.

Influence of soil texture, moisture, and surface cracks on the performance of a root-feeding flea beetle, Longitarsus bethae (Coleoptera: Chrysomelidae), a biological control agent for Lantana camara (Verbenaceae).

PubMed

Simelane, David O

2007-06-01

Laboratory studies were conducted to determine the influence of soil texture, moisture and surface cracks on adult preference and survival of the root-feeding flea beetle, Longitarsus bethae Savini and Escalona (Coleoptera: Chrysomelidae), a natural enemy of the weed, Lantana camara L. (Verbenaceae). Adult feeding, oviposition preference, and survival of the immature stages of L. bethae were examined at four soil textures (clayey, silty loam, sandy loam, and sandy soil), three soil moisture levels (low, moderate, and high), and two soil surface conditions (with or without surface cracks). Both soil texture and moisture had no influence on leaf feeding and colonization by adult L. bethae. Soil texture had a significant influence on oviposition, with adults preferring to lay on clayey and sandy soils to silty or sandy loam soils. However, survival to adulthood was significantly higher in clayey soils than in other soil textures. There was a tendency for females to deposit more eggs at greater depth in both clayey and sandy soils than in other soil textures. Although oviposition preference and depth of oviposition were not influenced by soil moisture, survival in moderately moist soils was significantly higher than in other moisture levels. Development of immature stages in high soil moisture levels was significantly slower than in other soil moisture levels. There were no variations in the body size of beetles that emerged from different soil textures and moisture levels. Females laid almost three times more eggs on cracked than on noncracked soils. It is predicted that clayey and moderately moist soils will favor the survival of L. bethae, and under these conditions, damage to the roots is likely to be high. This information will aid in the selection of suitable release sites where L. bethae would be most likely to become established.

Effect of soil moisture on the sorption of trichloroethene vapor to vadose-zone soil at picatinny arsenal, New Jersey

USGS Publications Warehouse

Smith, J.A.; Chiou, C.T.; Kammer, J.A.; Kile, D.E.

1990-01-01

This report presents data on the sorption of trichloroethene (TCE) vapor to vadose-zone soil above a contaminated water-table aquifer at Picatinny Arsenal in Morris County, NJ. To assess the impact of moisture on TCE sorption, batch experiments on the sorption of TCE vapor by the field soil were carried out as a function of relative humidity. The TCE sorption decreases as soil moisture content increases from zero to saturation soil moisture content (the soil moisture content in equilibrium with 100% relative humidity). The moisture content of soil samples collected from the vadose zone was found to be greater than the saturation soil-moisture content, suggesting that adsorption of TCE by the mineral fraction of the vadose-zone soil should be minimal relative to the partition uptake by soil organic matter. Analyses of soil and soil-gas samples collected from the field indicate that the ratio of the concentration of TCE on the vadose-zone soil to its concentration in the soil gas is 1-3 orders of magnitude greater than the ratio predicted by using an assumption of equilibrium conditions. This apparent disequilibrium presumably results from the slow desorption of TCE from the organic matter of the vadose-zone soil relative to the dissipation of TCE vapor from the soil gas.

Assessment of Version 4 of the SMAP Passive Soil Moisture Standard Product

NASA Technical Reports Server (NTRS)

O'neill, P. O.; Chan, S.; Bindlish, R.; Jackson, T.; Colliander, A.; Dunbar, R.; Chen, F.; Piepmeier, Jeffrey R.; Yueh, S.; Entekhabi, D.;

The global distribution and dynamics of surface soil moisture

NASA Astrophysics Data System (ADS)

McColl, Kaighin A.; Alemohammad, Seyed Hamed; Akbar, Ruzbeh; Konings, Alexandra G.; Yueh, Simon; Entekhabi, Dara

2017-01-01

Surface soil moisture has a direct impact on food security, human health and ecosystem function. It also plays a key role in the climate system, and the development and persistence of extreme weather events such as droughts, floods and heatwaves. However, sparse and uneven observations have made it difficult to quantify the global distribution and dynamics of surface soil moisture. Here we introduce a metric of soil moisture memory and use a full year of global observations from NASA's Soil Moisture Active Passive mission to show that surface soil moisture--a storage believed to make up less than 0.001% of the global freshwater budget by volume, and equivalent to an, on average, 8-mm thin layer of water covering all land surfaces--plays a significant role in the water cycle. Specifically, we find that surface soil moisture retains a median 14% of precipitation falling on land after three days. Furthermore, the retained fraction of the surface soil moisture storage after three days is highest over arid regions, and in regions where drainage to groundwater storage is lowest. We conclude that lower groundwater storage in these regions is due not only to lower precipitation, but also to the complex partitioning of the water cycle by the surface soil moisture storage layer at the land surface.

Observations of a two-layer soil moisture influence on surface energy dynamics and planetary boundary layer characteristics in a semiarid shrubland

NASA Astrophysics Data System (ADS)

Sanchez-Mejia, Zulia Mayari; Papuga, Shirley A.

2014-01-01

We present an observational analysis examining soil moisture control on surface energy dynamics and planetary boundary layer characteristics. Understanding soil moisture control on land-atmosphere interactions will become increasingly important as climate change continues to alter water availability. In this study, we analyzed 4 years of data from the Santa Rita Creosote Ameriflux site. We categorized our data independently in two ways: (1) wet or dry seasons and (2) one of the four cases within a two-layer soil moisture framework for the root zone based on the presence or absence of moisture in shallow (0-20 cm) and deep (20-60 cm) soil layers. Using these categorizations, we quantified the soil moisture control on surface energy dynamics and planetary boundary layer characteristics using both average responses and linear regression. Our results highlight the importance of deep soil moisture in land-atmosphere interactions. The presence of deep soil moisture decreased albedo by about 10%, and significant differences were observed in evaporative fraction even in the absence of shallow moisture. The planetary boundary layer height (PBLh) was largest when the whole soil profile was dry, decreasing by about 1 km when the whole profile was wet. Even when shallow moisture was absent but deep moisture was present the PBLh was significantly lower than when the entire profile was dry. The importance of deep moisture is likely site-specific and modulated through vegetation. Therefore, understanding these relationships also provides important insights into feedbacks between vegetation and the hydrologic cycle and their consequent influence on the climate system.

Towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations

NASA Astrophysics Data System (ADS)

Bircher, Simone; Richaume, Philippe; Mahmoodi, Ali; Mialon, Arnaud; Fernandez-Moran, Roberto; Wigneron, Jean-Pierre; Demontoux, François; Jonard, François; Weihermüller, Lutz; Andreasen, Mie; Rautiainen, Kimmo; Ikonen, Jaakko; Schwank, Mike; Drusch, Mattias; Kerr, Yann H.

2017-04-01

From the passive L-band microwave radiometer onboard the Soil Moisture and Ocean Salinity (SMOS) space mission global surface soil moisture data is retrieved every 2 - 3 days. Thus far, the empirical L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer model applied in the SMOS soil moisture retrieval algorithm is exclusively calibrated over test sites in dry and temperate climate zones. Furthermore, the included dielectric mixing model relating soil moisture to relative permittivity accounts only for mineral soils. However, soil moisture monitoring over the higher Northern latitudes is crucial since these regions are especially sensitive to climate change. A considerable positive feedback is expected if thawing of these extremely organic soils supports carbon decomposition and release to the atmosphere. Due to differing structural characteristics and thus varying bound water fractions, the relative permittivity of organic material is lower than that of the most mineral soils at a given water content. This assumption was verified by means of L-band relative permittivity laboratory measurements of organic and mineral substrates from various sites in Denmark, Finland, Scotland and Siberia using a resonant cavity. Based on these data, a simple empirical dielectric model for organic soils was derived and implemented in the SMOS Soil Moisture Level 2 Prototype Processor (SML2PP). Unfortunately, the current SMOS retrieved soil moisture product seems to show unrealistically low values compared to in situ soil moisture data collected from organic surface layers in North America, Europe and the Tibetan Plateau so that the impact of the dielectric model for organic soils cannot really be tested. A simplified SMOS processing scheme yielding higher soil moisture levels has recently been proposed and is presently under investigation. Furthermore, recalibration of the model parameters accounting for vegetation and roughness effects that were thus far only evaluated using the default dielectric model for mineral soils is ongoing for the "organic" L-MEB version. Additionally, in order to decide where a soil moisture retrieval using the "organic" dielectric model should be triggered, information on soil organic matter content in the soil surface layer has to be considered in the retrieval algorithm. For this purpose, SoilGrids (www.soilgrids.org) providing soil organic carbon content (SOCC) in g/kg is under study. A SOCC threshold based on the relation between the SoilGrids' SOCC and the presence of organic soil surface layers (relevant to alter the microwave L-band emissions from the land surface) in the SoilGrids' source soil profile information has to be established. In this communication, we present the current status of the above outlined studies with the objective to advance towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations.

[Detecting the moisture content of forest surface soil based on the microwave remote sensing technology.

PubMed

Li, Ming Ze; Gao, Yuan Ke; Di, Xue Ying; Fan, Wen Yi

2016-03-01

The moisture content of forest surface soil is an important parameter in forest ecosystems. It is practically significant for forest ecosystem related research to use microwave remote sensing technology for rapid and accurate estimation of the moisture content of forest surface soil. With the aid of TDR-300 soil moisture content measuring instrument, the moisture contents of forest surface soils of 120 sample plots at Tahe Forestry Bureau of Daxing'anling region in Heilongjiang Province were measured. Taking the moisture content of forest surface soil as the dependent variable and the polarization decomposition parameters of C band Quad-pol SAR data as independent variables, two types of quantitative estimation models (multilinear regression model and BP-neural network model) for predicting moisture content of forest surface soils were developed. The spatial distribution of moisture content of forest surface soil on the regional scale was then derived with model inversion. Results showed that the model precision was 86.0% and 89.4% with RMSE of 3.0% and 2.7% for the multilinear regression model and the BP-neural network model, respectively. It indicated that the BP-neural network model had a better performance than the multilinear regression model in quantitative estimation of the moisture content of forest surface soil. The spatial distribution of forest surface soil moisture content in the study area was then obtained by using the BP neural network model simulation with the Quad-pol SAR data.

Where did my wifi go? Measuring soil moisture using wifi signal strength

NASA Astrophysics Data System (ADS)

Hut, Rolf; de Jeu, Richard

2015-04-01

Soil moisture is tricky to measure. Currently soil moisture is measured at small footprints using probes and other field devices, or at large footprints using satellites. Promising developments in measuring soil moisture are using fiber optic cables for measurements along a line, or using cosmos rays for field scale measurements. In this demonstration we present a low cost alternative to measure soil moisture at footprints of a few square meters. We use a wifi hotspot and a wifi dongle, both mounted in a cantenna for beam forming. We aim the hotspot on a piece of soil and put the dongle in the path of the reflection. By logging the signal strength of the wifi netwerk, we have a proxy for soil moisture. A first proof of concept is presented.

Modelling of Space-Time Soil Moisture in Savannas and its Relation to Vegetation Patterns

NASA Astrophysics Data System (ADS)

Rodriguez-Iturbe, I.; Mohanty, B.; Chen, Z.

2017-12-01

A physically derived space-time representation of the soil moisture field is presented. It includes the incorporation of a "jitter" process acting over the space-time soil moisture field and accounting for the short distance heterogeneities in topography, soil, and vegetation characteristics. The modelling scheme allows for the representation of spatial random fluctuations of soil moisture at small spatial scales and reproduces quite well the space-time correlation structure of soil moisture from a field study in Oklahoma. It is shown that the islands of soil moisture above different thresholds have sizes which follow power distributions over an extended range of scales. A discussion is provided about the possible links of this feature with the observed power law distributions of the clusters of trees in savannas.

High-Resolution Soil Moisture Retrieval using SMAP-L Band Radiometer and RISAT-C band Radar Data for the Indian Subcontinent

NASA Astrophysics Data System (ADS)

Singh, G.; Das, N. N.; Panda, R. K.; Mohanty, B.; Entekhabi, D.; Bhattacharya, B. K.

2016-12-01

Soil moisture status at high resolution (1-10 km) is vital for hydrological, agricultural and hydro-metrological applications. The NASA Soil Moisture Active Passive (SMAP) mission had potential to provide reliable soil moisture estimate at finer spatial resolutions (3 km and 9 km) at the global extent, but suffered a malfunction of its radar, consequently making the SMAP mission observations only from radiometer that are of coarse spatial resolution. At present, the availability of high-resolution soil moisture product is limited, especially in developing countries like India, which greatly depends on agriculture for sustaining a huge population. Therefore, an attempt has been made in the reported study to combine the C-band synthetic aperture radar (SAR) data from Radar Imaging Satellite (RISAT) of the Indian Space Research Organization (ISRO) with the SMAP mission L-band radiometer data to obtain high-resolution (1 km and 3 km) soil moisture estimates. In this study, a downscaling approach (Active-Passive Algorithm) implemented for the SMAP mission was used to disaggregate the SMAP radiometer brightness temperature (Tb) using the fine resolution SAR backscatter (σ0) from RISAT. The downscaled high-resolution Tb was then subjected to tau-omega model in conjunction with high-resolution ancillary data to retrieve soil moisture at 1 and 3 km scale. The retrieved high-resolution soil moisture estimates were then validated with ground based soil moisture measurement under different hydro-climatic regions of India. Initial results show tremendous potential and reasonable accuracy for the retrieved soil moisture at 1 km and 3 km. It is expected that ISRO will implement this approach to produce high-resolution soil moisture estimates for the Indian subcontinent.

Large-area Soil Moisture Surveys Using a Cosmic-ray Rover: Approaches and Results from Australia

NASA Astrophysics Data System (ADS)

Hawdon, A. A.; McJannet, D. L.; Renzullo, L. J.; Baker, B.; Searle, R.

2017-12-01

Recent improvements in satellite instrumentation has increased the resolution and frequency of soil moisture observations, and this in turn has supported the development of higher resolution land surface process models. Calibration and validation of these products is restricted by the mismatch of scales between remotely sensed and contemporary ground based observations. Although the cosmic ray neutron soil moisture probe can provide estimates soil moisture at a scale useful for the calibration and validation purposes, it is spatially limited to a single, fixed location. This scaling issue has been addressed with the development of mobile soil moisture monitoring systems that utilizes the cosmic ray neutron method, typically referred to as a `rover'. This manuscript describes a project designed to develop approaches for undertaking rover surveys to produce soil moisture estimates at scales comparable to satellite observations and land surface process models. A custom designed, trailer-mounted rover was used to conduct repeat surveys at two scales in the Mallee region of Victoria, Australia. A broad scale survey was conducted at 36 x 36 km covering an area of a standard SMAP pixel and an intensive scale survey was conducted over a 10 x 10 km portion of the broad scale survey, which is at a scale equivalent to that used for national water balance modelling. We will describe the design of the rover, the methods used for converting neutron counts into soil moisture and discuss factors controlling soil moisture variability. We found that the intensive scale rover surveys produced reliable soil moisture estimates at 1 km resolution and the broad scale at 9 km resolution. We conclude that these products are well suited for future analysis of satellite soil moisture retrievals and finer scale soil moisture models.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.

2014-08-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.

Study Variability of Seasonal Soil Moisture in Ensemble of CMIP5 Models Over South Asia During 1950-2005

NASA Astrophysics Data System (ADS)

Fahim, A. M.; Shen, R.; Yue, Z.; Di, W.; Mushtaq Shah, S.

2015-12-01

Moisture in the upper most layer of soil column from 14 different models under Coupled Model Intercomparison Project Phase-5 (CMIP5) project were analyzed for four seasons of the year. Aim of this study was to explore variability in soil moisture over south Asia using multi model ensemble and relationship between summer rainfall and soil moisture for spring and summer season. GLDAS (Global Land Data Assimilation System) dataset set was used for comparing CMIP5 ensemble mean soil moisture in different season. Ensemble mean represents soil moisture well in accordance with the geographical features; prominent arid regions are indicated profoundly. Empirical Orthogonal Function (EOF) analysis was applied to study the variability. First component of EOF explains 17%, 16%, 11% and 11% variability for spring, summer, autumn and winter season respectively. Analysis reveal increasing trend in soil moisture over most parts of Afghanistan, Central and north western parts of Pakistan, northern India and eastern to south eastern parts of China, in spring season. During summer, south western part of India exhibits highest negative trend while rest of the study area show minute trend (increasing or decreasing). In autumn, south west of India is under highest negative loadings. During winter season, north western parts of study area show decreasing trend. Summer rainfall has very week (negative or positive) spatial correlation, with spring soil moisture, while possess higher correlation with summer soil moisture. Our studies have significant contribution to understand complex nature of land - atmosphere interactions, as soil moisture prediction plays an important role in the cycle of sink and source of many air pollutants. Next level of research should be on filling the gaps between accurately measuring the soil moisture using satellite remote sensing and land surface modelling. Impact of soil moisture in tracking down different types of pollutant will also be studied.

Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture

NASA Technical Reports Server (NTRS)

Blanchard, M. B.; Greeley, R.; Goettelman, R.

1974-01-01

Two methods are described which are used to estimate soil moisture remotely using the 0.4- to 14.0 micron wavelength region: (1) measurement of spectral reflectance, and (2) measurement of soil temperature. The reflectance method is based on observations which show that directional reflectance decreases as soil moisture increases for a given material. The soil temperature method is based on observations which show that differences between daytime and nighttime soil temperatures decrease as moisture content increases for a given material. In some circumstances, separate reflectance or temperature measurements yield ambiguous data, in which case these two methods may be combined to obtain a valid soil moisture determination. In this combined approach, reflectance is used to estimate low moisture levels; and thermal inertia (or thermal diffusivity) is used to estimate higher levels. The reflectance method appears promising for surface estimates of soil moisture, whereas the temperature method appears promising for estimates of near-subsurface (0 to 10 cm).

Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture

NASA Technical Reports Server (NTRS)

Blanchard, M. B.; Greeley, R.; Goettelman, R.

1974-01-01

Two methods are used to estimate soil moisture remotely using the 0.4- to 14.0-micron wavelength region: (1) measurement of spectral reflectance, and (2) measurement of soil temperature. The reflectance method is based on observations which show that directional reflectance decreases as soil moisture increases for a given material. The soil temperature method is based on observations which show that differences between daytime and nighttime soil temperatures decrease as moisture content increases for a given material. In some circumstances, separate reflectance or temperature measurements yield ambiguous data, in which case these two methods may be combined to obtain a valid soil moisture determination. In this combined approach, reflectance is used to estimate low moisture levels; and thermal inertia (or thermal diffusivity) is used to estimate higher levels. The reflectance method appears promising for surface estimates of soil moisture, whereas the temperature method appears promising for estimates of near-subsurface (0 to 10 cm).

Contribution of hydraulically lifted deep moisture to the water budget in a Southern California mixed forest

NASA Astrophysics Data System (ADS)

Kitajima, Kuni; Allen, Michael F.; Goulden, Michael L.

2013-12-01

and shrubs growing in California's mountains rely on deep roots to survive the hot and dry Mediterranean climate summer. The shallow montane soil cannot hold enough water to support summer transpiration, and plants must access deeper moisture from the weathered bedrock. We used the HYDRUS-1D model to simulate the moisture flux through the soil-plant continuum in Southern California's San Jacinto Mountains. The mechanisms facilitating deep water access are poorly understood, and it is possible that either or both hydraulic lift and capillary rise contribute to the survival and activity of trees and soil microorganisms. We modified HYDRUS to incorporate hydraulic lift and drove it with meteorological and physiological data. The modeled quantity of water lifted hydraulically ranged from near zero during the wet months to ~28 mm month-1 in midsummer. Likewise, modeled capillary rise was negligible during the winter and averaged ~15 mm month-1 during June through November. Both mechanisms provided water to support evapotranspiration during the dry months. Isotopic measurements of xylem water for eight shrub and tree species confirmed the importance of a deep source of water. Conventional and automated minirhizotron observations showed that fine-root and rhizomorph biomass remained relatively constant year-round, while mycorrhizal hyphae biomass varied markedly, peaking in the wet season and declining by ~70% in the dry season. Model results predict that hydraulic lift and capillary rise play key roles in Southern California's mountains: they support evapotranspiration and photosynthesis during the summer drought; they contribute to the year-round survival of fine roots and soil microorganisms.

Using lagged dependence to identify (de)coupled surface and subsurface soil moisture values

NASA Astrophysics Data System (ADS)

Carranza, Coleen D. U.; van der Ploeg, Martine J.; Torfs, Paul J. J. F.

2018-04-01

Recent advances in radar remote sensing popularized the mapping of surface soil moisture at different spatial scales. Surface soil moisture measurements are used in combination with hydrological models to determine subsurface soil moisture values. However, variability of soil moisture across the soil column is important for estimating depth-integrated values, as decoupling between surface and subsurface can occur. In this study, we employ new methods to investigate the occurrence of (de)coupling between surface and subsurface soil moisture. Using time series datasets, lagged dependence was incorporated in assessing (de)coupling with the idea that surface soil moisture conditions will be reflected at the subsurface after a certain delay. The main approach involves the application of a distributed-lag nonlinear model (DLNM) to simultaneously represent both the functional relation and the lag structure in the time series. The results of an exploratory analysis using residuals from a fitted loess function serve as a posteriori information to determine (de)coupled values. Both methods allow for a range of (de)coupled soil moisture values to be quantified. Results provide new insights into the decoupled range as its occurrence among the sites investigated is not limited to dry conditions.

Energy and Water Fluxes in Heterogeneous Mediterranean Water-limited Ecosystems

NASA Astrophysics Data System (ADS)

Detto, M.; Katul, G.; Mancini, M.

2005-12-01

Research efforts in distributed eco-hydrologic models often fall in one of two categories: prognostic, in which predictions of root-zone soil moisture content and land surface fluxes is required for a projected radiative and precipitation forcing time series, or diagnostic in which the relationship between soil water status and atmospheric water vapor demand is to be derived for the various components of the landscape. The latter relationships are now receiving broad attention in climate change, hydrological, and ecological studies of arid and semi-arid ecosystems. This interest is now a central focus given the recognition that the component latent heat flux sensitivity to soil moisture decline can directly impact plant productivity, carbon and nutrient cycling, and ground water recharge. With projected shifts in precipitation statistics, mainly towards increased desertification, the "stability" of these ecosystems is highly dependent on their ability to uptake water at low soil moisture Here, we determine the relationship between soil water status and atmospheric water vapor demand for patchy landscapes within a semi-arid ecosystems using a combination remote sensing products and field experiments. In particular, we investigate how VIS/NIR measurements, in conjunction with standard micrometeorological data and ground based thermal infrared thermometers, provide "diagnostic" hydrologic relationship between soil water content and potential evapo-transpiration for the various components of the landscape. These experiments were conducted in the Orroli site, situated in the mid-west of Sardinia (Italy) within the Flumendosa river watershed, which is considered one of the most important water supply resources to the island. The landscape is a mixture of Mediterranean patchy vegetation types: trees, including wild olives (/Olea sylvestris/) and cork oaks (/Quercus suber/), different shrubs (/Asparagus acutifolius, Rubus ulmifolius/) and herbaceous species (/Asphodelus microcarpus, Ferula comunis, Scolymus hispanicum/) that are present only during wet seasons. The bare soil is the dominant landcover (~70%) during the summer .

A model of the CO2 exchanges between biosphere and atmosphere in the tundra

NASA Technical Reports Server (NTRS)

Labgaa, Rachid R.; Gautier, Catherine

1992-01-01

A physical model of the soil thermal regime in a permafrost terrain has been developed and validated with soil temperature measurements at Barrow, Alaska. The model calculates daily soil temperatures as a function of depth and average moisture contents of the organic and mineral layers using a set of five climatic variables, i.e., air temperature, precipitation, cloudiness, wind speed, and relative humidity. The model is not only designed to study the impact of climate change on the soil temperature and moisture regime, but also to provide the input to a decomposition and net primary production model. In this context, it is well known that CO2 exchanges between the terrestrial biosphere and the atmosphere are driven by soil temperature through decomposition of soil organic matter and root respiration. However, in tundra ecosystems, net CO2 exchange is extremely sensitive to soil moisture content; therefore it is necessary to predict variations in soil moisture in order to assess the impact of climate change on carbon fluxes. To this end, the present model includes the representation of the soil moisture response to changes in climatic conditions. The results presented in the foregoing demonstrate that large errors in soil temperature and permafrost depth estimates arise from neglecting the dependence of the soil thermal regime on soil moisture contents. Permafrost terrain is an example of a situation where soil moisture and temperature are particularly interrelated: drainage conditions improve when the depth of the permafrost increases; a decrease in soil moisture content leads to a decrease in the latent heat required for the phase transition so that the heat penetrates faster and deeper, and the maximum depth of thaw increases; and as excepted, soil thermal coefficients increase with moisture.

What is the philosophy of modelling soil moisture movement?

NASA Astrophysics Data System (ADS)

Chen, J.; Wu, Y.

2009-12-01

In laboratory, the soil moisture movement in the different soil textures has been analysed. From field investigation, at a spot, the soil moisture movement in the root zone, vadose zone and shallow aquifer has been explored. In addition, on ground slopes, the interflow in the near surface soil layers has been studied. Along the regions near river reaches, the expansion and shrink of the saturated area due to rainfall occurrences have been observed. From those previous explorations regarding soil moisture movement, numerical models to represent this hydrologic process have been developed. However, generally, due to high heterogeneity and stratification of soil in a basin, modelling soil moisture movement is rather challenging. Normally, some empirical equations or artificial manipulation are employed to adjust the soil moisture movement in various numerical models. In this study, we inspect the soil moisture movement equations used in a watershed model, SWAT (Soil and Water Assessment Tool) (Neitsch et al., 2005), to examine the limitations of our knowledge in such a hydrologic process. Then, we adopt the features of a topographic-information based on a hydrologic model, TOPMODEL (Beven and Kirkby, 1979), to enhance the representation of soil moisture movement in SWAT. Basically, the results of the study reveal, to some extent, the philosophy of modelling soil moisture movement in numerical models, which will be presented in the conference. Beven, K.J. and Kirkby, M.J., 1979. A physically based variable contributing area model of basin hydrology. Hydrol. Science Bulletin, 24: 43-69. Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Williams, J.R. and King, K.W., 2005. Soil and Water Assessment Tool Theoretical Documentation, Grassland, soil and research service, Temple, TX.

Exploring the Role of Soil Moisture Conditions for Rainfall Triggered Landslides on Catchment Scale: the case of the Ialomita Sub Carpathians, Romania

NASA Astrophysics Data System (ADS)

Chitu, Zenaida; Bogaard, Thom; Adler, Mary-Jeanne; Steele-Dunne, Susan; Hrachowitz, Markus; Busuioc, Aristita; Sandric, Ionut; Istrate, Alexandru

2014-05-01

Like in many parts of the world, landslides represent in Romania recurrent phenomena that produce numerous damages to the infrastructure every few years. The high frequency of landslide events over the world has resulted to the development of many early warning systems that are based on the definition of rainfall thresholds triggering landslides. In Romania in particular, recent studies exploring the temporal occurrence of landslides have revealed that rainfall represents the most important triggering factor for landslides. The presence of low permeability soils and gentle slope degrees in the Ialomita Subcarpathians of Romania makes that cumulated precipitation over variable time interval and the hydraulic response of the soil plays a key role in landslides triggering. In order to identify the slope responses to rainfall events in this particular area we investigate the variability of soil moisture and its relationship to landslide events in three Subcarpathians catchments (Cricovul Dulce, Bizididel and Vulcana) by combining in situ measurements, satellite-based radiometry and hydrological modelling. For the current study, hourly soil moisture measurements from six soil moisture monitoring stations that are fitted with volumetric soil moisture sensors, temperature soil sensors and rain gauges sensors are used. Pedotransfer functions will be applied in order to infer hydraulic soil properties from soil texture sampled from 50 soil profiles. The information about spatial and temporal variability of soil moisture content will be completed with the Level 2 soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) mission. A time series analysis of soil moisture is planned to be integrated to landslide and rainfall time series in order to determine a preliminary rainfall threshold triggering landslides in Ialomita Subcarpathians.

Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR)

PubMed Central

Wagner, Wolfgang; Pathe, Carsten; Doubkova, Marcela; Sabel, Daniel; Bartsch, Annett; Hasenauer, Stefan; Blöschl, Günter; Scipal, Klaus; Martínez-Fernández, José; Löw, Alexander

2008-01-01

The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments. PMID:27879759

Hydrologic responses to restored wildfire regimes revealed by soil moisture-vegetation relationships

NASA Astrophysics Data System (ADS)

Boisramé, Gabrielle; Thompson, Sally; Stephens, Scott

2018-02-01

Many forested mountain watersheds worldwide evolved with frequent fire, which Twentieth Century fire suppression activities eliminated, resulting in unnaturally dense forests with high water demand. Restoration of pre-suppression forest composition and structure through a variety of management activities could improve forest resilience and water yields. This study explores the potential for "managed wildfire", whereby naturally ignited fires are allowed to burn, to alter the water balance. Interest in this type of managed wildfire is increasing, yet its long-term effects on water balance are uncertain. We use soil moisture as a spatially-distributed hydrologic indicator to assess the influence of vegetation, fire history and landscape position on water availability in the Illilouette Creek Basin in Yosemite National Park. Over 6000 manual surface soil moisture measurements were made over a period of three years, and supplemented with continuous soil moisture measurements over the top 1m of soil in three sites. Random forest and linear mixed effects models showed a dominant effect of vegetation type and history of vegetation change on measured soil moisture. Contemporary and historical vegetation maps were used to upscale the soil moisture observations to the basin and infer soil moisture under fire-suppressed conditions. Little change in basin-averaged soil moisture was inferred due to managed wildfire, but the results indicated that large localized increases in soil moisture had occurred, which could have important impacts on local ecology or downstream flows.

Quantifying the influence of deep soil moisture on ecosystem albedo: The role of vegetation

NASA Astrophysics Data System (ADS)

Sanchez-Mejia, Zulia Mayari; Papuga, Shirley Anne; Swetish, Jessica Blaine; van Leeuwen, Willem Jan Dirk; Szutu, Daphne; Hartfield, Kyle

2014-05-01

As changes in precipitation dynamics continue to alter the water availability in dryland ecosystems, understanding the feedbacks between the vegetation and the hydrologic cycle and their influence on the climate system is critically important. We designed a field campaign to examine the influence of two-layer soil moisture control on bare and canopy albedo dynamics in a semiarid shrubland ecosystem. We conducted this campaign during 2011 and 2012 within the tower footprint of the Santa Rita Creosote Ameriflux site. Albedo field measurements fell into one of four Cases within a two-layer soil moisture framework based on permutations of whether the shallow and deep soil layers were wet or dry. Using these Cases, we identified differences in how shallow and deep soil moisture influence canopy and bare albedo. Then, by varying the number of canopy and bare patches within a gridded framework, we explore the influence of vegetation and soil moisture on ecosystem albedo. Our results highlight the importance of deep soil moisture in land surface-atmosphere interactions through its influence on aboveground vegetation characteristics. For instance, we show how green-up of the vegetation is triggered by deep soil moisture, and link deep soil moisture to a decrease in canopy albedo. Understanding relationships between vegetation and deep soil moisture will provide important insights into feedbacks between the hydrologic cycle and the climate system.

Validation and reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cui, Yaokui; Long, Di; Hong, Yang; Zeng, Chao; Zhou, Jie; Han, Zhongying; Liu, Ronghua; Wan, Wei

2016-12-01

Soil moisture is a key variable in the exchange of water and energy between the land surface and the atmosphere, especially over the Tibetan Plateau (TP) which is climatically and hydrologically sensitive as the Earth's 'third pole'. Large-scale spatially consistent and temporally continuous soil moisture datasets are of great importance to meteorological and hydrological applications, such as weather forecasting and drought monitoring. The Fengyun-3B Microwave Radiation Imager (FY-3B/MWRI) soil moisture product is a relatively new passive microwave product, with the satellite being launched on November 5, 2010. This study validates and reconstructs FY-3B/MWRI soil moisture across the TP. First, the validation is performed using in situ measurements within two in situ soil moisture measurement networks (1° × 1° and 0.25° × 0.25°), and also compared with the Essential Climate Variable (ECV) soil moisture product from multiple active and passive satellite soil moisture products using new merging procedures. Results show that the ascending FY-3B/MWRI product outperforms the descending product. The ascending FY-3B/MWRI product has almost the same correlation as the ECV product with the in situ measurements. The ascending FY-3B/MWRI product has better performance than the ECV product in the frozen season and under the lower NDVI condition. When the NDVI is higher in the unfrozen season, uncertainty in the ascending FY-3B/MWRI product increases with increasing NDVI, but it could still capture the variability in soil moisture. Second, the FY-3B/MWRI soil moisture product is subsequently reconstructed using the back-propagation neural network (BP-NN) based on reconstructed MODIS products, i.e., LST, NDVI, and albedo. The reconstruction method of generating the soil moisture product not only considers the relationship between the soil moisture and NDVI, LST, and albedo, but also the relationship between the soil moisture and four-dimensional variations using the longitude, latitude, DEM and day of year (DOY). Results show that the soil moisture could be well reconstructed with R2 higher than 0.56, RMSE less than 0.1 cm3 cm-3, and Bias less than 0.07 cm3 cm-3 for both frozen and unfrozen seasons, compared with the in situ measurements at the two networks. Third, the reconstruction method is applied to generate surface soil moisture over the TP. Both original and reconstructed FY-3B/MWRI soil moisture products could be valuable in studying meteorology, hydrology, and ecosystems over the TP.

Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grossiord, Charlotte; Sevanto, Sanna Annika; Limousin, Jean -Marc

Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit ( VPD) and soil moisture variations, and the generality of these effects across forest types and environments usingmore » four manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water ( REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Altogether, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.« less

Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use

DOE PAGES

Grossiord, Charlotte; Sevanto, Sanna Annika; Limousin, Jean -Marc; ...

2017-12-14

Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit ( VPD) and soil moisture variations, and the generality of these effects across forest types and environments usingmore » four manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water ( REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Altogether, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.« less

Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grossiord, Charlotte; Sevanto, Sanna; Limousin, Jean-Marc

Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit (VPD) and soil moisture variations, and the generality of these effects across forest types and environments using fourmore » manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water (REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Overall, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.« less

A Citizen Science Soil Moisture Sensor to Support SMAP Calibration/Validation

NASA Astrophysics Data System (ADS)

Podest, E.; Das, N. N.

2016-12-01

The Soil Moisture Active Passive (SMAP) satellite mission was launched in Jan. 2015 and is currently acquiring global measurements of soil moisture in the top 5 cm of the soil every 3 days. SMAP has partnered with the GLOBE program to engage students from around the world to collect in situ soil moisture and help validate SMAP measurements. The current GLOBE SMAP soil moisture protocol consists in collecting a soil sample, weighing, drying and weighing it again in order to determine the amount of water in the soil. Preparation and soil sample collection can take up to 20 minutes and drying can take up to 3 days. We have hence developed a soil moisture measurement device based on Arduino-like microcontrollers along with off-the-shelf and homemade sensors that are accurate, robust, inexpensive and quick and easy to use so that they can be implemented by the GLOBE community and citizen scientists alike. This talk will discuss building, calibration and validation of the soil moisture measuring device and assessing the quality of the measurements collected. This work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

Observing and modeling links between soil moisture, microbes and CH4 fluxes from forest soils

NASA Astrophysics Data System (ADS)

Christiansen, Jesper; Levy-Booth, David; Barker, Jason; Prescott, Cindy; Grayston, Sue

2017-04-01

Soil moisture is a key driver of methane (CH4) fluxes in forest soils, both of the net uptake of atmospheric CH4 and emission from the soil. Climate and land use change will alter spatial patterns of soil moisture as well as temporal variability impacting the net CH4 exchange. The impact on the resultant net CH4 exchange however is linked to the underlying spatial and temporal distribution of the soil microbial communities involved in CH4 cycling as well as the response of the soil microbial community to environmental changes. Significant progress has been made to target specific CH4 consuming and producing soil organisms, which is invaluable in order to understand the microbial regulation of the CH4 cycle in forest soils. However, it is not clear as to which extent soil moisture shapes the structure, function and abundance of CH4 specific microorganisms and how this is linked to observed net CH4 exchange under contrasting soil moisture regimes. Here we report on the results from a research project aiming to understand how the CH4 net exchange is shaped by the interactive effects soil moisture and the spatial distribution CH4 consuming (methanotrophs) and producing (methanogens). We studied the growing season variations of in situ CH4 fluxes, microbial gene abundances of methanotrophs and methanogens, soil hydrology, and nutrient availability in three typical forest types across a soil moisture gradient in a temperate rainforest on the Canadian Pacific coast. Furthermore, we conducted laboratory experiments to determine whether the net CH4 exchange from hydrologically contrasting forest soils responded differently to changes in soil moisture. Lastly, we modelled the microbial mediation of net CH4 exchange along the soil moisture gradient using structural equation modeling. Our study shows that it is possible to link spatial patterns of in situ net exchange of CH4 to microbial abundance of CH4 consuming and producing organisms. We also show that the microbial community responds different to environmental change dependent on the soil moisture regime. These results are important to include in future modeling efforts to predict changes in soil-atmosphere exchange of CH4 under global change.

Soil moisture sensitivity of autotrophic and heterotrophic forest floor respiration in boreal xeric pine and mesic spruce forests

NASA Astrophysics Data System (ADS)

Ťupek, Boris; Launiainen, Samuli; Peltoniemi, Mikko; Heikkinen, Jukka; Lehtonen, Aleksi

2016-04-01

Litter decomposition rates of the most process based soil carbon models affected by environmental conditions are linked with soil heterotrophic CO2 emissions and serve for estimating soil carbon sequestration; thus due to the mass balance equation the variation in measured litter inputs and measured heterotrophic soil CO2 effluxes should indicate soil carbon stock changes, needed by soil carbon management for mitigation of anthropogenic CO2 emissions, if sensitivity functions of the applied model suit to the environmental conditions e.g. soil temperature and moisture. We evaluated the response forms of autotrophic and heterotrophic forest floor respiration to soil temperature and moisture in four boreal forest sites of the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) by a soil trenching experiment during year 2015 in southern Finland. As expected both autotrophic and heterotrophic forest floor respiration components were primarily controlled by soil temperature and exponential regression models generally explained more than 90% of the variance. Soil moisture regression models on average explained less than 10% of the variance and the response forms varied between Gaussian for the autotrophic forest floor respiration component and linear for the heterotrophic forest floor respiration component. Although the percentage of explained variance of soil heterotrophic respiration by the soil moisture was small, the observed reduction of CO2 emissions with higher moisture levels suggested that soil moisture response of soil carbon models not accounting for the reduction due to excessive moisture should be re-evaluated in order to estimate right levels of soil carbon stock changes. Our further study will include evaluation of process based soil carbon models by the annual heterotrophic respiration and soil carbon stocks.

The use of remotely sensed soil moisture data in large-scale models of the hydrological cycle

NASA Technical Reports Server (NTRS)

Salomonson, V. V.; Gurney, R. J.; Schmugge, T. J.

1985-01-01

Manabe (1982) has reviewed numerical simulations of the atmosphere which provided a framework within which an examination of the dynamics of the hydrological cycle could be conducted. It was found that the climate is sensitive to soil moisture variability in space and time. The challenge arises now to improve the observations of soil moisture so as to provide up-dated boundary condition inputs to large scale models including the hydrological cycle. Attention is given to details regarding the significance of understanding soil moisture variations, soil moisture estimation using remote sensing, and energy and moisture balance modeling.

Evaluation of HCMM data for assessing soil moisture and water table depth. [South Dakota

NASA Technical Reports Server (NTRS)

Moore, D. G.; Heilman, J. L.; Tunheim, J. A.; Westin, F. C.; Heilman, W. E.; Beutler, G. A.; Ness, S. D. (Principal Investigator)

1981-01-01

Soil moisture in the 0-cm to 4-cm layer could be estimated with 1-mm soil temperatures throughout the growing season of a rainfed barley crop in eastern South Dakota. Empirical equations were developed to reduce the effect of canopy cover when radiometrically estimating the soil temperature. Corrective equations were applied to an aircraft simulation of HCMM data for a diversity of crop types and land cover conditions to estimate the soil moisture. The average difference between observed and measured soil moisture was 1.6% of field capacity. Shallow alluvial aquifers were located with HCMM predawn data. After correcting the data for vegetation differences, equations were developed for predicting water table depths within the aquifer. A finite difference code simulating soil moisture and soil temperature shows that soils with different moisture profiles differed in soil temperatures in a well defined functional manner. A significant surface thermal anomaly was found to be associated with shallow water tables.

SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann

2011-01-01

Soil Moisture Active Passive (SMAP) satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the supporting brightness temperature observations are common to both SMAP and European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are opportunities for synergies between the two missions. These include exploiting the data for calibration and validation and establishing longer term L-band brightness temperature and derived soil moisture products. In this investigation we will be using SMOS brightness temperature, ancillary data, and soil moisture products to develop and evaluate a candidate SMAP L2 passive soil moisture retrieval algorithm. This work will begin with evaluations based on the SMOS product grids and ancillary data sets and transition to those that will be used by SMAP. An important step in this analysis is reprocessing the multiple incidence angle observations provided by SMOS to a global brightness temperature product that simulates the constant 40 degree incidence angle observations that SMAP will provide. The reprocessed brightness temperature data provide a basis for evaluating different SMAP algorithm alternatives. Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval. In this first phase, we utilized only the Single Channel Algorithm (SCA), which is based on the radiative transfer equation and uses the channel that is most sensitive to soil moisture (H-pol). Brightness temperature is corrected sequentially for the effects of temperature, vegetation, roughness (dynamic ancillary data sets) and soil texture (static ancillary data set). European Centre for Medium-Range Weather Forecasts (ECMWF) estimates of soil temperature for the top layer (as provided as part of the SMOS ancillary data) were used to correct for surface temperature effects and to derive microwave emissivity. ECMWF data were also used for precipitation forecasts, presence of snow, and frozen ground. Vegetation options are described below. One year of soil moisture observations from a set of four watersheds in the U.S. were used to evaluate four different retrieval methodologies: (1) SMOS soil moisture estimates (version 400), (2) SeA soil moisture estimates using the SMOS/SMAP data with SMOS estimated vegetation optical depth, which is part of the SMOS level 2 product, (3) SeA soil moisture estimates using the SMOS/SMAP data and the MODIS-based vegetation climatology data, and (4) SeA soil moisture estimates using the SMOS/SMAP data and actual MODIS observations. The use of SMOS real-world global microwave observations and the analyses described here will help in the development and selection of different land surface parameters and ancillary observations needed for the SMAP soil moisture algorithms. These investigations will greatly improve the quality and reliability of this SMAP product at launch.

Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers

PubMed Central

Liu, Cheng; Qian, Hongzhou; Cao, Weixing; Ni, Jun

2018-01-01

To meet the demand of intelligent irrigation for accurate moisture sensing in the soil vertical profile, a soil profile moisture sensor was designed based on the principle of high-frequency capacitance. The sensor consists of five groups of sensing probes, a data processor, and some accessory components. Low-resistivity copper rings were used as components of the sensing probes. Composable simulation of the sensor’s sensing probes was carried out using a high-frequency structure simulator. According to the effective radiation range of electric field intensity, width and spacing of copper ring were set to 30 mm and 40 mm, respectively. A parallel resonance circuit of voltage-controlled oscillator and high-frequency inductance-capacitance (LC) was designed for signal frequency division and conditioning. A data processor was used to process moisture-related frequency signals for soil profile moisture sensing. The sensor was able to detect real-time soil moisture at the depths of 20, 30, and 50 cm and conduct online inversion of moisture in the soil layer between 0–100 cm. According to the calibration results, the degree of fitting (R2) between the sensor’s measuring frequency and the volumetric moisture content of soil sample was 0.99 and the relative error of the sensor consistency test was 0–1.17%. Field tests in different loam soils showed that measured soil moisture from our sensor reproduced the observed soil moisture dynamic well, with an R2 of 0.96 and a root mean square error of 0.04. In a sensor accuracy test, the R2 between the measured value of the proposed sensor and that of the Diviner2000 portable soil moisture monitoring system was higher than 0.85, with a relative error smaller than 5%. The R2 between measured values and inversed soil moisture values for other soil layers were consistently higher than 0.8. According to calibration test and field test, this sensor, which features low cost, good operability, and high integration, is qualified for precise agricultural irrigation with stable performance and high accuracy. PMID:29883420

Disaggregation Of Passive Microwave Soil Moisture For Use In Watershed Hydrology Applications

NASA Astrophysics Data System (ADS)

Fang, Bin

In recent years the passive microwave remote sensing has been providing soil moisture products using instruments on board satellite/airborne platforms. Spatial resolution has been restricted by the diameter of antenna which is inversely proportional to resolution. As a result, typical products have a spatial resolution of tens of kilometers, which is not compatible for some hydrological research applications. For this reason, the dissertation explores three disaggregation algorithms that estimate L-band passive microwave soil moisture at the subpixel level by using high spatial resolution remote sensing products from other optical and radar instruments were proposed and implemented in this investigation. The first technique utilized a thermal inertia theory to establish a relationship between daily temperature change and average soil moisture modulated by the vegetation condition was developed by using NLDAS, AVHRR, SPOT and MODIS data were applied to disaggregate the 25 km AMSR-E soil moisture to 1 km in Oklahoma. The second algorithm was built on semi empirical physical models (NP89 and LP92) derived from numerical experiments between soil evaporation efficiency and soil moisture over the surface skin sensing depth (a few millimeters) by using simulated soil temperature derived from MODIS and NLDAS as well as AMSR-E soil moisture at 25 km to disaggregate the coarse resolution soil moisture to 1 km in Oklahoma. The third algorithm modeled the relationship between the change in co-polarized radar backscatter and the remotely sensed microwave change in soil moisture retrievals and assumed that change in soil moisture was a function of only the canopy opacity. The change detection algorithm was implemented using aircraft based the remote sensing data from PALS and UAVSAR that were collected in SMPAVEX12 in southern Manitoba, Canada. The PALS L-band h-polarization radiometer soil moisture retrievals were disaggregated by combining them with the PALS and UAVSAR L-band hh-polarization radar spatial resolutions of 1500 m and 5 m/800 m, respectively. All three algorithms were validated using ground measurements from network in situ stations or handheld hydra probes. The validation results demonstrate the practicability on coarse resolution passive microwave soil moisture products.

Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers.

PubMed

Gao, Zhenran; Zhu, Yan; Liu, Cheng; Qian, Hongzhou; Cao, Weixing; Ni, Jun

2018-05-21

To meet the demand of intelligent irrigation for accurate moisture sensing in the soil vertical profile, a soil profile moisture sensor was designed based on the principle of high-frequency capacitance. The sensor consists of five groups of sensing probes, a data processor, and some accessory components. Low-resistivity copper rings were used as components of the sensing probes. Composable simulation of the sensor’s sensing probes was carried out using a high-frequency structure simulator. According to the effective radiation range of electric field intensity, width and spacing of copper ring were set to 30 mm and 40 mm, respectively. A parallel resonance circuit of voltage-controlled oscillator and high-frequency inductance-capacitance (LC) was designed for signal frequency division and conditioning. A data processor was used to process moisture-related frequency signals for soil profile moisture sensing. The sensor was able to detect real-time soil moisture at the depths of 20, 30, and 50 cm and conduct online inversion of moisture in the soil layer between 0⁻100 cm. According to the calibration results, the degree of fitting ( R ²) between the sensor’s measuring frequency and the volumetric moisture content of soil sample was 0.99 and the relative error of the sensor consistency test was 0⁻1.17%. Field tests in different loam soils showed that measured soil moisture from our sensor reproduced the observed soil moisture dynamic well, with an R ² of 0.96 and a root mean square error of 0.04. In a sensor accuracy test, the R ² between the measured value of the proposed sensor and that of the Diviner2000 portable soil moisture monitoring system was higher than 0.85, with a relative error smaller than 5%. The R ² between measured values and inversed soil moisture values for other soil layers were consistently higher than 0.8. According to calibration test and field test, this sensor, which features low cost, good operability, and high integration, is qualified for precise agricultural irrigation with stable performance and high accuracy.

On the soil moisture estimate at basin scale in Mediterranean basins with the ASAR sensor: the Mulargia basin case study

NASA Astrophysics Data System (ADS)

Fois, Laura; Montaldo, Nicola

2017-04-01

Soil moisture plays a key role in water and energy exchanges between soil, vegetation and atmosphere. For water resources planning and managementthesoil moistureneeds to be accurately and spatially monitored, specially where the risk of desertification is high, such as Mediterranean basins. In this sense active remote sensors are very attractive for soil moisture monitoring. But Mediterranean basinsaretypicallycharacterized by strong topography and high spatial variability of physiographic properties, and only high spatial resolution sensorsare potentially able to monitor the strong soil moisture spatial variability.In this regard the Envisat ASAR (Advanced Synthetic Aperture Radar) sensor offers the attractive opportunity ofsoil moisture mapping at fine spatial and temporal resolutions(up to 30 m, every 30 days). We test the ASAR sensor for soil moisture estimate in an interesting Sardinian case study, the Mulargia basin withan area of about 70 sq.km. The position of the Sardinia island in the center of the western Mediterranean Sea basin, its low urbanization and human activity make Sardinia a perfect reference laboratory for Mediterranean hydrologic studies. The Mulargia basin is a typical Mediterranean basinin water-limited conditions, and is an experimental basin from 2003. For soil moisture mapping23 satellite ASAR imagery at single and dual polarization were acquired for the 2003-2004period.Satellite observationsmay bevalidated through spatially distributed soil moisture ground-truth data, collected over the whole basin using the TDR technique and the gravimetric method, in days with available radar images. The results show that ASAR sensor observations can be successfully used for soil moisture mapping at different seasons, both wet and dry, but an accurate calibration with field data is necessary. We detect a strong relationship between the soil moisture spatial variability and the physiographic properties of the basin, such as soil water storage capacity, deep and texture of soils, type and density of vegetation, and topographic parameters. Finally we demonstrate that the high resolution ASAR imagery are an attractive tool for estimating surface soil moisture at basin scale, offering a unique opportunity for monitoring the soil moisture spatial variability in typical Mediterranean basins.

Mapping of bare soil surface parameters from TerraSAR-X radar images over a semi-arid region

NASA Astrophysics Data System (ADS)

Gorrab, A.; Zribi, M.; Baghdadi, N.; Lili Chabaane, Z.

2015-10-01

The goal of this paper is to analyze the sensitivity of X-band SAR (TerraSAR-X) signals as a function of different physical bare soil parameters (soil moisture, soil roughness), and to demonstrate that it is possible to estimate of both soil moisture and texture from the same experimental campaign, using a single radar signal configuration (one incidence angle, one polarization). Firstly, we analyzed statistically the relationships between X-band SAR (TerraSAR-X) backscattering signals function of soil moisture and different roughness parameters (the root mean square height Hrms, the Zs parameter and the Zg parameter) at HH polarization and for an incidence angle about 36°, over a semi-arid site in Tunisia (North Africa). Results have shown a high sensitivity of real radar data to the two soil parameters: roughness and moisture. A linear relationship is obtained between volumetric soil moisture and radar signal. A logarithmic correlation is observed between backscattering coefficient and all roughness parameters. The highest dynamic sensitivity is obtained with Zg parameter. Then, we proposed to retrieve of both soil moisture and texture using these multi-temporal X-band SAR images. Our approach is based on the change detection method and combines the seven radar images with different continuous thetaprobe measurements. To estimate soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our approaches are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: (1) roughness variations during the three-month radar acquisition campaigns were not accounted for; (2) a simple correction for temporal variations in roughness was included. The results reveal a small improvement in the estimation of soil moisture when a correction for temporal variations in roughness is introduced. Finally, by considering the estimated temporal dynamics of soil moisture, a methodology is proposed for the retrieval of clay and sand content (expressed as percentages) in soil. Two empirical relationships were established between the mean moisture values retrieved from the seven acquired radar images and the two soil texture components over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved.

Canadian Experiment for Soil Moisture in 2010 (CanEX-SM10): Overview and Preliminary Results

NASA Technical Reports Server (NTRS)

Magagi, Ramata; Berg, Aaron; Goita, Kalifa; Belair, Stephane; Jackson, Tom; Toth, B.; Walker, A.; McNairn, H.; O'Neill, P.; Moghdam. M;

Inter-comparison of soil moisture sensors from the soil moisture active passive marena Oklahoma in situ sensor testbed (SMAP-MOISST)

USDA-ARS?s Scientific Manuscript database

The diversity of in situ soil moisture network protocols and instrumentation led to the development of a testbed for comparing in situ soil moisture sensors. Located in Marena, Oklahoma on the Oklahoma State University Range Research Station, the testbed consists of four base stations. Each station ...

Improving long-term global precipitation dataset using multi-sensor surface soil moisture retrievals and the soil moisture analysis rainfall tool (SMART)

USDA-ARS?s Scientific Manuscript database

Using multiple historical satellite surface soil moisture products, the Kalman Filtering-based Soil Moisture Analysis Rainfall Tool (SMART) is applied to improve the accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available rain g...

On the temporal and spatial variability of near-surface soil moisture for the identification of representative in situ soil moisture monitoring stations

USDA-ARS?s Scientific Manuscript database

The high spatio-temporal variability of soil moisture complicates the validation of remotely sensed soil moisture products using in-situ monitoring stations. Therefore, a standard methodology for selecting the most repre- sentative stations for the purpose of validating satellites and land surface ...

Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper-resolution model

USDA-ARS?s Scientific Manuscript database

Accurate global mapping of soil moisture is the goal of the Soil Moisture Active Passive (SMAP) mission, which is expected to improve the estimation of water, energy, and carbon exchanges between the land and the atmosphere. Like other satellite products, the SMAP soil moisture retrievals need to be...

Impact of mulches and growing season on indicator bacteria survival during lettuce cultivation.

PubMed

Xu, Aixia; Buchanan, Robert L; Micallef, Shirley A

2016-05-02

In fresh produce production, the use of mulches as ground cover to retain moisture and control weeds is a common agricultural practice, but the influence that various mulches have on enteric pathogen survival and dispersal is unknown. The goal of this study was to assess the impact of different mulching methods on the survival of soil and epiphytic fecal indicator bacteria on organically grown lettuce during different growing seasons. Organically managed lettuce, cultivated with various ground covers--polyethylene plastic, corn-based biodegradable plastic, paper and straw mulch--and bare ground as a no-mulch control, was overhead inoculated with manure-contaminated water containing known levels of generic Escherichia coli and Enterococcus spp. Leaves and soil samples were collected at intervals over a two week period on days 0, 1, 3, 5, 7, 10 and 14, and quantitatively assessed for E. coli, fecal coliforms and Enterococcus spp. Data were analyzed using mixed models with repeated measures and an exponential decline with asymptote survival model. Indicator bacterial concentrations in the lettuce phyllosphere decreased over time under all treatments, with more rapid E. coli declines in the fall than in the spring (p<0.01). Persistence of E. coli in spring was correlated with higher maximum and minimum temperatures in this season, and more regular rainfall. The survival model gave very good fits for the progression of E. coli concentrations in the phyllosphere over time (R(2)=0.88 ± 0.12). In the spring season, decline rates of E. coli counts were faster (2013 p=0.18; 2014 p<0.005) for the bare ground-cultivated lettuce compared to mulches. In fall 2014, the E. coli decline rate on paper mulch-grown lettuce was higher (p<0.005). Bacteria fluctuated more, and persisted longer, in soil compared to lettuce phyllosphere, and mulch type was a factor for fecal coliform levels (p<0.05), with higher counts retrieved under plastic mulches in all trials, and higher enterococci levels under straw in fall 2014 (p<0.05). This study demonstrates that mulches used in lettuce production may impact the fate of enteric bacteria in soil or on lettuce, most likely in relation to soil moisture retention, and other weather-related factors, such as temperature and rainfall. The data suggest that the time between exposure to a source of enteric bacteria and harvesting of the crop is season dependent, which has implications for determining best harvest times. Copyright © 2016 Elsevier B.V. All rights reserved.

Understanding Soil Moisture

USDA-ARS?s Scientific Manuscript database

Understanding soil moisture is critical for landscape irrigation management. This landscaep irrigation seminar will compare volumetric and matric potential soil-moisture sensors, discuss the relationship between their readings and demonstrate how to use these data. Soil water sensors attempt to sens...

Trends in Soil Moisture Reflect More Than Slope Position: Soils on San Cristóbal Island, Galápagos as a Case Study

NASA Astrophysics Data System (ADS)

Percy, M.; Singha, K.; Benninger, L. K.; Riveros-Iregui, D. A.; Mirus, B. B.

2015-12-01

The spatial and temporal distribution of soil moisture in tropical critical zones depends upon a number of variables including topographic position, soil texture, overlying vegetation, and local microclimates. We investigate the influences on soil moisture on a tropical basaltic island (San Cristóbal, Galápagos) across a variety of microclimates during the transition from the wetter to the drier season. We used multiple approaches to characterize spatial and temporal patterns in soil moisture at four sites across microclimates ranging from arid to very humid. The microclimates on San Cristóbal vary with elevation, so our monitoring includes two sites in the transitional zone at lower elevations, one in the humid zone at moderate elevations, and one in the very humid zone in higher elevations. We made over 250 near-surface point measurements per site using a Hydrosense II probe, and estimated the lateral variability in soil moisture across each site with an EM-31 electrical conductivity meter. We also monitored continuous time-series of in-situ soil moisture dynamics using three nested TDR probes collocated with meteorological stations at each of the sites. Preliminary analysis indicates that soils in the very humid zone have lower electrical conductivities across all the hillslopes as compared to the humid and transitional zones, which suggests that additional factors beyond climate and slope position are important. While soil texture across the very humid site is fairly uniform, variations in vegetation have a strong control on soil moisture patterns. At the remaining sites the vegetation patterns also have a very strong local influence on soil moisture, but correlation between the depth to clay layers and soil moisture patterns suggests that mineralogy is also important. Our findings suggest that the microclimatic setting is a crucial consideration for understanding relations between vegetation, soil texture, and soil-moisture dynamics in tropical critical zones.

Ecohydrological responses of a model semiarid system to precipitation pulses after a global change type dry-down depend on growth-form, event size, and time since establishment

NASA Astrophysics Data System (ADS)

Barron-Gafford, G. A.; Minor, R. L.; Braun, Z.; Potts, D. L.

2012-12-01

Woody encroachment into grasslands alters ecosystem structure and function both above- and belowground. Aboveground, woody plant canopies increase leaf area index and alter patterns of interception, infiltration and runoff. Belowground, woody plants alter root distribution and increase maximum rooting depth with the effect of accessing deeper pools of soil moisture and shifting the timing and duration of evapotranspiration. In turn, these woody plants mediate hydrological changes that influence patterns of ecosystem CO2 exchange and productivity. Given projections of more variable precipitation and increased temperatures for many semiarid regions, differences in physiological performance are likely to drive changes in ecosystem-scale carbon and water flux depending on the degree of woody cover. Ultimately, as soil moisture declines with decreased precipitation, differential patterns of environmental sensitivity among growth-forms and their dependence on groundwater will only become more important in determining ecosystem resilience to future change. Here, we created a series of 1-meter deep mesocosms that housed either a woody mesquite shrub, a bunchgrass, or was left as bare soil. Five replicates of each were maintained under current ambient air temperatures, and five replicates were maintained under projected (+4oC) air temperatures. Each mesocosm was outfitted with an array of soil moisture, temperature, water potential, and CO2 exchange concentration sensors at the near-surface, 30, 55, and 80cm depths to quantify patterns of soil moisture and respiratory CO2 exchange efflux in response to rainfall events of varying magnitude and intervening dry periods of varying duration. In addition, we used minirhizotrons to quantify the response of roots to episodic rainfall. During the first year, bunchgrasses photosynthetically outperformed mesquite saplings across a wider range of temperatures under dry conditions, regardless of growth temperature (ambient or +4oC). Both growth forms were similarly responsive to episodic rainfall, regardless of event magnitude, though mesquite were able to maintain photosynthetic function for a longer period in response to each rain. However, in the second year of the experiment a new pattern of response to moisture and high temperature stress emerged. Under dry conditions, mesquite sustained high photosynthetic rates across a wider range of atmospheric temperatures and were less responsive to rainfall, regardless of event magnitude. In contrast, the limiting effect of high temperatures on bunchgrass photosynthesis was soil moisture dependent. In this case, the effects of high temperature limitation were exaggerated under dry conditions and relaxed when soil moisture was more abundant. Together, these trends yielded a significantly greater photosynthetic assimilation by deeper-rooted mesquite shrubs than shallow-rooted bunchgrasses under both temperature regimes. Combining these aboveground measurements of carbon uptake with belowground estimates of carbon efflux will allow us to make much more informed projections of net carbon balance within mixed vegetation shrublands across a range of global climate change projections.

Increasing Vulnerability to Drought and Climate Change on the Navajo Nation, southwestern United States

NASA Astrophysics Data System (ADS)

Hiza, M. M.; Kelley, K. B.; Francis, H.

2011-12-01

The Navajo Nation of Arizona, New Mexico, and Utah, is an ecologically sensitive semi-arid to arid area where rapid growth of one of the largest population of Native Americans is outstripping the capacity of the land to sustain them. Recent drought conditions, combined with increasing temperatures, are significantly altering the habitability of a region already characterized by harsh living conditions. In addition to altered landscape conditions due to climatic change, drought, and varying land use practices over the last 200 years, the Navajo people have been affected by land use policies and harsh economic conditions that weaken their cultural fabric. Increasing aridity combined with drought threaten the very existence of Navajo culture and the survival of traditional Navajo communities. People presently living on these Native lands are unique in American society as their traditional lifestyle requires intimate knowledge of the ecosystem, knowledge that has been passed on for generations through oral traditions. We present data from the lifelong observations of 73 Native American elders that provide a record of the changes in plants and animals, water availability, weather, and sand or dust storms. This information is used to complement the scant long-term meteorological records and historical documentation for the region to further refine our understanding of the historical trends and local impacts of climate change and drought. Among the most cited changes is a long-term decrease in the amount of annual snowfall over the past century, a transition from wet conditions to dry conditions in the 1940s, and a decline in surface water features. The lack of available water, in addition to changing socioeconomic conditions, was mentioned as a leading cause for the decline in the ability to grow corn and other crops. Other noted changes include the disappearance of springs, and of plant and animal populations (particularly medicinal plants, cottonwood trees, beavers, and eagles). Changes in the frequency of wind, sand and dust storms (more frequent in the 1950s and increasing in the 1990s) were also observed. Important information that cannot be easily gleaned from meteorological and stream flow records are also recorded in our consultations. For example, they include observations of soil moisture and the description of disappearing migratory birds that rely on water sources. Local monitoring of soil moisture conditions today indicates that a rapid decline occurs in the Springtime. The fact that soil moisture was noted in the past to persist through the spring dry season, until the late summer monsoon season has profound implications for impacts to ecosystem viability that may have already occurred with climate change and drought. In addition, these changes in soil moisture also help us understand the mechanisms contributing to current drought severity. We conclude that a long-term drying trend and decreasing snowpack, superimposed on regional drought cycles, will magnify the cultural and literal erosion and desertification of the Navajo Nation and leave its people increasingly vulnerable to climate extremes.

Ozone Sensitivity in Sweet Corn (Zea mays L.) Plants: A Possible Relationship to Water Balance

PubMed Central

Harris, Michael J.; Heath, Robert L.

1981-01-01

Stomatal characteristics affecting gas exchange were compared in two sweet corn hybrids (var. Bonanza and Monarch Advance) which differ in foliar ozone sensitivity. No significant differences were observed in stomatal frequencies, guard cell lengths, or conductances to water vapor diffusion. When plant water status was compared, leaf-water potentials for the ozone-resistant cultivar, Bonanza, were lower. A comparison of the relationship between soil- and leaf-water potential indicated that the leaf-water potential of Bonanza was more sensitive to declines in soil-water potential. Additionally, a comparison of stomatal conductance to water vapor diffusion as soil moisture declined and following root detachment indicated that stomata of Bonanza were, likewise, more sensitive to increasing water stress. Data suggest that these differences are attributable to a greater shoot-to-root fresh weight ratio and higher resistance to water movement in the water-conducting tissues for Bonanza. Our observations suggest that root and water delivery system characteristics play a major contributory role in the determination of foliar ozone sensitivity in this species. PMID:16662019

Effect of soil moisture on the temperature sensitivity of Northern soils

NASA Astrophysics Data System (ADS)

Minions, C.; Natali, S.; Ludwig, S.; Risk, D.; Macintyre, C. M.

2017-12-01

Arctic and boreal ecosystems are vast reservoirs of carbon and are particularly sensitive to climate warming. Changes in the temperature and precipitation regimes of these regions could significantly alter soil respiration rates, impacting atmospheric concentrations and affecting climate change feedbacks. Many incubation studies have shown that both temperature and soil moisture are important environmental drivers of soil respiration; this relationship, however, has rarely been demonstrated with in situ data. Here we present the results of a study at six field sites in Alaska from 2016 to 2017. Low-power automated soil gas systems were used to measure soil surface CO2 flux from three forced diffusion chambers and soil profile concentrations from three soil depth chambers at hourly intervals at each site. HOBO Onset dataloggers were used to monitor soil moisture and temperature profiles. Temperature sensitivity (Q10) was determined at each site using inversion analysis applied over different time periods. With highly resolved data sets, we were able to observe the changes in soil respiration in response to changes in temperature and soil moisture. Through regression analysis we confirmed that temperature is the primary driver in soil respiration, but soil moisture becomes dominant beyond a certain threshold, suppressing CO2 flux in soils with high moisture content. This field study supports the conclusions made from previous soil incubation studies and provides valuable insights into the impact of both temperature and soil moisture changes on soil respiration.

Automated Quality Control of in Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products

NASA Astrophysics Data System (ADS)

Ek, M. B.; Xia, Y.; Ford, T.; Wu, Y.; Quiring, S. M.

2015-12-01

The North American Soil Moisture Database (NASMD) was initiated in 2011 to provide support for developing climate forecasting tools, calibrating land surface models and validating satellite-derived soil moisture algorithms. The NASMD has collected data from over 30 soil moisture observation networks providing millions of in situ soil moisture observations in all 50 states as well as Canada and Mexico. It is recognized that the quality of measured soil moisture in NASMD is highly variable due to the diversity of climatological conditions, land cover, soil texture, and topographies of the stations and differences in measurement devices (e.g., sensors) and installation. It is also recognized that error, inaccuracy and imprecision in the data set can have significant impacts on practical operations and scientific studies. Therefore, developing an appropriate quality control procedure is essential to ensure the data is of the best quality. In this study, an automated quality control approach is developed using the North American Land Data Assimilation System phase 2 (NLDAS-2) Noah soil porosity, soil temperature, and fraction of liquid and total soil moisture to flag erroneous and/or spurious measurements. Overall results show that this approach is able to flag unreasonable values when the soil is partially frozen. A validation example using NLDAS-2 multiple model soil moisture products at the 20 cm soil layer showed that the quality control procedure had a significant positive impact in Alabama, North Carolina, and West Texas. It had a greater impact in colder regions, particularly during spring and autumn. Over 433 NASMD stations have been quality controlled using the methodology proposed in this study, and the algorithm will be implemented to control data quality from the other ~1,200 NASMD stations in the near future.

Pasture age effects on N[sub 2]O, NO and CH[sub 4] emissions in the Atlantic Lowlands of Costa Rica

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keller, M.; Reiners, W.A.; Veldkamp, E.

A study conducted in Brazil indicated that N[sub 2]O emissions increased following forest conversion to pasture. Our first study in Costa Rica indicated the reverse. To explore this contradiction, we measured N[sub 2]O, NO, and CH[sub 4] emissions in a chronosequence of 8 sites comprising forest and derive pastures of ayes 2 to 25 years, all on the same soil type in the Atlantic Lowlands of Costa Rica. We found large differences through the chronosequence in the fluxes of these three gases. Flux changes were related to changes in available nitrogen, organic matter, moisture content, and bulk density in themore » soil. N[sub 2]O emissions from the 2-year pasture were much greater than from the forest. Emissions declined with pasture age so that 25-year pasture had much smaller emissions than the forest. NO emissions from young pastures were similar to forest emissions, then declined sharply with pasture age. Forest soils consumed CH[sub 4]. Pasture soils mainly produced CH[sub 4]. Prediction of the effects of land use change on trace gas fluxes in the tropics will require an assessment of the history and soil condition of individual land units.« less

Soil moisture: Some fundamentals. [agriculture - soil mechanics

NASA Technical Reports Server (NTRS)

Milstead, B. W.

1975-01-01

A brief tutorial on soil moisture, as it applies to agriculture, is presented. Information was taken from books and papers considered freshman college level material, and is an attempt to briefly present the basic concept of soil moisture and a minimal understanding of how water interacts with soil.

Use of physically-based models and Soil Taxonomy to identify soil moisture classes: Problems and proposals

NASA Astrophysics Data System (ADS)

Bonfante, A.; Basile, A.; de Mascellis, R.; Manna, P.; Terribile, F.

2009-04-01

Soil classification according to Soil Taxonomy include, as fundamental feature, the estimation of soil moisture regime. The term soil moisture regime refers to the "presence or absence either of ground water or of water held at a tension of less than 1500 kPa in the soil or in specific horizons during periods of the year". In the classification procedure, defining of the soil moisture control section is the primary step in order to obtain the soil moisture regimes classification. Currently, the estimation of soil moisture regimes is carried out through simple calculation schemes, such as Newhall and Billaux models, and only in few cases some authors suggest the use of different more complex models (i.e., EPIC) In fact, in the Soil Taxonomy, the definition of the soil moisture control section is based on the wetting front position in two different conditions: the upper boundary is the depth to which a dry soil will be moistened by 2.5 cm of water within 24 hours and the lower boundary is the depth to which a dry soil will be moistened by 7.5 cm of water within 48 hours. Newhall, Billaux and EPIC models don't use physical laws to describe soil water flows, but they use a simple bucket-like scheme where the soil is divided into several compartments and water moves, instantly, only downward when the field capacity is achieved. On the other side, a large number of one-dimensional hydrological simulation models (SWAP, Cropsyst, Hydrus, MACRO, etc..) are available, tested and successfully used. The flow is simulated according to pressure head gradients through the numerical solution of the Richard's equation. These simulation models can be fruitful used to improve the study of soil moisture regimes. The aims of this work are: (i) analysis of the soil moisture control section concept by a physically based model (SWAP); (ii) comparison of the classification obtained in five different Italian pedoclimatic conditions (Mantova and Lodi in northern Italy; Salerno, Benevento and Caserta in southern Italy) applying the classical models (Newhall e Billaux) and the physically-based models (CropSyst e SWAP), The results have shown that the Soil Taxonomy scheme for the definition of the soil moisture regime is unrealistic for the considered Mediterranean soil hydrological conditions. In fact, the same classifications arise irrespective of the soil type. In this respect some suggestions on how modified the section control boundaries were formulated. Keywords: Soil moisture regimes, Newhall, Swap, Soil Taxonomy

Spatiotemporal Variability of Hillslope Soil Moisture Across Steep, Highly Dissected Topography

NASA Astrophysics Data System (ADS)

Jarecke, K. M.; Wondzell, S. M.; Bladon, K. D.

2016-12-01

Hillslope ecohydrological processes, including subsurface water flow and plant water uptake, are strongly influenced by soil moisture. However, the factors controlling spatial and temporal variability of soil moisture in steep, mountainous terrain are poorly understood. We asked: How do topography and soils interact to control the spatial and temporal variability of soil moisture in steep, Douglas-fir dominated hillslopes in the western Cascades? We will present a preliminary analysis of bimonthly soil moisture variability from July-November 2016 at 0-30 and 0-60 cm depth across spatially extensive convergent and divergent topographic positions in Watershed 1 of the H.J. Andrews Experimental Forest in central Oregon. Soil moisture monitoring locations were selected following a 5 m LIDAR analysis of topographic position, aspect, and slope. Topographic position index (TPI) was calculated as the difference in elevation to the mean elevation within a 30 m radius. Convergent (negative TPI values) and divergent (positive TPI values) monitoring locations were established along northwest to northeast-facing aspects and within 25-55 degree slopes. We hypothesized that topographic position (convergent vs. divergent), as well as soil physical properties (e.g., texture, bulk density), control variation in hillslope soil moisture at the sub-watershed scale. In addition, we expected the relative importance of hillslope topography to the spatial variability in soil moisture to differ seasonally. By comparing the spatiotemporal variability of hillslope soil moisture across topographic positions, our research provides a foundation for additional understanding of subsurface flow processes and plant-available soil-water in forests with steep, highly dissected terrain.

Assimilating soil moisture into an Earth System Model

NASA Astrophysics Data System (ADS)

Stacke, Tobias; Hagemann, Stefan

2017-04-01

Several modelling studies reported potential impacts of soil moisture anomalies on regional climate. In particular for short prediction periods, perturbations of the soil moisture state may result in significant alteration of surface temperature in the following season. However, it is not clear yet whether or not soil moisture anomalies affect climate also on larger temporal and spatial scales. In an earlier study, we showed that soil moisture anomalies can persist for several seasons in the deeper soil layers of a land surface model. Additionally, those anomalies can influence root zone moisture, in particular during explicitly dry or wet periods. Thus, one prerequisite for predictability, namely the existence of long term memory, is evident for simulated soil moisture and might be exploited to improve climate predictions. The second prerequisite is the sensitivity of the climate system to soil moisture. In order to investigate this sensitivity for decadal simulations, we implemented a soil moisture assimilation scheme into the Max-Planck Institute for Meteorology's Earth System Model (MPI-ESM). The assimilation scheme is based on a simple nudging algorithm and updates the surface soil moisture state once per day. In our experiments, the MPI-ESM is used which includes model components for the interactive simulation of atmosphere, land and ocean. Artificial assimilation data is created from a control simulation to nudge the MPI-ESM towards predominantly dry and wet states. First analyses are focused on the impact of the assimilation on land surface variables and reveal distinct differences in the long-term mean values between wet and dry state simulations. Precipitation, evapotranspiration and runoff are larger in the wet state compared to the dry state, resulting in an increased moisture transport from the land to atmosphere and ocean. Consequently, surface temperatures are lower in the wet state simulations by more than one Kelvin. In terms of spatial pattern, the largest differences between both simulations are seen for continental areas, while regions with a maritime climate are least sensitive to soil moisture assimilation.

Hydrologic data assimilation with a hillslope-scale-resolving model and L band radar observations: Synthetic experiments with the ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Flores, Alejandro N.; Bras, Rafael L.; Entekhabi, Dara

2012-08-01

Soil moisture information is critical for applications like landslide susceptibility analysis and military trafficability assessment. Existing technologies cannot observe soil moisture at spatial scales of hillslopes (e.g., 100 to 102 m) and over large areas (e.g., 102 to 105 km2) with sufficiently high temporal coverage (e.g., days). Physics-based hydrologic models can simulate soil moisture at the necessary spatial and temporal scales, albeit with error. We develop and test a data assimilation framework based on the ensemble Kalman filter for constraining uncertain simulated high-resolution soil moisture fields to anticipated remote sensing products, specifically NASA's Soil Moisture Active-Passive (SMAP) mission, which will provide global L band microwave observation approximately every 2-3 days. The framework directly assimilates SMAP synthetic 3 km radar backscatter observations to update hillslope-scale bare soil moisture estimates from a physics-based model. Downscaling from 3 km observations to hillslope scales is achieved through the data assimilation algorithm. Assimilation reduces bias in near-surface soil moisture (e.g., top 10 cm) by approximately 0.05 m3/m3and expected root-mean-square errors by at least 60% in much of the watershed, relative to an open loop simulation. However, near-surface moisture estimates in channel and valley bottoms do not improve, and estimates of profile-integrated moisture throughout the watershed do not substantially improve. We discuss the implications of this work, focusing on ongoing efforts to improve soil moisture estimation in the entire soil profile through joint assimilation of other satellite (e.g., vegetation) and in situ soil moisture measurements.

Downscaling near-surface soil moisture from field to plot scale: A comparative analysis under different environmental conditions

NASA Astrophysics Data System (ADS)

Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio

2018-02-01

Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently correlated to a climate indicator such as the aridity index.

Operational Mapping of Soil Moisture Using Synthetic Aperture Radar Data: Application to the Touch Basin (France)

PubMed Central

Baghdadi, Nicolas; Aubert, Maelle; Cerdan, Olivier; Franchistéguy, Laurent; Viel, Christian; Martin, Eric; Zribi, Mehrez; Desprats, Jean François

2007-01-01

Soil moisture is a key parameter in different environmental applications, such as hydrology and natural risk assessment. In this paper, surface soil moisture mapping was carried out over a basin in France using satellite synthetic aperture radar (SAR) images acquired in 2006 and 2007 by C-band (5.3 GHz) sensors. The comparison between soil moisture estimated from SAR data and in situ measurements shows good agreement, with a mapping accuracy better than 3%. This result shows that the monitoring of soil moisture from SAR images is possible in operational phase. Moreover, moistures simulated by the operational Météo-France ISBA soil-vegetation-atmosphere transfer model in the SIM-Safran-ISBA-Modcou chain were compared to radar moisture estimates to validate its pertinence. The difference between ISBA simulations and radar estimates fluctuates between 0.4 and 10% (RMSE). The comparison between ISBA and gravimetric measurements of the 12 March 2007 shows a RMSE of about 6%. Generally, these results are very encouraging. Results show also that the soil moisture estimated from SAR images is not correlated with the textural units defined in the European Soil Geographical Database (SGDBE) at 1:1000000 scale. However, dependence was observed between texture maps and ISBA moisture. This dependence is induced by the use of the texture map as an input parameter in the ISBA model. Even if this parameter is very important for soil moisture estimations, radar results shown that the textural map scale at 1:1000000 is not appropriate to differentiate moistures zones. PMID:28903238

Concerning the relationship between evapotranspiration and soil moisture

NASA Technical Reports Server (NTRS)

Wetzel, Peter J.; Chang, Jy-Tai

1987-01-01

The relationship between the evapotranspiration and soil moisture during the drying, supply-limited phase is studied. A second scaling parameter, based on the evapotranspirational supply and demand concept of Federer (1982), is defined; the parameter, referred to as the threshold evapotranspiration, occurs in vegetation-covered surfaces just before leaf stomata close and when surface tension restricts moisture release from bare soil pores. A simple model for evapotranspiration is proposed. The effects of natural soil heterogeneities on evapotranspiration computed from the model are investigated. It is observed that the natural variability in soil moisture, caused by the heterogeneities, alters the relationship between regional evapotranspiration and the area average soil moisture.

A simulation study of scene confusion factors in sensing soil moisture from orbital radar

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.; Roth, F. T.

1983-01-01

Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1km, and 3 km by 3 km. Distributions of actual near-surface soil moisture are established daily for a 23-day accounting period using a water budget model. Within the 23-day period, three orbital radar overpasses are simulated roughly corresponding to generally moist, wet, and dry soil moisture conditions. The radar simulations are performed by a target/sensor interaction model dependent upon a terrain model, land-use classification, and near-surface soil moisture distribution. The accuracy of soil-moisture classification is evaluated for each single-date radar observation and also for multi-date detection of relative soil moisture change. In general, the results for single-date moisture detection show that 70% to 90% of cropland can be correctly classified to within +/- 20% of the true percent of field capacity. For a given radar resolution, the expected classification accuracy is shown to be dependent upon both the general soil moisture condition and also the geographical distribution of land-use and topographic relief. An analysis of cropland, urban, pasture/rangeland, and woodland subregions within the test site indicates that multi-temporal detection of relative soil moisture change is least sensitive to classification error resulting from scene complexity and topographic effects.

Effects of height on treetop transpiration and stomatal conductance in coast redwood (Sequoia sempervirens).

PubMed

Ambrose, Anthony R; Sillett, Stephen C; Koch, George W; Van Pelt, Robert; Antoine, Marie E; Dawson, Todd E

2010-10-01

Treetops become increasingly constrained by gravity-induced water stress as they approach maximum height. Here we examine the effects of height on seasonal and diurnal sap flow dynamics at the tops of 12 unsuppressed Sequoia sempervirens (D. Don) Endl. (coast redwood) trees 68-113 m tall during one growing season. Average treetop sap velocity (V(S)), transpiration per unit leaf area (E(L)) and stomatal conductance per unit leaf area (G(S)) significantly decreased with increasing height. These differences in sap flow were associated with an unexpected decrease in treetop sapwood area-to-leaf area ratios (A(S):A(L)) in the tallest trees. Both E(L) and G(S) declined as soil moisture decreased and vapor pressure deficit (D) increased throughout the growing season with a greater decline in shorter trees. Under high soil moisture and light conditions, reference G(S) (G(Sref); G(S) at D = 1 kPa) and sensitivity of G(S) to D (-δ; dG(S)/dlnD) significantly decreased with increasing height. The close relationship we observed between G(Sref) and -δ is consistent with the role of stomata in regulating E(L) and leaf water potential (Ψ(L)). Our results confirm that increasing tree height reduces gas exchange of treetop foliage and thereby contributes to lower carbon assimilation and height growth rates as S. sempervirens approaches maximum height.

A Mulitivariate Statistical Model Describing the Compound Nature of Soil Moisture Drought

NASA Astrophysics Data System (ADS)

Manning, Colin; Widmann, Martin; Bevacqua, Emanuele; Maraun, Douglas; Van Loon, Anne; Vrac, Mathieu

2017-04-01

Soil moisture in Europe acts to partition incoming energy into sensible and latent heat fluxes, thereby exerting a large influence on temperature variability. Soil moisture is predominantly controlled by precipitation and evapotranspiration. When these meteorological variables are accumulated over different timescales, their joint multivariate distribution and dependence structure can be used to provide information of soil moisture. We therefore consider soil moisture drought as a compound event of meteorological drought (deficits of precipitation) and heat waves, or more specifically, periods of high Potential Evapotraspiration (PET). We present here a statistical model of soil moisture based on Pair Copula Constructions (PCC) that can describe the dependence amongst soil moisture and its contributing meteorological variables. The model is designed in such a way that it can account for concurrences of meteorological drought and heat waves and describe the dependence between these conditions at a local level. The model is composed of four variables; daily soil moisture (h); a short term and a long term accumulated precipitation variable (Y1 and Y_2) that account for the propagation of meteorological drought to soil moisture drought; and accumulated PET (Y_3), calculated using the Penman Monteith equation, which can represent the effect of a heat wave on soil conditions. Copula are multivariate distribution functions that allow one to model the dependence structure of given variables separately from their marginal behaviour. PCCs then allow in theory for the formulation of a multivariate distribution of any dimension where the multivariate distribution is decomposed into a product of marginal probability density functions and two-dimensional copula, of which some are conditional. We apply PCC here in such a way that allows us to provide estimates of h and their uncertainty through conditioning on the Y in the form h=h|y_1,y_2,y_3 (1) Applying the model to various Fluxnet sites across Europe, we find the model has good skill and can particularly capture periods of low soil moisture well. We illustrate the relevance of the dependence structure of these Y variables to soil moisture and show how it may be generalised to offer information of soil moisture on a widespread scale where few observations of soil moisture exist. We then present results from a validation study of a selection of EURO CORDEX climate models where we demonstrate the skill of these models in representing these dependencies and so offer insight into the skill seen in the representation of soil moisture in these models.

High-resolution soil moisture mapping in Afghanistan

NASA Astrophysics Data System (ADS)

Hendrickx, Jan M. H.; Harrison, J. Bruce J.; Borchers, Brian; Kelley, Julie R.; Howington, Stacy; Ballard, Jerry

2011-06-01

Soil moisture conditions have an impact upon virtually all aspects of Army activities and are increasingly affecting its systems and operations. Soil moisture conditions affect operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, military engineering activities, blowing dust and sand, watershed responses, and flooding. This study further explores a method for high-resolution (2.7 m) soil moisture mapping using remote satellite optical imagery that is readily available from Landsat and QuickBird. The soil moisture estimations are needed for the evaluation of IED sensors using the Countermine Simulation Testbed in regions where access is difficult or impossible. The method has been tested in Helmand Province, Afghanistan, using a Landsat7 image and a QuickBird image of April 23 and 24, 2009, respectively. In previous work it was found that Landsat soil moisture can be predicted from the visual and near infra-red Landsat bands1-4. Since QuickBird bands 1-4 are almost identical to Landsat bands 1- 4, a Landsat soil moisture map can be downscaled using QuickBird bands 1-4. However, using this global approach for downscaling from Landsat to QuickBird scale yielded a small number of pixels with erroneous soil moisture values. Therefore, the objective of this study is to examine how the quality of the downscaled soil moisture maps can be improved by using a data stratification approach for the development of downscaling regression equations for each landscape class. It was found that stratification results in a reliable downscaled soil moisture map with a spatial resolution of 2.7 m.

Evaluating the Utility of Remotely-Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring

NASA Technical Reports Server (NTRS)

Bolten, John D.; Crow, Wade T.; Zhan, Xiwu; Jackson, Thomas J.; Reynolds,Curt

2010-01-01

Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.

Analysis of spatiotemporal soil moisture patterns at the catchment scale using a wireless sensor network

NASA Astrophysics Data System (ADS)

Bogena, Heye R.; Huisman, Johan A.; Rosenbaum, Ulrike; Weuthen, Ansgar; Vereecken, Harry

2010-05-01

Soil water content plays a key role in partitioning water and energy fluxes and controlling the pattern of groundwater recharge. Despite the importance of soil water content, it is not yet measured in an operational way at larger scales. The aim of this paper is to present the potential of real-time monitoring for the analysis of soil moisture patterns at the catchment scale using the recently developed wireless sensor network SoilNet [1], [2]. SoilNet is designed to measure soil moisture, salinity and temperature in several depths (e.g. 5, 20 and 50 cm). Recently, a small forest catchment Wüstebach (~27 ha) has been instrumented with 150 sensor nodes and more than 1200 soil sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories). From August to November 2009, more than 6 million soil moisture measurements have been performed. We will present first results from a statistical and geostatistical analysis of the data. The observed spatial variability of soil moisture corresponds well with the 800-m scale variability described in [3]. The very low scattering of the standard deviation versus mean soil moisture plots indicates that sensor network data shows less artificial soil moisture variations than soil moisture data originated from measurement campaigns. The variograms showed more or less the same nugget effect, which indicates that the sum of the sub-scale variability and the measurement error is rather time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil water content, which poses an upper limit and is typically not strongly variable in headwater catchments with relatively homogeneous soil. The spatiotemporal variability in soil moisture at 50 cm depth was significantly lower than at 5 and 20 cm. This finding indicates that the considerable variability of the top soil is buffered deeper in the soil due to lateral and vertical water fluxes. Topographic features showed the strongest correlation with soil moisture during dry periods, indicating that the control of topography on the soil moisture pattern depends on the soil water status. Interpolation using the external drift kriging method demonstrated that the high sampling density allows capturing the key patterns of soil moisture variation in the Wüstebach catchment. References: [1] Bogena, H.R., J.A. Huisman, C. Oberdörster, H. Vereecken (2007): Evaluation of a low-cost soil water content sensor for wireless network applications. Journal of Hydrology: 344, 32- 42. [2] Rosenbaum, U., Huisman, J.A., Weuthen, A., Vereecken, H. and Bogena, H.R. (2010): Quantification of sensor-to-sensor variability of the ECH2O EC-5, TE and 5TE sensors in dielectric liquids. Accepted for publication in Vadose Zone Journal (09/2009). [3] Famiglietti J.S., D. Ryu, A. A. Berg, M. Rodell and T. J. Jackson (2008), Field observations of soil moisture variability across scales, Water Resour. Res. 44, W01423, doi:10.1029/2006WR005804.

Pupal development of Ceratitis capitata (Diptera: Tephritidae) and Diachasmimorpha longicaudata (Hymenoptera: Braconidae) at different moisture values in four soil types.

PubMed

Bento, F de M M; Marques, R N; Costa, M L Z; Walder, J M M; Silva, A P; Parra, J R P

2010-08-01

This study aimed to evaluate adult emergence and duration of the pupal stage of the Mediterranean fruit fly, Ceratitis capitata (Wiedemann), and emergence of the fruit fly parasitoid, Diachasmimorpha longicaudata (Ashmead), under different moisture conditions in four soil types, using soil water matric potential. Pupal stage duration in C. capitata was influenced differently for males and females. In females, only soil type affected pupal stage duration, which was longer in a clay soil. In males, pupal stage duration was individually influenced by moisture and soil type, with a reduction in pupal stage duration in a heavy clay soil and in a sandy clay, with longer duration in the clay soil. As matric potential decreased, duration of the pupal stage of C. capitata males increased, regardless of soil type. C. capitata emergence was affected by moisture, regardless of soil type, and was higher in drier soils. The emergence of D. longicaudata adults was individually influenced by soil type and moisture factors, and the number of emerged D. longicaudata adults was three times higher in sandy loam and lower in a heavy clay soil. Always, the number of emerged adults was higher at higher moisture conditions. C. capitata and D. longicaudata pupal development was affected by moisture and soil type, which may facilitate pest sampling and allow release areas for the parasitoid to be defined under field conditions.

Development and Validation of The SMAP Enhanced Passive Soil Moisture Product

NASA Technical Reports Server (NTRS)

Chan, S.; Bindlish, R.; O'Neill, P.; Jackson, T.; Chaubell, J.; Piepmeier, J.; Dunbar, S.; Colliander, A.; Chen, F.; Entekhabi, D.;

Soil moisture retrival from Sentinel-1 and Modis synergy

NASA Astrophysics Data System (ADS)

Gao, Qi; Zribi, Mehrez; Escorihuela, Maria Jose; Baghdadi, Nicolas

2017-04-01

This study presents two methodologies retrieving soil moisture from SAR remote sensing data. The study is based on Sentinel-1 data in the VV polarization, over a site in Urgell, Catalunya (Spain). In the two methodologies using change detection techniques, preprocessed radar data are combined with normalized difference vegetation index (NDVI) auxiliary data to estimate the mean soil moisture with a resolution of 1km. By modeling the relationship between the backscatter difference and NDVI, the soil moisture at a specific NDVI value is retrieved. The first algorithm is already developed on West Africa(Zribi et al., 2014) from ERS scatterometer data to estimate soil water status. In this study, it is adapted to Sentinel-1 data and take into account the high repetitiveness of data in optimizing the inversion approach. Another new method is developed based on the backscatter difference between two adjacent days of Sentinel-1 data w.r.t. NDVI, with smaller vegetation change, the backscatter difference is more sensitive to soil moisture. The proposed methodologies have been validated with the ground measurement in two demonstrative fields with RMS error about 0.05 (in volumetric moisture), and the coherence between soil moisture variations and rainfall events is observed. Soil moisture maps at 1km resolution are generated for the study area. The results demonstrate the potential of Sentinel-1 data for the retrieval of soil moisture at 1km or even better resolution.

Evaluating ESA CCI soil moisture in East Africa.

PubMed

McNally, Amy; Shukla, Shraddhanand; Arsenault, Kristi R; Wang, Shugong; Peters-Lidard, Christa D; Verdin, James P

2016-06-01

To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and NASA's Soil Moisture Active Passive (SMAP), however these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we use East Africa as a case study to evaluate the quality of a 30+ year time series of merged active-passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM). Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we found substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies were well correlated (R>0.5) with modeled, seasonal soil moisture, and in some regions, NDVI. We use correlation analysis and qualitative comparisons at seasonal time scales to show that remotely sensed soil moisture can add information to a convergence of evidence framework that traditionally relies on rainfall and NDVI in moderately vegetated regions.

Irrigation scheduling using soil moisture sensors

USDA-ARS?s Scientific Manuscript database

Soil moisture sensors were evaluated and used for irrigation scheduling in humid region. Soil moisture sensors were installed in soil at depths of 15cm, 30cm, and 61cm belowground. Soil volumetric water content was automatically measured by the sensors in a time interval of an hour during the crop g...

Comparison of different assimilation methodologies of groundwater levels to improve predictions of root zone soil moisture with an integrated terrestrial system model

NASA Astrophysics Data System (ADS)

Zhang, Hongjuan; Kurtz, Wolfgang; Kollet, Stefan; Vereecken, Harry; Franssen, Harrie-Jan Hendricks

2018-01-01

The linkage between root zone soil moisture and groundwater is either neglected or simplified in most land surface models. The fully-coupled subsurface-land surface model TerrSysMP including variably saturated groundwater dynamics is used in this work. We test and compare five data assimilation methodologies for assimilating groundwater level data via the ensemble Kalman filter (EnKF) to improve root zone soil moisture estimation with TerrSysMP. Groundwater level data are assimilated in the form of pressure head or soil moisture (set equal to porosity in the saturated zone) to update state vectors. In the five assimilation methodologies, the state vector contains either (i) pressure head, or (ii) log-transformed pressure head, or (iii) soil moisture, or (iv) pressure head for the saturated zone only, or (v) a combination of pressure head and soil moisture, pressure head for the saturated zone and soil moisture for the unsaturated zone. These methodologies are evaluated in synthetic experiments which are performed for different climate conditions, soil types and plant functional types to simulate various root zone soil moisture distributions and groundwater levels. The results demonstrate that EnKF cannot properly handle strongly skewed pressure distributions which are caused by extreme negative pressure heads in the unsaturated zone during dry periods. This problem can only be alleviated by methodology (iii), (iv) and (v). The last approach gives the best results and avoids unphysical updates related to strongly skewed pressure heads in the unsaturated zone. If groundwater level data are assimilated by methodology (iii), EnKF fails to update the state vector containing the soil moisture values if for (almost) all the realizations the observation does not bring significant new information. Synthetic experiments for the joint assimilation of groundwater levels and surface soil moisture support methodology (v) and show great potential for improving the representation of root zone soil moisture.

Soil moisture inferences from thermal infrared measurements of vegetation temperatures

NASA Technical Reports Server (NTRS)

Jackson, R. D. (Principal Investigator)

1981-01-01

Thermal infrared measurements of wheat (Triticum durum) canopy temperatures were used in a crop water stress index to infer root zone soil moisture. Results indicated that one time plant temperature measurement cannot produce precise estimates of root zone soil moisture due to complicating plant factors. Plant temperature measurements do yield useful qualitative information concerning soil moisture and plant condition.

Soil moisture modeling review

NASA Technical Reports Server (NTRS)

Hildreth, W. W.

1978-01-01

A determination of the state of the art in soil moisture transport modeling based on physical or physiological principles was made. It was found that soil moisture models based on physical principles have been under development for more than 10 years. However, these models were shown to represent infiltration and redistribution of soil moisture quite well. Evapotranspiration has not been as adequately incorporated into the models.

Soil moisture monitoring for crop management

NASA Astrophysics Data System (ADS)

Boyd, Dale

2015-07-01

The 'Risk management through soil moisture monitoring' project has demonstrated the capability of current technology to remotely monitor and communicate real time soil moisture data. The project investigated whether capacitance probes would assist making informed pre- and in-crop decisions. Crop potential and cropping inputs are increasingly being subject to greater instability and uncertainty due to seasonal variability. In a targeted survey of those who received regular correspondence from the Department of Primary Industries it was found that i) 50% of the audience found the information generated relevant for them and less than 10% indicted with was not relevant; ii) 85% have improved their knowledge/ability to assess soil moisture compared to prior to the project, with the most used indicator of soil moisture still being rain fall records; and iii) 100% have indicated they will continue to use some form of the technology to monitor soil moisture levels in the future. It is hoped that continued access to this information will assist informed input decisions. This will minimise inputs in low decile years with a low soil moisture base and maximise yield potential in more favourable conditions based on soil moisture and positive seasonal forecasts

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Remote sensing of soil moisture using airborne hyperspectral data

USGS Publications Warehouse

Finn, M.; Lewis, M.; Bosch, D.; Giraldo, Mario; Yamamoto, K.; Sullivan, D.; Kincaid, R.; Luna, R.; Allam, G.; Kvien, Craig; Williams, M.

2011-01-01

Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.

Remote sensing of soil moisture using airborne hyperspectral data

USGS Publications Warehouse

Finn, Michael P.; Lewis, Mark (David); Bosch, David D.; Giraldo, Mario; Yamamoto, Kristina H.; Sullivan, Dana G.; Kincaid, Russell; Luna, Ronaldo; Allam, Gopala Krishna; Kvien, Craig; Williams, Michael S.

2011-01-01

Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R 2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.

Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

USGS Publications Warehouse

Gu, Yingxin; Hunt, E.; Wardlow, B.; Basara, J.B.; Brown, Jesslyn F.; Verdin, J.P.

2008-01-01

The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r???0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r???0.22). Copyright 2008 by the American Geophysical Union.

Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data

NASA Astrophysics Data System (ADS)

Moradizadeh, Mina; Saradjian, Mohammad R.

2018-03-01

Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.

On the Soil Roughness Parameterization Problem in Soil Moisture Retrieval of Bare Surfaces from Synthetic Aperture Radar

PubMed Central

Verhoest, Niko E.C; Lievens, Hans; Wagner, Wolfgang; Álvarez-Mozos, Jesús; Moran, M. Susan; Mattia, Francesco

2008-01-01

Synthetic Aperture Radar has shown its large potential for retrieving soil moisture maps at regional scales. However, since the backscattered signal is determined by several surface characteristics, the retrieval of soil moisture is an ill-posed problem when using single configuration imagery. Unless accurate surface roughness parameter values are available, retrieving soil moisture from radar backscatter usually provides inaccurate estimates. The characterization of soil roughness is not fully understood, and a large range of roughness parameter values can be obtained for the same surface when different measurement methodologies are used. In this paper, a literature review is made that summarizes the problems encountered when parameterizing soil roughness as well as the reported impact of the errors made on the retrieved soil moisture. A number of suggestions were made for resolving issues in roughness parameterization and studying the impact of these roughness problems on the soil moisture retrieval accuracy and scale. PMID:27879932

Application of neural network to remote sensing of soil moisture using theoretical polarimetric backscattering coefficients

NASA Technical Reports Server (NTRS)

Wang, L.; Shin, R. T.; Kong, J. A.; Yueh, S. H.

1993-01-01

This paper investigates the potential application of neural network to inversion of soil moisture using polarimetric remote sensing data. The neural network used for the inversion of soil parameters is multi-layer perceptron trained with the back-propagation algorithm. The training data include the polarimetric backscattering coefficients obtained from theoretical surface scattering models together with an assumed nominal range of soil parameters which are comprised of the soil permittivity and surface roughness parameters. Soil permittivity is calculated from the soil moisture and the assumed soil texture based on an empirical formula at C-, L-, and P-bands. The rough surface parameters for the soil surface, which is described by the Gaussian random process, are the root-mean-square (rms) height and correlation length. For the rough surface scattering, small perturbation method is used for the L-band frequency, and Kirchhoff approximation is used for the C-band frequency to obtain the corresponding backscattering coefficients. During the training, the backscattering coefficients are the inputs to the neural net and the output from the net are compared with the desired soil parameters to adjust the interconnecting weights. The process is repeated for each input-output data entry and then for the entire training data until convergence is reached. After training, the backscattering coefficients are applied to the trained neural net to retrieve the soil parameters which are compared with the desired soil parameters to verify the effectiveness of this technique. Several cases are examined. First, for simplicity, the correlation length and rms height of the soil surface are fixed while soil moisture is varied. Soil moisture obtained using the neural networks with either L-band or C-band backscattering coefficients for the HH and VV polarizations as inputs is in good agreement with the desired soil moisture. The neural net output matches the desired output for the soil moisture range of 16 to 60 percent for the C-band case. The next case investigated is to vary both soil moisture and rms height while keeping the correlation length fixed. For this case, C-band backscattering coefficients are not sufficient for retrieving two parameters because the Kirchhoff approximation gives the same HH and VV backscattering coefficients. Therefore, the backscattering coefficients at two different frequency bands are necessary to find both the soil moisture and rms height. Finally, the neural nets are also applied to simultaneously invert soil moisture, rms height, and correlation length. Overall, the soil moisture retrieved from the neural network agrees very well with the desired soil moisture. This suggests that the neural network shows potential for retrieval of soil parameters from remote sensing data.

The impact of fog on soil moisture dynamics in the Namib Desert

NASA Astrophysics Data System (ADS)

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Vogt, Roland; Li, Lin; Seely, Mary K.

2018-03-01

Soil moisture is a crucial component supporting vegetation dynamics in drylands. Despite increasing attention on fog in dryland ecosystems, the statistical characterization of fog distribution and how fog affects soil moisture dynamics have not been seen in literature. To this end, daily fog records over two years (Dec 1, 2014-Nov 1, 2016) from three sites within the Namib Desert were used to characterize fog distribution. Two sites were located within the Gobabeb Research and Training Center vicinity, the gravel plains and the sand dunes. The third site was located at the gravel plains, Kleinberg. A subset of the fog data during rainless period was used to investigate the effect of fog on soil moisture. A stochastic modeling framework was used to simulate the effect of fog on soil moisture dynamics. Our results showed that fog distribution can be characterized by a Poisson process with two parameters (arrival rate λ and average depth α (mm)). Fog and soil moisture observations from eighty (Aug 19, 2015-Nov 6, 2015) rainless days indicated a moderate positive relationship between soil moisture and fog in the Gobabeb gravel plains, a weaker relationship in the Gobabeb sand dunes while no relationship was observed at the Kleinberg site. The modeling results suggested that mean and major peaks of soil moisture dynamics can be captured by the fog modeling. Our field observations demonstrated the effects of fog on soil moisture dynamics during rainless periods at some locations, which has important implications on soil biogeochemical processes. The statistical characterization and modeling of fog distribution are of great value to predict fog distribution and investigate the effects of potential changes in fog distribution on soil moisture dynamics.

Evaluating the influence of antecedent soil moisture on variability of the North American Monsoon precipitation in the coupled MM5/VIC modeling system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Chunmei; Leung, Lai R.; Gochis, David

2009-11-29

The influence of antecedent soil moisture on North American monsoon system (NAMS) precipitation variability was explored using the MM5 mesoscale model coupled with the Variable Infiltration Capacity (VIC) land surface model. Sensitivity experiments were performed with extreme wet and dry initial soil moisture conditions for both the 1984 wet monsoon year and the 1989 dry year. The MM5-VIC model reproduced the key features of NAMS in 1984 and 1989 especially over northwestern Mexico. Our modeling results indicate that the land surface has memory of the initial soil wetness prescribed at the onset of the monsoon that persists over most ofmore » the region well into the monsoon season (e.g. until August). However, in contrast to the classical thermal contrast concept, where wetter soils lead to cooler surface temperatures, less land-sea thermal contrast, weaker monsoon circulations and less precipitation, the coupled model consistently demonstrated a positive soil moisture – precipitation feedback. Specifically, anomalously wet premonsoon soil moisture always lead to enhanced monsoon precipitation, and the reverse was also true. The surface temperature changes induced by differences in surface energy flux partitioning associated with pre-monsoon soil moisture anomalies changed the surface pressure and consequently the flow field in the coupled model, which in turn changed moisture convergence and, accordingly, precipitation patterns. Both the largescale circulation change and local land-atmospheric interactions in response to premonsoon soil moisture anomalies play important roles in the coupled model’s positive soil moisture monsoon precipitation feedback. However, the former may be sensitive to the strength and location of the thermal anomalies, thus leaving open the possibility of both positive and negative soil moisture precipitation feedbacks.« less

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary

2014-01-01

Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

A study of the influence of soil moisture on future precipitation

NASA Technical Reports Server (NTRS)

Fennessy, M. J.; Sud, Y. C.

1983-01-01

Forty years of precipitation and surface temperature data observed over 261 Local Climatic Data (LCD) stations in the Continental United States was utilized in a ground hydrology model to yield soil moisture time series at each station. A month-by-month soil moisture dataset was constructed for each year. The monthly precipitation was correlated with antecedent monthly precipitation, soil moisture and vapotranspiration separately. The maximum positive correlation is found to be in the drought prone western Great Plains region during the latter part of summer. There is also some negative correlation in coastal regions. The correlations between soil moisture and precipitation particularly in the latter part of summer, suggest that large scale droughts over extended periods may be partially maintained by the feedback influence of soil moisture on rainfall. In many other regions the lack of positive correlation shows that there is no simple answer such as higher land-surface evapotranspiration leads to more precipitation, and points out the complexity of the influence of soil moisture on the ensuring precipitation.

Misrepresentation and amendment of soil moisture in conceptual hydrological modelling

NASA Astrophysics Data System (ADS)

Zhuo, Lu; Han, Dawei

2016-04-01

Although many conceptual models are very effective in simulating river runoff, their soil moisture schemes are generally not realistic in comparison with the reality (i.e., getting the right answers for the wrong reasons). This study reveals two significant misrepresentations in those models through a case study using the Xinanjiang model which is representative of many well-known conceptual hydrological models. The first is the setting of the upper limit of its soil moisture at the field capacity, due to the 'holding excess runoff' concept (i.e., runoff begins on repletion of its storage to the field capacity). The second is neglect of capillary rise of water movement. A new scheme is therefore proposed to overcome those two issues. The amended model is as effective as its original form in flow modelling, but represents more logically realistic soil water processes. The purpose of the study is to enable the hydrological model to get the right answers for the right reasons. Therefore, the new model structure has a better capability in potentially assimilating soil moisture observations to enhance its real-time flood forecasting accuracy. The new scheme is evaluated in the Pontiac catchment of the USA through a comparison with satellite observed soil moisture. The correlation between the XAJ and the observed soil moisture is enhanced significantly from 0.64 to 0.70. In addition, a new soil moisture term called SMDS (Soil Moisture Deficit to Saturation) is proposed to complement the conventional SMD (Soil Moisture Deficit).

An integrated GIS application system for soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Wang, Di; Shen, Runping; Huang, Xiaolong; Shi, Chunxiang

2014-11-01

The gaps in knowledge and existing challenges in precisely describing the land surface process make it critical to represent the massive soil moisture data visually and mine the data for further research.This article introduces a comprehensive soil moisture assimilation data analysis system, which is instructed by tools of C#, IDL, ArcSDE, Visual Studio 2008 and SQL Server 2005. The system provides integrated service, management of efficient graphics visualization and analysis of land surface data assimilation. The system is not only able to improve the efficiency of data assimilation management, but also comprehensively integrate the data processing and analysis tools into GIS development environment. So analyzing the soil moisture assimilation data and accomplishing GIS spatial analysis can be realized in the same system. This system provides basic GIS map functions, massive data process and soil moisture products analysis etc. Besides,it takes full advantage of a spatial data engine called ArcSDE to effeciently manage, retrieve and store all kinds of data. In the system, characteristics of temporal and spatial pattern of soil moiture will be plotted. By analyzing the soil moisture impact factors, it is possible to acquire the correlation coefficients between soil moisture value and its every single impact factor. Daily and monthly comparative analysis of soil moisture products among observations, simulation results and assimilations can be made in this system to display the different trends of these products. Furthermore, soil moisture map production function is realized for business application.

On-irrigator pasture soil moisture sensor

NASA Astrophysics Data System (ADS)

Eng-Choon Tan, Adrian; Richards, Sean; Platt, Ian; Woodhead, Ian

2017-02-01

In this paper, we presented the development of a proximal soil moisture sensor that measured the soil moisture content of dairy pasture directly from the boom of an irrigator. The proposed sensor was capable of soil moisture measurements at an accuracy of  ±5% volumetric moisture content, and at meter scale ground area resolutions. The sensor adopted techniques from the ultra-wideband radar to enable measurements of ground reflection at resolutions that are smaller than the antenna beamwidth of the sensor. An experimental prototype was developed for field measurements. Extensive field measurements using the developed prototype were conducted on grass pasture at different ground conditions to validate the accuracy of the sensor in performing soil moisture measurements.

Soil moisture and the persistence of North American drought

NASA Technical Reports Server (NTRS)

Oglesby, Robert J.; Erickson, David J., III

1989-01-01

Numerical sensitivity experiments on the effects of soil moisture on North American summertime climate are performed using a 12-layer global atmospheric general circulation model. Consideration is given to the hypothesis that reduced soil moisture may induce and amplify warm, dry summers of midlatitude continental interiors. The simulations resemble the conditions of the summer of 1988, including an extensive drought over much of North America. It is found that a reduction in soil moisture leads to an increase in surface temperature, lower surface pressure, increased ridging aloft, and a northward shift of the jet stream. It is shown that low-level moisture advection from the Gulf of Mexico is important in the maintenance of persistent soil moisture deficits.

Soil-moisture sensors and irrigation management

USDA-ARS?s Scientific Manuscript database

This agricultural irrigation seminar will cover the major classes of soil-moisture sensors; their advantages and disadvantages; installing and reading soil-moisture sensors; and using their data for irrigation management. The soil water sensor classes include the resistance sensors (gypsum blocks, g...

Soil Moisture Retrieval with Airborne PALS Instrument over Agricultural Areas in SMAPVEX16

NASA Technical Reports Server (NTRS)

Colliander, Andreas; Jackson, Thomas J.; Cosh, Mike; Misra, Sidharth; Bindlish, Rajat; Powers, Jarrett; McNairn, Heather; Bullock, P.; Berg, A.; Magagi, A.;

Measuring Soil Moisture using the Signal Strength of Buried Bluetooth Devices.

NASA Astrophysics Data System (ADS)

Hut, R.; Campbell, C. S.

2015-12-01

A low power bluetooth Low Energy (BLE) device is burried 20cm into the soil and a smartphone is placed on top of the soil to test if bluetooth signal strength can be related to soil moisture. The smartphone continuesly records and stores bluetooth signal strength of the device. The soil is artifcially wetted and drained. Results show a relation between BLE signal strength and soil moisture that could be used to measure soil moisture using these off-the-shelf consumer electronics. This opens the possibily to develop sensors that can be buried into the soil, possibly below the plow-line. These sensors can measure local parameters such as electric conductivity, ph, pressure, etc. Readings would be uploaded to a device on the surface using BLE. The signal strength of this BLE would be an (additional) measurement of soil moisture.

An empirical model for the complex dielectric permittivity of soils as a function of water content

NASA Technical Reports Server (NTRS)

Wang, J. R.; Chmugge, T. J.

1978-01-01

The recent measurements on the dielectric properties of soils shows that the variation of dielectric constant with moisture content depends on soil types. The observed dielectric constant increases only slowly with moisture content up to a transition point. Beyond the transition it increases rapidly with moisture content. The moisture value of transition region was found to be higher for high clay content soils than for sandy soils. Many mixing formulas were compared with, and were found incompatible with, the measured dielectric variations of soil-water mixtures. A simple empirical model was proposed to describe the dielectric behavior of ths soil-water mixtures. The relationship between transition moisture and wilting point provides a means of estimating soil dielectric properties on the basis of texture information.

Surface soil moisture retrieval over a Mediterranean semi-arid region using X-band TerraSAR-X SAR data

NASA Astrophysics Data System (ADS)

Azza, Gorrab; Zribi, Mehrez; Baghdadi, Nicolas; Mougenot, Bernard; Boulet, Gilles; Lili-Chabaane, Zohra

2015-04-01

Mapping surface soil moisture with meter-scale spatial resolution is appropriate for multi- domains particularly hydrology and agronomy. It allows water resources and irrigation management decisions, drought monitoring and validation of multi-hydrological water balance models. In the last years, various studies have demonstrated the large potential of radar remote sensing data, mainly from C frequency band, to retrieve soil moisture. However, the accuracy of the soil moisture estimation, by inversing backscattering radar coefficients (σ°), is affected by the influence of surface roughness and vegetation biomass contributions. In recent years, different empirical, semi empirical and physical approaches are developed for bare soil conditions, to estimate accurately spatial soil moisture variability. In this study, we propose an approach based on the change detection method for the retrieval of surface soil moisture at a higher spatial resolution. The proposal algorithm combines multi-temporal X-band SAR images (TerraSAR-X) with different continuous thetaprobe measurements. Seven thetaprobe stations are installed at different depths over the central semi arid region of Tunisia (9°23' - 10°17' E, 35° 1'-35°55' N). They cover approximately the entire of our study site and provide regional scale information. Ground data were collected over agricultural bare soil fields simultaneously to various TerraSAR-X data acquired during 2013-2014 and 2014-2015. More than fourteen test fields were selected for each spatial acquisition campaign, with variations in soil texture and in surface soil roughness. For each date, we considered the volumetric water content with thetaprobe instrument and gravimetric sampling; we measured also the roughness parameters with pin profilor. To retrieve soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our analyses are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of the measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: On the first one, we applied the change detection approach between successive radar images (∆σ°) assuming unchanged soil roughness effects. Our soil moisture retrieval algorithm was validated on the basis of comparisons between estimated and in situ soil moisture measurements over test fields. Using this option, results have shown an accuracy (RMSE) of about 4.8 %. Secondly, we corrected the sensitivity of the radar backscatter images to the surface roughness variability. Results have shown a reduction of the difference between the retrieved soil moisture and ground measurements with an RMSE about 3.7%.

The hysteretic evapotranspiration—Vapor pressure deficit relation

NASA Astrophysics Data System (ADS)

Zhang, Quan; Manzoni, Stefano; Katul, Gabriel; Porporato, Amilcare; Yang, Dawen

2014-02-01

Diurnal hysteresis between evapotranspiration (ET) and vapor pressure deficit (VPD) was reported in many ecosystems, but justification for its onset and magnitude remains incomplete with biotic and abiotic factors invoked as possible explanations. To place these explanations within a holistic framework, the occurrence of hysteresis was theoretically assessed along a hierarchy of model systems where both abiotic and biotic components are sequentially added. Lysimeter evaporation (E) measurements and model calculations using the Penman equation were used to investigate the effect of the time lag between net radiation and VPD on the hysteresis in the absence of any biotic effects. Modulations from biotic effects on the ET-VPD hysteresis were then added using soil-plant-atmosphere models of different complexities applied to a grassland ecosystem. The results suggest that the hysteresis magnitude depends on the radiation-VPD lag, while the plant and soil water potentials are both key factors modulating the hysteretic ET-VPD relation as soil moisture declines. In particular, larger hysteresis magnitude is achieved at less negative leaf water potential, root water potential, and soil water potential. While plant hydraulic capacitance affects the leaf water potential-ET relation, it has negligible effects on the ET-VPD hysteresis. Therefore, the genesis and magnitude of the ET-VPD hysteresis are controlled directly by both abiotic factors such as soil water availability, biotic factors (leaf and root water potentials, which in turn depend on soil moisture), and the time lag between radiation and VPD.

Analysis of in situ resources for the Soil Moisture Active Passive Validation Experiments in 2015 and 2016

NASA Astrophysics Data System (ADS)

Cosh, M. H.; Jackson, T. J.; Colliander, A.; Bindlish, R.; McKee, L.; Goodrich, D. C.; Prueger, J. H.; Hornbuckle, B. K.; Coopersmith, E. J.; Holifield Collins, C.; Smith, J.

2016-12-01

With the launch of the Soil Moisture Active Passive Mission (SMAP) in 2015, a new era of soil moisture monitoring was begun. Soil moisture is available on a near daily basis at a 36 km resolution for the globe. But this dataset is only as valuable if its products are accurate and reliable. Therefore, in order to demonstrate the accuracy of the soil moisture product, NASA enacted an extensive calibration and validation program with many in situ soil moisture networks contributing data across a variety of landscape regimes. However, not all questions can be answered by these networks. As a result, two intensive field experiments were executed to provide more detailed reference points for calibration and validation. Multi-week field campaigns were conducted in Arizona and Iowa at the USDA Agricultural Research Service Walnut Gulch and South Fork Experimental Watersheds, respectively. Aircraft observations were made to provide a high resolution data product. Soil moisture, soil roughness and vegetation data were collected at high resolution to provide a downscaled dataset to compare against aircraft and satellite estimates.

Sources of seasonal water-supply forecast skill in the western US

USGS Publications Warehouse

Dettinger, Michael

2007-01-01

Many water supplies in the western US depend on water that is stored in snowpacks and reservoirs during the cool, wet seasons for release and use in the following warm seasons. Managers of these water supplies must decide each winter how much water will be available in subsequent seasons so that they can proactively capture and store water and can make reliable commitments for later deliveries. Long-lead water-supply forecasts are thus important components of water managers' decisionmaking. Present-day operational water-supply forecasts draw skill from observations of the amount of water in upland snowpacks, along with estimates of the amount of water otherwise available (often via surrogates for antecedent precipitation, soil moisture or baseflows). Occasionally, the historical hydroclimatic influences of various global climate conditions may be factored in to forecasts. The relative contributions of (potential) forecast skill for January-March and April-July seasonal water- supply availability from these sources are mapped across the western US as lag correlations among elements of the inputs and outputs from a physically based, regional land-surface hydrology model of the western US from 1950-1999. Information about snow-water contents is the most valuable predictor for forecasts made through much of the cool-season but, before the snows begin to fall, indices of El Nino-Southern Oscillation are the primary source of whatever meager skill is available. The contributions to forecast skill made available by knowledge of antecedent flows (a traditional predictor) and soil moisture at the time the long-lead forecast is issued are compared, to gain insights into the potential usefulness of new soil-moisture monitoring options in the region. When similar computations are applied to simulated flows under historical conditions, but with a uniform +2°C warming imposed, the widespread diminution of snowpacks reduces forecast skills, although skill contributed by measures of antecedent moisture conditions (soil moisture or baseflows) grow in stature, relative to snowpacks, in partial compensation. Forecast skills, e.g., of March forecasts for April-July water supplies from those parts of the region that yield the majority of the runoff, decline by an average of about 15% of captured variance in response to the imposed warming.

Influence of Hydrological Flow Paths on Rates and Forms of Nitrogen Losses from Mediterranean Watersheds

NASA Astrophysics Data System (ADS)

Lohse, K. A.; Sanderman, J.; Amundson, R. G.

2005-12-01

Patterns of precipitation and runoff in California are changing and likely to influence the structure and functioning of watersheds. Studies have demonstrated that hydrologic flushing during seasonal transitions in Mediterranean ecosystems can exert a strong control on nitrogen (N) export, yet few studies have examined the influence of different hydrological flow paths on rates and forms of nitrogen (N) losses. Here we illuminate the influence of variations in precipitation and hydrological pathways on the rate and form of N export along a toposequence of a well-characterized Mediterranean catchment in northern California. As a part of a larger study examining particulate and dissolved carbon loss, we analyzed seasonal patterns of dissolved organic nitrogen (DON), nitrate and ammonium concentrations in rainfall, throughfall, matrix and preferential flow, and stream samples over the course of one water year. We also analyzed seasonal soil N dynamics along this toposequence. During the transition to the winter rain season, but prior to any soil water displacement to the stream, DON and nitrate moved through near-surface soils as preferential flow. Once hillslope soils became saturated, saturated subsurface flow flushed nitrate from the hollow resulting in high stream nitrate/DON concentrations. Between storms, stream nitrate/DON concentrations were lower and appeared to reflect deep subsurface water flow chemistry. During the transition to the wet season, rates of soil nitrate production were high in the hollow relative to the hillslope soils. In the spring, these rates systematically declined as soil moisture decreased. Results from our study suggest seasonal fluctuations in soil moisture control soil N cycling and seasonal changes in the hydrological connection between hillslope soils and streams control the seasonal production and export of hydrologic N.

Arbuscular mycorrhizal fungi make a complex contribution to soil aggregation

NASA Astrophysics Data System (ADS)

McGee, Peter; Daynes, Cathal; Damien, Field

2013-04-01

Soil aggregates contain solid and fluid components. Aggregates develop as a consequence of the organic materials, plants and hyphae of arbuscular mycorrhizal (AM) fungi acting on the solid phase. Various correlative studies indicate hyphae of AM fungi enmesh soil particles, but their impact on the pore space is poorly understood. Hyphae may penetrate between particles, remove water from interstitial spaces, and otherwise re-arrange the solid phase. Thus we might predict that AM fungi also change the pore architecture of aggregates. Direct observations of pore architecture of soil, such as by computer-aided tomography (CT), is difficult. The refractive natures of solid and biological material are similar. The plant-available water in various treatments allows us to infer changes in pore architecture. Our experimental studies indicate AM fungi have a complex role in the formation and development of aggregates. Soils formed from compost and coarse subsoil materials were planted with mycorrhizal or non-mycorrhizal seedlings and the resultant soils compared after 6 or 14 months in separate experiments. As well as enmeshing particles, AM fungi were associated with the development of a complex pore space and greater pore volume. Even though AM fungi add organic matter to soil, the modification of pore space is not correlated with organic carbon. In a separate study, we visualised hyphae of AM fungi in a coarse material using CT. In this study, hyphae appeared to grow close to the surfaces of particles with limited ramification across the pore spaces. Hyphae of AM fungi appear to utilise soil moisture for their growth and development of mycelium. The strong correlation between moisture and hyphae has profound implications for soil aggregation, plant utilisation of soil water, and the distribution of water as water availability declines.

Soil moisture estimation using reflected solar and emitted thermal infrared radiation

NASA Technical Reports Server (NTRS)

Jackson, R. D.; Cihlar, J.; Estes, J. E.; Heilman, J. L.; Kahle, A.; Kanemasu, E. T.; Millard, J.; Price, J. C.; Wiegand, C. L.

1978-01-01

Classical methods of measuring soil moisture such as gravimetric sampling and the use of neutron moisture probes are useful for cases where a point measurement is sufficient to approximate the water content of a small surrounding area. However, there is an increasing need for rapid and repetitive estimations of soil moisture over large areas. Remote sensing techniques potentially have the capability of meeting this need. The use of reflected-solar and emitted thermal-infrared radiation, measured remotely, to estimate soil moisture is examined.

Passive Microwave Remote Sensing of Soil Moisture

NASA Technical Reports Server (NTRS)

Njoku, Eni G.; Entekhabi, Dara

1996-01-01

Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earth's land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are limited to regions that have either bare soil or low to moderate amounts of vegetation cover. A particular advantage of passive microwave sensors is that in the absence of significant vegetation cover soil moisture is the dominant effect on the received signal. The spatial resolutions of passive Microwave soil moisture sensors currently considered for space operation are in the range 10-20 km. The most useful frequency range for soil moisture sensing is 1-5 GHz. System design considerations include optimum choice of frequencies, polarizations, and scanning configurations, based on trade-offs between requirements for high vegetation penetration capability, freedom from electromagnetic interference, manageable antenna size and complexity, and the requirement that a sufficient number of information channels be available to correct for perturbing geophysical effects. This paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods. Particularly promising are methods for optimally assimilating passive microwave data into hydrologic models. Further studies are needed to investigate the effects on microwave observations of within-footprint spatial heterogeneity of vegetation cover and subsurface soil characteristics, and to assess the limitations imposed by heterogeneity on the retrievability of large-scale soil moisture information from remote observations.

The sensitivity of numerically simulated climates to land-surface boundary conditions

NASA Technical Reports Server (NTRS)

Mintz, Y.

1982-01-01

Eleven sensitivity experiments that were made with general circulation models to see how land-surface boundary conditions can influence the rainfall, temperature, and motion fields of the atmosphere are discussed. In one group of experiments, different soil moistures or albedos are prescribed as time-invariant boundary conditions. In a second group, different soil moistures or different albedos are initially prescribed, and the soil moisture (but not the albedo) is allowed to change with time according to the governing equations for soil moisture. In a third group, the results of constant versus time-dependent soil moistures are compared.

Application of IEM model on soil moisture and surface roughness estimation

NASA Technical Reports Server (NTRS)

Shi, Jiancheng; Wang, J. R.; Oneill, P. E.; Hsu, A. Y.; Engman, E. T.

1995-01-01

Monitoring spatial and temporal changes of soil moisture are of importance to hydrology, meteorology, and agriculture. This paper reports a result on study of using L-band SAR imagery to estimate soil moisture and surface roughness for bare fields. Due to limitations of the Small Perturbation Model, it is difficult to apply this model on estimation of soil moisture and surface roughness directly. In this study, we show a simplified model derived from the Integral Equation Model for estimation of soil moisture and surface roughness. We show a test of this model using JPL L-band AIRSAR data.

Remotely sensed soil moisture input to a hydrologic model

NASA Technical Reports Server (NTRS)

Engman, E. T.; Kustas, W. P.; Wang, J. R.

1989-01-01

The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.

Direct and indirect effects of atmospheric conditions and soil moisture on surface energy partitioning revealed by a prolonged drought at a temperate forest site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, Lianhong; Meyers, T. P.; Pallardy, Stephen G.

2006-01-01

The purpose of this paper is to examine the mechanism that controls the variation of surface energy partitioning between latent and sensible heat fluxes at a temperate deciduous forest site in central Missouri, USA. Taking advantage of multiple micrometeorological and ecophysiological measurements and a prolonged drought in the middle of the 2005 growing season at this site, we studied how soil moisture, atmospheric vapor pressure deficit (VPD), and net radiation affected surface energy partitioning. We stratified these factors to minimize potential confounding effects of correlation among them. We found that all three factors had direct effects on surface energy partitioning,more » but more important, all three factors also had crucial indirect effects. The direct effect of soil moisture was characterized by a rapid decrease in Bowen ratio with increasing soil moisture when the soil was dry and by insensitivity of Bowen ratio to variations in soil moisture when the soil was wet. However, the rate of decrease in Bowen ratio when the soil was dry and the level of soil moisture above which Bowen ratio became insensitive to changes in soil moisture depended on atmospheric conditions. The direct effect of increased net radiation was to increase Bowen ratio. The direct effect of VPD was very nonlinear: Increased VPD decreased Bowen ratio at low VPD but increased Bowen ratio at high VPD. The indirect effects were much more complicated. Reduced soil moisture weakened the influence of VPD but enhanced the influence of net adiation on surface energy partitioning. Soil moisture also controlled how net radiation influenced the relationship between surface energy partitioning and VPD and how VPD affected the relationship between surface energy partitioning and net radiation. Furthermore, both increased VPD and increased net radiation enhanced the sensitivity of Bowen ratio to changes in soil moisture and the effect of drought on surface energy partitioning. The direct and indirect effects of atmospheric conditions and soil moisture on surface energy partitioning identified in this paper provide a target for testing atmospheric general circulation models in their representation of land-atmosphere coupling.« less

[Simulation of cropland soil moisture based on an ensemble Kalman filter].

PubMed

Liu, Zhao; Zhou, Yan-Lian; Ju, Wei-Min; Gao, Ping

2011-11-01

By using an ensemble Kalman filter (EnKF) to assimilate the observed soil moisture data, the modified boreal ecosystem productivity simulator (BEPS) model was adopted to simulate the dynamics of soil moisture in winter wheat root zones at Xuzhou Agro-meteorological Station, Jiangsu Province of China during the growth seasons in 2000-2004. After the assimilation of observed data, the determination coefficient, root mean square error, and average absolute error of simulated soil moisture were in the ranges of 0.626-0.943, 0.018-0.042, and 0.021-0.041, respectively, with the simulation precision improved significantly, as compared with that before assimilation, indicating the applicability of data assimilation in improving the simulation of soil moisture. The experimental results at single point showed that the errors in the forcing data and observations and the frequency and soil depth of the assimilation of observed data all had obvious effects on the simulated soil moisture.

Exploiting Soil Moisture, Precipitation, and Streamflow Observations to Evaluate Soil Moisture/Runoff Coupling in Land Surface Models

NASA Astrophysics Data System (ADS)

Crow, W. T.; Chen, F.; Reichle, R. H.; Xia, Y.; Liu, Q.

2018-05-01

Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in prestorm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the National Aeronautics and Space Administration Soil Moisture Active Passive Level-4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between prestorm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation volume converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltration-excess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent subsurface stormflow or saturation-excess runoff generation processes.

Land-atmosphere coupling and soil moisture memory contribute to long-term agricultural drought

NASA Astrophysics Data System (ADS)

Kumar, S.; Newman, M.; Lawrence, D. M.; Livneh, B.; Lombardozzi, D. L.

2017-12-01

We assessed the contribution of land-atmosphere coupling and soil moisture memory on long-term agricultural droughts in the US. We performed an ensemble of climate model simulations to study soil moisture dynamics under two atmospheric forcing scenarios: active and muted land-atmosphere coupling. Land-atmosphere coupling contributes to a 12% increase and 36% decrease in the decorrelation time scale of soil moisture anomalies in the US Great Plains and the Southwest, respectively. These differences in soil moisture memory affect the length and severity of modeled drought. Consequently, long-term droughts are 10% longer and 3% more severe in the Great Plains, and 15% shorter and 21% less severe in the Southwest. An analysis of Coupled Model Intercomparsion Project phase 5 data shows four fold uncertainty in soil moisture memory across models that strongly affects simulated long-term droughts and is potentially attributable to the differences in soil water storage capacity across models.

Evaluation of a simple, point-scale hydrologic model in simulating soil moisture using the Delaware environmental observing system

NASA Astrophysics Data System (ADS)

Legates, David R.; Junghenn, Katherine T.

2018-04-01

Many local weather station networks that measure a number of meteorological variables (i.e. , mesonetworks) have recently been established, with soil moisture occasionally being part of the suite of measured variables. These mesonetworks provide data from which detailed estimates of various hydrological parameters, such as precipitation and reference evapotranspiration, can be made which, when coupled with simple surface characteristics available from soil surveys, can be used to obtain estimates of soil moisture. The question is Can meteorological data be used with a simple hydrologic model to estimate accurately daily soil moisture at a mesonetwork site? Using a state-of-the-art mesonetwork that also includes soil moisture measurements across the US State of Delaware, the efficacy of a simple, modified Thornthwaite/Mather-based daily water balance model based on these mesonetwork observations to estimate site-specific soil moisture is determined. Results suggest that the model works reasonably well for most well-drained sites and provides good qualitative estimates of measured soil moisture, often near the accuracy of the soil moisture instrumentation. The model exhibits particular trouble in that it cannot properly simulate the slow drainage that occurs in poorly drained soils after heavy rains and interception loss, resulting from grass not being short cropped as expected also adversely affects the simulation. However, the model could be tuned to accommodate some non-standard siting characteristics.

Dynamics and characteristics of soil temperature and moisture of active layer in central Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhao, L.; Hu, G.; Wu, X.; Tian, L.

2017-12-01

Research on the hydrothermal properties of active layer during the thawing and freezing processes was considered as a key question to revealing the heat and moisture exchanges between permafrost and atmosphere. The characteristics of freezing and thawing processes at Tanggula (TGL) site in permafrost regions on the Tibetan Plateau, the results revealed that the depth of daily soil temperature transmission was about 40 cm shallower during thawing period than that during the freezing period. Soil warming process at the depth above 140 cm was slower than the cooling process, whereas they were close below 140 cm depth. Moreover, the hydro-thermal properties differed significantly among different stages. Precipitation caused an obviously increase in soil moisture at 0-20 cm depth. The vertical distribution of soil moisture could be divided into two main zones: less than 12% in the freeze state and greater than 12% in the thaw state. In addition, coupling of moisture and heat during the freezing and thawing processes also showed that soil temperature decreased faster than soil moisture during the freezing process. At the freezing stage, soil moisture exhibited an exponential relationship with the absolute soil temperature. Energy consumed for water-ice conversion during the freezing process was 149.83 MJ/m2 and 141.22 MJ/m2 in 2011 and 2012, respectively, which was estimated by the soil moisture variation.

Generating large-scale estimates from sparse, in-situ networks: multi-scale soil moisture modeling at ARS watersheds for NASA’s soil moisture active passive (SMAP) calibration/validation mission

USDA-ARS?s Scientific Manuscript database

NASA’s SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networ...

Inventory of File gdas1.t06z.sfluxgrbf00.grib2

Science.gov Websites

analysis Volumetric Soil Moisture Content [Fraction] 007 0.1-0.4 m below ground SOILW analysis Volumetric Soil Moisture Content [Fraction] 008 0-0.1 m below ground TMP analysis Temperature [K] 009 0.1-0.4 m Volumetric Soil Moisture Content [Fraction] 068 1-2 m below ground SOILW analysis Volumetric Soil Moisture

Analysis of in situ resources of for the Soil Moisture Active Passive Validation Experiments in 2015 and 2016

USDA-ARS?s Scientific Manuscript database

With the launch of the Soil Moisture Active Passive Mission (SMAP) in 2015, a new era of soil moisture monitoring was begun. Soil moisture is available on a near daily basis at a 36 km resolution for the globe. But this dataset is only as valuable if its products are accurate and reliableas its acc...

SMAP soil moisture drying more rapid than observed in situ following rainfall events

USDA-ARS?s Scientific Manuscript database

We examine soil drying rates by comparing observations from the NASA Soil Moisture Active Passive (SMAP) mission to surface soil moisture from in situ probes during drydown periods at SMAP validation sites. SMAP and in situ probes record different soil drying dynamics after rainfall. We modeled this...

A Round Robin evaluation of AMSR-E soil moisture retrievals

NASA Astrophysics Data System (ADS)

Mittelbach, Heidi; Hirschi, Martin; Nicolai-Shaw, Nadine; Gruber, Alexander; Dorigo, Wouter; de Jeu, Richard; Parinussa, Robert; Jones, Lucas A.; Wagner, Wolfgang; Seneviratne, Sonia I.

2014-05-01

Large-scale and long-term soil moisture observations based on remote sensing are promising data sets to investigate and understand various processes of the climate system including the water and biochemical cycles. Currently, the ESA Climate Change Initiative for soil moisture develops and evaluates a consistent global long-term soil moisture data set, which is based on merging passive and active remotely sensed soil moisture. Within this project an inter-comparison of algorithms for AMSR-E and ASCAT Level 2 products was conducted separately to assess the performance of different retrieval algorithms. Here we present the inter-comparison of AMSR-E Level 2 soil moisture products. These include the public data sets from University of Montana (UMT), Japan Aerospace and Space Exploration Agency (JAXA), VU University of Amsterdam (VUA; two algorithms) and National Aeronautics and Space Administration (NASA). All participating algorithms are applied to the same AMSR-E Level 1 data set. Ascending and descending paths of scaled surface soil moisture are considered and evaluated separately in daily and monthly resolution over the 2007-2011 time period. Absolute values of soil moisture as well as their long-term anomalies (i.e. removing the mean seasonal cycle) and short-term anomalies (i.e. removing a five weeks moving average) are evaluated. The evaluation is based on conventional measures like correlation and unbiased root-mean-square differences as well as on the application of the triple collocation method. As reference data set, surface soil moisture of 75 quality controlled soil moisture sites from the International Soil Moisture Network (ISMN) are used, which cover a wide range of vegetation density and climate conditions. For the application of the triple collocation method, surface soil moisture estimates from the Global Land Data Assimilation System are used as third independent data set. We find that the participating algorithms generally display a better performance for the descending compared to the ascending paths. A first classification of the sites defined by geographical locations show that the algorithms have a very similar average performance. Further classifications of the sites by land cover types and climate regions will be conducted which might result in a more diverse performance of the algorithms.

Land surface dynamics monitoring using microwave passive satellite sensors

NASA Astrophysics Data System (ADS)

Guijarro, Lizbeth Noemi

Soil moisture, surface temperature and vegetation are variables that play an important role in our environment. There is growing demand for accurate estimation of these geophysical parameters for the research of global climate models (GCMs), weather, hydrological and flooding models, and for the application to agricultural assessment, land cover change, and a wide variety of other uses that meet the needs for the study of our environment. The different studies covered in this dissertation evaluate the capabilities and limitations of microwave passive sensors to monitor land surface dynamics. The first study evaluates the 19 GHz channel of the SSM/I instrument with a radiative transfer model and in situ datasets from the Illinois stations and the Oklahoma Mesonet to retrieve land surface temperature and surface soil moisture. The surface temperatures were retrieved with an average error of 5 K and the soil moisture with an average error of 6%. The results show that the 19 GHz channel can be used to qualitatively predict the spatial and temporal variability of surface soil moisture and surface temperature at regional scales. In the second study, in situ observations were compared with sensor observations to evaluate aspects of low and high spatial resolution at multiple frequencies with data collected from the Southern Great Plains Experiment (SGP99). The results showed that the sensitivity to soil moisture at each frequency is a function of wavelength and amount of vegetation. The results confirmed that L-band is more optimal for soil moisture, but each sensor can provide soil moisture information if the vegetation water content is low. The spatial variability of the emissivities reveals that resolution suffers considerably at higher frequencies. The third study evaluates C- and X-bands of the AMSR-E instrument. In situ datasets from the Soil Moisture Experiments (SMEX03) in South Central Georgia were utilized to validate the AMSR-E soil moisture product and to derive surface soil moisture with a radiative transfer model. The soil moisture was retrieved with an average error of 2.7% at X-band and 6.7% at C-band. The AMSR-E demonstrated its ability to successfully infer soil moisture during the SMEX03 experiment.

Application of Multitemporal Remotely Sensed Soil Moisture for the Estimation of Soil Physical Properties

NASA Technical Reports Server (NTRS)

Mattikalli, N. M.; Engman, E. T.; Jackson, T. J.; Ahuja, L. R.

1997-01-01

This paper demonstrates the use of multitemporal soil moisture derived from microwave remote sensing to estimate soil physical properties. The passive microwave ESTAR instrument was employed during June 10-18, 1992, to obtain brightness temperature (TB) and surface soil moisture data in the Little Washita watershed, Oklahoma. Analyses of spatial and temporal variations of TB and soil moisture during the dry-down period revealed a direct relationship between changes in T and soil moisture and soil physical (viz. texture) and hydraulic (viz. saturated hydraulic conductivity, K(sat)) properties. Statistically significant regression relationships were developed for the ratio of percent sand to percent clay (RSC) and K(sat), in terms of change components of TB and surface soil moisture. Validation of results using field measured values and soil texture map indicated that both RSC and K(sat) can be estimated with reasonable accuracy. These findings have potential applications of microwave remote sensing to obtain quick estimates of the spatial distributions of K(sat), over large areas for input parameterization of hydrologic models.

Experimental evidence and modelling of drought induced alternative stable soil moisture states

NASA Astrophysics Data System (ADS)

Robinson, David; Jones, Scott; Lebron, Inma; Reinsch, Sabine; Dominguez, Maria; Smith, Andrew; Marshal, Miles; Emmett, Bridget

2017-04-01

The theory of alternative stable states in ecosystems is well established in ecology; however, evidence from manipulation experiments supporting the theory is limited. Developing the evidence base is important because it has profound implications for ecosystem management. Here we show evidence of the existence of alternative stable soil moisture states induced by drought in an upland wet heath. We used a long-term (15 yrs) climate change manipulation experiment with moderate sustained drought, which reduced the ability of the soil to retain soil moisture by degrading the soil structure, reducing moisture retention. Moreover, natural intense droughts superimposed themselves on the experiment, causing an unexpected additional alternative soil moisture state to develop, both for the drought manipulation and control plots; this impaired the soil from rewetting in winter. Our results show the coexistence of three stable states. Using modelling with the Hydrus 1D software package we are able to show the circumstances under which shifts in soil moisture states are likely to occur. Given the new understanding it presents a challenge of how to incorporate feedbacks, particularly related to soil structure, into soil flow and transport models?

Soil moisture profile variability in land-vegetation- atmosphere continuum

NASA Astrophysics Data System (ADS)

Wu, Wanru

Soil moisture is of critical importance to the physical processes governing energy and water exchanges at the land-air boundary. With respect to the exchange of water mass, soil moisture controls the response of the land surface to atmospheric forcing and determines the partitioning of precipitation into infiltration and runoff. Meanwhile, the soil acts as a reservoir for the storage of liquid water and slow release of water vapor into the atmosphere. The major motivation of the study is that the soil moisture profile is thought to make a substantial contribution to the climate variability through two-way interactions between the land-surface and the atmosphere in the coupled ocean-atmosphere-land climate system. The characteristics of soil moisture variability with soil depth may be important in affecting the atmosphere. The natural variability of soil moisture profile is demonstrated using observations. The 16-year field observational data of soil moisture with 11-layer (top 2.0 meters) measured soil depths over Illinois are analyzed and used to identify and quantify the soil moisture profile variability, where the atmospheric forcing (precipitation) anomaly propagates down through the land-branch of the hydrological cycle with amplitude damping, phase shift, and increasing persistence. Detailed statistical data analyses, which include application of the periodogram method, the wavelet method and the band-pass filter, are made of the variations of soil moisture profile and concurrently measured precipitation for comparison. Cross-spectral analysis is performed to obtain the coherence pattern and phase correlation of two time series for phase shift and amplitude damping calculation. A composite of the drought events during this time period is analyzed and compared with the normal (non-drought) case. A multi-layer land surface model is applied for modeling the soil moisture profile variability characteristics and investigating the underlying mechanisms. Numerical experiments are conducted to examine the impacts of some potential controlling factors, which include atmospheric forcing (periodic and pulse) at the upper boundary, the initial soil moisture profile, the relative root abundance and the soil texture, on the variability of soil moisture profile and the corresponding evapotranspiration. Similar statistical data analyses are performed for the experimental data. Observations from the First International Satellite Land Surface Climatological Project (ISLSCP) Field Experiment (FIFE) are analyzed and used for the testing of model. The integration of the observational and modeling approaches makes it possible to better understand the mechanisms by which the soil moisture profile variability is generated with phase shift, fluctuation amplitude damping and low-pass frequency filtering with soil depth, to improve the strategies of parameterizations in land surface schemes, and furthermore, to assess its contribution to climate variability.

Historical climate controls soil respiration responses to current soil moisture.

PubMed

Hawkes, Christine V; Waring, Bonnie G; Rocca, Jennifer D; Kivlin, Stephanie N

2017-06-13

Ecosystem carbon losses from soil microbial respiration are a key component of global carbon cycling, resulting in the transfer of 40-70 Pg carbon from soil to the atmosphere each year. Because these microbial processes can feed back to climate change, understanding respiration responses to environmental factors is necessary for improved projections. We focus on respiration responses to soil moisture, which remain unresolved in ecosystem models. A common assumption of large-scale models is that soil microorganisms respond to moisture in the same way, regardless of location or climate. Here, we show that soil respiration is constrained by historical climate. We find that historical rainfall controls both the moisture dependence and sensitivity of respiration. Moisture sensitivity, defined as the slope of respiration vs. moisture, increased fourfold across a 480-mm rainfall gradient, resulting in twofold greater carbon loss on average in historically wetter soils compared with historically drier soils. The respiration-moisture relationship was resistant to environmental change in field common gardens and field rainfall manipulations, supporting a persistent effect of historical climate on microbial respiration. Based on these results, predicting future carbon cycling with climate change will require an understanding of the spatial variation and temporal lags in microbial responses created by historical rainfall.

The Detection and Characterization of Urbanization, Industrialization, and Longwall Mining Impacts on Forest Ecosystems Through the Use of GiS and Remote Sensing Techniques

NASA Astrophysics Data System (ADS)

Pfeil-McCullough, Erin Kathleen

Urbanization has far reaching and significant effects on forest ecosystems, directly through urban development and indirectly through supportive processes such as coal mining and agriculture. Urban processes modify the landscape leading to altered hillslope hydrology, increased disturbance, and the introduction of non-native forest pathogens. This dissertation addresses several challenges in our ability to detect these urbanization impacts on forests via geospatial analyses. The role of forests in urban hydrological processes has been extensively studied, but the impacts of urbanized hydrology on forests remain poorly examined. This dissertation documented impacts to hydrology and forests at variety of temporal and spatial scales: 1) A geospatial comparison of the historic and contemporary forests of Allegheny County, Pennsylvania revealed substantial shifts in tree species, but less change in the species soil moisture preference. These results document additional evidence that increased heterogeneity in urban soil moisture alters forest structure. 2) To examine soil moisture changes, impacts of longwall mine subsidence were assessed by using a Landsat based canopy moisture index and hot spot analysis tools at the forest patch scale. Declines in forest canopy moisture were detected over longwall mines as mining progressed through time, and results contradicted assumptions that the hydrological impacts overlying LMS recover within 4-5 years following subsidence of undermined land. 3) Utilizing a landslide susceptibility model (SINMAP), increases in landslide susceptibility were predicted in Pittsburgh, PA based on several scenarios of ash tree loss to the emerald ash borer (EAB), a bark beetle that rapidly kills ash trees. This model provides a tool to predict changes in landslide susceptibility following tree loss, increasing the understanding of urban forest function and its role in slope stability. Detecting how urbanized hydrology impacts forest health, function, and development is fundamental to sustaining the services forests provide. Results from this dissertation will ultimately allow improvements in the management and protection of both trees and water resources in urban systems and beyond.

Simulating the Dependence of Aspen on Redistributed Snow

NASA Astrophysics Data System (ADS)

Soderquist, B.; Kavanagh, K.; Link, T. E.; Seyfried, M. S.; Winstral, A. H.

2013-12-01

In mountainous regions across the western USA, the distribution of aspen (Populus tremuloides) is often directly related to heterogeneous soil moisture subsidies resulting from redistributed snow. With decades of climate and precipitation data across elevational and precipitation gradients, the Reynolds Creek Experimental Watershed (RCEW) in southwest Idaho provides a unique opportunity to study the relationship between aspen and redistributed snow. Within the RCEW, the total amount of precipitation has not changed in the past 50 years, but there are sharp declines in the percentage of the precipitation falling as snow. As shifts in the distribution of available moisture continue, future trends in aspen net primary productivity (NPP) remain uncertain. In order to assess the importance of snowdrift subsidies, NPP of three aspen stands was simulated at sites spanning elevational and precipitation gradients using the biogeochemical process model BIOME-BGC. At the aspen site experiencing the driest climate and lowest amount of precipitation from snow, approximately 400 mm of total precipitation was measured from November to March of 2008. However, peak measured snow water equivalent (SWE) held in drifts directly upslope of this stand was approximately 2100 mm, 5 times more moisture than the uniform winter precipitation layer initially assumed by BIOME-BGC. BIOME-BGC simulations in dry years forced by adjusted precipitation data resulted in NPP values approximately 30% higher than simulations assuming a uniform precipitation layer. Using BIOME-BGC and climate data from 1985-2011, the relationship between simulated NPP and measured basal area increments (BAI) improved after accounting for redistributed snow, indicating increased simulation representation. In addition to improved simulation capabilities, soil moisture data, diurnal branch water potential, and stomatal conductance observations at each site detail the use of soil moisture in the rooting zone and the onset of drought stress occurring in stands located along a precipitation phase gradient. These results further emphasize the importance of redistributed snow in heterogeneous landscapes along with the need to account for temporal shifts in water resource availability when assessing ecosystem vulnerability to climate change.

Land surface-precipitation feedback and ramifications on storm dynamics.

NASA Astrophysics Data System (ADS)

Baisya, H.; PV, R.; Pattnaik, S.

2017-12-01

A series of numerical experiments are carried out to investigate the sensitivity of a landfalling monsoon depression to land surface conditions using the Weather Research and Forecasting (WRF) model. Results suggest that precipitation is largely modulated by moisture influx and precipitation efficiency. Three cloud microphysical schemes (WSM6, WDM6, and Morrison) are examined, and Morrison is chosen for assessing the land surface-precipitation feedback analysis, owing to better precipitation forecast skills. It is found that increased soil moisture facilitates Moisture Flux Convergence (MFC) with reduced moisture influx, whereas a reduced soil moisture condition facilitates moisture influx but not MFC. A higher Moist Static Energy (MSE) is noted due to increased evapotranspiration in an elevated moisture scenario which enhances moist convection. As opposed to moist surface, sensible heat dominates in a reduced moisture scenario, ensued by an overall reduction in MSE throughout the Planetary Boundary Layer (PBL). Stability analysis shows that Convective Available Potential Energy (CAPE) is comparable in magnitude for both increased and decreased moisture scenarios, whereas Convective Inhibition (CIN) shows increased values for the reduced moisture scenario as a consequence of drier atmosphere leading to suppression of convection. Simulations carried out with various fixed soil moisture levels indicate that the overall precipitation features of the storm are characterized by initial soil moisture condition, but precipitation intensity at any instant is modulated by soil moisture availability. Overall results based on this case study suggest that antecedent soil moisture plays a crucial role in modulating precipitation distribution and intensity of a monsoon depression.

Land cover effects on thresholds for surface runoff generation in Eastern Madagascar

NASA Astrophysics Data System (ADS)

van Meerveld, Ilja H. J.; Prasad Ghimire, Chandra; Zwartendijk, Bob W.; Ravelona, Maafaka; Lahitiana, Jaona; Bruijnzeel, L. Adrian

2016-04-01

Reforestation and natural regrowth in the tropics are promoted for a wide range of benefits, including carbon sequestration, land rehabilitation and streamflow regulation. However, their effects on runoff generation mechanisms and streamflow are still poorly understood. Evaporative losses (transpiration and interception) likely increase with forest regrowth, while infiltration rates are expected to increase and surface runoff occurrence is, therefore, expected to decrease. As part of a larger project investigating the effects of land use on hydrological processes in upland Eastern Madagascar, this presentation reports on a comparison of the thresholds for surface runoff generation at a degraded grassland site, a young secondary forest site (5-7 years; LAI 1.83) and a mature secondary forest site (ca. 20 years; LAI 3.39). Surface runoff was measured on two (young and mature secondary forest) or three (degraded site) 3 m by 10 m plots over a one-year period (October 2014-September 2015). Soil moisture was measured at four (degraded site) to six depths (both forests), while perched groundwater levels were measured in piezometers installed at 30 cm below the soil surface. Soil hydraulic conductivity was measured in situ at the surface and at 10-20 and 20-30 cm depths at three locations in each plot. Porosity, moisture content at field capacity and bulk density were determined from soil cores taken at 2.5-7.5, 12.5-17.5 and 22.5-27.5 cm depth. The porosity and texture of the different plots were comparable. The hydraulic conductivity of the soil differed between the different land uses and declined sharply at 20-30 cm below the soil surface. Total surface runoff during the study period was 11% of incident rainfall at the degraded site vs. 2% for the two secondary forest sites. Maximum monthly runoff coefficients were 22%, 3.5% and 2.7% for the degraded site, the young forest site and the mature forest site, respectively, but individual event runoff coefficients could be as high as 45%, 12%, and 10%, respectively. Initial analyses indicate that a threshold rainfall amount was required before surface runoff occurs. Comparison of surface runoff occurrence with perched groundwater levels and soil moisture data showed that surface runoff was generated once the top-soil (0-20 cm) became saturated because of impeded drainage to the low hydraulic conductivity deeper layers. Thresholds for saturation overland flow generation were higher at the two forested sites compared to the degraded grassland due to their greater percolation to deeper layers, faster shallow lateral flow, and larger available storage in the top layers. The detailed analyses of the soil moisture and rainfall thresholds for surface runoff generation and their temporal variation will be used to develop a bucket-based conceptual model for runoff generation at these upland tropical sites. Key words: Runoff plot, rainfall threshold, soil moisture, saturation overland flow, secondary forest, soil hydraulic conductivity, Madagascar, p4ges project

Electrical methods of determining soil moisture content

NASA Technical Reports Server (NTRS)

Silva, L. F.; Schultz, F. V.; Zalusky, J. T.

1975-01-01

The electrical permittivity of soils is a useful indicator of soil moisture content. Two methods of determining the permittivity profile in soils are examined. A method due to Becher is found to be inapplicable to this situation. A method of Slichter, however, appears to be feasible. The results of Slichter's method are extended to the proposal of an instrument design that could measure available soil moisture profile (percent available soil moisture as a function of depth) from a surface measurement to an expected resolution of 10 to 20 cm.

Stream Flow Prediction by Remote Sensing and Genetic Programming

NASA Technical Reports Server (NTRS)

Chang, Ni-Bin

2009-01-01

A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

Soil moisture ground truth, Lafayette, Indiana, site; St. Charles Missouri, site; Centralia, Missouri, site

NASA Technical Reports Server (NTRS)

Jones, E. B.

1975-01-01

The soil moisture ground-truth measurements and ground-cover descriptions taken at three soil moisture survey sites located near Lafayette, Indiana; St. Charles, Missouri; and Centralia, Missouri are given. The data were taken on November 10, 1975, in connection with airborne remote sensing missions being flown by the Environmental Research Institute of Michigan under the auspices of the National Aeronautics and Space Administration. Emphasis was placed on the soil moisture in bare fields. Soil moisture was sampled in the top 0 to 1 in. and 0 to 6 in. by means of a soil sampling push tube. These samples were then placed in plastic bags and awaited gravimetric analysis.

Change in soil fungal community structure driven by a decline in ectomycorrhizal fungi following a mountain pine beetle (Dendroctonus ponderosae) outbreak.

PubMed

Pec, Gregory J; Karst, Justine; Taylor, D Lee; Cigan, Paul W; Erbilgin, Nadir; Cooke, Janice E K; Simard, Suzanne W; Cahill, James F

2017-01-01

Western North American landscapes are rapidly being transformed by forest die-off caused by mountain pine beetle (Dendroctonus ponderosae), with implications for plant and soil communities. The mechanisms that drive changes in soil community structure, particularly for the highly prevalent ectomycorrhizal fungi in pine forests, are complex and intertwined. Critical to enhancing understanding will be disentangling the relative importance of host tree mortality from changes in soil chemistry following tree death. Here, we used a recent bark beetle outbreak in lodgepole pine (Pinus contorta) forests of western Canada to test whether the effects of tree mortality altered the richness and composition of belowground fungal communities, including ectomycorrhizal and saprotrophic fungi. We also determined the effects of environmental factors (i.e. soil nutrients, moisture, and phenolics) and geographical distance, both of which can influence the richness and composition of soil fungi. The richness of both groups of soil fungi declined and the overall composition was altered by beetle-induced tree mortality. Soil nutrients, soil phenolics and geographical distance influenced the community structure of soil fungi; however, the relative importance of these factors differed between ectomycorrhizal and saprotrophic fungi. The independent effects of tree mortality, soil phenolics and geographical distance influenced the community composition of ectomycorrhizal fungi, while the community composition of saprotrophic fungi was weakly but significantly correlated with the geographical distance of plots. Taken together, our results indicate that both deterministic and stochastic processes structure soil fungal communities following landscape-scale insect outbreaks and reflect the independent roles tree mortality, soil chemistry and geographical distance play in regulating the community composition of soil fungi. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

NASA Astrophysics Data System (ADS)

Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

2015-09-01

The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

Estimation of surface soil moisture and roughness from multi-angular ASAR imagery in the Watershed Allied Telemetry Experimental Research (WATER)

NASA Astrophysics Data System (ADS)

Wang, S. G.; Li, X.; Han, X. J.; Jin, R.

2010-06-01

Radar remote sensing has demonstrated its applicability to the retrieval of basin-scale soil moisture. The mechanism of radar backscattering from soils is complicated and strongly influenced by surface roughness. Furthermore, retrieval of soil moisture using AIEM-like models is a classic example of the underdetermined problem due to a lack of credible known soil roughness distributions at a regional scale. Characterization of this roughness is therefore crucial for an accurate derivation of soil moisture based on backscattering models. This study aims to directly obtain surface roughness information along with soil moisture from multi-angular ASAR images. The method first used a semi-empirical relationship that connects the roughness slope (Zs) and the difference in backscattering coefficient (Δσ) from ASAR data in different incidence angles, in combination with an optimal calibration form consisting of two roughness parameters (the standard deviation of surface height and the correlation length), to estimate the roughness parameters. The deduced surface roughness was then used in the AIEM model for the retrieval of soil moisture. An evaluation of the proposed method was performed in a grassland site in the middle stream of the Heihe River Basin, where the Watershed Allied Telemetry Experimental Research (WATER) was taken place. It has demonstrated that the method is feasible to achieve reliable estimation of soil water content. The key challenge to surface soil moisture retrieval is the presence of vegetation cover, which significantly impacts the estimates of surface roughness and soil moisture.

Disaggregation of remotely sensed soil moisture under all sky condition using machine learning approach in Northeast Asia

NASA Astrophysics Data System (ADS)

Kim, S.; Kim, H.; Choi, M.; Kim, K.

2016-12-01

Estimating spatiotemporal variation of soil moisture is crucial to hydrological applications such as flood, drought, and near real-time climate forecasting. Recent advances in space-based passive microwave measurements allow the frequent monitoring of the surface soil moisture at a global scale and downscaling approaches have been applied to improve the spatial resolution of passive microwave products available at local scale applications. However, most downscaling methods using optical and thermal dataset, are valid only in cloud-free conditions; thus renewed downscaling method under all sky condition is necessary for the establishment of spatiotemporal continuity of datasets at fine resolution. In present study Support Vector Machine (SVM) technique was utilized to downscale a satellite-based soil moisture retrievals. The 0.1 and 0.25-degree resolution of daily Land Parameter Retrieval Model (LPRM) L3 soil moisture datasets from Advanced Microwave Scanning Radiometer 2 (AMSR2) were disaggregated over Northeast Asia in 2015. Optically derived estimates of surface temperature (LST), normalized difference vegetation index (NDVI), and its cloud products were obtained from MODerate Resolution Imaging Spectroradiometer (MODIS) for the purpose of downscaling soil moisture in finer resolution under all sky condition. Furthermore, a comparison analysis between in situ and downscaled soil moisture products was also conducted for quantitatively assessing its accuracy. Results showed that downscaled soil moisture under all sky condition not only preserves the quality of AMSR2 LPRM soil moisture at 1km resolution, but also attains higher spatial data coverage. From this research we expect that time continuous monitoring of soil moisture at fine scale regardless of weather conditions would be available.

[Sap flow characteristics of Quercus liaotungensis in response to sapwood area and soil moisture in the loess hilly region, China].

PubMed

Lyu, Jin Lin; He, Qiu Yue; Yan, Mei Jie; Li, Guo Qing; Du, Sheng

2018-03-01

To examine the characteristics of sap flow in Quercus liaotungensis and their response to environmental factors under different soil moisture conditions, Granier-type thermal dissipation probes were used to measure xylem sap flow of trees with different sapwood area in a natural Q. liaotungensis forest in the loess hilly region. Solar radiation, air temperature, relative air humidity, precipitation, and soil moisture were monitored during the study period. The results showed that sap flux of Q. liaotungensis reached daily peaks earlier than solar radiation and vapor pressure deficit. The diurnal dynamics of sap flux showed a similar pattern to those of the environmental factors. Trees had larger sap flux during the period with higher soil moisture. Under the same soil moisture conditions, trees with larger diameter and sapwood areas had significantly higher sap flux than those with smaller diameter and sapwood areas. Sap flux could be fitted with vapor pressure deficit, solar radiation, and the integrated index of the two factors using exponential saturation function. Differences in the fitted curves and parameters suggested that sap flux tended to reach saturation faster under higher soil moisture. Furthermore, trees in the smaller diameter class were more sensitive to the changes of soil moisture. The ratio of daily sap flux per unit vapor pressure deficit under lower soil moisture condition to that under higher soil moisture condition was linearly correlated to sapwood area. The regressive slope in smaller diameter class was larger than that in bigger diameter class, which further indicated the higher sensitivity of trees with smaller diameter class to soil moisture. These results indicated that wider sapwood of larger diameter class provided a buffer against drought stress.

From Sub-basin to Grid Scale Soil Moisture Disaggregation in SMART, A Semi-distributed Hydrologic Modeling Framework

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.

2016-12-01

A computationally efficient, semi-distributed hydrologic modeling framework is developed to simulate water balance at a catchment scale. The Soil Moisture and Runoff simulation Toolkit (SMART) is based upon the delineation of contiguous and topologically connected Hydrologic Response Units (HRUs). In SMART, HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are distributed cross sections or equivalent cross sections (ECS) delineated in first order sub-basins. ECSs are formulated by aggregating topographic and physiographic properties of the part or entire first order sub-basins to further reduce computational time in SMART. Previous investigations using SMART have shown that temporal dynamics of soil moisture are well captured at a HRU level using the ECS delineation approach. However, spatial variability of soil moisture within a given HRU is ignored. Here, we examined a number of disaggregation schemes for soil moisture distribution in each HRU. The disaggregation schemes are either based on topographic based indices or a covariance matrix obtained from distributed soil moisture simulations. To assess the performance of the disaggregation schemes, soil moisture simulations from an integrated land surface-groundwater model, ParFlow.CLM in Baldry sub-catchment, Australia are used. ParFlow is a variably saturated sub-surface flow model that is coupled to the Common Land Model (CLM). Our results illustrate that the statistical disaggregation scheme performs better than the methods based on topographic data in approximating soil moisture distribution at a 60m scale. Moreover, the statistical disaggregation scheme maintains temporal correlation of simulated daily soil moisture while preserves the mean sub-basin soil moisture. Future work is focused on assessing the performance of this scheme in catchments with various topographic and climate settings.

MODIS-based spatiotemporal patterns of soil moisture and evapotranspiration interactions in Tampa Bay urban watershed

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent

2011-09-01

Soil moisture and evapotranspiration (ET) is affected by both water and energy balances in the soilvegetation- atmosphere system, it involves many complex processes in the nexus of water and thermal cycles at the surface of the Earth. These impacts may affect the recharge of the upper Floridian aquifer. The advent of urban hydrology and remote sensing technologies opens new and innovative means to undertake eventbased assessment of ecohydrological effects in urban regions. For assessing these landfalls, the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing images can be used for the estimation of such soil moisture change in connection with two other MODIS products - Enhanced Vegetation Index (EVI), Land Surface Temperature (LST). Supervised classification for soil moisture retrieval was performed for Tampa Bay area on the 2 kmx2km grid with MODIS images. Machine learning with genetic programming model for soil moisture estimation shows advances in image processing, feature extraction, and change detection of soil moisture. ET data that were derived by Geostationary Operational Environmental Satellite (GOES) data and hydrologic models can be retrieved from the USGS web site directly. Overall, the derived soil moisture in comparison with ET time series changes on a seasonal basis shows that spatial and temporal variations of soil moisture and ET that are confined within a defined region for each type of surfaces, showing clustered patterns and featuring space scatter plot in association with the land use and cover map. These concomitant soil moisture patterns and ET fluctuations vary among patches, plant species, and, especially, location on the urban gradient. Time series plots of LST in association with ET, soil moisture and EVI reveals unique ecohydrological trends. Such ecohydrological assessment can be applied for supporting the urban landscape management in hurricane-stricken regions.

A practical approach for deriving all-weather soil moisture content using combined satellite and meteorological data

NASA Astrophysics Data System (ADS)

Leng, Pei; Li, Zhao-Liang; Duan, Si-Bo; Gao, Mao-Fang; Huo, Hong-Yuan

2017-09-01

Soil moisture has long been recognized as one of the essential variables in the water cycle and energy budget between Earth's surface and atmosphere. The present study develops a practical approach for deriving all-weather soil moisture using combined satellite images and gridded meteorological products. In this approach, soil moisture over the Moderate Resolution Imaging Spectroradiometer (MODIS) clear-sky pixels are estimated from the Vegetation Index/Temperature (VIT) trapezoid scheme in which theoretical dry and wet edges were determined pixel to pixel by China Meteorological Administration Land Data Assimilation System (CLDAS) meteorological products, including air temperature, solar radiation, wind speed and specific humidity. For cloudy pixels, soil moisture values are derived by the calculation of surface and aerodynamic resistances from wind speed. The approach is capable of filling the soil moisture gaps over remaining cloudy pixels by traditional optical/thermal infrared methods, allowing for a spatially complete soil moisture map over large areas. Evaluation over agricultural fields indicates that the proposed approach can produce an overall generally reasonable distribution of all-weather soil moisture. An acceptable accuracy between the estimated all-weather soil moisture and in-situ measurements at different depths could be found with an Root Mean Square Error (RMSE) varying from 0.067 m3/m3 to 0.079 m3/m3 and a slight bias ranging from 0.004 m3/m3 to -0.011 m3/m3. The proposed approach reveals significant potential to derive all-weather soil moisture using currently available satellite images and meteorological products at a regional or global scale in future developments.

Ecosystem-scale plant hydraulic strategies inferred from remotely-sensed soil moisture

NASA Astrophysics Data System (ADS)

Bassiouni, M.; Good, S. P.; Higgins, C. W.

2017-12-01

Characterizing plant hydraulic strategies at the ecosystem scale is important to improve estimates of evapotranspiration and to understand ecosystem productivity and resilience. However, quantifying plant hydraulic traits beyond the species level is a challenge. The probability density function of soil moisture observations provides key information about the soil moisture states at which evapotranspiration is reduced by water stress. Here, an inverse Bayesian approach is applied to a standard bucket model of soil column hydrology forced with stochastic precipitation inputs. Through this approach, we are able to determine the soil moisture thresholds at which stomata are open or closed that are most consistent with observed soil moisture probability density functions. This research utilizes remotely-sensed soil moisture data to explore global patterns of ecosystem-scale plant hydraulic strategies. Results are complementary to literature values of measured hydraulic traits of various species in different climates and previous estimates of ecosystem-scale plant isohydricity. The presented approach provides a novel relation between plant physiological behavior and soil-water dynamics.

Determining the frequency, depth and velocity of preferential flow by high frequency soil moisture monitoring

NASA Astrophysics Data System (ADS)

Hardie, Marcus; Lisson, Shaun; Doyle, Richard; Cotching, William

2013-01-01

Preferential flow in agricultural soils has been demonstrated to result in agrochemical mobilisation to shallow ground water. Land managers and environmental regulators need simple cost effective techniques for identifying soil - land use combinations in which preferential flow occurs. Existing techniques for identifying preferential flow have a range of limitations including; often being destructive, non in situ, small sampling volumes, or are subject to artificial boundary conditions. This study demonstrated that high frequency soil moisture monitoring using a multi-sensory capacitance probe mounted within a vertically rammed access tube, was able to determine the occurrence, depth, and wetting front velocity of preferential flow events following rainfall. Occurrence of preferential flow was not related to either rainfall intensity or rainfall amount, rather preferential flow occurred when antecedent soil moisture content was below 226 mm soil moisture storage (0-70 cm). Results indicate that high temporal frequency soil moisture monitoring may be used to identify soil type - land use combinations in which the presence of preferential flow increases the risk of shallow groundwater contamination by rapid transport of agrochemicals through the soil profile. However use of high frequency based soil moisture monitoring to determine agrochemical mobilisation risk may be limited by, inability to determine the volume of preferential flow, difficulty observing macropore flow at high antecedent soil moisture content, and creation of artificial voids during installation of access tubes in stony soils.

[Soil moisture estimation method based on both ground-based remote sensing data and air temperature in a summer maize ecosystem.

PubMed

Wang, Min Zheng; Zhou, Guang Sheng

2016-06-01

Soil moisture is an important component of the soil-vegetation-atmosphere continuum (SPAC). It is a key factor to determine the water status of terrestrial ecosystems, and is also the main source of water supply for crops. In order to estimate soil moisture at different soil depths at a station scale, based on the energy balance equation and the water deficit index (WDI), a soil moisture estimation model was established in terms of the remote sensing data (the normalized difference vegetation index and surface temperature) and air temperature. The soil moisture estimation model was validated based on the data from the drought process experiment of summer maize (Zea mays) responding to different irrigation treatments carried out during 2014 at Gucheng eco-agrometeorological experimental station of China Meteorological Administration. The results indicated that the soil moisture estimation model developed in this paper was able to evaluate soil relative humidity at different soil depths in the summer maize field, and the hypothesis was reasonable that evapotranspiration deficit ratio (i.e., WDI) linearly depended on soil relative humidity. It showed that the estimation accuracy of 0-10 cm surface soil moisture was the highest (R 2 =0.90). The RMAEs of the estimated and measured soil relative humidity in deeper soil layers (up to 50 cm) were less than 15% and the RMSEs were less than 20%. The research could provide reference for drought monitoring and irrigation management.

Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

NASA Astrophysics Data System (ADS)

DY, C. Y.; Fung, J. C. H.

2016-08-01

A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

A method for soil moisture probes calibration and validation of satellite estimates.

PubMed

Holzman, Mauro; Rivas, Raúl; Carmona, Facundo; Niclòs, Raquel

2017-01-01

Optimization of field techniques is crucial to ensure high quality soil moisture data. The aim of the work is to present a sampling method for undisturbed soil and soil water content to calibrated soil moisture probes, in a context of the SMOS (Soil Moisture and Ocean Salinity) mission MIRAS Level 2 soil moisture product validation in Pampean Region of Argentina. The method avoids soil alteration and is recommended to calibrated probes based on soil type under a freely drying process at ambient temperature. A detailed explanation of field and laboratory procedures to obtain reference soil moisture is shown. The calibration results reflected accurate operation for the Delta-T thetaProbe ML2x probes in most of analyzed cases (RMSE and bias ≤ 0.05 m 3 /m 3 ). Post-calibration results indicated that the accuracy improves significantly applying the adjustments of the calibration based on soil types (RMSE ≤ 0.022 m 3 /m 3 , bias ≤ -0.010 m 3 /m 3 ). •A sampling method that provides high quality data of soil water content for calibration of probes is described.•Importance of calibration based on soil types.•A calibration process for similar soil types could be suitable in practical terms, depending on the required accuracy level.

Ecosystem warming increases sap flow rates of northern red oak trees

DOE PAGES

Juice, Stephanie M.; Templer, Pamela H.; Phillips, Nathan G.; ...

2016-03-17

Over the next century, air temperature increases up to 5°C are projected for the northeastern United States. As evapotranspiration strongly influences water loss from terrestrial ecosystems, the ecophysiological response of trees to warming will have important consequences for forest water budgets. We measured growing season sap flow rates in mature northern red oak ( Quercus rubra L.) trees in a combined air (up to 5.5°C above ambient) and soil (up to 1.85°C above ambient at 6-cm depth) warming experiment at Harvard Forest, Massachusetts, United States. Through principal components analysis, we found air and soil temperatures explained the largest amount ofmore » variance in environmental variables associated with rates of sap flow, with relative humidity, photosynthetically active radiation and vapor pressure deficit having significant, but smaller, effects. On average, each 1°C increase in temperature increased sap flow rates by approximately 1100 kg H 2O m -2 sapwood area day-1 throughout the growing season and by 1200 kg H 2O m -2 sapwood area day -1 during the early growing season. Reductions in the number of cold winter days correlated positively with increased sap flow during the early growing season (a decrease in 100 heating-degree days was associated with a sapflow increase in approximately 5 kg H 2O m -2 sapwood area day -1). Soil moisture declined with increased treatment temperatures, and each soil moisture percentage decrease resulted in a decrease in sap flow of approximately 360 kg H2O m -22 sapwood area day -1. At night, soil moisture correlated positively with sap flow. Finally, these results demonstrate that warmer air and soil temperatures in winter and throughout the growing season lead to increased sap flow rates, which could affect forest water budgets throughout the year.« less

Bark beetle-induced tree mortality alters stand energy budgets due to water budget changes

NASA Astrophysics Data System (ADS)

Reed, David E.; Ewers, Brent E.; Pendall, Elise; Frank, John; Kelly, Robert

2018-01-01

Insect outbreaks are major disturbances that affect a land area similar to that of forest fires across North America. The recent mountain pine bark beetle ( D endroctonus ponderosae) outbreak and its associated blue stain fungi ( Grosmannia clavigera) are impacting water partitioning processes of forests in the Rocky Mountain region as the spatially heterogeneous disturbance spreads across the landscape. Water cycling may dramatically change due to increasing spatial heterogeneity from uneven mortality. Water and energy storage within trees and soils may also decrease, due to hydraulic failure and mortality caused by blue stain fungi followed by shifts in the water budget. This forest disturbance was unique in comparison to fire or timber harvesting because water fluxes were altered before significant structural change occurred to the canopy. We investigated the impacts of bark beetles on lodgepole pine ( Pinus contorta) stand and ecosystem level hydrologic processes and the resulting vertical and horizontal spatial variability in energy storage. Bark beetle-impacted stands had on average 57 % higher soil moisture, 1.5 °C higher soil temperature, and 0.8 °C higher tree bole temperature over four growing seasons compared to unimpacted stands. Seasonal latent heat flux was highly correlated with soil moisture. Thus, high mortality levels led to an increase in ecosystem level Bowen ratio as sensible heat fluxes increased yearly and latent heat fluxes varied with soil moisture levels. Decline in canopy biomass (leaf, stem, and branch) was not seen, but ground-to-atmosphere longwave radiation flux increased, as the ground surface was a larger component of the longwave radiation. Variability in soil, latent, and sensible heat flux and radiation measurements increased during the disturbance. Accounting for stand level variability in water and energy fluxes will provide a method to quantify potential drivers of ecosystem processes and services as well as lead to greater confidence in measurements for all dynamic disturbances.

Ecosystem warming increases sap flow rates of northern red oak trees

DOE Office of Scientific and Technical Information (OSTI.GOV)

Juice, Stephanie M.; Templer, Pamela H.; Phillips, Nathan G.

Over the next century, air temperature increases up to 5°C are projected for the northeastern United States. As evapotranspiration strongly influences water loss from terrestrial ecosystems, the ecophysiological response of trees to warming will have important consequences for forest water budgets. We measured growing season sap flow rates in mature northern red oak ( Quercus rubra L.) trees in a combined air (up to 5.5°C above ambient) and soil (up to 1.85°C above ambient at 6-cm depth) warming experiment at Harvard Forest, Massachusetts, United States. Through principal components analysis, we found air and soil temperatures explained the largest amount ofmore » variance in environmental variables associated with rates of sap flow, with relative humidity, photosynthetically active radiation and vapor pressure deficit having significant, but smaller, effects. On average, each 1°C increase in temperature increased sap flow rates by approximately 1100 kg H 2O m -2 sapwood area day-1 throughout the growing season and by 1200 kg H 2O m -2 sapwood area day -1 during the early growing season. Reductions in the number of cold winter days correlated positively with increased sap flow during the early growing season (a decrease in 100 heating-degree days was associated with a sapflow increase in approximately 5 kg H 2O m -2 sapwood area day -1). Soil moisture declined with increased treatment temperatures, and each soil moisture percentage decrease resulted in a decrease in sap flow of approximately 360 kg H2O m -22 sapwood area day -1. At night, soil moisture correlated positively with sap flow. Finally, these results demonstrate that warmer air and soil temperatures in winter and throughout the growing season lead to increased sap flow rates, which could affect forest water budgets throughout the year.« less

Evaluation of the cosmic-ray neutron method for measuring integral soil moisture dynamics of a forested head water catchment

NASA Astrophysics Data System (ADS)

Bogena, H. R.; Metzen, D.; Baatz, R.; Hendricks Franssen, H.; Huisman, J. A.; Montzka, C.; Vereecken, H.

2011-12-01

Measurements of low-energy secondary neutron intensity above the soil surface by cosmic-ray soil moisture probes (CRP) can be used to estimate soil moisture content. CRPs utilise the fact that high-energy neutrons initiated by cosmic rays are moderated (slowed to lower energies) most effectively by collisions with hydrogen atoms contained in water molecules in the soil. The conversion of neutron intensity to soil moisture content can potentially be complicated because neutrons are also moderated by aboveground water storage (e.g. vegetation water content, canopy storage of interception). Recently, it was demonstrated experimentally that soil moisture content derived from CRP measurements agrees well with average moisture content from gravimetric soil samples taken within the footprint of the cosmic ray probe, which is proposed to be up to several hundred meters in size [1]. However, the exact extension and shape of the CRP integration footprint is still an open question and it is also unclear how CRP measurements are affected by the soil moisture distribution within the footprint both in horizontal and vertical directions. In this paper, we will take advantage of an extensive wireless soil moisture sensor network covering most of the estimated footprint of the CRP. The network consists of 150 nodes and 900 soil moisture sensors which were installed in the small forested Wüstebach catchment (~27 ha) in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories) [2]. This unique soil moisture data set provides a consistent picture of the hydrological status of the catchment in a high spatial and temporal resolution and thus the opportunity to evaluate the CRP measurements in a rigorous way. We will present first results of the comparison with a specific focus on the sensitivity of the CRP measurements to soil moisture variation in both the horizontal and vertical direction. Furthermore, the influence of forest biomass and shallow groundwater table fluctuations on the attenuation of cosmic-ray neutrons will be considered.

Studies and Application of Remote Sensing Retrieval Method of Soil Moisture Content in Land Parcel Units in Irrigation Area

NASA Astrophysics Data System (ADS)

Zhu, H.; Zhao, H. L.; Jiang, Y. Z.; Zang, W. B.

2018-05-01

Soil moisture is one of the important hydrological elements. Obtaining soil moisture accurately and effectively is of great significance for water resource management in irrigation area. During the process of soil moisture content retrieval with multiremote sensing data, multi- remote sensing data always brings multi-spatial scale problems which results in inconformity of soil moisture content retrieved by remote sensing in different spatial scale. In addition, agricultural water use management has suitable spatial scale of soil moisture information so as to satisfy the demands of dynamic management of water use and water demand in certain unit. We have proposed to use land parcel unit as the minimum unit to do soil moisture content research in agricultural water using area, according to soil characteristics, vegetation coverage characteristics in underlying layer, and hydrological characteristic into the basis of study unit division. We have proposed division method of land parcel units. Based on multi thermal infrared and near infrared remote sensing data, we calculate the ndvi and tvdi index and make a statistical model between the tvdi index and soil moisture of ground monitoring station. Then we move forward to study soil moisture remote sensing retrieval method on land parcel unit scale. And the method has been applied in Hetao irrigation area. Results show that compared with pixel scale the soil moisture content in land parcel unit scale has displayed stronger correlation with true value. Hence, remote sensing retrieval method of soil moisture content in land parcel unit scale has shown good applicability in Hetao irrigation area. We converted the research unit into the scale of land parcel unit. Using the land parcel units with unified crops and soil attributes as the research units more complies with the characteristics of agricultural water areas, avoids the problems such as decomposition of mixed pixels and excessive dependence on high-resolution data caused by the research units of pixels, and doesn't involve compromises in the spatial scale and simulating precision like the grid simulation. When the application needs are met, the production efficiency of products can also be improved at a certain degree.

Use of midlatitude soil moisture and meteorological observations to validate soil moisture simulations with biosphere and bucket models

NASA Technical Reports Server (NTRS)

Robock, Alan; Vinnikov, Konstantin YA.; Schlosser, C. Adam; Speranskaya, Nina A.; Xue, Yongkang

1995-01-01

Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMs) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth's surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSiB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil moisture are compared to observations of soil moisture, literally 'ground truth,' snow cover, surface albedo, and net radiation, and with each other. For three of the stations, the SSiB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring -- SSiB incorrectly puts all the snowmelt into runoff. While producing similar soil moisture simulations, the models produce very different surface latent and sensible heat fluxes, which would have large effects on GCM simulations.

Using the Spatial Persistence of Soil Moisture Patterns to Estimate Catchment Soil Moisture in Semi-arid Areas

NASA Astrophysics Data System (ADS)

Willgoose, G. R.

2006-12-01

In humid catchments the spatial distribution of soil water is dominated by subsurface lateral fluxes, which leads to a persistent spatial pattern of soil moisture principally described by the topographic index. In contrast, semi-arid, and dryer, catchments are dominated by vertical fluxes (infiltration and evapotranspiration) and persistent spatial patterns, if they exist, are subtler. In the first part of this presentation the results of a reanalysis of a number of catchment-scale long-term spatially-distributed soil moisture data sets are presented. We concentrate on Tarrawarra and SASMAS, both catchments in Australia that are water-limited for at least part of the year and which have been monitored using a variety of technologies. Using the data from permanently installed instruments (neutron probe and reflectometry) both catchments show persistent patterns at the 1-3 year timescale. This persistent pattern is not evident in the field campaign data where field portable instruments (reflectometry) instruments were used. We argue, based on high-resolution soil moisture semivariograms, that high short-distance variability (100mm scale) means that field portable instrument cannot be replaced at the same location with sufficient accuracy to ensure deterministic repeatability of soil moisture measurements from campaign to campaign. The observed temporal persistence of the spatial pattern can be caused by; (1) permanent features of the landscape (e.g. vegetation, soils), or (2) long term memory in the soil moisture store. We argue that it is permanent in which case it is possible to monitor the soil moisture status of a catchment using a single location measurement (continuous in time) of soil moisture using a permanently installed reflectometry instrument. This instrument will need to be calibrated to the catchment averaged soil moisture but the temporal persistence of the spatial pattern of soil moisture will mean that this calibration will be deterministically stable with time. In the second part of this presentation we will explore aspects of the calibration using data from the SASMAS site using the multiscale spatial resolution data (100m to 10km) provided by permanently installed reflectometry instruments, and how this single site measurement technique may complement satellite data.

Ground truth report 1975 Phoenix microwave experiment. [Joint Soil Moisture Experiment

NASA Technical Reports Server (NTRS)

Blanchard, B. J.

1975-01-01

Direct measurements of soil moisture obtained in conjunction with aircraft data flights near Phoenix, Arizona in March, 1975 are summarized. The data were collected for the Joint Soil Moisture Experiment.

Survival and leaching of fecal bacteria after slurry spreading on mountain hay meadows: consequences for the management of water contamination risk.

PubMed

Trevisan, D; Vansteelant, J Y; Dorioz, J M

2002-01-01

The aim of this work is to achieve a better understanding of the behavior of fecal coliform populations on the vegetation and in the soil after slurry spreading in environmental conditions, typical of vegetative growth period in mountain hay meadows. Changes in fecal coliform populations on the vegetation and in the soil were monitored in situ for 3 months after slurry spreading on 9 plots. The variations found in populations are related to the agricultural, soil. and climatic characteristics of plots and to the moisture regime of soils. These observations are compared with laboratory experiments on undisturbed soil microcosms. In absence of water flux, survival durations recorded in the laboratory and in the field are of the same order of magnitude. The data enable us to pinpoint the influence of various factors affecting the decline and transfer of fecal bacteria in the plant-soil system and consequently to discuss the risk management of water contamination by agriculture.

A review of spatial downscaling of satellite remotely sensed soil moisture

NASA Astrophysics Data System (ADS)

Peng, Jian; Loew, Alexander; Merlin, Olivier; Verhoest, Niko E. C.

2017-06-01

Satellite remote sensing technology has been widely used to estimate surface soil moisture. Numerous efforts have been devoted to develop global soil moisture products. However, these global soil moisture products, normally retrieved from microwave remote sensing data, are typically not suitable for regional hydrological and agricultural applications such as irrigation management and flood predictions, due to their coarse spatial resolution. Therefore, various downscaling methods have been proposed to improve the coarse resolution soil moisture products. The purpose of this paper is to review existing methods for downscaling satellite remotely sensed soil moisture. These methods are assessed and compared in terms of their advantages and limitations. This review also provides the accuracy level of these methods based on published validation studies. In the final part, problems and future trends associated with these methods are analyzed.

Evaluating ESA CCI Soil Moisture in East Africa

NASA Technical Reports Server (NTRS)

McNally, Amy; Shukla, Shraddhanand; Arsenault, Kristi R.; Wang, Shugong; Peters-Lidard, Christa D.; Verdin, James P.

2016-01-01

To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and NASAs Soil Moisture Active Passive (SMAP), however these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we use East Africa as a case study to evaluate the quality of a 30+ year time series of merged active-passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM). Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we found substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies were well correlated (R greater than 0.5) with modeled, seasonal soil moisture, and in some regions, NDVI. We use correlation analysis and qualitative comparisons at seasonal time scales to show that remotely sensed soil moisture can add information to a convergence of evidence framework that traditionally relies on rainfall and NDVI in moderately vegetated regions.

The Value of SMAP Soil Moisture Observations For Agricultural Applications

NASA Astrophysics Data System (ADS)

Mladenova, I. E.; Bolten, J. D.; Crow, W.; Reynolds, C. A.

2017-12-01

Knowledge of the amount of soil moisture (SM) in the root zone (RZ) is critical source of information for crop analysts and agricultural agencies as it controls crop development and crop condition changes and can largely impact end-of-season yield. Foreign Agricultural Services (FAS), a subdivision of U.S. Department of Agriculture (USDA) that is in charge with providing information on current and expected global crop supply and demand estimates, has been relying on RZSM estimates generated by the modified two-layer Palmer model, which has been enhanced to allow the assimilation of satellite-based soil moisture data. Generally the accuracy of model-based soil moisture estimates is dependent on the precision of the forcing data that drives the model and more specifically, the accuracy of the precipitation data. Data assimilation gives the opportunity to correct for such precipitation-related inaccuracies and enhance the quality of the model estimates. Here we demonstrate the value of ingesting passive-based soil moisture observations derived from the Soil Moisture Active Passive (SMAP) mission. In terms of agriculture, general understanding is that the change in soil moisture conditions precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop conditions. Therefore, we assess the accuracy of the SMAP enhanced Palmer model by examining the lag rank cross-correlation coefficient between the model generated soil moisture observations and the Normalized Difference Vegetation Index (NDVI).

MoisturEC: an R application for geostatistical estimation of moisture content from electrical conductivity data

NASA Astrophysics Data System (ADS)

Terry, N.; Day-Lewis, F. D.; Werkema, D. D.; Lane, J. W., Jr.

2017-12-01

Soil moisture is a critical parameter for agriculture, water supply, and management of landfills. Whereas direct data (as from TDR or soil moisture probes) provide localized point scale information, it is often more desirable to produce 2D and/or 3D estimates of soil moisture from noninvasive measurements. To this end, geophysical methods for indirectly assessing soil moisture have great potential, yet are limited in terms of quantitative interpretation due to uncertainty in petrophysical transformations and inherent limitations in resolution. Simple tools to produce soil moisture estimates from geophysical data are lacking. We present a new standalone program, MoisturEC, for estimating moisture content distributions from electrical conductivity data. The program uses an indicator kriging method within a geostatistical framework to incorporate hard data (as from moisture probes) and soft data (as from electrical resistivity imaging or electromagnetic induction) to produce estimates of moisture content and uncertainty. The program features data visualization and output options as well as a module for calibrating electrical conductivity with moisture content to improve estimates. The user-friendly program is written in R - a widely used, cross-platform, open source programming language that lends itself to further development and customization. We demonstrate use of the program with a numerical experiment as well as a controlled field irrigation experiment. Results produced from the combined geostatistical framework of MoisturEC show improved estimates of moisture content compared to those generated from individual datasets. This application provides a convenient and efficient means for integrating various data types and has broad utility to soil moisture monitoring in landfills, agriculture, and other problems.

Impacts of precipitation and potential evapotranspiration patterns on downscaling soil moisture in regions with large topographic relief

NASA Astrophysics Data System (ADS)

Cowley, Garret S.; Niemann, Jeffrey D.; Green, Timothy R.; Seyfried, Mark S.; Jones, Andrew S.; Grazaitis, Peter J.

2017-02-01

Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution soil moisture using fine-resolution topographic, vegetation, and soil data to produce fine-resolution (10-30 m) estimates of soil moisture. The EMT+VS model performs well at catchments with low topographic relief (≤124 m), but it has not been applied to regions with larger ranges of elevation. Large relief can produce substantial variations in precipitation and potential evapotranspiration (PET), which might affect the fine-resolution patterns of soil moisture. In this research, simple methods to downscale temporal average precipitation and PET are developed and included in the EMT+VS model, and the effects of spatial variations in these variables on the surface soil moisture estimates are investigated. The methods are tested against ground truth data at the 239 km2 Reynolds Creek watershed in southern Idaho, which has 1145 m of relief. The precipitation and PET downscaling methods are able to capture the main features in the spatial patterns of both variables. The space-time Nash-Sutcliffe coefficients of efficiency of the fine-resolution soil moisture estimates improve from 0.33 to 0.36 and 0.41 when the precipitation and PET downscaling methods are included, respectively. PET downscaling provides a larger improvement in the soil moisture estimates than precipitation downscaling likely because the PET pattern is more persistent through time, and thus more predictable, than the precipitation pattern.

Assessing artificial neural networks and statistical methods for infilling missing soil moisture records

NASA Astrophysics Data System (ADS)

Dumedah, Gift; Walker, Jeffrey P.; Chik, Li

2014-07-01

Soil moisture information is critically important for water management operations including flood forecasting, drought monitoring, and groundwater recharge estimation. While an accurate and continuous record of soil moisture is required for these applications, the available soil moisture data, in practice, is typically fraught with missing values. There are a wide range of methods available to infilling hydrologic variables, but a thorough inter-comparison between statistical methods and artificial neural networks has not been made. This study examines 5 statistical methods including monthly averages, weighted Pearson correlation coefficient, a method based on temporal stability of soil moisture, and a weighted merging of the three methods, together with a method based on the concept of rough sets. Additionally, 9 artificial neural networks are examined, broadly categorized into feedforward, dynamic, and radial basis networks. These 14 infilling methods were used to estimate missing soil moisture records and subsequently validated against known values for 13 soil moisture monitoring stations for three different soil layer depths in the Yanco region in southeast Australia. The evaluation results show that the top three highest performing methods are the nonlinear autoregressive neural network, rough sets method, and monthly replacement. A high estimation accuracy (root mean square error (RMSE) of about 0.03 m/m) was found in the nonlinear autoregressive network, due to its regression based dynamic network which allows feedback connections through discrete-time estimation. An equally high accuracy (0.05 m/m RMSE) in the rough sets procedure illustrates the important role of temporal persistence of soil moisture, with the capability to account for different soil moisture conditions.

Use of satellite and modelled soil moisture data for predicting event soil loss at plot scale

NASA Astrophysics Data System (ADS)

Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

2015-03-01

The potential of coupling soil moisture and a~USLE-based model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in Central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e. the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the RUSLE/USLE, enhances the capability of the model to account for variations in event soil losses, being the soil moisture an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to of ~ 0.35 and a root-mean-square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

Enhancement and inhibition of microbial activity in hydrocarbon- contaminated arctic soils: Implications for nutrient-amended bioremediation

USGS Publications Warehouse

Braddock, J.F.; Ruth, M.L.; Catterall, P.H.; Walworth, J.L.; McCarthy, K.A.

1997-01-01

Bioremediation is being used or proposed as a treatment option at many hydrocarbon-contaminated sites. One such site is a former bulk-fuel storage facility near Barrow, AK, where contamination persists after approximately 380 m3 of JP-5 was spilled in 1970. The soil at the site is primarily coarse sand with low organic carbon (<1%) end low moisture (1-3%) contents. We examined the effects of nutrient additions on microorganisms in contaminated soil from this site in laboratory microcosms and in mesocosms incubated for 6 weeks in the field. Nitrogen was the major limiting nutrient in this system, but microbial populations and activity were maximally enhanced by additions of both nitrogen and phosphorus. When nutrients were added to soil in the field at three levels of N:P (100:45, 200:90, and 300:135 mg/kg soil), the greatest stimulation in microbial activity occurred at the lowest, rather than the highest, level of nutrient addition. The total soil-water potentials ranged from -2 to -15 bar with increasing levels of fertilizer. Semivolatile hydrocarbon concentrations declined significantly only in the soils treated at the low fertilizer level. These results indicate that an understanding of nutrient effects at a specific site is essential for successful bioremediation.Bioremediation is being used or proposed as a treatment option at many hydrocarbon-contaminated sites. One such site is a former bulk-fuel storage facility near Barrow, AK, where contamination persists after approximately 380 m3 of JP-5 was spilled in 1970. The soil at the site is primarily coarse sand with low organic carbon (<1%) and low moisture (1-3%) contents. We examined the effects of nutrient additions on microorganisms in contaminated soil from this site in laboratory microcosms and in mesocosms incubated for 6 weeks in the field. Nitrogen was the major limiting nutrient in this system, but microbial populations and activity were maximally enhanced by additions of both nitrogen and phosphorus. When nutrients were added to soil in the field at three levels of N:P (100:45, 200:90, and 300:135 mg/kg soil), the greatest stimulation in microbial activity occurred at the lowest, rather than the highest, level of nutrient addition. The total soil-water potentials ranged from -2 to -15 bar with increasing levels of fertilizer. Semi-volatile hydrocarbon concentrations declined significantly only in the soils treated at the low fertilizer level. These results indicate that an understanding of nutrient effects at a specific site is essential for successful bioremediation.

Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

PubMed

Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

2016-05-01

Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

Root Water Uptake and Soil Moisture Pattern Dynamics - Capturing Connections, Controls and Causalities

NASA Astrophysics Data System (ADS)

Blume, T.; Heidbuechel, I.; Hassler, S. K.; Simard, S.; Guntner, A.; Stewart, R. D.; Weiler, M.

2015-12-01

We hypothesize that there is a shift in controls on landscape scale soil moisture patterns when plants become active during the growing season. Especially during the summer soil moisture patterns are not only controlled by soils, topography and related abiotic site characteristics but also by root water uptake. Root water uptake influences soil moisture patterns both in the lateral and vertical direction. Plant water uptake from different soil depths is estimated based on diurnal fluctuations in soil moisture content and was investigated with a unique setup of 46 field sites in Luxemburg and 15 field sites in Germany. These sites cover a range of geologies, soils, topographic positions and types of vegetation. Vegetation types include pasture, pine forest (young and old) and different deciduous forest stands. Available data at all sites includes information at high temporal resolution from 3-5 soil moisture and soil temperature profiles, matrix potential, piezometers and sapflow sensors as well as standard climate data. At sites with access to a stream, discharge or water level is also recorded. The analysis of soil moisture patterns over time indicates a shift in regime depending on season. Depth profiles of root water uptake show strong differences between different forest stands, with maximum depths ranging between 50 and 200 cm. Temporal dynamics of signal strength within the profile furthermore suggest a locally shifting spatial distribution of root water uptake depending on water availability. We will investigate temporal thresholds (under which conditions spatial patterns of root water uptake become most distinct) as well as landscape controls on soil moisture and root water uptake dynamics.

Soil Moisture Retrieval Using Convolutional Neural Networks: Application to Passive Microwave Remote Sensing

NASA Astrophysics Data System (ADS)

Hu, Z.; Xu, L.; Yu, B.

2018-04-01

A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN). Soil moisture plays an important role in the water cycle. However, with the rapidly increasing of the acquiring technology for remotely sensed data, it's a hard task for remote sensing practitioners to find a fast and convenient model to deal with the massive data. In this paper, the AMSR-E brightness temperatures are used to train CNN for the prediction of the European centre for medium-range weather forecasts (ECMWF) model. Compared with the classical inversion methods, the deep learning-based method is more suitable for global soil moisture retrieval. It is very well supported by graphics processing unit (GPU) acceleration, which can meet the demand of massive data inversion. Once the model trained, a global soil moisture map can be predicted in less than 10 seconds. What's more, the method of soil moisture retrieval based on deep learning can learn the complex texture features from the big remote sensing data. In this experiment, the results demonstrates that the CNN deployed to retrieve global soil moisture can achieve a better performance than the support vector regression (SVR) for soil moisture retrieval.

An Overview of Production and Validation of the SMAP Passive Soil Moisture Product

NASA Technical Reports Server (NTRS)

Chan, S.; O'Neill, P.; Njoku, E.; Jackson, T.; Bindlish, R.

2015-01-01

The Soil Moisture Active Passive (SMAP) mission is an L-band mission scheduled for launch in Jan. 2015. The SMAP instruments consist of a radar and a radiometer to obtain complementary information from space for soil moisture and freeze/thaw state research and applications. By utilizing novel designs in antenna construction, retrieval algorithms, and acquisition hardware, SMAP provides a capability for global mapping of soil moisture and freeze/thaw state with unprecedented accuracy, resolution, and coverage. This improvement in hydrosphere state measurement is expected to advance our understanding of the processes that link the terrestrial water, energy and carbon cycles, improve our capability in flood prediction and drought monitoring, and enhance our skills in weather and climate forecast. For swath-based soil moisture measurement, SMAP generates three operational geophysical data products: (1) the radiometer-only soil moisture product (L2_SM_P) posted at 36-kilometer resolution, (2) the radar-only soil moisture product (L2_SM_A) posted at 3-kilometers resolution, and (3) the radar-radiometer combined soil moisture product (L2_SM_AP) posted at 9-kilometers resolution. Each product draws on the strengths of the underlying sensor(s) and plays a unique role in hydroclimatological and hydrometeorological applications. A full suite of SMAP data products is given in Table 1.

Can the normalized soil moisture index improve the prediction of soil organic carbon based on hyperspectral remote sensing data?

NASA Astrophysics Data System (ADS)

van Wesemael, Bas; Nocita, Marco

2016-04-01

One of the problems for mapping of soil organic carbon (SOC) at large-scale based on visible - near and short wave infrared (VIS-NIR-SWIR) remote sensing techniques is the spatial variation of topsoil moisture when the images are collected. Soil moisture is certainly an aspect causing biased SOC estimations, due to the problems in discriminating reflectance differences due to either variations in organic matter or soil moisture, or their combination. In addition, the difficult validation procedures make the accurate estimation of soil moisture from optical airborne a major challenge. After all, the first millimeters of the soil surface reflect the signal to the airborne sensor and show a large spatial, vertical and temporal variation in soil moisture. Hence, the difficulty of assessing the soil moisture of this thin layer at the same moment of the flight. The creation of a soil moisture proxy, directly retrievable from the hyperspectral data is a priority to improve the large-scale prediction of SOC. This paper aims to verify if the application of the normalized soil moisture index (NSMI) to Airborne Prima Experiment (APEX) hyperspectral images could improve the prediction of SOC. The study area was located in the loam region of Wallonia, Belgium. About 40 samples were collected from bare fields covered by the flight lines, and analyzed in the laboratory. Soil spectra, corresponding to the sample locations, were extracted from the images. Once the NSMI was calculated for the bare fields' pixels, spatial patterns, presumably related to within field soil moisture variations, were revealed. SOC prediction models, built using raw and pre-treated spectra, were generated from either the full dataset (general model), or pixels belonging to one of the two classes of NSMI values (NSMI models). The best result, with a RMSE after validation of 1.24 g C kg-1, was achieved with a NSMI model, compared to the best general model, characterized by a RMSE of 2.11 g C kg-1. These results confirmed the advantage to controlling the effect of soil moisture on the detection of SOC. The NSMI proved to be a flexible concept, due to the possible use of different SWIR wavelengths, and ease of use, because measurements of soil moisture by other techniques are not needed. However, in the future, it will be important to assess the effectiveness of the NSMI for different soil types, and other hyperspectral sensors.

Soil moisture-soil temperature interrelationships on a sandy-loam soil exposed to full sunlight

Treesearch

David A. Marquis

1967-01-01

In a study of birch regeneration in New Hampshire, soil moisture and temperature were found to be intimately related. Not only does low moisture lead to high temperature, but high temperature undoubtedly accelerates soil drying, setting up a vicious cycle of heating and drying that may prevent seed germination or kill seedlings.

Soil-Site Factors Affecting Southern Upland Oak Managment and Growth

Treesearch

John K. Francis

1980-01-01

Soil supplies trees with physical support, moisture, oxygen, and nutrients. Amount of moisture most limits tree growth; and soil and topographic factors such as texture and aspect, which influence available soil moisture. are most useful in predicting growth. Equations that include soil and topographic variables can be used to predict site index. Foresters can also...

MoisturEC: A New R Program for Moisture Content Estimation from Electrical Conductivity Data.

PubMed

Terry, Neil; Day-Lewis, Frederick D; Werkema, Dale; Lane, John W

2018-03-06

Noninvasive geophysical estimation of soil moisture has potential to improve understanding of flow in the unsaturated zone for problems involving agricultural management, aquifer recharge, and optimization of landfill design and operations. In principle, several geophysical techniques (e.g., electrical resistivity, electromagnetic induction, and nuclear magnetic resonance) offer insight into soil moisture, but data-analysis tools are needed to "translate" geophysical results into estimates of soil moisture, consistent with (1) the uncertainty of this translation and (2) direct measurements of moisture. Although geostatistical frameworks exist for this purpose, straightforward and user-friendly tools are required to fully capitalize on the potential of geophysical information for soil-moisture estimation. Here, we present MoisturEC, a simple R program with a graphical user interface to convert measurements or images of electrical conductivity (EC) to soil moisture. Input includes EC values, point moisture estimates, and definition of either Archie parameters (based on experimental or literature values) or empirical data of moisture vs. EC. The program produces two- and three-dimensional images of moisture based on available EC and direct measurements of moisture, interpolating between measurement locations using a Tikhonov regularization approach. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Soil Tillage Management Affects Maize Grain Yield by Regulating Spatial Distribution Coordination of Roots, Soil Moisture and Nitrogen Status.

PubMed

Wang, Xinbing; Zhou, Baoyuan; Sun, Xuefang; Yue, Yang; Ma, Wei; Zhao, Ming

2015-01-01

The spatial distribution of the root system through the soil profile has an impact on moisture and nutrient uptake by plants, affecting growth and productivity. The spatial distribution of the roots, soil moisture, and fertility are affected by tillage practices. The combination of high soil density and the presence of a soil plow pan typically impede the growth of maize (Zea mays L.).We investigated the spatial distribution coordination of the root system, soil moisture, and N status in response to different soil tillage treatments (NT: no-tillage, RT: rotary-tillage, SS: subsoiling) and the subsequent impact on maize yield, and identify yield-increasing mechanisms and optimal soil tillage management practices. Field experiments were conducted on the Huang-Huai-Hai plain in China during 2011 and 2012. The SS and RT treatments significantly reduced soil bulk density in the top 0-20 cm layer of the soil profile, while SS significantly decreased soil bulk density in the 20-30 cm layer. Soil moisture in the 20-50 cm profile layer was significantly higher for the SS treatment compared to the RT and NT treatment. In the 0-20 cm topsoil layer, the NT treatment had higher soil moisture than the SS and RT treatments. Root length density of the SS treatment was significantly greater than density of the RT and NT treatments, as soil depth increased. Soil moisture was reduced in the soil profile where root concentration was high. SS had greater soil moisture depletion and a more concentration root system than RT and NT in deep soil. Our results suggest that the SS treatment improved the spatial distribution of root density, soil moisture and N states, thereby promoting the absorption of soil moisture and reducing N leaching via the root system in the 20-50 cm layer of the profile. Within the context of the SS treatment, a root architecture densely distributed deep into the soil profile, played a pivotal role in plants' ability to access nutrients and water. An optimal combination of deeper deployment of roots and resource (water and N) availability was realized where the soil was prone to leaching. The correlation between the depletion of resources and distribution of patchy roots endorsed the SS tillage practice. It resulted in significantly greater post-silking biomass and grain yield compared to the RT and NT treatments, for summer maize on the Huang-Huai-Hai plain.

Soil Tillage Management Affects Maize Grain Yield by Regulating Spatial Distribution Coordination of Roots, Soil Moisture and Nitrogen Status

PubMed Central

Wang, Xinbing; Zhou, Baoyuan; Sun, Xuefang; Yue, Yang; Ma, Wei; Zhao, Ming

2015-01-01

The spatial distribution of the root system through the soil profile has an impact on moisture and nutrient uptake by plants, affecting growth and productivity. The spatial distribution of the roots, soil moisture, and fertility are affected by tillage practices. The combination of high soil density and the presence of a soil plow pan typically impede the growth of maize (Zea mays L.).We investigated the spatial distribution coordination of the root system, soil moisture, and N status in response to different soil tillage treatments (NT: no-tillage, RT: rotary-tillage, SS: subsoiling) and the subsequent impact on maize yield, and identify yield-increasing mechanisms and optimal soil tillage management practices. Field experiments were conducted on the Huang-Huai-Hai plain in China during 2011 and 2012. The SS and RT treatments significantly reduced soil bulk density in the top 0–20 cm layer of the soil profile, while SS significantly decreased soil bulk density in the 20–30 cm layer. Soil moisture in the 20–50 cm profile layer was significantly higher for the SS treatment compared to the RT and NT treatment. In the 0-20 cm topsoil layer, the NT treatment had higher soil moisture than the SS and RT treatments. Root length density of the SS treatment was significantly greater than density of the RT and NT treatments, as soil depth increased. Soil moisture was reduced in the soil profile where root concentration was high. SS had greater soil moisture depletion and a more concentration root system than RT and NT in deep soil. Our results suggest that the SS treatment improved the spatial distribution of root density, soil moisture and N states, thereby promoting the absorption of soil moisture and reducing N leaching via the root system in the 20–50 cm layer of the profile. Within the context of the SS treatment, a root architecture densely distributed deep into the soil profile, played a pivotal role in plants’ ability to access nutrients and water. An optimal combination of deeper deployment of roots and resource (water and N) availability was realized where the soil was prone to leaching. The correlation between the depletion of resources and distribution of patchy roots endorsed the SS tillage practice. It resulted in significantly greater post-silking biomass and grain yield compared to the RT and NT treatments, for summer maize on the Huang-Huai-Hai plain. PMID:26098548

Different rates of soil drying after rainfall are observed by the SMOS satellite and the South Fork In Situ Soil Moisture Network

USDA-ARS?s Scientific Manuscript database

Soil moisture affects the spatial variation of land–atmosphere interactions through its in'uence on the balance of latent and sensible heat 'ux. Wetter soils are more prone to 'ooding because a smaller fraction of rainfall can in'ltrate into the soil. The Soil Moisture and Oceanic Salinity (SMOS) sa...

[Variation characteristics of soil moisture in apple orchards of Luochuan County, Shaanxi Province of Northwest China].

PubMed

Wang, Yan-Ping; Han, Ming-Yu; Zhang, Lin-Sen; Dang, Yong-Jian; Qu, Jun-Tao

2012-03-01

To have an overall understanding on the soil moisture characteristics in the apple orchards of Luochuan County can not only provide theoretical basis for selecting apple orchard sites, choosing the best root-stock combination, and improving the soil water management, but also has reference importance in increasing the productive efficiency of our apple orchards. In this study, a fixed-point continuous monitoring was conducted on the overall soil moisture environment and the variation characteristics of soil moisture in the County apple orchards differed in age class, stand type, and tree type (standard or dwarfed). For the apple orchards in the County, the rhizosphere (0-200 cm) soils of most apple trees were water-deficient, and the deficit in 0-60 cm soil layer was less than that in 60-200 cm layer. During growth season, the water storage in 0-60 cm soil layer had the same variation trend as the rainfall pattern. The relative soil moisture content in most orchards was less than 60% , and seasonal drought was quite severe. The coefficient of variation of soil moisture content decreased with soil depth. With the increasing age of the orchards, soil water storage decreased. At the same planting density, the orchards with dwarfed trees had more water storage in 0-5 m soil layer than the orchards with standard trees. However, when the orchards were planted with dwarfed trees at a higher density, the soil water storage in the orchards with dwarfed trees was lesser than that in the standard orchards. The mature orchards on highland had the highest soil moisture content, followed by the mature orchards on flat land, and on terraced land. Tree density had great effects on the soil moisture content. When the tree density was the same, planting dwarfed trees could decrease the water consumption, and increase the soil moisture content significantly. To decrease the planting density through the removal of trees would be an effective way to maintain the soil water balance of apple orchards, and achieve the sustainable development of the orchards.

Evaluating new SMAP soil moisture for drought monitoring in the rangelands of the US High Plains

USGS Publications Warehouse

Velpuri, Naga Manohar; Senay, Gabriel B.; Morisette, Jeffrey T.

2016-01-01

Level 3 soil moisture datasets from the recently launched Soil Moisture Active Passive (SMAP) satellite are evaluated for drought monitoring in rangelands.Validation of SMAP soil moisture (SSM) with in situ and modeled estimates showed high level of agreement.SSM showed the highest correlation with surface soil moisture (0-5 cm) and a strong correlation to depths up to 20 cm.SSM showed a reliable and expected response of capturing seasonal dynamics in relation to precipitation, land surface temperature, and evapotranspiration.Further evaluation using multi-year SMAP datasets is necessary to quantify the full benefits and limitations for drought monitoring in rangelands.

Low-Cost Soil Moisture Profile Probe Using Thin-Film Capacitors and a Capacitive Touch Sensor.

PubMed

Kojima, Yuki; Shigeta, Ryo; Miyamoto, Naoya; Shirahama, Yasutomo; Nishioka, Kazuhiro; Mizoguchi, Masaru; Kawahara, Yoshihiro

2016-08-15

Soil moisture is an important property for agriculture, but currently commercialized soil moisture sensors are too expensive for many farmers. The objective of this study is to develop a low-cost soil moisture sensor using capacitors on a film substrate and a capacitive touch integrated circuit. The performance of the sensor was evaluated in two field experiments: a grape field and a mizuna greenhouse field. The developed sensor captured dynamic changes in soil moisture at 10, 20, and 30 cm depth, with a period of 10-14 days required after sensor installation for the contact between capacitors and soil to settle down. The measured soil moisture showed the influence of individual sensor differences, and the influence masked minor differences of less than 0.05 m³·m(-3) in the soil moisture at different locations. However, the developed sensor could detect large differences of more than 0.05 m³·m(-3), as well as the different magnitude of changes, in soil moisture. The price of the developed sensor was reduced to 300 U.S. dollars and can be reduced even more by further improvements suggested in this study and by mass production. Therefore, the developed sensor will be made more affordable to farmers as it requires low financial investment, and it can be utilized for decision-making in irrigation.

Low-Cost Soil Moisture Profile Probe Using Thin-Film Capacitors and a Capacitive Touch Sensor

PubMed Central

Kojima, Yuki; Shigeta, Ryo; Miyamoto, Naoya; Shirahama, Yasutomo; Nishioka, Kazuhiro; Mizoguchi, Masaru; Kawahara, Yoshihiro

2016-01-01

Soil moisture is an important property for agriculture, but currently commercialized soil moisture sensors are too expensive for many farmers. The objective of this study is to develop a low-cost soil moisture sensor using capacitors on a film substrate and a capacitive touch integrated circuit. The performance of the sensor was evaluated in two field experiments: a grape field and a mizuna greenhouse field. The developed sensor captured dynamic changes in soil moisture at 10, 20, and 30 cm depth, with a period of 10–14 days required after sensor installation for the contact between capacitors and soil to settle down. The measured soil moisture showed the influence of individual sensor differences, and the influence masked minor differences of less than 0.05 m3·m−3 in the soil moisture at different locations. However, the developed sensor could detect large differences of more than 0.05 m3·m−3, as well as the different magnitude of changes, in soil moisture. The price of the developed sensor was reduced to 300 U.S. dollars and can be reduced even more by further improvements suggested in this study and by mass production. Therefore, the developed sensor will be made more affordable to farmers as it requires low financial investment, and it can be utilized for decision-making in irrigation. PMID:27537881

Uncertainty in Ecohydrological Modeling in an Arid Region Determined with Bayesian Methods

PubMed Central

Yang, Junjun; He, Zhibin; Du, Jun; Chen, Longfei; Zhu, Xi

2016-01-01

In arid regions, water resources are a key forcing factor in ecosystem circulation, and soil moisture is the critical link that constrains plant and animal life on the soil surface and underground. Simulation of soil moisture in arid ecosystems is inherently difficult due to high variability. We assessed the applicability of the process-oriented CoupModel for forecasting of soil water relations in arid regions. We used vertical soil moisture profiling for model calibration. We determined that model-structural uncertainty constituted the largest error; the model did not capture the extremes of low soil moisture in the desert-oasis ecotone (DOE), particularly below 40 cm soil depth. Our results showed that total uncertainty in soil moisture prediction was improved when input and output data, parameter value array, and structure errors were characterized explicitly. Bayesian analysis was applied with prior information to reduce uncertainty. The need to provide independent descriptions of uncertainty analysis (UA) in the input and output data was demonstrated. Application of soil moisture simulation in arid regions will be useful for dune-stabilization and revegetation efforts in the DOE. PMID:26963523

Passive Microwave Soil Moisture Retrieval through Combined Radar/Radiometer Ground Based Simulator with Special Reference to Dielectric Schemes

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K., ,, Dr.; O'Neill, Peggy, ,, Dr.

2014-05-01

Soil moisture is an important element for weather and climate prediction, hydrological sciences, and applications. Hence, measurements of this hydrologic variable are required to improve our understanding of hydrological processes, ecosystem functions, and the linkages between the Earth's water, energy, and carbon cycles (Srivastava et al. 2013). The retrieval of soil moisture depends not only on parameterizations in the retrieval algorithm but also on the soil dielectric mixing models used (Behari 2005). Although a number of soil dielectric mixing models have been developed, testing these models for soil moisture retrieval has still not been fully explored, especially with SMAP-like simulators. The main objective of this work focuses on testing different dielectric models for soil moisture retrieval using the Combined Radar/Radiometer (ComRAD) ground-based L-band simulator developed jointly by NASA/GSFC and George Washington University (O'Neill et al., 2006). The ComRAD system was deployed during a field experiment in 2012 in order to provide long active/passive measurements of two crops under controlled conditions during an entire growing season. L-band passive data were acquired at a look angle of 40 degree from nadir at both horizontal & vertical polarization. Currently, there are many dielectric models available for soil moisture retrieval; however, four dielectric models (Mironov, Dobson, Wang & Schmugge and Hallikainen) were tested here and found to be promising for soil moisture retrieval (some with higher performances). All the above-mentioned dielectric models were integrated with Single Channel Algorithms using H (SCA-H) and V (SCA-V) polarizations for the soil moisture retrievals. All the ground-based observations were collected from test site-United States Department of Agriculture (USDA) OPE3, located a few miles away from NASA GSFC. Ground truth data were collected using a theta probe and in situ sensors which were then used for validation. Analysis indicated a higher performance in terms of soil moisture retrieval accuracy for the Mironov dielectric model (RMSE of 0.035 m3/m3), followed by Dobson, Wang & Schmugge, and Hallikainen. This analysis indicates that Mironov dielectric model is promising for passive-only microwave soil moisture retrieval and could be a useful choice for SMAP satellite soil moisture retrieval. Keywords: Dielectric models; Single Channel Algorithm, Combined Radar/Radiometer, Soil moisture; L band References: Behari, J. (2005). Dielectric Behavior of Soil (pp. 22-40). Springer Netherlands O'Neill, P. E., Lang, R. H., Kurum, M., Utku, C., & Carver, K. R. (2006), Multi-Sensor Microwave Soil Moisture Remote Sensing: NASA's Combined Radar/Radiometer (ComRAD) System. In IEEE MicroRad, 2006 (pp. 50-54). IEEE. Srivastava, P. K., Han, D., Rico Ramirez, M. A., & Islam, T. (2013), Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology, 498, 292-304. USDA OPE3 web site at http://www.ars.usda.gov/Research/.

Advances in Assimilation of Satellite-Based Passive Microwave Observations for Soil-Moisture Estimation

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J. M.; Pauwels, Valentijn; Reichle, Rolf H.; Draper, Clara; Koster, Randy; Liu, Qing

2012-01-01

Satellite-based microwave measurements have long shown potential to provide global information about soil moisture. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS, [1]) mission as well as the future National Aeronautics and Space Administration (NASA) Soil Moisture Active and Passive (SMAP, [2]) mission measure passive microwave emission at L-band frequencies, at a relatively coarse (40 km) spatial resolution. In addition, SMAP will measure active microwave signals at a higher spatial resolution (3 km). These new L-band missions have a greater sensing depth (of -5cm) compared with past and present C- and X-band microwave sensors. ESA currently also disseminates retrievals of SMOS surface soil moisture that are derived from SMOS brightness temperature observations and ancillary data. In this research, we address two major challenges with the assimilation of recent/future satellite-based microwave measurements: (i) assimilation of soil moisture retrievals versus brightness temperatures for surface and root-zone soil moisture estimation and (ii) scale-mismatches between satellite observations, models and in situ validation data.

NASA Giovanni: A Tool for Visualizing, Analyzing, and Inter-comparing Soil Moisture Data

NASA Technical Reports Server (NTRS)

Teng, William; Rui, Hualan; Vollmer, Bruce; deJeu, Richard; Fang, Fan; Lei, Guang-Dih; Parinussa, Robert

2014-01-01

There are many existing satellite soil moisture algorithms and their derived data products, but there is no simple way for a user to inter-compare the products or analyze them together with other related data. An environment that facilitates such inter-comparison and analysis would be useful for validation of satellite soil moisture retrievals against in situ data and for determining the relationships between different soil moisture products. As part of the NASA Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) family of portals, which has provided users worldwide with a simple but powerful way to explore NASA data, a beta prototype Giovanni Inter-comparison of Soil Moisture Products portal has been developed. A number of soil moisture data products are currently included in the prototype portal. More will be added, based on user requirements and feedback and as resources become available. Two application examples for the portal are provided. The NASA Giovanni Soil Moisture portal is versatile and extensible, with many possible uses, for research and applications, as well as for the education community.

A New Approach in Downscaling Microwave Soil Moisture Product using Machine Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid

2016-04-01

Understating the soil moisture pattern has significant impact on flood modeling, drought monitoring, and irrigation management. Although satellite retrievals can provide an unprecedented spatial and temporal resolution of soil moisture at a global-scale, their soil moisture products (with a spatial resolution of 25-50 km) are inadequate for regional study, where a resolution of 1-10 km is needed. In this study, a downscaling approach using Genetic Programming (GP), a specialized version of Genetic Algorithm (GA), is proposed to improve the spatial resolution of satellite soil moisture products. The GP approach was applied over a test watershed in United States using the coarse resolution satellite data (25 km) from Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture products, the fine resolution data (1 km) from Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index, and ground based data including land surface temperature, vegetation and other potential physical variables. The results indicated the great potential of this approach to derive the fine resolution soil moisture information applicable for data assimilation and other regional studies.

Can we quantify the variability of soil moisture across scales using Electromagnetic Induction ?

NASA Astrophysics Data System (ADS)

Robinet, Jérémy; von Hebel, Christian; van der Kruk, Jan; Govers, Gerard; Vanderborght, Jan

2017-04-01

Soil moisture is a key variable in many natural processes. Therefore, technological and methodological advancements are of primary importance to provide accurate measurements of spatial and temporal variability of soil moisture. In that context, ElectroMagnetic Induction (EMI) instruments are often cited as a hydrogeophysical method with a large potential, through the measurement of the soil apparent electrical conductivity (ECa). To our knowledge, no studies have evaluated the potential of EMI to characterize variability of soil moisture on both agricultural and forested land covers in a (sub-) tropical environment. These differences in land use could be critical as differences in temperature, transpiration and root water uptake can have significant effect, notably on the electrical conductivity of the pore water. In this study, we used an EMI instrument to carry out a first assessment of the impact of deforestation and agriculture on soil moisture in a subtropical region in the south of Brazil. We selected slopes of different topographies (gentle vs. steep) and contrasting land uses (natural forest vs. agriculture) within two nearby catchments. At selected locations on the slopes, we measured simultaneously ECa using EMI and a depth-weighted average of the soil moisture using TDR probes installed within soil pits. We found that the temporal variability of the soil moisture could not be measured accurately with EMI, probably because of important temporal variations of the pore water electrical conductivity and the relatively small temporal variations in soil moisture content. However, we found that its spatial variability could be effectively quantified using a non-linear relationship, for both intra- and inter-slopes variations. Within slopes, the ECa could explained between 67 and 90% of the variability of the soil moisture, while a single non-linear model for all the slopes could explain 55% of the soil moisture variability. We eventually showed that combining a specific relationship for the most degraded slope (steep slope under agriculture) and a single relationship for all the other slopes, both non-linear relations, yielded the best results with an overall explained variance of 90%. We applied the latter model to measurements of the ECa along transects at the different slopes, which allowed us to highlight the strong control of topography on the soil moisture content. We also observed a significant impact of the land use with higher moisture content on the agricultural slopes, probably due to a reduced evapotranspiration.

Variability of soil moisture proxies and hot days across the climate regimes of Australia

NASA Astrophysics Data System (ADS)

Holmes, A.; Rüdiger, C.; Mueller, B.; Hirschi, M.; Tapper, N.

2017-07-01

The frequency of extreme events such as heat waves are expected to increase due to the effect of climate change, particularly in semiarid regions of Australia. Recent studies have indicated a link between soil moisture deficits and heat extremes, focusing on the coupling between the two. This study investigates the relationship between the number of hot days (Tx90) and four soil moisture proxies (Standardized Precipitation Index, Antecedent Precipitation Index, Mount's Soil Dryness Index, and Keetch-Byram Drought Index), and how the strength of this relationship changes across various climate regimes within Australia. A strong anticorrelation between Tx90 and each moisture index is found, particularly for tropical savannas and temperate regions. However, the magnitude of the increase in Tx90 with decreasing moisture is strongest in semiarid and arid regions. It is also shown that the Tx90-soil moisture relationship strengthens during the El Niño phases of El Niño-Southern Oscillation in regions which are more sensitive to changes in soil moisture.

Muiti-Sensor Historical Climatology of Satellite-Derived Global Land Surface Moisture

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Richard; Holmes, Thomas

2007-01-01

A historical climatology of continuous satellite derived global land surface soil moisture is being developed. The data set consists of surface soil moisture retrievals from observations of both historical and currently active satellite microwave sensors, including Nimbus-7 SMMR, DMSP SSM/I, TRMM TMI, and AQUA AMSR-E. The data sets span the period from November 1978 through the end of 2006. The soil moisture retrievals are made with the Land Parameter Retrieval Model, a physically-based model which was developed jointly by researchers from the above institutions. These data are significant in that they are the longest continuous data record of observational surface soil moisture at a global scale. Furthermore, while previous reports have intimated that higher frequency sensors such as on SSM/I are unable to provide meaningful information on soil moisture, our results indicate that these sensors do provide highly useful soil moisture data over significant parts of the globe, and especially in critical areas located within the Earth's many arid and semi-arid regions.

COSMOS: COsmic-ray Soil Moisture Observing System planned for the United States

NASA Astrophysics Data System (ADS)

Zweck, C.; Zreda, M.; Shuttleworth, J.; Zeng, X.

2008-12-01

Because soil water exerts a critical control on weather, climate, ecosystem, and water cycle, understanding soil moisture changes in time and space is crucial for many fields within natural sciences. A serious handicap in soil moisture measurements is the mismatch between limited point measurements using contact methods and remote sensing estimates over large areas. We present a novel method to measure soil moisture non- invasively at an intermediate spatial scale that will alleviate this problem. The method takes advantage of the dependence of cosmic-ray neutron intensity on the hydrogen content of soils (Zreda et al., Geophysical Research Letters, accepted). Low-energy cosmic-ray neutrons are produced and moderated in the soil, transported from the soil into the atmosphere where they are measured with a cosmic-ray neutron probe to provide integrated soil moisture content over a footprint of several hundred meters and a depth of a few decimeters. The method and the instrument are intended for deployment in the continental-scale COSMOS network that is designed to cover the contiguous region of the USA. Fully deployed, the COSMOS network will consist of up to 500 probes, and will provide continuous soil moisture content (together with atmospheric pressure, temperature and relative humidity) measured and reported hourly. These data will be used for initialization and assimilation of soil moisture conditions in weather and short-term (seasonal) climate forecasting, and for other land-surface applications.

Exchange of carbonyl sulfide (OCS) between soils and atmosphere under various CO2 concentrations

NASA Astrophysics Data System (ADS)

Bunk, Rüdiger; Behrendt, Thomas; Yi, Zhigang; Andreae, Meinrat O.; Kesselmeier, Jürgen

2017-06-01

A new continuous integrated cavity output spectroscopy analyzer and an automated soil chamber system were used to investigate the exchange processes of carbonyl sulfide (OCS) between soils and the atmosphere under laboratory conditions. The exchange patterns of OCS between soils and the atmosphere were found to be highly dependent on soil moisture and ambient CO2 concentration. With increasing soil moisture, OCS exchange ranged from emission under dry conditions to an uptake within an optimum moisture range, followed again by emission at high soil moisture. Elevated CO2 was found to have a significant impact on the exchange rate and direction as tested with several soils. There is a clear tendency toward a release of OCS at higher CO2 levels (up to 7600 ppm), which are typical for the upper few centimeters within soils. At high soil moisture, the release of OCS increased sharply. Measurements after chloroform vapor application show that there is a biotic component to the observed OCS exchange. Furthermore, soil treatment with the fungi inhibitor nystatin showed that fungi might be the dominant OCS consumers in the soils we examined. We discuss the influence of soil moisture and elevated CO2 on the OCS exchange as a change in the activity of microbial communities. Physical factors such as diffusivity that are governed by soil moisture also play a role. Comparing KM values of the enzymes to projected soil water CO2 concentrations showed that competitive inhibition is unlikely for carbonic anhydrase and PEPCO but might occur for RubisCO at higher CO2 concentrations.

Estimating surface soil moisture from SMAP observations using a neural network technique

USDA-ARS?s Scientific Manuscript database

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to June 2016 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observ...

An approach to constructing a homogeneous time series of soil mositure using SMOS

USDA-ARS?s Scientific Manuscript database

Overlapping soil moisture time series derived from two satellite microwave radiometers (SMOS, Soil Moisture and Ocean Salinity; AMSR-E, Advanced Microwave Scanning Radiometer - Earth Observing System) are used to generate a soil moisture time series from 2003 to 2010. Two statistical methodologies f...

Linking carbon and water relations to drought-induced mortality in Pinus flexilis seedlings.

PubMed

Reinhardt, Keith; Germino, Matthew J; Kueppers, Lara M; Domec, Jean-Christophe; Mitton, Jeffry

2015-07-01

Survival of tree seedlings at high elevations has been shown to be limited by thermal constraints on carbon balance, but it is unknown if carbon relations also limit seedling survival at lower elevations, where water relations may be more important. We measured and modeled carbon fluxes and water relations in first-year Pinus flexilis seedlings in garden plots just beyond the warm edge of their natural range, and compared these with dry-mass gain and survival across two summers. We hypothesized that mortality in these seedlings would be associated with declines in water relations, more so than with carbon-balance limitations. Rather than gradual declines in survivorship across growing seasons, we observed sharp, large-scale mortality episodes that occurred once volumetric soil-moisture content dropped below 10%. By this point, seedling water potentials had decreased below -5 MPa, seedling hydraulic conductivity had decreased by 90% and seedling hydraulic resistance had increased by >900%. Additionally, non-structural carbohydrates accumulated in aboveground tissues at the end of both summers, suggesting impairments in phloem-transport from needles to roots. This resulted in low carbohydrate concentrations in roots, which likely impaired root growth and water uptake at the time of critically low soil moisture. While photosynthesis and respiration on a leaf area basis remained high until critical hydraulic thresholds were exceeded, modeled seedling gross primary productivity declined steadily throughout the summers. At the time of mortality, modeled productivity was insufficient to support seedling biomass-gain rates, metabolism and secondary costs. Thus the large-scale mortality events that we observed near the end of each summer were most directly linked with acute, episodic declines in plant hydraulic function that were linked with important changes in whole-seedling carbon relations. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Space-time modeling of soil moisture

NASA Astrophysics Data System (ADS)

Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

2017-11-01

A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

SoilNet - A Zigbee based soil moisture sensor network

NASA Astrophysics Data System (ADS)

Bogena, H. R.; Weuthen, A.; Rosenbaum, U.; Huisman, J. A.; Vereecken, H.

2007-12-01

Soil moisture plays a key role in partitioning water and energy fluxes, in providing moisture to the atmosphere for precipitation, and controlling the pattern of groundwater recharge. Large-scale soil moisture variability is driven by variation of precipitation and radiation in space and time. At local scales, land cover, soil conditions, and topography act to redistribute soil moisture. Despite the importance of soil moisture, it is not yet measured in an operational way, e.g. for a better prediction of hydrological and surface energy fluxes (e.g. runoff, latent heat) at larger scales and in the framework of the development of early warning systems (e.g. flood forecasting) and the management of irrigation systems. The SoilNet project aims to develop a sensor network for the near real-time monitoring of soil moisture changes at high spatial and temporal resolution on the basis of the new low-cost ZigBee radio network that operates on top of the IEEE 802.15.4 standard. The sensor network consists of soil moisture sensors attached to end devices by cables, router devices and a coordinator device. The end devices are buried in the soil and linked wirelessly with nearby aboveground router devices. This ZigBee wireless sensor network design considers channel errors, delays, packet losses, and power and topology constraints. In order to conserve battery power, a reactive routing protocol is used that determines a new route only when it is required. The sensor network is also able to react to external influences, e.g. such as rainfall occurrences. The SoilNet communicator, routing and end devices have been developed by the Forschungszentrum Juelich and will be marketed through external companies. We will present first results of experiments to verify network stability and the accuracy of the soil moisture sensors. Simultaneously, we have developed a data management and visualisation system. We tested the wireless network on a 100 by 100 meter forest plot equipped with 25 end devices each consisting of 6 vertically arranged soil moisture sensors. The next step will be the instrumentation of two small catchments (~30 ha) with a 30 m spacing of the end devices. juelich.de/icg/icg-4/index.php?index=739

Enhancing soil moisture monitoring via cosmic-ray neutron sensing in farmlands by combining field site tests with an uncertainty analysis

NASA Astrophysics Data System (ADS)

Oswald, S. E.; Scheiffele, L. M.; Baroni, G.; Ingwersen, J.; Schrön, M.

2017-12-01

One application of Cosmic-Ray Neutron Sensing (CRNS) is to investigate soil moisture on agricultural fields during the crop season. This fully employs the non-invasive character of CRNS without interference with agricultural practices of the farmland. The changing influence of vegetation on CRNS has to be dealt with as well as spatio-temporal influences, e.g. by irrigation or harvest. Previous work revealed that the CRNS signal on farmland shows complex and non-unique response because of the hydrogen pools in different depths and distances. This creates a challenge for soil moisture estimation and subsequent use for irrigation management or hydrological modelling. Thus, a special aim of our study was to assess the uncertainty of CRNS in cropped fields and to identify underlying causes of uncertainty. We have applied CRNS at two field sites during the growing season that were accompanied by intensive measurements of soil moisture, vegetation parameters, and irrigation events. Sources of uncertainty were identified from the experimental data. A Monte Carlo approach was used to propagate these uncertainties to CRNS soil moisture estimations. In addition, a sensitivity analysis was performed to identify the most important factors explaining this uncertainty. Results showed that CRNS soil moisture compares well to the soil moisture network when the point values were converted to weighted water content with all hydrogen pools included. However, when considered as a stand-alone method to retrieve volumetric soil moisture, the performance decreased. The support volume including its penetration depth showed also a considerable uncertainty, especially in relatively dry soil moisture conditions. Of seven factors analyzed, actual soil moisture profile, bulk density, incoming neutron correction and calibrated parameter N0 were found to play an important role. One possible improvement could be a simple correction factor based on independent data of soil moisture profiles to better account for the sensitivity of the CRNS signal to the upper soil layers. This is an important step to improve the method for validation of remote sensing products or agricultural water management and establish CRNS as an applied monitoring tool on farmland.

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

NASA Astrophysics Data System (ADS)

Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry

2017-05-01

In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

Land surface-precipitation feedback analysis for a landfalling monsoon depression in the Indian region

NASA Astrophysics Data System (ADS)

Baisya, Himadri; Pattnaik, Sandeep; Rajesh, P. V.

2017-03-01

A series of numerical experiments are carried out to investigate the sensitivity of a landfalling monsoon depression to land surface conditions using the Weather Research and Forecasting (WRF) model. Results suggest that precipitation is largely modulated by moisture influx and precipitation efficiency. Three cloud microphysical schemes (WSM6, WDM6, and Morrison) are examined, and Morrison is chosen for assessing the land surface-precipitation feedback analysis, owing to better precipitation forecast skills. It is found that increased soil moisture facilitates Moisture Flux Convergence (MFC) with reduced moisture influx, whereas a reduced soil moisture condition facilitates moisture influx but not MFC. A higher Moist Static Energy (MSE) is noted due to increased evapotranspiration in an elevated moisture scenario which enhances moist convection. As opposed to moist surface, sensible heat dominates in a reduced moisture scenario, ensued by an overall reduction in MSE throughout the Planetary Boundary Layer (PBL). Stability analysis shows that Convective Available Potential Energy (CAPE) is comparable in magnitude for both increased and decreased moisture scenarios, whereas Convective Inhibition (CIN) shows increased values for the reduced moisture scenario as a consequence of drier atmosphere leading to suppression of convection. Simulations carried out with various fixed soil moisture levels indicate that the overall precipitation features of the storm are characterized by initial soil moisture condition, but precipitation intensity at any instant is modulated by soil moisture availability. Overall results based on this case study suggest that antecedent soil moisture plays a crucial role in modulating precipitation distribution and intensity of a monsoon depression.

Quantifying the hydrological responses to climate change in an intact forested small watershed in Southern China

USGS Publications Warehouse

Zhou, G.; Wei, X.; Wu, Y.; Huang, Y.; Yan, J.; Zhang, Dongxiao; Zhang, Q.; Liu, J.; Meng, Z.; Wang, C.; Chu, G.; Liu, S.; Tang, X.; Liu, Xiuying

2011-01-01

Responses of hydrological processes to climate change are key components in the Intergovernmental Panel for Climate Change (IPCC) assessment. Understanding these responses is critical for developing appropriate mitigation and adaptation strategies for sustainable water resources management and protection of public safety. However, these responses are not well understood and little long-term evidence exists. Herein, we show how climate change, specifically increased air temperature and storm intensity, can affect soil moisture dynamics and hydrological variables based on both long-term observation and model simulations using the Soil and Water Assessment Tool (SWAT) in an intact forested watershed (the Dinghushan Biosphere Reserve) in Southern China. Our results show that, although total annual precipitation changed little from 1950 to 2009, soil moisture decreased significantly. A significant decline was also found in the monthly 7-day low flow from 2000 to 2009. However, the maximum daily streamflow in the wet season and unconfined groundwater tables have significantly increased during the same 10-year period. The significant decreasing trends on soil moisture and low flow variables suggest that the study watershed is moving towards drought-like condition. Our analysis indicates that the intensification of rainfall storms and the increasing number of annual no-rain days were responsible for the increasing chance of both droughts and floods. We conclude that climate change has indeed induced more extreme hydrological events (e.g. droughts and floods) in this watershed and perhaps other areas of Southern China. This study also demonstrated usefulness of our research methodology and its possible applications on quantifying the impacts of climate change on hydrology in any other watersheds where long-term data are available and human disturbance is negligible. ?? 2011 Blackwell Publishing Ltd.

Quantifying the hydrological responses to climate change in an intact forested small watershed in southern China

USGS Publications Warehouse

Zhou, Guo-Yi; Wei, Xiaohua; Wu, Yiping; Liu, Shu-Guang; Huang, Yuhui; Yan, Junhua; Zhang, Deqiang; Zhang, Qianmei; Liu, Juxiu; Meng, Ze; Wang, Chunlin; Chu, Guowei; Liu, Shizhong; Tang, Xu-Li; Liu, Xiaodong

2011-01-01

Responses of hydrological processes to climate change are key components in the Intergovernmental Panel for Climate Change (IPCC) assessment. Understanding these responses is critical for developing appropriate mitigation and adaptation strategies for sustainable water resources management and protection of public safety. However, these responses are not well understood and little long-term evidence exists. Herein, we show how climate change, specifically increased air temperature and storm intensity, can affect soil moisture dynamics and hydrological variables based on both long-term observation and model simulations using the Soil and Water Assessment Tool (SWAT) in an intact forested watershed (the Dinghushan Biosphere Reserve) in Southern China. Our results show that, although total annual precipitation changed little from 1950 to 2009, soil moisture decreased significantly. A significant decline was also found in the monthly 7-day low flow from 2000 to 2009. However, the maximum daily streamflow in the wet season and unconfined groundwater tables have significantly increased during the same 10-year period. The significant decreasing trends on soil moisture and low flow variables suggest that the study watershed is moving towards drought-like condition. Our analysis indicates that the intensification of rainfall storms and the increasing number of annual no-rain days were responsible for the increasing chance of both droughts and floods. We conclude that climate change has indeed induced more extreme hydrological events (e.g. droughts and floods) in this watershed and perhaps other areas of Southern China. This study also demonstrated usefulness of our research methodology and its possible applications on quantifying the impacts of climate change on hydrology in any other watersheds where long-term data are available and human disturbance is negligible.

Topographic Controls on Spatial Patterns of Soil Texture and Moisture in a Semi-arid Montane Catchment with Aspect-Dependent Vegetation

NASA Astrophysics Data System (ADS)

Lehman, B. M.; Niemann, J. D.

2008-12-01

Soil moisture exerts significant control over the partitioning of latent and sensible energy fluxes, the magnitude of both vertical and lateral water fluxes, the physiological and water-use characteristics of vegetation, and nutrient cycling. Considerable progress has been made in determining how soil characteristics, topography, and vegetation influence spatial patterns of soil moisture in humid environments at the catchment, hillslope, and plant scales. However, understanding of the controls on soil moisture patterns beyond the plant scale in semi-arid environments remains more limited. This study examines the relationships between the spatial patterns of near surface soil moisture (upper 5 cm), terrain indices, and soil properties in a small, semi-arid, montane catchment. The 8 ha catchment, located in the Cache La Poudre River Canyon in north-central Colorado, has a total relief of 115 m and an average elevation of 2193 m. It is characterized by steep slopes and shallow, gravelly/sandy soils with scattered granite outcroppings. Depth to bedrock ranges from 0 m to greater than 1 m. Vegetation in the catchment is highly correlated with topographic aspect. In particular, north-facing hillslopes are predominately vegetated by ponderosa pines, while south-facing slopes are mostly vegetated by several shrub species. Soil samples were collected at a 30 m resolution to characterize soil texture and bulk density, and several datasets consisting of more than 300 point measurements of soil moisture were collected using time domain reflectometry (TDR) between Fall 2007 and Summer 2008 at a 15 m resolution. Results from soil textural analysis performed with sieving and the ASTM standard hydrometer method show that soil texture is finer on the north-facing hillslope than on the south-facing hillslope. Cos(aspect) is the best univariate predictor of silts, while slope is the best predictor of coarser fractions up to fine gravel. Bulk density increases with depth but shows no significant relationship with topographic indices. When the catchment average soil moisture is low, the variance of soil moisture increases with the average. When the average is high, the variance remains relatively constant. Little of the variation in soil moisture is explained by topographic indices when the catchment is either very wet or dry; however, when the average soil moisture takes on intermediate values, cos(aspect) is consistently the best predictor among the terrain indices considered.

Improving Water Level and Soil Moisture Over Peatlands in a Global Land Modeling System

NASA Technical Reports Server (NTRS)

Bechtold, M.; De Lannoy, G. J. M.; Roose, D.; Reichle, R. H.; Koster, R. D.; Mahanama, S. P.

2017-01-01

New model structure for peatlands results in improved skill metrics (without any parameter calibration) Simulated surface soil moisture strongly affected by new model, but reliable soil moisture data lacking for validation.

Impact of Plant Functional Types on Coherence Between Precipitation and Soil Moisture: A Wavelet Analysis

NASA Astrophysics Data System (ADS)

Liu, Qi; Hao, Yonghong; Stebler, Elaine; Tanaka, Nobuaki; Zou, Chris B.

2017-12-01

Mapping the spatiotemporal patterns of soil moisture within heterogeneous landscapes is important for resource management and for the understanding of hydrological processes. A critical challenge in this mapping is comparing remotely sensed or in situ observations from areas with different vegetation cover but subject to the same precipitation regime. We address this challenge by wavelet analysis of multiyear observations of soil moisture profiles from adjacent areas with contrasting plant functional types (grassland, woodland, and encroached) and precipitation. The analysis reveals the differing soil moisture patterns and dynamics between plant functional types. The coherence at high-frequency periodicities between precipitation and soil moisture generally decreases with depth but this is much more pronounced under woodland compared to grassland. Wavelet analysis provides new insights on soil moisture dynamics across plant functional types and is useful for assessing differences and similarities in landscapes with heterogeneous vegetation cover.

Microwave remote sensing of soil moisture, volume 1. [Guymon, Oklahoma and Dalhart, Texas

NASA Technical Reports Server (NTRS)

Mcfarland, M. J. (Principal Investigator); Theis, S. W.; Rosenthal, W. D.; Jones, C. L.

1982-01-01

Multifrequency sensor data from NASA's C-130 aircraft were used to determine which of the all weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. The perpendicular vegetation index (PVI) as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture. A linear equation was developed to estimate percent field capacity as a function of L-band emissivity and the vegetation index. The prediction algorithm improves the estimation of moisture significantly over predictions from L-band emissivity alone.

A Data-Driven Approach for Daily Real-Time Estimates and Forecasts of Near-Surface Soil Moisture

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Reichle, Rolf H.; Mahanama, Sarith P. P.

2017-01-01

NASAs Soil Moisture Active Passive (SMAP) mission provides global surface soil moisture retrievals with a revisit time of 2-3 days and a latency of 24 hours. Here, to enhance the utility of the SMAP data, we present an approach for improving real-time soil moisture estimates (nowcasts) and for forecasting soil moisture several days into the future. The approach, which involves using an estimate of loss processes (evaporation and drainage) and precipitation to evolve the most recent SMAP retrieval forward in time, is evaluated against subsequent SMAP retrievals themselves. The nowcast accuracy over the continental United States (CONUS) is shown to be markedly higher than that achieved with the simple yet common persistence approach. The accuracy of soil moisture forecasts, which rely on precipitation forecasts rather than on precipitation measurements, is reduced relative to nowcast accuracy but is still significantly higher than that obtained through persistence.

Plan of research for integrated soil moisture studies. Recommendations of the Soil Moisture Working Group

NASA Technical Reports Server (NTRS)

1980-01-01

Soil moisture information is a potentially powerful tool for applications in agriculture, water resources, and climate. At present, it is difficult for users of this information to clearly define their needs in terms of accuracy, resolution and frequency because of the current sparsity of data. A plan is described for defining and conducting an integrated and coordinated research effort to develop and refine remote sensing techniques which will determine spatial and temporal variations of soil moisture and to utilize soil moisture information in support of agricultural, water resources, and climate applications. The soil moisture requirements of these three different application areas were reviewed in relation to each other so that one plan covering the three areas could be formulated. Four subgroups were established to write and compile the plan, namely models, ground-based studies, aircraft experiments, and spacecraft missions.

Historical climate controls soil respiration responses to current soil moisture

PubMed Central

Waring, Bonnie G.; Rocca, Jennifer D.; Kivlin, Stephanie N.

2017-01-01

Ecosystem carbon losses from soil microbial respiration are a key component of global carbon cycling, resulting in the transfer of 40–70 Pg carbon from soil to the atmosphere each year. Because these microbial processes can feed back to climate change, understanding respiration responses to environmental factors is necessary for improved projections. We focus on respiration responses to soil moisture, which remain unresolved in ecosystem models. A common assumption of large-scale models is that soil microorganisms respond to moisture in the same way, regardless of location or climate. Here, we show that soil respiration is constrained by historical climate. We find that historical rainfall controls both the moisture dependence and sensitivity of respiration. Moisture sensitivity, defined as the slope of respiration vs. moisture, increased fourfold across a 480-mm rainfall gradient, resulting in twofold greater carbon loss on average in historically wetter soils compared with historically drier soils. The respiration–moisture relationship was resistant to environmental change in field common gardens and field rainfall manipulations, supporting a persistent effect of historical climate on microbial respiration. Based on these results, predicting future carbon cycling with climate change will require an understanding of the spatial variation and temporal lags in microbial responses created by historical rainfall. PMID:28559315

Advanced Soil Moisture Network Technologies; Developments in Collecting in situ Measurements for Remote Sensing Missions

NASA Astrophysics Data System (ADS)

Moghaddam, M.; Silva, A. R. D.; Akbar, R.; Clewley, D.

2015-12-01

The Soil moisture Sensing Controller And oPtimal Estimator (SoilSCAPE) wireless sensor network has been developed to support Calibration and Validation activities (Cal/Val) for large scale soil moisture remote sensing missions (SMAP and AirMOSS). The technology developed here also readily supports small scale hydrological studies by providing sub-kilometer widespread soil moisture observations. An extensive collection of semi-sparse sensor clusters deployed throughout north-central California and southern Arizona provide near real time soil moisture measurements. Such a wireless network architecture, compared to conventional single points measurement profiles, allows for significant and expanded soil moisture sampling. The work presented here aims at discussing and highlighting novel and new technology developments which increase in situ soil moisture measurements' accuracy, reliability, and robustness with reduced data delivery latency. High efficiency and low maintenance custom hardware have been developed and in-field performance has been demonstrated for a period of three years. The SoilSCAPE technology incorporates (a) intelligent sensing to prevent erroneous measurement reporting, (b) on-board short term memory for data redundancy, (c) adaptive scheduling and sampling capabilities to enhance energy efficiency. A rapid streamlined data delivery architecture openly provides distribution of in situ measurements to SMAP and AirMOSS cal/val activities and other interested parties.

Effects of land preparation and artificial vegetation on soil moisture variation in a loess hilly catchment of China

NASA Astrophysics Data System (ADS)

Feng, Tianjiao; Wei, Wei; Chen, Liding; Yu, Yang

2017-04-01

In the dryland regions, soil moisture is the main factor to determine vegetation growth and ecosystem restoration. Land preparation and vegetation restoration are the principal means for improving soil water content(SWC). Thus, it is important to analyze the coupling role of these two means on soil moisture. In this study, soil moisture were monitored at a semi-arid loess hilly catchment of China, during the growing season of 2014 and 2015. Four different land preparation methods (level ditches, fish-scale pits, adverse grade tablelands and level benches)and vegetation types(Prunus armeniaca, Platycladus orientalis, Platycladus orientalis and Caragana microphylla) were included in the experimental design. Our results showed that: (1)Soil moisture content differed across land preparation types, which is higher for fish-scale pits and decreased in the order of level ditches and adverse grade tablelands.(2) Rainwater harvesting capacity of fish-scale pits is greater than adverse grade tablelands. However the water holding capacity is much higher at soils prepared with the adverse grade tablelands method than the ones prepared by fish-scale pits methods. (3) When land preparation method is similar, vegetation play a key role in soil moisture variation. For example, the mean soil moisture under a Platycladus orientalis field is 26.72% higher than a Pinus tabulaeformis field, with the same land preparation methods. (4)Soil moisture in deeper soil layers is more affected by changes in the vegetation cover while soil moisture in the shallower layers is more affected by the variation in the land preparation methods. Therefore, we suggest that vegetation types such as: Platycladus orientalisor as well as soil preparation methods such as level ditch and fish-scale pit are the most appropriate vegetation cover and land preparation methods for landscape restoration in semi-arid loess hilly area. This conclusion was made based on the vegetation type and land preparation with the best water-holding capacity.

Low moisture availability inhibits the enhancing effect of increased soil temperature on net photosynthesis of white birch (Betula papyrifera) seedlings grown under ambient and elevated carbon dioxide concentrations.

PubMed

Ambebe, Titus F; Dang, Qing-Lai

2009-11-01

White birch (Betula papyrifera Marsh.) seedlings were grown under two carbon dioxide concentrations (ambient: 360 micromol mol(-1) and elevated: 720 micromol mol(-1)), three soil temperatures (5, 15 and 25 degrees C initially, increased to 7, 17 and 27 degrees C, respectively, 1 month later) and three moisture regimes (low: 30-40%; intermediate: 45-55% and high: 60-70% field water capacity) in greenhouses. In situ gas exchange and chlorophyll fluorescence were measured after 2 months of treatments. Net photosynthetic rate (A(n)) of seedlings grown under the intermediate and high moisture regimes increased from low to intermediate T(soil) and then decreased to high T(soil). There were no significant differences between the low and high T(soil), with the exception that A(n) was significantly higher under high than low T(soil) at the high moisture regime. No significant T(soil) effect on A(n) was observed at the low moisture regime. The intermediate T(soil) increased stomatal conductance (g(s)) only at intermediate and high but not at low moisture regime, whereas there were no significant differences between the low and high T(soil) treatments. Furthermore, the difference in g(s) between the intermediate and high T(soil) at high moisture regime was not statistically significant. The low moisture regime significantly reduced the internal to ambient CO2 concentration ratio at all T(soil). There were no significant individual or interactive effects of treatment on maximum carboxylation rate of Rubisco, light-saturated electron transport rate, triose phosphate utilization or potential photochemical efficiency of photosystem II. The results of this study suggest that soil moisture condition should be taken into account when predicting the responses of white birch to soil warming.

Optimizing available water capacity using microwave satellite data for improving irrigation management

NASA Astrophysics Data System (ADS)

Gupta, Manika; Bolten, John; Lakshmi, Venkat

2015-04-01

This work addresses the improvement of available water capacity by developing a technique for estimating soil hydraulic parameters through the utilization of satellite-retrieved near surface soil moisture. The prototype involves the usage of Monte Carlo analysis to assimilate historical remote sensing soil moisture data available from the Advanced Microwave Scanning Radiometer (AMSR-E) within the hydrological model. The main hypothesis used in this study is that near-surface soil moisture data contain useful information that can describe the effective hydrological conditions of the basin such that when appropriately In the method followed in this study the hydraulic parameters are derived directly from information on the soil moisture state at the AMSR-E footprint scale and the available water capacity is derived for the root zone by coupling of AMSR-E soil moisture with the physically-based hydrological model. The available capacity water, which refers to difference between the field capacity and wilting point of the soil and represent the soil moisture content at 0.33 bar and 15 bar respectively is estimated from the soil hydraulic parameters using the van Genuchten equation. The initial ranges of soil hydraulic parameters are taken in correspondence with the values available from the literature based on Soil Survey Geographic (SSURGO) database within the particular AMSR-E footprint. Using the Monte Carlo simulation, the ranges are narrowed in the region where simulation shows a good match between predicted and near-surface soil moisture from AMSR-E. In this study, the uncertainties in accurately determining the parameters of the nonlinear soil water retention function for large-scale hydrological modeling is the focus of the development of the Bayesian framework. Thus, the model forecasting has been combined with the observational information to optimize the model state and the soil hydraulic parameters simultaneously. The optimization process is divided into two steps during one time interval: the state variable is optimized through the state filter and the optimal parameter values are then transferred for retrieving soil moisture. However, soil moisture from sensors such as AMSR-E can only be retrieved for the top few centimeters of soil. So, for the present study, a homogeneous soil system has been considered. By assimilating this information into the model, the accuracy of model structure in relating surface moisture dynamics to deeper soil profiles can be ascertained. To evaluate the performance of the system in helping improve simulation accuracy and whether they can be used to obtain soil moisture profiles at poorly gauged catchments alongwith the available water capacity, the root mean square error (RMSE) and Mean Bias error (MBE) are used to measure the performance of the soil moisture simulations. The optimized parameters as compared to the pedo-transfer based parameters were found to reduce the RMSE from 0.14 to 0.04 and 0.15 to 0.07 in surface layer and root zone respectively.

Stochastic soil water balance under seasonal climates

PubMed Central

Feng, Xue; Porporato, Amilcare; Rodriguez-Iturbe, Ignacio

2015-01-01

The analysis of soil water partitioning in seasonally dry climates necessarily requires careful consideration of the periodic climatic forcing at the intra-annual timescale in addition to daily scale variabilities. Here, we introduce three new extensions to a stochastic soil moisture model which yields seasonal evolution of soil moisture and relevant hydrological fluxes. These approximations allow seasonal climatic forcings (e.g. rainfall and potential evapotranspiration) to be fully resolved, extending the analysis of soil water partitioning to account explicitly for the seasonal amplitude and the phase difference between the climatic forcings. The results provide accurate descriptions of probabilistic soil moisture dynamics under seasonal climates without requiring extensive numerical simulations. We also find that the transfer of soil moisture between the wet to the dry season is responsible for hysteresis in the hydrological response, showing asymmetrical trajectories in the mean soil moisture and in the transient Budyko's curves during the ‘dry-down‘ versus the ‘rewetting‘ phases of the year. Furthermore, in some dry climates where rainfall and potential evapotranspiration are in-phase, annual evapotranspiration can be shown to increase because of inter-seasonal soil moisture transfer, highlighting the importance of soil water storage in the seasonal context. PMID:25663808

Fate of 14C-labeled dissolved organic matter in paddy and upland soils in responding to moisture.

PubMed

Chen, Xiangbi; Wang, Aihua; Li, Yang; Hu, Lening; Zheng, Hua; He, Xunyang; Ge, Tida; Wu, Jinshui; Kuzyakov, Yakov; Su, Yirong

2014-08-01

Soil organic matter (SOM) content in paddy soils is higher than that in upland soils in tropical and subtropical China. The dissolved organic matter (DOM) concentration, however, is lower in paddy soils. We hypothesize that soil moisture strongly controls the fate of DOM, and thereby leads to differences between the two agricultural soils under contrasting management regimens. A 100-day incubation experiment was conducted to trace the fate and biodegradability of DOM in paddy and upland soils under three moisture levels: 45%, 75%, and 105% of the water holding capacity (WHC). (14)C labeled DOM, extracted from the (14)C labeled rice plant material, was incubated in paddy and upland soils, and the mineralization to (14)CO2 and incorporation into microbial biomass were analyzed. Labile and refractory components of the initial (14)C labeled DOM and their respective half-lives were calculated by a double exponential model. During incubation, the mineralization of the initial (14)C labeled DOM in the paddy soils was more affected by moisture than in the upland soils. The amount of (14)C incorporated into the microbial biomass (2.4-11.0% of the initial DOM-(14)C activity) was less affected by moisture in the paddy soils than in the upland soils. At any of the moisture levels, 1) the mineralization of DOM to (14)CO2 within 100 days was 1.2-2.1-fold higher in the paddy soils (41.9-60.0% of the initial DOM-(14)C activity) than in the upland soils (28.7-35.7%), 2) (14)C activity remaining in solution was significantly lower in the paddy soils than in the upland soils, and 3) (14)C activity remaining in the same agricultural soil solution was not significantly different among the three moisture levels after 20 days. Therefore, moisture strongly controls DOM fate, but moisture was not the key factor in determining the lower DOM in the paddy soils than in the upland soils. The UV absorbance of DOM at 280 nm indicates less aromaticity of DOM from the paddy soils than from the upland soils. At any of the moisture levels, much more labile DOM was found in paddy soils (34.3-49.2% of the initial (14)C labeled DOM) compared with that in upland soils (19.4-23.9%). This demonstrates that the lower DOM content in the paddy soil compared with that in the upland soil is probably determined by the less complex components and structure of the DOM. Copyright © 2014 Elsevier B.V. All rights reserved.

Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2013-08-01

Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.

Is soil moisture initialization important for seasonal to decadal predictions?

NASA Astrophysics Data System (ADS)

Stacke, Tobias; Hagemann, Stefan

2014-05-01

The state of soil moisture can can have a significant impact on regional climate conditions for short time scales up to several months. However, focusing on seasonal to decadal time scales, it is not clear whether the predictive skill of global a Earth System Model might be enhanced by assimilating soil moisture data or improving the initial soil moisture conditions with respect to observations. As a first attempt to provide answers to this question, we set up an experiment to investigate the life time (memory) of extreme soil moisture states in the coupled land-atmosphere model ECHAM6-JSBACH, which is part of the Max Planck Institute for Meteorology's Earth System Model (MPI-ESM). This experiment consists of an ensemble of 3 years simulations which are initialized with extreme wet and dry soil moisture states for different seasons and years. Instead of using common thresholds like wilting point or critical soil moisture, the extreme states were extracted from a reference simulation to ensure that they are within the range of simulated climate variability. As a prerequisite for this experiment, the soil hydrology in JSBACH was improved by replacing the bucket-type soil hydrology scheme with a multi-layer scheme. This new scheme is a more realistic representation of the soil, including percolation and diffusion fluxes between up to five separate layers, the limitation of bare soil evaporation to the uppermost soil layer and the addition of a long term water storage below the root zone in regions with deep soil. While the hydrological cycle is not strongly affected by this new scheme, it has some impact on the simulated soil moisture memory which is mostly strengthened due to the additional deep layer water storage. Ensemble statistics of the initialization experiment indicate perturbation lengths between just a few days up to several seasons for some regions. In general, the strongest effects are seen for wet initialization during northern winter over cold and humid regions, while the shortest memory is found during northern spring. For most regions, the soil moisture memory is either sensitive to wet or to dry perturbations, indicating that soil moisture anomalies interact with the respective weather pattern for a given year and might be able to enhance or dampen extreme conditions. To further investigate this effect, the simulations will be repeated using JSBACH with prescribed meteorological forcing to better disentangle the direct effects of soil moisture initialization and the atmospheric response.

[Relationships between soil moisture and needle-fall in Masson pine forests in acid rain region of Chongqing, Southwest China].

PubMed

Wang, Yi-Hao; Wang, Yan-Hui; Li, Zhen-Hua; Yu, Peng-Tao; Xiong, Wei; Hao, Jia; Duan, Jian

2012-10-01

From March 2009 to November 2011, an investigation was conducted on the spatiotemporal variation of soil moisture and its effects on the needle-fall in Masson pine (Pinus massoniana) forests in acid rain region of Chongqing, Southeast China, with the corresponding soil moisture thresholds determined. No matter the annual precipitation was abundant, normal or less than average, the seasonal variation of soil moisture in the forests could be obviously divided into four periods, i.e., sufficient (before May), descending (from June to July), drought (from August to September), and recovering (from October to November). With increasing soil depth, the soil moisture content increased after an initial decrease, but the difference of the soil moisture content among different soil layers decreased with decreasing annual precipitation. The amount of monthly needle-fall in the forests in growth season was significantly correlated with the water storage in root zone (0-60 cm soil layer), especially in the main root zone (20-50 cm soil layer). Soil field capacity (or capillary porosity) and 82% of field capacity (or 80% of capillary porosity) were the main soil moisture thresholds affecting the litter-fall. It was suggested that in acid rain region, Masson pine forest was easily to suffer from water deficit stress, especially in dry-summer period. The water deficit stress, together with already existed acid rain stress, would further threaten the health of the Masson forest.

Quantifying the influence of deep soil moisture on ecosystem albedo: the role of vegetation Zulia M. Sánchez-Mejía 1 and Shirley A. Papuga1 1School of Natural Resources and the Environment, University of Arizona, Tucson, AZ

NASA Astrophysics Data System (ADS)

Sanchez-Mejia, Z. M.; Papuga, S. A.

2012-12-01

Water limited ecosystems in arid and semiarid regions are characterized by sparse vegetation and a relatively large fraction of bare soil. Importantly, the land surface in these dryland regions is highly sensitive to pulses of moisture that affect the vegetation canopy in density and color, as well as the soil color. Changes in surface conditions due to these pulses have been shown to affect the surface energy fluxes and atmospheric processes in these regions. For instance, previous studies have shown that shallow soil moisture ( < 20 cm below the surface) significantly changes surface albedo (a= SWup/ SWin). Recent studies have highlighted the importance of deep soil moisture ( > 20 cm below the surface) for vegetation dynamics in these regions. We hypothesize that deep soil moisture will change vegetation canopy density and color enough that changes in albedo will be observable at the surface, therefore linking deep soil moisture and albedo. We adopt a conceptual framework to address this hypothesis, where at any point in time the soil profile falls into one of four cases: (1) dry shallow soil and dry deep soil; (2) wet shallow soil and dry deep soil; (3) wet shallow soil and wet deep soil; and (4) dry shallow soil and wet deep soil. At a creosotebush dominated ecosystem of the Santa Rita Experimental Range, southern Arizona during summers of 2011 and 2012, we took albedo measurements during these cases at multiple bare and vegetated patches within the footprint of an eddy covariance tower. We found that when the soil is completely dry (Case 1) albedo is highest in both bare and vegetated patches. Likewise, when the soil is wet in both the shallow and deep regions (Case 3), albedo is lowest in both bare and vegetated patches. Interestingly, we also found that albedo is significantly lower for vegetated patches when the deep soil is wet and shallow soil is dry (Case 4). These results imply that deep soil moisture can be important in altering ecosystem level albedo. We note that ecosystems with higher percent vegetative cover are likely to be more sensitive to deep soil moisture driven changes in albedo. To quantify the influence of percent cover on ecosystem albedo, we populate a 100 x 100 cell grid randomly with bare and vegetated cells. For each case, we assign an albedo value to each cell based on probability distribution functions (PDFs) of soil moisture and albedo created from our field campaign data. Using this technique we can identify for each soil moisture case at which point the percent vegetative cover will significantly influence ecosystem albedo. Quantitative analyses of these ecosystem interactions help identify the unique role of deep soil moisture in land surface - atmosphere interactions.

A procedure for calculating daily moisture stress and its utility in regressions of growth and weather

Treesearch

Robert Zahner; Albert R. Stage

1966-01-01

A method is described for computing daily values of moisture stress on forest vegetation, or water deficits, based on the differences between Thornthwaite's potential evapotranspiration and computed soil-moisture depletion. More realistic functions are used for soil-moisture depletion on specific soil types than have been customary. These functions relate daily...

High-resolution Mapping of Permafrost and Soil Freeze/thaw Dynamics in the Tibetan Plateau Based on Multi-sensor Satellite Observations

NASA Astrophysics Data System (ADS)

Zhang, W.; Yi, Y.; Yang, K.; Kimball, J. S.

2016-12-01

The Tibetan Plateau (TP) is underlain by the world's largest extent of alpine permafrost ( 2.5×106 km2), dominated by sporadic and discontinuous permafrost with strong sensitivity to climate warming. Detailed permafrost distributions and patterns in most of the TP region are still unknown due to extremely sparse in-situ observations in this region characterized by heterogeneous land cover and large temporal dynamics in surface soil moisture conditions. Therefore, satellite-based temperature and moisture observations are essential for high-resolution mapping of permafrost distribution and soil active layer changes in the TP region. In this study, we quantify the TP regional permafrost distribution at 1-km resolution using a detailed satellite data-driven soil thermal process model (GIPL2). The soil thermal model is calibrated and validated using in-situ soil temperature/moisture observations from the CAMP/Tibet field campaign (9 sites: 0-300 cm soil depth sampling from 1997-2007), a multi-scale soil moisture and temperature monitoring network in the central TP (CTP-SMTMN, 57 sites: 5-40 cm, 2010-2014) and across the whole plateau (China Meteorology Administration, 98 sites: 0-320 cm, 2000-2015). Our preliminary results using the CAMP/Tibet and CTP-SMTMN network observations indicate strong controls of surface thermal and soil moisture conditions on soil freeze/thaw dynamics, which vary greatly with underlying topography, soil texture and vegetation cover. For regional mapping of soil freeze/thaw and permafrost dynamics, we use the most recent soil moisture retrievals from the NASA SMAP (Soil Moisture Active Passive) sensor to account for the effects of temporal soil moisture dynamics on soil thermal heat transfer, with surface thermal conditions defined by MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature records. Our study provides the first 1-km map of spatial patterns and recent changes of permafrost conditions in the TP.

Field-Scale Soil Moisture Observations in Irrigated Agriculture Fields Using the Cosmic-ray Neutron Rover

NASA Astrophysics Data System (ADS)

Franz, T. E.; Avery, W. A.; Finkenbiner, C. E.; Wang, T.; Brocca, L.

2014-12-01

Approximately 40% of global food production comes from irrigated agriculture. With the increasing demand for food even greater pressures will be placed on water resources within these systems. In this work we aimed to characterize the spatial and temporal patterns of soil moisture at the field-scale (~500 m) using the newly developed cosmic-ray neutron rover near Waco, NE. Here we mapped soil moisture of 144 quarter section fields (a mix of maize, soybean, and natural areas) each week during the 2014 growing season (May to September). The 11 x11 km study domain also contained 3 stationary cosmic-ray neutron probes for independent validation of the rover surveys. Basic statistical analysis of the domain indicated a strong inverted parabolic relationship between the mean and variance of soil moisture. The relationship between the mean and higher order moments were not as strong. Geostatistical analysis indicated the range of the soil moisture semi-variogram was significantly shorter during periods of heavy irrigation as compared to non-irrigated periods. Scaling analysis indicated strong power law behavior between the variance of soil moisture and averaging area with minimal dependence of mean soil moisture on the slope of the power law function. Statistical relationships derived from the rover dataset offer a novel set of observations that will be useful in: 1) calibrating and validating land surface models, 2) calibrating and validating crop models, 3) soil moisture covariance estimates for statistical downscaling of remote sensing products such as SMOS and SMAP, and 4) provide center-pivot scale mean soil moisture data for optimal irrigation timing and volume amounts.

Using SMAP to identify structural errors in hydrologic models

NASA Astrophysics Data System (ADS)

Crow, W. T.; Reichle, R. H.; Chen, F.; Xia, Y.; Liu, Q.

2017-12-01

Despite decades of effort, and the development of progressively more complex models, there continues to be underlying uncertainty regarding the representation of basic water and energy balance processes in land surface models. Soil moisture occupies a central conceptual position between atmosphere forcing of the land surface and resulting surface water fluxes. As such, direct observations of soil moisture are potentially of great value for identifying and correcting fundamental structural problems affecting these models. However, to date, this potential has not yet been realized using satellite-based retrieval products. Using soil moisture data sets produced by the NASA Soil Moisture Active/Passive mission, this presentation will explore the use of the remotely-sensed soil moisture data products as a constraint to reject certain types of surface runoff parameterizations within a land surface model. Results will demonstrate that the precision of the SMAP Level 4 Surface and Root-Zone soil moisture product allows for the robust sampling of correlation statistics describing the true strength of the relationship between pre-storm soil moisture and subsequent storm-scale runoff efficiency (i.e., total storm flow divided by total rainfall both in units of depth). For a set of 16 basins located in the South-Central United States, we will use these sampled correlations to demonstrate that so-called "infiltration-excess" runoff parameterizations under predict the importance of pre-storm soil moisture for determining storm-scale runoff efficiency. To conclude, we will discuss prospects for leveraging this insight to improve short-term hydrologic forecasting and additional avenues for SMAP soil moisture products to provide process-level insight for hydrologic modelers.

A Time Series Analysis of Global Soil Moisture Data Products for Water Cycle Studies

NASA Astrophysics Data System (ADS)

Zhan, X.; Yin, J.; Liu, J.; Fang, L.; Hain, C.; Ferraro, R. R.; Weng, F.

2017-12-01

Water is essential for sustaining life on our planet Earth and water cycle is one of the most important processes of out weather and climate system. As one of the major components of the water cycle, soil moisture impacts significantly the other water cycle components (e.g. evapotranspiration, runoff, etc) and the carbon cycle (e.g. plant/crop photosynthesis and respiration). Understanding of soil moisture status and dynamics is crucial for monitoring and predicting the weather, climate, hydrology and ecological processes. Satellite remote sensing has been used for soil moisture observation since the launch of the Scanning Multi-channel Microwave Radiometer (SMMR) on NASA's Nimbus-7 satellite in 1978. Many satellite soil moisture data products have been made available to the science communities and general public. The soil moisture operational product system (SMOPS) of NOAA NESDIS has been operationally providing global soil moisture data products from each of the currently available microwave satellite sensors and their blends. This presentation will provide an update of SMOPS products. The time series of each of these soil moisture data products are analyzed against other data products, such as precipitation and evapotranspiration from other independent data sources such as the North America Land Data Assimilation System (NLDAS). Temporal characteristics of these water cycle components are explored against some historical events, such as the 2010 Russian, 2010 China and 2012 United States droughts, 2015 South Carolina floods, etc. Finally whether a merged global soil moisture data product can be used as a climate data record is evaluated based on the above analyses.

Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture

USGS Publications Warehouse

McNally, Amy; Gregory J. Husak,; Molly Brown,; Carroll, Mark L.; Funk, Christopher C.; Soni Yatheendradas,; Kristi Arsenault,; Christa Peters-Lidard,; Verdin, James

2015-01-01

The Soil Moisture Active Passive (SMAP) mission will provide soil moisture data with unprecedented accuracy, resolution, and coverage, enabling models to better track agricultural drought and estimate yields. In turn, this information can be used to shape policy related to food and water from commodity markets to humanitarian relief efforts. New data alone, however, do not translate to improvements in drought and yield forecasts. New tools will be needed to transform SMAP data into agriculturally meaningful products. The objective of this study is to evaluate the possibility and efficiency of replacing the rainfall-derived soil moisture component of a crop water stress index with SMAP data. The approach is demonstrated with 0.1°-resolution, ~10-day microwave soil moisture from the European Space Agency and simulated soil moisture from the Famine Early Warning Systems Network Land Data Assimilation System. Over a West Africa domain, the approach is evaluated by comparing the different soil moisture estimates and their resulting Water Requirement Satisfaction Index values from 2000 to 2010. This study highlights how the ensemble of indices performs during wet versus dry years, over different land-cover types, and the correlation with national-level millet yields. The new approach is a feasible and useful way to quantitatively assess how satellite-derived rainfall and soil moisture track agricultural water deficits. Given the importance of soil moisture in many applications, ranging from agriculture to public health to fire, this study should inspire other modeling communities to reformulate existing tools to take advantage of SMAP data.

Neural Network-Based Retrieval of Surface and Root Zone Soil Moisture using Multi-Frequency Remotely-Sensed Observations

NASA Astrophysics Data System (ADS)

Hamed Alemohammad, Seyed; Kolassa, Jana; Prigent, Catherine; Aires, Filipe; Gentine, Pierre

2017-04-01

Knowledge of root zone soil moisture is essential in studying plant's response to different stress conditions since plant photosynthetic activity and transpiration rate are constrained by the water available through their roots. Current global root zone soil moisture estimates are based on either outputs from physical models constrained by observations, or assimilation of remotely-sensed microwave-based surface soil moisture estimates with physical model outputs. However, quality of these estimates are limited by the accuracy of the model representations of physical processes (such as radiative transfer, infiltration, percolation, and evapotranspiration) as well as errors in the estimates of the surface parameters. Additionally, statistical approaches provide an alternative efficient platform to develop root zone soil moisture retrieval algorithms from remotely-sensed observations. In this study, we present a new neural network based retrieval algorithm to estimate surface and root zone soil moisture from passive microwave observations of SMAP satellite (L-band) and AMSR2 instrument (X-band). SMAP early morning observations are ideal for surface soil moisture retrieval. AMSR2 mid-night observations are used here as an indicator of plant hydraulic properties that are related to root zone soil moisture. The combined observations from SMAP and AMSR2 together with other ancillary observations including the Solar-Induced Fluorescence (SIF) estimates from GOME-2 instrument provide necessary information to estimate surface and root zone soil moisture. The algorithm is applied to observations from the first 18 months of SMAP mission and retrievals are validated against in-situ observations and other global datasets.

Dust emission parameterization scheme over the MENA region: Sensitivity analysis to soil moisture and soil texture

NASA Astrophysics Data System (ADS)

Gherboudj, Imen; Beegum, S. Naseema; Marticorena, Beatrice; Ghedira, Hosni

2015-10-01

The mineral dust emissions from arid/semiarid soils were simulated over the MENA (Middle East and North Africa) region using the dust parameterization scheme proposed by Alfaro and Gomes (2001), to quantify the effect of the soil moisture and clay fraction in the emissions. For this purpose, an extensive data set of Soil Moisture and Ocean Salinity soil moisture, European Centre for Medium-Range Weather Forecasting wind speed at 10 m height, Food Agricultural Organization soil texture maps, MODIS (Moderate Resolution Imaging Spectroradiometer) Normalized Difference Vegetation Index, and erodibility of the soil surface were collected for the a period of 3 years, from 2010 to 2013. Though the considered data sets have different temporal and spatial resolution, efforts have been made to make them consistent in time and space. At first, the simulated sandblasting flux over the region were validated qualitatively using MODIS Deep Blue aerosol optical depth and EUMETSAT MSG (Meteosat Seciond Generation) dust product from SEVIRI (Meteosat Spinning Enhanced Visible and Infrared Imager) and quantitatively based on the available ground-based measurements of near-surface particulate mass concentrations (PM10) collected over four stations in the MENA region. Sensitivity analyses were performed to investigate the effect of soil moisture and clay fraction on the emissions flux. The results showed that soil moisture and soil texture have significant roles in the dust emissions over the MENA region, particularly over the Arabian Peninsula. An inversely proportional dependency is observed between the soil moisture and the sandblasting flux, where a steep reduction in flux is observed at low friction velocity and a gradual reduction is observed at high friction velocity. Conversely, a directly proportional dependency is observed between the soil clay fraction and the sandblasting flux where a steep increase in flux is observed at low friction velocity and a gradual increase is observed at high friction velocity. The magnitude of the percentage reduction/increase in the sandblasting flux decreases with the increase of the friction velocity for both soil moisture and soil clay fraction. Furthermore, these variables are interdependent leading to a gradual decrease in the percentage increase in the sandblasting flux for higher soil moisture values.

Improvment of the Trapezoid Method Using Raw Landsat Image Digital Count Data for Soil Moisture Estimation in the Texas (usa) High Plains

NASA Astrophysics Data System (ADS)

Shafian, S.; Maas, S. J.

2015-12-01

Variations in soil moisture strongly affect surface energy balances, regional runoff, land erosion and vegetation productivity (i.e., potential crop yield). Hence, the estimation of soil moisture is very valuable in the social, economic, humanitarian (food security) and environmental segments of society. Extensive efforts to exploit the potential of remotely sensed observations to help quantify this complex variable are ongoing. This study aims at developing a new index, the Thermal Ground cover Moisture Index (TGMI), for estimating soil moisture content. This index is based on empirical parameterization of the relationship between raw image digital count (DC) data in the thermal infrared spectral band and ground cover (determined from raw image digital count data in the red and near-infrared spectral bands).The index uses satellite-derived information only, and the potential for its operational application is therefore great. This study was conducted in 18 commercial agricultural fields near Lubbock, TX (USA). Soil moisture was measured in these fields over two years and statistically compared to corresponding values of TGMI determined from Landsat image data. Results indicate statistically significant correlations between TGMI and field measurements of soil moisture (R2 = 0.73, RMSE = 0.05, MBE = 0.17 and AAE = 0.049), suggesting that soil moisture can be estimated using this index. It was further demonstrated that maps of TGMI developed from Landsat imagery could be constructed to show the relative spatial distribution of soil moisture across a region.

NASAs Soil Moisture Active Passive (SMAP) Mission and Opportunities For Applications Users

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Escobar, Vanessa; Moran, Susan; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni G.; Doorn, Brad; Entin, Jared K.

2013-01-01

Water in the soil, both its amount (soil moisture) and its state (freeze/thaw), plays a key role in water and energy cycles, in weather and climate, and in the carbon cycle. Additionally, soil moisture touches upon human lives in a number of ways from the ravages of flooding to the needs for monitoring agricultural and hydrologic droughts. Because of their relevance to weather, climate, science, and society, accurate and timely measurements of soil moisture and freeze/thaw state with global coverage are critically important.

SMOS+RAINFALL: Evaluating the ability of different methodologies to improve rainfall estimations using soil moisture data from SMOS

NASA Astrophysics Data System (ADS)

Pellarin, Thierry; Brocca, Luca; Crow, Wade; Kerr, Yann; Massari, Christian; Román-Cascón, Carlos; Fernández, Diego

2017-04-01

Recent studies have demonstrated the usefulness of soil moisture retrieved from satellite for improving rainfall estimations of satellite based precipitation products (SBPP). The real-time version of these products are known to be biased from the real precipitation observed at the ground. Therefore, the information contained in soil moisture can be used to correct the inaccuracy and uncertainty of these products, since the value and behavior of this soil variable preserve the information of a rain event even for several days. In this work, we take advantage of the soil moisture data from the Soil Moisture and Ocean Salinity (SMOS) satellite, which provides information with a quite appropriate temporal and spatial resolution for correcting rainfall events. Specifically, we test and compare the ability of three different methodologies for this aim: 1) SM2RAIN, which directly relate changes in soil moisture to rainfall quantities; 2) The LMAA methodology, which is based on the assimilation of soil moisture in two models of different complexity (see EGU2017-5324 in this same session); 3) The SMART method, based on the assimilation of soil moisture in a simple hydrological model with a different assimilation/modelling technique. The results are tested for 6 years over 10 sites around the world with different features (land surface, rainfall climatology, orography complexity, etc.). These preliminary and promising results are shown here for the first time to the scientific community, as also the observed limitations of the different methodologies. Specific remarks on the technical configurations, filtering/smoothing of SMOS soil moisture or re-scaling techniques are also provided from the results of different sensitivity experiments.

Assessment of SMOS Soil Moisture Retrieval Parameters Using Tau-Omega Algorithms for Soil Moisture Deficit Estimation

NASA Technical Reports Server (NTRS)

Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika

2014-01-01

Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.

Downscaling essential climate variable soil moisture using multisource data from 2003 to 2010 in China

NASA Astrophysics Data System (ADS)

Wang, Hui-Lin; An, Ru; You, Jia-jun; Wang, Ying; Chen, Yuehong; Shen, Xiao-ji; Gao, Wei; Wang, Yi-nan; Zhang, Yu; Wang, Zhe; Quaye-Ballard, Jonathan Arthur

2017-10-01

Soil moisture plays an important role in the water cycle within the surface ecosystem, and it is the basic condition for the growth of plants. Currently, the spatial resolutions of most soil moisture data from remote sensing range from ten to several tens of km, while those observed in-situ and simulated for watershed hydrology, ecology, agriculture, weather, and drought research are generally <1 km. Therefore, the existing coarse-resolution remotely sensed soil moisture data need to be downscaled. This paper proposes a universal and multitemporal soil moisture downscaling method suitable for large areas. The datasets comprise land surface, brightness temperature, precipitation, and soil and topographic parameters from high-resolution data and active/passive microwave remotely sensed essential climate variable soil moisture (ECV_SM) data with a spatial resolution of 25 km. Using this method, a total of 288 soil moisture maps of 1-km resolution from the first 10-day period of January 2003 to the last 10-day period of December 2010 were derived. The in-situ observations were used to validate the downscaled ECV_SM. In general, the downscaled soil moisture values for different land cover and land use types are consistent with the in-situ observations. Mean square root error is reduced from 0.070 to 0.061 using 1970 in-situ time series observation data from 28 sites distributed over different land uses and land cover types. The performance was also assessed using the GDOWN metric, a measure of the overall performance of the downscaling methods based on the same dataset. It was positive in 71.429% of cases, indicating that the suggested method in the paper generally improves the representation of soil moisture at 1-km resolution.

WaterSense Soil Moisture-Based Control Technologies Notice of Intent (NOI)

EPA Pesticide Factsheets

By directly measuring the amount of moisture in the soil, soil moisture-based control technologies tailor irrigation schedules to meet landscape water needs based on seasonal patterns, as well as prevailing conditions in the landscape.

Combined evaluation of optical and microwave satellite dataset for soil moisture deficit estimation

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Han, Dawei; Islam, Tanvir; Singh, Sudhir Kumar; Gupta, Manika; Gupta, Dileep Kumar; Kumar, Pradeep

2016-04-01

Soil moisture is a key variable responsible for water and energy exchanges from land surface to the atmosphere (Srivastava et al., 2014). On the other hand, Soil Moisture Deficit (or SMD) can help regulating the proper use of water at specified time to avoid any agricultural losses (Srivastava et al., 2013b) and could help in preventing natural disasters, e.g. flood and drought (Srivastava et al., 2013a). In this study, evaluation of Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and soil moisture from Soil Moisture and Ocean Salinity (SMOS) satellites are attempted for prediction of Soil Moisture Deficit (SMD). Sophisticated algorithm like Adaptive Neuro Fuzzy Inference System (ANFIS) is used for prediction of SMD using the MODIS and SMOS dataset. The benchmark SMD estimated from Probability Distributed Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the validation. The performances are assessed in terms of Nash Sutcliffe Efficiency, Root Mean Square Error and the percentage of bias between ANFIS simulated SMD and the benchmark. The performance statistics revealed a good agreement between benchmark and the ANFIS estimated SMD using the MODIS dataset. The assessment of the products with respect to this peculiar evidence is an important step for successful development of hydro-meteorological model and forecasting system. The analysis of the satellite products (viz. SMOS soil moisture and MODIS LST) towards SMD prediction is a crucial step for successful hydrological modelling, agriculture and water resource management, and can provide important assistance in policy and decision making. Keywords: Land Surface Temperature, MODIS, SMOS, Soil Moisture Deficit, Fuzzy Logic System References: Srivastava, P.K., Han, D., Ramirez, M.A., Islam, T., 2013a. Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology 498, 292-304. Srivastava, P.K., Han, D., Rico-Ramirez, M.A., Al-Shrafany, D., Islam, T., 2013b. Data fusion techniques for improving soil moisture deficit using SMOS satellite and WRF-NOAH land surface model. Water Resources Management 27, 5069-5087. Srivastava, P.K., Han, D., Rico-Ramirez, M.A., O'Neill, P., Islam, T., Gupta, M., 2014. Assessment of SMOS soil moisture retrieval parameters using tau-omega algorithms for soil moisture deficit estimation. Journal of Hydrology 519, 574-587.

An Arduino Based Citizen Science Soil Moisture Sensor in Support of SMAP and GLOBE

NASA Astrophysics Data System (ADS)

Podest, E.; Das, N. N.; Rajasekaran, E.; Jeyaram, R.; Lohrli, C.; Hovhannesian, H.; Fairbanks, G.

2017-12-01

Citizen science allows individuals anywhere in the world to engage in science by collecting environmental variables. One of the longest running platforms for the collection of in situ variables is the GLOBE program, which is international in scope and encourages students and citizen scientists alike to collect in situ measurements. NASA's Soil Moisture Active Passive (SMAP) satellite mission, which has been acquiring global soil moisture measurements every 3 days of the top 5 cm of the soil since 2015, has partnered with the GLOBE program to engage students from around the world to collect in situ soil moisture and help validate SMAP measurements. The current GLOBE SMAP soil moisture protocol consists in collecting a soil sample, weighing, drying and weighing it again in order to determine the amount of water in the soil. Preparation and soil sample collection can take up to 20 minutes and drying can take up to 3 days. We have hence developed a soil moisture measurement device based on Arduino- microcontrollers along with off-the-shelf and homemade sensors that are accurate, robust, inexpensive and quick and easy to use so that they can be implemented by the GLOBE community and citizen scientists alike. In addition, we have developed a phone app, which interfaces with the Arduino, displays the soil moisture value and send the measurement to the GLOBE database. This talk will discuss building, calibration and validation of the soil moisture measuring device and assessing the quality of the measurements collected. This work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

Downscaling SMAP Radiometer Soil Moisture over the CONUS using Soil-Climate Information and Ensemble Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, P.; Moradkhani, H.

2017-12-01

Soil moisture contributes significantly towards the improvement of weather and climate forecast and understanding terrestrial ecosystem processes. It is known as a key hydrologic variable in the agricultural drought monitoring, flood modeling and irrigation management. While satellite retrievals can provide an unprecedented information on soil moisture at global-scale, the products are generally at coarse spatial resolutions (25-50 km2). This often hampers their use in regional or local studies, which normally require a finer resolution of the data set. This work presents a new framework based on an ensemble learning method while using soil-climate information derived from remote-sensing and ground-based observations to downscale the level 3 daily composite version (L3_SM_P) of SMAP radiometer soil moisture over the Continental U.S. (CONUS) at 1 km spatial resolution. In the proposed method, a suite of remotely sensed and in situ data sets in addition to soil texture information and topography data among others were used. The downscaled product was validated against in situ soil moisture measurements collected from a limited number of core validation sites and several hundred sparse soil moisture networks throughout the CONUS. The obtained results indicated a great potential of the proposed methodology to derive the fine resolution soil moisture information applicable for fine resolution hydrologic modeling, data assimilation and other regional studies.

Inter-Annual Variability of Soil Moisture Stress Function in the Wheat Field

NASA Astrophysics Data System (ADS)

Akuraju, V. R.; Ryu, D.; George, B.; Ryu, Y.; Dassanayake, K. B.

2014-12-01

Root-zone soil moisture content is a key variable that controls the exchange of water and energy fluxes between land and atmosphere. In the soil-vegetation-atmosphere transfer (SVAT) schemes, the influence of root-zone soil moisture on evapotranspiration (ET) is parameterized by the soil moisture stress function (SSF). Dependence of actual ET: potential ET (fPET) or evaporative fraction to the root-zone soil moisture via SSF can also be used inversely to estimate root-zone soil moisture when fPET is estimated by remotely sensed land surface states. In this work we present fPET versus available soil water (ASW) in the root zone observed in the experimental farm sites in Victoria, Australia in 2012-2013. In the wheat field site, fPET vs ASW exhibited distinct features for different soil depth, net radiation, and crop growth stages. Interestingly, SSF in the wheat field presented contrasting shapes for two cropping years of 2012 and 2013. We argue that different temporal patterns of rainfall (and resulting soil moisture) during the growing seasons in 2012 and 2013 are responsible for the distinctive SSFs. SSF of the wheat field was simulated by the Agricultural Production Systems sIMulator (APSIM). The APSIM was able to reproduce the observed fPET vs. ASW. We discuss implications of our findings for existing modeling and (inverse) remote sensing approaches relying on SSF and alternative growth-stage-dependent SSFs.

Detection of moisture and moisture related phenomena from Skylab. [Texas

NASA Technical Reports Server (NTRS)

Eagleman, J. R.; Pogge, E. C.; Moore, R. K. (Principal Investigator); Hardy, N.; Lin, W.; League, L.

1973-01-01

The author has identified the following significant results. This is a preliminary report on the ability to detect soil moisture variation from the two different sensors on board Skylab. Initial investigations of S190A and Sl94 Skylab data and ground truth has indicated the following significant results. (1) There was a decrease in Sl94 antenna temperature from NW to SE across the Texas test site. (2) Soil moisture increases were measured from NW to SE across the test site. (3) There was a general increase in precipitation distribution and radar echoes from NW to SE across the site for the few days prior to measurements. This was consistent with the soil moisture measurements and gives more complete coverage of the site. (4) There are distinct variations in soil textures over the test site. This affects the moisture holding capacity of soils and must be considered. (5) Strong correlation coefficients were obtained between S194 antenna temperature and soil moisutre content. As the antenna temperature decreases soil moisture increases. (6) The Sl94 antenna temperature correlated best with soil mositure content in the upper two inches of the soil. A correlation coefficient of .988 was obtained. (7) Sl90A photographs in the red-infrared region were shown to be useful for identification of Abilene clay loam and for determining the distribution of this soil type.