Geology topics

Shu-Guang Liu

Publications and source records attributed to Shu-Guang Liu.

At least 19 recordsLinked to original sources

USGS2015

Spatial variations in immediate greenhouse gases and aerosol emissions and resulting radiative forcing from wildfires in interior Alaska

Boreal fires can cool the climate; however, this conclusion came from individual fires and may not represent the whole story. We hypothesize that the climatic impact of boreal fires depends on local landscape heterogeneity such as burn severity, prefire vegetation type, and soil properties. To test this hypothesis, spatially explicit emission of greenhouse gases (GHGs) and aerosols and their resulting radiative forcing are required as an important and necessary component towards a full assessment. In this study, we integrated remote sensing (Landsat and MODIS) and models (carbon consumption model, emission factors model, and radiative forcing model) to calculate the carbon consumption, GHGs and aerosol emissions, and their radiative forcing of 2001–2010 fires at 30 m resolution in the Yukon River Basin of Alaska. Total carbon consumption showed significant spatial variation, with a mean of 2,615 g C m −2 and a standard deviation of 2,589 g C m −2 . The carbon consumption led to different amounts of GHGs and aerosol emissions, ranging from 593.26 Tg (CO 2 ) to 0.16 Tg (N 2 O). When converted to equivalent CO 2 based on global warming potential metric, the maximum 20 years equivalent CO 2 was black carbon (713.77 Tg), and the lowest 20 years equivalent CO 2 was organic carbon (−583.13 Tg). The resulting radiative forcing also showed significant spatial variation: CO 2 , CH 4 , and N 2 O can cause a 20-year mean radiative forcing of 7.41 W m −2 with a standard deviation of 2.87 W m −2 . This emission forcing heterogeneity indicates that different boreal fires have different climatic impacts. When considering the spatial variation of other forcings, such as surface shortwave forcing, we may conclude that some boreal fires, especially boreal deciduous fires, can warm the climate.

Alaska↗

USGS2015

Corn Belt soil carbon and macronutrient budgets with projected sustainable stover harvest

Corn ( Zea mays L.) stover has been identified as a prime feedstock for biofuel production in the U.S. Corn Belt because of its perceived abundance and availability, but long-term stover harvest effects on regional nutrient budgets have not been evaluated. We defined the minimum stover requirement (MSR) to maintain current soil organic carbon levels and then estimated current and future soil carbon (C), nitrogen (N), phosphorus (P), and potassium (K) budgets for various stover harvest scenarios. Analyses for 2006 through 2010 across the entire Corn Belt indicated that currently, 28 Tg or 1.6 Mg ha −1 of stover could be sustainably harvested from 17.95 million hectares (Mha) with N, P, and K removal of 113, 26, and 47 kg ha −1 , respectively, and C removal for that period was estimated to be 4.55 Mg C ha −1 . Assuming continued yield increases and a planted area of 26.74 Mha in 2050, 77.4 Tg stover (or 2.4 Mg ha −1 ) could be sustainably harvested with N, P, and K removal of 177, 37, and 72 kg ha −1 , respectively, along with C removal of &sim;6.57 Mg C ha −1 . Although there would be significant variation across the region, harvesting only the excess over the MSR under current fertilization rates would result in a small depletion of soil N (−5 ± 27 kg ha −1 ) and K (−20 ± 31 kg ha −1 ) and a moderate surplus of P (36 ± 18 kg ha −1 ). Our 2050 projections based on continuing to keep the MSR, but having higher yields indicate that soil N and K deficits would become larger, thus emphasize the importance of balancing soil nutrient supply with crop residue removal.

Iowa, Illinois, Indiana, Michigan, Minnesota, Miss↗

USGS2015

Spatiotemporal variation of surface shortwave forcing from fire-induced albedo change in interior Alaska

The albedo change caused by both fires and subsequent succession is spatially heterogeneous, leading to the need to assess the spatiotemporal variation of surface shortwave forcing (SSF) as a component to quantify the climate impacts of high-latitude fires. We used an image reconstruction approach to compare postfire albedo with the albedo assuming fires had not occurred. Combining the fire-caused albedo change from the 2001-2010 fires in interior Alaska and the monthly surface incoming solar radiation, we examined the spatiotemporal variation of SSF in the early successional stage of around 10 years. Our results showed that while postfire albedo generally increased in fall, winter, and spring, some burned areas could show an albedo decrease during these seasons. In summer, the albedo increased for several years and then declined again. The spring SSF distribution did not show a latitudinal decrease from south to north as previously reported. The results also indicated that although the SSF is usually largely negative in the early successional years, it may not be significant during the first postfire year. The annual 2005-2010 SSF for the 2004 fire scars was -1.30, -4.40, -3.31, -4.00, -3.42, and -2.47 Wm-2. The integrated annual SSF map showed significant spatial variation with a mean of -3.15 Wm-2 and a standard deviation of 3.26 Wm-2, 16% of burned areas having positive SSF. Our results suggest that boreal deciduous fires would be less positive for climate change than boreal evergreen fires. Future research is needed to comprehensively investigate the spatiotemporal radiative and non-radiative forcings to determine the effect of boreal fires on climate.

Alaska↗

USGS2014

The carbon cycle and hurricanes in the United States between 1900 and 2011

Hurricanes cause severe impacts on forest ecosystems in the United States. These events can substantially alter the carbon biogeochemical cycle at local to regional scales. We selected all tropical storms and more severe events that made U.S. landfall between 1900 and 2011 and used hurricane best track database, a meteorological model (HURRECON), National Land Cover Database (NLCD), U. S. Department of Agirculture Forest Service biomass dataset, and pre- and post-MODIS data to quantify individual event and annual biomass mortality. Our estimates show an average of 18.2 TgC/yr of live biomass mortality for 1900–2011 in the US with strong spatial and inter-annual variability. Results show Hurricane Camille in 1969 caused the highest aboveground biomass mortality with 59.5 TgC. Similarly 1954 had the highest annual mortality with 68.4 TgC attributed to landfalling hurricanes. The results presented are deemed useful to further investigate historical events, and the methods outlined are potentially beneficial to quantify biomass loss in future events.

Scientific Reports↗

USGS2014

Improvement of the R-SWAT-FME framework to support multiple variables and multi-objective functions

Application of numerical models is a common practice in the environmental field for investigation and prediction of natural and anthropogenic processes. However, process knowledge, parameter identifiability, sensitivity, and uncertainty analyses are still a challenge for large and complex mathematical models such as the hydrological/water quality model, Soil and Water Assessment Tool (SWAT). In this study, the previously developed R program language-SWAT-Flexible Modeling Environment (R-SWAT-FME) was improved to support multiple model variables and objectives at multiple time steps (i.e., daily, monthly, and annually). This expansion is significant because there is usually more than one variable (e.g., water, nutrients, and pesticides) of interest for environmental models like SWAT. To further facilitate its easy use, we also simplified its application requirements without compromising its merits, such as the user-friendly interface. To evaluate the performance of the improved framework, we used a case study focusing on both streamflow and nitrate nitrogen in the Upper Iowa River Basin (above Marengo) in the United States. Results indicated that the R-SWAT-FME performs well and is comparable to the built-in auto-calibration tool in multi-objective model calibration. Overall, the enhanced R-SWAT-FME can be useful for the SWAT community, and the methods we used can also be valuable for wrapping potential R packages with other environmental models.

Science of the Total Environment↗

USGS2012

MODIS-informed greenness responsesto daytime land surface temperaturefluctuations and wildfire disturbancesin the Alaskan Yukon River Basin

Pronounced climate warming and increased wildfire disturbances are known to modify forest composition and control the evolution of the boreal ecosystem over the Yukon River Basin (YRB) in interior Alaska. In this study, we evaluate the post-fire green-up rate using the normalized difference vegetation index (NDVI) derived from 250 m 7 day eMODIS (an alternative and application-ready type of Moderate Resolution Imaging Spectroradiometer (MODIS) data) acquired between 2000 and 2009. Our analyses indicate measureable effects on NDVI values from vegetation type, burn severity, post-fire time, and climatic variables. The NDVI observations from both fire scars and unburned areas across the Alaskan YRB showed a tendency of an earlier start to the growing season (GS); the annual variations in NDVI were significantly correlated to daytime land surface temperature (LST) fluctuations; and the rate of post-fire green-up depended mainly on burn severity and the time of post-fire succession. The higher average NDVI values for the study period in the fire scars than in the unburned areas between 1950 and 2000 suggest that wildfires enhance post-fire greenness due to an increase in post-fire evergreen and deciduous species components

Alaska↗

USGS2012

Identifying potential areas for biofuel production and evaluating the environmental effects: a case study of the James River Basin in the Midwestern United States

Biofuels are now an important resource in the United States because of the Energy Independence and Security Act of 2007. Both increased corn growth for ethanol production and perennial dedicated energy crop growth for cellulosic feedstocks are potential sources to meet the rising demand for biofuels. However, these measures may cause adverse environmental consequences that are not yet fully understood. This study 1) evaluates the long-term impacts of increased frequency of corn in the crop rotation system on water quantity and quality as well as soil fertility in the James River Basin and 2) identifies potential grasslands for cultivating bioenergy crops (e.g. switchgrass), estimating the water quality impacts. We selected the soil and water assessment tool, a physically based multidisciplinary model, as the modeling approach to simulate a series of biofuel production scenarios involving crop rotation and land cover changes. The model simulations with different crop rotation scenarios indicate that decreases in water yield and soil nitrate nitrogen (NO 3 -N) concentration along with an increase in NO 3 -N load to stream water could justify serious concerns regarding increased corn rotations in this basin. Simulations with land cover change scenarios helped us spatially classify the grasslands in terms of biomass productivity and nitrogen loads, and we further derived the relationship of biomass production targets and the resulting nitrogen loads against switchgrass planting acreages. The suggested economically efficient (planting acreage) and environmentally friendly (water quality) planting locations and acreages can be a valuable guide for cultivating switchgrass in this basin. This information, along with the projected environmental costs (i.e. reduced water yield and increased nitrogen load), can contribute to decision support tools for land managers to seek the sustainability of biofuel development in this region.

Missouri↗

USGS2012

A land-use and land-cover modeling strategy to support a national assessment of carbon stocks and fluxes

Changes in land use, land cover, disturbance regimes, and land management have considerable influence on carbon and greenhouse gas (GHG) fluxes within ecosystems. Through targeted land-use and land-management activities, ecosystems can be managed to enhance carbon sequestration and mitigate fluxes of other GHGs. National-scale, comprehensive analyses of carbon sequestration potential by ecosystem are needed, with a consistent, nationally applicable land-use and land-cover (LULC) modeling framework a key component of such analyses. The U.S. Geological Survey has initiated a project to analyze current and projected future GHG fluxes by ecosystem and quantify potential mitigation strategies. We have developed a unique LULC modeling framework to support this work. Downscaled scenarios consistent with IPCC Special Report on Emissions Scenarios (SRES) were constructed for U.S. ecoregions, and the FORE-SCE model was used to spatially map the scenarios. Results for a prototype demonstrate our ability to model LULC change and inform a biogeochemical modeling framework for analysis of subsequent GHG fluxes. The methodology was then successfully used to model LULC change for four IPCC SRES scenarios for an ecoregion in the Great Plains. The scenario-based LULC projections are now being used to analyze potential GHG impacts of LULC change across the U.S.

Applied Geography↗

USGS2012

Current and potential sustainable corn stover feedstock for biofuel production in the United States

Increased demand for corn ( Zea mays L.) stover as a feedstock for cellulosic ethanol raises concerns about agricultural sustainability. Excessive corn stover harvesting could have long-term impacts on soil quality. We estimated current and future stover production and evaluated the potential harvestable stover amount (HSA) that could be used for biofuel feedstock in the United States by defining the minimum stover requirement (MSR) associated with the current soil organic carbon (SOC) content, tillage practices, and crop rotation systems. Here we show that the magnitude of the current HSA is limited (31 Tg y −1 , dry matter) due to the high MSR for maintaining the current SOC content levels of soils that have a high carbon content. An alternative definition of MSR for soils with a moderate level of SOC content could significantly elevate the annual HSA to 68.7 Tg, or even to 132.2 Tg if the amount of currently applied manure is counted to partially offset the MSR. In the future, a greater potential for stover feedstock could come from an increase in stover yield, areal harvest index, and/or the total planted area. These results suggest that further field experiments on MSR should be designed to identify differences in MSR magnitude between maintaining SOC content and preventing soil erosion, and to understand the role of current SOC content level in determining MSR from soils with a wide range of carbon contents and climatic conditions.

Biomass and Bioenergy↗

USGS2012

Urbanization eases water crisis in China

Socioeconomic development in China has resulted in rapid urbanization, which includes a large amount of people making the transition from rural areas to cities. Many have speculated that this mass migration may have worsened the water crisis in many parts of the country. However, this study shows that the water crisis would be more severe if the rural-to-urban migration did not occur.

Environmental Development↗

USGS2012

Modeling of land use and reservoir effects on nonpoint source pollution in a highly agricultural basin

Nonpoint source (NPS) pollution is tightly linked to land use activities that determine the sources and magnitudes of pollutant loadings to stream water. The pollutant loads may also be alleviated within reservoirs because of the physical interception resulting from changed hydrological regimes and other biochemical processes. It is important but challenging to assess the NPS pollution processes with human effects due to the measurement limitations. The objective of this study is to evaluate the effects of human activities such as land uses and reservoir operation on the hydrological and NPS pollution processes in a highly agricultural area-the Iowa River Basin-using the Soil and Water Assessment Tool (SWAT). The evaluation of model performance at multiple sites reveals that SWAT can consistently simulate the daily streamflow, and monthly/annual sediment and nutrient loads (nitrate nitrogen and mineral phosphorus) in the basin. We also used the calibrated model to estimate the trap efficiencies of sediment (~78%) and nutrients (~30%) in the Coralville Reservoir within the basin. These non-negligible effects emphasize the significance of incorporating the sediment and nutrient removal mechanisms into watershed system studies. The spatial quantification of the critical NPS pollution loads can help identify hot-spot areas that are likely locations for the best management practices.

Iowa↗

USGS2012

Novel approach for computing photosynthetically active radiation for productivity modeling using remotely sensed images in the Great Plains, United States

Gross primary production (GPP) is a key indicator of ecosystem performance, and helps in many decision-making processes related to environment. We used the Eddy covariancelight use efficiency (EC-LUE) model for estimating GPP in the Great Plains, United States in order to evaluate the performance of this model. We developed a novel algorithm for computing the photosynthetically active radiation (PAR) based on net radiation. A strong correlation ( R 2 =0.94, N =24) was found between daily PAR and Landsat-based mid-day instantaneous net radiation. Though the Moderate Resolution Spectroradiometer (MODIS) based instantaneous net radiation was in better agreement ( R 2 =0.98, N =24) with the daily measured PAR, there was no statistical significant difference between Landsat based PAR and MODIS based PAR. The EC-LUE model validation also confirms the need to consider biological attributes (C 3 versus C 4 plants) for potential light use efficiency. A universal potential light use efficiency is unable to capture the spatial variation of GPP. It is necessary to use C 3 versus C 4 based land use/land cover map for using EC-LUE model for estimating spatiotemporal distribution of GPP.

Journal of Applied Remote Sensing↗

USGS2012

R-SWAT-FME user's guide

R program language-Soil and Water Assessment Tool-Flexible Modeling Environment (R-SWAT-FME) (Wu and Liu, 2012) is a comprehensive modeling framework that adopts an R package, Flexible Modeling Environment (FME) (Soetaert and Petzoldt, 2010), for the Soil and Water Assessment Tool (SWAT) model (Arnold and others, 1998; Neitsch and others, 2005). This framework provides the functionalities of parameter identifiability, model calibration, and sensitivity and uncertainty analysis with instant visualization. This user's guide shows how to apply this framework for a customized SWAT project.

Open-File Report↗

USGS2011

Quantifying the hydrological responses to climate change in an intact forested small watershed in southern China

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.

Guangdong Province↗

USGS2011

Estimating seasonal evapotranspiration from temporal satellite images

Estimating seasonal evapotranspiration (ET) has many applications in water resources planning and management, including hydrological and ecological modeling. Availability of satellite remote sensing images is limited due to repeat cycle of satellite or cloud cover. This study was conducted to determine the suitability of different methods namely cubic spline, fixed, and linear for estimating seasonal ET from temporal remotely sensed images. Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) model in conjunction with the wet METRIC (wMETRIC), a modified version of the METRIC model, was used to estimate ET on the days of satellite overpass using eight Landsat images during the 2001 crop growing season in Midwest USA. The model-estimated daily ET was in good agreement ( R 2 = 0.91) with the eddy covariance tower-measured daily ET. The standard error of daily ET was 0.6 mm (20%) at three validation sites in Nebraska, USA. There was no statistically significant difference ( P > 0.05) among the cubic spline, fixed, and linear methods for computing seasonal (July–December) ET from temporal ET estimates. Overall, the cubic spline resulted in the lowest standard error of 6 mm (1.67%) for seasonal ET. However, further testing of this method for multiple years is necessary to determine its suitability.

Irrigation Science↗

USGS2011

Derived crop management data for the LandCarbon Project

The LandCarbon project is assessing potential carbon pools and greenhouse gas fluxes under various scenarios and land management regimes to provide information to support the formulation of policies governing climate change mitigation, adaptation and land management strategies. The project is unique in that spatially explicit maps of annual land cover and land-use change are created at the 250-meter pixel resolution. The project uses vast amounts of data as input to the models, including satellite, climate, land cover, soil, and land management data. Management data have been obtained from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) and USDA Economic Research Service (ERS) that provides information regarding crop type, crop harvesting, manure, fertilizer, tillage, and cover crop (U.S. Department of Agriculture, 2011a, b, c). The LandCarbon team queried the USDA databases to pull historic crop-related management data relative to the needs of the project. The data obtained was in table form with the County or State Federal Information Processing Standard (FIPS) and the year as the primary and secondary keys. Future projections were generated for the A1B, A2, B1, and B2 Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) scenarios using the historic data values along with coefficients generated by the project. The PBL Netherlands Environmental Assessment Agency (PBL) Integrated Model to Assess the Global Environment (IMAGE) modeling framework (Integrated Model to Assess the Global Environment, 2006) was used to develop coefficients for each IPCC SRES scenario, which were applied to the historic management data to produce future land management practice projections. The LandCarbon project developed algorithms for deriving gridded data, using these tabular management data products as input. The derived gridded crop type, crop harvesting, manure, fertilizer, tillage, and cover crop products are used as input to the LandCarbon models to represent the historic and the future scenario management data. The overall algorithm to generate each of the gridded management products is based on the land cover and the derived crop type. For each year in the land cover dataset, the algorithm loops through each 250-meter pixel in the ecoregion. If the current pixel in the land cover dataset is an agriculture pixel, then the crop type is determined. Once the crop type is derived, then the crop harvest, manure, fertilizer, tillage, and cover crop values are derived independently for that crop type. The following is the overall algorithm used for the set of derived grids. The specific algorithm to generate each management dataset is discussed in the respective section for that dataset, along with special data handling and a description of the output product.

Open-File Report↗

USGS2011

Baseline and projected future carbon storage and greenhouse-gas fluxes in the Great Plains region of the United States

This assessment was conducted to fulfill the requirements of section 712 of the Energy Independence and Security Act (EISA) of 2007 and to improve understanding of carbon and greenhouse gas (GHG) fluxes in the Great Plains region in the central part of the United States. The assessment examined carbon storage, carbon fluxes, and other GHG fluxes (methane and nitrous oxide) in all major terrestrial ecosystems (forests, grasslands/shrublands, agricultural lands, and wetlands) and freshwater aquatic systems (rivers, streams, lakes, and impoundments) in two time periods: baseline (generally in the first half of the 2010s) and future (projections from baseline to 2050). The assessment was based on measured and observed data collected by the U.S. Geological Survey (USGS) and many other agencies and organizations and used remote sensing, statistical methods, and simulation models.

Great Plains↗

USGS2010

The need for simultaneous evaluation of ecosystem services and land use change

We are living in a period of massive global change. This rate of change may be almost without precedent in geologic history ( 1 ). Even the most remote areas of the planet are influenced by human activities. Modern landscapes have been highly modified to accommodate a growing human population that the United Nations has forecast to peak at 9.1 billion by 2050. Over this past century, reliance on services from ecosystems has increased significantly and, over past decades, sustainability of our modern, intensively managed ecosystems has been a topic of serious international concern ( 1 ). Numerous papers addressing a particular land-use change effect on specific ecosystem services have recently been published. For example, there is currently great interest in increasing biofuel production to achieve energy inde- pendence goals and recent papers have independently focused attention on impacts of land-use change on single ecosystem services such as carbon sequestration ( 2 ) and many others (e.g., water availability, biodiversity, pollination). However, land-use change clearly affects myriad ecosystem services simultaneously. Hence, a broader perspective and context is needed to evaluate and understand interrelated affects on multiple ecosystem services, especially as we strive for the goal of sustainably managing global ecosystems. Similarly, land uses affect ecosystem services synergistically; single land-use evaluations may be misleading because the overall impact on an ecosystem is not evaluated. A more holistic approach would provide a means and framework to characterize how land-use change affects provisioning of goods and services of complete ecosystems.

Environmental Science & Technology↗