Simulation of carbon dioxide mineralization and its effect on fault leakage rates in the South Georgia rift basin, southeastern U.S.

Over the past few decades, measured levels of atmospheric carbon dioxide have substantially increased. One of the ways to limit the adverse impacts of increased carbon dioxide concentrations is to capture and store it inside Earth's subsurface, a process known as CO2 sequestration. The success of this method is critically dependent on the ability to confine injected CO2 for up to thousands of years. Establishing effective maintenance of sealing systems of reservoirs is of importance to prevent CO2 leakage. In addition, understanding the nature and rate of potential CO2 leakage related to this injection process is essential to evaluating seal effectiveness and ultimately mitigating global warming. In this study, we evaluated the impact of common chemical reactions between CO2 and subsurface materials in situ as well as the relationship between CO2 plume distribution and the CO2 leakage within the seal zone that cause mineralization. Using subsurface seismic data and well log information, a three-dimensional model consisting of a reservoir and seal zones was created and evaluated for the South Georgia Rift (SGR) basin in the southeastern U.S. The Computer Modeling Group (CMG, 2017), was used to model the effect of CO2 mineralization on the optimal values of fault permeability permeabilitydue to fluid substitution between the formation water and CO2. The model simulated the chemical reactions between carbon dioxide and mafic minerals to produce stable minerals of carbonate rock that form in the fault. Preliminary results show that CO2 migration can be controlled effectively for fault permeability values between 0.1-1 mD. Within this range, mineralization effectively reduced CO2 leakage within the seal zone.

Land cover and vegetation carbon stock changes in Greece: A 29-year assessment based on CORINE and Landsat land cover data.

Evaluation of carbon sequestration in various land cover types is a valuable tool for environmental policies targeting towards minimization of CO2 emissions and climate change impacts. For the past few decades, remotely sensed information on land cover has been used as useful alternative to ground observations and has proved to be a robust tool for studying land use / land cover (LULC) changes. The present work deals with the assessment of land-cover changes in a Mediterranean country - Greece, where expected climate change impacts and desertification risk are stated to be severe. This work focused on the CORINE land cover inventory at a spatial resolution of 100 m from 1990 to 2018 and selected Landsat images at 30 m spatial resolution for 1990, 2000 and 2018. Results indicated that the dominant land-cover changes in Greece over the predefined 29-year period, are related to land transformation from Non-irrigated arable land to Irrigated areas, implying an intensification of agricultural practices. Natural grasslands lose a substantial part of their areas transforming into Sclerophyllus vegetation and Sparsely vegetated areas. Forests gain areas from Transitional woodland-shrub and Olive groves increase their extent indicating an overall transition to woody vegetation. Estimation of Vegetation Carbon Stocks indicated a moderate decrease in the 1990 decade followed by a significant increase up to 2012 and a slight decrease thereafter. Forests of all types are by far the most important carbon sinks. Possible implications of country's recent economic crisis were examined and results indicated that economic welfare of the country seems to favor certain land cover types such as Mixed Forests and Permanently Irrigated land, but also preservation of the Vegetation Carbon Stocks.

Mapping Land Use Land Cover Change in the Lower Mekong Basin from 1997 to 2010.

The Lower Mekong Basin (LMB) is biologically diverse, economically important, and home to about 65 million people. The region has undergone extensive environmental changes since the 1990s due to such factors as agricultural expansion and intensification, deforestation, more river damming, increased urbanization, growing human populations, expansion of industrial forest plantations, plus frequent natural disasters from flooding and drought. The Mekong river is also heavily used for human transportation, fishing, drinking water, and irrigation. This paper discusses use of pre-existing LULC maps from 1997 and 2010 to derive a LMB regional LULC change map for 9 classes per date using GIS overlay techniques. The change map was derived to aid SWAT hydrologic modeling applications in the LMB, given the 2010 map is currently used in multiple LMB SWAT models, whereas the 1997 map was previously used. The 2010 LULC map was constructed from Landsat and MODIS satellite data, while the 1997 map was from before the MODIS era and therefore based on available Landsat data. The 1997-2010 LULC change map showed multiple trends. Permanent agriculture had expanded in certain sub-basins into previously forested areas. Some agricultural areas were converted to industrial forest plantations. Extensive forest changes also occurred in some locations, such as areas changed to shifting cultivation or permanent crops. Also, the 1997 map under classified some urban areas, whereas the 2010 LULC map showed improved identification of such areas. LULC map accuracy were assessed for 213 randomly sampled locations. The 1997 and 2010 LULC maps showed high overall agreements with reference data exceeding 87%. The LULC change map yielded a moderately high level of overall agreement (78%) that improved to ~83% once LULC classification scheme specificity was reduced (forests and agriculture were each mapped as singular classes). The change map regionally showed a 4% decrease in agriculture and a 4 % increase in deciduous and evergreen forests combined, though deforestation hot spot areas also were evident. The project yielded LULC map data sets that are now available for aiding additional studies that assess LMB LULC change and the impacts such change may pose to water, agriculture, forestry, and disaster management efforts. More work is needed to map, quantify and assess LULC change since 2010 and to further update the 2010 LULC map currently used in the LMB SWAT models.

Very high resolution, altitude-corrected, TMPA-based monthly satellite precipitation product over the CONUS.

The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) product provided over 17 years of gridded precipitation datasets. However, the accuracy and spatial resolution of TMPA limits the applicability in hydrometeorological applications. We present a dataset that enhances the accuracy and spatial resolution of the TMPA monthly product (3B43). We resample the TMPA data to a 1 km grid and apply a correction function derived from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) to reduce bias in the data. We confirm a linear relationship between bias and elevation above 1,500 meters where TMPA underestimates measured precipitation, providing a proof-of-concept of how simple linear scaling can be used to augment existing satellite datasets. The result of the correction is the High-Resolution Altitude-Corrected Precipitation product (HRAC-Precip) for the CONUS. Using 9,200 precipitation stations from the Global Historical Climatology Network (GHCN), we compare the accuracy of TMPA 3B43 versus the new HRAC-Precip product. The results show an improvement of the mean absolute error of 12.98% on average.

Web-based decision support system tools: The Soil and Water Assessment Tool Online visualization and analyses (SWATOnline) and NASA earth observation data downloading and reformatting tool (NASAaccess).

The current influx of climate related information required scientists to communicate their findings to decision makers in governments, disaster preparedness organizations, and the general public. The Soil and Water Assessment Tool (SWAT) is a powerful modelling tool that allows scientists to simulate many of the physical processes involved in the water cycle. This article presents the design, methods and development efforts to overcome some of the limitations of the previously developed SWAT visualization software programs by creating a set of modular web applications that can be duplicated, customized, and run. Moreover, this article features a web application development tool for climate data retrieval. The NASAaccess fetches, extracts and reformats climate data from the National Aeronautics and Space Administration servers and outputs data compatible with hydrological models. This work has the potential to increase the SWAT's model impact on non-technically trained stakeholders and decision makers charged with water and climate management.

Evaluating hotspots for stormwater harvesting through participatory sensing.

Geographic Information Systems have been widely accepted to manage and manipulate spatial data associated with the hydrologic response of a watershed. Due to climate change and drought impacts, there is a need to conserve freshwater resources, which can be accomplished by introducing the concept of stormwater harvesting. Apart from hotspot identification and site screening, several economic, social, cultural, environmental aspects need to be considered before finalizing the suitable site for stormwater harvesting. The shortlisted sites are commonly ranked by considering various parameters, i.e. water demand, availability of stormwater and distance to end-use locations, which relate to economic aspects. In the present study, socio-environmental considerations are also constituted by adopting a web-GIS based approach. The geospatial datasets and metadata associated with the study area are organized as a repository in the open source database server (PostgreSQL/PostGIS), which is further assessed and analyzed by using GeoServer. This technique publishes the geospatial datasets to the public domain websites that can be accessed and visualized around the clock and across the world. This will help stakeholders gather and store responses from water planners and inhabitants, while minimizing the time and cost associated with field visits for collecting individual responses. In this respect, a questionnaire is prepared that includes queries associated with site selection and the responses are gathered from various institutions, water professionals, stakeholders and residents. Once the responses are collected, the Analytic Hierarchy Process has been implemented to compute the relative weights of each criterion with respect to the responses collected. The weights thus obtained assisted the planners in deciding the suitable stormwater harvesting site for Dehradun city in India. In context to responses gathered the sites 'B' and 'D' are given the maximum weightage to be the suitable sites in the study region. Also, the socio-environmental criteria such as 'community acceptance', 'recreational activities' and 'need for water reuse' have gathered the maximum weightage from the responses for the specific sites. Hence, the proposed methodology demonstrated how water professionals, civilians, planners, stakeholders and public can be included as participants in water-related decision making processes.

PASSIVE/ACTIVE MICROWAVE SOIL MOISTURE CHANGE DISAGGREGATION USING SMAPVEX12 DATA.

The SMAPVEX12 (Soil Moisture Active Passive (SMAP) Validation Experiment 2012) experiment was conducted during June-July 2012 in Manitoba, Canada with the goal of collecting remote sensing data and ground measurements for the development and testing of soil moisture retrieval algorithms under varying vegetation and soil conditions for the SMAP satellite. The aircraft based soil moisture data provided by the passive/active microwave sensor PALS (Passive and Active L-band System) has a nominal spatial resolution of 1600 m. However, this resolution is not compatible with agricultural, meteorological and hydrological studies that require high spatial resolutions and this issue can be solved by soil moisture disaggregation. The soil moisture disaggregation algorithm integrates radiometer soil moisture retrievals and high-resolution radar observations and it can provide soil moisture estimates at a finer scale than the radiometer data alone. In this study, a change detection algorithm was used for disaggregation of coarse resolution passive microwave soil moisture retrievals with radar backscatter coefficients obtained from the higher spatial resolution UAVSAR (Unmanned Air Vehicle Synthetic Aperture Radar) at crop field scale. The accuracy of the disaggregated change in soil moisture was evaluated using ground based soil moisture measurements collected during SMAPVEX12 campaign. The results showed that soil moisture spatial variabilities were better characterized by the disaggregated change in soil moisture estimates at 5 m / 800 m resolution as well as good agreement with in situ measurements. It also showed that VWC (Vegetation Water Content) did not have a big impact on disaggregation algorithm performance, with R2 of the disaggregated results ranging 0.628-0.794. The 5 m and 800m resolution disaggregated soil moisture did no show significant difference in statistical performance variables.

Ground and satellite based observation datasets for the Lower Mekong River Basin.

In 'Satellite observations and modeling to understand the Lower Mekong River Basin streamflow variability' [1] hydrological fluxes, meteorological variables, land cover land use maps, and soil characteristics and parameters data were compiled and processed for the Lower Mekong River Basin. In this work, daily streamflow time series data at nine gauges located at five different countries in the Mekong region (Thailand, Laos People׳s Democratic Republic (PDR), Myanmar, Cambodia, and Viet Nam) is presented. Satellite-based daily precipitation and air temperature (minimum & maximum) data is processed and provided over the entire basin as part of the dataset provided in this work. Moreover, land cover land use raster data that contains 18 classes that cover agriculture, urban, range and forests land cover land use classes for the basin is offered. In addition, a soil data that contains physical and chemical characteristics needed by physically based hydrological models to simulate the cycling of water and air is also provided.

Satellite observations and modeling to understand the Lower Mekong River basin streamflow variability.

In this work, we have used the Soil & Water Assessment Tool (SWAT) to examine streamflow variability of the Lower Mekong River Basin (LMRB) associated with changes in the Upper Mekong River Basin (UMRB) inflows. Two hypothetical experiments were formulated and evaluated for the LMRB, where we conducted runoff simulations with multiple inflow changes that include upstream runoff yield increase and decrease scenarios. Streamflow variability of the LMRB was quantified by two streamflow metrics that explain flow variability and predictability, and high flow disturbance. The model experiments were performed for the Lower Mekong River Basin with identical climate, soil, and other watershed characteristics data. Remote sensing precipitation (Tropical Rainfall Measurement Mission, TRMM, and Global Precipitation Measurement mission, GPM), meteorological data as well as spatial data that include a digital elevation model, newly developed soil information (Harmonized World Soil Database, HWSD), and land use and land cover were processed as input to the LMRB model simulations. Observed daily streamflow data along the Lower Mekong River from Chiang Sean, Thailand to Kratie, Cambodia were used for calibration and validation. Our work results suggest that the Lower Mekong River streamflow is highly variable and has a low predictability (Colwell index of about 32%). We found that releasing more water from upstream Mekong during rainfall months by 30% would result in a reduction in the Lower Mekong streamflow predictability by about 21%. This reduction in predictability is mainly attributed to a decrease in the Contingency index. Our work shows that the ability to predict floods/droughts at the Lower Mekong River would be reduced if there is any anticipated change (i.e., increase/decrease) from UMRB releases. Our results also show that releasing more flows from the upstream Mekong would also affect flood duration and the frequency of flood occurrences downstream. The results of this work thus help to quantify the sensitivity of streamflow variability at the Lower Mekong River Basin to upstream anthropogenic changes.

Improved Hydrological Decision Support System for the Lower Mekong River Basin Using Satellite-Based Earth Observations.

Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region's hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling.

Evaluating Renewable Groundwater Stress with GRACE Data in Greece.

Groundwater is a resilient water source and its importance is even greater in periods of drought. Areas such as the Mediterranean where adverse climate change effects are expected are bell-weather locations for groundwater depletion and are of considerable interest. The present study evaluates renewable groundwater stress (RGS) as the ratio of groundwater use to groundwater availability, quantifying use as the trend in gravity recovery and climate experiment-derived (GRACE) subsurface anomalies (ΔGWtrend ) and renewable groundwater availability as mean annual recharge. Estimates for mean annual recharge for the various regions in Greece have been derived using numerical models. Our results highlight two RGS regimes in Greece (variable stress and unstressed) of the four characteristic stress regimes, that is, overstressed, variable stress, human-dominated stress, and unstressed, defined as a function of the sign of use and the sign of groundwater availability (positive or negative). Variable stress areas are found in Central Greece (Thessaly region), where intensive agriculture results in negative ΔGWtrend values combined with positive mean annual recharge rates. RGS values range from -0.05 to 0, indicating a low impact area. Within this region, adverse effects of groundwater overexploitation are already evident based on the negative GRACE anomalies; however, recharge is still positive, mitigating the effects of over-pumping. The rest of Greek aquifers fall within the unstressed category, with RGS values from 0.02 to 0.05, indicating that the rate of use is less than the natural recharge rate.

A comparative study of available water in the major river basins of the world.

Numerous large river basins of the world have few and irregular observations of the components of the terrestrial hydrological cycle with the exception of stream gauges at a few locations and at the outlet along with sparsely distributed rain gauges. Using observations from satellite sensors and output from global land surface models, it is possible to study these under-observed river basins. With populations greater than a billion people, some of these rivers (e.g., the Ganga-Brahmaputra, the Yangtze, the Nile and the Mekong) are the economic engines of the countries they transect, yet thorough assessment of their flow dynamics and variability in regard to water resource management is still lacking. In this paper, we use soil moisture (0-2m) and surface runoff from the NASA Global Land Data Assimilation System (GLDAS), evapotranspiration, and Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and rainfall from the Tropical Rainfall Measuring Mission (TRMM) and total water storage anomaly from the Gravity Recovery and Climate Experiment (GRACE) to examine variability of individual water balance components. To this end, understanding the inter-annual and intra-seasonal variability and the spatial variability of the water balance components in the major river basins of the world will help to plan for improved management of water resources for the future.

Repeated attempts improve tracheal tube insertion time using the intubating laryngeal airway in a mannequin.

STUDY OBJECTIVE: To determine if repeated performance of endotracheal tube insertion via the intubating laryngeal airway (ILA) would shorten insertion time in mannequins. DESIGN: Prospective study. SETTING: Clinical Skills Laboratory, Department of Anesthesia, Toronto Western Hospital. PARTICIPANTS: 65 department anesthesiologists. MEASUREMENTS: After a video training session, anesthesiologists with no previous experience with the ILA performed 5 consecutive ILA-guided tracheal tube intubations on a mannequin. Each participant completed Task 1: insertion of an ILA; Task 2: blind insertion of a tracheal tube through the ILA, and Task 3: removal of the ILA. The time required for each task and the total intubation time for the three tasks over the 5 attempts were recorded. These times were compared using repeated-measures analysis of variance. The success rate among the 5 attempts was compared using Chi-Square analyses. MAIN RESULTS: A total of 65 anesthesiologists performed 5 ILA-guided tracheal intubations each. Total intubation time decreased from the first to the fifth attempt (92.6 ± 22.7 sec, 74.5 ± 19.2 sec, 66.5 ± 16.5 sec, 65.9 ± 19.9 sec, and 60.8 ± 16.3 sec; P < 0.001). Significant differences in intubation times were noted between the first and second, and the second and third attempts (P < 0.001 and P = 0.02, respectively). The success rate did not change over the 5 attempts (84.6%, 89.2%, 84.6%, 89.2%, and 90.8%; P = 0.737). CONCLUSIONS: Total intubation time decreased by 34% (92.6 to 60.8 sec) over the 5 attempts in mannequins. The success rate ranged from 84.6% to 90.8% and did not differ significantly over the 5 attempts.