Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.     

Applying Statistical Causal Analyses to Agricultural Conservation: A Case Study Examining P Loss Impacts

Estimating the effect of agricultural conservation practices on reducing nutrient loss using observational data can be confounded by factors such as differing crop types and management practices. As we may not have the full knowledge of these confounding factors, conventional statistical meta‐analysis methods can be misleading. We discuss the use of two statistical causal analysis methods for quantifying the effects of water and soil conservation practices in reducing P loss from agricultural fields. With the propensity score method, a subset of data was used to form a treatment group and a control group with similar distributions of confounding factors. With the multilevel modeling method, data were stratified based on important confounding factors, and the conservation practice effect was evaluated for each stratum. Both methods resulted in similar estimates of the conservation practice effect (total P load reduction avg. ~70%). In addition, both methods show evidence of conservation practices reducing the incremental increase in total P export per unit increase in fertilizer application. These results are presented as examples of the types of outcomes provided by statistical causal analyses, not to provide definitive estimates of P loss reduction. The enhanced meta‐analysis methods presented within are applicable for improved assessment of agricultural practices and their effects and can be used for providing realistic parameter values for watershed‐scale modeling.     

Modeling urban solar energy with high spatiotemporal resolution: A case study in Toronto,Canada

This research presents a method to determine the maximum potential for the capturing of solar radiation on the rooftop of buildings in an urban environment. This involves the modeling of solar energy potential and comparison to historical building energy demand profiles through the use of 3-D solar simulation software tools and geographic information systems (GIS). The objective is to accurately identify the amount of surface area that is suitable for solar photovoltaic (PV) installations and to estimate the hourly PV electricity generation potential of existing building rooftops in an urban environment. This study demonstrates a viable approach for modeling urban solar energy and offers valuable information for electricity distributors, policy makers, and urban energy planners to facilitate the substantial design of a green built environment. The developed methodology is comprised of three main sections: (1) determination of suitable rooftop area, (2) determination of the amount of incident solar radiation available per rooftop, and (3) estimation of hourly solar PV electricity generation potential. A case study was performed using this method for Ryerson University, located in Toronto, Canada. It was found that solar PV could supply up to 19% of the study area’s electricity demands during peak consumption hours. The potential benefits of solar PV was also estimated based upon hourly greenhouse gas emission intensity factors as well as Time-of-Use (TOU) savings through the Ontario Feed-in-Tariff (FIT) program, which allows for better representation of the positive impacts of solar technologies.     

Spatio-temporal characteristics of PM10 concentration across Malaysia

The recurrence of forest fires in Southeast Asia and associated biomass burning, has contributed markedly to the problem of trans-boundary haze and the long-range movement of pollutants in the region. Air pollutants, specifically particulate matter in the atmosphere, have received extensive attention, mainly because of their adverse effect on people's health. In this study, the spatial and temporal variability of the PM10 concentration across Malaysia was analyzed by means of the rotated principal component analysis. The results suggest that the variability of the PM10 concentration can be decomposed into four dominant modes, each characterizing different spatial and temporal variations. The first mode characterizes the southwest coastal region of the Malaysian Peninsular with the PM10 showing a peak concentration during the summer monsoon i.e. when the winds are predominantly southerlies or southwesterlies, and a minimal concentration during the winter monsoon. The second mode features the region of western Borneo with the PM10 exhibiting a concentration surge in August–September, which is likely to be the result of the northward shift of the Inter Tropical Convergence Zone (ITCZ) and the subsequent rapid arrival of the rainy season. The third mode delineates the northern region of the Malaysian Peninsular with strong bimodality in the PM10 concentration. Seasonally, this component exhibits two concentration maxima during the late winter and summer monsoons, as well as two minima during the inter-monsoon periods. The fourth dominant mode characterizes the northern Borneo region which exhibits weaker seasonality of the PM10 concentration. Generally, the seasonal fluctuation of the PM10 concentration is largely associated with the seasonal variation of rainfall in the country. However, in addition to this, the PM10 concentration also fluctuates markedly in two timescale bands i.e. 10–20 days quasi-biweekly (QBW) and 30–60 days lower frequency (LF) band of the intra-seasonal timescales. These intra-seasonal fluctuations show strong seasonality with the largest fraction of variance occurring during the boreal summer and the weakest variance during the winter. Generally, the LF intra-seasonal oscillation is stronger compared to the QBW intra-seasonal band.     

Modeling traffic air pollution in street canyons in New York City for intra-urban exposure assessment in the US Multi-Ethnic Study of atherosclerosis and air pollution

We evaluated the Danish AirGIS air quality and exposure model system using air quality measurement data from New York City in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Measurements were used from three US EPA Air Quality System (AQS) monitoring stations and a comprehensive MESA Air measurement campaign including about 150 different locations and about 650 samples of about 2 week measurements of NO_x, NO₂ and PM_2.5. AirGIS is a deterministic exposure model system based on the dispersion models Operational Street Pollution Model (OSPM) and the Urban Background Model (UBM). The UBM model reproduced the annual levels within 1–26% depending on station and pollutant at the three urban background EPA monitor stations, and generally reproduced well the seasonal and diurnal variation. The full model with OSPM and UBM reproduced the MESA Air measurements with a correlation coefficient of r² = 0.51 for NO_x, r² = 0.28 for NO₂ and r² = 0.73 for PM_2.5.     

How good is GLASOD?

The Global Assessment of Soil Degradation (GLASOD) has been the most influential global appraisal of land quality in terms of environmental policy. However, its expert judgments were never tested for their consistency and could not be reproduced at unvisited sites, while the relationship between the GLASOD assessments of land degradation and the social and economic impact of that degradation remains unclear. Yet, other methodologies that could respond to urgent calls for an updated assessment of the global environmental quality are not operational or, at best, in progress. Therefore, we evaluate the reliability and social relevance of the GLASOD approach and assess its candidacy for new global environmental assessments. The study concentrates on the African continent, capitalizing on new GIS data to delineate and define the characteristics of GLASOD map units. Consistency is tested by comparing expert judgments on soil degradation hazard for similar combinations of biophysical conditions and land use. Reproducibility is evaluated by estimating an ordered logit model that relates the qualitative land degradation classes to easily available information on explanatory variables, the results of which can be used to assess the land degradation at unvisited sites. Finally, a cross-sectional analysis investigates the relation between GLASOD assessments and crop production data at sub-national scale and its association with the prevalence of malnutrition. The GLASOD assessments prove to be only moderately consistent and hardly reproducible, while the counter-intuitive trend with crop production reveals the complexity of the production-degradation relationship. It appears that increasing prevalence of malnutrition coincides with poor agro-productive conditions and highly degraded land. The GLASOD approach can be improved by resolving the differences in conceptualization among experts and by defining the boundaries of the ordered classes in the same units as independent, quantitative land degradation data.     

Monitoring Environmental Impact in the Upper Sonoran Lifestyle: A New Tool for Rapid Ecological Assessment

Characterized by expensive housing, high socioeconomic status, and topographic relief, Upper Sonoran Lifestyle communities are found primarily along the Wildland-Urban Interface (WUI) in the Phoenix, Arizona metro area. Communities like these sprawl into the wildlands in the United States Southwest, creating a distinct urban fringe. This article, through locational comparison, introduces and evaluates a new field assessment tool for monitoring anthropogenic impact on soil–vegetation interactions along the well-maintained multi-use recreational trails in Upper Sonoran Lifestyle region. Comparing data from randomly selected transects along other multi-use trails with data from a control site revealed three key indicators of anthropogenic disturbances on soil–vegetation interactions: soil disturbance, vegetation disturbance, and vegetation density. Soil and vegetation disturbance displayed an average distance decay exponent factor of −0.60, while vegetation density displayed a reverse decay average of 0.60. Other important indicators of disturbance included vegetation type, biological soil crusts, and soil bulk density. The predictive ability of this new field tool enhances its applicability, offering a powerful rapid ecological assessment method for monitoring long-term anthropogenic impact in the Upper Sonoran Lifestyle, and other sprawling cities along the WUI.     

Hydrogeochemical Indicators of Groundwater Flow Systems in the Yangwu River Alluvial Fan,Xinzhou Basin,Shanxi, China

Based on analysis of groundwater hydrochemical and isotopic indicators, this article aims to identify the groundwater flow systems in the Yangwu River alluvial fan, in the Xinzhou Basin, China. Groundwater δ²H and δ¹⁸O values indicate that the origin of groundwater is mainly from precipitation, with local evaporative influence. d-excess values lower than 10% in most groundwaters suggest a cold climate during recharge in the area. Major ion chemistry, including rCa/rMg and rNa/rCl ratios, show that groundwater salinization is probably dominated by water–rock interaction (e.g., silicate mineral weathering, dissolution of calcite and dolomite and cation exchange) in the Yangwu River alluvial fan, and locally by intensive evapotranspiration in the Hutuo River valley. Cl and Sr concentrations follow an increasing trend in shallow groundwater affected by evaporation, and a decreasing trend in deep groundwater. ⁸⁷Sr/⁸⁶Sr ratios reflect the variety of lithologies encountered during throughflow. The groundwater flow systems (GFS) of the Yangwu River alluvial fan include local and intermediate flow systems. Hydrogeochemical modeling results, simulated using PHREEQC, reveal water–rock interaction processes along different flow paths. This modeling method is more effective for characterizing flow paths in the intermediate system than in the local system. Artificial exploitation on groundwater in the alluvial fan enhances mixing between different groundwater flow systems.     

Degassing of H/He, CFCs and SF6 by denitrification: Measurements and two-phase transport simulations

The production of N₂ gas by denitrification may lead to the appearance of a gas phase below the water table prohibiting the conservative transport of tracer gases required for groundwater dating. We used a two-phase flow and transport model (STOMP) to study the reliability of ³H/³He, CFCs and SF₆ as groundwater age tracers under agricultural land where denitrification causes degassing. We were able to reproduce the amount of degassing (R² = 69%), as well as the ³H (R² = 79%) and ³He (R² = 76%) concentrations observed in a ³H/³He data set using simple 2D models. We found that the TDG correction of the ³H/³He age overestimated the control ³He/³He age by 2.1 years, due to the accumulation of ³He in the gas phase. The total uncertainty of degassed ³H/³He ages of 6 years (± 2 σ) is due to the correction of degassed ³He using the TDG method, but also due to the travel time in the unsaturated zone and the diffusion of bomb peak ³He. CFCs appear to be subject to significant degradation in anoxic groundwater and SF₆ is highly susceptible to degassing. We conclude that ³H/³He is the most reliable method to date degassed groundwater and that two-phase flow models such as STOMP are useful tools to assist in the interpretation of degassed groundwater age tracer data.     

Influence of temporally variable groundwater flow conditions on point measurements and contaminant mass flux estimations

Monitoring of contaminant concentrations, e.g., for the estimation of mass discharge or contaminant degradation rates, often is based on point measurements at observation wells. In addition to the problem, that point measurements may not be spatially representative, a further complication may arise due to the temporal dynamics of groundwater flow, which may cause a concentration measurement to be not temporally representative. This paper presents results from a numerical modeling study focusing on temporal variations of the groundwater flow direction. “Measurements” are obtained from point information representing observation wells installed along control planes using different well frequencies and configurations. Results of the scenario simulations show that temporally variable flow conditions can lead to significant temporal fluctuations of the concentration and thus are a substantial source of uncertainty for point measurements. Temporal variation of point concentration measurements may be as high as the average concentration determined, especially near the plume fringe, even when assuming a homogeneous distribution of the hydraulic conductivity. If a heterogeneous hydraulic conductivity field is present, the concentration variability due to a fluctuating groundwater flow direction varies significantly within the control plane and between the different realizations. Determination of contaminant mass fluxes is also influenced by the temporal variability of the concentration measurement, especially for large spacings of the observation wells. Passive dosimeter sampling is found to be appropriate for evaluating the stationarity of contaminant plumes as well as for estimating average concentrations over time when the plume has fully developed. Representative sampling has to be performed over several periods of groundwater flow fluctuation. For the determination of mass fluxes at heterogeneous sites, however, local fluxes, which may vary considerably along a control plane, have to be accounted for. Here, dosimeter sampling in combination with time integrated local water flux measurements can improve mass flux estimates under dynamic flow conditions.