Challenges and Opportunities for Creating Intelligent Hazard Alerts: The “FloodHippo” Prototype

Disasters evolving from hazards are a persistent and deadly occurrence in the United States. Despite this, hazard alerts have remained spatially vague, temporally imprecise, and lack actionable information. These deficiencies indicate a divide between the status quo and what is possible given modern environmental models, geographic information systems (GIS), and smartphone capabilities. This work describes an alternative, prototype system, “FloodHippo,” which integrates operational model outputs, cloud‐based GIS, and expanded communication channels to provide personal and interactive disaster alerts for floods. The precepts and methods underpinning FloodHippo apply equally to other disasters that evolve over space and time, presenting the opportunity for a more intelligent disaster response system. The development of such a system would not only minimize current shortcomings in disaster alerts but also improve resilience through individual action, along with community, academic, and federal cooperation.     

Establishing a Regional Monitoring Strategy: The Pacific Northwest Forest Plan

adaptive monitoring design. Adaptive monitoring design is an iterative process that refines the specifications for monitoring over time as a result of experience in implementing a monitoring program, assessing results, and interacting with users. An adaptive design therefore facilitates ecosystem management. We also discuss lessons of temporal and spatial scales raised by the consideration of a design for ecosystem management. Three additional issues—integration of information from different sources, institutional infrastructure, and the roles of individuals working in an interagency setting—are also identified, but not developed in detail.     

RESEARCH: Comparison of Temporal Trends in Ambient and Compliance Trace Element and PCB Data in Pool 2 of the Mississippi River, USA, 1985–1995

6+ ), copper (Cu), lead (Pb), mercury (Hg), nickel (Ni), selenium (Se), zinc (Zn), and polychlorinated biphenyls (PCBs). Water-column, bed-sediment, and fish-tissue (fillets) data collected by five government agencies comprised the ambient data set; effluent data from five registered facilities comprised the compliance data set. The nonparametric Mann-Kendall trend test indicated that 33% of temporal trends in all data were statistically significant (P < 0.05). Possible reasons for this were low sample sizes, and a high percentage of samples below the analytical detection limit. Trends in compliance data were more distinct; most trace elements decreased significantly, probably due to improvements in wastewater treatment. Seven trace elements (Cr, Cd, Cu, Pb, Hg, Ni, and Zn) had statistically significant decreases in wastewater and portions of either or both ambient water and bed sediment. No trends were found in fish tissue. Inconsistency in trends between ambient and compliance data were often found for individual constituents, making overall similarity between the data sets difficult to determine. Logistical differences in monitoring programs, such as varying field and laboratory methods among agencies, made it difficult to assess ambient temporal trends.     

POTENTIAL EFFECTS OF CLIMATE CHANGE ON AGRICULTURAL WATER USE IN THE SOUTHEAST U.S.1

ABSTRACT: Climate change has the potential to have dramatic effects on the agricultural sector nationally and internationally as documented in many research papers. This paper reports on research that was focused on a specific crop growing area to demonstrate how farm managers might respond to climate-induced yield changes and the implications of these responses for agricultural water use. The Hadley model was used to generate climate scenarios for important agricultural areas of Georgia in 2030 and 2090. Linked crop response models indicated generally positive yield changes, as increased temperatures were associated with increased precipitation and CO2. Using a farm management model, differences in climate-induced yield impacts among crops led to changes in crop mix and associated water use; non-irrigated cropland received greater benefit since irrigated land was already receiving adequate moisture. Model results suggest that farm managers will increase cropping intensity by decreasing fallowing and increasing double cropping; corn acreage decreased dramatically, peanuts decreased moderately and cotton and winter wheat increased. Water use on currently irrigated cropland fell. The potential for increased water use through conversion of agriculturally important, but currently non-irrigated, growing areas is substantial.     

Unexpected high PCB and total DDT levels in the breeding population of red kite (Milvus milvus) from Doñana National Park, south-western Spain

This study provides information on the current status of contamination by organochlorines (DDTs, PCBs, PCDDs and PCDFs) in the declining red kite (Milvus milvus L.) population breeding in the Do?ana National Park (DNP), south-western Spain. Analyses were performed in addled eggs collected between 1999 and 2001. DDE concentrations ranged from 0.1 to 33.5 microg/g ww, representing more than 86% of the total DDTs. Of the samples studied, 50% showed DDE levels above those associated with reproductive impairment in other raptor species. Concentrations of ortho PCBs (average 36.8 microg/g ww+/-37.7) in 50% of the eggs were much higher than levels reported to cause reduced hatching success, embryo mortality, and deformities in birds (>20 microg/g ww). It is remarkable that average ortho PCB and DDE concentrations showed an increase of one order of magnitude compared to previous data for the species during the 80s. Total PCDD/Fs showed levels in the low pg/g range (7.2-42 pg/g ww), having PCDDs and PCDFs similar contributions in most samples. Total mean TEQs were 238 pg/g (ww), being the range 7.02-667 pg/g (ww). Spatial variation within DNP was observed for PCBs, DDTs, as well as for TEQs. Since some eggs exceeded the NOEL (67%) and LOEL (33%) reported for other raptor species, we would expect the red kite to experience detrimental effects to dioxin-like toxicity. Our results suggest that organochlorine contaminants should be regarded as an element of concern in the population under study, in addition to other conservation problems already reported. Further investigations should be undertaken to identify potential sources of these chemicals in DNP, and to find out if organochlorine contamination is present in other predator species in the area, as well as their potential health effects on individuals and/or populations.     

A uniform fish consumption advisory protocol for the Ohio River

ORSANCO and the six Ohio River main stem states have been working to align states' fish consumption advisories (FCAs) to enhance the value of advice issued to the public. To achieve this goal, ORSANCO worked closely with a panel consisting of state and USEPA representatives. The result of this effort is the Ohio River Fish Consumption Advisory Protocol (ORFCAP). The ORFCAP represents a single set of variables agreed upon by the panel that allows for a standardized protocol to create advisory thresholds to which states can defer to issue consumption advice for the Ohio River. The ORFCAP identifies ORSANCO as a clearinghouse for data which will be distributed to the panel for decision making. Other components include identifying primary contaminants of concern (PCBs and mercury) and dividing the river into four reporting units. The protocol was developed to issue FCAs for the protection of sensitive populations using five advisory groupings for PCBs and four for mercury. Specific variables used in the calculation of advisory thresholds such as health protection values, cooking reductions, average meal sizes, etc., were selected by the panel. Lastly, the protocol calls for FCA decisions to be based on analysis of the most recent 10?years of data for each species in each reporting unit to determine size class needs and advisory groupings. Upon pending implementation of the protocol by the main stem states, these decisions will be made annually through a series of discussions involving ORSANCO, the panel, and other appropriate state personnel.     

Assessing possible visitor-use impacts on water quality in Yosemite National Park, California

There is concern that visitor-use associated activities, such as bathing, dish washing, wastewater production, and stock animal use near lakes and streams, could cause degradation of water quality in Yosemite National Park. A study was conducted during 2004-2007 to assess patterns in nutrient and Escherichia coli (E. coli) concentrations in the Merced and Tuolumne Rivers and characterize natural background concentrations of nutrients in the park. Results indicated that nutrient and E. coli concentrations were low, even compared to other undeveloped sites in the United States. A multiple linear regression approach was used to model natural background concentrations of nutrients, with basin characteristics as explanatory variables. Modeled nitrogen concentrations increased with elevation, and modeled phosphorus concentrations increased with basin size. Observed concentrations (±uncertainty) were compared to modeled concentrations (±uncertainty) to identify sites that might be impacted by point sources of nutrients, as indicated by large model residuals. Statistically significant differences in observed and modeled concentrations were observed at only a few locations, indicating that most sites were representative of natural background conditions. The empirical modeling approach used in this study can be used to estimate natural background conditions at any point along a study reach in areas minimally impacted by development, and may be useful for setting water-quality standards in many national parks.     

Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange

Net ecosystem CO₂ exchange (NEE) is typically measured directly by eddy covariance towers or is estimated by ecosystem process models, yet comparisons between the data obtained by these two methods can show poor correspondence. There are three potential explanations for this discrepancy. First, estimates of NEE as measured by the eddy-covariance technique are laden with uncertainty and can potentially provide a poor baseline for models to be tested against. Second, there could be fundamental problems in model structure that prevent an accurate simulation of NEE. Third, ecosystem process models are dependent on ecophysiological parameter sets derived from field measurements in which a single parameter for a given species can vary considerably. The latter problem suggests that with such broad variation among multiple inputs, any ecosystem modeling scheme must account for the possibility that many combinations of apparently feasible parameter values might not allow the model to emulate the observed NEE dynamics of a terrestrial ecosystem, as well as the possibility that there may be many parameter sets within a particular model structure that can successfully reproduce the observed data. We examined the extent to which these three issues influence estimates of NEE in a widely used ecosystem process model, Biome-BGC, by adapting the generalized likelihood uncertainty estimation (GLUE) methodology. This procedure involved 400,000 model runs, each with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in estimates of NEE that were compared to daily NEE data from young and mature Ponderosa pine stands at Metolius, Oregon. Of the 400,000 simulations run with different parameter sets for each age class (800,000 total), over 99% of the simulations underestimated the magnitude of net ecosystem CO₂ exchange, with only 4.07% and 0.045% of all simulations providing satisfactory simulations of the field data for the young and mature stands, even when uncertainties in eddy-covariance measurements are accounted for. Results indicate fundamental shortcomings in the ability of this model to produce realistic carbon flux data over the course of forest development, and we suspect that much of the mismatch derives from an inability to realistically model ecosystem respiration. However, difficulties in estimating historic climate data are also a cause for model-data mismatch, particularly in a highly ecotonal region such as central Oregon. This latter difficulty may be less prevalent in other ecosystems, but it nonetheless highlights a challenge in trying to develop a dynamic representation of the terrestrial biosphere.