@article{collins_david_riggs_allen_pavelsky_lin_pan_yamazaki_meentemeyer_sanchez_2024, title={Global patterns in river water storage dependent on residence time}, url={https://doi.org/10.1038/s41561-024-01421-5}, DOI={10.1038/s41561-024-01421-5}, abstractNote={Abstract Accurate assessment of global river flows and stores is critical for informing water management practices, but current estimates of global river flows exhibit substantial spread and estimates of river stores remain sparse. Estimates of river flows and stores are hampered by uncertainties in land runoff, an unobserved quantity that provides water input to rivers. Here we leverage global river flow observations and an ensemble of land surface models to generate a globally gauge-corrected monthly river flow and storage dataset. We estimate a global river storage mean (± monthly variability) of 2,246 ± 505 km 3 and a global continental flow of 37,411 ± 7,816 km 3 yr −1 . Our global river water storage time series demonstrates that flow wave residence time is a fundamental driver that can double or halve river water stores and their variability. We also reconcile the wide range in previous estimates of monthly variability in global river flows. We identify previously underappreciated freshwater sources to the ocean from the Maritime Continent (Indonesia, Malaysia and Papua New Guinea) amounting to 1.6 times the Congo River and illustrate our capability of detecting severe anthropogenic water withdrawals.}, journal={Nature Geoscience}, author={Collins, Elyssa L. and David, Cédric H. and Riggs, Ryan and Allen, George H. and Pavelsky, Tamlin M. and Lin, Peirong and Pan, Ming and Yamazaki, Dai and Meentemeyer, Ross K. and Sanchez, Georgina M.}, year={2024}, month={Apr} }
 @article{gay_martin_v. caldwell_emanuel_sanchez_suttles_2023, title={Riparian buffers increase future baseflow and reduce peakflows in a developing watershed}, volume={862}, ISSN={["1879-1026"]}, url={http://dx.doi.org/10.1016/j.scitotenv.2022.160834}, DOI={10.1016/j.scitotenv.2022.160834}, abstractNote={Land conversion and climate change are stressing freshwater resources. Riparian areas, streamside vegetation/forest land, are critical for regulating hydrologic processes and riparian buffers are used as adaptive management strategies for mitigating land conversion effects. However, our ability to anticipate the efficacy of current and alternative riparian buffers under changing conditions remains limited. To address this information gap, we simulated hydrologic responses for different levels of buffer protection under a future scenario of land/climate change through the year 2060. We used the Soil and Water Assessment Tool (SWAT) to project future streamflow in the Upper Neuse River watershed in North Carolina, USA. We tested the capacity of riparian buffers to mitigate the effects of future land use and climate change on daily mean streamflow under three buffer treatments: present buffer widths and fully forested 15 m and 30 m buffers throughout the basin. The treatments were tested using a combination of a future climate change scenario and landcover projections that indicated a doubling of low-intensity development between 2017 and 2060. In areas with >50 % development, the 30 m buffers were particularly effective at increasing average daily streamflow during the lowest flow events by 4 % and decreasing flow during highest flow events by 3 % compared to no buffer protection. In areas between 20 and 50 % development, both 15 m and 30 m buffers reduced low flow by 8 % with minimal effects on high flow. Results indicate that standardized buffers might be more effective at a local scale with further research needing to focus on strategic buffer placement at the watershed scale. These findings highlight a novel approach for integrating buffers into hydrologic modeling and potential for improved methodology. Understanding the effects of riparian buffers on streamflow is crucial given the pressing need to develop innovative strategies that promote the conservation of invaluable ecosystem services.}, journal={SCIENCE OF THE TOTAL ENVIRONMENT}, publisher={Elsevier BV}, author={Gay, Elly T. and Martin, Katherine L. and V. Caldwell, Peter and Emanuel, Ryan E. and Sanchez, Georgina M. and Suttles, Kelly M.}, year={2023}, month={Mar} }
 @book{gurley_garcía_pfeifle_sanchez_2023, title={Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65}, url={https://doi.org/10.3133/sir20235036}, DOI={10.3133/sir20235036}, abstractNote={First posted June 21, 2023 For additional information, contact: For more information about this publication, contactProgram CoordinatorU.S. Geological SurveyWater Availability and Use Science ProgramNational Water Quality ProgramEmail: wausp-info@usgs.govFor additional information, visithttps://www.usgs.gov/programs/national-water-quality-programContact Pubs Warehouse Water resources in the coastal region of North Carolina and South Carolina (Coastal Carolinas) are currently under stress from competing ecological and societal needs. Projected changes in climate and population are expected to place even more stress on water resources in the region. The Coastal Carolinas Focus Area Study was initiated by the U.S. Geological Survey Water Availability and Use Science Program's National Water Census to investigate these stressors and their effects on water resources for the Coastal Carolinas. As part of that study, the Soil and Water Assessment Tool (SWAT) model was used to investigate future streamflow and irrigation demand under six scenarios for the Cape Fear and Pee Dee River Basins, which flow through the Coastal Carolinas and into the Atlantic Ocean.For each river basin, historical (2000 through 2014) Soil and Water Assessment Tool models were minimally calibrated, and future (2055 through 2065) scenario models were developed based on three alternative global climate models, two alternative urban growth projections, and water-use projections that correspond to each global climate model and urban growth projection pair. The river basins were delineated into 2,928 and 5,678 subbasins for the Cape Fear and Pee Dee, respectively, each approximately 2.6 square miles (mi2) in size. The best available water-use and wastewater discharge data were used for historical model calibration. The models simulated monthly mean streamflow with median Nash-Sutcliffe efficiency values of 0.53 (n = 36) and 0.61 (n = 33) in the Cape Fear and Pee Dee River Basins, respectively. Average percent bias was −4.8 percent for the Cape Fear River Basin and −1.2 percent for the Pee Dee River Basin. Catchments for streamgages chosen for model calibration that were small (less than 100 mi2) to medium (100–1,000 mi2) in area tended to perform better than larger catchments (greater than 1,000 mi2).Historical models were used to develop future model scenarios by replacing historical weather, land-use, and water-use input datasets with projected datasets. One small, gaged catchment was selected to illustrate how the models can be used to evaluate the relative differences in simulated streamflow resulting from alternative global climate models and urban growth projections. For the selected catchment, future climate projections had a much greater influence on simulated streamflow than urban growth projections. Simulated cumulative monthly mean streamflow results for this catchment differed by 26 percent under alternative global climate models and differed by 2.4 percent under alternative urban growth projections.Irrigation demand was modeled for subbasins with cropland. Simulated differences in irrigation demand were more pronounced and widespread across the model domain under the alternative future climate scenarios compared to alternative urban growth scenarios.The calibrated and future scenario models have the capability to run on a daily time step and simulate streamflow and irrigation demand for thousands of small subbasins in the Cape Fear and Pee Dee River Basins. The models and underlying datasets enable future analyses for large and small areas within the basins.}, author={Gurley, Laura N. and García, Ana María and Pfeifle, Cassandra A. and Sanchez, Georgina M.}, year={2023} }
 @article{sanchez_petrasova_skrip_collins_lawrimore_vogler_terando_vukomanovic_mitasova_meentemeyer_2023, title={Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk}, volume={13}, ISSN={["2045-2322"]}, url={http://dx.doi.org/10.1038/s41598-023-46195-9}, DOI={10.1038/s41598-023-46195-9}, abstractNote={Abstract}, number={1}, journal={SCIENTIFIC REPORTS}, publisher={Springer Science and Business Media LLC}, author={Sanchez, Georgina M. and Petrasova, Anna and Skrip, Megan M. and Collins, Elyssa L. and Lawrimore, Margaret A. and Vogler, John B. and Terando, Adam and Vukomanovic, Jelena and Mitasova, Helena and Meentemeyer, Ross K.}, year={2023}, month={Nov} }
 @book{garcía_eaton_sanchez_keisman_ullman_blackwell_2023, title={Value-aligned planning objectives for restoring North Carolina aquatic resources}, url={https://doi.org/10.3133/ofr20221058}, DOI={10.3133/ofr20221058}, abstractNote={First posted April 11, 2023 For additional information, contact: South Atlantic Water Science CenterU.S. Geological Survey3916 Sunset Ridge RoadRaleigh, NC 27607Contact Pubs Warehouse Rapid population growth and development in the southeastern United States have resulted in substantial impairment to freshwater aquatic ecosystems. National or regional restoration policies strive to address impaired ecosystems but can suffer from inconsistent and opaque processes. The Clean Water Act, for example, establishes reallocation mechanisms to transfer ecosystem services from sites of disturbance to compensation sites to offset aquatic resource functions that are unavoidably lost through land development. However, planning for the prioritization of compensatory mitigation areas is often hampered by unstructured decision-making processes that are narrowly framed because they are not co-produced with stakeholders affected by, or having an interest in, the impacts and mitigation. This summary report represents the collaborative efforts of the U.S. Geological Survey and the North Carolina Department of Environmental Quality, Division of Mitigation Services, to co-develop an applied decision framework following the principles of structured decision-making for prioritizing watershed catchments by their potential for realizing a range of beneficial outcomes from future mitigation projects. The framework focuses on supporting the State’s nationally recognized stream and wetlands compensatory mitigation program by clarifying a discrete decision problem and specifying agency and stakeholder values to formulate fundamental and means objectives for prioritizing restoration sites. The co-development of this decision framework resulted in a number of useful insights from the perspective of the decision maker, including recognition (1) that the problem is a multi-objective decision driven by values beyond restoring lost functionality of ecosystems (that is, biogeophysical goals), (2) that the decision comprises a linked and sequential planning-to-implementation process, and (3) that future risk associated with land-use and climate change must be considered. The outcomes of this collaboration can serve as a systematic and transparent framework to prioritize a wide range of restoration, conservation, and resource-allocation activities in similar environmental contexts across the Nation.}, author={García, Ana María and Eaton, Mitchell and Sanchez, Georgina M. and Keisman, Jennifer L. and Ullman, Kirsten and Blackwell, James}, year={2023} }
 @article{sanchez_eaton_garcia_keisman_ullman_blackwell_meentemeyer_2022, title={Integrating principles and tools of decision science into value-driven watershed planning for compensatory mitigation}, volume={12}, ISSN={["1939-5582"]}, url={https://doi.org/10.1002/eap.2766}, DOI={10.1002/eap.2766}, abstractNote={Abstract}, journal={ECOLOGICAL APPLICATIONS}, author={Sanchez, Georgina M. M. and Eaton, Mitchell J. J. and Garcia, Ana M. M. and Keisman, Jennifer and Ullman, Kirsten and Blackwell, James and Meentemeyer, Ross K. K.}, year={2022}, month={Dec} }
 @article{collins_sanchez_terando_stillwell_mitasova_sebastian_meentemeyer_2022, title={Predicting flood damage probability across the conterminous United States}, volume={17}, ISSN={["1748-9326"]}, url={https://doi.org/10.1088/1748-9326/ac4f0f}, DOI={10.1088/1748-9326/ac4f0f}, abstractNote={Abstract}, number={3}, journal={ENVIRONMENTAL RESEARCH LETTERS}, author={Collins, Elyssa L. and Sanchez, Georgina M. and Terando, Adam and Stillwell, Charles C. and Mitasova, Helena and Sebastian, Antonia and Meentemeyer, Ross K.}, year={2022}, month={Mar} }
 @misc{matallana-ramirez_whetten_sanchez_payn_2021, title={Breeding for Climate Change Resilience: A Case Study of Loblolly Pine (Pinus taeda L.) in North America}, volume={12}, ISSN={["1664-462X"]}, url={https://doi.org/10.3389/fpls.2021.606908}, DOI={10.3389/fpls.2021.606908}, abstractNote={Earth’s atmosphere is warming and the effects of climate change are becoming evident. A key observation is that both the average levels and the variability of temperature and precipitation are changing. Information and data from new technologies are developing in parallel to provide multidisciplinary opportunities to address and overcome the consequences of these changes in forest ecosystems. Changes in temperature and water availability impose multidimensional environmental constraints that trigger changes from the molecular to the forest stand level. These can represent a threat for the normal development of the tree from early seedling recruitment to adulthood both through direct mortality, and by increasing susceptibility to pathogens, insect attack, and fire damage. This review summarizes the strengths and shortcomings of previous work in the areas of genetic variation related to cold and drought stress in forest species with particular emphasis on loblolly pine (Pinus taedaL.), the most-planted tree species in North America. We describe and discuss the implementation of management and breeding strategies to increase resilience and adaptation, and discuss how new technologies in the areas of engineering and genomics are shaping the future of phenotype-genotype studies. Lessons learned from the study of species important in intensively-managed forest ecosystems may also prove to be of value in helping less-intensively managed forest ecosystems adapt to climate change, thereby increasing the sustainability and resilience of forestlands for the future.}, journal={FRONTIERS IN PLANT SCIENCE}, author={Matallana-Ramirez, Lilian P. and Whetten, Ross W. and Sanchez, Georgina M. and Payn, Kitt G.}, year={2021}, month={Apr} }
 @article{smart_vukomanovic_sills_sanchez_2021, title={Cultural ecosystem services caught in a 'coastal squeeze' between sea level rise and urban expansion}, volume={66}, ISSN={["1872-9495"]}, url={https://doi.org/10.1016/j.gloenvcha.2020.102209}, DOI={10.1016/j.gloenvcha.2020.102209}, abstractNote={Sea level rise and urbanization exert complex synergistic pressures on the provision of ecosystem services (ES) in coastal regions. Anticipating when and where both biophysical and cultural ES will be affected by these two types of coastal environmental change is critical for sustainable land-use planning and management. Biophysical (provisioning and regulating) services can be mapped using secondary data. We demonstrate an approach to mapping cultural ES by engaging stakeholders in iterative participatory mapping of personally and communally valuable cultural ES. We identify hotspots where highly valued cultural ES and high values for biophysical ES co-occur and generate spatially-explicit projections of sea level rise and urban expansion through 2060 to quantify impacts of the ‘coastal squeeze’ on ES. We study Johns Island, South Carolina, USA as an example of a vulnerable community in a low-lying region experiencing both rising water levels and a rapid influx of new residents and development. Our projections of environmental change through 2060 indicate that on Johns Island, cultural ES face disproportionately greater risk of decline than biophysical ES, with almost three quarters of the island’s cultural ES affected. We find that hotspots for cultural ES, such as community heritage sites and scenic vistas of oak-lined roads and marshes, rarely co-occur (only 3% area) with biophysical ES such as high values of carbon sequestration and agricultural production. This confirms the importance of engaging with local stakeholders to map cultural ES and puts them on a more level playing field with biophysical ES in decision-making contexts. Projected declines and limited overlap between biophysical and cultural ES highlight the need for tighter coordination between conservation and community planning, and for including locally valued cultural ES in assessments of threats posed by the ‘coastal squeeze’ of sea level rise and urban expansion.}, journal={GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS}, publisher={Elsevier BV}, author={Smart, Lindsey S. and Vukomanovic, Jelena and Sills, Erin O. and Sanchez, Georgina}, year={2021}, month={Jan} }
 @article{sanchez_terando_smith_garcía_wagner_meentemeyer_2020, title={Forecasting water demand across a rapidly urbanizing region}, volume={730}, url={https://doi.org/10.1016/j.scitotenv.2020.139050}, DOI={10.1016/j.scitotenv.2020.139050}, abstractNote={Urban growth and climate change together complicate planning efforts meant to adapt to increasingly scarce water supplies. Several studies have independently examined the impacts of urban planning and climate change on water demand, but little attention has been given to their combined impact. Here we forecast urban water demand using a Geographically Weighted Regression model informed by socio-economic, environmental and landscape pattern metrics. The purpose of our study is to evaluate how future scenarios of population densities and climate warming will jointly affect water demand across two rapidly growing U.S. states (North Carolina and South Carolina). Our forecasts indicate that regional water demand by 2065 will increase by 37%–383% relative to the baseline in 2010, across all scenarios of change. Our results show future water demand will increase under rising temperatures, but could be ameliorated by policies that promote higher density development and urban infill. These water-efficient land use policies show a 5% regional reduction in water demand and up to 25% reduction locally for counties with the highest expected population growth by 2065. For rural counties experiencing depopulation, the land use policies we considered are insufficient to significantly reduce water demand. For expanding communities seeking to increase their adaptive capacity to changing socio-environmental conditions, our framework can assist in developing sustainable solutions.}, journal={Science of The Total Environment}, publisher={Elsevier BV}, author={Sanchez, Georgina M. and Terando, Adam and Smith, Jordan W. and García, Ana M. and Wagner, Chad R. and Meentemeyer, Ross K.}, year={2020}, month={Aug}, pages={139050} }
 @article{li_sun_caldwell_cohen_fang_zhang_oudin_sanchez_meentemeyer_2020, title={Impacts of Urbanization on Watershed Water Balances Across the Conterminous United States}, url={https://doi.org/10.1029/2019WR026574}, DOI={10.1029/2019WR026574}, abstractNote={Abstract}, journal={Water Resources Research}, author={Li, Cheng and Sun, Ge and Caldwell, Peter V. and Cohen, Erika and Fang, Yuan and Zhang, Yindan and Oudin, Ludovic and Sanchez, Georgina M. and Meentemeyer, Ross K.}, year={2020}, month={Jul} }
 @article{spatiotemporal patterns and drivers of soil contamination with heavy metals during an intensive urbanization period (1989–2018) in southern china_2020, url={http://dx.doi.org/10.1016/j.envpol.2020.114075}, DOI={10.1016/j.envpol.2020.114075}, abstractNote={This three-decade long study was conducted in the Pearl River Delta (PRD), a rapidly urbanizing region in southern China. Extensive soil samples for a diverse land uses were collected in 1989 (113), 2005 (1384), 2009 (521), and 2018 (421) for heavy metals of As, Cr, Cd, Cu, Hg, Ni, Pb and Zn. Multiple pollution indices and Structural Equation Models (SEMs) were used in attribution analysis and comprehensive assessments. Data showed that majority of the sampling sites was contaminated by one or more heavy metals, but pollutant concentrations had not reached levels of concerns for food security or human health. There was an increasing trend in heavy metal contamination over time and the variations of soil contamination were site-, time- and pollutant-dependent. Areas with high concentrations of heavy metals overlapped with highly industrialized and populated areas in western part of the study region. A dozen SEMs path analyses were used to compare the relative influences of key environmental factors on soil contamination across space and time. The high or elevated soil contaminations by As, Cr, Ni, Cu and Zn were primarily affected by soil properties during the study period, except 1989–2005, followed by land use patterns. Parent materials had a significant effect on elevated soil contamination of Cd, Cr, Ni, Pb and overall soil pollution during 1989–2005. We hypothesized that other factors not considered in the present study, such as atmospheric deposition, sewage irrigation, and agrochemical uses, may be also important to explain the variability of soil contamination. This study implied that strategies to improve soil physiochemical properties and optimize landscape structures are viable methods to mitigate soil contamination. Future studies should monitor pollutant sources identified by this study to fully understand the causes of heavy metal contamination in rapidly industrialized regions in southern China.}, journal={Environmental Pollution}, year={2020}, month={May} }
 @article{koch_dorning_van berkel_beck_sanchez_shashidharan_smart_zhang_smith_meentemeyer_et al._2019, title={Modeling landowner interactions and development patterns at the urban fringe}, volume={182}, ISSN={["1872-6062"]}, url={http://dx.doi.org/10.1016/j.landurbplan.2018.09.023}, DOI={10.1016/j.landurbplan.2018.09.023}, abstractNote={Population growth and unrestricted development policies are driving low-density urbanization and fragmentation of peri-urban landscapes across North America. While private individuals own most undeveloped land, little is known about how their decision-making processes shape landscape-scale patterns of urbanization over time. We introduce a hybrid agent-based modeling (ABM) – cellular automata (CA) modeling approach, developed for analyzing dynamic feedbacks between landowners’ decisions to sell their land for development, and resulting patterns of landscape fragmentation. Our modeling approach builds on existing conceptual frameworks in land systems modeling by integrating an ABM into an established grid-based land-change model – FUTURES. The decision-making process within the ABM involves landowner agents whose decision to sell their land to developers is a function of heterogeneous preferences and peer-influences (i.e., spatial neighborhood relationships). Simulating landowners’ decision to sell allows an operational link between the ABM and the CA module. To test our hybrid ABM-CA approach, we used empirical data for a rapidly growing region in North Carolina for parameterization. We conducted a sensitivity analysis focusing on the two most relevant parameters—spatial actor distribution and peer-influence intensity—and evaluated the dynamic behavior of the model simulations. The simulation results indicate different peer-influence intensities lead to variable landscape fragmentation patterns, suggesting patterns of spatial interaction among landowners indirectly affect landscape-scale patterns of urbanization and the fragmentation of undeveloped forest and farmland.}, journal={LANDSCAPE AND URBAN PLANNING}, author={Koch, Jennifer and Dorning, Monica A. and Van Berkel, Derek B. and Beck, Scott M. and Sanchez, Georgina M. and Shashidharan, Ashwin and Smart, Lindsey S. and Zhang, Qiang and Smith, Jordan W. and Meentemeyer, Ross K. and et al.}, year={2019}, month={Feb}, pages={101–113} }
 @article{bhattachan_jurjonas_moody_morris_sanchez_smart_taillie_emanuel_seekamp_2018, title={Sea level rise impacts on rural coastal social-ecological systems and the implications for decision making}, volume={90}, ISSN={1462-9011}, url={http://dx.doi.org/10.1016/j.envsci.2018.10.006}, DOI={10.1016/j.envsci.2018.10.006}, abstractNote={Many rural coastal regions are distinctly vulnerable to sea level rise because of their remoteness, isolation from central planning agencies, and poverty. To better plan for future sea level changes in these regions, an interdisciplinary approach to assess the social and environmental impacts of sea level rise and their dynamic feedbacks is important. In this paper, we use a socio-ecological system framework to investigate sea level rise impacts to the Albemarle-Pamlico Peninsula, a rural, low-lying coastal region in eastern North Carolina. Specifically, we show that 42% of the region could be inundated and property losses of up to US $14 billion could be incurred with 100 cm of sea level rise. We also synthesize the impacts of sea level rise on the region’s social-ecological system and present strategies to strengthen the adaptive capacity of the ecosystem, markets and communities. We conclude with a discussion on the differing climate change risk perceptions amongst the stakeholders as well as implications for decision-making. Sea level rise will continue to threaten the functioning of this social-ecological system of rural, low-lying coastal communities. A socio-ecological system framework provides a lens through which the impacts of sea level rise can be evaluated for rural, low-lying coastal communities. The framework presented here necessitates interdisciplinary research and highlights the importance of mutual learning amongst stakeholders in other rural coastal regions.}, journal={Environmental Science & Policy}, publisher={Elsevier BV}, author={Bhattachan, A. and Jurjonas, M.D. and Moody, A.C. and Morris, P.R. and Sanchez, G.M. and Smart, L.S. and Taillie, P.J. and Emanuel, R.E. and Seekamp, E.L.}, year={2018}, month={Dec}, pages={122–134} }
 @article{sanchez_smith_terando_sun_meentemeyer_2018, title={Spatial Patterns of Development Drive Water Use}, volume={54}, ISSN={["1944-7973"]}, url={https://doi.org/10.1002/2017WR021730}, DOI={10.1002/2017wr021730}, abstractNote={Abstract}, number={3}, journal={WATER RESOURCES RESEARCH}, publisher={American Geophysical Union (AGU)}, author={Sanchez, G. M. and Smith, J. W. and Terando, A. and Sun, G. and Meentemeyer, R. K.}, year={2018}, month={Mar}, pages={1633–1649} }
 @article{linking watershed-scale stream health and socioeconomic indicators with spatial clustering and structural equation modeling_2015, url={http://dx.doi.org/10.1016/j.envsoft.2015.04.012}, DOI={10.1016/j.envsoft.2015.04.012}, abstractNote={In this study, spatial clustering techniques were used in combination with Structural Equation Modeling (SEM) to characterize the relationships between in-stream health indicators and socioeconomic measures of communities. The study area is the Saginaw River Watershed in Michigan. Four measures of stream health were considered: the Index of Biological Integrity, Hilsenhoff Biotic Index, Family Index of Biological Integrity, and number of Ephemeroptera, Plecoptera, and Trichoptera taxa. The stream health indicators were predicted using nine socioeconomic variables that capture vulnerability in population. The results of spatial clustering showed that incorporating clustering configuration improves the model prediction. A total of 510 Confirmatory Factor Analysis (CFAs) and 85 multivariate regression models were developed for each spatial cluster within the watershed and compared with the model performance without spatial clustering (at the watershed level). In general, watershed level CFAs outperformed cluster level CFAs, while the reverse was true for the regression models.}, journal={Environmental Modelling & Software}, year={2015}, month={Aug} }
 @article{development of a socio-ecological environmental justice model for watershed-based management_2014, url={http://dx.doi.org/10.1016/j.jhydrol.2013.08.014}, DOI={10.1016/j.jhydrol.2013.08.014}, abstractNote={The dynamics and relationships between society and nature are complex and difficult to predict. Anthropogenic activities affect the ecological integrity of our natural resources, specifically our streams. Further, it is well-established that the costs of these activities are born unequally by different human communities. This study considered the utility of integrating stream health metrics, based on stream health indicators, with socio-economic measures of communities, to better characterize these effects. This study used a spatial multi-factor model and bivariate mapping to produce a novel assessment for watershed management, identification of vulnerable areas, and allocation of resources. The study area is the Saginaw River watershed located in Michigan. In-stream hydrological and water quality data were used to predict fish and macroinvertebrate measures of stream health. These measures include the Index of Biological Integrity (IBI), Hilsenhoff Biotic Index (HBI), Family IBI, and total number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa. Stream health indicators were then compared to spatially coincident socio-economic data, obtained from the United States Census Bureau (2010), including race, income, education, housing, and population size. Statistical analysis including spatial regression and cluster analysis were used to examine the correlation between vulnerable human populations and environmental conditions. Overall, limited correlation was observed between the socio-economic data and ecological measures of stream health, with the highest being a negative correlation of 0.18 between HBI and the social parameter household size. Clustering was observed in the datasets with urban areas representing a second order clustering effect over the watershed. Regions with the worst stream health and most vulnerable social populations were most commonly located nearby or down-stream to highly populated areas and agricultural lands.}, journal={Journal of Hydrology}, year={2014}, month={Oct} }