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Sustainable land management (SLM) is a leading policy issue in Ethiopia. However, the adoption and continuous use of SLM technologies remain low. This study investigates the interrelationship of adopted SLM technologies and key factors of farmers’ decisions to use SLM technologies in the North Gojjam sub-basin of the Upper Blue Nile. The study was based on the investigation of cross-sectional data obtained from 414 randomly selected rural household heads, focus group discussions, and key informant interviews. Descriptive statistics and Econometric models (i.e., Multivariate Probit and Poisson regression) were used to analyze quantitative data, while a content analysis method was used for qualitative data analysis. Results indicate that at least one type of SLM technology was implemented by 94% of farm households in the North Gojjam sub-basin. The most widely used technologies were chemical fertilizer, soil bund, and animal manure. Most of the adopted SLM technologies complement each other. Farm size, family size, male-headed household, local institutions, perception of soil erosion, livestock size, total income, and extension service increased the adoption probability of most SLM technologies. Plot fragmentation, household age, plot distance, off-farm income, market distance, and perception of good fertile soil discourage the adoption probability of most SLM technologies. To scale up SLM technologies against land degradation, it is important to consider households’ demographic characteristics, the capacity of farm households, and plot-level related factors relevant to the specific SLM technologies being promoted.
Alelgn Ewunetu; Belay Simane; Ermias Teferi; Benjamin F. Zaitchik. Relationships and the Determinants of Sustainable Land Management Technologies in North Gojjam Sub-Basin, Upper Blue Nile, Ethiopia. Sustainability 2021, 13, 6365 .
AMA StyleAlelgn Ewunetu, Belay Simane, Ermias Teferi, Benjamin F. Zaitchik. Relationships and the Determinants of Sustainable Land Management Technologies in North Gojjam Sub-Basin, Upper Blue Nile, Ethiopia. Sustainability. 2021; 13 (11):6365.
Chicago/Turabian StyleAlelgn Ewunetu; Belay Simane; Ermias Teferi; Benjamin F. Zaitchik. 2021. "Relationships and the Determinants of Sustainable Land Management Technologies in North Gojjam Sub-Basin, Upper Blue Nile, Ethiopia." Sustainability 13, no. 11: 6365.
From the heated debates over the airborne transmission of the novel coronavirus to the abrupt Earth system changes caused by the sudden lockdowns, the dire circumstances resulting from the coronavirus disease 2019 (COVID‐19) pandemic have brought the field of GeoHealth to the forefront of visibility in science and policy. The pandemic has inadvertently provided an opportunity to study how human response has impacted the Earth system, how the Earth system may impact the pandemic, and the capacity of GeoHealth to inform real‐time policy. The lessons learned throughout our responses to the COVID‐19 pandemic are shaping the future of GeoHealth.
Morgan E. Gorris; Susan C. Anenberg; Daniel L. Goldberg; Gaige Hunter Kerr; Jennifer D. Stowell; Daniel Tong; Benjamin F. Zaitchik. Shaping the Future of Science: COVID‐19 Highlighting the Importance of GeoHealth. GeoHealth 2021, 5, 1 .
AMA StyleMorgan E. Gorris, Susan C. Anenberg, Daniel L. Goldberg, Gaige Hunter Kerr, Jennifer D. Stowell, Daniel Tong, Benjamin F. Zaitchik. Shaping the Future of Science: COVID‐19 Highlighting the Importance of GeoHealth. GeoHealth. 2021; 5 (5):1.
Chicago/Turabian StyleMorgan E. Gorris; Susan C. Anenberg; Daniel L. Goldberg; Gaige Hunter Kerr; Jennifer D. Stowell; Daniel Tong; Benjamin F. Zaitchik. 2021. "Shaping the Future of Science: COVID‐19 Highlighting the Importance of GeoHealth." GeoHealth 5, no. 5: 1.
The coupling of rapid warming and wetland degradation on the Tibetan Plateau has motivated studies of climate influence on wetland change in the region. These studies typically examine large, topographically homogeneous regions, whereas conservation efforts sometimes require fine-grained information in rugged terrain. This study addresses topographically constrained wetlands on the Eastern Tibetan, where herders report significant wetland degradation. We used Landsat images to examine changes in wetland areas and Sentinel-1 SAR images to investigate water level and vegetation structure. We also analyzed trends in precipitation, growing season length, and reference evapotranspiration in weather station records. Snow cover and the vegetation growing season were quantified using MODIS observations. We analyzed estimates of actual evapotranspiration using the Atmosphere-Land Exchange Inverse model (ALEXI) and the Simplified Surface Energy Balance model (SSEBop). Satellite-informed analyses failed to confirm herders’ accounts of reduced wetland function, as no coherent trends were found in wetland area, water content, or vegetation structure. An analysis of meteorological records did indicate a warming-induced increase in reference evapotranspiration, and both meteorological records and satellites suggest that the growing season had lengthened, potentially increasing water demand and driving wetland change. The discrepancies between the satellite data and local observations pointed to temporal, spatial, and epistemological gaps in combining scientific data with empirical evidence in understanding wetland change on the Tibetan Plateau.
Jianing Fang; Benjamin Zaitchik. Challenges in Reconciling Satellite-Based and Locally Reported Estimates of Wetland Change: A Case of Topographically Constrained Wetlands on the Eastern Tibetan Plateau. Remote Sensing 2021, 13, 1484 .
AMA StyleJianing Fang, Benjamin Zaitchik. Challenges in Reconciling Satellite-Based and Locally Reported Estimates of Wetland Change: A Case of Topographically Constrained Wetlands on the Eastern Tibetan Plateau. Remote Sensing. 2021; 13 (8):1484.
Chicago/Turabian StyleJianing Fang; Benjamin Zaitchik. 2021. "Challenges in Reconciling Satellite-Based and Locally Reported Estimates of Wetland Change: A Case of Topographically Constrained Wetlands on the Eastern Tibetan Plateau." Remote Sensing 13, no. 8: 1484.
The COVID-19 pandemic has become one of the great historical events of the modern era, presenting a generational challenge to the world. Questions about the role of weather on SARS-CoV-2 transmission led to the gathering of scientists at an online event, the “International Virtual Symposium on Climatological, Meteorological and Environmental factors in the COVID-19 pandemic,” convened on 4–6 August 2020 under the auspices of the World Meteorological Organization. This collection of papers arise from the Symposium.
Neville Sweijd; Benjamin F. Zaitchik. The 2020 WMO symposium on climatological, meteorological and environmental factors in the COVID-19 pandemic: A special issue from symposium presentations. One Health 2021, 12, 100243 -100243.
AMA StyleNeville Sweijd, Benjamin F. Zaitchik. The 2020 WMO symposium on climatological, meteorological and environmental factors in the COVID-19 pandemic: A special issue from symposium presentations. One Health. 2021; 12 ():100243-100243.
Chicago/Turabian StyleNeville Sweijd; Benjamin F. Zaitchik. 2021. "The 2020 WMO symposium on climatological, meteorological and environmental factors in the COVID-19 pandemic: A special issue from symposium presentations." One Health 12, no. : 100243-100243.
Climate variability is an important driver of irrigation water use in many regions. Efforts to anticipate climate change impacts on future water availability can benefit from understanding how irrigation water demand has responded to these drivers to date. Here we apply satellite‐derived data, meteorological reanalysis, an advanced land surface model, and available state‐level reports to quantify irrigation demand sensitivities to temperature and precipitation across the Contiguous United States, for the period of 2002‐2017. As expected, strong negative correlations are found between precipitation and irrigation withdrawals, both simulated and reported. Temperature sensitivities, however, vary by region and season, as do the interactive effects of temperature and precipitation on irrigation. Climate‐induced irrigation variability is largest in transitional climate zones. These transitional zones are generally separate from the regions where rates of irrigation withdrawals are greatest, such that climate‐induced variability in irrigation demand represents a water resource consideration that is distinct from chronic over‐pumping.This article is protected by copyright. All rights reserved.
Wanshu Nie; Benjamin F. Zaitchik; Matthew Rodell; Sujay V. Kumar; Kristi R. Arsenault; Hamada S. Badr. Irrigation Water Demand Sensitivity to Climate Variability Across the Contiguous United States. Water Resources Research 2021, 57, 1 .
AMA StyleWanshu Nie, Benjamin F. Zaitchik, Matthew Rodell, Sujay V. Kumar, Kristi R. Arsenault, Hamada S. Badr. Irrigation Water Demand Sensitivity to Climate Variability Across the Contiguous United States. Water Resources Research. 2021; 57 (3):1.
Chicago/Turabian StyleWanshu Nie; Benjamin F. Zaitchik; Matthew Rodell; Sujay V. Kumar; Kristi R. Arsenault; Hamada S. Badr. 2021. "Irrigation Water Demand Sensitivity to Climate Variability Across the Contiguous United States." Water Resources Research 57, no. 3: 1.
There is an increasing demand for a land surface temperature (LST) dataset with both fine spatial and temporal resolutions due to the key role of LST in the Earth’s land–atmosphere system. Currently, the technique most commonly used to meet the demand is thermal infrared (TIR) remote sensing. However, cloud contamination interferes with TIR transmission through the atmosphere, limiting the potential of space-borne TIR sensors to provide the LST with complete spatio-temporal coverage. To solve this problem, we developed a two-step integrated method to: (i) estimate the 10-km LST with a high spatial coverage from passive microwave (PMW) data using the multilayer perceptron (MLP) model; and (ii) downscale the LST to 1 km and fill the gaps based on the geographically and temporally weighted regression (GTWR) model. Finally, the 1-km all-weather LST for cloudy pixels was fused with Aqua MODIS clear-sky LST via bias correction. This method was applied to produce the all-weather LST products for both daytime and nighttime during the years 2013–2018 in South China. The evaluations showed that the accuracy of the reproduced LST on cloudy days was comparable to that of the MODIS LST in terms of mean absolute error (2.29–2.65 K), root mean square error (2.92–3.25 K), and coefficients of determination (0.82–0.92) against the in situ measurements at four flux stations and ten automatic meteorological stations with various land cover types. The spatial and temporal analysis showed that the MLP-GTWR LST were highly consistent with the MODIS, in situ, and ERA5-Land LST, with the satisfactory ability to present the LST pattern under cloudy conditions. In addition, the MLP-GTWR method outperformed a gap-filling method and another TIR-PMW integrated method due to the local strategy in MLP and the consideration of temporal non-stationarity relationship in GTWR. Therefore, the test of the developed method in the frequently cloudy South China indicates the efficient potential for further application to other humid regions to generate the LST under cloudy condition.
Zhen Gao; Ying Hou; Benjamin Zaitchik; Yongzhe Chen; Weiping Chen. A Two-Step Integrated MLP-GTWR Method to Estimate 1 km Land Surface Temperature with Complete Spatial Coverage in Humid, Cloudy Regions. Remote Sensing 2021, 13, 971 .
AMA StyleZhen Gao, Ying Hou, Benjamin Zaitchik, Yongzhe Chen, Weiping Chen. A Two-Step Integrated MLP-GTWR Method to Estimate 1 km Land Surface Temperature with Complete Spatial Coverage in Humid, Cloudy Regions. Remote Sensing. 2021; 13 (5):971.
Chicago/Turabian StyleZhen Gao; Ying Hou; Benjamin Zaitchik; Yongzhe Chen; Weiping Chen. 2021. "A Two-Step Integrated MLP-GTWR Method to Estimate 1 km Land Surface Temperature with Complete Spatial Coverage in Humid, Cloudy Regions." Remote Sensing 13, no. 5: 971.
From the heated debates over the airborne transmission of the novel coronavirus to the abrupt Earth system changes caused by the sudden lockdowns, the dire circumstances resulting from the coronavirus disease 2019 (COVID-19) pandemic has brought the field of GeoHealth to the forefront of visibility in science and policy. The pandemic has inadvertently provided an opportunity to study how human response has impacted the Earth system, how the Earth system may impact the pandemic, and the capacity of GeoHealth to inform real-time policy. The lessons learned throughout our responses to the COVID-19 pandemic are shaping the future of GeoHealth.
Morgan E Gorris; Susan C Anenberg; Daniel L Goldberg; Gaige Hunter Kerr; Jennifer D Stowell; Daniel Tong; Benjamin F Zaitchik. Shaping the future of science: COVID-19 highlighting the importance of GeoHealth. 2021, 1 .
AMA StyleMorgan E Gorris, Susan C Anenberg, Daniel L Goldberg, Gaige Hunter Kerr, Jennifer D Stowell, Daniel Tong, Benjamin F Zaitchik. Shaping the future of science: COVID-19 highlighting the importance of GeoHealth. . 2021; ():1.
Chicago/Turabian StyleMorgan E Gorris; Susan C Anenberg; Daniel L Goldberg; Gaige Hunter Kerr; Jennifer D Stowell; Daniel Tong; Benjamin F Zaitchik. 2021. "Shaping the future of science: COVID-19 highlighting the importance of GeoHealth." , no. : 1.
Mapping and quantifying land degradation status is important for identifying vulnerable areas and to design sustainable landscape management. This study maps and quantifies land degradation status in the north Gojjam sub-basin of the Upper Blue Nile River (Abbay) using GIS and remote sensing integrated with multicriteria analysis (MCA). This is accomplished using a combination of biological, physical, and chemical land degradation indicators to generate a comprehensive land degradation assessment. All indicators were standardized and weighted using analytical hierarchy and pairwise comparison techniques. About 45.3% of the sub-basin was found to experience high to very high soil loss risk, with an average soil loss of 46 t ha−1yr−1. More than half of the sub-basin was found to experience moderate to high level of biological degradation (low vegetation status and low soil organic matter level). In total, 80.2% of the area is characterized as having a moderate level of physical land degradation. Similarly, the status of chemical degradation for about 55.8% and 39% of the sub-basin was grouped as low and moderate, respectively. The combined spatial MCA of biological, chemical, and physical land degradation indicators showed that about 1.14%, 32%, 35.4%, and 30.5% of the sub-basin exhibited very low, low, moderate, and high degradation level, respectively. This study has concluded that soil erosion and high level of biological degradation are the most important indicators of land degradation in the north Gojjam sub-basin. Hence, the study suggests the need for integrated land management practices to reduce land degradation, enhance the soil organic matter content, and increase the vegetation cover in the sub-basin.
Alelgn Ewunetu; Belay Simane; Ermias Teferi; Benjamin Zaitchik. Mapping and Quantifying Comprehensive Land Degradation Status Using Spatial Multicriteria Evaluation Technique in the Headwaters Area of Upper Blue Nile River. Sustainability 2021, 13, 2244 .
AMA StyleAlelgn Ewunetu, Belay Simane, Ermias Teferi, Benjamin Zaitchik. Mapping and Quantifying Comprehensive Land Degradation Status Using Spatial Multicriteria Evaluation Technique in the Headwaters Area of Upper Blue Nile River. Sustainability. 2021; 13 (4):2244.
Chicago/Turabian StyleAlelgn Ewunetu; Belay Simane; Ermias Teferi; Benjamin Zaitchik. 2021. "Mapping and Quantifying Comprehensive Land Degradation Status Using Spatial Multicriteria Evaluation Technique in the Headwaters Area of Upper Blue Nile River." Sustainability 13, no. 4: 2244.
Ethiopia’s socioeconomic development is strongly dependent on both its natural resources and hydroclimatic dynamics. Current and projected effects of climate change and variability in the Horn of Africa pose an enormous challenge to the country’s water resources management. We modeled multi-basin runoff scenarios in the country by calibrating statistical models first followed by extrapolation of the regressed functions into a future data domain under assumptions of stationarity. Precipitation and average near-surface air temperature predictors were used to calibrate Generalized Linear Models (GLM) to project 2011-2070 monthly runoff in a high-emission scenario (RCP 8.5) for selected General Circulation Models (GCM). Gridded fields of downscaled and bias-corrected precipitation, Tmax and Tmin for 10 CMIP5 GCMs were obtained from the NASA NEX-GDDP database. Hydrologic simulations from the NASA Land Data Assimilation System (LDAS) were used as proxies of observational basin response. Noah-MP’s climate forcings (CHIRPS precipitation and MERRA temperatures) were used to perform additional bias-correction over basin-averaged predictors extracted from the NEX-GDDP ensemble models. Monthly mean estimates for precipitation/temperature projections showed wetter/warmer conditions than the baseline for almost all regions. 2011-2040 July temperature climatology in most GCMs exhibited the strongest warming (> 1.5C o) in Central Ethiopia and it gradually decreased northwards and southwards. Correlation analysis showed that precipitation variations explain most of runoff variability during the rainy seasons. Future GLM runoff estimates suggest a generalized national increase of mean annual water supply when compared with historical LDAS, although spatio-temporal differences were observed across the country. The mentioned hydrological gains are driven by spatially distributed changes in precipitation with the biggest positive trends in the southeastern region followed by moderate precipitation increases in the Central Highlands and neutral changes in the Northwest. Few GCMs (e.g., GFDL-CM3) project drier conditions in the rainy seasons and a slight decrease in the mean annual runoff for most basins. The wettest model in the Abay basin, IPSL-CM5A-LR, predicts 15% increase in annual runoff when compared to historical averages.
Jose M. Molina; Benjamin F. Zaitchik; Zablon A. Adane. Future Water Supply Projections in Ethiopia Under Climate Change Using NASA NEX-GDDP and LDAS Simulations. 2021, 1 .
AMA StyleJose M. Molina, Benjamin F. Zaitchik, Zablon A. Adane. Future Water Supply Projections in Ethiopia Under Climate Change Using NASA NEX-GDDP and LDAS Simulations. . 2021; ():1.
Chicago/Turabian StyleJose M. Molina; Benjamin F. Zaitchik; Zablon A. Adane. 2021. "Future Water Supply Projections in Ethiopia Under Climate Change Using NASA NEX-GDDP and LDAS Simulations." , no. : 1.
The headwaters of the Blue Nile River in Ethiopia contain fragile mountain ecosystems and are highly susceptible to land degradation that impacts water quality and flow dynamics in a major transboundary river system. This study evaluates the status of land use/cover (LULC) change and key drivers of change over the past 31 years through a combination of satellite remote sensing and surveying of the local understanding of LULC patterns and drivers. Seven major LULC types (forest land, plantation forest, grazing land, agriculture land, bush and shrub land, bare land, and water bodies) from Landsat images of 1986, 1994, 2007, and 2017 were mapped. Agriculture and plantation forest land use/cover types increased by 21.4% and 368.8%, respectively, while other land use/cover types showed a decreasing trend: water body by 50.0%, bare land by 7.9%, grassland by 41.7%, forest by 28.9%, and bush and shrubland by 38.4%. Overall, 34.6% of the landscape experienced at least one LULC transition over the past 31 years, with 15.3% representing the net change and 19.3% representing the swap change. The percentage change in plantation forest land increased with an increasing altitude and slope gradient during the study period. The mapped LULC changes are consistent with the pressures reported by local residents. They are also consistent with root causes that include population growth, land tenure and common property rights, persistent poverty, weak enforcement of rules and low levels of extension services, a lack of public awareness, and poor infrastructure. Hence, the drivers for LULC should be controlled, and sustainable resources use is required; otherwise, these resources will soon be lost and will no longer be able to play their role in socioeconomic development and environmental sustainability.
Alelgn Ewunetu; Belay Simane; Ermias Teferi; Benjamin F. Zaitchik. Land Cover Change in the Blue Nile River Headwaters: Farmers’ Perceptions, Pressures, and Satellite-Based Mapping. Land 2021, 10, 68 .
AMA StyleAlelgn Ewunetu, Belay Simane, Ermias Teferi, Benjamin F. Zaitchik. Land Cover Change in the Blue Nile River Headwaters: Farmers’ Perceptions, Pressures, and Satellite-Based Mapping. Land. 2021; 10 (1):68.
Chicago/Turabian StyleAlelgn Ewunetu; Belay Simane; Ermias Teferi; Benjamin F. Zaitchik. 2021. "Land Cover Change in the Blue Nile River Headwaters: Farmers’ Perceptions, Pressures, and Satellite-Based Mapping." Land 10, no. 1: 68.
Optimization-based methods for the food-energy-water nexus can assist decision-making on critical infrastructure but are limited in scope and applicability. We provide an overview of optimization-based systems modeling techniques for operations researchers and systems modelers for the nexus. We find that the literature has contributed to the understanding of nexus interdependencies and has provided a framework for sustainability studies. We observe that the majority of the papers expand bottom-up models for one or two nexus components into the three, which may lead to asymmetric representation of the three sectors. Socioeconomic and political economy drivers are often exogenous to the models. The vast majority of papers can be further enhanced to account for local priorities, and the underlying decision-making process of stakeholders across the supply chains and at the interdependencies. Greater regional downscaling and technological detail along with more robust data could also enhance nexus systems modeling.
Charalampos Avraam; Ying Zhang; Sriram Sankaranarayanan; Benjamin Zaitchik; Emma Moynihan; Prathibha Juturu; Roni Neff; Sauleh Siddiqui. Optimization-Based Systems Modeling for the Food-Energy-Water Nexus. Current Sustainable/Renewable Energy Reports 2021, 8, 4 -16.
AMA StyleCharalampos Avraam, Ying Zhang, Sriram Sankaranarayanan, Benjamin Zaitchik, Emma Moynihan, Prathibha Juturu, Roni Neff, Sauleh Siddiqui. Optimization-Based Systems Modeling for the Food-Energy-Water Nexus. Current Sustainable/Renewable Energy Reports. 2021; 8 (1):4-16.
Chicago/Turabian StyleCharalampos Avraam; Ying Zhang; Sriram Sankaranarayanan; Benjamin Zaitchik; Emma Moynihan; Prathibha Juturu; Roni Neff; Sauleh Siddiqui. 2021. "Optimization-Based Systems Modeling for the Food-Energy-Water Nexus." Current Sustainable/Renewable Energy Reports 8, no. 1: 4-16.
South and Southeast Asia is subject to significant hydrometeorological extremes, including drought. Under rising temperatures, growing populations, and an apparent weakening of the South Asian monsoon in recent decades, concerns regarding drought and its potential impacts on water and food security are on the rise. Reliable sub-seasonal to seasonal (S2S) hydrological forecasts could, in principle, help governments and international organizations to better assess risk and act in the face of an oncoming drought. Here, we leverage recent improvements in S2S meteorological forecasts and the growing power of Earth observations to provide more accurate monitoring of hydrological states for forecast initialization. Information from both sources is merged in a South and Southeast Asia sub-seasonal to seasonal hydrological forecasting system (SAHFS-S2S), developed collaboratively with the NASA SERVIR program and end users across the region. This system applies the Noah-Multiparameterization (NoahMP) Land Surface Model (LSM) in the NASA Land Information System (LIS), driven by downscaled meteorological fields from the Global Data Assimilation System (GDAS) and Climate Hazards InfraRed Precipitation products (CHIRP and CHIRPS) to optimize initial conditions. The NASA Goddard Earth Observing System Model sub-seasonal to seasonal (GEOS-S2S) forecasts, downscaled using the National Center for Atmospheric Research (NCAR) General Analog Regression Downscaling (GARD) tool and quantile mapping, are then applied to drive 5 km resolution hydrological forecasts to a 9-month forecast time horizon. Results show that the skillful predictions of root zone soil moisture can be made 1 to 2 months in advance for forecasts initialized in rainy seasons and up to 8 months when initialized in dry seasons. The memory of accurate initial conditions can positively contribute to forecast skills throughout the entire 9-month prediction period in areas with limited precipitation. This SAHFS-S2S has been operationalized at the International Centre for Integrated Mountain Development (ICIMOD) to support drought monitoring and warning needs in the region.
Yifan Zhou; Benjamin F. Zaitchik; Sujay V. Kumar; Kristi R. Arsenault; Mir A. Matin; Faisal M. Qamer; Ryan A. Zamora; Kiran Shakya. Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins. Hydrology and Earth System Sciences 2021, 25, 41 -61.
AMA StyleYifan Zhou, Benjamin F. Zaitchik, Sujay V. Kumar, Kristi R. Arsenault, Mir A. Matin, Faisal M. Qamer, Ryan A. Zamora, Kiran Shakya. Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins. Hydrology and Earth System Sciences. 2021; 25 (1):41-61.
Chicago/Turabian StyleYifan Zhou; Benjamin F. Zaitchik; Sujay V. Kumar; Kristi R. Arsenault; Mir A. Matin; Faisal M. Qamer; Ryan A. Zamora; Kiran Shakya. 2021. "Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins." Hydrology and Earth System Sciences 25, no. 1: 41-61.
Early studies of weather, seasonality, and environmental influences on COVID-19 have yielded inconsistent and confusing results. To provide policy-makers and the public with meaningful and actionable environmentally-informed COVID-19 risk estimates, the research community must meet robust methodological and communication standards.
Benjamin F. Zaitchik; Neville Sweijd; Joy Shumake-Guillemot; Andy Morse; Chris Gordon; Aileen Marty; Juli Trtanj; Juerg Luterbacher; Joel Botai; Swadhin Behera; Yonglong Lu; Jane Olwoch; Ken Takahashi; Jennifer D. Stowell; Xavier Rodó. A framework for research linking weather, climate and COVID-19. Nature Communications 2020, 11, 1 -3.
AMA StyleBenjamin F. Zaitchik, Neville Sweijd, Joy Shumake-Guillemot, Andy Morse, Chris Gordon, Aileen Marty, Juli Trtanj, Juerg Luterbacher, Joel Botai, Swadhin Behera, Yonglong Lu, Jane Olwoch, Ken Takahashi, Jennifer D. Stowell, Xavier Rodó. A framework for research linking weather, climate and COVID-19. Nature Communications. 2020; 11 (1):1-3.
Chicago/Turabian StyleBenjamin F. Zaitchik; Neville Sweijd; Joy Shumake-Guillemot; Andy Morse; Chris Gordon; Aileen Marty; Juli Trtanj; Juerg Luterbacher; Joel Botai; Swadhin Behera; Yonglong Lu; Jane Olwoch; Ken Takahashi; Jennifer D. Stowell; Xavier Rodó. 2020. "A framework for research linking weather, climate and COVID-19." Nature Communications 11, no. 1: 1-3.
Diarrheal disease remains a major cause of childhood mortality and morbidity causing poor health and economic outcomes. In low-resource settings, young children are exposed to numerous risk factors for enteric pathogen transmission within their dwellings, though the relative importance of different transmission pathways varies by pathogen species. The objective of this analysis was to model associations between five household-level risk factors—water, sanitation, flooring, caregiver education, and crowding—and infection status for endemic enteric pathogens in children in five surveillance studies. Data were combined from 22 sites in which a total of 58,000 stool samples were tested for 16 specific enteropathogens using qPCR. Risk ratios for pathogen- and taxon-specific infection status were modeled using generalized linear models along with hazard ratios for all-cause diarrhea in proportional hazard models, with the five household-level variables as primary exposures adjusting for covariates. Improved drinking water sources conferred a 17% reduction in diarrhea risk; however, the direction of its association with particular pathogens was inconsistent. Improved sanitation was associated with a 9% reduction in diarrhea risk with protective effects across pathogen species and taxa of around 10–20% risk reduction. A 9% reduction in diarrhea risk was observed in subjects with covered floors, which were also associated with decreases in risk for zoonotic enteropathogens. Caregiver education and household crowding showed more modest, inconclusive results. Combining data from diverse sites, this analysis quantified associations between five household-level exposures on risk of specific enteric infections, effects which differed by pathogen species but were broadly consistent with hypothesized transmission mechanisms. Such estimates may be used within expanded water, sanitation, and hygiene (WASH) programs to target interventions to the particular pathogen profiles of individual communities and prioritize resources.
Josh M. Colston; Abu S. G. Faruque; M. Jahangir Hossain; Debasish Saha; Suman Kanungo; Inácio Mandomando; M. Imran Nisar; Anita K. M. Zaidi; Richard Omore; Robert F. Breiman; Samba O. Sow; Anna Roose; Myron M. Levine; Karen L. Kotloff; Tahmeed Ahmed; Pascal Bessong; Zulfiqar Bhutta; Estomih Mduma; Pablo Penatero Yori; Prakash Sunder Shrestha; Maribel P. Olortegui; Gagandeep Kang; Aldo A. M. Lima; Jean Humphrey; Andrew Prendergast; Francesca Schiaffino; Benjamin F. Zaitchik; Margaret N. Kosek. Associations between Household-Level Exposures and All-Cause Diarrhea and Pathogen-Specific Enteric Infections in Children Enrolled in Five Sentinel Surveillance Studies. International Journal of Environmental Research and Public Health 2020, 17, 8078 .
AMA StyleJosh M. Colston, Abu S. G. Faruque, M. Jahangir Hossain, Debasish Saha, Suman Kanungo, Inácio Mandomando, M. Imran Nisar, Anita K. M. Zaidi, Richard Omore, Robert F. Breiman, Samba O. Sow, Anna Roose, Myron M. Levine, Karen L. Kotloff, Tahmeed Ahmed, Pascal Bessong, Zulfiqar Bhutta, Estomih Mduma, Pablo Penatero Yori, Prakash Sunder Shrestha, Maribel P. Olortegui, Gagandeep Kang, Aldo A. M. Lima, Jean Humphrey, Andrew Prendergast, Francesca Schiaffino, Benjamin F. Zaitchik, Margaret N. Kosek. Associations between Household-Level Exposures and All-Cause Diarrhea and Pathogen-Specific Enteric Infections in Children Enrolled in Five Sentinel Surveillance Studies. International Journal of Environmental Research and Public Health. 2020; 17 (21):8078.
Chicago/Turabian StyleJosh M. Colston; Abu S. G. Faruque; M. Jahangir Hossain; Debasish Saha; Suman Kanungo; Inácio Mandomando; M. Imran Nisar; Anita K. M. Zaidi; Richard Omore; Robert F. Breiman; Samba O. Sow; Anna Roose; Myron M. Levine; Karen L. Kotloff; Tahmeed Ahmed; Pascal Bessong; Zulfiqar Bhutta; Estomih Mduma; Pablo Penatero Yori; Prakash Sunder Shrestha; Maribel P. Olortegui; Gagandeep Kang; Aldo A. M. Lima; Jean Humphrey; Andrew Prendergast; Francesca Schiaffino; Benjamin F. Zaitchik; Margaret N. Kosek. 2020. "Associations between Household-Level Exposures and All-Cause Diarrhea and Pathogen-Specific Enteric Infections in Children Enrolled in Five Sentinel Surveillance Studies." International Journal of Environmental Research and Public Health 17, no. 21: 8078.
Spending time outdoors is associated with increased physical activity; however, high ambient temperature/humidity, together with built environment features in urban versus rural environments, may influence physical activity. We conducted an intervention trial with 89 urban and 88 rural participants performing normal activities on Days 1–2 (baseline) and spending an additional 30 min outdoors on Days 3–7 (intervention) in the summer. Participants wore a pedometer with real-time visual feedback to track daily steps taken and a thermometer clipped to their shoe to track temperatures experienced individually. Hygrometer–thermometers were deployed in participants’ neighborhoods to collect finer resolution ambient heat indexes in addition to regional weather station measurements. Using linear mixed effects models and adjusting for ambient conditions and individual-level factors, participants on average walked 637 (95%CI (83, 1192)) more steps and had a 0.59 °C (95%CI (0.30, 0.88)) lower daily mean individually experienced heat index during intervention days compared to baseline days. The intervention benefit of increased physical activity was greater in rural residents who were less active at baseline, compared to urban residents. Our results suggest adding a small amount of additional time outdoors may improve physical activity without increasing participants’ heat exposure, even during summer in a humid subtropical climate.
Suwei Wang; Molly B. Richardson; Connor Y.H. Wu; Benjamin F. Zaitchik; Julia M. Gohlke. Effect of an Additional 30 Minutes Spent Outdoors during Summer on Daily Steps and Individually Experienced Heat Index. International Journal of Environmental Research and Public Health 2020, 17, 7558 .
AMA StyleSuwei Wang, Molly B. Richardson, Connor Y.H. Wu, Benjamin F. Zaitchik, Julia M. Gohlke. Effect of an Additional 30 Minutes Spent Outdoors during Summer on Daily Steps and Individually Experienced Heat Index. International Journal of Environmental Research and Public Health. 2020; 17 (20):7558.
Chicago/Turabian StyleSuwei Wang; Molly B. Richardson; Connor Y.H. Wu; Benjamin F. Zaitchik; Julia M. Gohlke. 2020. "Effect of an Additional 30 Minutes Spent Outdoors during Summer on Daily Steps and Individually Experienced Heat Index." International Journal of Environmental Research and Public Health 17, no. 20: 7558.
Border regions have been implicated as important hot spots of malaria transmission, particularly in Latin America, where free movement rights mean that residents can cross borders using just a national ID. Additionally, rural livelihoods largely depend on short-term migrants traveling across borders via the Amazon’s river networks to work in extractive industries, such as logging. As a result, there is likely considerable spillover across country borders, particularly along the border between Peru and Ecuador. This border region exhibits a steep gradient of transmission intensity, with Peru having a much higher incidence of malaria than Ecuador. In this paper, we integrate 13 years of weekly malaria surveillance data collected at the district level in Peru and the canton level in Ecuador, and leverage hierarchical Bayesian spatiotemporal regression models to identify the degree to which malaria transmission in Ecuador is influenced by transmission in Peru. We find that increased case incidence in Peruvian districts that border the Ecuadorian Amazon is associated with increased incidence in Ecuador. Our results highlight the importance of coordinated malaria control across borders.
Annika K. Gunderson; Rani E. Kumar; Cristina Recalde-Coronel; Luis E. Vasco; Andree Valle-Campos; Carlos F. Mena; Benjamin F. Zaitchik; Andres G. Lescano; William K. Pan; Mark M. Janko. Malaria Transmission and Spillover across the Peru–Ecuador Border: A Spatiotemporal Analysis. International Journal of Environmental Research and Public Health 2020, 17, 7434 .
AMA StyleAnnika K. Gunderson, Rani E. Kumar, Cristina Recalde-Coronel, Luis E. Vasco, Andree Valle-Campos, Carlos F. Mena, Benjamin F. Zaitchik, Andres G. Lescano, William K. Pan, Mark M. Janko. Malaria Transmission and Spillover across the Peru–Ecuador Border: A Spatiotemporal Analysis. International Journal of Environmental Research and Public Health. 2020; 17 (20):7434.
Chicago/Turabian StyleAnnika K. Gunderson; Rani E. Kumar; Cristina Recalde-Coronel; Luis E. Vasco; Andree Valle-Campos; Carlos F. Mena; Benjamin F. Zaitchik; Andres G. Lescano; William K. Pan; Mark M. Janko. 2020. "Malaria Transmission and Spillover across the Peru–Ecuador Border: A Spatiotemporal Analysis." International Journal of Environmental Research and Public Health 17, no. 20: 7434.
The characteristics of urban land surfaces contribute to the urban heat island, and, in turn, can exacerbate the severity of heat wave impacts. However, the mechanisms and complex interactions in urban areas underlying land surface temperature are still being understood. Understanding these mechanisms is necessary to design strategies that mitigate land temperatures in our cities. Using the recently available night-time moderate-resolution thermal satellite imagery and employing advanced nonlinear statistical models, we seek to answer the question “What is the influence and relative importance of urban characteristics on land surface temperature, during both the day and night?” To answer this question, we analyze urban land surface temperature in four cities across the United States. We devise techniques for training and validating nonlinear statistical models on geostatistical data and use these models to assess the interdependent effects of urban characteristics on urban surface temperature. Our results suggest that vegetation and impervious surfaces are the most important urban characteristics associated with land surface temperature. While this may be expected, this is the first study to quantify this relationship for Landsat-resolution nighttime temperature estimates. Our results also demonstrate the potential for using nonlinear statistical analysis to investigate land surface temperature and its relationships with urban characteristics. Improved understanding of these relationships influencing both night and day land surface temperature will assist planners undertaking climate change adaptation and heat wave mitigation.
T.M. Logan; Benjamin Zaitchik; S. Guikema; A. Nisbet. Night and day: The influence and relative importance of urban characteristics on remotely sensed land surface temperature. Remote Sensing of Environment 2020, 247, 111861 .
AMA StyleT.M. Logan, Benjamin Zaitchik, S. Guikema, A. Nisbet. Night and day: The influence and relative importance of urban characteristics on remotely sensed land surface temperature. Remote Sensing of Environment. 2020; 247 ():111861.
Chicago/Turabian StyleT.M. Logan; Benjamin Zaitchik; S. Guikema; A. Nisbet. 2020. "Night and day: The influence and relative importance of urban characteristics on remotely sensed land surface temperature." Remote Sensing of Environment 247, no. : 111861.
Access to credible estimates of water‐use are critical for making optimal operational decisions and investment plans to ensure reliable and affordable provisioning of water. Furthermore, identifying the key predictors of water use is important for regulators to promote sustainable development policies to reduce water use. In this paper, we propose a data‐driven framework, grounded in statistical learning theory, to develop a rigorously evaluated predictive model of state‐level, per capita water use in the US as a function of various geographic, climatic and socioeconomic variables. Specifically, we compare the accuracy of various statistical methods in predicting the state‐level, per capita water use and find that the model based on the Random Forest algorithm outperforms all other models. We then leverage the Random Forest model to identify key factors associated with high water‐usage intensity among different sectors in the US. More specifically, irrigated farming, thermoelectric energy generation, and urbanization were identified as the most water‐intensive anthropogenic activities, on a per capita basis. Among the climate factors, precipitation was found to be a key predictor of per capita water use, with drier conditions associated with higher water usage. Overall, our study highlights the utility of leveraging data‐driven modeling to gain valuable insights related to the water use patterns across expansive geographical areas.
E. Wongso; R. Nateghi; B. Zaitchik; S. Quiring; R. Kumar. A Data‐Driven Framework to Characterize State‐Level Water Use in the United States. Water Resources Research 2020, 56, 1 .
AMA StyleE. Wongso, R. Nateghi, B. Zaitchik, S. Quiring, R. Kumar. A Data‐Driven Framework to Characterize State‐Level Water Use in the United States. Water Resources Research. 2020; 56 (9):1.
Chicago/Turabian StyleE. Wongso; R. Nateghi; B. Zaitchik; S. Quiring; R. Kumar. 2020. "A Data‐Driven Framework to Characterize State‐Level Water Use in the United States." Water Resources Research 56, no. 9: 1.
The objective of this study was to evaluate the performance of satellite rainfall estimates (Climate Hazards Group Infrared Precipitation with Stations version 2 (CHIRPSv2) and Multi-Source Weighted-Ensemble Precipitation version 2 (MSWEPv2) from 1981 to 2018 for monthly meteorological drought analysis over the Upper Blue Nile (UBN) basin. The reference for the performance evaluation was rainfall measured in situ selected with reference to the elevation zones of the basin: Highland, midland, and lowland. Both the measured and estimated rainfall datasets were aggregated by month at a spatial resolution of 10 km × 10 km with a temporal coverage of 38 years from 1981 to 2018 and evaluated with respect to raw precipitation statistics and the standardized precipitation index (SPI). The values of SPI were validated with reference to documented meteorological drought records of the country. The mean bias, correlation coefficient, probability of bias (PBias, %), mean error (ME, mm), and root mean square error (RMSE, mm) values across the elevation zones for CHIRPSv2 were found to be 1.07, 0.91, 6.75, 7.74, and 122.34, respectively. The corresponding values were 1.19, 0.87, 18.56, 19.54, and 130.26 for MSWEPv2. Based on this result, CHIRPSv2 was employed to analyze the magnitude of drought in the different elevation zones of the UBN. The magnitude (SPI) of monthly meteorological drought over the entire UBN basin from 1981 to 2018 ranged from 0 to −3.74. The strongest negative SPI value (−3.74) was observed in August 1984 in midland areas. The highest magnitude of drought was −3.0 in July 2015 over the highland and −3.03 in June 2015 over the lowland during 2014–2017. The observed drought was characterized by extreme, severe, and moderate levels. The mean frequency of severe/extreme meteorological drought in the 38-year period over the highland, midland, and lowland parts of the UBN ranged from 7% to 11%. The average of severe/extreme drought events in each of the elevation zones of the basin was 9%, that is, drought occurred almost every 10 years for all elevation zones of the basin. Over the 38-year period, severe/extreme drought occurred at the onset and/or offset time of rainy season over all elevation zones of the basin. The UBN is characterized as a drought-prone basin. However, the frequency and magnitude of drought could neither be described as a decreasing nor as an increasing linear trend. Thus, the farming practices in the basin need to be enhanced with an improved early warning system and drought-resistant seed technologies.
Mintesinot Taye; Dejene Sahlu; Benjamin Zaitchik; Mulugeta Neka. Evaluation of Satellite Rainfall Estimates for Meteorological Drought Analysis over the Upper Blue Nile Basin, Ethiopia. Geosciences 2020, 10, 352 .
AMA StyleMintesinot Taye, Dejene Sahlu, Benjamin Zaitchik, Mulugeta Neka. Evaluation of Satellite Rainfall Estimates for Meteorological Drought Analysis over the Upper Blue Nile Basin, Ethiopia. Geosciences. 2020; 10 (9):352.
Chicago/Turabian StyleMintesinot Taye; Dejene Sahlu; Benjamin Zaitchik; Mulugeta Neka. 2020. "Evaluation of Satellite Rainfall Estimates for Meteorological Drought Analysis over the Upper Blue Nile Basin, Ethiopia." Geosciences 10, no. 9: 352.
Although coronavirus disease 2019 (COVID-19) emerged in January 2020, there is no quantified effect size for non-pharmaceutical interventions (NPI) to control the outbreak in the continental US. Objective. To quantify national and sub-national effect sizes of NPIs in the US. Design. This is an observational study for which we obtained daily county level COVID-19 cases and deaths from January 22, 2020 through the phased removal of social distancing protections. A stepped-wedge cluster-randomized trial (SW-CRT) analytical approach is used, leveraging the phased implementation of policies. Data include 3142 counties from all 50 US states and the District of Columbia. Exposures. County-level NPIs were obtained from online county and state policy databases, then classified into four intervention levels: Level 1 (low) – declaration of a State of Emergency; Level 2 (moderate) – school closures, restricting nursing home access, or closing restaurants and bars; Level 3 (high) – non-essential business closures, suspending non-violent arrests, suspending elective medical procedures, suspending evictions, or restricting mass gatherings of at least 10 people; and Level 4 (aggressive) – sheltering in place / stay-at-home, public mask requirements, or travel restrictions. Additional county-level data were obtained to record racial (Black, Hispanic), economic (educational level, poverty), demographic (rural/urban) and climate factors (temperature, specific humidity, solar radiation). Main Outcomes. The primary outcomes are rates of COVID-19 cases, deaths and case doubling times. NPI effects are measured separately for nine US Census Region (Pacific, Mountain, West North Central, East North Central, West South Central, East South Central, South Atlantic, Middle Atlantic, New England). Results. Aggressive NPIs (level 4) significantly reduced COVID-19 case and death rates in all US Census Regions, with effect sizes ranging from 4.1% to 25.7% and 5.5% to 25.5%, respectively, for each day they were active. No other intervention level achieved significance across all US Regions. Intervention levels 3 and 4 both increased COVID-19 doubling times, with effects peaking at 25 and 40 days after initiation of each policy, respectively. The effectiveness of level 3 NPIs varied, reducing case rates in all regions except North Central states, but associated with significantly higher death rates in all regions except Pacific states. Intervention levels 1 and 2 did not indicate any effect on COVID-19 propagation and, in some regions, these interventions were associated with increased COVID-19 cases and deaths. Heterogeneity of NPI effects are associated with racial composition, poverty, urban-rural environment, and climate factors. Conclusion. Aggressive NPIs are effective tools to reduce COVID-19 propagation and mortality. Reducing social and environmental disparities may improve NPI effects in regions where less strict policies are in place.
William K. Pan; Stefanos Tyrovolas; Giné-Vázquez Iago; Rishav Raj Dasgupta; Fernández Daniel; Ben Zaitchik; Paul M. Lantos; Christopher W. Woods. COVID-19: Effectiveness of Non-Pharmaceutical Interventions in the United States before Phased Removal of Social Distancing Protections Varies by Region. 2020, 1 .
AMA StyleWilliam K. Pan, Stefanos Tyrovolas, Giné-Vázquez Iago, Rishav Raj Dasgupta, Fernández Daniel, Ben Zaitchik, Paul M. Lantos, Christopher W. Woods. COVID-19: Effectiveness of Non-Pharmaceutical Interventions in the United States before Phased Removal of Social Distancing Protections Varies by Region. . 2020; ():1.
Chicago/Turabian StyleWilliam K. Pan; Stefanos Tyrovolas; Giné-Vázquez Iago; Rishav Raj Dasgupta; Fernández Daniel; Ben Zaitchik; Paul M. Lantos; Christopher W. Woods. 2020. "COVID-19: Effectiveness of Non-Pharmaceutical Interventions in the United States before Phased Removal of Social Distancing Protections Varies by Region." , no. : 1.