DIY meteorology: Use of citizen science to monitor snow dynamics in a data-sparse city

Cities are under pressure to operate their services effectively and project costs of operations across various timeframes. In high-latitude and high-altitude urban centers, snow management is one of the larger unknowns and has both operational and budgetary limitations. Snowfall and snow depth observations within urban environments are important to plan snow clearing and prepare for the effects of spring runoff on cities' drainage systems. In-house research functions are expensive, but one way to overcome that expense and still produce effective data is through citizen science. In this paper, we examine the potential to use citizen science for snowfall data collection in urban environments. A group of volunteers measured daily snowfall and snow depth at an urban site in Saskatoon (Canada) during two winters. Reliability was assessed with a statistical consistency analysis and a comparison with other data sets collected around Saskatoon. We found that citizen-science-derived data were more reliable and relevant for many urban management stakeholders. Feedback from the participants demonstrated reflexivity about social learning and a renewed sense of community built around generating reliable and useful data. We conclude that citizen science holds great potential to improve data provision for effective and sustainable city planning and greater social learning benefits overall

DIY meteorology: Use of citizen science to monitor snow dynamics in a data-sparse city

Cities are under pressure to operate their services effectively and project costs of operations across various timeframes. In high-latitude and high-altitude urban centers, snow management is one of the larger unknowns and has both operational and budgetary limitations. Snowfall and snow depth observations within urban environments are important to plan snow clearing and prepare for the effects of spring runoff on cities' drainage systems. In-house research functions are expensive, but one way to overcome that expense and still produce effective data is through citizen science. In this paper, we examine the potential to use citizen science for snowfall data collection in urban environments. A group of volunteers measured daily snowfall and snow depth at an urban site in Saskatoon (Canada) during two winters. Reliability was assessed with a statistical consistency analysis and a comparison with other data sets collected around Saskatoon. We found that citizen-science-derived data were more reliable and relevant for many urban management stakeholders. Feedback from the participants demonstrated reflexivity about social learning and a renewed sense of community built around generating reliable and useful data. We conclude that citizen science holds great potential to improve data provision for effective and sustainable city planning and greater social learning benefits overall

Spatiotemporal variability of four precipitation-based drought indices in Xinjiang, China

Global increases in duration and prevalence of droughts require detailed drought characterization at various spatial and temporal scales. In this study, drought severity in Xinjiang, China was investigated between 1961 and 2012. Using meteorological data from 55 weather stations, the UNEP (1993) index (I-A), Erinc's aridity index (I-m), and Sahin's aridity index (I-sh) were calculated at the monthly and annual timescales and compared to the Penman-Monteith based standard precipitation evapotranspiration index (SPEIPM). Drought spatiotemporal variability was analyzed for north (NX), south (SX), and entire Xinjiang (EX). I-m could not be calculated at 51 stations in winter as T-max was below 0. At the monthly timescale, I-A, I-m, and I-sh correlated poorly to SPEIPM because of seasonality and temporal variability, but annual I-A, I-m, and I-sh correlated well with SPEIPM. Annual I-A, I-m, and I-sh showed strong spatial variability. The 15 extreme droughts denoted by monthly SPEIPM occurred in NX but out of phase in SX. Annual precipitation, maximum temperature, and relative and specific humidity increased, while air pressure and potential evapotranspiration decreased over 1961-2012. The resulting increases in the four drought indices indicated that drought severity in Xinjiang decreased, because the local climate became warmer and wetter.Chinese National Science Foundations [U1203182, 51579213]; State Foundation for Studying Abroad [201506305014]; China 111 projectMinistry of Education, China - 111 Project [B12007]This study was financially supported by the Xinjiang Joint Project of the Chinese National Science Foundations (U1203182, 51579213), the State Foundation for Studying Abroad (201506305014), and China 111 project (B12007). We also thank the Meteorological Data Sharing Service Network in China (cdc.nmic.cn) for supplying weather data. The constructive comments of three anonymous reviewers strengthened the analyses of this paper

Data from: Feedbacks between shallow groundwater dynamics and surface topography on runoff generation in flat fields

In winter, saturation excess (SE) ponding is observed regularly in temperate lowland regions. Surface runoff dynamics are controlled by small topographical features that are unaccounted for in hydrological models. To better understand storage and routing effects of small scale topography and their interaction with shallow groundwater under SE conditions, we developed a model of reduced complexity to investigate SE runoff generation, emphasizing feedbacks between shallow groundwater dynamics and mesotopography. The dynamic specific yield affected unsaturated zone water storage, causing rapid switches between negative and positive head and a flatter groundwater mound than predicted by analytical agro-hydrological models. Accordingly, saturated areas were larger and local groundwater fluxes smaller than predicted, leading to surface runoff generation. Mesotopographic features routed water over larger distances, providing a feedback mechanism that amplified changes to the shape of the groundwater mound. This in turn enhanced runoff generation, but whether it also resulted in runoff events depended on the geometry and location of the depressions. Whereas conditions favourable to runoff generation may abound during winter, these feedbacks profoundly reduce the predictability of SE runoff: statistically identical rainfall series may result in completely different runoff generation. The model results indicate that waterlogged areas in any given rainfall event are larger than those predicted by current analytical groundwater models used for drainage design. This change in the groundwater mound extent has implications for crop growth and damage assessments

FASTR model validation data

File contains water balance results generated with the FASTR hydrological model for three numerical validation experiments

FASTR experiment 1: role of the unsaturated zone moisture profile

File contains water balance results simulated with the FASTR hydrological model for 15,000 combinations of initial groundwater level, soil hydraulic parameters, saturated hydraulic conductivity, and precipitation structure

FASTR experiment 2: seasonal saturation excess runoff generation in fields with mesotopography

File contains water balance results simulated with the FASTR hydrological model for 1,080 combinations of mesotopography, soil hydraulic parameters, saturated hydraulic conductivity, and precipitation structure

Snow and weather data Saskatoon, SK, Canada. Winter 2013-2014, 2014-2015

Daily values for snowfall, snow depth, and snow density from citizen science study in Saskatoon, SK. Complemented with daily temperature and wind speed values