Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Estimating Potential Climate Change Effects on the Upper Neuse Watershed Water Balance Using the SWAT Model

Climate change poses water resource challenges for many already water stressed watersheds throughout the world. One such watershed is the Upper Neuse Watershed in North Carolina, which serves as a water source for the large and growing Research Triangle Park region. The aim of this study was to quantify possible changes in the watershed’s water balance due to climate change. To do this, we used the Soil and Water Assessment Tool (SWAT) model forced with different climate scenarios for baseline, mid‐century, and end‐century time periods using five different downscaled General Circulation Models. Before running these scenarios, the SWAT model was calibrated and validated using daily streamflow records within the watershed. The study results suggest that, even under a mitigation scenario, precipitation will increase by 7.7% from the baseline to mid‐century time period and by 9.8% between the baseline and end‐century time period. Over the same periods, evapotranspiration (ET) would decrease by 5.5 and 7.6%, water yield would increase by 25.1% and 33.2%, and soil water would increase by 1.4% and 1.9%. Perhaps most importantly, the model results show, under a high emission scenario, large seasonal differences with ET estimated to decrease by up to 42% and water yield to increase by up to 157% in late summer and fall. Planning for the wetter predicted future and corresponding seasonal changes will be critical for mitigating the impacts of climate change on water resources.     

Circumpolar status of Arctic ptarmigan: Population dynamics and trends

Rock ptarmigan (Lagopus muta) and willow ptarmigan (L. lagopus) are Arctic birds with a circumpolar distribution but there is limited knowledge about their status and trends across their circumpolar distribution. Here, we compiled information from 90 ptarmigan study sites from 7 Arctic countries, where almost half of the sites are still monitored. Rock ptarmigan showed an overall negative trend on Iceland and Greenland, while Svalbard and Newfoundland had positive trends, and no significant trends in Alaska. For willow ptarmigan, there was a negative trend in mid-Sweden and eastern Russia, while northern Fennoscandia, North America and Newfoundland had no significant trends. Both species displayed some periods with population cycles (short 3–6 years and long 9–12 years), but cyclicity changed through time for both species. We propose that simple, cost-efficient systematic surveys that capture the main feature of ptarmigan population dynamics can form the basis for citizen science efforts in order to fill knowledge gaps for the many regions that lack systematic ptarmigan monitoring programs.

     

Muskox status,recent variation,and uncertain future

Ambio - Muskoxen (Ovibos moschatus) are an integral component of Arctic biodiversity. Given low genetic diversity, their ability to respond to future and rapid Arctic change is unknown, although...     

Growth of Dehalococcoides spp. and increased abundance of reductive dehalogenase genes in anaerobic PCB-contaminated sediment microcosms

Polychlorinated biphenyls (PCBs) contaminate 19% of US Superfund sites and represent a serious risk to human and environmental health. One promising strategy to remediate PCB-contaminated sediments utilizes organohalide-respiring bacteria (OHRB) that dechlorinate PCBs.

However, functional genes that act as biomarkers for PCB dechlorination processes (i.e., reductive dehalogenase genes) are poorly understood. Here, we developed anaerobic sediment microcosms that harbor an OHRB community dominated by the genus Dehalococcoides. During the 430-day microcosm incubation, Dehalococcoides 16S rRNA sequences increased two orders of magnitude to 10⁷ copies/g of sediment, and at the same time, PCB118 decreased by as much as 70%. In addition, the OHRB community dechlorinated a range of penta- and tetra-chlorinated PCB congeners including PCBs 66, 70?+?74?+?76, 95, 90?+?101, and PCB110 without exogenous electron donor. We quantified candidate reductive dehalogenase (RDase) genes over a 430-day incubation period and found rd14, a reductive dehalogenase that belongs to Dehalococcoides mccartyi strain CG5, was enriched to 10⁷ copies/g of sediment. At the same time, pcbA5 was enriched to only 10⁵ copies/g of sediment. A survey for additional RDase genes revealed sequences similar to strain CG5’s rd4 and rd8. In addition to demonstrating the PCB dechlorination potential of native microbial communities in contaminated freshwater sediments, our results suggest candidate functional genes with previously unexplored potential could serve as biomarkers of PCB dechlorination processes.

     

Improving dialogue among researchers,local and indigenous peoples and decision-makers to address issues of climate change in the North

Ambio - The Circumpolar North has been changing rapidly within the last decades, and the socioeconomic systems of the Eurasian Arctic and Siberia in particular have displayed the most dramatic...     

Understanding interactions between urban development policies and GHG emissions: A case study in Stockholm Region

Human-induced urban growth and sprawl have implications for greenhouse gas (GHG) emissions that may not be included in conventional GHG accounting methods. Improved understanding of this issue requires use of interactive, spatial-explicit social–ecological systems modeling. This paper develops a comprehensive approach to modeling GHG emissions from urban developments, considering Stockholm County, Sweden as a case study. GHG projections to 2040 with a social–ecological system model yield overall greater emissions than simple extrapolations in official climate action planning. The most pronounced difference in emissions (39% higher) from energy use single-residence buildings resulting from urban sprawl. And this difference is not accounted for in the simple extrapolations. Scenario results indicate that a zoning policy, restricting urban development in certain areas, can mitigate 72% of the total emission effects of the model-projected urban sprawl. The study outcomes include a decision support interface for communicating results and policy implications with policymakers.

     

Correction to: Keeping pace with forestry: Multi-scale conservation in a changing production forest matrix

Ambio - In the original published article, the sentence “Nevertheless, semi-natural forest remnants continue to be harvested and fragmented (Svensson et al. 2018; Jonsson et al. 2019), and...     

A novel sigma coordinate system to simulate abrupt changes of underwater terrain in a hydrodynamic model: application to Lake Mead,USA

The sigma (SIG) coordinate system in ocean circulation simulation models results inevitably in horizontal pressure gradient error. This problem also emerges in models of deep lakes or reservoirs with the same characteristics of underwater terrain mutation. SIG coordinates reflect vertical relative stratification but cannot be used to calculate horizontal pressure gradient force in places with drastic topographic changes; this results in vertical water temperature and circulation errors. In deep lakes or reservoirs, differences in water density caused by the temperature difference between upper and lower water bodies is the primary cause of thermal stratification phenomena. Lake Mead was used as a case study on steep topography based on Environmental Fluid Dynamics Code (EFDC) model in this study. SIG coordinates result in close agreement between the calibrated temperature time series at the top and middle water layers, but disparity in the bottom water layer. The error emerges in the horizontal pressure gradient error due to the SIG coordinate transformation. Neither increasing the vertical resolution nor adjusting the horizontal viscosity coefficient resolve this error. We test the sigma-zed (SGZ) coordinate which combines Z coordinate and SIG coordinate as a replacement for the SIG coordinate to find that they effectively reduce the model’s runtime and simulation efficiency. The vertical temperature distribution in SGZ coordinate mode is more accurate than the distribution in SIG coordinate mode. The Navier-Stokes horizontal gradient and advection diffusion equation results under SIG coordinates are very sensitive to the pressure gradient. The replacement also enhances resolution near the thermocline, facilitates reclosing of the water bottom and the equal sigma surface, lends significant advantages in terms of vertical temperature in the simulation for local deep water with steep terrain, and shortens runtime for 0.14 h. SGZ mixed coordinates are recommended in the simulation of deep lakes or reservoirs wherein the underwater topography is large (with abundant continuous deep trenches or reefs).

     

Fine-resolution mapping of wildfire fuel types for Canada: Fuzzy logic modeling for an Alberta pilot area

The Canadian Forest Fire Danger Rating System (CFFDRS) is used daily across Canada for evaluating forest fire danger. Fuel-type information is one of the inputs required by the models used in the CFFDRS. In this project, three fuel-type maps with a 25 m resolution were produced for a pilot study area located in Alberta using land cover only; land cover and biomass; and, land cover, biomass and leaf area index data derived from satellite imagery. The relationships between inputs and fuel types were determined mainly by the opinions of forest fire scientists and incorporated into a computer program using fuzzy set methodology. Not all the CFFDRS fuel types could be distinguished using these inputs; three of the coniferous types had to be grouped into one common fuel type. Overall accuracy was between 74 and 83% based on ground-truth comparisons. The most accurate map resulted from land cover and biomass data. Detailed accuracy assessment indicated that the overall accuracy increased up to 86% if ambiguous fuel type identification was considered. No combination of inputs was able to define a fuel type with absolute certainty, which is a reflection of differing expert opinions and the small number of inputs used to produce the maps.