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.     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

Backwater Confluences of the Ohio River: Organic and Inorganic Fingerprints Explain Sediment Dynamics in Wetlands and Marinas

In the Ohio River (OR), backwater confluence sedimentation dynamics are understudied, however, these river features are expected to be influential on the system’s ecological and economic function when integrated along the river’s length. In the following paper, we test the efficacy of organic and inorganic tracers for sediment fingerprinting in backwater confluences; we use fingerprinting results to evidence sediment dynamics controlling deposition patterns in confluences used for wetland and marina functions; and we quantify the spatial extent of tributary drainages with wetland and marina features in OR confluences. Both organic and inorganic tracers statistically differentiate sediment from stream and river end‐members. Carbon and nitrogen stable isotopes produce greater uncertainty in fingerprinting results than inorganic elemental tracers. Uncertainty analysis of the nonconservative tracer term in the organic matter fingerprinting application estimates an apparent enrichment of the carbon stable isotopes during instream residence, and the nonconservativeness is quantified with a statistical approach unique to the fingerprinting literature. Wetland and marina features in OR confluences impact 42% and 11% of tributary drainage areas, respectively. Sediment dynamics show wetland and marina confluences experience deposition from river backwaters with longitudinally linear and nonlinear patterns, respectively, from sediment sources.     

Adaptation of Climate Model Projections of Streamflow to Account for Upstream Anthropogenic Impairments

A statistical procedure is developed to adjust natural streamflows simulated by dynamical models in downstream reaches, to account for anthropogenic impairments to flow that are not considered in the model. The resulting normalized downstream flows are appropriate for use in assessments of future anthropogenically impaired flows in downstream reaches. The normalization is applied to assess the potential effects of climate change on future water availability on the Rio Grande at a gage just above the major storage reservoir on the river. Model‐simulated streamflow values were normalized using a statistical parameterization based on two constants that relate observed and simulated flows over a 50‐year historical baseline period (1964–2013). The first normalization constant is a ratio of the means, and the second constant is the ratio of interannual standard deviations between annual gaged and simulated flows. This procedure forces the gaged and simulated flows to have the same mean and variance over the baseline period. The normalization constants can be kept fixed for future flows, which effectively assumes that upstream water management does not change in the future, or projected management changes can be parameterized by adjusting the constants. At the gage considered in this study, the effect of the normalization is to reduce simulated historical flow values by an average of 72% over an ensemble of simulations, indicative of the large fraction of natural flow diverted from the river upstream from the gage. A weak tendency for declining flow emerges upon averaging over a large ensemble, with tremendous variability among the simulations. By the end of the 21st Century the higher‐emission scenarios show more pronounced declines in streamflow.     

Sanitation workers at the frontline: work and vulnerability in response to COVID-19

ABSTRACT

The absence of a vaccine and effective treatment for COVID-19 has created public panic and burdened the health systems in most countries. Along with health workers’, sanitation personnel are also working at the frontlines in the war against the disease by keeping cities clean. Sanitation workers are engaged in Drudgery, Dangerous, Dirty and Dehumanising work that makes them vulnerable for developing the chronic respiratory diseases due to the exposure of various hazardous materials and toxic gases that are emitted from the solid waste. The sanitation workers working on a contractual basis are excluded from the labour policies and welfare programs who are playing a vital role in fighting the pandemic. Women sanitation workers are even more vulnerable because most of them are non-literate, poor in financial management and under-represented in the sanitation employee’s union. The local and state governments should protect and safeguard sanitation workers by providing them with adequate protective equipment, ensure payment of paying adequate salaries and provide them with health insurance.     

Natural gas engine driven heat pump system – a case study of an office building

ABSTRACT

An eQUEST model was developed to conduct a simulation study of a natural gas engine-driven heat pump (GEHP) for an office building in Woodstock, Ontario, Canada. Prior to the installation of the GEHP, the heating and cooling demands of the office building were provided by rooftop units (RTUs), comprising of natural gas heater and electric air conditioner. Energy consumption for both GEHP and RTUs were monitored for operation in alternating months. These recorded energy consumptions along with weather data were used in the regression analysis. The developed eQUEST models were validated and calibrated with the regression analysis results with respect to the ASHRAE Guideline 14–2014. The eventual models were then applied to investigate the potential annual energy consumption, greenhouse gas (GHG) emission and energy cost savings achieved by using the GEHP in Woodstock, and other cities in Canada, particularly in Ontario.     

Searching for Networks: Ecological Connectivity for Amphibians Under Climate Change

Environmental Management - Ecological connectivity depends on key elements within the landscape, which can support ecological fluxes, species richness and long-term viability of a biological...     

An evaluation of in situ microcosms for validating aquatic fate and transport models

The fates of two compounds, 2,4 Dichlorophenoxy Acetic Acid Butoxyethyl Ester (2,4-DBEE) and 1,4 Dichlorobenzene (1,4-DCB), were examined in in situ microcosms placed in a pond and compared with the fates in the pond itself. Results also were compared with predictions of an aquatic fate and transport model (EXAMS). Decay rates of 2,4-DBEE were not significantly different among the microcosms, pond and model predictions. The decay rate of 1,4-DCB in the microcosms was significantly lower than the rate for the pond, and lower than the rate predicted by the model. The low volatility of 1,4-DCB in the microcosms is attributed primarily to lack of water surface turbulence in the microcosms.     

Phototransformation of <Emphasis Type="SmallCaps">l</Emphasis>-tryptophan and formation of humic substances in water

Humic substances are poorly known, though they represent a major pool of non-biotic organic carbon on earth. In particular, there is little knowledge on the formation of humic substances by irradiation of organic matter dissolved in waters. Specifically, it is known that humic substances can be formed from proteins by photochemical processes in surface waters, but the role of single amino acids and their transformation pathways are not yet known. Therefore, here we studied the phototransformation of aqueous l-tryptophan under simulated sunlight. Irradiated l-tryptophan solutions were analyzed by absorption, fluorescence, nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopies, chromatography, potentiometry and mass spectrometry (MS). The solutions appeared turbid after irradiation; therefore, nephelometry and dynamic laser light scattering were used to characterize the suspended particles. Results show that about 95% of l-tryptophan was degraded in 8-h irradiation, undergoing deamination and decarboxylation of the amino acidic moieties to release ammonium and formate. The MS signal at m/z 146 suggests the formation of 3-ethylindole, while pH-metric and NMR data revealed the presence of hydroxylated compounds. The phototransformation intermediates of l-tryptophan had fluorescence and absorption spectra similar to those of humic substances, they were able to produce ^·OH upon irradiation and tended to aggregate by both ionic and hydrophobic interactions. Overall, our findings reveal for the first time the nature of products formed upon phototransformation of l-tryptophan. Interestingly, the transformation of l-tryptophan is quite different from that of the previously studied l-tyrosine, although both compounds produce humic-like materials under irradiation.