A generic system dynamics model for simulating and evaluating the hydrological performance of reconstructed watersheds

International audienceThe mining of oil sands in northern Alberta, Canada, involves the stripping and salvage of surface soil layers to gain access to the oil mines. The oil sands industry has committed to reconstructing these disturbed watersheds to replicate the performance of the natural soil horizons and to reproduce the various functions of natural watersheds. The selection of the texture and thickness of the reconstructed soil cover layers is based primarily on the concept that all covers must have sufficient moisture for vegetation over the growing season. Assessment of the hydrological performance of the reconstructed soil covers is crucial to select the best cover alternative. A generic system dynamics watershed (GSDW) model is developed, based on the existing site-specific SDW model, and applied to five reconstructed watersheds located in the Athabasca mining basin, Alberta, Canada; and one natural watershed (boreal forest) located in Saskatchewan, Canada; to simulate the various hydrological processes; in particular, soil moisture patterns and actual evapotranspiration, in reconstructed and natural watersheds. The model is capable of capturing the dynamics of the water balance components in both reconstructed and natural watersheds. The developed GSDW model provides a vital tool, which enables the investigation of the utility of different soil cover alternative designs and evaluation of their performance. Moreover, the model can be used to conduct short- and long- term predictions under different climate scenarios

NDM-539: IRON ORE MINE WASTE FLOODWATER EXTENT MAPPING UTILIZING REMOTE SENSING DERIVED INDICES

The collapse of two iron ore mine dams in south-eastern Brazil on 5 November 2015 is one of the recent environmental disasters. The clean-up and environment recovery would take several years and cost billions of dollars. Mapping the extent of the affected areas and monitoring the water quality deterioration is a challenge. In this study the new optical satellite SENTINEL 2 imagery along LANDSAT 8 were utilized to test the applicability of the Land Surface Water Index (LSWI) and Modified Normalized Difference Water Index (MNDWI) in the mapping process. The systematic coverage of the study area from the aforementioned satellites before and after the incident were studied and compared. The dynamics of LSWI, MNDWI were utilized in the delineation of the affected areas. Both quantitative and qualitative measures to assess the mine waste floodwater extent were developed. The high reflectance in both the 650-nm and 750-nm wavebands as an indication of Iron-Oxide precipitates occurrence was also tested. The study revealed that the mine tailings extended about 500 Km downstream. The affected areas and extent revealed from the study results were validated against the official figures from the Brazilian government. There was a good agreement between the study results and the published figures. The temporal variation in the Iron-Oxide precipitates occurrence was successfully mapped. In addition, visual interpretation go well with the study results. The findings of this study indicates that the proposed algorithm can be used in the timely mapping of the iron ore mine waste floodwater disaster

A generic system dynamics model for simulating and evaluating the hydrological performance of reconstructed watersheds

A generic system dynamics watershed (GSDW) model is developed and applied to five reconstructed watersheds located in the Athabasca mining basin, Alberta, Canada, and one natural watershed (boreal forest) located in Saskatchewan, Canada, to simulate various hydrological processes in reconstructed and natural watersheds. This paper uses the root mean square error (RMSE), the mean absolute relative error (MARE), and the correlation coefficient (<i>R</i>) as the main performance indicators, in addition to the visual comparison. For the South Bison Hills (SBH), South West Sand Storage (SWSS) and Old Aspen (OA) simulated soil moisture, the RMSE values ranges between 2.5–4.8 mm, and the MARE ranges from 7% to 18%, except for the D2-cover it was 26% for the validation year. The <i>R</i> statistics ranges from 0.3 to 0.77 during the validation period. The error between the measured and simulated cumulative actual evapotranspiration (AET) flux for the SWSS, SBH, and the OA sites were 2%, 5%, and 8%, respectively. The developed GSDW model enables the investigation of the utility of different soil cover designs and evaluation of their performance. The model is capable of capturing the dynamics of water balance components, and may used to conduct short- and long- term predictions under different climate scenarios

Who will dominate the global fossil fuel trade?

Fossil fuels are not distributed evenly throughout the world, and hence the countries rely heavily on international trade to secure energy supply. Characterization of the energy trade network is needed to conduct long-term assessments of energy security. This study proposes a modeling framework to assess the evolution of energy trade under current conditions as well as under future scenarios up to 2050. The total trade of each country is estimated with trade predictive models (TPMs) using key variables. Subsequently, a matrix-balancing method (RAS) is used to estimate the annual bilateral trades. The projected energy trade network in 2050 varies under each shared socioeconomic pathway (SSP) of the future, with annual fossil fuel global trades among countries ranging between 538 and 215 EJ. Canada, USA, Venezuela, and China are projected to dominate the global trade network, with Canada-USA remaining the most dominant fossil fuel trade link up to 2050

Serum S-adenosylmethionine, but not methionine, increases in response to overfeeding in humans

Background: Plasma concentration of the methyl donor S-adenosylmethionine (SAM) is linearly associated with body mass index (BMI) and fat mass. As SAM is a high-energy compound and a sensor of cellular nutrient status, we hypothesized that SAM would increase with overfeeding. Methods: Forty normal to overweight men and women were overfed by 1250 kcal per day for 28 days. Results: Serum SAM increased from 106 to 130 nmol/l (P=0.006). In stratified analysis, only those with weight gain above the median (high-weight gainers; average weight gain 3.9±0.3 kg) had increased SAM (+42%, P=0.001), whereas low-weight gainers (weight gain 1.5±0.2 kg) did not (Pinteraction=0.018). Overfeeding did not alter serum concentrations of the SAM precursor, methionine or the products, S-adenosyl-homocysteine and homocysteine. The SAM/SAH (S-adenosylhomocysteine) ratio was unchanged in the total population, but increased in high-weight gainers (+52%, P=0.006, Pinteraction =0.005). Change in SAM correlated positively with change in weight (r=0.33, P=0.041) and fat mass (r=0.44, P=0.009), but not with change in protein intake or plasma methionine, glucose, insulin or low-density lipoprotein (LDL)-cholesterol. Conclusion: Overfeeding raised serum SAM in proportion to the fat mass gained. The increase in SAM may help stabilize methionine levels, and denotes a responsiveness of SAM to nutrient state in humans. The role of SAM in human energy metabolism deserves further attention.A K Elshorbagy, F Jernerén, D Samocha-Bonet, H Refsum and L K Heilbron

Assessment of agricultural adaptations to climate change from a water-energy-food nexus perspective

Adapting agriculture to climate change without deteriorating natural resources (e.g., water and energy) is critical to sustainable development. In this paper, we first comprehensively evaluate six agricultural adaptations in response to climate change (2021–2050) through the lens of the water-energy-food (WEF) nexus in Saskatchewan, Canada, using a previously developed nexus model—WEF-Sask. The adaptations involve agronomic measures (early planting date, reducing soil evaporation, irrigation expansion), genetic improvement (cultivars with larger growing degree days (GDD) requirement), and combinations of individual adaptations. The results show that the selected adaptations compensate for crop yield losses (wheat, canola, pea), caused by climate change, to various extents. However, from a nexus perspective, there are mixed effects on water productivity (WP), total agricultural water (green and blue) use, energy consumption for irrigation, and hydropower generation. Individual adaptations such as early planting date and increased GDD requirement compensate for yield losses in both rainfed (0–60 %) and irrigated (18–100 %) conditions with extra use of green water (5–7 %), blue water (2–14 %), and energy for irrigation (2–14 %). Reducing soil water evaporation benefits the overall WEF nexus by compensating for rainfed yield losses (25–82 %) with less use of blue water and energy consumption for irrigation. The combination of the above three adaptations has the potential to sustain agricultural production in water-scarce regions. If irrigation expansion is also included, the combined adaptation almost fully offsets agricultural production losses from climate change but significantly increases blue water use (143–174 %) and energy consumption for irrigation while reducing hydropower production (3 %). This study provides an approach to comprehensively evaluating agricultural adaptation strategies, in response to climate change, and insights to inform decision-makers

Quantifying interactions in the water-energy-food nexus: data-driven analysis utilizing a causal inference method

Introduction: There is a pressing need for a holistic approach to optimize water-energy-food (WEF) resources management and to address their interlinkages with other resources due to population growth, socio-economic development, and climate change. However, the structural and spatial extent of the WEF system boundaries cause exponential growth in computational complexity, making exploratory data analysis crucial to obtain insight into the system’s characteristics and focus on critical components. Methods: This study conducts a multiscale investigation of the WEF nexus within the Canadian prairie provinces (Alberta, Saskatchewan, and Manitoba), utilizing causal-correlational analysis and the multispatial Convergence Cross Mapping (mCCM) method. Initially, we employed regression analysis to establish equations, along with their coefficients of determination (R2), to identify patterns among pairs of WEF sectors, gross domestic product (GDP), and greenhouse gas (GHG) emissions. Subsequently, we conducted a causal analysis between correlated pairs using the mCCM method to explore the cause-and-effect relationships between sector pairs within the Canadian prairie provinces; both individually and as a single unit over the period 1990-2020. Results and discussion: Results show that energy and water are the most influential sectors on GHG emissions and GDP in the prairies as a whole. Energy has a stronger influence on GHG compared to water and food sectors, while water has the strongest causal influence on the GDP of Alberta, and food and energy do so for Saskatchewan and Manitoba, respectively. The trade-offs for improving WEF nexus security strongly depend on the scale of the system under investigation, highlighting the need for careful deliberations around boundary judgment for decision-making. This study provides a better understanding of the WEF-GDP-GHG nexus in the Canadian prairies and existing interrelationships among the aforementioned sectors, helping to build more efficient WEF nexus models for further simulation and scenario analysis

Cooperation in a transboundary river basin: a large-scale socio-hydrological model of the Eastern Nile

While conflict-and-cooperation phenomena in transboundary basins have been widely studied, much less work has been devoted to representing the process interactions in a quantitative way. This paper identifies the main factors in the riparian countries' willingness to cooperate in the Eastern Nile River basin, involving Ethiopia, Sudan, and Egypt, from 1983 to 2016. We propose a quantitative model of the willingness to cooperate at the national and river basin scales. Our results suggest that relative political stability and foreign direct investment can explain Ethiopia's decreasing willingness to cooperate between 2009 and 2016. Further, we show that the 2008 food crisis may account for Sudan recovering its willingness to cooperate with Ethiopia. Long-term lack of trust among the riparian countries may have reduced basin-wide cooperation. While the proposed model has some limitations regarding model assumptions and parameters, it does provide a quantitative representation of the evolution of cooperation pathways among the riparian countries, which can be used to explore the effects of changes in future dam operation and other management decisions on the emergence of conflict and cooperation in the basin