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

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

A stochastic reconstruction framework for analysis of water resource system vulnerability to climate-induced changes in river flow regime

Assessments of potential impacts of climate change on water resources systems are generally based on the use of downscaled climate scenarios to force hydrological and water resource systems models and hence quantify potential changes in system response. This approach, however, has several limitations. The uncertainties in current climate and hydrological models can be large, such analyses are rapidly outdated as new scenarios become available, and limited insight into system response is obtained. Here, we propose an alternative methodology in which system vulnerability is analyzed directly as a function of the potential variations in flow characteristics. We develop a stochastic reconstruction framework that generates a large ensemble of perturbed flow series at the local scale to represent a range of potential flow responses to climate change. From a theoretical perspective, the proposed reconstruction scheme can be considered as an extension of both the conventional resampling and the simple delta-methods. By the use of a two-parameter representation of regime change (i.e., the shift in the timing of the annual peak and the shift in the annual flow volume), system vulnerability can be visualized in a two-dimensional map. The methodology is applied to the current water resource system in southern Alberta, Canada, to explore the system's vulnerability to potential changes in the streamflow regime. Our study shows that the system is vulnerable to the expected decrease in annual flow volume, particularly when it is combined with an earlier annual peak. Under such conditions, adaptation will be required to return the system to the feasible operational mode. © 2013. American Geophysical Union. All Rights Reserved

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

The First International Mini-Symposium on Methionine Restriction and Lifespan

It has been 20 years since the Orentreich Foundation for the Advancement of Science, under the leadership Dr. Norman Orentreich, first reported that low methionine (Met) ingestion by rats extends lifespan (Orentreich et al., 1993). Since then, several studies have replicated the effects of dietary methionine restricted (MR) in delaying age-related diseases (Richie et al., 1994; Miller et al., 2005; Ables et al., 2012; Sanchez-Roman and Barja, 2013). We report the abstracts from the First International Mini-Symposium on Methionine Restriction and Lifespan held in Tarrytown, NY, September 2013. The goals were (1) to gather researchers with an interest in MR and lifespan, (2) to exchange knowledge, (3) to generate ideas for future investigations, and (4) to strengthen relationships within this community. The presentations highlighted the importance of research on cysteine, growth hormone (GH), and ATF4 in the paradigm of aging. In addition, the effects of dietary restriction or MR in the kidneys, liver, bones, and the adipose tissue were discussed. The symposium also emphasized the value of other species, e.g., the naked mole rat, Brandt's bat, and Drosophila, in aging research. Overall, the symposium consolidated scientists with similar research interests and provided opportunities to conduct future collaborative studies (Figure 3)

HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community

Recently, deep learning (DL) has emerged as a revolutionary and versatile tool transforming industry applications and generating new and improved capabilities for scientific discovery and model building. The adoption of DL in hydrology has so far been gradual, but the field is now ripe for breakthroughs. This paper suggests that DL-based methods can open up a complementary avenue toward knowledge discovery in hydrologic sciences. In the new avenue, machine-learning algorithms present competing hypotheses that are consistent with data. Interrogative methods are then invoked to interpret DL models for scientists to further evaluate. However, hydrology presents many challenges for DL methods, such as data limitations, heterogeneity and co-evolution, and the general inexperience of the hydrologic field with DL. The roadmap toward DL-powered scientific advances will require the coordinated effort from a large community involving scientists and citizens. Integrating process-based models with DL models will help alleviate data limitations. The sharing of data and baseline models will improve the efficiency of the community as a whole. Open competitions could serve as the organizing events to greatly propel growth and nurture data science education in hydrology, which demands a grassroots collaboration. The area of hydrologic DL presents numerous research opportunities that could, in turn, stimulate advances in machine learning as well.</p

Plasma Metabolomic Profiles Reflective of Glucose Homeostasis in Non-Diabetic and Type 2 Diabetic Obese African-American Women

Insulin resistance progressing to type 2 diabetes mellitus (T2DM) is marked by a broad perturbation of macronutrient intermediary metabolism. Understanding the biochemical networks that underlie metabolic homeostasis and how they associate with insulin action will help unravel diabetes etiology and should foster discovery of new biomarkers of disease risk and severity. We examined differences in plasma concentrations of >350 metabolites in fasted obese T2DM vs. obese non-diabetic African-American women, and utilized principal components analysis to identify 158 metabolite components that strongly correlated with fasting HbA1c over a broad range of the latter (r = −0.631; p<0.0001). In addition to many unidentified small molecules, specific metabolites that were increased significantly in T2DM subjects included certain amino acids and their derivatives (i.e., leucine, 2-ketoisocaproate, valine, cystine, histidine), 2-hydroxybutanoate, long-chain fatty acids, and carbohydrate derivatives. Leucine and valine concentrations rose with increasing HbA1c, and significantly correlated with plasma acetylcarnitine concentrations. It is hypothesized that this reflects a close link between abnormalities in glucose homeostasis, amino acid catabolism, and efficiency of fuel combustion in the tricarboxylic acid (TCA) cycle. It is speculated that a mechanism for potential TCA cycle inefficiency concurrent with insulin resistance is “anaplerotic stress” emanating from reduced amino acid-derived carbon flux to TCA cycle intermediates, which if coupled to perturbation in cataplerosis would lead to net reduction in TCA cycle capacity relative to fuel delivery

Emerging Themes and Future Directions of Multi-Sector Nexus Research and Implementation

Water, energy, and food are all essential components of human societies. Collectively, their respective resource systems are interconnected in what is called the “nexus”. There is growing consensus that a holistic understanding of the interdependencies and trade-offs between these sectors and other related systems is critical to solving many of the global challenges they present. While nexus research has grown exponentially since 2011, there is no unified, overarching approach, and the implementation of concepts remains hampered by the lack of clear case studies. Here, we present the results of a collaborative thought exercise involving 75 scientists and summarize them into 10 key recommendations covering: the most critical nexus issues of today, emerging themes, and where future efforts should be directed. We conclude that a nexus community of practice to promote open communication among researchers, to maintain and share standardized datasets, and to develop applied case studies will facilitate transparent comparisons of models and encourage the adoption of nexus approaches in practice