Polynomial Surrogates for Open-Channel Flows in Random Steady State

Assessing epistemic uncertainties is considered as a milestone for improving numerical predictions of a dynamical system. In hydrodynamics, uncertainties in input parameters translate into uncertainties in simulated water levels through the shallow water equations. We investigate the ability of generalized polynomial chaos (gPC) surrogate to evaluate the probabilistic features of water level simulated by a 1-D hydraulic model (MASCARET) with the same accuracy as a classical Monte Carlo method but at a reduced computational cost. This study highlights that the water level probability density function and covariance matrix are better estimated with the polynomial surrogate model than with a Monte Carlo approach on the forward model given a limited budget of MASCARET evaluations. The gPC-surrogate performance is first assessed on an idealized channel with uniform geometry and then applied on the more realistic case of the Garonne River (France) for which a global sensitivity analysis using sparse least-angle regression was performed to reduce the size of the stochastic problem. For both cases, Galerkin projection approximation coupled to Gaussian quadrature that involves a limited number of forward model evaluations is compared with least-square regression for computing the coefficients when the surrogate is parameterized with respect to the local friction coefficient and the upstream discharge. The results showed that a gPC-surrogate with total polynomial degree equal to 6 requiring 49 forward model evaluations is sufficient to represent the water level distribution (in the sense of the \(\ell _2\) norm), the probability density function and the water level covariance matrix for further use in the framework of data assimilation. In locations where the flow dynamics is more complex due to bathymetry, a higher polynomial degree is needed to retrieve the water level distribution. The use of a surrogate is thus a promising strategy for uncertainty quantification studies in open-channel flows and should be extended to unsteady flows. It also paves the way toward cost-effective ensemble-based data assimilation for flood forecasting and water resource management.     

Influence of community-based natural resource management strategies in the resilience of social-ecological systems

Different social-ecological systems around the world are managed under community-based natural resource management (CBNRM) strategies. This paper analyses how CBNRM strategies influence the resilience of social-ecological systems to the disturbances they face, drawing upon the experience of three Latin American cases (two in Mexico and one in Colombia). The cases differ in their CBNRM approach and in the time these governance systems have been in place. By using a mixed-method approach, we review the socio-ecological history and describe each CBNRM characteristics. We then assess their resilience to socioeconomic and environmental disturbances through a set of indicators. We found that CBNRM strategies influence positively and negatively resilience and that internal decisions might address important threats. On the positive side, the social-ecological systems with longer tradition of CBNRM and more local buy-in of commonly agreed objectives appear to be more resilient to environmental challenges. But, internal governance factors such as power imbalances, poor income distribution, and gender inequities linked to CBNRM undermine resilience and foster out migration. Finally, communities appear to have limited capacities to cope with external disturbances such as global drivers of change or national policies that negatively affect their social-ecological resilience.

     

Correction to: Influence of community-based natural resource management strategies in the resilience of social-ecological systems

Regional Environmental Change - The published online version contains mistake. Author name was incorrectly captured. Instead of Maria del Mar Delgado-Serrano was incorrectly captured as Ma del Mar...     

From mixed farming to intensive agriculture: energy profiles of agriculture in Quebec,Canada, 1871–2011

Regional Environmental Change - This article presents an energy analysis of Quebec agroecoystems at five periods of time: 1871, 1931, 1951, 1981, and 2011, calculating for each year the various...     

Trees on the move: using decision theory to compensate for climate change at the regional scale in forest social-ecological systems

Regional Environmental Change - The adaptation of social-ecological systems such as managed forests depends largely on decisions taken by forest managers who must choose among a wide range of...     

From vineyards to feedlots: a fund-flow scanning of sociometabolic transition in the Vallès County (Catalonia) 1860–1956–1999

Regional Environmental Change - We analyse the changes to agricultural metabolism in four municipalities of Vallès County (Catalonia, Iberia) by accounting for their agroecosystem funds and...     

A Mathematical Model for the Effects of Fertilization on Nitrogen Concentrations in Unsaturated Soil on Blueberry Farms in Southern New Jersey

Nitrogen is commonly known as a food source for crops. However, the nitrogen compounds used in crop fertilizers, most commonly nitrate (NO₃) and ammonium (NH₄), are not widely understood. Blueberry plants do not take up these compounds as efficiently as organic nitrogen so varying amounts of leaching into the soil and groundwater will occur. A biogeochemical model consisting of ordinary and partial differential equations is implemented to computationally predict the concentrations of nitrate and ammonium in unsaturated soil of blueberry plants, specifically in the southern region of New Jersey. The model takes into account the type of soil of the region, the nitrate uptake of the plant, the water content in the roots region, the pressure heads in the soil pores, and the application rates of fertilizers containing nitrate, ammonium, and organic nitrogen. Computational simulations demonstrate that the model accounts for natural processes and, in addition, show that commonly used fertilizer application rates cause unnecessarily high concentrations of both nitrate and ammonium in the unsaturated soil level. Further, simulations show that decreasing nitrate fertilizer applications by 85.7% in annual and 91.8% in bi-annual schedules provides an optimal system for safe reapplication.     

Sustainability indicators in the swine industry of the Brazilian State of Santa Catarina

In recent decades, there has been a growing concern about measuring and evaluating the results of intensive production practices, such as the mode of integration practiced on a large scale by agro-industries. The present study discusses the application and the results of a Sustainability Indicators System in the context of the swine industry in the Brazilian State of Santa Catarina. These indicators, focused on the level of sustainability maturity, can be used as a way to diagnose and compare the efficiency of the industry from a broader perspective. The research findings indicate that most of the pig farms that have been studied can be classified as “in search of sustainability or sustainable.” Nevertheless, there are differences among the dimensions and between the most ranked farms and the others which must be considered for a better design and application of public policies and company strategies toward an effective and balanced social, economic and environmental sustainability.     

Assessing strategies to mitigate phosphorus leaching from drained clay soils

Assessing mitigation of phosphorus (P) leaching from subsurface drainage systems is challenging due to high spatial and temporal variation in leaching. Mean measured total P leaching from a clayey soil in an eight-year study period (four replicates per treatment) was (kg ha^?1 year^?1): 1.21 from shallow autumn tillage (ShT), 0.84 from unfertilised fallow (UF), 0.81 from conventional autumn ploughing (CT) and 0.57 from structure liming (SL–CT). Treatment was not significant using Richards–Baker flow index or a distance factor as covariate (p = 0.084 and 0.057). A tendency for lower leaching was obtained comparing SL-CT with ShT (p _adjusted = 0.060 and 0.009 respectively). A combination of measures adapted to drainage conditions and clay content in different parts of the field is proposed since P leaching was approximately halved from an adjacent field (4.3 ha) in a three-year post-period compared with a three-year pre-period for structure liming the entire field and drainage system renovation plus structure lime drain backfilling.