Validation de nouvelles perspectives pour le dimensionnement des techniques de traitement des eaux pluviales par comparaison d'un modèle de dimensionnement à HEC-HMS

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Blue and grey urban water footprints through citizens’ perception and time series analysis of Brazilian dynamics

This is an Accepted Manuscript of an article published by Taylor & Francis in Hydrological Sciences Journal on 4 March 2021, available online: https://doi.org/10.1080/02626667.2021.1879388Predicting future water demands of societies is a major challenge because it involves a holistic understanding of possible changes within socio-hydrological systems. Although recent research has made efforts to translate social dimensions into the analysis of hydrological systems, few studies have involved citizen participation in water footprint analysis. This paper integrates time series with citizens’ perceptions, knowledge and beliefs concerning sanitation elements to account for municipal blue and grey water footprints in São Carlos, Brazil, from 2009 to 2016, and potential water footprints in 2030 and 2050. In this case study, grey footprint potentially exceeds the blue water footprint by up to 35 times, and volunteered information suggested a reduction in water consumption, larger garbage production and greater investment in sanitation infrastructure from authorities. We conclude that public knowledge can be used to delineate possible water footprint scenarios and reveal paradoxes in the coevolution of socio-hydrological systems on an urban scale

Mitigating Drought Financial Risk for Water Supply Sector through Index-Based Insurance Contracts

Drought management strategies have primarily focused on structural measures, which are insufficient to prevent water supply disruptions and economic losses. In this concept, adaptation entails anticipating the negative financial consequences of extreme weather events and taking appropriate measures to prevent and mitigate them. As a result, insurance is a valuable adaptation measure for compensating unexpected losses and preventing financial damage from becoming long-term economic damage. We simulated indexed insurance for the Cantareira Water Supply System (CWSS). The system is responsible for providing water to 7.2 million people in the Metropolitan Region of São Paulo (MRSP). Our methodology consists of three steps: (1) describing the indexed variable, (2) computing economic losses depending on event magnitude, and (3) evaluating risk premiums for low, medium, and high coverage levels. According to our findings, an annual fee (premium) of USD 0.43, 0.87, and 1.73 should be charged per person to obtain drought coverage for 3, 6, and 12 months (low, medium, and high levels), respectively. These values account for 1.7 %, 3.4 %, and 6.7 % of the annual costs paid by CWSS-supplied users, accordingly. The premium fee can be incorporated into water bills as a novel technique to pool the risk between supplied users and the utility, thereby protecting them against surcharge fluctuations.</p

Modeling freshwater quality scenarios with ecosystem-based adaptation in the headwaters of the Cantareira system, Brazil

Although hydrologic models provide hypothesis testing of complex dynamics occurring at catchments, freshwater quality modeling is still incipient at many subtropical headwaters. In Brazil, a few modeling studies assess freshwater nutrients, limiting policies on hydrologic ecosystem services. This paper aims to compare freshwater quality scenarios under different land-use and land-cover (LULC) change, one of them related to ecosystem-based adaptation (EbA), in Brazilian headwaters. Using the spatially semi-distributed Soil and Water Assessment Tool (SWAT) model, nitrate, total phosphorous (TP) and sediment were modeled in catchments ranging from 7.2 to 1037&thinsp;km2. These headwaters were eligible areas of the Brazilian payment for ecosystem services (PES) projects in the Cantareira water supply system, which had supplied water to 9 million people in the São Paulo metropolitan region (SPMR). We considered SWAT modeling of three LULC scenarios: (i) recent past scenario (S1), with historical LULC in 1990; (ii) current land-use scenario (S2), with LULC for the period 2010–2015 with field validation; and (iii) future land-use scenario with PES (S2&thinsp;+&thinsp;EbA). This latter scenario proposed forest cover restoration through EbA following the river basin plan by 2035. These three LULC scenarios were tested with a selected record of rainfall and evapotranspiration observed in 2006–2014, with the occurrence of extreme droughts. To assess hydrologic services, we proposed the hydrologic service index (HSI), as a new composite metric comparing water pollution levels (WPL) for reference catchments, related to the grey water footprint (greyWF) and water yield. On the one hand, water quality simulations allowed for the regionalization of greyWF at spatial scales under LULC scenarios. According to the critical threshold, HSI identified areas as less or more sustainable catchments. On the other hand, conservation practices simulated through the S2&thinsp;+&thinsp;EbA scenario envisaged not only additional and viable best management practices (BMP), but also preventive decision-making at the headwaters of water supply systems.</p

Performance analysis of physically-based (HEC-RAS, CADDIES) and AI-based (LSTM) flood models for two case studies

Megacities in developing countries are commonly affected by flooding events. The use of flood models can contribute to an evidence-based decision-making process. For a good representation, these models require physical data for catchment parameterization, and observed data for calibration and validation, which is often scarce. In this study, we analysed the performance results of physically-based (HEC-RAS, CADDIES) and AI-based (LSTM) flood models for two case studies: the Narmada basin in India and the Aricanduva catchment in Brazil. The models were evaluated for accuracy, interpretability, running time, and complexity.</p

Nitric oxide sensing in plants is mediated by proteolytic control of group VII ERF transcription factors

Nitric oxide (NO) is an important signaling compound in prokaryotes and eukaryotes. In plants, NO regulates critical developmental transitions and stress responses. Here, we identify a mechanism for NO sensing that coordinates responses throughout development based on targeted degradation of plant-specific transcriptional regulators, the group VII ethylene response factors (ERFs). We show that the N-end rule pathway of targeted proteolysis targets these proteins for destruction in the presence of NO, and we establish them as critical regulators of diverse NO-regulated processes, including seed germination, stomatal closure, and hypocotyl elongation. Furthermore, we define the molecular mechanism for NO control of germination and crosstalk with abscisic acid (ABA) signaling through ERF-regulated expression of ABSCISIC ACID INSENSITIVE5 (ABI5). Our work demonstrates how NO sensing is integrated across multiple physiological processes by direct modulation of transcription factor stability and identifies group VII ERFs as central hubs for the perception of gaseous signals in plants

The Cys-Arg/N-end rule pathway is a general sensor of abiotic stress in flowering plants

Abiotic stresses impact negatively on plant growth, profoundly affecting yield and quality of crops. Although much is known about plant responses, very little is understood at the molecular level about the initial sensing of environmental stress. In plants, hypoxia (low oxygen, which occurs during flooding) is directly sensed by the Cys-Arg/N-end rule pathway of ubiquitin-mediated proteolysis, through oxygen-dependent degradation of group VII Ethylene Response Factor transcription factors (ERFVIIs) via amino-terminal (Nt-) cysteine [1, 2]. Using Arabidopsis (Arabidopsis thaliana) and barley (Hordeum vulgare), we show that the pathway regulates plant responses to multiple abiotic stresses. In Arabidopsis, genetic analyses revealed that response to these stresses is controlled by N-end rule regulation of ERFVII function. Oxygen sensing via the Cys-Arg/N-end rule in higher eukaryotes is linked through a single mechanism to nitric oxide (NO) sensing [3, 4]. In plants, the major mechanism of NO synthesis is via NITRATE REDUCTASE (NR), an enzyme of nitrogen assimilation [5]. Here, we identify a negative relationship between NR activity and NO levels and stabilization of an artificial Nt-Cys substrate and ERFVII function in response to environmental changes. Furthermore, we show that ERFVIIs enhance abiotic stress responses via physical and genetic interactions with the chromatin-remodeling ATPase BRAHMA. We propose that plants sense multiple abiotic stresses through the Cys-Arg/N-end rule pathway either directly (via oxygen sensing) or indirectly (via NO sensing downstream of NR activity). This single mechanism can therefore integrate environment and response to enhance plant survival

Additive scales in degenerative disease - calculation of effect sizes and clinical judgment

<p>Abstract</p> <p>Background</p> <p>The therapeutic efficacy of an intervention is often assessed in clinical trials by scales measuring multiple diverse activities that are added to produce a cumulative global score. Medical communities and health care systems subsequently use these data to calculate pooled effect sizes to compare treatments. This is done because major doubt has been cast over the clinical relevance of statistically significant findings relying on <it>p </it>values with the potential to report chance findings. Hence in an aim to overcome this pooling the results of clinical studies into a meta-analyses with a statistical calculus has been assumed to be a more definitive way of deciding of efficacy.</p> <p>Methods</p> <p>We simulate the therapeutic effects as measured with additive scales in patient cohorts with different disease severity and assess the limitations of an effect size calculation of additive scales which are proven mathematically.</p> <p>Results</p> <p>We demonstrate that the major problem, which cannot be overcome by current numerical methods, is the complex nature and neurobiological foundation of clinical psychiatric endpoints in particular and additive scales in general. This is particularly relevant for endpoints used in dementia research. 'Cognition' is composed of functions such as memory, attention, orientation and many more. These individual functions decline in varied and non-linear ways. Here we demonstrate that with progressive diseases cumulative values from multidimensional scales are subject to distortion by the limitations of the additive scale. The non-linearity of the decline of function impedes the calculation of effect sizes based on cumulative values from these multidimensional scales.</p> <p>Conclusions</p> <p>Statistical analysis needs to be guided by boundaries of the biological condition. Alternatively, we suggest a different approach avoiding the error imposed by over-analysis of cumulative global scores from additive scales.</p

Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts

As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and feedbacks in complex human–water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed and in the quantity of socio-hydrological data. The benchmark dataset comprises (1) detailed review-style reports about the events and key processes between the two events of a pair; (2) the key data table containing variables that assess the indicators which characterize management shortcomings, hazard, exposure, vulnerability, and impacts of all events; and (3) a table of the indicators of change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators of change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses, e.g. focused on causal links between risk management; changes in hazard, exposure and vulnerability; and flood or drought impacts. The data can also be used for the development, calibration, and validation of sociohydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al., 2023, https://doi.org/10.5880/GFZ.4.4.2023.001)