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Global performance for all clusters, represented here by their linguistic descriptors (Table 1), and considering four performance criteria, annual number of failures regarding flood control, recreational use and ecological flow, and annual en.ergy production.
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Climate change can significantly affect water systems with negative impacts on many facets of society and ecosystems. Therefore, significant attention must be devoted to the development of efficient adaptation strategies. More specifically, the reoperation of water resources systems to keep the overall performance within acceptable limits should be...
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... the adapted guide curve for Kiamika's reservoir for cluster 5 (strong seasonality scenarios), prescribed by the optimization model. We can see that the adaptation adjusts the drawdown-refill cycle to account for a stronger seasonality and earlier spring snowmelt. Fig. 7. Comparison of official and adapted guide curves at Kiamika Reservoir. Fig. 8 shows the performances associated with the current operating policy for each cluster identified by its linguistic descriptor as listed in Table 1: no-change, large annual volume, moderate seasonality, low annual volume and strong seasonality. Each point corresponds to the performance achieved for each one of the 828 30-year future ...
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... catchment of Raba River to the drinking water reservoir Dobczyce in Poland; their calculations showed 1i) a large variability of the sediment load between months and (2) the predicted climate changes will cause a significant increase of mineral fraction loads (silt and clay) during months with high flows. Sant Anna et al. [30] presented a hydrologically-driven approach to climate change adaptation aiming at supporting the reoperation of D&R systems that is organized around (1) the use of a large ensemble of GCM hydro-climate projections to drive a climate stress test, (2) the bottomup clustering of those hydrologic projections based on hydrologic attributes that are both relevant to the region of interest and interpretable by the operators, and (3) the identification of adaptation measures for each cluster after developing a one-way coupling of an optimization model with a simulation model. The climate impact assessment was illustrated with the multipurpose multireservoir system of the Lievre River basin in Quebec in Canada and their results showed that cluster-5 of 44 specific, adapted, operating rules can improve the performance of the system and reveal its operational flexibility with respect to the different operating objectives. ...
Dam and Reservoir (D&R) systems during their long history suffered from hundreds of failures, whose mechanisms are accelerated by climate change. To assess the vulnerability of D&R systems to climate change a methodology is presented based on literature that is consistent with the EC technical guidelines. This methodology includes (i) the typologization of the groups of the potential climate hazards, the components of the D&R systems, and the impacts of the groups of hazards on D&R systems, and (ii) the presentation of climate indicators that are usually employed in D&R systems. The typologization of the methodology facilitates its fast application and its comparison with other methodologies. The methodology is applied to the Almopeos D&R system in Greece. Three General Circulation Model and Regional Climate Model combinations from the EURO-CORDEX ensemble are selected, bias-corrected against ERA5Land and used to estimate the values of the selected indicators and thus to quantify the potential climate impacts. The vulnerability analysis identified three groups of climate hazards that are (i) temperature increase and extreme heat, (ii) precipitation decrease, aridity and droughts and (iii) extreme precipitation and flooding, as potential significant hazards, for which a detailed risk assessment is required to propose the required adaptation strategies.
... This approach enables a more nuanced assessment of climate change impacts and priority policies and engages stakeholders in climate-related decision-making (Kuang & Liao, 2020;Poff et al., 2016). In contrast, the topdown approach evaluates the performance of water resource systems based on a set of global climate projections, typically downscaled to represent local conditions, making it unsuitable for identifying thresholds of performance with respect to changes in climate exposure (Sant'Anna et al., 2022). In our study, the bottom-up approach depends on a locally relevant integrated hydro-economic model to characterize and assess the system performance with regard to future climate projections. ...
... It was first proposed by Pereira and Pinto (1991) to solve the hydro-thermal scheduling problem in Brazil. Like any Dynamic Programming algorithm, SDDP converts the original sequential decision-making problem into a sequence of one-stage problems that are solved recursively (Sant'Anna et al., 2022). In this study, we extend the application of the SDDP approach beyond its traditional use for the operation of single or few reservoirs, in order to assess the probabilistic trade-offs between multiple sectors and agricultural intra-sectors across their spatial locations in a large river basin spanning multiple jurisdictions under future climate conditions. ...
Pressures on water resources are fueling conflicts between sectors. This trend will likely worsen under future climate‐induced water stress, jeopardizing food, energy and human water security in most arid and semi‐arid regions. Probabilistic analysis using stochastic optimization modeling can characterize multi‐sector vulnerabilities and risks associated with future water stress. This study identifies the probabilistic trade‐offs between agricultural, urban and energy sectors in the Ebro Basin (Spain). Two intervention policies have been examined and compared: (a) agricultural priority, and (b) energy priority, for two planning horizons 2040–2070 and 2070–2100. Results show that the human water security goal is achieved under both intervention policies. However, the achievement of the food and energy security goals depends on the policy objectives and on the spatial location of irrigation schemes and hydropower plants, which result in different stream flows across the basin. The policy choice results in substantially different benefit gains and losses by sector and therefore by location. None of the sectoral production priority policy provides an equitable sharing of benefits among all sectors and locations under climate change, which is an important issue, because the success or failure of policy interventions would depend on the distribution of the gains and losses of benefits across the basin. Policy uptake by stakeholders would depend on reaching win‐win outcomes where losers are compensated, while delivering acceptable levels of food, energy and human water security in large river basins. Information on the probabilistic trade‐offs contributes to the design of water management strategies capable of addressing the multi‐sector vulnerability.
... Since the overall behavior of six different groups is known, it would be easier for decision-makers to develop mitigating plans and define priorities (Viviroli et al., 2011). These mitigation plans should rely on investing in measures to build resilience to the impacts of climate change, such as improving infrastructure (Dong et al., 2019;Kolokytha & Malamataris, 2020;Sant'Anna et al., 2022), strengthening natural systems (Fossey & Rousseau, 2016;Hessen & Vandvik, 2022), and diversifying supply chains of food and water (Gomez et al., 2021;Zeff et al., 2014). Looking at the intra-annual variability, enhancement of forecast models may take advantage of the hydrological similarity of groups, adjusting and developing models specifically for each group rather than relying on generalized models that fail to capture the unique characteristics and peculiarities of hydrological behavior. ...
Despite hosting ∼16% of the global freshwater and almost 50% of water resources in South America, Brazilian catchment‐scale relationships between drivers and streamflow are still poorly understood. Here, we used streamflow signatures and attributes of 735 catchments from the Catchment Attributes for Brazil data set to investigate the dominant hydrological processes for the catchments. We also assess how catchments group based on hydrologic behavior similarities and analyze which climatic/landscape attributes control the streamflow variability. To classify and group the catchments, we used the k‐means method optimized by the Elbow approach, along with a Principal Component Analysis. Uncertainty on catchment grouping was checked by k‐fold cross‐validation. Then, we used a recursive feature elimination using the random forest technique to assess the most influential catchment attributes to the hydrological signatures. Our results revealed six similarity groups, which followed mainly an aridity gradient ranging from the wettest to the driest, but also seasonality. The climate is the primary driver of hydrological behavior for the water‐limited groups, highlighting the influence and importance of the atmospheric demand in several Brazilian catchments. High soil storage capacity in energy‐limited catchments associated with high precipitation led to high discharge all year due to the subsurface fluxes' contribution. Our findings may be useful to improve streamflow predictability and hydrological behavior identification by further understanding hydrological similarities and their signatures due to catchment landscape characteristics. Further, by employing an easily reproducible methodology and clear metrics to weigh uncertainty, our study provides a significant step toward establishing a catchment‐scale common classification system.
... Since the overall behavior of six different groups is known, it would be easier for decision-makers to develop mitigating plans and define priorities (Viviroli et al., 2011). These mitigation plans should rely on investing in measures to build resilience to the impacts of climate change, such as improving infrastructure (Dong et al., 2019;Kolokytha & Malamataris, 2020;Sant'Anna et al., 2022), strengthening natural systems (Fossey & Rousseau, 2016;Hessen & Vandvik, 2022), and diversifying supply chains of food and water (Gomez et al., 2021;Zeff et al., 2014). Looking at the intra-annual variability, enhancement of forecast models may take advantage of the hydrological similarity of groups, adjusting and developing models specifically for each group rather than relying on generalized models that fail to capture the unique characteristics and peculiarities of hydrological behavior. ...
Brazil hosts approximately 16% of the global freshwater and almost 50% of water resources in South America. However, the catchment-scale relationships between drivers and streamflow are still poorly understood. In this paper, the dominant hydrological processes for the Brazilian catchments were investigated. Additionally, were explored how these catchments can be categorized based on their hydrologic similarities, pointing the key climatic and landscape attributes influencing streamflow variability. There were used streamflow signatures and attributes of 735 catchments from the Catchment Attributes for Brazil (CABra) dataset along with machine learning techniques. The main results revealed six distinct similarity groups, primarily aligned with an aridity gradient ranging from the wettest to the driest. Climate emerged as the primary driver of hydrological behavior for the “dry” groups, highlighting the influence and importance of land-atmosphere interactions in Brazilian catchments. Conversely, catchments within the “wet” groups, characterized by high soil storage capacity and high precipitation, exhibit consistently high discharge levels throughout the year, primarily attributable to subsurface flux contributions. The findings obtained here may be useful to improve streamflow predictability by further understanding hydrological similarities and their signatures due to catchment landscape characteristics. Aside, this study may provide a significant step toward a unified global catchment-scale classification system, due to Brazil’s diverse hydroclimate and landscapes, the relatively easy and reproducible methodology, and clear metrics to weigh uncertainty.
... Considering the inherent uncertainty associated to climate change and its impact on the flow regime, it is best to carry out this adaptation exercise on several potential alterations of the flow regime. The result is a portfolio of adapted reservoir operating policies and their performances expressed, for example, in terms of hydropower generation, food production, water supply reliability, etc. Analyzing this portfolio then reveals the adaptive capacity of the system to potential alterations of the flow regime (Sant'Anna et al., 2022). ...
... Adapting reservoir operations to climate change is challenging and involves understanding and integrating various approaches (Herman et al., 2020). In academic discussions, the main focus has mainly been on three different approaches: top-down (Arnell, 2004;Brekke et al., 2009), bottom-up (Brown andWilby, 2012), and a more recently-developed, hydrologically driven approach (Sant'Anna et al., 2022;Pulido-Velazquez et al., 2022). The top-down approach focuses on formulating adaptation strategies based on the performance of water resource systems under a selected set of climate projections from global or regional models (Arnell, 2004). ...
... The top-down approach focuses on formulating adaptation strategies based on the performance of water resource systems under a selected set of climate projections from global or regional models (Arnell, 2004). Due to the discrete nature of these projections, this approach is often ill-suited for detecting performance thresholds under deep uncertainty related to climate change (Culley et al., 2016;Sant'Anna et al., 2022). The bottom-up approach rather seeks to identify robust solutions, i.e. solutions that will perform relatively well across a wide range of hydrologic conditions independently from climate models' projections Lachaut et al., 2022). ...
Large-scale climate variability patterns such as El Niño-Southern Oscillation (ENSO) influence the hydrology and hence affect the management of water resources in numerous regions around the globe. The presence of multiyear drought and wet periods is already challenging as these long, extreme, events tend to stress water resources systems much more than multiple, isolated, ones. This manuscript presents a variant of a hydrologically-driven approach to assess the performance of large-scale water resources systems in regions where the long-term persistence that characterizes the flow regime is likely to be affected by climate change. This approach comprises several steps including the construction of a large ensemble of hydrological projections which are bias-corrected in the frequency domain to account for the long-term persistence; the clustering of these projections based on hydrologic attributes to identify likely alterations of the flow regime; and the use of an optimization model to derive allocation policies tailored to identified alterations of the flow regime. The proposed approach is tested on the Senegal River basin which has experienced multiyear dry, normal, and wet periods in the past. The analysis of allocation policies highlights the relevance of climate-tailored policies in adapting to climate change, with climate tailored policies yielding moderate gains under the most extreme alterations, while they remain meaningful under more moderate ones.
Las cuencas de montaña son consideradas como los sistemas hidrológicos de mayor afectación por el cambio climático, estimándose impactos significativos en los recursos hídricos y las demandas de agua. Este estudio evalúa la respuesta hidrológica de una cuenca del altiplano peruano frente a cambios de los patrones de precipitación y temperatura. El conocer con anticipación el efecto del cambio climático sobre la oferta hídrica toma relevante importancia para la toma de decisiones en la planificación a corto, mediano y largo plazos del uso del agua y la gestión de los recursos hídricos. A partir de la implementación del Modelo Integrado de Cambio Climático y Recursos Hídricos (HydroBID) se evaluaron 30 escenarios climáticos que consideraron cambios en la precipitación entre -20 y +20 %, temperatura entre 0 y 6 °C, y combinaciones de éstos formulados según las proyecciones para el área de estudio disponibles en la literatura. Los resultados mostraron que por cada 10 % de incremento de la precipitación se produjo un aumento promedio de 23.4 % en el caudal; mientras que por cada 10 % de disminución de la precipitación se generó una reducción promedio del caudal de 16 %. Asimismo, se evidenció que por cada 1 °C de subida de la temperatura se generó en promedio un 5 % de reducción del caudal. Se determinó que la variación de las tasas de precipitación, temperatura y su interacción entre ellas generarían cambios en los caudales futuros, mostrando efectos en la variación temporal y espacial de la cuenca.
