85 research outputs found

    Informing Water Management by Direct Use of Snow Information as Surrogate of Medium-to-Long Range Streamflow Forecast

    No full text
    Medium-to-long range streamflow forecast provide a key assistance in anticipating hydro- climatic adverse events and prompting effective adaptation measures. For instance, accurate medium-long range streamflow forecasts have a great potential to improve water reservoir operation by enabling more efficient allocation of water volumes in time (e.g. via hedging). Unfortunately, these forecasts often lacks reliability and accuracy, especially when low-frequency climate forcing (e.g. ENSO) is not intense enough to improve the forecast lead time (e.g. in Europe), and might be computationally very demanding, In this work, we explore the direct use of both rough snow data (e.g. snow depth) and snow water equivalent estimates as surrogate of medium-to-long range streamflow forecast to inform the operation of a regulated lake. The underlying idea is that snow data contains key information on current and future water availability throughout the snow melting season that might significantly improve the operation's anticipation potential. We adopt a three step methodology: First, we compute the upper bound of the system performance by assuming perfect foresight and we assess the value of additional information as the difference between this ideal solution and current operation. Using input variable selection, we then select the most relevant snow information to explain the release trajectory associated to the upper bound operating policy. Finally, we derive the optimal policy conditioned upon the selected variables by Multi-Objecting Evolutionary Direct Policy Search. The methodology is demonstrated on the snow-dominated Lake Como river basin, in the Italian Alps. Lake Como is a regulated lake primarily used to supply water to a large cultivated area and snowmelt from May-July is the most important contribution to the creation of the seasonal storage. Results show that using raw data or simple SWE estimates can largely improve anticipation capability in the daily operation of the lake thus increasing the reservoir hedging potential and the overall system performance over irrigation deficit

    Informing the operations of water reservoirs over multiple temporal scales by direct use of hydro-meteorological data

    No full text
    Water reservoir systems may become more adaptive and reliable to external changes by enlarging the information sets used in their operations. Models and forecasts of future hydro-climatic and socio-economic conditions are traditionally used for this purpose. Nevertheless, the identification of skillful forecasts and models might be highly critical when the system comprises several processes with inconsistent dynamics (fast and slow) and disparate levels of predictability. In these contexts, the direct use of observational data, describing the current conditions of the water system, may represent a practicable and zero-cost alternative. This paper contrasts the relative contribution of state observations and perfect forecasts of future water availability in improving multipurpose water reservoirs operation over short- and long-term temporal scales. The approach is demonstrated on the snow-dominated Lake Como system, operated for flood control and water supply. The Information Selection Assessment (ISA) framework is adopted to retrieve the most relevant information to be used for conditioning the operations. By explicitly distinguishing between observational dataset and future forecasts, we quantify the relative contribution of current water system state estimates and perfect streamflow forecasts in improving the lake regulation with respect to both flood control and water supply. Results show that using the available observational data capturing slow dynamic processes, particularly the snow melting process, produces a 10% improvement in the system performance. This latter represents the lower bound of the potential improvement, which may increase to the upper limit of 40% in case skillful (perfect) long-term streamflow forecasts are used

    Fostering cooperation in power asymmetrical water systems by the use of direct release rules and index-based insurance schemes

    No full text
    In river basin systems, power asymmetry is often responsible of inefficient and unbalanced water allocations. Climate change and anthropogenic pressure will possibly exacerbate such disparities as the dominant party controls an increasingly limited shared resource. In this context, the deployment of cooperation mechanisms giving greater consideration to a balanced distribution of the benefits, while improving system-wide efficiency, may be desirable. This often implies the intervention of a third party (e.g., the river basin water authority) imposing normative constraints (e.g., a minimum release) on the party in the dominant position. However, this imposition will be more acceptable to the dominant party if coupled with some form of compensation. For a public agency, compensation may be burdensome, especially when the allowance is triggered by natural events whose timing and magnitude are highly uncertain. In this context, index-based insurance contracts may represent a viable alternative and reduce the cost of achieving socially desirable outcomes. In this paper, we develop a hybrid cooperation mechanism composed of i) a direct normative constraint imposed by a regulator, and ii) an indirect financial tool, an index-based insurance contract, to be used as a compensation measure. The approach is developed for the Lake Como multi-purpose water system, Italy: a complex Alpine river basin, supporting several hydropower reservoirs and finally flowing into a regulated lake which supplies water to several downstream uses, mostly irrigated agriculture. The system is characterized by a manifest geographic power asymmetry: the upstream hydropower companies are free to release their stored water in time irrespective of the timing of the downstream demands. This situation can lead to financial losses by the downstream users and undesirable social outcomes. Results suggest that financial instruments may offer a reliable and relatively inexpensive alternative to other forms of compensation, and thereby favor more balanced management of multi-purpose water systems characterized by power asymmetry. This finding is especially relevant in times when granting of licenses to use/withdrawal water are often being reviewed with attention to environmental protection and equity issues

    Financial tools to induce cooperation in power asymmetrical water systems

    No full text
    In multi-purpose water systems, power asymmetry is often responsible of inefficient and inequitable water allocations. Climate Change and anthropogenic pressure are expected to exacerbate such disparities at the expense of already disadvantaged groups. The intervention of a third party, charged with redefining water sharing policies to give greater consideration to equity and social justice, may be desirable. Nevertheless, to be accepted by private actors, this interposition should be coupled with some form of compensation. For a public agency, compensation measures may be burdensome, especially when the allowance is triggered by natural events whose timing and magnitude are subject to uncertainty. In this context, index based insurance contracts may represent a viable alternative option and reduce the cost of achieving socially desirable outcomes. In this study we explore soft measures to achieve global change mitigation by designing a hybrid coordination mechanism composed of i) a direct normative constraint and ii) an indirect financial compensatory tool. The performance of an index-based insurance (i.e. hedging) contract to be used as a compensation tool is evaluated relative to more traditional alternatives. First, the performance of the status quo system, or baseline (BL), is contrasted to an idealized scenario in which a central planner (CP) maximizes global efficiency. Then, the CP management is analyzed in order to identify an efficient water rights redistribution to be legally imposed on the advantaged stakeholders in the BL scenario. Finally, a hedging contract is designed to compensate those stakeholders more negatively affected by the legal constraint. The approach is demonstrated on a multi-purpose water system in Italy, where different decision makers individually manage the same resource. The system is characterized by a manifest power asymmetry: the upstream users, i.e. hydropower companies, are free to release their stored water in time irrespective of the timing of downstream users, i.e. farmers, demands. This situation can lead to financial losses by the farmers, an already disadvantaged group, and, as demonstrated by previous work, lead the global system to underperform. Results suggest that financial hedging tools may offer a reliable and relatively inexpensive alternative to other forms of compensation, and thereby favor more equitable management of multi-purpose water systems characterized by power asymmetry. This finding is especially relevant in times where granting of licenses to use/withdrawal water are often being reviewed with attention to environmental protection and social justice issues

    Insurance portfolio diversification through bundling for competing agents exposed to uncorrelated drought and flood risks

    No full text
    Reported global economic losses from climate disasters have substantially increased in the recent decades mainly due to economic growth, along with greater concentrations of people and property in threatened areas and increased weather extremes. In this context, conflict among competing water users in shared water systems can be exacerbated by a perceived increase in financial vulnerability. Risk management tools such as insurance contracts play a critical role in reducing weather related financial vulnerability and promoting risk reduction. However risk diversification is key to guarantee a functioning and sustainable insurance market. In this work we explore the potential of risk diversification strategies involving index-based insurance bundled contract solutions, to manage financial risk in a multi-purpose water system prone to both drought and flood risk. Risk diversification can allow for reduced insurance premiums in situations in which the bundled risks are entirely, or mostly, uncorrelated. Jointly covering flood and drought related risks from competing users in the same geographic area represents a novel application. The approach is demonstrated using a case study on Lake Maggiore, a regulated lake whose management is highly controversial due to numerous and competing human activities. In particular we focus on the ongoing conflict among the lakeshore population, affected by flood risk, and the downstream farmers’ districts, facing drought related losses. Results are promising and indicate that bundling uncorrelated risks from competing users is beneficial to both promoting insurance premium affordability and facilitating collaboration schemes at the catchment scale

    Designing and assessing weather-based financial hedging contracts to mitigate water conflicts at the river basin scale. A case study in the Italian Alps

    No full text
    Growing water demands and more frequent and severe droughts are increasingly challenging water management in many regions worldwide, exacerbating water disputes and reducing the space for negotiated agreements at the catchment scale. In the lack of a centralized controller, the design and deployment of coordination and/or regulatory mechanisms is a way to improve system-wide efficiency while preserving the distributed nature of the decision making setting, and facilitating cooperation among institutionally independent decision-makers. Recent years have witnessed an increased interest in index-based insurance contracts as mechanisms for sharing hydro-meteorological risk in complex and heterogeneous decision making context (e.g. multiple stakeholders and institutionally independent decision makers). In this study, we explore the potential for index-based insurance contracts to mitigate the conflict in a water system characterized by (political) power asymmetry between hydropower companies upstream and farmers downstream. The Lake Como basin in the Italian Alps is considered as a case study. We generated alternative regulatory mechanisms in the form of minimum release constraints to the hydropower facilities, and designed an insurance contract for hedging against hydropower relative revenue losses. The fundamental step in designing this type of insurance contracts is the identification of a suitable index, which triggers the payouts as well as the payout function, defined by strike level and slope (e.g., euros/index unit). A portfolio of index-based contracts was designed for the case study and evaluated in terms of revenue floor, basis risk and revenue fluctuation around the mean, both with and without insurance. Over the long term, the insurance proved to be capable to keep the minimum revenue above a specified level while providing a greater certainty on the revenue trend. This result shows the possibility to augment farmer's supply with little loss for hydropower companies, thus helping in mitigating the conflict between the stakeholders

    Snow Water Equivalent Retrieval Using Multitemporal COSMO Skymed X-Band SAR Images To Inform Water Systems Operation.

    No full text
    In this work, we explore the use of exogenous snow-related information for enhancing the operation of water facilities in snow dominated watersheds. Traditionally, such information is assimilated into short-to-medium term streamflow forecasts, which are then used to inform water systems operation. Here, we adopt an alternative model-free approach, where the policy is directly conditioned upon a small set of selected observational data able to surrogate the snow-pack dynamics. In snow-fed water systems, the Snow Water Equivalent (SWE) stored in the basin often represents the largest contribution to the future season streamflow. The SWE estimation process is challenged by the high temporal and spatial variability of snow-pack and snow properties. Traditional retrieval methods, based on few ground sensors and optical satellites, often fail at representing the spatial diversity of snow conditions over large basins and at producing continuous (gap-free) data at the high sample frequency (e.g. daily) required to optimally control water systems. Against this background, SWE estimates from remote sensed radar products stand out, being able to acquire spatial information with no dependence on cloud coverage. In this work, we propose a technique for retrieving SWE estimates from Synthetic Aperture Radar (SAR) Cosmo SkyMed X-band images: a regression model, calibrated on ground SWE measurements, is implemented on dry snow maps obtained through a multi-temporal approach. The unprecedented spatial scale of this application is novel w.r.t. state of the art radar analysis conducted on limited spatial domains. The operational value of the SAR retrieved SWE estimates is evaluated based on ISA, a recently developed information selection and assessment framework. The method is demonstrated on a snow-rain fed river basin in the Italian Alps. Preliminary results show SAR images have a good potential for monitoring snow conditions and for improving water management operations

    Modeling the water-energy nexus under changing energy market and climate conditions: a case study in the Italian Alps

    No full text
    Climate change and growing population are expected to severely affect freshwater availability by the end of 21th century. Many river basins, especially in the Mediterranean region, are likely to become more prone to periods of reduced water supply, risking considerable impacts on the society, the environment, and the economy, thus emphasizing the need to rethink the way water resources are distributed, managed, and used at the regional and river basin scale. This paradigm shift will be essential to cope with the undergoing global change, characterized by growing water demands and by increasingly uncertain hydrologic regimes. Most of the literature traditionally focused on predicting the impacts of climate change on water resources, while our understanding of the human footprint on the hydrological cycle is limited. For example, changes in the operation of the Alpine hydropower reservoirs induced by socio-economic drivers (e.g., development of renewable energy) have been already observed over the last few years and have produced relevant impacts on multiple water uses due to the altered distribution of water volumes in time and space. Modeling human decisions as well as the links between society and environmental systems becomes key to develop reliable projections on the co-evolution of the coupled human-water systems and deliver robust adaptation strategies. This work contributes a preliminary model-based analysis of the behaviour of hydropower operators under changing energy market and climate conditions. The proposed approach is developed for the San Giacomo-Cancano reservoir system located in the Lake Como catchment. The identification of the current operating policy is supported by input variable selection methods to select the most relevant hydrological and market based drivers to explain the observed release time series. The identified model is then simulated under a set of future scenarios, accounting for both climate and socio-economic change (e.g., expansion of the electric vehicle sector, load balancing from renewable energy), to eventually estimate the impacts on the multi-sector services involved (i.e., hydropower, flood protection, irrigation supply). Preliminary results show that the magnitude of the socio-economic change impacts is comparable with the one induced by climate change
    corecore