Understanding how hydrological forecast quality impacts the management of hydroelectric reservoirs

2021 ◽  
Author(s):  
Maria-Helena Ramos ◽  
Manon Cassagnole ◽  
Ioanna Zalachori ◽  
Guillaume Thirel ◽  
Rémy Garçon ◽  
...  
Keyword(s):  
Economic Value ◽  
Optimal Placement ◽  
Economic Losses ◽  
Positive Bias ◽  
Production Rates ◽  
Hydroelectric Reservoirs ◽  
Hydroelectric Reservoir ◽  
Streamflow Forecasts ◽  
The Impact ◽  
Forecast Quality

<p>The evaluation of inflow forecast quality and value is essential in hydroelectric reservoir management. Forecast value can be quantified by the economic gains obtained when optimizing hydroelectric reservoir operations informed by weather and hydrological forecasts. This study [1] investigates the impact of 7-day streamflow forecasts on the optimal management of hydroelectric reservoirs and the associated economic gains. Flows from ten catchments in France are synthetically generated over a 4-year period to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts define the inflows to ten hydroelectric reservoirs, which are conceptually parametrized. Each reservoir is associated to a downstream power plant with yield 1 which produces electricity valued with a price signal. The system is modelled using linear programming. Relationships between forecast quality and economic value (hydropower revenue) show that forecasts with a recurrent positive bias (overestimation) and low accuracy generate the highest economic losses when compared to the reference management system where forecasts are equal to observed inflows. The smallest losses are observed for forecast systems with under-dispersion reliability bias, while forecast systems with negative bias (underestimation) show intermediate losses. Overall, the losses (which amount to millions of Euros) represent approximately 1% to 3% of the revenue over the study period. Besides revenue, the forecast quality also impacts spillage, stock evolution, production hours and production rates. For instance, forecasting systems that present a positive bias result in a tendency of operations to keep the storage at lower levels so that the reservoir can be able to handle the high volumes expected. This impacts the optimal placement of production at the best hours (i.e. when prices are higher) and the opportunity to produce electricity at higher production rates. Our study showed that when using biased forecasting systems, hydropower production is not only planned during more hours at lower rates but also at hours with lower median prices of electricity. The modelling approaches adopted in our study are certainly far from representing all the complexity of hydropower management under uncertainty. However, they proved to be adapted to obtaining the first orders of magnitude of the value of inflow forecasts in elementary situations.</p><p>[1] https://doi.org/10.5194/hess-2020-410</p>

scholarly journals Impact of the quality of hydrological forecasts on the management and revenue of hydroelectric reservoirs – a conceptual approach

2021 ◽  
Vol 25 (2) ◽  
pp. 1033-1052
Author(s):  
Manon Cassagnole ◽  
Maria-Helena Ramos ◽  
Ioanna Zalachori ◽  
Guillaume Thirel ◽  
Rémy Garçon ◽  
...  
Keyword(s):  
Optimization Model ◽  
Economic Value ◽  
Systematic Evaluation ◽  
Economic Losses ◽  
Conceptual Approach ◽  
Hydroelectric Reservoirs ◽  
Streamflow Forecasts ◽  
Operational Systems ◽  
The Impact

Abstract. The improvement of a forecasting system and the continuous evaluation of its quality are recurrent steps in operational practice. However, the systematic evaluation of forecast value or usefulness for better decision-making is less frequent, even if it is also essential to guide strategic planning and investments. In the hydropower sector, several operational systems use medium-range hydrometeorological forecasts (up to 7–10 d ahead) and energy price predictions as input to models that optimize hydropower production. The operation of hydropower systems, including the management of water stored in reservoirs, is thus partially impacted by weather and hydrological conditions. Forecast value can be quantified by the economic gains obtained with the optimization of operations informed by the forecasts. In order to assess how much improving the quality of hydrometeorological forecasts will improve their economic value, it is essential to understand how the system and its optimization model are sensitive to sequences of input forecasts of different quality. This paper investigates the impact of 7 d streamflow forecasts of different quality on the management of hydroelectric reservoirs and the economic gains generated from a linear programming optimization model. The study is based on a conceptual approach. Flows from 10 catchments in France are synthetically generated over a 4-year period to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts define the inflows to 10 hydroelectric reservoirs, which are conceptually parameterized. Relationships between forecast quality and economic value (hydropower revenue) show that forecasts with a recurrent positive bias (overestimation) and low accuracy generate the highest economic losses when compared to the reference management system where forecasts are equal to observed inflows. The smallest losses are observed for forecast systems with underdispersion reliability bias, while forecast systems with negative bias (underestimation) show intermediate losses. Overall, the losses (which amount to millions of Euros) represent approximately 1 % to 3 % of the revenue over the study period. Besides revenue, the quality of the forecasts also impacts spillage, stock evolution, production hours and production rates, with systematic over- and underestimations being able to generate some extreme reservoir management situations.

scholarly journals Impact of the quality of hydrological forecasts on the managementand revenue of hydroelectric reservoirs – a conceptual approach

2020 ◽  
Author(s):  
Manon Cassagnole ◽  
Maria-Helena Ramos ◽  
Ioanna Zalachori ◽  
Guillaume Thirel ◽  
Rémy Garçon ◽  
...  
Keyword(s):  
Optimization Model ◽  
Economic Value ◽  
Systematic Evaluation ◽  
Economic Losses ◽  
Conceptual Approach ◽  
Hydroelectric Reservoirs ◽  
Streamflow Forecasts ◽  
Operational Systems ◽  
The Impact

Abstract. The improvement of a forecasting system and the continuous evaluation of its quality are recurrent steps in operational practice. However, the systematic evaluation of forecast value or usefulness for better decision-making is less frequent, even if it is also essential to guide strategic planning and investments. In the hydropower sector, several operational systems use medium-range hydrometeorological forecasts (up to 7–10 days ahead) and energy price predictions as input to models that optimize hydropower production. The operation of hydropower systems, including the management of water stored in reservoirs, is thus partially impacted by weather and hydrological conditions. Forecast value can be quantified by the economic gains obtained with the optimization of operations informed by the forecasts. In order to assess how much improving the quality of hydrometeorological forecasts will also improve their economic value, it is also essential to understand how the system and its optimization model are sensitive to sequences of input forecasts of different quality. This paper investigates the impact of 7-day streamflow forecasts of different quality on the management of hydroelectric reservoirs and the economic gains generated from a linear programming optimization model. The study is based on a conceptual approach, where inflows to 10 reservoirs in France are synthetically generated over a 4-year period to obtain forecasts of different quality in terms of accuracy and reliability. Relationships between forecast quality and economic value (hydropower revenue) show that forecasts with a recurrent positive bias (overestimation) and low accuracy generate the highest economic losses, when compared to the reference management system where forecasts are equal to observed inflows. The smallest losses are observed for forecast systems with under-dispersion reliability bias, while forecast systems with negative bias (underestimation) show intermediate losses. Overall, the losses represent approximately 3 % to 1 % (in M€) of the revenue over the study period. Besides revenue, the quality of the forecasts also impacts spillage, stock evolution, production hours and production rates, with systematic over- and under-estimations being able to generate some extreme reservoir management situations.

What value do mangroves have in reducing the cost of storm surges?

2020 ◽  
Author(s):  
Christopher Thomas ◽  
Siddharth Narayan ◽  
Joss Matthewman ◽  
Christine Shepard ◽  
Laura Geselbracht ◽  
...  
Keyword(s):  
Storm Surge ◽  
Insurance Industry ◽  
Economic Value ◽  
Storm Surges ◽  
Coastal Flooding ◽  
Economic Losses ◽  
Modelling Framework ◽  
Catastrophe Modelling ◽  
The Cost ◽  
The Impact

<p>With coastlines becoming increasingly urbanised worldwide, the economic risk posed by storm surges to coastal communities has never been greater. Given the financial and ecological costs of manmade coastal defences, the past few years have seen growing interest in the effectiveness of natural coastal “defences” in reducing the risk of flooding to coastal properties, but estimating their actual economic value in reducing storm surge risk remains a challenging subject.</p><p>In this study, we estimate the value of mangroves in reducing annual losses to property from storm surges along a large stretch of coastline in Florida (USA), by employing a catastrophe modelling approach widely used in the insurance industry. We use a hydrodynamic coastal flood model coupled to a property loss model and a large property exposure dataset to estimate annual economic losses from hurricane-driven storm surges in Collier County, a hurricane-prone part of Florida. We then estimate the impact that removing mangroves in the region would have on average annual losses (AAL) caused by coastal flooding. We find that mangroves reduce AAL to properties behind them by over 25%, and that these benefits are distributed very heterogeneously along the coastline. Mangrove presence can also act to enhance the storm surge risk in areas where development has occurred seaward of mangroves.</p><p>In addition to looking at annual losses, we also focus on the storm surge caused by a specific severe event in Florida, based on Hurricane Irma (2017), and we estimate that existing mangroves reduced economic property damage by hundreds of millions of USD, and reduced coastal flooding for hundreds of thousands of people.</p><p>Together these studies aim to financially quantify some of the risk reduction services provided by natural defences in terms of reducing the cost of coastal flooding, and show that these services can be included in a catastrophe modelling framework commonly used in the insurance industry.</p>

scholarly journals Quantifying the Benefits of Targeting for Pandemic Response

2021 ◽  
Author(s):  
Sergio Camelo ◽  
Dragos F. Ciocan ◽  
Dan A. Iancu ◽  
Xavier S. Warnes ◽  
Spyros I. Zoumpoulis
Keyword(s):  
Economic Value ◽  
Population Group ◽  
Economic Losses ◽  
Modeling Framework ◽  
Social Contacts ◽  
Policy Makers ◽  
Flexible Modeling ◽  
Trade Offs ◽  
The Impact

To respond to pandemics such as COVID-19, policy makers have relied on interventions that target specific population groups or activities. Such targeting is potentially contentious, so rigorously quantifying its benefits and downsides is critical for designing effective and equitable pandemic control policies. We propose a flexible modeling framework and a set of associated algorithms that compute optimally targeted, time-dependent interventions that coordinate across two dimensions of heterogeneity: population group characteristics and the specific activities that individuals engage in during the normal course of a day. We showcase a complete implementation in a case study focused on the Île-de-France region of France, based on commonly available hospitalization, community mobility, social contacts and economic data. We find that optimized dual-targeted policies have a simple and explainable structure, imposing less confinement on group-activity pairs that generate a relatively high economic value prorated by activity-specific social contacts. When compared to confinements based on uniform or less granular targeting, dual-targeted policies generate substantial complementarities that lead to Pareto improvements, reducing the number of deaths and the economic losses overall and reducing the time in confinement foreach population group. Since dual-targeted policies could lead to increased discrepancies in the confinements faced by distinct groups, we also quantify the impact of requirements that explicitly limit such disparities, and find that satisfactory intermediate trade-offs may be achievable through limited targeting.

scholarly journals Analisis Perkiraan Biaya Ekonomi Deforestasi Di Kalimantan Barat

2019 ◽  
Vol 8 (1) ◽  
pp. 59
Author(s):  
Akhmad Yani
Keyword(s):  
Research Question ◽  
Economic Value ◽  
Economic Loss ◽  
Forest Area ◽  
Economic Losses ◽  
Economic Costs ◽  
West Kalimantan ◽  
High Level ◽  
Almost All ◽  
The Impact

Almost all forest areas in the districts / cities in West Kalimantan experience reduced area. Reducing the area of forest area or deforestation can, of course, have a detrimental impact on the environment which in turn can disrupt the sustainability of development itself. Deforestation has ecological, economic and social impacts. The higher the rate of deforestation, it will cause the potential impact will also increase. West Kalimantan experienced a fairly high level of deforestation. This gives an indication that the impact caused by deforestation in West Kalimantan has a relatively high potential. In other words, deforestation causes losses including economic losses. Related to this, the research question is how much economic value is the loss caused by deforestation in West Kalimantan? This research has 2 (two) objectives: first, calculating the economic costs of deforestation in West Kalimantan during the period 2009-2015, and second, analyzing the effect of the economic costs of deforestation on West Kalimantan's GDP during the period 2009-2015. Based on the data base for the period 2009 to 2015 and using the benefit transfer technique, this research has found that the highest economic losses occur in the secondary production forest and the lowest in the conservation forest area. Furthermore, during the period 2009 to 2015, this study has found that the highest economic loss value occurred in 2013 and the lowest occurred in 2011. Overall, the value of economic losses in the form of a combination of depletion and degradation provides a less significant reduction on the value of the forestry sub-sector GRDP in West Kalimantan.

The Impact of Public Health Programs on Economic Development

1971 ◽  
Vol 1 (3) ◽  
pp. 285-292 ◽  
Author(s):  
A. Kühner
Keyword(s):  
Economic Value ◽  
Economic Effects ◽  
Economic Losses ◽  
Mortality And Morbidity ◽  
Public Health Programs ◽  
Eradication Program ◽  
Health Investments ◽  
Agricultural Laborers ◽  
Malaria Eradication ◽  
The Impact

This paper is based on an attempt to describe the economic effects of a health program and to measure these effects. Multiple and complex factors make it difficult to determine the economic value of health investments. This problem of measurement may be solved by considering that any improvement of health means an increase and any deterioration of health indicates a decrease in the working capacities of the labor force. This paper suggests that death and disease cause losses of working time and gross domestic product (GDP). The example presented relates to malaria and to the effects of the malaria eradication program in Thailand. For the computation of economic losses due to malaria mortality and morbidity, a model was constructed in which the main variables are combined. The computations show the GDP lost year by year by the agricultural laborers who die or are sick as a result of malaria. The losses of GDP are calculated over a period of 12 years. Their downward trend is attributed to the impact (benefits) of the malaria eradication program. A separate series of computations (Table 2) indicates the economic losses of GDP that would be expected in the absence of a malaria eradication program.

THE MAIN DIRECTIONS OF ECONOMIC SUPPORT OF THE REGIONAL SECURITY SYSTEM OF THE POPULATION

2020 ◽  
Vol 1 (11) ◽  
pp. 133-140
Author(s):  
E. V. DMITRIEVA ◽  
Keyword(s):  
Crisis Management ◽  
Security System ◽  
Regional Security ◽  
Economic Losses ◽  
Economic Damage ◽  
Economic Activities ◽  
The Sustainable Development ◽  
Economic Support ◽  
The Impact ◽  
Crisis Situations

The article considers topical issues of economic support for the development of the regional security system of the population against various risks. The dependence of the impact of the scale of crisis situations on economic activities in the constituent entities of the Russian Federation, which become a serious barrier to the sustainable development of the regions of the country, was investigated. The increasing importance of risks of economic losses from accidents and disasters at potentially dangerous facilities as a result of the complex influence of natural, manmade and fire factors has been established. An analysis was carried out and proposals were developed to implement the key tasks of the state in the field of ensuring the protection of the population and territories of the country from disasters in order to ensure the stability of the economy. The organizational structure, division of tasks and functions between officials, crisis management structures and responding units were analyzed, taking into account the reduction in current financial costs. On the basis of a study of the peculiarities of the regions of the country, recommendations were formed to fulfill the necessary tasks by the anti-crisis management bodies in the field of reducing economic damage on the basis of preventing crisis situations and ensuring fire safety. It is proposed to organize the practical application of a complex automated security system based on modern developments with the application of improving the qualities and efficiency of anti-crisis management processes in order to increase economic efficiency. Initial data were formed to reduce potential threats of a natural, man-made, fire and other nature in the regions using financial and economic mechanisms. It is proposed to implement a set of priority measures to further improve and increase the potential of economic support for the anti-crisis management system. The materials of the article can be used in planning the main directions of the development of the regional population security system and the implementation of socio-economic development programs.

Water in the economy of Tamil Nadu, India: more flexible water allocation policies offer a possible way out of water-induced economic stagnation and will be good for the environment and the poor

Water Policy ◽  
2006 ◽  
Vol 8 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Ramesh Bhatia ◽  
John Briscoe ◽  
R. P. S. Malik ◽  
Lindy Miller ◽  
Smita Misra ◽  
...  
Keyword(s):  
Water Allocation ◽  
Water Policy ◽  
Tamil Nadu ◽  
Economic Value ◽  
The State ◽  
Allocation Policy ◽  
Rural And Urban ◽  
State Income ◽  
Important Exception ◽  
The Impact

The state of Tamil Nadu, India, is in the grips of a water crisis, with demand far outstripping supply. As the economy of the state grows, this crisis is going to become ever more serious. To date the focus of state water policy has been on trying to augment supplies, from within the state (even from desalinization) and from neighboring states. In addition, the water use is regulated in a way that does not encourage the highest value uses. International experience shows that supply-side measures must be complemented by demand-side measures and that practice must move away from fixed, command-and-control allocation policies towards flexible allocation mechanisms, which facilitate the voluntary movement of water from low to high-value uses. This study addresses the question of whether such a change in allocation policies is worth doing. It addresses this question by developing optimization models for each of the 17 river basins in Tamil Nadu (including an assessment of the economic value of water in different end-uses – agriculture, domestic and industry), then using an input–output model embedded in a social accounting matrix (SAM), to assess the impact of these changes on the state economy and on different rural and urban employment groups. The results suggest that a shift to a flexible water allocation system would bring major environmental, economic and social benefits to the state. Compared with the current “fixed sectoral allocation” policy, a flexible allocation policy would, in 2020, result in 15% less overall water used; 24% less water pumped from aquifers; 20% higher state income; with all strata, rich and poor, benefiting similarly, with one important exception, that of agricultural laborers.

scholarly journals Seasonal streamflow forecasting by conditioning climatology with precipitation indices

2017 ◽  
Vol 21 (3) ◽  
pp. 1573-1591 ◽  
Author(s):  
Louise Crochemore ◽  
Maria-Helena Ramos ◽  
Florian Pappenberger ◽  
Charles Perrin
Keyword(s):  
Long Range ◽  
Precipitation Forecast ◽  
Low Flow ◽  
Drought Risk ◽  
Streamflow Forecasting ◽  
Streamflow Forecasts ◽  
Precipitation Indices ◽  
Seasonal Streamflow ◽  
Prediction Approach ◽  
The Impact

Abstract. Many fields, such as drought-risk assessment or reservoir management, can benefit from long-range streamflow forecasts. Climatology has long been used in long-range streamflow forecasting. Conditioning methods have been proposed to select or weight relevant historical time series from climatology. They are often based on general circulation model (GCM) outputs that are specific to the forecast date due to the initialisation of GCMs on current conditions. This study investigates the impact of conditioning methods on the performance of seasonal streamflow forecasts. Four conditioning statistics based on seasonal forecasts of cumulative precipitation and the standardised precipitation index were used to select relevant traces within historical streamflows and precipitation respectively. This resulted in eight conditioned streamflow forecast scenarios. These scenarios were compared to the climatology of historical streamflows, the ensemble streamflow prediction approach and the streamflow forecasts obtained from ECMWF System 4 precipitation forecasts. The impact of conditioning was assessed in terms of forecast sharpness (spread), reliability, overall performance and low-flow event detection. Results showed that conditioning past observations on seasonal precipitation indices generally improves forecast sharpness, but may reduce reliability, with respect to climatology. Conversely, conditioned ensembles were more reliable but less sharp than streamflow forecasts derived from System 4 precipitation. Forecast attributes from conditioned and unconditioned ensembles are illustrated for a case of drought-risk forecasting: the 2003 drought in France. In the case of low-flow forecasting, conditioning results in ensembles that can better assess weekly deficit volumes and durations over a wider range of lead times.

scholarly journals Detection of Rhodococcus fascians, the Causative Agent of Lily Fasciation in South Korea

Pathogens ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 241
Author(s):  
Joon Moh Park ◽  
Jachoon Koo ◽  
Se Won Kang ◽  
Sung Hee Jo ◽  
Jeong Mee Park
Keyword(s):  
Phylogenetic Analysis ◽  
South Korea ◽  
Nicotiana Benthamiana ◽  
Economic Value ◽  
Virulence Gene ◽  
Economic Losses ◽  
Herbaceous Perennials ◽  
Rhodococcus Fascians ◽  
Different Strains

Rhodococcus fascians is an important pathogen that infects various herbaceous perennials and reduces their economic value. In this study, we examined R. fascians isolates carrying a virulence gene from symptomatic lily plants grown in South Korea. Phylogenetic analysis using the nucleotide sequences of 16S rRNA, vicA, and fasD led to the classification of the isolates into four different strains of R. fascians. Inoculation of Nicotiana benthamiana with these isolates slowed root growth and resulted in symptoms of leafy gall. These findings elucidate the diversification of domestic pathogenic R. fascians and may lead to an accurate causal diagnosis to help reduce economic losses in the bulb market.

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