scholarly journals Weather Risk Assessment for Collective Water Supply and Sewerage Systems

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1970
Author(s):  
Janusz R. Rak ◽  
Katarzyna Wartalska ◽  
Bartosz Kaźmierczak

The weather derivatives market as an instrument of effective weather risk management is still not flexible enough for many industries. The water supply and sewerage industry is sensitive primarily to heavy rainfalls and periods of high and low temperatures: days with heavy rainfall may cause a hydraulic overload of the sewerage systems; on hot days, the water demand increases significantly; on frost days, the risk of water pipe failure grows. The work aimed to summarise methods of weather risk management and propose indices that will help to protect the interests of the water supply and sewerage industry in Poland. Three indices were proposed: a daily precipitation index, frost day index, and hot day index. The frequency of reaching these indices in Poland was verified with the use of meteorological data from 1970–2019, for 19 locations. The non-parametric Mann-Kendall test was used to determine the climate change impact on the exceedance frequency of the proposed indicators. The results showed that the indexes were exceeded in the past once every 6 years, on average. The hot day index was exceeded the least often, but it was the only one with a clear (growing) trend observed.

2002 ◽  
Vol 83 (8) ◽  
pp. 1193-1198 ◽  
Author(s):  
Richard J. Murnane ◽  
Michael Crowe ◽  
Allan Eustis ◽  
Susan Howard ◽  
Judy Koepsell ◽  
...  

2008 ◽  
Vol 37 (1) ◽  
pp. 63-78 ◽  
Author(s):  
Calum G. Turvey ◽  
Michael Norton

This paper introduces a web-based computer program designed to evaluate weather risk management and weather insurance in the United States. The paper outlines the economics of weather risk in terms of agricultural production and household well-being; defines weather risk in terms of intensity, duration, and frequency; and illustrates the computer program use by comparing heat and precipitation risks at Ardmore, Oklahoma, and Ithaca, New York.


Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 945
Author(s):  
Monika Wieczorek-Kosmala

The energy sector is perceived as one of the most exposed sectors to the consequences of weather risk both directly (damages of its infrastructure) and indirectly (frictions to the energy supply–demand balance). The main aim of this paper is to provide an insight into the impact of weather risk on economic activity of companies operating in the energy sector in Poland. The empirical objective is to examine whether energy companies: (i) identify their relevant weather risk exposures; (ii) evaluate the impact of weather risk in the cost-revenues dimension; and (iii) implement weather risk management tools, in this case—weather derivatives. In a methodical context, this study relies on a unique research approach and derives from works that examine companies’ risk disclosures in annual reports, by applying textual content analysis. The results indicate that Polish energy companies recognize the impact of weather risk on their performance, also in the cost-revenues dimension. However, although the reported weather risk management methods were diversified, the examined companies did not use weather derivatives to hedge their weather risk exposures. In the overall dimension, the companies leading with the perception and management of weather risk were diversified regarding performance and market size.


2005 ◽  
Vol 8 (1) ◽  
pp. 127-140 ◽  
Author(s):  
Patrick L. Brockett ◽  
Mulong Wang ◽  
Chuanhou Yang

2019 ◽  
Vol 79 (1) ◽  
pp. 2-26 ◽  
Author(s):  
Wenjun Zhu ◽  
Lysa Porth ◽  
Ken Seng Tan

Purpose The purpose of this paper is to propose an improved reinsurance pricing framework, which includes a crop yield forecasting model that integrates weather variables and crop production information from different geographically correlated regions using a new credibility estimator, and closed form reinsurance pricing formulas. A yield restatement approach to account for changing crop mix through time is also demonstrated. Design/methodology/approach The new crop yield forecasting model is empirically analyzed based on detailed farm-level data from Manitoba, Canada, covering 216 crop varieties from 19,238 farms from 1996 to 2011. As well, corresponding weather data from 30 stations, including daily temperature and precipitation, are considered. Algorithms that combine screening regression, cross-validation and principal component analysis are evaluated for the purpose of achieving efficient dimension reduction and model selection. Findings The results show that the new yield forecasting model provides significant improvements over the classical regression model, both in terms of in-sample and out-of-sample forecasting abilities. Research limitations/implications The empirical analysis is limited to data from the province of Manitoba, Canada, and other regions may show different results. Practical implications This research is useful from a risk management perspective for insurers and reinsurers, and the framework may also be used to develop improved weather risk management strategies to help manage adverse weather events. Originality/value This is the first paper to integrate a credibility estimator for crop yield forecasting, and develop a closed form reinsurance pricing formula.


Sign in / Sign up

Export Citation Format

Share Document