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Jet-Chau Wen, Shao-Yang Huang, Chia-Chen Hsu and Kou-Chiang Chang

Taiwan is located between the world's largest landmass, the continent of Asia, and its largest ocean, the Pacific Ocean. The Tropic of Cancer passes through the island of…

Abstract

Taiwan is located between the world's largest landmass, the continent of Asia, and its largest ocean, the Pacific Ocean. The Tropic of Cancer passes through the island of Taiwan, giving it a subtropical and tropical oceanic climate. High temperatures and rainfall and strong winds characterize the climate. Because of Taiwan's position in the Asian monsoon region, its climate is greatly influenced by monsoons as well as by its own complicated topography. The annual mean temperatures in the lowlands are 22–25°C, and the monthly mean temperature exceeds 20°C for eight months starting with April each year. The period from June to August is the hottest season with mean temperatures of 27–29°C. Temperatures are cooler between November and March; in most places, the coldest monthly mean temperature is above 15°C. The climate is mild rather than cold and temperatures only fall dramatically when a cold front affects the region. Average annual rainfall in the lowlands of Taiwan is in the range of 1,600–2,500mm. Due to the influences of topography and the monsoon climate, the rainfall differs greatly with different areas and seasons. In mountainous areas, average rainfall may exceed 4,000mm/yr. Rainfall is generally higher in mountainous areas than in lowland areas, higher in the east than in the west, and higher on windward slopes than on the leeward side. The northeast monsoon prevails during the winter; this is the rainy season in the north though rainfall is not intense. But the same winter period is the dry season in the south. During the summer, the southwest monsoon prevails, often giving rise to convective thunderstorms and bringing intense and copious rainfall. With added downpours brought by typhoons, this season often accounts for over 50% of annual rainfall in the south so that central and southern regions often suffer greatly. Relative humidity on the island of Taiwan, surrounded by ocean, is high, usually measuring in the range of 78–85%. In the north, relative humidity is higher during winter than during summer. The situation in the south is the opposite. Over the past 100 years, the rainfall in the north has increased, while the rainfall in the south has decreased. The trend is not as consistent as that of the temperature change (Environmental Protection Administration, Executive Yuan, R.O.C. (Taiwan), 2002).

Details

Climate Change Adaptation and Disaster Risk Reduction: An Asian Perspective
Type: Book
ISBN: 978-0-85724-485-7

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Article

Truong An Dang

The purpose of this study is to evaluate the rainfall intensities and their limits for durations from 0.25 to 8 h with return periods from 2 to 100 years for Ca Mau City…

Abstract

Purpose

The purpose of this study is to evaluate the rainfall intensities and their limits for durations from 0.25 to 8 h with return periods from 2 to 100 years for Ca Mau City in Vietnam.

Design/methodology/approach

First, the quality of the historical rainfall data series in 44 years (1975–2018) at Ca Mau station was assessed using the standard normal homogeneity test and the Pettitt test. Second, the appraised rainfall data series are used to establish the rainfall intensity-duration-frequency curve for the study area.

Findings

Based on the findings, a two-year return period, the extreme rainfall intensities (ERIs) ranged from 9.1 mm/h for 8 h rainstorms to 91.2 mm/h for 0.25 h. At a 100-year return period, the ERIs ranged from 18.4 mm/h for 8 h rainstorms to 185.8 mm/h for 0.25 h. The results also show that the narrowest uncertainty level between the lower and upper limits recorded 1.6 mm at 8 h for the two-year return period while the widest range is at 42.5 mm at 0.25 h for the 100-year return period. In general, the possibility of high-intensity rainfall values compared to the extreme rainfall intensities is approximately 2.0% at the 100-year return period.

Originality/value

The results of the rainfall IDF curves can provide useful information for policymakers to make the right decisions in controlling and minimizing flooding in the study area.

Details

International Journal of Climate Change Strategies and Management, vol. 12 no. 5
Type: Research Article
ISSN: 1756-8692

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Article

Luana Lavagnoli Moreira, Rafael Rezende Novais, Dimaghi Schwamback and Salomão Martins de Carvalho Júnior

The most common methodology to estimate erosivity is using rainfall data obtained from rain monitoring stations. However, the quality of this estimation may be compromised…

Abstract

Purpose

The most common methodology to estimate erosivity is using rainfall data obtained from rain monitoring stations. However, the quality of this estimation may be compromised due to low density, operational problems and maintenance cost of rainfall monitoring stations, common problem encountered in developing countries such as Brazil. The objective of this study was to evaluate the applicability of pluviometric data obtained by TRMM satellite images for the spatiotemporal characterization of erosivity in the state of Espírito Santo (Brazil).

Design/methodology/approach

For this, rainfall data and annual and monthly erosivities of 71 rainfall stations were statistically compared with those from TRMM images.

Findings

For this, rainfall data and annual and monthly erosivities of 71 rainfall stations were statistically compared with those from TRMM images. The estimate proved that TRMM is efficient since the NSE values were higher than 0.70 and the coefficient of determination was higher than 0.77 for monthly and annual erosivities, but in most months and yearly, erosivity was overestimated.

Practical implications

The use of satellite images to estimate rainfall allowed the spatial representation over time (months) of the oscillating degree of erosivity in the state of Espírito Santo (Brazil). The spatialization may provide an identification of areas and periods in which are essential for the implementation of land use management in order to minimize environmental problems related to soil loss.

Originality/value

The technique applied may be an alternative to overcome common problems on rainfall monitoring station, such as low density, low data reliability, high manutention and maintenance cost and operational problems.

Details

World Journal of Science, Technology and Sustainable Development, vol. 17 no. 3
Type: Research Article
ISSN: 2042-5945

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Article

Seung Kyu LEE and Truong An Dang

This study aims to investigate aspects related to the changing trends of the rainfall extremes in the entire Mekong Delta in the period of 32 years (1984-2015) applying…

Abstract

Purpose

This study aims to investigate aspects related to the changing trends of the rainfall extremes in the entire Mekong Delta in the period of 32 years (1984-2015) applying rainfall extreme indices. First, the homogeneity tests were applied to assess the quality of observed rainfall data series. The authors, then, investigated three rainfall indices including the number of very heavy rainfall days 20 mm (R20), number of days above 50 mm (R50) and number of days above 100 mm (R100) applying the Mann-Kendall test and Sen’s slope estimate.

Design/methodology/approach

First, the homogeneity tests were applied to assess the quality of observed rainfall data series. The authors, then, investigated three rainfall indices including the number of very heavy rainfall days 20 mm (R20), number of days above 50 mm (R50) and number of days above 100 mm (R100) applying the Mann-Kendall test and Sen’s slope estimate.

Findings

The results of R20 pointed out that an insignificant upward tendency was found in the coastal provinces, whereas an insignificant downward tendency was also recorded in the inland provinces. Regarding the number of R50, a similar trend to R20 was recorded with five stations slightly increased and five stations slightly decreased. For the number of R100, the results recorded an absence of significant trends over the entire study area. Approximately 58.5% of stations show a slightly decreasing trend, while 41.5% of the remaining stations recorded a slightly increasing trend.

Originality/value

For the number of R100, the results recorded an absence of the significant trends over the entire study area. Approximately 58.5% of stations show a slightly decreasing trend, while 41.5% of the remaining stations recorded a slightly increasing trend. Of note is the fact that the number of R100 occurred more frequently in the northern provinces, which means the northern region is facing a high risk of flooding.

Details

International Journal of Climate Change Strategies and Management, vol. 12 no. 5
Type: Research Article
ISSN: 1756-8692

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Article

Abby ShalekBriski, Wade Brorsen, James K. Rogers, Jon T. Biermacher, David Marburger and Jeff Edwards

The authors determine the effectiveness of the Rainfall Index Annual Forage Program (RIAFP) in offsetting yield risk of winter annual forage growers. The authors also…

Abstract

Purpose

The authors determine the effectiveness of the Rainfall Index Annual Forage Program (RIAFP) in offsetting yield risk of winter annual forage growers. The authors also evaluate the effectiveness in reducing risk of potential alternative weather indices.

Design/methodology/approach

The RIAFP is designed to compensate forage producers when yield losses occur. Prior research found weak correlation between the rainfall index and actual winter annual forage yields. The authors use long-term small-plot variety trials of rye, ryegrass, wheat, triticale and oats with rainfall recorded on site and measure the correlation of the index with actual rainfall and actual yields. The alternative indices include frequency of precipitation events and of days with temperature below freezing.

Findings

The correlation between actual rainfall and the current RMA index was strongly positive as in previous research. Correlations between forage yields and monthly intervals of the current RMA index were mostly statistically insignificant, and many had an unexpected sign. All indices had some correlations that were inconsistent across time intervals and forage variety. The inconsistent signs suggest a nonlinear relationship with weather and forage yield, indicating that rainfall can be too much or too little. The number of days below freezing has the most potential of the three measures examined.

Practical implications

Producers should view the winter forage RIAFP as a risk-increasing income-transfer farm program. A product to reduce the risk for forage producers may need to use a crop growth simulation model or another approach that can capture the nonlinearity.

Originality/value

Considerably more data were considered than in past research. Past research did not consider alternative weather indices. The program should be continued if its goal is to serve as disguised income transfer, but it should be discontinued if its goal is to reduce risk.

Details

Agricultural Finance Review, vol. 81 no. 1
Type: Research Article
ISSN: 0002-1466

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Article

Razeef Mohd, Muheet Ahmed Butt and Majid Zaman Baba

Weather forecasting is the trending topic around the world as it is the way to predict the threats posed by extreme rainfall conditions that lead to damage the human life…

Abstract

Purpose

Weather forecasting is the trending topic around the world as it is the way to predict the threats posed by extreme rainfall conditions that lead to damage the human life and properties. These issues can be managed only when the occurrence of the worse weather is predicted in advance, and sufficient warnings can be executed in time. Thus, keeping in mind the importance of the rainfall prediction system, the purpose of this paper is to propose an effective rainfall prediction model using the nonlinear auto-regressive with external input (NARX) model.

Design/methodology/approach

The paper proposes a rainfall prediction model using the time-series prediction that is enabled using the NARX model. The time-series prediction ensures the effective prediction of the rainfall in a particular area or the locality based on the rainfall data in the previous term or month or year. The proposed NARX model serves as an adaptive prediction model, for which the rainfall data of the previous period is the input, and the optimal computation is based on the proposed algorithm. The adaptive prediction using the proposed algorithm is exhibited in the NARX, and the proposed algorithm is developed based on the Grey Wolf Optimization and the Levenberg–Marqueret (LM) algorithm. The proposed algorithm inherits the advantages of both the algorithms with better computational time and accuracy.

Findings

The analysis using two databases enables the better understanding of the proposed rainfall detection methods and proves the effectiveness of the proposed prediction method. The effectiveness of the proposed method is enhanced and the accuracy is found to be better compared with the other existing methods and the mean square error and percentage root mean square difference of the proposed method are found to be around 0.0093 and 0.207.

Originality/value

The rainfall prediction is enabled adaptively using the proposed Grey Wolf Levenberg–Marquardt (GWLM)-based NARX, wherein an algorithm, named GWLM, is proposed by the integration of Grey Wolf Optimizer and LM algorithm.

Details

Data Technologies and Applications, vol. 54 no. 1
Type: Research Article
ISSN: 2514-9288

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Article

Tong Wen, Wen Chen, Liang Zhang and Xiaoming Liu

Under the background of rapid urbanization, all kinds of urban water problems have gradually come into being: local flooding frequently happens, water environment is…

Abstract

Under the background of rapid urbanization, all kinds of urban water problems have gradually come into being: local flooding frequently happens, water environment is deteriorated, water-supply is in tension, etc. Meanwhile, with rapid development of higher education in China, campus area and scale are gradually expanding, but traditional campus construction has many drawbacks. In order to promote sponge campus planning and construction of universities in hilly areas and provide demonstration windows for sponge city construction, based on deficiencies of campus construction of Hunan City University in the aspect of water resource utilization, we used ArcGis spatial analysis method, simulation method and comparative analysis method on Storm Water Management Model (SWMM) to establish sponge campus construction indexes, content system and optimal design strategies with objectives of campus water safety, water environment and water resource utilization. Results indicate that: difference between sponge campus planning and traditional campus planning mainly lies in rainfall management. We combed the design process of sponge campus planning in hilly areas from the perspective of rainfall management, and simulated the process of sponge facilities controlling the rainfall in the campus via computer model to verify reasonability of sponge facility planning and select the optimal planning and construction plan. This study has defined design process of sponge campus planning in hilly areas to a certain degree and provided a research basis for sponge campus planning and construction of universities, setting up a typical example and driving effects on solving urban local flooding problem and rainfall resource utilization in hilly areas.

Details

Open House International, vol. 44 no. 3
Type: Research Article
ISSN: 0168-2601

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Article

Sergio Cabrales, Jesus Solano, Carlos Valencia and Rafael Bautista

In the equatorial Pacific, rainfall is affected by global climate phenomena, such as El Niño Southern Oscillation (ENSO). However, current publicly available methodologies…

Abstract

Purpose

In the equatorial Pacific, rainfall is affected by global climate phenomena, such as El Niño Southern Oscillation (ENSO). However, current publicly available methodologies for valuing weather derivatives do not account for the influence of ENSO. The purpose of this paper is to develop a complete framework suitable for valuing rainfall derivatives in the equatorial Pacific.

Design/methodology/approach

In this paper, we implement a Markov chain for the occurrence of rain and a gamma model for the conditional quantities using vector generalized linear models (VGLM). The ENSO forecast probabilities reported by the International Research Institute for Climate and Society (IRI) are included as independent variables using different alternatives. We then employ the Esscher transform to price rainfall derivatives.

Findings

The methodology is applied and calibrated using the historical rainfall data collected at the El Dorado airport weather station in Bogotá. All the estimated coefficients turn out to be significant. The results prove more accurate than those of Markovian gamma models based on purely statistical descriptions of the daily rainfall probabilities.

Originality/value

This procedure introduces the novelty of incorporating variables related to the climatic phenomena, which are the forecast probabilities regularly published for the occurrence of El Niño and La Niña.

Details

Agricultural Finance Review, vol. 80 no. 4
Type: Research Article
ISSN: 0002-1466

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Article

Rui Zhou, Johnny Siu-Hang Li and Jeffrey Pai

The purpose of this paper is to examine the reduction of crop yield uncertainty using rainfall index insurances. The insurance payouts are determined by a transparent…

Abstract

Purpose

The purpose of this paper is to examine the reduction of crop yield uncertainty using rainfall index insurances. The insurance payouts are determined by a transparent rainfall index rather than actual crop yield of any producer, thereby circumventing problems of adverse selection and moral hazard. The authors consider insurances on rainfall indexes of various months and derive an optimal insurance portfolio that minimizes the income variance for a crop producer.

Design/methodology/approach

Various regression models are considered to relate crop yield to monthly mean temperature and monthly cumulative precipitation. A bootstrapping method is used to simulate weather indexes and corn yield in a future year with the correlation between precipitation and temperature incorporated. Based on the simulated scenarios, the optimal insurance portfolio that minimizes the income variance for a crop producer is obtained. In addition, the impact of correlation between temperature and precipitation, availability of temperature index insurance and geographical basis risk on the effectiveness of rainfall index insurance is examined.

Findings

The authors illustrate the approach with the corn yield in Illinois east crop reporting district and weather data of a city in the same district. The analysis shows that corn yield in this district is negatively influenced by excessive precipitation in May and drought in June–August. Rainfall index insurance portfolio can reduce the income variance by up to 51.84 percent. Failing to incorporate the correlation between temperature and precipitation decreases variance reduction by 11.6 percent. The presence of geographical basis risk decreases variance reduction by a striking 24.11 percent. Allowing for the purchase of both rainfall and temperature index insurances increases variance reduction by 13.67 percent.

Originality/value

By including precipitation shortfall into explanatory variables, the extended crop yield model explains more fluctuation in crop yield than existing models. The authors use a bootstrapping method instead of complex parametric models to simulate weather indexes and crop yield for a future year and assess the effectiveness of rainfall index insurance. The optimal insurance portfolio obtained provides insights on the practical development of rainfall insurance for corn producers, from the selection of triggering index to the demand of the insurance.

Details

Agricultural Finance Review, vol. 78 no. 5
Type: Research Article
ISSN: 0002-1466

Keywords

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Article

Winifred Chepkoech, Nancy W. Mungai, Silke Stöber, Hillary K. Bett and Hermann Lotze-Campen

Understanding farmers’ perceptions of how the climate is changing is vital to anticipating its impacts. Farmers are known to take appropriate steps to adapt only when they…

Abstract

Purpose

Understanding farmers’ perceptions of how the climate is changing is vital to anticipating its impacts. Farmers are known to take appropriate steps to adapt only when they perceive change to be taking place. This study aims to analyse how African indigenous vegetable (AIV) farmers perceive climate change in three different agro-climatic zones (ACZs) in Kenya, identify the main differences in historical seasonal and annual rainfall and temperature trends between the zones, discuss differences in farmers’ perceptions and historical trends and analyse the impact of these perceived changes and trends on yields, weeds, pests and disease infestation of AIVs.

Design/methodology/approach

Data collection was undertaken in focus group discussions (FGD) (N = 211) and during interviews with individual farmers (N = 269). The Mann–Kendall test and regression were applied for trend analysis of time series data (1980-2014). Analysis of variance and least significant difference were used to test for differences in mean rainfall data, while a chi-square test examined the association between farmer perceptions and ACZs. Coefficient of variation expressed as a percentage was used to show variability in mean annual and seasonal rainfall between the zones.

Findings

Farmers perceived that higher temperatures, decreased rainfall, late onset and early retreat of rain, erratic rainfall patterns and frequent dry spells were increasing the incidences of droughts and floods. The chi-square results showed a significant relationship between some of these perceptions and ACZs. Meteorological data provided some evidence to support farmers’ perceptions of changing rainfall. No trend was detected in mean annual rainfall, but a significant increase was recorded in the semi-humid zone. A decreasing maximum temperature was noted in the semi-humid zone, but otherwise, an overall increase was detected. There were highly significant differences in mean annual rainfall between the zones. Farmers perceived reduced yields and changes in pest infestation and diseases in some AIVs to be prevalent in the dry season. This study’s findings provide a basis for local and timely institutional changes, which could certainly help in reducing the adverse effects of climate change.

Originality/value

This is an original research paper and the historical trends, farmers’ perceptions and effects of climate change on AIV production documented in this paper may also be representative of other ACZs in Kenya.

Details

International Journal of Climate Change Strategies and Management, vol. 10 no. 4
Type: Research Article
ISSN: 1756-8692

Keywords

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