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1 – 10 of over 3000
Book part
Publication date: 12 July 2021

Ummi Hani Mahamad Anuar and Nor Eliza Alias

Climate change is expected to alter the major components of hydrological regime such as streamflow and water availability. The magnitude and their impacts are still…

Abstract

Climate change is expected to alter the major components of hydrological regime such as streamflow and water availability. The magnitude and their impacts are still uncertain. Therefore, it is highly required to study streamflow and flood vulnerability in tropical river basins particularly urbanised basin such as Langat River Basin. This study aims to model the future streamflow of Langat River Basin due to climate change using Rainfall-Runoff Inundation (RRI) model. Daily rainfall data obtained from Department of Irrigation and Drainage Malaysia and topographic data from HydroSHEDS at 15-second resolution were used. The projected future rainfall (2075–2099) is extracted from MRI-AGCM3.2s under the worst carbon emission scenario, RCP8.5. The annual maximum series of 1-day rainfall is selected for statistical bias correction using Quantile Mapping. The General Circulation Model data were found to be greatly corrected with reasonable Nash–Sutcliffe efficiency, Percent bias and Root Mean Square Error values. The mean of maximum 1-day future rainfall in Langat River Basin is found to be inconsistent where parts of the upstream will experience an increment at about 7% while other parts decrease at 8%. Meanwhile, the rainfall at downstream area are expected to decrease at 40%. Based on RRI simulation, the future streamflow can achieve up to 92% increment.

Book part
Publication date: 31 December 2010

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

Open Access
Article
Publication date: 5 October 2020

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

Keywords

Article
Publication date: 15 January 2020

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

Keywords

Article
Publication date: 20 August 2018

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

Open Access
Article
Publication date: 18 May 2018

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…

6609

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

Article
Publication date: 5 June 2020

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

Keywords

Article
Publication date: 24 February 2012

Md. Mizanur Rahman, Nazlee Ferdousi, Yasuo Sato, Shoji Kusunoki and Akio Kitoh

The purpose of this paper is to demonstrate the use of the Meteorological Research Institute (MRI) global 20-km mesh Atmospheric General Circulation Model (AGCM), called…

Abstract

Purpose

The purpose of this paper is to demonstrate the use of the Meteorological Research Institute (MRI) global 20-km mesh Atmospheric General Circulation Model (AGCM), called MRI-AGCM, to simulate rainfall and mean surface air temperature. Through calibration and validation the MRI-AGCM was adapted for Bangladesh for generating rainfall and temperature scenarios.

Design/methodology/approach

The model generated rainfall was calibrated with ground-based observed data in Bangladesh during the period of 1979-2006. The Climate Research Unit (CRU) data are also used for understanding of the model performance. Better performance of MRI-AGCM obtained through validation process increased confidence in utilizing it in the future rainfall projection for Bangladesh.

Findings

Rainfall and mean surface air temperature projection for Bangladesh is experimentally obtained for the period of 2075-2099. This work finds that the MRI-AGCM simulated rainfall and temperature are not directly useful in application purpose. However, after validation and calibration, acceptable performance is obtained in estimating annual rainfall and mean surface air temperature in Bangladesh.

Originality/value

Change of rainfall is projected about 0.64 percent in monsoon season (JJAS), 1.90 percent in post-monsoon season (ON) and 13.46 percent in Winter season (DJF) during the period of 2075-2099. Similarly, change of mean surface air temperature is projected about 2.5 degrees Celsius for the same period.

Details

International Journal of Climate Change Strategies and Management, vol. 4 no. 1
Type: Research Article
ISSN: 1756-8692

Keywords

Article
Publication date: 4 April 2019

Simona Franzoni and Cristian Pelizzari

The variability of weather at tourist destinations can significantly affect travel decisions by tourists and their comfort. In particular, rain affects the profitability…

Abstract

Purpose

The variability of weather at tourist destinations can significantly affect travel decisions by tourists and their comfort. In particular, rain affects the profitability of hospitality firms that can hardly contrast the phenomenon of heavy rain. Therefore, the assessment of rainfall financial risks, i.e. the negative economic effects caused by rain, becomes crucial to safeguarding the profitability of the hospitality industry. The purpose of this study is to assess such risks.

Design/methodology/approach

The present work contributes to the literature on weather/climate change and tourism by advancing a model for the rainfall financial risk assessment of hospitality firms. The model is based on scenario correlation between business performances and rain and originates from the Enterprise Risk Management (ERM) presented by the Committee of Sponsoring Organizations of the Treadway Commission (COSO), where some tools to adequately face business risks are advanced.

Findings

The model is complemented by an empirical experiment based on the business performances of the hospitality industry of Lake Garda and the amount of rainfall in the same area during the decade 2005-2014. The empirical application detects scenario correlation between those variables over time. In particular, the findings open opportunities to purchase financial instruments (insurance contracts, derivative instruments, etc.) with greater awareness, with the purpose of mitigating the negative impacts of rain on business performances of hospitality firms.

Originality/value

The model improves scenario analysis by introducing scenario correlation, which is a tool for assessing the highly nonlinear links between business performances and rain in today’s complex world. This is the essential step that firms should perform if they want to successfully adopt strategic decisions about rainfall financial risk management.

Details

International Journal of Contemporary Hospitality Management, vol. 31 no. 3
Type: Research Article
ISSN: 0959-6119

Keywords

Open Access
Article
Publication date: 23 April 2018

Francis Wasswa Nsubuga and Hannes Rautenbach

In view of the consensus that climate change is happening, scientists have documented several findings about Uganda’s recent climate, as well as its variability and…

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Abstract

Purpose

In view of the consensus that climate change is happening, scientists have documented several findings about Uganda’s recent climate, as well as its variability and change. The purpose of this study is to review what has been documented, thus it gives an overview of what is known and seeks to explain the implications of a changing climate, hence what ought to be known to create a climate resilient environment.

Design/methodology/approach

Terms such as “climate”, “climate change” and “climate variability” were identified in recent peer-reviewed published literature to find recent climate-related literature on Uganda. Findings from independent researchers and consultants are incorporated. Data obtained from rainfall and temperature observations and from COSMO-CLM Regional Climate Model-Coordinated Regional Climate Downscaling Experiment (CCLM CORDEX) data, European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) data and Global Precipitation Climatology Centre (GPCC) have been used to generate spatial maps, seasonal outputs and projections using GrADS 2.02 and Geographic Information System (GIS) software for visualization.

Findings

The climate of Uganda is tropical in nature and influenced by the Inter-Tropical Convergence Zone (ITCZ), varied relief, geo-location and inland lakes, among other factors. The impacts of severe weather and climate trends and variability have been documented substantially in the past 20-30 years. Most studies indicated a rainfall decline. Daily maximum and minimum temperatures are on the rise, while projections indicate a decrease in rainfall and increase in temperature both in the near and far future. The implication of these changes on society and the economy are discussed herein. Cost of inaction is expected to become huge, given factors like, the growing rate of the population and the slow expanding economy experienced in Uganda. Varied forms of adaptation to the impacts of climate change are being implemented, especially in the agricultural sector and at house hold level, though not systematically.

Originality/value

This review of scientific research findings aims to create a better understanding of the recent climate change and variability in Uganda and provides a baseline of summarized information for use in future research and actions.

Details

International Journal of Climate Change Strategies and Management, vol. 10 no. 5
Type: Research Article
ISSN: 1756-8692

Keywords

1 – 10 of over 3000