Search results for: rainfall temporal pattern

Authors: Alemayehu Muluneh, Saskia Keesstra, Leo Stroosnijder, Woldeamlak Bewket, Ashenafi Burka

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There are some scientific evidences and a belief by many that forests attract rain and deforestation contributes to a decline of rainfall. However, there is still a lack of concrete scientific evidence on the role of forests in rainfall amount. In this paper, we investigate the forest-rainfall relationships in the environmentally hot spot area of the Central Rift Valley (CRV) of Ethiopia. Specifically, we evaluate long term (1970-2009) rainfall variability and its relationship with historical forest cover and the relationship between existing forest cover and topographical variables and rainfall distribution. The study used 16 long term and 15 short term rainfall stations. The Mann-Kendall test, bi variate and multiple regression models were used. The results show forest and wood land cover continuously declined over the 40 years period (1970-2009), but annual rainfall in the rift valley floor increased by 6.42 mm/year. But, on the escarpment and highlands, annual rainfall decreased by 2.48 mm/year. The increase in annual rainfall in the rift valley floor is partly attributable to the increase in evaporation as a result of increasing temperatures from the 4 existing lakes in the rift valley floor. Though, annual rainfall is decreasing on the escarpment and highlands, there was no significant correlation between this rainfall decrease and forest and wood land decline and also rainfall variability in the region was not explained by forest cover. Hence, the decrease in annual rainfall on the escarpment and highlands is likely related to the global warming of the atmosphere and the surface waters of the Indian Ocean. Spatial variability of number of rainy days from systematically observed two-year’s rainfall data (2012-2013) was significantly (R2=-0.63) explained by forest cover (distance from forest). But, forest cover was not a significant variable (R2=-0.40) in explaining annual rainfall amount. Generally, past deforestation and existing forest cover showed very little effect on long term and short term rainfall distribution, but a significant effect on number of rainy days in the CRV of Ethiopia.

Keywords: elevation, forest cover, rainfall, slope

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Authors: Chisomo Patrick Kumbuyo, Katsuyuki Shimizu, Hiroshi Yasuda, Yoshinobu Kitamura

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This study deals with a way of predicting Malawi rainfall from global sea surface temperature (SST) using a simple multiple regression model. Monthly rainfall data from nine stations in Malawi grouped into two zones on the basis of inter-station rainfall correlations were used in the study. Zone 1 consisted of Karonga and Nkhatabay stations, located in northern Malawi; and Zone 2 consisted of Bolero, located in northern Malawi; Kasungu, Dedza, Salima, located in central Malawi; Mangochi, Makoka and Ngabu stations located in southern Malawi. Links between Malawi rainfall and SST based on statistical correlations were evaluated and significant results selected as predictors for the regression models. The predictors for Zone 1 model were identified from the Atlantic, Indian and Pacific oceans while those for Zone 2 were identified from the Pacific Ocean. The correlation between the fit of predicted and observed rainfall values of the models were satisfactory with r=0.81 and 0.54 for Zone 1 and 2 respectively (significant at less than 99.99%). The results of the models are in agreement with other findings that suggest that SST anomalies in the Atlantic, Indian and Pacific oceans have an influence on the rainfall patterns of Southern Africa.

Keywords: Malawi rainfall, forecast model, predictors, SST

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Authors: Nji Queenta Ngum, Mwanza Mulunda

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Introduction Most African research reports on the frequent aflatoxin contamination of various foodstuffs, with researchers rarely specifying which of the Aspergillus species are present in these commodities. Numerous research works provide evidence of the ability of fungi to grow, thrive, and interact with other crop species and focus on the fact that these processes are largely affected by climatic variables. South Africa is a water-stressed country with high spatio-temporal rainfall variability; moreover, temperatures have been projected to rise at a rate twice the global rate. This weather pattern change may lead to crop stress encouraging mold contamination with subsequent mycotoxin production. In this study, the biodiversity and distribution of Aspergillus species with their corresponding toxins in maize from six distinct maize producing regions with different weather patterns in South Africa were investigated. Materials And Methods By applying cultural and molecular methods, a total of 1028 maize samples from six distinct agro-climatic regions were examined for contamination by the Aspergillus species while the high performance liquid chromatography (HPLC) method was applied to analyse the level of contamination by aflatoxins. Results About 30% of the overall maize samples were contaminated by at least one Aspergillus species. Less than 30% (28.95%) of the 228 isolates subjected to the aflatoxigenic test was found to possess at least one of the aflatoxin biosynthetic genes. Furthermore, almost 20% were found to be contaminated with aflatoxins, with mean total aflatoxin concentration levels of 64.17 ppb. Amongst the contaminated samples, 59.02% had mean total aflatoxin concentration levels above the SA regulatory limit of 20ppb for animals and 10 for human consumption. Conclusion In this study, climate variables (rainfall reduction) were found to significantly (p<0.001) influence the occurrence of the Aspergillus species (especially Aspergillus fumigatus) and the production of aflatoxin in South Africa commercial maize by maize variety, year of cultivation as well as the agro-climatic region in which the maize is cultivated. This included, amongst others, a reduction in the average annual rainfall of the preceding year to about 21.27 mm, and, as opposed to other regions whose average maximum rainfall ranged between 37.24 – 44.1 mm, resulted in a significant increase in the aflatoxin contamination of maize.

Keywords: aspergillus species, aflatoxins, diversity, drought, food safety, HPLC and PCR techniques

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Authors: Clarinda Vitorino Nhangumbe, Ercília Sousa

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Weather derivatives are financial products used to cover non catastrophic weather events with a weather index as the underlying asset. The rainfall weather derivative pricing model is modeled based in the assumption that the rainfall dynamics follows Ornstein-Uhlenbeck process, and the partial differential equation approach is used to derive the convection-diffusion two dimensional time dependent partial differential equation, where the spatial variables are the rainfall index and rainfall depth. To compute the approximation solutions of the partial differential equation, the appropriate boundary conditions are suggested, and an explicit numerical method is proposed in order to deal efficiently with the different choices of the coefficients involved in the equation. Being an explicit numerical method, it will be conditionally stable, then the stability region of the numerical method and the order of convergence are discussed. The model is tested for real precipitation data.

Keywords: finite differences method, ornstein-uhlenbeck process, partial differential equations approach, rainfall derivatives

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Authors: R. Premasiri, W. A. H. A. Abeygunasekara, S. M. Hewavidana, T. Jananthan, R. M. S. Madawala, K. Vaheeshan

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Forecasting the potential for disastrous events such as landslides has become one of the major necessities in the current world. Most of all, the landslides occurred in Sri Lanka are found to be triggered mostly by intense rainfall events. The study area is the landslide near Gerandiella waterfall which is located by the 41st kilometer post on Nuwara Eliya-Gampala main road in Kotmale Division in Sri Lanka. The landslide endangers the entire Kotmale town beneath the slope. Geographic Information System (GIS) platform is very much useful when it comes to the need of emulating the real-world processes. The models are used in a wide array of applications ranging from simple evaluations to the levels of forecast future events. This project investigates the possibility of developing a dynamic model to map the spatial distribution of the slope stability. The model incorporates several theoretical models including the infinite slope model, Green Ampt infiltration model and Perched ground water flow model. A series of rainfall values can be fed to the model as the main input to simulate the dynamics of slope stability. Hydrological model developed using GIS is used to quantify the perched water table height, which is one of the most critical parameters affecting the slope stability. Infinite slope stability model is used to quantify the degree of slope stability in terms of factor of safety. DEM was built with the use of digitized contour data. Stratigraphy was modeled in Surfer using borehole data and resistivity images. Data available from rainfall gauges and piezometers were used in calibrating the model. During the calibration, the parameters were adjusted until a good fit between the simulated ground water levels and the piezometer readings was obtained. This model equipped with the predicted rainfall values can be used to forecast of the slope dynamics of the area of interest. Therefore it can be investigated the slope stability of rainfall induced landslides by adjusting temporal dimensions.

Keywords: factor of safety, geographic information system, hydrological model, slope stability

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Authors: Majid Mathlouthi, Fethi Lebdi

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Throughout the world, the extent and magnitude of droughts have economic, social and environmental consequences. Today climate change has become more and more felt; most likely they increase the frequency and duration of droughts. An analysis by event of dry event, from series of observations of the daily rainfall is carried out. A daily precipitation threshold value has been set. A catchment localized in Northern Tunisia where the average rainfall is about 600 mm has been studied. Rainfall events are defined as an uninterrupted series of rainfall days understanding at least a day having received a precipitation superior or equal to a fixed threshold. The dry events are constituted of a series of dry days framed by two successive rainfall events. A rainfall event is a vector of coordinates the duration, the rainfall depth per event and the duration of the dry event. The depth and duration are found to be correlated. So we use conditional probabilities to analyse the depth per event. The negative binomial distribution fits well the dry event. The duration of the rainfall event follows a geometric distribution. The length of the climatically cycle adjusts to the Incomplete Gamma. Results of this analysis was used to study of the effects of climate change on water resources and crops and to calibrate precipitation models with little rainfall records. In response to long droughts in the basin, the drought management system is based on three phases during each of the three phases; different measurements are applied and executed. The first is before drought, preparedness and early warning; the second is drought management, mitigation in the event of drought; and the last subsequent drought, when the drought is over.

Keywords: dry spell, precipitation threshold, climate vulnerability, adaptation measures

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Authors: Pei-Chih Wu, Hsin-Chih Lai, Yung-Lung Lee, Yun-Yao Chi, Ching-Yi Horng, Hsien-Chang Wang

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The impact of climate change to health has always been well documented. Amongst them, water-borne infectious diseases, chronic adverse effects or cancer risks due to chemical contamination in flooding or drought events are especially important in river basin. This study therefore utilizes GIS and different models to integrate demographic, land use, disaster prevention, social-economic factors, and human health assessment in the Erren River basin. Therefore, through the collecting of climatic, demographic, health surveillance, water quality and other water monitoring data, potential risks associated with the Erren River Basin are established and to understand human exposure and vulnerability in response to climate extremes. This study assesses the temporal and spatial patterns of melioidosis (2000-2015) and various cancer incidents in Tainan and Kaohsiung cities. The next step is to analyze the spatial association between diseases incidences, climatic factors, land uses, and other demographic factors by using ArcMap and GeoDa. The study results show that amongst all melioidosis cases in Taiwan, 24% cases (115) residence occurred in the Erren River basin. The relationship between the cases and in Tainan and Kaohsiung cities are associated with population density, aging indicator, and residence in Erren River basin. Risks from flooding due to heavy rainfall and fish farms in spatial lag regression are also related. Through liver cancer, the preliminary analysis in temporal and spatial pattern shows an increases pattern in annual incidence without clusters in Erren River basin. Further analysis of potential cancers connected to heavy metal contamination from water pollution in Erren River is established. The final step is to develop an assessment tool for human exposure from water contamination and vulnerability in response to climate extremes for the second year.

Keywords: climate change, health impact, health adaptation, Erren River Basin

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Authors: Alexander P. Eremeev, Ivan E. Kurilenko, Pavel R. Varshavskiy

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In this paper, the problem of the application of temporal reasoning and case-based reasoning in intelligent decision support systems is considered. The method of case-based reasoning with temporal dependences for the solution of problems of real-time diagnostics and forecasting in intelligent decision support systems is described. This paper demonstrates how the temporal case-based reasoning system can be used in intelligent decision support systems of the car access control. This work was supported by RFBR.

Keywords: analogous reasoning, case-based reasoning, intelligent decision support systems, temporal reasoning

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Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: Mohd N. Ahmad, Lariyah Mohd Sidek

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The study had shown that Sungai Penchala (urban) was experiencing localized rainfall and hazardous air pollution due to urbanization. The high rainfall that partly added by localized rain had been seen as a threat of causing the flash floods and water quality deterioration in the area. The air pollution that consisted of mainly particulate matter (PM10), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) gave an alarming air pollution index (API) to the surrounding area. Comparison among urban area (Sungai Penchala), sub-urban (Gombak), and green areas (Jerantut plus Temerloh) with respect to the rainfall parameters and air pollutants, it was found that the degree of intensities of the parameters was positively related with the urbanization. The air pollutants especially NO2, SO2, and CO were in tandem with the increase of the rainfall. Specifically, if the water catchment area is physically near to the urban area, then the authorities need to look into related urban development program by considering the management of emitted pollutants with respect to the ecological setting of the urban area.

Keywords: urbanization, green area localized rainfall, air pollution, sub-urban area

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Authors: Amidu Owolabi Ayeni

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Studies have shown that spatio-temporal distribution and variability of climatic variables, urban land use, and population have had substantial impact on water supply. It is based on these facts that the impacts of climate, urbanization, and population on water supply in Lagos State Nigeria remain the focus of this study. Population and water production data on Lagos State between 1963 and 2006 were collected, and used for time series and projection analyses. Multi-temporal land-sat images of 1975, 1995 and NigeriaSat-1 imagery of 2007 were used for land use change analysis. The population of Lagos State increased by about 557.1% between 1963 and 2006, correspondingly, safe water supply increased by 554%. Currently, 60% of domestic water use in urban areas of Lagos State is from groundwater while 75% of rural water is from unsafe surface water. Between 1975 and 2007, urban land use increased by about 235.9%. The 46years climatic records revealed that temperature and evaporation decreased slightly while rainfall and Relatively Humidity (RH) decreased consistently. Based on these trends, the Lagos State population and required water are expected to increase to about 19.8millions and 2418.9ML/D respectively by the year 2026. Rainfall is likely to decrease by -6.68mm while temperature will increase by 0.950C by 2026. Urban land use is expected to increase by 20% with expectation of serious congestion in the suburb areas. With these results, over 50% of the urban inhabitants will be highly water poor in future if the trends continue unabated.

Keywords: challenges, climate change, urbanization, water supply

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Authors: Ali Reza Vaezi, Naser Fakori Ivand, Fereshteh Azarifam

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Interrill erosion is the detachment and transfer of soil particles between the rills due to the impact of raindrops and the shear stress of shallow surface runoff. This erosion can be affected by some soil properties such as texture, amount of organic matter and stability of soil aggregates. Information on the temporal variation of interrill erosion during a rainfall event and the effect soil properties have on it can help in understanding the process of runoff production and soil loss between the rills in hillslopes. The importance of this study is especially grate in semi-arid regions, where the soil is weakly aggregated and vegetation cover is mostly poor. Therefore, this research was conducted to investigate the temporal variation of surface flow and interrill erosion and the effect of soil properties on it in some semi-arid soils. A field experiment was done in eight different soil textures under simulated rainfalls with uniform intensity. A total of twenty four plots were installed for eight study soils with three replicates in the form of a random complete block design along the land. The plots were 1.2 m (length) × 1 m (width) in dimensions which designed with a distance of 3 m from each other across the slope. Then, soil samples were purred into the plots. The plots were surrounded by a galvanized sheet, and runoff and soil erosion equipment were placed at their outlets. Rainfall simulation experiments were done using a designed portable simulator with an intensity of 60 mm per hour for 60 minutes. A plastic cover was used around the rainfall simulator frame to prevent the impact of the wind on the free fall of water drops. Runoff production and soil loss were measured during 1 hour time with 5-min intervals. In order to study soil properties, such as particle size distribution, aggregate stability, bulk density, ESP and Ks were determined in the laboratory. Correlation and regression analysis was done to determine the effect of soil properties on runoff and interrill erosion. Results indicated that the study soils have lower booth organic matter content and aggregate stability. The soils, except for coarse textured textures, are calcareous and with relatively higher exchangeable sodium percentages (ESP). Runoff production and soil loss didn’t occur in sand, which was associated with higher infiltration and drainage rates. In other study soils, interrill erosion occurred simultaneously with the generation of runoff. A strong relationship was found between interrill erosion and surface runoff (R2 = 0.75, p< 0.01). The correlation analysis showed that surface runoff was significantly affected by some soil properties consisting of sand, silt, clay, bulk density, gravel, hydraulic conductivity (Ks), lime (calcium carbonate), and ESP. The soils with lower Ks such as fine-textured soils, produced higher surface runoff and more interrill erosion. In the soils, Surface runoff production temporally increased during rainfall and finally reached a peak after about 25-35 min. Time to peak was very short (30 min) in fine-textured soils, especially clay, which was related to their lower infiltration rate.

Keywords: erosion plot, rainfall simulator, soil properties, surface flow

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Authors: Elham Sharifineyestani, Mohammad Farshchin

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Tropical cyclones are one of the most expensive and deadliest natural disasters. They cause heavy rainfall and serious flash flooding that result in billions of dollars of damage and considerable mortality each year in the United States. Prediction of the frequency of tropical cyclone-induced rainfall events can be helpful in emergency planning and flood risk management. In this study, we have developed a machine-learning model to predict the exceedance frequencies of tropical cyclone-induced rainfall events in the United States. Model results show a satisfactory agreement with available observations. To examine the effectiveness of our approach, we also have compared the result of our predictions with the exceedance frequencies predicted using a physics-based rainfall model by Feldmann.

Keywords: flash flooding, tropical cyclones, frequencies, machine learning, risk management

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Authors: Arti Devi, Parthasarthi Choudhury

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Extreme rainfall frequency analysis for Meteorological Sub-Division 4 of India was analysed using L-moments approach. Serial Correlation and Mann Kendall tests were conducted for checking serially independent and stationarity of the observations. The discordancy measure for the sites was conducted to detect the discordant sites. The regional homogeneity was tested by comparing with 500 generated homogeneous regions using a 4 parameter Kappa distribution. The best fit distribution was selected based on ZDIST statistics and L-moments ratio diagram from the five extreme value distributions GPD, GLO, GEV, P3 and LP3. The LN3 distribution was selected and regional rainfall frequency relationship was established using index-rainfall procedure. A regional mean rainfall relationship was developed using multiple linear regression with latitude and longitude of the sites as variables.

Keywords: L-moments, ZDIST statistics, serial correlation, Mann Kendall test

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Authors: Ahmed Najah Ahmed Al-Mahfoodh, Ali Najah Ahmed Al-Mahfoodh, Ahmed Al-Shafie

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In this study, genetic programming (GP) technique has been investigated in prediction of set of rainfall-runoff data. To assess the effect of input parameters on the model, the sensitivity analysis was adopted. To evaluate the performance of the proposed model, three statistical indexes were used, namely; Correlation Coefficient (CC), Mean Square Error (MSE) and Correlation of Efficiency (CE). The principle aim of this study is to develop a computationally efficient and robust approach for predict of rainfall-runoff which could reduce the cost and labour for measuring these parameters. This research concentrates on the Johor River in Johor State, Malaysia.

Keywords: genetic programming, prediction, rainfall-runoff, Malaysia

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Authors: Geng-Gui Wang, Chia-Hao Chang, Jee-Cheng Wu

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A shoreline is a line where a body of water and the shore meet. It provides economic and social security to coastal habitations. However, shorelines face multiple threats due to both natural processes and man-made effects because of disasters, rapid urbanization, industrialization, and sand deposition and erosion, etc. In this study, we analyzed multi-temporal satellite images of the Yilan coast, Taiwan from 1978 to 2016, using the United States Geological Survey (USGS) Digital Shoreline Analysis System (DSAS), weather information (as rainfall records and typhoon routes), and man-made construction project data to explore the causes of shoreline changes. The results showed that the shoreline at Yilan coast is greatly influenced by typhoons and anthropogenic interventions.

Keywords: shoreline change, multi-temporal satellite, digital shoreline analysis system, DSAS, Yi-Lan coast

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Authors: Evan Hajani, Ataur Rahman, Khaled Haddad

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Climate change will affect the hydrological cycle in many different ways such as increase in evaporation and rainfalls. There have been growing interests among researchers to identify the nature of trends in historical rainfall data in many different parts of the world. This paper examines the trends in annual maximum rainfall data from 30 stations in New South Wales, Australia by using two non-parametric tests, Mann-Kendall (MK) and Spearman’s Rho (SR). Rainfall data were analyzed for fifteen different durations ranging from 6 min to 3 days. It is found that the sub-hourly durations (6, 12, 18, 24, 30, and 48 minutes) show statistically significant positive (upward) trends whereas longer duration (sub-daily and daily) events generally show a statistically significant negative (downward) trend. It is also found that the MK test and SR test provide notably different results for some rainfall event durations considered in this study. Since shorter duration sub-hourly rainfall events show positive trends at many stations, the design rainfall data based on stationary frequency analysis for these durations need to be adjusted to account for the impact of climate change. These shorter durations are more relevant to many urban development projects based on smaller catchments having a much shorter response time.

Keywords: climate change, Mann-Kendall test, Spearman’s Rho test, trends, design rainfall

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Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Mary Nsabagwa, Triphonia Jacob Ngailo, Joachim Reuder, Sch¨attler Ulrich, Musa Semujju

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The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Keywords: comparative performance, the COSMO model, the WRF model, light rainfall events, extreme rainfall events

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Authors: Agbortoko Manyigbe Ayuk Nkem, Eno Cynthia Osuh

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This paper sets to examine the relationship between climate change and urban livelihood through a vulnerability assessment of the urban poor in Douala. Urban development in Douala places priority towards industrial and city-centre development with little focus on the urban poor in terms of housing units and areas of sustenance. With the high rate of urbanisation and increased land prices, the urban poor are forced to occupy marginal lands which are mainly wetlands, wastelands and along abandoned neighbourhoods prone to natural hazards. Due to climate change and its effects, these wetlands are constantly flooded thereby destroying homes, properties, and crops. Also, most of these urban dwellers have found solace in urban agriculture as a means for survival. However, since agriculture in tropical regions like Cameroon depends largely on seasonal rainfall, the changes in rainfall pattern has led to misplaced periods for crop planting and a huge wastage of resources as rainfall becomes very unreliable with increased temperature levels. Data for the study was obtained from both primary and secondary sources. Secondary sources included published materials related to climate change and vulnerability. Primary data was obtained through focus-group discussions with some urban farmers while a stratified sampling of residents within marginal lands was done. Each stratum was randomly sampled to obtain information on different stressors related to climate change and their effect on livelihood. Findings proved that the high rate of rural-urban migration into Douala has led to increased prevalence of the urban poor and their vulnerability to climate change as evident in their constant fight against flood from unexpected sea level rise and irregular rainfall pattern for urban agriculture. The study also proved that women were most vulnerable as they depended solely on urban agriculture and its related activities like retailing agricultural products in different urban markets which to them serves as a main source of income in the attainment of basic needs for the family. Adaptation measures include the constant use of sand bags, raised makeshifts as well as cultivation along streams, planting after evidence of constant rainfall has become paramount for sustainability.

Keywords: adaptation, Douala, Cameroon, climate change, development, livelihood, vulnerability

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Authors: Emmanuel Iyamuremye

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Extreme rainfall events have caused significant damage to agriculture, ecology, and infrastructure, disruption of human activities, injury, and loss of life. They also have significant social, economic, and environmental consequences because they considerably damage urban as well as rural areas. Early detection of extreme maximum rainfall helps to implement strategies and measures, before they occur, hence mitigating the consequences. Extreme value theory has been used widely in modeling extreme rainfall and in various disciplines, such as financial markets, the insurance industry, failure cases. Climatic extremes have been analyzed by using either generalized extreme value (GEV) or generalized Pareto (GP) distributions, which provides evidence of the importance of modeling extreme rainfall from different regions of the world. In this paper, we focused on Peak Over Thresholds approach, where the Poisson-generalized Pareto distribution is considered as the proper distribution for the study of the exceedances. This research also considers the use of the generalized Pareto (GP) distribution with a Poisson model for arrivals to describe peaks over a threshold. The research used statistical techniques to fit models that used to predict extreme rainfall in Kigali. The results indicate that the proposed Poisson-GP distribution provides a better fit to maximum monthly rainfall data. Further, the Poisson-GP models are able to estimate various return levels. The research also found a slow increase in return levels for maximum monthly rainfall for higher return periods, and further, the intervals are increasingly wider as the return period is increasing.

Keywords: exceedances, extreme value theory, generalized Pareto distribution, Poisson generalized Pareto distribution

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi

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This study was designed to find the best-fit probability distribution of annual rainfall based on 50 years sample (1966-2015) in the Karkheh river basin at Iran using six probability distributions: Normal, 2-Parameter Log Normal, 3-Parameter Log Normal, Pearson Type 3, Log Pearson Type 3 and Gumbel distribution. The best fit probability distribution was selected using Stormwater Management and Design Aid (SMADA) software and based on the Residual Sum of Squares (R.S.S) between observed and estimated values Based on the R.S.S values of fit tests, the Log Pearson Type 3 and then Pearson Type 3 distributions were found to be the best-fit probability distribution at the Jelogir Majin and Pole Zal rainfall gauging station. The annual values of expected rainfall were calculated using the best fit probability distributions and can be used by hydrologists and design engineers in future research at studied region and other region in the world.

Keywords: Log Pearson Type 3, SMADA, rainfall, Karkheh River

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Authors: Zerihun Yohannes Amare, Belayneh Birku Geremew, Nigatu Melise Kebede, Sisaynew Getahun Amera

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In Ethiopia, agricultural production is predominantly rainfed. The El Niño Southern Oscillation (ENSO) is the driver of climate variability, which affects the agricultural production system in the country. This paper aims to study trends, variability of rainfall, and impacts of El Niño Southern Oscillation (ENSO) on rainfall amount. The study was carried out in Ethiopia's Western Amhara National Regional State, which features a variety of seasons that characterize the nation. Monthly rainfall data were collected from fifteen meteorological stations of Western Amhara. Selected El Niño and La Niña years were also extracted from National Oceanic and Atmospheric Administration (NOAA) from 1986 to 2015. Once the data quality was checked and inspected, the monthly rainfall data of the selected stations were arranged in Microsoft Excel Spreadsheet and analyzed using XLSTAT software. The coefficient of variation and the Mann-Kendall non-parametric statistical test was employed to analyze trends and variability of rainfall and temperature. The long-term recorded annual rainfall data indicated that there was an increasing trend from 1986 to 2015 insignificantly. The rainfall variability was less (Coefficient of Variation, CV = 8.6%); also, the mean monthly rainfall of Western Amhara decreased during El Niño years and increased during La Niña years, especially in the rainy season (JJAS) over 30 years. This finding will be useful to suggest possible adaptation strategies and efficient use of resources during planning and implementation.

Keywords: rainfall, Mann-Kendall test, El Niño, La Niña, Western Amhara, Ethiopia

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Authors: Apu Kumar Saha, Mrinmoy Majumder

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The increase in the concentration of Green House gases all over the World has induced global warming phenomena whereby the average temperature of the world has aggravated to impact the pattern of climate in different regions. The frequency of extreme event has increased, early onset of season and change in an average amount of rainfall all are engrossing the conclusion that normal pattern of climate is changing. Sophisticated and complex models are prepared to estimate the future situation of the climate in different zones of the Earth. As hydro-energy is directly related to climatic parameters like rainfall and evaporation such energy resources will have to sustain the onset of the climatic abnormalities. The present investigation has tried to assess the impact of climatic abnormalities upon hydropower potential of different regions of the World. In this regard multi-criteria, decision making, and the neural network is used to predict the impact of the change cognitively by an index. The results from the study show that hydro-energy potential of Asian region is mostly vulnerable with respect to other regions of the world. The model results also encourage further application of the index to analyze the impact of climate change on the potential of hydro-energy.

Keywords: hydro-energy potential, neural networks, multi criteria decision analysis, environmental and ecological engineering

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Authors: G. Venkata Rao, R. Srinivasa Rao, B. Neelima Sri Priya

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The over extraction of groundwater from the coastal aquifers, result in reduction of groundwater resource and lowering of water level. In general, the depletion of groundwater level enhances the landward migration of saltwater wedge. Now a days the ground water extraction increases by year to year because increased population and industrialization. The ground water is the only source of irrigation, domestic and Industrial purposes at Pydibhimavaram industrial area, which is located in the coastal belt of Srikakulam district, India of Latitudes 18.145N 83.627E and Longitudes 18.099N 83.674E. The present study has been attempted to calculate amount of water getting recharged into this aquifer, status of rainfall pattern for the past two decades and the runoff is calculated by using Khosla’s formula with available rainfall and temperature in the study area. A decision support model has been developed on the basis of Monthly Extractions of the water from the ground through bore wells and the Net Recharge of the aquifer. It is concluded that the amount of extractions is exceeding the amount of recharge from May to October in a given year which will in turn damage the water balance in the subsurface layers.

Keywords: aquifer, decision support model, groundwater extraction, run off estimation and rainfall

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Authors: N. Sopipan

Abstract:

In this paper, we study of rainfall time series of weather stations in Nakhon Ratchasima province in Thailand using various statistical methods enabled to analyse the behaviour of rainfall in the study areas. Time-series analysis is an important tool in modelling and forecasting rainfall. ARIMA and Holt-Winter models based on exponential smoothing were built. All the models proved to be adequate. Therefore, could give information that can help decision makers establish strategies for proper planning of agriculture, drainage system and other water resource applications in Nakhon Ratchasima province. We found the best perform for forecasting is ARIMA(1,0,1)(1,0,1)12.

Keywords: ARIMA Models, exponential smoothing, Holt-Winter model

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Authors: Antonello Troncone, Luigi Pugliese, Andrea Parise, Enrico Conte

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The present study deals with the landslides periodically reactivated by groundwater level fluctuations owing to rainfall. The main type of movement which generally characterizes these landslides consists in sliding with quite small-displacement rates. Another peculiar characteristic of these landslides is that soil deformations are essentially concentrated within a thin shear band located below the body of the landslide, which, consequently, undergoes an approximately rigid sliding. In this context, a simple method is proposed in the present study to forecast the movements of this type of landslides owing to rainfall. To this purpose, the landslide body is schematized by means of a two-block model. Some analytical solutions are derived to relate rainfall measurements with groundwater level oscillations and these latter, in turn, to landslide mobility. The proposed method is attractive for engineering applications since it requires few parameters as input data, many of which can be obtained from conventional geotechnical tests. To demonstrate the predictive capability of the proposed method, the application to a well-documented landslide periodically reactivated by rainfall is shown.

Keywords: rainfall, water level fluctuations, landslide mobility, two-block model

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Authors: Leila Rashidian, Mina Rajabali

Abstract:

Industrialization has made progress and comfort for human beings in many aspects. It is not only achievement for the global environment but also factor for destruction and disruption of the Earth's climate. In this study, we used LARS.WG model and down scaling of general circulation climate model HADCM-3 daily precipitation amounts, minimum and maximum temperature and daily sunshine hours. These data are provided by the meteorological organization for Caspian Sea coastal station such as Anzali, Manjil, Rasht, Lahijan and Astara since their establishment is from 1982 until 2010. According to the IPCC scenarios, including series A1b, A2, B1, we tried to simulate data from 2010 to 2040. The rainfall pattern has changed. So we have a rainfall distribution inappropriate in different months.

Keywords: climate change, Lars.WG, HADCM3, Gillan province, climatic parameters, A2 scenario

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Authors: Thanh Van Hoang, Tien Yin Chou, Yao Min Fang, Yi Min Huang, Xuan Linh Nguyen

Abstract:

Reliable information on the spatial distribution of annual rainfall and temperature is essential in research projects relating to urban and regional planning. This research presents results of a classification of temperature and rainfall in the Red River Delta of northern Vietnam based on measurements from seven meteorological stations (Ha Nam, Hung Yen, Lang, Nam Dinh, Ninh Binh, Phu Lien, Thai Binh) in the river basin over a thirty-years period from 1982-2011. The average accumulated rainfall trends in the delta are analysed and form the basis of research essential to weather and climate forecasting. This study employs interpolation based on the Kriging Method for daily rainfall (min and max) and daily temperature (min and max) in order to improve the understanding of sources of variation and uncertainly in these important meteorological parameters. To the Kriging method, the results will show the different models and the different parameters based on the various precipitation series. The results provide a useful reference to assist decision makers in developing smart agriculture strategies for the Red River Delta in Vietnam.

Keywords: spatial interpolation method, ArcGIS, temperature variability, rainfall variability, Red River Delta, Vietnam

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Authors: Melese Tadesse Morebo

Abstract:

Pastoral and agro-pastoral communities in East Africa, particularly in Ethiopia, are vulnerable to climate-related risks. The aim of this study is to characterize the annual, seasonal, and monthly rainfall and temperature of the middle and lower awash areas of Ethiopia. Start of season (SOS), end of season (EOS), length of growing season (LGS), number of rainy days, and probability of dry spell occurrences were analyzed using INSTAT Plus (v3.7) software. Daily rainfall and temperature data for 33 years (1990–2022) from six stations were analyzed. The result of the study revealed that the annual rainfall in the study area as a whole showed an increasing trend, but its trend was statistically non-significant. During the study period, the Kiremt rainfall at Amibara station showed statistically significant increasing trends. The trend analysis of SOS, EOS, and LGS shows up and down trends at all stations. The mean lengths of growing seasons in the study area ranged from 20 to 61 days during the study period. In the study area, the annual mean maximum temperature ranged between 34.1°C and 38.3°C over the last three decades. All stations within the research area during the study period, the annual minimum temperature exhibited a substantial impact.

Keywords: annual rainfall, LGS, minimum temperature, Mann-Kendall test

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Authors: Lubaina Soni, Claire Farrell, Christopher Szota, Tim D. Fletcher

Abstract:

Green roofs are a promising engineered ecosystem for reducing stormwater runoff and restoring vegetation cover in cities. Plants can contribute to rainfall retention by rapidly depleting water in the substrate; however, this increases the risk of plant drought stress. Green roof configurations, therefore, need to provide plants the opportunity to efficiently deplete the substrate but also avoid severe drought stress. This study used green roof modules placed in a rainout shelter during a six-month rainfall regime simulated in Melbourne, Australia. Rainfall was applied equally with an overhead irrigation system on each module. Aside from rainfall, modules were under natural climatic conditions, including temperature, wind, and radiation. A single species, Ficinia nodosa, was planted with five different treatments and three replicates of each treatment. In this experiment, we tested the impact of three plant cover treatments (0%, 50% and 100%) on rainfall retention and plant drought stress. We also installed two runoff zone treatments covering 50% of the substrate surface for additional modules with 0% and 50% plant cover to determine whether directing rainfall resources towards plant roots would reduce drought stress without impacting rainfall retention. The retention performance for the simulated rainfall events was measured, quantifying all components for hydrological performance and survival on green roofs. We found that evapotranspiration and rainfall retention were similar for modules with 50% and 100% plant cover. However, modules with 100% plant cover showed significantly higher plant drought stress. Therefore, planting at a lower cover/density reduced plant drought stress without jeopardizing rainfall retention performance. Installing runoff zones marginally reduced evapotranspiration and rainfall retention, but by approximately the same amount for modules with 0% and 50% plant cover. This indicates that reduced evaporation due to the installation of the runoff zones likely contributed to reduced evapotranspiration and rainfall retention. Further, runoff occurred from modules with runoff zones faster than those without, indicating that we created a faster pathway for water to enter and leave the substrate, which also likely contributed to lower overall evapotranspiration and retention. However, despite some loss in retention performance, modules with 50% plant cover installed with runoff zones showed significantly lower drought stress in plants compared to those without runoff zones. Overall, we suggest that reducing plant cover represents a simple means of optimizing green roof performance but creating runoff zones may reduce plant drought stress at the cost of reduced rainfall retention.

Keywords: green roof, plant cover, plant drought stress, rainfall retention

Procedia PDF Downloads 115