Uncertainties In Future Projections Of Extreme Rainfall: The Role Of Climate Model, Emission Scenario And Randomness

Climate change has resulted in substantial variations in annual extreme rainfall quantiles in different durations and return periods. Predicting the future changes in extreme rainfall quantiles is essential for various water resources design, assessment, and decision making purposes. Current Predictions of future rainfall extremes, however, exhibit large uncertainties. According to extreme value theory, rainfall extremes are rather random variables, with changing distributions around different return periods; therefore there are uncertainties even under current climate conditions. Regarding future condition, our large-scale knowledge is obtained using global climate models, forced with certain emission scenarios. There are widely known deficiencies with climate models, particularly with respect to precipitation projections. There is also recognition of the limitations of emission scenarios in representing the future global change. Apart from these large-scale uncertainties, the downscaling methods also add uncertainty into estimates of future extreme rainfall when they convert the larger-scale projections into local scale. The aim of this research is to address these uncertainties in future projections of extreme rainfall of different durations and return periods. We plugged 3 emission scenarios with 2 global climate models and used LARS-WG, a well-known weather generator, to stochastically downscale daily climate models’ projections for the city of Saskatoon, Canada, by 2100. The downscaled projections were further disaggregated into hourly resolution using our new stochastic and non-parametric rainfall disaggregator. The extreme rainfall quantiles can be consequently identified for different durations (1-hour, 2-hour, 4-hour, 6-hour, 12-hour, 18-hour and 24-hour) and return periods (2-year, 10-year, 25-year, 50-year, 100-year) using Generalized Extreme Value (GEV) distribution. By providing multiple realizations of future rainfall, we attempt to measure the extent of total predictive uncertainty, which is contributed by climate models, emission scenarios, and downscaling/disaggregation procedures. The results show different proportions of these contributors in different durations and return periods.

Extension And Testing Of A 2D Hydrodynamic Model For Direct Rainfall Runoff Simulation

While the simulation of flood risks originating from the overtopping of river banks is well covered within continuously evaluated programs to improve flood protection measures, flash flooding is not. Flash floods are triggered by short, local thunderstorm cells with high precipitation intensities. Small catchments have short response times and flow paths and convective thunder cells may result in potential flooding of endangered settlements. Assessing local flooding and pathways of flood requires a detailed hydraulic simulation of the surface runoff. Hydrological models usually do not incorporate surface runoff at this detailedness but rather empirical equations are applied for runoff detention. In return 2D hydrodynamic models usually do not allow distributed rainfall as input nor are any types of soil/surface interaction implemented as in hydrological models. Considering several cases of local flash flooding during the last years the issue emerged for practical reasons but as well as research topics to closing the model gap between distributed rainfall and distributed runoff formation. Therefore, a 2D hydrodynamic model, depth-averaged flow equations using the finite volume discretization, was extended to accept direct rainfall enabling to simulate the associated runoff formation. The model itself is used as numerical engine, rainfall is introduced via the modification of waterlevels at fixed time intervals. The paper not only deals with the general application of the software, but intends to test the numerical stability and reliability of simulation results. The performed tests are made using different artificial as well as measured rainfall series as input. Key parameters of the simulation such as losses, roughness or time intervals for water level manipulations are tested regarding their impact on the stability.

The aliasing effect, the Fejer Kernel and temporally aggregated long memory processes

This paper derives the spectral density function of aggregated long memory processes in light of the aliasing effect. The results are different from previous analyses in the literature and a small simulation exercise provides evidence in our favour. The main result point to that flow aggregates from long memory processes shall be less biased than stock ones, although both retain the degree of long memory. This result is illustrated with the daily US Dollar/ French Franc exchange rate series.

Spectral properties of temporally aggregated long memory processes

This paper derives the spectral density function of aggregated long memory processes in light of the aliasing effect. The results are different from previous analyses in the literature and a small simulation exercise provides evidence in our favour. The main result point to that flow aggregates from long memory processes shall be less biased than stock ones, although both retain the degree of long memory. This result is illustrated with the daily US Dollar/ French Franc exchange rate series.

Statistical modelling of extreme rainfall in Madeira Island

Extreme rainfall events have triggered a significant number of flash floods in Madeira Island along its past and recent history. Madeira is a volcanic island where the spatial rainfall distribution is strongly affected by its rugged topography. In this thesis, annual maximum of daily rainfall data from 25 rain gauge stations located in Madeira Island were modelled by the generalised extreme value distribution. Also, the hypothesis of a Gumbel distribution was tested by two methods and the existence of a linear trend in both distributions parameters was analysed. Estimates for the 50– and 100–year return levels were also obtained. Still in an univariate context, the assumption that a distribution function belongs to the domain of attraction of an extreme value distribution for monthly maximum rainfall data was tested for the rainy season. The available data was then analysed in order to find the most suitable domain of attraction for the sampled distribution. In a different approach, a search for thresholds was also performed for daily rainfall values through a graphical analysis. In a multivariate context, a study was made on the dependence between extreme rainfall values from the considered stations based on Kendall’s τ measure. This study suggests the influence of factors such as altitude, slope orientation, distance between stations and their proximity of the sea on the spatial distribution of extreme rainfall. Groups of three pairwise associated stations were also obtained and an adjustment was made to a family of extreme value copulas involving the Marshall–Olkin family, whose parameters can be written as a function of Kendall’s τ association measures of the obtained pairs.

Spatial Assessment of Indices for Characterizing the Erosive Force of Rainfall in El Salvador Republic

Soil erosion data in El Salvador Republic are scarce and there is no rainfall erosivity map for this region. Considering that rainfall erosivity is an important guide for planning soil erosion control practices, a spatial assessment of indices for characterizing the erosive force of rainfall in El Salvador Republic was carried out. Using pluviometric records from 25 weather stations, we applied two methods: erosivity index equation and the Fournier index. In all study area, the rainiest period is from May to November. Annual values of erosivity index ranged from 7,196 to 17,856 MJ mm ha(-1) h(-1) year(-1) and the Fournier index ranged from 52.9 to 110.0 mm. The erosivity map showed that the study area can be broadly divided into three major erosion risk zones, and the Fournier index map was divided into four zones. Both methods revealed that the erosive force is severe in all study area and presented significant spatial correlation with each other. The erosive force in the country is concentrated mainly from May to November.

Effects of rainfall on water quality in six sequentially disposed fishponds with continuous water flow

O estudo foi efetuado durante o período de chuva (dezembro-fevereiro) em seis viveiros de produção semi-intensiva de peixes, a fim de avaliar o efeito da chuva na qualidade da água de viveiros que apresentam fluxo contínuo de água, a qual é passada de um viveiro para outro sem tratamento prévio. Foram amostrados oito pontos de coleta nas saídas dos viveiros. O viveiro P1 (próximo à nascente) apresentou as menores concentrações físicas e químicas da água e as maiores no viveiro P4 (considerado um ponto crítico recebendo material alóctone proveniente de outros viveiros e do escoamento do setor de criação de rãs). A disposição seqüencial dos viveiros estudados promoveu aumento nas concentrações dos nutrientes, clorofila-a e condutividade. As chuvas características desta época do ano aumentaram o fluxo de água nos viveiros e conseqüentemente, carreando material particulado e dissolvido de um viveiro para outro e, promovendo um aumento das variáveis limnológicas em direção do P3 ao P6. Os resultados sugerem que a chuva no período de estudo afetou positivamente a qualidade da água dos viveiros estudados, porém, como os sistemas analisados estão dispostos em distribuição seqüencial e escoamento constante da água de viveiros e tanques paralelos sem tratamento prévio, cuidados devem ser averiguados para que o aumento do fluxo de água provocado pelas chuvas não tenha efeito adverso nos viveiros estudados.

Effect of temperature, leaf wetness, and rainfall on the production of Guignardia citricarpa ascospores and on back spot severity on sweet orange

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Growth regulator losses from cotton plants due to rainfall

Reguladores de crescimento aplicados às plantas de algodoeiro (Gossypium hirsutum L.) podem ser lavados em função da ocorrência de chuvas. Chuvas que ocorrem próximas à época de aplicação podem ocasionar elevada perda e necessidade de reaplicação dos produtos visando à taxa de crescimento desejada. Avaliou-se o efeito do intervalo de tempo entre a ocorrência de chuva simulada e a aplicação de cloreto de mepiquat e cloreto de chlormequat no algodoeiro no crescimento das plantas, além de estimar a necessidade de reaplicação dos reguladores. Plantas de algodão foram cultivadas em vasos de 12 L que permaneceram em casa de vegetação. Os reguladores de crescimento foram aplicados 40 dias após a emergência, quando 50% das plantas apresentavam botão floral. A chuva foi simulada 1, 2, 4, 6 e 24 horas após a aplicação dos reguladores. Determinou-se a altura das plantas antes da aplicação dos produtos e a cada 3 dias até o 30º dia. Na colheita, foi avaliado o número de ramos e estruturas reprodutivas, com posterior determinação da massa da matéria seca. Também foi determinado o crescimento acumulado e taxa de crescimento das plantas. Os dois reguladores reduziram a massa da matéria seca das plantas, independente do intervalo para ocorrência da chuva. O crescimento excessivo das plantas foi controlado, porém, com eficiência reduzida quanto menor o intervalo para simulação de chuva. em todos os períodos avaliados houve perda de produtos, com necessidade de reaplicação. A taxa de reaplicação de cloreto de mepiquat para os diferentes intervalos de chuva foi, em média, 17% maior.

Reproductive phenology of a northeast Brazilian mangrove community: Environmental and biotic constraints

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Rainfall intensity and Mepiquat Chloride persistence in cotton

Em parte das regiões onde se encontram as maiores áreas de algodão no Brasil atualmente, o índice pluviométrico está ao redor de 2.000 mm anuais, existindo risco de ocorrer lavagem do Cloreto de Mepiquat (CM) das folhas do algodoeiro antes de ser absorvido pelas plantas. O objetivo deste trabalho foi avaliar a lavagem do CM aplicado no algodoeiro por diferentes laminas de chuva simulada. Os tratamentos constaram de três doses do regulador à base de cloreto de mepiquat: 0, 15.0 e 30.0 g ha-1 e quatro lâminas de chuva simulada: 5, 10, 20 e 40 mm, mais um tratamento sem chuva. Foram utilizados vasos de 12 litros de capacidade e a cultivar Delta Opal. Os parâmetros avaliados foram: altura de plantas, número de ramos reprodutivos, massa de matéria seca, retenção de estruturas reprodutivas e área foliar. Quanto maior a intensidade de chuva ocorrida após a aplicação do regulador maior foi o comprometimento da ação do produto, que repercutiu em interferência no crescimento das plantas. Chuvas de 5.0 mm, ocorridas 90 minutos após a aplicação do cloreto de mepiquat, já causaram prejuízo na ação do produto no crescimento do algodoeiro, sendo o efeito maior com o aumento da quantidade de chuva simulada.

Using error bounds to compare aggregated generalized transportation models

A comparative study of aggregation error bounds for the generalized transportation problem is presented. A priori and a posteriori error bounds were derived and a computational study was performed to (a) test the correlation between the a priori, the a posteriori, and the actual error and (b) quantify the difference of the error bounds from the actual error. Based on the results we conclude that calculating the a priori error bound can be considered as a useful strategy to select the appropriate aggregation level. The a posteriori error bound provides a good quantitative measure of the actual error.

Leaching of nitrate and ammonium from cover crop straws as affected by rainfall

Nitrogen (N) mineralization dynamics in no-till systems is affected, among other factors, by N amount and quality in the mulch and by climatic conditions. Leaching of NO3-N and NH4-N from six plant species used as soil cover crops in tropical environments were evaluated when the straw was submitted to rainfall after chemical desiccation. Millet (Pennisetum glaucum), guinea sorghum (Sorghum vulgare), black oat (Avena strigosa), triticale (Triticum secale), Indian hemp (Crotalaria juncea), and brachiaria (Brachiaria decumbens) were grown in a greenhouse, in Botucatu-SP, Brazil. Forty-five days after emergence, the plants were cut at the root collar, oven-dried, and submitted to simulated rainfalls of 4.4, 8.7, 17.04, 34.9, and 69.8 mm, considering an amount of straw equivalent to 8 t ha(-1) of dry matter. The amounts of N-NO3- extracted from the straw by rainwater were very small. However, accumulated rainfall around 70 mm caused ammonium leaching ranging from 2.5 to 9.5kg ha(-1), depending on the species. Plant residues of triticale and black oat (grasses) and Indian hemp (legume) showed high N leaching intensity with the first rains after chemical desiccation. The amount of N leached from straw was highly correlated with N tissue content.

An intelligent system to real time rainfall prediction using radar data

This work presents a new approach for rainfall measurements making use of weather radar data for real time application to the radar systems operated by institute of Meteorological Research (IPMET) - UNESP - Bauru - SP-Brazil. Several real time adjustment techniques has been presented being most of them based on surface rain-gauge network. However, some of these methods do not regard the effect of the integration area, time integration and distance rainfall-radar. In this paper, artificial neural networks have been applied for generate a radar reflectivity-rain relationships which regard all effects described above. To evaluate prediction procedure, cross validation was performed using data from IPMET weather Doppler radar and rain-gauge network under the radar umbrella. The preliminary results were acceptable for rainfalls prediction. The small errors observed result from the spatial density and the time resolution of the rain-gauges networks used to calibrate the radar.