Comparing CFSR and conventional weather data for discharge and soil loss modelling with SWAT in small catchments in the Ethiopian Highlands

Accurate rainfall data are the key input parameter for modelling river discharge and soil loss. Remote areas of Ethiopia often lack adequate precipitation data and where these data are available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and soil loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 112 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed soil loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Soil loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and soil loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible.

Anthropogenic aerosol emissions and rainfall decline in South-West Australia - accompanying model results in NetCDF format

It is commonly understood that the observed decline in precipitation in South-West Australia during the 20th century is caused by anthropogenic factors. Candidates therefore are changes to large-scale atmospheric circulations due to global warming, extensive deforestation and anthropogenic aerosol emissions - all of which are effective on different spatial and temporal scales. This contribution focusses on the role of rapidly rising aerosol emissions from anthropogenic sources in South-West Australia around 1970. An analysis of historical longterm rainfall data of the Bureau of Meteorology shows that South-West Australia as a whole experienced a gradual decline in precipitation over the 20th century. However, on smaller scales and for the particular example of the Perth catchment area, a sudden drop in precipitation around 1970 is apparent. Modelling experiments at a convection-resolving resolution of 3.3km using the Weather and Research Forecasting (WRF) model version 3.6.1 with the aerosol-aware Thompson-Eidhammer microphysics scheme are conducted for the period 1970-1974. A comparison of four runs with different prescribed aerosol emissions and without aerosol effects demonstrates that tripling the pre-1960s atmospheric CCN and IN concentrations can suppress precipitation by 2-9%, depending on the area and the season. This suggests that a combination of all three processes is required to account for the gradual decline in rainfall seen for greater South-West Australia and for the sudden drop observed in areas along the West Coast in the 1970s: changing atmospheric circulations, deforestation and anthropogenic aerosol emissions.

A space-time hybrid hourly rainfall model for derived flood frequency analysis

For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series. First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in reproducing observed flood frequencies. The presented model has the potential to be used for ungauged locations through regionalisation of the model parameters.

Long-term Trends in Magnitude and Frequency of Extreme Rainfall Events in Florida

This study computed trends in extreme precipitation events of Florida for 1950-2010. Hourly aggregated rainfall data from 24 stations of the National Climatic Data Centre were analyzed to derive time-series of extreme rainfalls for 12 durations, ranging from 1 hour to 7 day. Non-parametric Mann-Kendall test and Theil-Sen Approach were applied to detect the significance of trends in annual maximum rainfalls, number of above threshold events and average magnitude of above threshold events for four common analysis periods. Trend Free Pre-Whitening (TFPW) approach was applied to remove the serial correlations and bootstrap resampling approach was used to detect the field significance of trends. The results for annual maximum rainfall revealed dominant increasing trends at the statistical significance level of 0.10, especially for hourly events in longer period and daily events in recent period. The number of above threshold events exhibited strong decreasing trends for hourly durations in all time periods.

INTERANNUAL VARIABILITY IN TROPICAL ESTUARINE COPEPOD ASSEMBLAGES OFF NORTHEASTERN BRAZIL

We studied copepod assemblage variability among years, seasons, and tidal states in the Mucuri River estuary (Bahia State, Brazil). Zooplankton samples were collected seasonally through five years (2002-2006) at three sampling stations, one of which was sampled over a complete tidal cycle (two ebb and two flood tides). Temperature, salinity, river flux, and rainfall data were collected. Winter and summer represented dry and wet seasons, respectively. Copepod abundances ranged from 40 to 63% of the total zooplankton assemblage and comprised 46 taxa, among which, common estuarine species such as Temora turbinata (first record for the studied area), Parvocalanus crassirostris, Acartia lilljeborgi, Oithona hebes were the most abundant (euryhaline species). Interannual and seasonal variations were most marked in stenohaline species, e.g.. Notodiaptomus sp. and Thermocyclops minutus; density variations of euryhaline species, which made up the majority of the abundant taxa, were most closely related to tides. Diversity and richness also followed an intertidal pattern of variation.

Size of the first spring generation of Helicoverpa punctigera (Wallengren) (Lepidoptera : Noctuidae) and winter rain in central Australia

Serious infestations of Helicoverpa punctigera are experienced yearly in the eastern cropping regions of Australia. Regression analysis was used to determine whether the size of the first generation in spring (G(1)), which is comprised mostly of immigrants from inland Australia, was related to monthly rainfall in inland winter breeding areas. Data from two long series of light-trap catches at Narrabri in New South Wales (NSW) and Turretfield in South Australia (SA) were used in the analyses. The size of G1 at Narrabri in each year was significantly regressed on the amount of rainfall in western Queensland and NSW in May and June. The size of G1 at Turretfield each year was significantly regressed on the amount of rain in May, June and July in western Queensland and NSW and also in the desert of central Western Australia. Low r(2) values of the regressions suggest that rainfall data for more sites, as well as biological and other physical factors, such as temperature, evaporation, and prevailing wind systems, may need to be included to improve forecasts of the potential magnitude of the infestations in coastal cropping regions.

Forecasting regional crop production using SOI phases: an example for the Australian peanut industry

Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing bodies. The industry could profitably use forecasts of likely production to adjust their operations strategically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.

Associations involving delays (particularly long delays) between certain weather parameters and geomagnetic activity

Four sunspot-minimum periods (1963-1966, 1971-1977, 1983-1987 and 1992-1997) have been examined for the results which are presented. Using several different weather parameters, tropospheric gravity waves, enhanced cold fronts and two rainfall data sets in Eastern Australia, associations at reasonably high levels of significance have been found with enhanced geomagnetic activity (EGA). Statistically this EGA involved either short delays of several days or long delays of about 20 days. The geomagnetic parameters used were (a) the AE index (b) the hourly H component for a number of stations and (c) the daily K-P-sum value. The K-P-sum analyses have shown that the EGA associated with the delays form part of four or five cycles of recurrent geomagnetic activity for 27-day periodicities. Furthermore statistically two recurrent cycles are found to exist concurrently, one apparently related to the short delays and the other to the long delays. Periodicities of 13.5 days are created because the two sets are displaced from each other by approximately this interval. A brief reference is made to the 13.5 periodicity known to exist for geomagnetic activity and the evidence in the literature for active regions on the sun to be displaced by 180 degrees of solar longitude.

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

Estimation of the extreme flash flood evolution in Barcelona county from 1351 to 2005

Every year, flash floods cause economic losses and major problems for undertaking daily activity in the Catalonia region (NE Spain). Sometimes catastrophic damage and casualties occur. When a long term analysis of floods is undertaken, a question arises regarding the changing role of the vulnerability and the hazard in risk evolution. This paper sets out to give some information to deal with this question, on the basis of analysis of all the floods that have occurred in Barcelona county (Catalonia) since the 14th century, as well as the flooded area, urban evolution, impacts and the weather conditions for any of most severe events. With this objective, the identification and classification of historical floods, and characterisation of flash-floods among these, have been undertaken. Besides this, the main meteorological factors associated with recent flash floods in this city and neighbouring regions are well-known. On the other hand, the identification of rainfall trends that could explain the historical evolution of flood hazard occurrence in this city has been analysed. Finally, identification of the influence of urban development on the vulnerability to floods has been carried out. Barcelona city has been selected thanks to its long continuous data series (daily rainfall data series, since 1854; one of the longest rainfall rate series of Europe, since 1921) and for the accurate historical archive information that is available (since the Roman Empire for the urban evolution). The evolution of flood occurrence shows the existence of oscillations in the earlier and later modern-age periods that can be attributed to climatic variability, evolution of the perception threshold and changes in vulnerability. A great increase of vulnerability can be assumed for the period 1850¿1900. The analysis of the time evolution for the Barcelona rainfall series (1854¿2000) shows that no trend exists, although, due to changes in urban planning, flash-floods impact has altered over this time. The number of catastrophic flash floods has diminished, although the extraordinary ones have increased.

Geomorphological method in the elaboration of hazard maps for flash-floods in the municipality of Jucuarán (El Salvador)

This work deals with the elaboration of flood hazard maps. These maps reflect the areas prone to floods based on the effects of Hurricane Mitch in the Municipality of Jucuarán of El Salvador. Stream channels located in the coastal range in the SE of El Salvador flow into the Pacific Ocean and generate alluvial fans. Communities often inhabit these fans can be affected by floods. The geomorphology of these stream basins is associated with small areas, steep slopes, well developed regolite and extensive deforestation. These features play a key role in the generation of flash-floods. This zone lacks comprehensive rainfall data and gauging stations. The most detailed topographic maps are on a scale of 1:25 000. Given that the scale was not sufficiently detailed, we used aerial photographs enlarged to the scale of 1:8000. The effects of Hurricane Mitch mapped on these photographs were regarded as the reference event. Flood maps have a dual purpose (1) community emergency plans, (2) regional land use planning carried out by local authorities. The geomorphological method is based on mapping the geomorphological evidence (alluvial fans, preferential stream channels, erosion and sedimentation, man-made terraces). Following the interpretation of the photographs this information was validated on the field and complemented by eyewitness reports such as the height of water and flow typology. In addition, community workshops were organized to obtain information about the evolution and the impact of the phenomena. The superimposition of this information enables us to obtain a comprehensive geomorphological map. Another aim of the study was the calculation of the peak discharge using the Manning and the paleohydraulic methods and estimates based on geomorphologic criterion. The results were compared with those obtained using the rational method. Significant differences in the order of magnitude of the calculated discharges were noted. The rational method underestimated the results owing to short and discontinuous periods of rainfall data with the result that probabilistic equations cannot be applied. The Manning method yields a wide range of results because of its dependence on the roughness coefficient. The paleohydraulic method yielded higher values than the rational and Manning methods. However, it should be pointed out that it is possible that bigger boulders could have been moved had they existed. These discharge values are lower than those obtained by the geomorphological estimates, i.e. much closer to reality. The flood hazard maps were derived from the comprehensive geomorphological map. Three categories of hazard were established (very high, high and moderate) using flood energy, water height and velocity flow deduced from geomorphological and eyewitness reports.

Estimation of alluvial recharge in the semiarid

In areas where there is irrigated agriculture, the recuperation of water reserves in alluvial aquifers may occur preferentially due to precipitation. Recharging can be evaluated from variation information of water depth measured in piezometers or observation wells. Thus, the aim of this research is to study the recharge in the alluvial aquifer formed by the Mimoso temporary stream in the semiarid region of Pernambuco (PE), Brazil, using the method of the fluctuation of the water level. This system is typical on the Brazilian Northeast semiarid region, using groundwater for domestic supply and for irrigation on small scale agriculture. Monthly potentiometric levels and rainfall data were used. The selected period for the study, from January 2002 to October 2009, involved extreme events of flooding and droughts as well as regular years, providing a better understanding of the behavior of the alluvial recharge. It was found that the system responds significantly to precipitation events. It was also observed that even with different soil textures in the study area, recharge factors were not significantly different. The study provided a better understanding of the behavior of aquifer recharge and its relationship with the soil and the rainfall events in the region.

Analyse bayésienne et classification pour modèles continus modifiés à zéro

Les modèles à sur-représentation de zéros discrets et continus ont une large gamme d'applications et leurs propriétés sont bien connues. Bien qu'il existe des travaux portant sur les modèles discrets à sous-représentation de zéro et modifiés à zéro, la formulation usuelle des modèles continus à sur-représentation -- un mélange entre une densité continue et une masse de Dirac -- empêche de les généraliser afin de couvrir le cas de la sous-représentation de zéros. Une formulation alternative des modèles continus à sur-représentation de zéros, pouvant aisément être généralisée au cas de la sous-représentation, est présentée ici. L'estimation est d'abord abordée sous le paradigme classique, et plusieurs méthodes d'obtention des estimateurs du maximum de vraisemblance sont proposées. Le problème de l'estimation ponctuelle est également considéré du point de vue bayésien. Des tests d'hypothèses classiques et bayésiens visant à déterminer si des données sont à sur- ou sous-représentation de zéros sont présentées. Les méthodes d'estimation et de tests sont aussi évaluées au moyen d'études de simulation et appliquées à des données de précipitation agrégées. Les diverses méthodes s'accordent sur la sous-représentation de zéros des données, démontrant la pertinence du modèle proposé. Nous considérons ensuite la classification d'échantillons de données à sous-représentation de zéros. De telles données étant fortement non normales, il est possible de croire que les méthodes courantes de détermination du nombre de grappes s'avèrent peu performantes. Nous affirmons que la classification bayésienne, basée sur la distribution marginale des observations, tiendrait compte des particularités du modèle, ce qui se traduirait par une meilleure performance. Plusieurs méthodes de classification sont comparées au moyen d'une étude de simulation, et la méthode proposée est appliquée à des données de précipitation agrégées provenant de 28 stations de mesure en Colombie-Britannique.

An agroclimatic assessment of the crop growth potential of south india

Usually, under rainfed conditions the growing period exists in the humid months. Hence, for agricultural planning knowledge about the variabilities of the duration of the humid seasons are very much needed. The crucial problem affecting agriculture is the persistency in receiving a specific amount of rainfall during a short period. Agricultural operations and decision making are highly dependent on the probability of receiving given amounts of rainfall; such periods should match the water requirements of different phenological phases of the crops. While prolonged dry periods during sensitive phases are detrimental to their growth and lower the yields, excess of rainfall causes soil erosion and loss of soil nutrients. These factors point to the importance of evaluation of wet and dry spells. In this study the weekly rainfall data have been analysed to estimate the probability of wet and dry periods at all selected stations of each agroclimatic zone and the crop growth potentials of the growing seasons have been analysed. The thesis consists of six Chapters.

Spatial and temporal characteristics of rain intensity in the peninsular Malaysia using TRMM rain rate

The present study is focused on the intensity distribution of rainfall in different classes and their contribution to the total seasonal rainfall. In addition, we studied the spatial and diurnal variation of the rainfall in the study areas. For the present study, we retrieved data from TRMM (Tropical Rain Measuring Mission) rain rate available in every 3 h temporal and 25 km spatial resolutions. Moreover, station rainfall data is used to validate the TRMM rain rate and found significant correlation between them (linear correlation coefficients are 0.96, 0.85, 0.75 and 0.63 for the stations Kota Bharu, Senai, Cameron highlands and KLIA, respectively). We selected four areas in the Peninsular Malaysia and they are south coastal, east coastal, west coastal and highland regions. Diurnal variation of frequency of rain occurrence is different for different locations. We noticed bimodal variation in the coastal areas in most of the seasons and unimodal variation in the highland/inland area. During the southwest monsoon period in the west coastal stations, there is no distinct diurnal variation. The distribution of different intensity classes during different seasons are explained in detail in the results