[Truncated abstract] Pesticides are often transported to streams and/or groundwater as a result of the occurrence of rainfall events which trigger surface runoff or rapid preferential flow through the unsaturated zone. Much of the theory of solute transport has been derived assuming steady state or slowly varying upper boundary conditions and continuous, averaged process descriptions. However, a review of pesticide dynamics reveals that pesticides are episodically transported, predominantly through discrete flow pathways and this transport is often initiated as a near surface process, driven by naturally variable and intermittent rainfall intensities. The objective of the thesis is to better understand how the structure of natural variability of rainfall intensities impacts upon pesticide transport by these fast flow processes. We first conducted an analysis of a lysimeter leaching experiment that was aimed at identifying the rainfall controls on herbicide transport. Multivariate analyses revealed that average water balance behaviour at low temporal resolution controlled water and bromide transport while extreme rainfall events and rainfall event frequency controlled herbicide transport. A minimalist event based modelling approach was able to simulate the observed herbicide transport without or with only minor calibration. ... Finally we conduct a climate based regional risk assessment of pesticide leaching for the Wheatbelt region of the south-west of Western Australia. This is done for a suite of pesticides on a single soil to evaluate the impact of rainfall variability alone. Moderately sorbing, slowly degrading solutes have a greater regional potential for rapid leaching than both strongly and weakly sorbing solutes. High leaching potentials are found along the western and southern coast and in the far-east, with a band of low leaching potential through the central Wheatbelt. This is despite higher annual rainfall in the central areas compared to the east, and it is found that this occurs because of a change in the dominant fast flow triggers from frequent low intensity rainfall on the coasts to high intensity infrequent storms in the east. The coefficient of variation of annual leaching loads is similarly distributed. Spatial patterns of leaching potential depend upon chemical properties and application time. Peak loads of chemicals to fast flow pathways are found to converge to mid-winter, indicating periods of high loads of multiple pesticides may be an unavoidable consequence of the seasonality of storm properties.

Department of Civil, Surveying and Environmental Engineering. Bibliography: leaves 246-255

In recent years, increased demands have been placed on hydrologists to find the most effective methods of making predictions of hydrologic variables in ungauged basins. A huge part of the southern African region is ungauged and, in gauged basins, the extent to which observed flows represent natural flows is unknown, given unquantified upstream activities. The need to exploit water resources for social and economic development, considered in the light of water scarcity forecasts for the region, makes the reliable quantification of water resources a priority. Contemporary approaches to the problem of hydrological prediction in ungauged basins in the region have relied heavily on calibration against a limited gauged streamflow database and somewhat subjective parameter regionalizations using areas of assumed hydrological similarity. The reliance of these approaches on limited historical records, often of dubious quality, introduces uncertainty in water resources decisions. Thus, it is necessary to develop methods of estimating model parameters that are less reliant on calibration. This thesis addresses the question of whether physical basin properties and the role they play in runoff generation processes can be used directly in the estimation of parameter values of the Pitman monthly rainfall-runoff model. A physically-based approach to estimating the soil moisture accounting and runoff parameters of a conceptual, monthly time-step rainfall-runoff model is proposed. The study investigates the physical meaning of the model parameters, establishes linkages between parameter values and basin physical properties and develops relationships and equations for estimating the parameters taking into account the spatial and temporal scales used in typical model applications. The estimationmethods are then tested in selected gauged basins in southern Africa and the results of model simulations evaluated against historical observed flows. The results of 71 basins chosen from the southern African region suggest that it is possible to directly estimate hydrologically relevant parameters for the Pitman model from physical basin attributes. For South Africa, the statistical and visual fit of the simulations using the revised parameters were at least as good as the current regional sets, albeit the parameter sets being different. In the other countries where no regionalized parameter sets currently exist, simulations were equally good. The availability, within the southern African region, of the appropriate physical basin data and the disparities in the spatial scales and the levels of detail of the data currently available were identified as potential sources of uncertainty. GIS and remote sensing technologies and a widespread use of this revised approach are expected to facilitate access to these data.

This thesis presents a discussion on the study undertaken in the application of the monthly time step Pitman rainfall-runoff model to the Kafue River basin. The study constituted one of the initial steps in the capacity building and expansion of the application of hydrologic models in the southern African region for water resources assessment, one of the core areas of the Southern African FRIEND project (Flow Regimes from International Experimental Network Data). The research process was undertaken in four major stages, each stage working towards achieving the research objectives. The first stage was the preparation of spatial data which included the selection and delineation of sub-catchments and inclusion of spatial features required to run the Pitman model and transferring the spatial data into SPATSIM. The second stage was the preparation of input data, mainly rainfall, streamflow, evaporation, and water abstraction data. This information was then imported into SPATSIM, which was able to assist in the further preparation of data by assessment of the input data quality, linking of observed flows and spatial interpolation of point rainfall data to average catchment rainfall in readiness for running and calibration of the model. The third stage was the running and calibration of the Pitman model. Use was made of both the automatic calibration facility, as well as manual calibration by means of the time series graph display and analysis facility of SPATSIM. Model calibration was used to obtain the best fit and an acceptable correlation between the simulated and the observed flows and to obtain simulation parameter sets for sub-catchments and regions within the Kafue catchment. The fourth stage was the analysis and evaluation of the model results. This included verification of results over different time periods and validation and testing of parameter transfers to other catchments. This stage also included the evaluation of SPATSIM as a tool for applying the model and as a database for the processing and storage of water resources data. The study’s output includes: A comprehensive database of hydrometeorological, physical catchment characteristics, landuse and water abstraction information for the Kafue basin; calibrated Pitman model parameters for the sub-catchments within the Kafue basin; recommendations for future work and data collection programmes for the application of the model. The study has also built capacity by facilitating training and exposure to rainfall-runoff models (specifically the Pitman model) and associated software, SPATSIM. In addition, the dissemination of the results of this study will serve as an effective way of raising awareness on the application of the Pitman model and the use of the SPATSIM software within Zambia and the region. The overall Pitman model results were found to be satisfactory and the calibrated model is able to reproduce the observed spatial and temporal variations in streamflow characteristics in the Kafue River basin.

Orientador: Célia Regina Lopes Zimback / Banca: Carlos Alberto Oliveira de Matos / Banca: Paulo Cesar Sentelhas / Resumo: As medidas diárias de chuva acumulada são informações de suma importância para a agricultura como, por exemplo, na aplicação de insumos, na estimativa da irrigação ou em cálculos de balanços hídricos. As informações atualmente disponíveis sobre chuvas diárias são, no geral, provenientes de pluviômetros convencionais de operação manual. A eficiência de pluviômetros em mensurar a precipitação em uma área está diretamente relacionada à distância entre os equipamentos. A maior rede de pluviômetros em operação no Estado de São Paulo, que está sob responsabilidade do DAEE (Departamento de Águas e Energia Elétrica), disponibiliza os totais diários com vários meses de defasagem, impossibilitando a utilização imediata dessas informações. A utilização de radares meteorológicos para a quantificação de chuva está associada à eficiência de equações de conversão do sinal eletrônico do radar (Z) em chuva (R), denominada relação ZR. Utilizando dados pluviométricos diários, entre 1995 e 1999, de sete estações dispostas numa área de 1.500 km2, e comparando com dados de radar no mesmo período, foi possível estabelecer uma relação ZR probabilística visando à acumulação diária da precipitação, representativa a área delimitada. A aplicação da relação ZR ajustada à área delimitada resultou em acumulações diárias mais próximas dos resultados observados pelos dados dos pluviômetros, quando comparadas aos resultados da relação ZR atualmente em uso, nos radares da UNESP. Nas acumulações de chuva, obtidas por radar, foram aplicadas interpolações geoestatísticas, resultando na melhoria da distribuição espacial dessas acumulações. Objetivando a complementação espacial e temporal das informações de chuva acumulada atualmente disponíveis, este estudo demonstra uma metodologia apropriada para determinação... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The daily measures of accumulated rain are very important information for agriculture, for example, in the fertilezer applications, the estimate of the irrigation or calculation of water balance. Currently, the information available of daily rain is, generally, provenient form conventional rain gauges manually operated. The efficiency of rain gauges in measuring the precipitation in an area is directly related to the distance between equipment. The biggest rain gauges net operating in the State of São Paulo in under responsibility of DAEE (Department of Water and Electric Energy) which provides daily information with several months of delay, impeding the information to be used immediately. The use of meteorological radars for the quantification of rain is associated to the efficiency of conversion equations of the radar electronic sign (Z) in rain (R), known as relationship ZR. Using daily rain data between 1995 and 1999, from seven stations located in an area of 1,500 km2 and comparing whit data from the radar in the same period, it was possible do establish a ZR probabilistic relation aiming at the daily amount of precipitation, which represents the delimited area. The application of the ZR relationship adjusted to the delimited area resulted in daily accumulation closer to the results observed by the rain gauges data when compared to the results of the ZR relationship currently in use in radar operated by UNESP. In the accumulation of rain, taken by the radar, geostatistic interpolations were applied, and the results were a better spatial distribution of these accumulations. Objectifying the space and temporal complementation of currently available the accumulated rain information, this research demonstrates an appropriate methodology to determinate regional ZR relationship, based on data from rain gauges, and the application of geoestaistic interpolation... (Complete abstract click electronic access below) / Mestre

The effect of altitude on individual storm precipitation in some of the San Dimas experimental watersheds is investigated. It is found that there is a well- defined increase of storm precipitation with altitude for storms greater than one inch. This increase is a linear function of storm depth. Using 41 storms of different magnitudes, a precipitation -altitude relationship is derived for a small area in the San Dimas Experimental Forest. The regionalization of this relationship and its transferability are tested by analyzing differences (errors) between computed and observed storm precipitation values in each case. In testing the regionalization of the precipitation- altitude relationship by computing mean areal storm precipitation over a larger area the standard error of estimate is around 11 percent. In transfering the same relationship the results are not as good and give a standard error of 16 percent. For individual points, however, the error is much higher. A rainfall- runoff model is used as a tool for evaluating the effect of precipitation errors, on simulated streamflow, in a watershed of 4.5 square miles. For annual flows, errors range between 3.4 and 12.3 percent while errors in simulated monthly flows are as high as 22 percent. It is also evident that there is a strong dependence of the error magnitude on the state (wet, dry, etc.) of the preceding year or months, whichever is applicable. An error propagation is observed as a result of consistently over -estimating the precipitation input to the model. This evaluation is more of a qualitative nature and the values of error given should be viewed in this sense.

Climate change threatens global food security by increasing extreme-weather shocks and reducing the productivity of major global crops. While recent research has highlighted the risk of rising extreme heat, comparatively little is known about how the intensity distribution of rainfall, and rainfall’s interactions with heat, influence global crops. Further, as the broader climate transition gains momentum, the industrial activities needed to mitigate and adapt to climate change will emit CO₂. These emissions remain unquantified and largely ignored in research and policy, and thus present an under-assessed risk to crops and society at large.This thesis advances the understanding of present and future agricultural risks from two aspects of hydroclimatic complexity: hourly rainfall intensity and temperature-moisture (T-M) couplings. Both aspects are expected to shift under climate change, with highly uncertain crop impacts. It further simulates the adaptation and mitigation emissions embedded in the broader climate transition, illuminating a previously under-appreciated benefit of enhance climate ambition. Climate warming is expected to intensify rainfall, decreasing the frequency of drizzle while boosting heavy and extreme events. I show that surprisingly heavy rainfall is optimal for US maize and soy yields, with yield loss due to drizzle and very extreme downpours. As a result, the future concentration of rainfall into fewer, heavier hourly events will benefit crop yields 2-3%, partly offsetting larger damages from warming. T-M couplings arising from land-air interactions and atmospheric circulation may shift under 21st Century warming, altering the likelihood of concurrent heat and drought extremes, with uncertain risks to crops. I demonstrate that maize and soy grown in regions with strong T-M couplings historically suffered enhanced crop sensitivity to heat. These couplings will strengthen over most of global croplands this century, worsening the impact of warming on crops by 5% globally, with large regional variations. The energetic demands of the broader climate transition – such as steel for wind turbines, and concrete for coastal barriers – will initially be satisfied by fossil fuels. I show that simulated mitigation and adaptation will emit 185GtCO₂ by 2100 under a transition path consistent with current policies (~2.7°C warming by 2100), equivalent to half the remaining carbon budget for 1.5°C. However, these emissions can be reduced by 90% under a 1.5°C transition path, a previously unidentified co-benefit of enhanced climate ambition.

No description available.

published_or_final_version / Applied Geosciences / Master / Master of Science

Dissertation submitted to the Faculty of Science, University of the Witwatersrand, for completion of the Degree of' Master of Science / The atmospheric response of the Colorado State University Regional Atmospheric Modelling System (RAMS) to sea-surface temperature anomaliesis investigated. A period of four days was chosen from 21 to 24 January 1981, where focus was placed on the development and dissipation of a tropical-temperate trough across Southern Africa. Previous experimenting this mesoscalenumerical model have detemined the kinematic, moisture, and thermodynamic nature of these synoptic features. The research in this dissertation focuses specifically on the sensitivity of the numerical model's simulated responses to positive sea-surface temperature anomalies. Three separate experiments were devised, in which positive anomalous temperatures were added to the ocean surface north of Madagascar (in the tropical Indian Ocean), at the region of the Agulhas Current retroflection, and along the tropical African west coast (in the Northern Benguela and Angola currents). The circulation aspects of each sensitivity test were investigated through the comparison of simulated variables such as vapour and cloud mixing ratios, temperature, streamlines and vertical velocity, with the same variables created by a control simulation. The results indicate that for the first sensitivity test, (the Madagascar anomaly), cyclogenesis was initiated over the area of modified sea temperatures which resulted in a marginal decrease in continental precipitation. The second sensitivity test (over the Agulhas retroflection) produced a much smaller simulated response to the addition of anomalously warm sea temperatures than the tropical Indian Ocean anomaly. Instability and precipitation values increased over the anomalously warm retroflection region, and were slowly transferred along the westerly wave perturbation and the South African east coast. The third sensitivity experiment showed a predominantly localised simulated increase in precipitation over Gabon and the Congo, with the slow southward progression of other simulated circulation differences taking place. The small perturbations in each of the simulated meteorological responses are consistent with the expected climate response to anomalously warm sea-surface temperatures in those areas. / AC 2018