An adaptation of the SCS-ACRU hydrograph generating technique for application in Eritrea.

Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2004.Many techniques have been developed over the years in first world countries for the estimation of flood hydrographs from small catchments for application in design, management and operations of water related issues. However, relatively little attention has been directed towards the transfer and adaptation of such techniques to developing countries in which major hydrological decisions are crucially needed, but in which a scarcity of quality hydrological data often occurs. As a result, hydrologists and engineers in developing countries are frequently unable to alleviate the problems that extreme rainfall events can create through destructive flood flows or, alternatively, they do not possess the appropriate tools with which to design economically viable hydraulic structures. Eritrea is a typical example of a developing country which faces difficulties in regard to the adaptation of an appropriate design flood estimation technique for application on small catchments. As a result, the need has arisen to adapt a relatively simple and robust design flood model that can aid hydrologists and engineers in making economic and safe designs of hydraulic structures in small catchments. One objective of this study was, therefore, to review approaches to hydrological modelling and design flood estimation techniques on small catchments, in order to identify the barriers regarding their adaptation, as well as to assist in the selection of an appropriate technique for application, in Eritrea. The southern African adaptation of the SCS (i.e. Soil Conservation Service) design hydrograph technique, which has become a standard method for design flood estimation from small catchments in that region, was selected for application on small catchments in Eritrea for several reasons. It relies on the determination of a simple catchment response index in the form of an initial Curve Number (CN), which reflects both the abstraction characteristics and the non-linear stormflow responses of the catchment from a discrete rainfall event. Many studies on the use of SCS-based hydrological models have identified that adjustment of the initial CN to a catchment's antecedent soil moisture (ASM) to be crucial, as the ASM has been found to be one of the most sensitive parameters for accurate estimates of design flood volumes and peak discharges. In hydrologically heterogeneous regions like Eritrea, the hypothesis was postulated that simulations using a suitable soil water budgeting procedure for CN adjustment would lead to improved estimates of design flood volumes and peak discharges when compared with adjustments using the conventional SCS antecedent moisture conditions (SCS-AMC) method. The primary objective of this dissertation was to develop a surrogate methodology for the soil water budgeting procedure of CN adjustment, because any direct applications of soil water budgeting techniques are impractical in most parts of Eritrea owing to a scarcity of adequate and quality controlled hydrological information. It was furthermore hypothesised that within reasonably similar climatic regions, median changes in soil moisture storage from the socalled "initial" catchment soil moisture conditions, i.e. LIS, were likely to be similar, while between different climatic regions median LISs were likely to be different. Additionally, it was postulated that climatic regions may be represented by a standard climate classification system. Based on the above hypotheses, the Koppen climate classification, which can be derived from mean monthly rainfall and temperature information, was first applied to the 712 relatively homogeneous hydrological response zones which had previously been identified in southern Africa. A high degree of homogeneity of median values of LIS, derived by the daily time step ACRU soil moisture budgeting model, was observed for zones occurring within each individual Koppen climate class (KCC) - this after a homogeneity test had been performed to check if zones falling in a specific KCC had similar values of median LIS. Further assessment within each KCC found in southern Africa then showed that a strong relationship existed between LIS and Mean Annual Precipitation (MAP). This relationship was, however, different between KCCs. By developing regression equations, good simulations of median LIS from MAP were observed in each KCC, illustrating the potential application of the Koppen climate classification system as an indicator of regional median LIS, when only very basic monthly climatological information is available. The next critical task undertaken was to test whether the estimate of median LIS from MAP by regression equation for a specific Koppen climate class identified in southern Africa would remain similar for an identical Koppen climatic region in Eritrea. As already mentioned, LIS may be determined from daily time step hydrological soil moisture budget models such as ACRU model. The performance of the ACRU stormflow modelling approach was, therefore, first verified on an Eritrean gauged research catchment, viz. the Afdeyu, in order to have confidence in the use of values of LIS generated by it. A SCS-ACRU stormflow modelling approach was then tested on the same catchment by using the new approach of CN adjustment, termed the ACRU-Koppen method, and results were compared against stormflow volumes obtained using the SCS-AMC classes and the Hawkins' soil water budgeting procedures for CN adjustment, as well as when CNs remain unadjusted. Despite the relatively limited level of information on climate, soils and land use for the Afdeyu research catchment, the ACRU model simulated both daily and monthly flows well. By comparing the outputs generated from the SCS model when using the different methods of CN adjustment, the ACRU-Koppen method displayed better levels of performances than either of the other two SCS-based methods. A further statistical comparison was made among the ACRU, the SCS adjusted by ACRU-Koppen, the SCS adjusted by AMC classes and the unadjusted SCS models for the five highest stormflows produced from the five highest daily rainfall amounts of each year on the Afdeyu catchment. The ACRU model produced highly acceptable statistics from stormflow simulations on the Afdeyu catchment when compared to the SCS-based estimates. In comparing results from the ACRU-Koppen method to those from the SCS-AMC and unadjusted CN methods it was found that, statistically, the ACRU-Koppen performed much better than either of the other two SCS based methods. On the strength of these results the following conclusions were drawn: • Changes in soil moisture storage from so-called "initial" catchment soil moisture conditions, i.e. L1S, are similar in similar climatic regions; and • Using the ACRU-Koppen method ofCN adjustment, the SCS-SA model can, therefore, be adapted for application in Eritrea, for which Koppen climates can be produced from monthly rainfall and temperature maps. Finally, future research needs for improvements in the SCS-ACRU-Koppen (SAK) approach in light of data availability and the estimation ofL1S were identified. From the findings of this research and South African experiences, a first version of a "SCSEritrea" user manual based on the SAK modelling approach has been produced to facilitate its use throughout Eritrea. This user manual, although not an integral part of this dissertation, is presented in its entirety as an Appendix. A first Version of the SCS-Eritrea software is also included

An empirical analysis of the effects of climate variables on national level economic growth

The influence of climate on economic growth is a topic of growing interest. Few studies have investigated the potential role that climate hazards and their cumulative effects have on the growth prospects for a country. Due to the relatively stationary spatial patterns of global climate, some regions and countries are more prone to climate hazards and climate variability than others. This study uses a precipitation index that preserves the spatial and temporal variability of precipitation and differentiates between precipitation maximums (such as floods) and minimums (such as droughts). The authors develop a year and country fixed effects regression model to test the influence of climate variables on measures of economic growth and activity. The results indicate that precipitation extremes (floods and droughts) are the dominant climate influence on economic growth and that the effects are significant and negative. The drought index is associated with a highly significant negative influence on growth of growth domestic product, while the flood index is associated with a negative influence on growth of gross domestic product and lagged effects on growth. Temperature has little significant effect. These results have important implications for economic projections of climate change impacts. In addition, adaptation strategies should give new consideration to the importance of water resources given the identification of precipitation extremes as the key climate influence on historical growth of gross domestic product.Climate Change Mitigation and Green House Gases,Science of Climate Change,Global Environment Facility,Climate Change Economics,Climate Change Impacts

Development of a framework for an integrated time-varying agrohydrological forecast system for Southern Africa: Initial results for seasonal forecasts

Uncertainty about hydro-climatic conditions in the immediate future (today), as well as the near (up to one week) and more distant futures (up to one season) remains a fundamental problem challenging decision makers in the fields such as water resources, agriculture, and many other water-sensitive sectors in Southern Africa. Currently many institutions, such as the SA Weather Service, provide weather and climate forecasts with lead times ranging from 1 d to one season. However, disconnects exist between the weather/climate forecasts and their links to agrohydrological models, and in the applications of forecast information for targeted agricultural and water-related decision-making. The skills level of the current weather and climate forecasts, and the mismatch in scales between the output from weather/climate models and the spatial scales at which hydrological models are applied, as well as the format of seasonal forecasts in that they cannot be used directly in agrohydrological models, are some of the problems identified in this study and are being addressed. This has necessitated the development of a GIS-based framework in which the ‘translation’ of weather and climate forecasts into more tangible agrohydrological forecasts such as streamflows, reservoir levels or crop yields is facilitated for all the inter-linked quaternary catchments for enhanced economic, environmental and societal decision making over South Africa in general, and in selected catchments in particular. For monthly and seasonal (i.e. 3-month lead time) forecasts, two methods, viz. the Historical Sequence Method and the Ensemble Re-Ordering Method have been developed to translate the triplet of forecast rainfall probabilities (i.e. above, near and below normal) into daily quantitative values of rainfall for use in hydrological models. The first method was applied together with the daily time step ACRU Model to simulate seasonal flow forecasts in the Mgeni catchment in KwaZulu-Natal, South Africa. In taking account of uncertainty in the seasonal rainfall forecasts through the process of translating these to daily streamflow simulations by the ACRU Model, some skilful initial forecasts of streamflows can be obtained which can assist decision makers to take protective action against the impacts of hydro-climatic variability.Keywords: GIS-based framework, translation of rainfall forecasts, ACRU Model, streamflow forecastin

Development of a framework for an integrated time-varying agrohydrological forecast system for southern Africa.

Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2007.Policy makers, water managers, farmers and many other sectors of the society in southern Africa are confronting increasingly complex decisions as a result of the marked day-to-day, intra-seasonal and inter-annual variability of climate. Hence, forecasts of hydro-climatic variables with lead times of days to seasons ahead are becoming increasingly important to them in making more informed risk-based management decisions. With improved representations of atmospheric processes and advances in computer technology, a major improvement has been made by institutions such as the South African Weather Service, the University of Pretoria and the University of Cape Town in forecasting southern Africa’s weather at short lead times and its various climatic statistics for longer time ranges. In spite of these improvements, the operational utility of weather and climate forecasts, especially in agricultural and water management decision making, is still limited. This is so mainly because of a lack of reliability in their accuracy and the fact that they are not suited directly to the requirements of agrohydrological models with respect to their spatial and temporal scales and formats. As a result, the need has arisen to develop a GIS based framework in which the “translation” of weather and climate forecasts into more tangible agrohydrological forecasts such as streamflows, reservoir levels or crop yields is facilitated for enhanced economic, environmental and societal decision making over southern Africa in general, and in selected catchments in particular. This study focuses on the development of such a framework. As a precursor to describing and evaluating this framework, however, one important objective was to review the potential impacts of climate variability on water resources and agriculture, as well as assessing current approaches to managing climate variability and minimising risks from a hydrological perspective. With the aim of understanding the broad range of forecasting systems, the review was extended to the current state of hydro-climatic forecasting techniques and their potential applications in order to reduce vulnerability in the management of water resources and agricultural systems. This was followed by a brief review of some challenges and approaches to maximising benefits from these hydro-climatic forecasts. A GIS based framework has been developed to serve as an aid to process all the computations required to translate near real time rainfall fields estimated by remotely sensed tools, as well as daily rainfall forecasts with a range of lead times provided by Numerical Weather Prediction (NWP) models into daily quantitative values which are suitable for application with hydrological or crop models. Another major component of the framework was the development of two methodologies, viz. the Historical Sequence Method and the Ensemble Re-ordering Based Method for the translation of a triplet of categorical monthly and seasonal rainfall forecasts (i.e. Above, Near and Below Normal) into daily quantitative values, as such a triplet of probabilities cannot be applied in its original published form into hydrological/crop models which operate on a daily time step. The outputs of various near real time observations, of weather and climate models, as well as of downscaling methodologies were evaluated against observations in the Mgeni catchment in KwaZulu-Natal, South Africa, both in terms of rainfall characteristics as well as of streamflows simulated with the daily time step ACRU model. A comparative study of rainfall derived from daily reporting raingauges, ground based radars, satellites and merged fields indicated that the raingauge and merged rainfall fields displayed relatively realistic results and they may be used to simulate the “now state” of a catchment at the beginning of a forecast period. The performance of three NWP models, viz. the C-CAM, UM and NCEP-MRF, were found to vary from one event to another. However, the C-CAM model showed a general tendency of under-estimation whereas the UM and NCEP-MRF models suffered from significant over-estimation of the summer rainfall over the Mgeni catchment. Ensembles of simulated streamflows with the ACRU model using ensembles of rainfalls derived from both the Historical Sequence Method and the Ensemble Re-ordering Based Method showed reasonably good results for most of the selected months and seasons for which they were tested, which indicates that the two methods of transforming categorical seasonal forecasts into ensembles of daily quantitative rainfall values are useful for various agrohydrological applications in South Africa and possibly elsewhere. The use of the Ensemble Re-ordering Based Method was also found to be quite effective in generating the transitional probabilities of rain days and dry days as well as the persistence of dry and wet spells within forecast cycles, all of which are important in the evaluation and forecasting of streamflows and crop yields, as well as droughts and floods. Finally, future areas of research which could facilitate the practical implementation of the framework were identified

Effects of Nanoclay Modification on Rheology of Bitumen and on Performance of Asphalt Mixtures

Civil Engineering and GeosciencesStructural EngineeringRoad and Railway Engineerin