Browsing by Author "Smithers, Jeffrey Colin."

Now showing 1 - 20 of 34

An adaptation of the SCS-ACRU hydrograph generating technique for application in Eritrea.
(2004) Ghile, Yonas Beyene.; Schulze, Roland Edgar.; Smithers, Jeffrey Colin.
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.
Assessing and improving the simulation of runoff and design flood estimation in urban areas using the ACRU and SCS-SA models.
(2022) Ndlovu, Zama Sibahle.; Smithers, Jeffrey Colin.
Urbanisation is increasing at a rapid rate. Pervious and vegetated land is increasingly being replaced by impermeable surfaces (roads, pavements, driveways, parking lots, etc.) resulting in large portions of total imperviousness in catchments. The expansion of urban areas alters the natural underlying surface condition affecting catchment characteristics. The most common impacts of urbanisation on the hydrology of a catchment are increased runoff volumes, reduced baseflows owing to less infiltration taking place and a decrease in catchment response time. These changes can result in increased flood risk and subsequent damage to urban infrastructure and affect livelihoods. Therefore, accurate modelling of runoff and estimation of design floods of highly urbanised areas is necessary, especially in the often neglected catchments with informal settlements and infrastructure and in peri-urban catchments. Peri urban areas are defined as those areas located adjacent to a city area and have a mix of both rural and urban characteristics. Two rainfall-runoff models, namely the ACRU and the Visual SCS-SA model, were selected for application on catchments with typical South African urban conditions. The models have been developed and tested in urban catchments, however not extensively. The study areas are located in the South African urbanised cities of Tshwane and Pietermaritzburg. ACRU is a daily time step conceptual and physically-based agro-hydrological model that is relatively more data intensive compared to the simpler SCS-SA model. Therefore, information systems such as Remote Sensing (RS) and Geographic Information System (GIS) have been explored to aid as data sources and tools for acquiring model input parameters, at a more accurate level. The ACRU default values by Tarboton and Schulze (1992) and impervious area estimations derived by Loots (2020) were initially used to estimate the ACRU impervious parameters. Additionally, the pixel-based land cover classification method using satellite images was carried out in detail for this study as an attempt to map impervious surfaces and obtain impervious ACRU parameters with improved accuracy. Impervious land use classes were also extracted from the 2018 South African National Land Cover Database (SANLC), 2018 Global Man-made Impervious Surface (GMIS) and the 2010 Global Artificial Impervious Areas (GAIA). In order to use the ACRU and SCS-SA models confidently, the simulated results need to be verified against reliable observed data for each impervious scenario, if observed data is available. QGIS was used to obtain and process data into information required for the selected models. Several model input data such as slope, elevation, and catchment rainfall were estimated through GIS. The models over simulated observed design floods for the urbancatchments. Obtaining reliable observed data (rainfall and runoff), and satellite images with good resolution proved to be a consistent challenge throughout the study and could have contributed to the poor performance of the models. Urban area data dating back to the1990s was extracted from the GAIA method for most of the simulation period and a trend in impervious area expansion linked to urbanisation was detected and analysed against simulated streamflow from the urban catchments.
Assessing the performance of regional flood frequency analysis methods in South Africa.
(2015) Nathanael, Jermaine Jonathan.; Smithers, Jeffrey Colin.; Horan, Mark John Christopher.
In engineering and flood hydrology, the estimation of a design flood refers to procedures whereby the magnitude of a flood is associated with a level of risk at a given site (Pegram and Parak, 2004). The use of a Regional Flood Frequency Analysis (RFFA) approach improves the accuracy and reliability of estimates of design floods. However, no RFFA method is currently widely used in South Africa, despite a number of RFFA studies having been undertaken, that include South Africa. Hence, the performance of the current RFFA approaches needs to be assessed in order to determine the best approaches to use and to determine if a new RFFA approach needs to be developed for use in South Africa. Through a review of the relevant literature it was found that the Meigh et al. (1997) Method, the Mkhandi et al. (2000) Method, the Görgens (2007) Joint Peak-Volume (JPV) Method, which uses a K-Region regionalisation, as well as a Veld zone regionalisation, and the Haile (2011) Method are most suitable for application in a nationwide study. Each regional approach was assessed by comparing their design flood estimates with those estimated from an at-site flood frequency analysis of the observed flood data, using both the General Extreme Value (GEV) and Log Pearson Type 3 (LP3) distributions. However, due to the LP3 distribution producing inconsistent design flood estimates, it was removed from further analysis and only the GEV distribution was assessed. Annual Maximum Flood (AMF) data were obtained from the Department of Water and Sanitation (DWS) for 1458 stations across the entire country. In addition to these datasets, 89 synthesised dam inflow records were obtained from the DWS and incorporated into the study. Due to a thorough data screening process, the final number of stations and dam inflow records analysed was reduced to 407 stations. In order to determine the overall accuracy of the RFFA methods, Relative Errors (RE) (%) were calculated at each station. Box plots and frequency plots were utilised to represent the distribution of relative errors and the degree of bias was measured using a ratio of the estimated and observed design floods. The results of the study show that the Haile Method generally performs better than the other RFFA methods, however it also consistently under-estimates. The Mkhandi Method generally over-estimates. The Meigh Method generally performs the worst, consistently over-estimating. For the JPV Methods, the K-Region regionalisation generally performs better than the Veld zone regionalisation; however, they both consistently over-estimate design floods. The poor overall performance of the RFFA methods are due to a number of reasons. In the case of the Mkhandi et al. (2000) Method, the tests for homogeneity that were developed were too lenient, which may have incorrectly defined regions as being homogeneous. In the case of the Meigh et al. (1997) Method, the regionalisation of homogeneous flood regions were too broad, where only two flood regions have been identified for South Africa. For the Haile (2011) Method, the logarithmic regressions developed for a number of regions were not able to determine index floods for all catchment areas. Therefore, power regressions were developed in this study. In the case of the JPV Methods, the Kovacs K-Regions and Veld zone regions were used, which have not been updated in the past several years. In response to the generally poor performance of the RFFA methods assessed in this study, it has been recommended that a new method be developed for application in design flood practice in South Africa.
Assessing the performance of techniques for disaggregating daily rainfall for design flood estimation in South Africa.
(2020) Ramlall, Ryshan.; Smithers, Jeffrey Colin.
Design Flood Estimation (DFE) and other hydrological modelling methods are used to limit the risk of failure and ensure the safe design of infrastructure and for the planning and management of water resources. The temporal distribution of rainfall has a significant impact on the magnitude and timing of flood peak discharges. Rainfall temporal distributions are therefore an important component of DFE approaches. In order to improve DFE methods which are based on event or continuous simulation rainfall-runoff models, it is generally necessary to use sub-daily time step rainfall hyetographs as input. However, the number of recording raingauges which provide sub-daily timesteps in South Africa is relatively scarce compared to those which provide daily data. Rainfall Temporal Disaggregation (RTD) techniques can be used to produce finer resolution data from coarser resolution data. Several RTD approaches have been applied in South Africa. However, application of RTD approaches locally is relatively limited, both in terms of diversity of approaches and cases of application, compared to those developed and applied internationally. Therefore, a need exists to further assess the performance of locally applied approaches as well update the list of available approaches through inclusion of internationally developed and applied RTD techniques. A pilot study was performed in which selected locally applied and internationally applied approaches were applied to disaggregated daily rainfall data. Some approaches were applied in their original form while others were modified. Temporal distributions of rainfall were represented by dimensionless Huff curves, which served as the basis for comparison of observed and disaggregated rainfall. It was found that for daily rainfall, the SCS3, SCS4 and Knoesen model approaches performed considerably better than the other approaches in the pilot study. The RTD approaches were further assessed using data from 14 additional rainfall stations. For the additional stations, the Knoesen model disaggregated depths provided the most realistic temporal distributions overall, followed by the SCS-SA approach. In additional, an adapted form of the Triangular distribution was found to show potential for disaggregation when a generalised value for the timing of the peak was utilised.
An assessment of scale issues related to the configuration of the ACRU model for design flood estimation
(2010) Chetty, Kershani Tinisha.; Schulze, Roland Edgar.; Smithers, Jeffrey Colin.
There is a frequent need for estimates of design floods by hydrologists and engineers for the design of hydraulic structures. There are various techniques for estimating these design floods which are dependent largely on the availability of data. The two main approaches to design flood estimation are categorised as methods based on the analysis of floods and those based on rainfall-runoff relationships. Amongst the methods based on the analysis of floods, regional flood frequency analysis is seen as a reliable and robust method and is the recommended approach. Design event models are commonly used for design flood estimation in rainfall-runoff based analyses. However, these have several simplifying assumptions which are important in design flood estimation. A continuous simulation approach to design flood estimation has many advantages and overcomes many of the limitations of the design event approach. A major concern with continuous simulation using a hydrological model is the scale at which should take place. According to Martina (2004) the “level” of representation that will preserve the “physical chain” of the hydrological processes, both in terms of scale of representation and level of description of the physical parameters for the modelling process, is a critical question to be addressed. The objectives of this study were to review the literature on different approaches commonly used in South Africa and internationally for design flood estimation and, based on the literature, assess the potential for the use of a continuous simulation approach to design flood estimation. Objectives of both case studies undertaken in this research were to determine the optimum levels of catchment discretisation, optimum levels of soil and land cover information required and, to assess the optimum use of daily rainfall stations for the configuration of the ACRU agrohydrological model when used as a continuous simulation model for design flood estimation. The last objective was to compare design flood estimates from flows simulated by the ACRU model with design flood estimates obtained from observed data. Results obtained for selected quaternary catchments in the Thukela Catchment and Lions River catchment indicated that modelling at the level of hydrological response units (HRU’s), using area weighted soils information and more than one driver rainfall station where possible, produced the most realistic results when comparing observed and simulated streamflows. Design flood estimates from simulated flows compared reasonably well with design flood estimates obtained from observed data only for QC59 and QCU20B.
An assessment of the use of remote sensing to estimate catchment rainfall for use in hydrological modelling and design flood estimation.
(2022) Khakhu, Khodani.; Smithers, Jeffrey Colin.
The accurate estimation of catchment rainfall is crucial, especially in hydrological modelling and flood hydrology which is used for the planning and design of hydrological infrastructures such as dams and bridges. Traditionally, catchment rainfall is estimated by making use of ground-based point rainfall measurements from rain gauges. The literature review conducted in this study supports that there is evidence of a decrease in the number of operational groundbased rainfall stations in South Africa which presents a challenge when estimating catchment rainfall for use in hydrological modelling and design flood estimation. Thus, innovative ways are required to estimate catchment rainfall and to improve the estimation of catchment design rainfall. This study investigated the use of remote sensing as an alternative way to estimate catchment design rainfall. To do this, a pilot study was first used to develop and test the methodology using a quaternary catchment that was selected based on the raingauge density. This was followed by the application of a refined methodology in another quaternary catchment which was used to verify the results that were obtained in the pilot study. After a comprehensive review of the literature, the remote sensing product selected for this study was the CHIRPS rainfall product. The methodology adopted first validated the remotely sensed rainfall data using the observed rainfall data and the estimated remotely sensed rainfall values were bias corrected using the observed rainfall data. The statistics that were used for validating are MAE, MBE, RMSE and D. The method that was used for bias correction was empirical quantile mapping Issues encountered, and as documented in the literature, include the unavailability of long periods of observed quality rainfall data and the limited and uneven spatial distribution of rainfall stations. Catchment rainfalls were estimated using observed rainfall, and this was assumed as the best estimate and was compared to the catchment rainfalls that were estimated using the biascorrected remotely sensed rainfalls. The performance of CHIRPS rainfall was varied among the approaches and the selected catchments. Nevertheless, the results from this study still show the potential of the use of remotely sensed rainfall to estimate catchment design rainfalls. At the daily timescale, satellite-derived and observed rainfall were poorly correlated and variable among locations. However, monthly and annual rainfall totals were in closer agreement with historical observations than the daily values. Despite the varied performance , the result of the study shows that CHIRPS rainfall product can be used to estimate catchment rainfall for hydrological modelling and flood frequency analysis. By acknowledging that the performance of remote sensing products is robust, it is of importance to note that the performance of the results presented is strictly for the catchments and stations selected for this project as well as the methods selected to validate and correct the bias in remotely sensed rainfall. The recommendations from the study are that a similar study is conducted in another region where there is even distribution of stations and a long record of quality observed rainfall beyond the year 2000 and consideration of the methods to identify outliers before making any meaningful estimations such as catchment rainfall from rainfall data.
Detecting and assessing the impacts of outlier events and data availability on design rainfall and flood estimation in South Africa.
(2021) Singh, Keanu Reeve.; Smithers, Jeffrey Colin.; Johnson, Katelyn Ann.
Accurate Design Rainfall Estimation (DRE) and Design Flood Estimation (DFE) require long periods of quality-controlled data for the planning, design, operation, and improved flood risk assessment of hydraulic structures. However, observed hydrological data frequently include outlier events and there is a decline of hydrological monitoring in South Africa which may impact DRE and DFE. It is therefore necessary to assess the impact of outlier events and reduced data availability on DRE and DFE. The aims of this study were to: (a) assess the impact of outlier events on DRE and DFE in South Africa, (b) assess the performance of outlier detection methods under South African conditions, and (c) assess the impact of reduced data availability on DRE and DFE in South Africa. The impact of synthetic Low Outlier (LO) and High Outlier (HO) events on DRE and DFE from observed and synthetically generated data series were assessed. The performance of the BoxPlot, Modified Z-Score (MSZ) and Multiple Grubbs-Beck Test (MGBT) outlier detection methods were assessed. Record length and network density were reduced to assess the impact of reduced data availability on DRE and DFE. Results from the analysis of observed data show that design rainfall is impacted by up to 22% and design floods by up to 45% in the presence of LOs. Design rainfall is impacted by up to 16% and design floods by up to 46% in the presence of HOs. For synthetically generated data series, design rainfall and floods are impacted by up to 2% and 1% respectively in the presence of LOs and by up to 13% in the presence of HOs. At best, LOs in observed rainfall and streamflow data are under-detected by up to 6% and 30% respectively by the MGBT method, whereas HOs are over-detected up to 50% and 150% respectively by the MZS method. Design rainfall and flood events are impacted by up to 4% and 24% respectively by reduced record lengths, and by up to 4.5% and 60% respectively from a reduced gauged network. This study indicates that outlier detection be adopted as regular practice in South Africa and that additional national resources must be directed towards maintaining and improving the hydrological monitoring networks in South Africa.
Development and application of decision support systems for improved planning and operation of large dams along the White Nile.
(2015) Zaake, Benon Tamukedde.; Smithers, Jeffrey Colin.
In this study the regulation of Lakes Victoria, Kyoga and Albert in East Africa are investigated with the objective of maximising hydropower production subject to system constraints for existing and future planned dams along the Upper White Nile in Uganda. A Decision Support System (DSS) has been assembled and applied to search for efficient lake-reservoir operating rules for this basin. Elements of the DSS include power plant functions, a simulation model of the Upper Nile Equatorial Lake Basin, the Stochastic Analysis Modelling and Simulation (SAMS) computer software package for analysing hydrologic time series and the Colorado State University Dynamic Programming (CSUDP) model for solution of the optimisation problem. A concurrent record of observed lake levels and outflows for the three lakes during the reference period 1899 – 2008 has been constructed from various long term monitoring stations and utilised to derive net basin supply or net inflow time series at a monthly and annual time scale. Statistical tests confirmed the non-stationarity of the annual lake net basin supply time series. A justification to model the stochastic process of the monthly inflows as a Markov process was also reached. A Univariate Shifting Mean model was fitted to the annual historical data in tandem with a model for temporal disaggregation of annual to monthly net basin supplies for the purposes of generating synthetic flow series. The model performed well in terms of preserving the statistical characteristics of the historical reference set for each lake. The synthetic time series are considered to be a useful reference data set for future research in generating reservoir operating rules. Two Dynamic Programming (DP) models that may be used to generate reservoir operating rules were investigated. The desired scope of optimization was however curtailed by the well-known dimensionality problem of DP. Application of the deterministic method of Incremental Dynamic Programming (IDP) to the optimisation problem could only be carried out on a monthly time step and for single years separately. Annual time step optimization could only be carried out for the historic net inflows. The 1000 stochastically generated time series of net basin supplies could not be utilized within the implicit framework of deriving operating rules due to impractical computational requirements. The IDP however, yielded a realistic set of optimal operating policies at an annual time scale for the historical reference period (1898 – 2008). The beginning of year lake levels and annual release magnitudes obtained were compared against similar data for natural unregulated lake conditions. It is concluded that, in general, lake regulation would yield desirable benefits in terms of hydropower generation but would lead to marked deviation from natural lake levels and more variable outflows. The Stochastic Dynamic Programing (SDP) model was only applied to Lake Victoria in single reservoir optimization scheme due to limitations imposed by the large dimensionality of the problem and difficulty of simultaneously incorporating multiple lake reservoir transition probability matrices in the model. Application of the model for Lake Victoria showed that, it was feasible to define final storage levels for discretized initial storage and previous period inflow class combinations. The results from the study indicate that realistic heuristic operation rules can be inferred from the results of applying the IDP models and SDP algorithm.
The development and assessment of a direct energy calculator for use in sugarcane production.
(2014) Boote, Darran N.; Smithers, Jeffrey Colin.; Lyne, Peter William Liversedge.; Van Antwerpen, Rianto.
The rising cost of energy coupled with an increasing awareness of Greenhouse Gas (GHG) emissions has led to a concerted effort to reduce fossil fuel Energy Use (EU) in all sectors. Sugarcane production in South Africa is dependent on fossil fuel to provide a source of energy for production. To remain commercially and environmentally sustainable, measures need to be taken to reduce EU and increase EU efficiencies of on-farm operations. The first step toward realising this is to identify and quantify energy inputs. Following on from this, total GHG emissions, also known as carbon footprint, can be estimated. The primary objective of this research is to develop an energy calculator to estimate EU in sugarcane production in South Africa. The results generated by the calculator highlight areas of high energy intensity and low energy efficiencies at three different levels of detail. Based on these results, changes in management practices and technological improvements can be made to reduce EU and carbon footprint. Case studies were used to test the functionality of the calculator. Results from the case studies show that, in irrigated sugarcane production, the harvest and transport process together with irrigation account for a majority of the total on-farm EU. For one of the case studies, an estimated 20 % saving in the total on-farm EU was identified and can be achieved if appropriate technology is adopted in irrigation practices. Less significant energy savings were realised when in-field tractor operations were optimised for best tractor-implement matching. It is envisaged that the energy calculator will help farmers minimise on-farm EU and subsequently reduce input costs and carbon footprint. It will also provide a valuable tool for researchers to benchmark and profile EU in sugarcane production in South Africa. Research focussed on the sustainable production of sugar, from the agricultural to milling phase is of high priority at present. The quantification of on-farm EU in sugarcane production will form a critical component of such research.
The development and assessment of a prototype water accounting system for South Africa using the ACRU2000 and MIKE BASIN models..
(2010) Kime, Dylan B.; Smithers, Jeffrey Colin.
South African water management areas could find themselves without enough water for its users due to new methods of performing water allocation as stipulated in the National Water Act of 1998. A water accounting system would address the need for accurate metering, monitoring and auditing of South Africa’s water resources to ensure that users are complying with their allocations. Such a system should be able to provide information such as comparisons between the simulated and observed flow of water at a point, comparisons between the amount of water allocated to a user and the actual water used by that user, and the source and destination of water at a point. This document contains a literature review, an explanation of the methods used to develop a prototype water accounting system and a discussion of the results from testing the system. A literature review was undertaken which covered topics in water resources planning, water resources operations, local legislation for water allocation and new technologies which could be applied to aid the management of water resources in South Africa. The results from the literature review indicated real time water accounting systems can give effect to water allocation rules. The water accounting system is comprised of two simulation models and a database. The models used for the study were the ACRU2000 model and the MIKE BASIN model. These models require data as well as a means to automate the transfer of data between the models and thus a database was developed. The database was developed in Microsoft Access and, in addition to the construction of a number of tables required to house the data, a database dashboard was made to control the functions of the database. An assessment of the ACRU2000 and MIKE BASIN models was performed in order to determine if they are suitable for use as water accounting tools. ACRU2000 was used for its process based, daily rainfall-runoff modelling capabilities. Due to the process based modelling capabilities of ACRU2000, forecasts of rainfall can be used as input to the simulations. Hot starting is the storing of internal model state variables at a particular time and the use of these variables in a different simulation to start the model up again. It was expected that, due to long simulation run times for ACRU2000, it would be beneficial to enable ACRU2000 to be hot started and an attempt to hot start ACRU2000 is presented. This would have allowed for significantly decreased simulation run times as the model can be warmed up for two years and thereafter hot started to run only for one day at a time. An assessment of the MIKE BASIN network allocation model to be used as a water accounting system was performed by attempting to meet the project objectives through building a fictional water supply network. The network is composed of a small catchment containing six runoff generating regions, a reservoir and ten water users. Three network allocation scenarios were constructed in order to fully test the rule sets and allocation capabilities currently available in the MIKE BASIN model. The study has shown that the tools and models used are capable of forming a rudimentary water accounting system. This is encouraging as it shows that there is the potential to improve the water resources management in South Africa using tools that already exist.
Development and assessment of an ensemble joint probability event based approach for design flood estimation in South Africa.
(2019) Dlamini, Nkosinathi Sethabile.; Smithers, Jeffrey Colin.
It has been reported that global climate change has impacted on the frequency as well as severity of flood events. Reliable flood estimates are required for managing and designing hydraulic structures, which is essential under extreme weather regimes in the future. Design flood estimation methods in South Africa are based on statistical analysis of past streamflow data, and rainfall based methods. Rainfall-based methods often have preference over streamflow-based methods for design flood estimation due to longer records of rainfall data that also have a greater spatial and temporal coverage than streamflow records. A key assumption in rainfall based methods for design flood estimation is the assumption regarding the exceedance probability of the estimated flood. It is generally assumed that the return period of the estimated flood will be the same return period as the input rainfall. This equality of rainfall and flood return periods is generally not true given the use of model parameters representing average conditions and the impact of antecedent moisture conditions on hydrological response. Hence, a Joint Probability Approach (JPA) where the key input model parameters, and not only the input design rainfall, are treated probabilistically will overcome the limitations associated with rainfall based design flood estimation. The underlying approach to the JPA is that instead of the use of a single combination of input variables to determine the flood characteristics, the method uses multiple combinations of flood producing parameters to determine the flood characteristics. In this study, a JPA was applied using the SCS-SA model, and the modelling framework used to determine the derived flood frequency curve is based on three principal elements. These include: (i) defining the key model inputs with their respective probability distributions and correlations, (ii) a stochastic model to synthesise sequences of the selected variables, and (iii) selecting an appropriate deterministic hydrological model to simulate the flood generation process, and use of the simulated outputs to derive the flood distribution. To evaluate the performance of the model, the results were compared to observed streamflow data. A statistical analysis was conducted in conjunction with graphs to verify the performance of the model. The Nash-Sutcliff Efficiency (NSE), absolute relative difference and Mean Absolute Relative Error (MARE) were used to evaluate the performance of the model. The results produced from applying the Ensemble SCS-SA model with rainfall that was fitted to the probability distribution of the 1 day design rainfall and sampling from the 90 % prediction intervals for each return period indicates that the model was performing relatively poorly in terms of estimating both the observed design runoff volume and design peak discharge for all the selected test catchments. The incorporation of the correlation between the rainfall depth and rainfall duration using a conditional probability distribution and in conjunction with the probability distributions of the other key input variables in the Ensemble SCS-SA model, resulted in significantly improved estimated runoff volume and peak discharges for all the catchments used. The Ensemble SCS-SA model has also shown potential and flexibility to deal with uncertainty by accounting for the distributed nature of the input variables and taking on values across the full range of their distribution in the modelling process, thus avoiding the potential of bias that can occur when adopting a single set of pre-determined input values. This study has shown the potential and flexibility of the Ensemble SCS-SA model to deal with uncertainty, providing opportunity for the expanded application of the model.
Development and assessment of an improved continuous simulation modelling system for design flood estimation in South Africa using the ACRU model.
(2019) Rowe, Thomas James.; Smithers, Jeffrey Colin.; Clark, David John.
An estimate of the risk associated with flood events is required to adequately design hydraulic structures and limit negative socio-economic impacts as a result of floods. The methods used to estimate design floods in South Africa are outdated and are in need of revision. A National Flood Studies Programme (NFSP) has recently been initiated by Smithers et al. (2016) to overhaul Design Flood Estimation (DFE) procedures in South Africa. One of the recommendations of the NFSP is development and assessment of a Continuous Simulation Modelling (CSM) approach to DFE. Consequently, the aim of this study is to further develop and assess the performance of an improved comprehensive CSM system, to consistently and reliably estimate design flood discharges in small catchments (0 - 100 km2) in South Africa using the ACRU model. In the development of the approach a strong emphasis has been placed on ease of use from a practitioner’s point of view. The aim is achieved through several specific objectives as summarised below. The first objective was to review CSM approaches applied locally and internationally for DFE, in order to identify research gaps and guide the development of an improved national CSM system for DFE in South Africa. The review culminates with a list of recommendations and steps required to develop and adopt a CSM approach for DFE in practice. The first critical step identified and required was the development of a comprehensive CSM system using the ACRU model (Schulze, 1995). This included: the structure of the system and how to implement the system, an enhanced land cover and soils classification to apply with the system and default input information and databases to use with the system. The second objective addresses the recommendations made from the literature review, where a comprehensive CSM system for DFE using the ACRU model is developed and described in detail. Based on similarities identified between the ACRU (Schulze, 1995) and SCS-SA models (Schmidt and Schulze, 1987a), as well as the fact that the SCS-SA model is relatively simple and widely applied in practice, the CSM system was adapted to be consistent with the land cover classification used in the SCS-SA model. This included the incorporation of a methodology and rules, developed by Rowe (2015), to represent land management practices and hydrological conditions within the ACRU model. The development of this comprehensive CSM system with default national scale inputs and land cover classifications contributes to new knowledge on how to package a CSM system for DFE in South Africa. The third objective focuses on the assessment and verification of the CSM system developed, using observed data. Through the verifications and assessments performed an inconsistency between daily simulated stormflow volumes and the volume of stormflow used in the daily stormflow peak discharge equation was identified. Therefore, a revision, which is more conceptually correct than the current assumption that all stormflow generated from an event contributes to the peak discharge on the day, was applied to the fraction of the simulated daily stormflow used in the peak discharge equation. This corrected the inconsistency and significantly improved the results, thereby providing an improved methodology to more accurately estimate peak discharges in the ACRU model than had hitherto been the case. Despite the improvement in the results, a general over-simulation of peak discharges was still evident. Consequently, further investigation of the ACRU stormflow peak discharge computations was performed in order to identify which approach provides the most satisfactory results (Objective 4). This included a performance assessment of both the SCS single Unit Hydrograph (UH) approach and the incremental UH approach. The performance of each approach was assessed using both estimated parameters and parameters derived from observed data. These parameters include stormflow volumes, catchment lag times, and the distribution of daily rainfall, where applicable, to each approach. Comparison of the results from the two approaches indicated that more accurate results are obtained when applying the incremental UH approach, when using both estimated or observed parameter inputs. In terms of the incremental UH approach, it was identified that the approach is more sensitive to the use of synthetic daily rainfall distributions compared to estimated lag times. Based on the results obtained new knowledge and additional research gaps related to: (i) improved estimation of the distribution of daily rainfall within the ACRU model, (ii) links between the distribution of daily rainfall and catchment lag time, and (iii) the need to further verify and possibly recalibrate CNs for South Africa were identified. The fifth objective addressed is an assessment of the impact of model configuration on the performance of the ACRU CSM system developed, in order to propose a final CSM system for DFE in South Africa. Results when using site-specific land cover and soils information are compared to those obtained when different sources of input information are used, such as the national land cover and soils maps developed for the entire country. The results when using these default national datasets were not particularly good, however recommendations are made to improve on the results. In addition, the most appropriate current databases to use with the CSM system are defined, providing users with the most appropriate default information currently available to use in the absence of site-specific information. The last objective addressed was a comparison of the performance of the final ACRU CSM system proposed in this study to that of the widely applied SCS-SA model and associated approaches, when using the same input information. Ultimately, the final ACRU CSM system proposed provides results that are superior to those from the SCS-SA model and associated approaches. In addition, several advantages of the ACRU CSM system over the traditional SCS-SA approaches were identified. Recommendations were, however, made to improve on the CSM system developed in this study and to use the results to update the SCS-SA model. New knowledge on the performance of the SCS-SA model and its associated approaches compared to that of the comprehensive CSM system developed for South Africa is therefore provided in this study.
Development and assessment of an integrated largescale hydrological modelling tool for water resources management in the Cauvery Catchment, India.
(2022) Horan, Robyn.; Smithers, Jeffrey Colin.; Kjeldsen, Thomas Rodding.; Clark, David John.; Toucher, Michele Lynn.
Economic development and population growth in southern India have resulted in rapid changes to land use, land management and water demand, significantly impacting and degrading water resources. The significant anthropogenic influences across the catchment have contributed to changes in hydrological functioning. Focussing on the highly contentious inter-state Cauvery River Catchment, this study aims to address the key scientific challenges faced within this catchment. The study was designed to develop an integrated large-scale hydrological model to improve water resource assessments in a highly heterogeneous and data-scarce region whilst considering the primary water resource challenges facing the Cauvery Catchment. The Upper Cauvery region, located in the Western Ghats, acts as the water tower of the catchment. The rainfall in the region is monsoonal, the topography is complex, and the rain gauge network is sparse, resulting in the estimation of rainfall being particularly challenging. The scarce rainfall data available in the Western Ghats region is hindering the understanding of the regional weather system, and the accepted rainfall dataset for India, Indian Meteorological Department rainfall grids, are known to have inaccurate estimations within the Western Ghats. The current knowledge of the meteorology and hydrology of the Upper Cauvery is limited. Additionally, the anthropogenic impact on local hydrological processes, such as streamflow, groundwater recharge and evapotranspiration, is poorly constrained. The current understanding of how these diverse local changes cumulatively impact water availability at the broader catchment scale is minimal. Small-scale rural water management and urban heterogeneity may strongly affect water resource availability across southern India. However, how such fine-scale factors propagate to the river catchment is largely unclear. The Global Water Availability Assessment (GWAVA) model was applied initially to the Upper Cauvery region to determine the suitability and compare model results from other modelling tools applied in the region. Two new versions of the GWAVA model were then developed. The first aimed to include small-scale runoff harvesting interventions (SSRHIs) into the model and quantify their impact on catchment water resources to address a renewed scientific interest in assessing their effectiveness in improving local water resources and the effects at a catchment scale. The second aimed to enhance the representation of groundwater and large operational dams whilst maintaining the model’s applicability to regions with low-data availability. The Indian Meteorological Department (IMD) gridded rainfall was compared to available gauges and selected remotely sensed datasets within the Upper Cauvery region. GWAVA will be utilised to assess the applicability of the remotely sensed data for a catchment rainfall estimation. GWAVA was determined to be a suitable tool to represent the Cauvery Catchment; however, the importance of an accurate spatial representation of rainfall for input into hydrological models and that comprehensive dam functionality is paramount to obtaining good results in this region was highlighted. Furthermore, the average GWAVA, VIC and SWAT ensemble provided a better predictive ability in catchments with dams than the individual models. The average ensemble offset uncertainty in input data and poor dam operation functionality within individual models. The inclusion of SSRHIs demonstrated that farm bunds appear to have a negligible effect on the average annual simulated streamflow. In contrast, tanks and check dams have a more significant and time-varying impact. The open water surface of the SSRHIs contributed to an increase in evaporation losses across the sub-catchment. The change in simulated groundwater storage with the inclusion of SSRHIs was not as significant as sub-catchmentscale literature, and field studies suggest. Including groundwater processes into GWAVA improved streamflow simulation in the headwater sub-catchments and the representation of the baseflow component such that low-flow model skill increased approximately 33-67% in the Cauvery and 66-100% in the Narmada. The existing dam routine was extended to account for large, regulated dams with two calibratable parameters. The routine improved streamflow simulation in sub-catchments downstream of major dams, where the streamflow was largely reflective of dam releases. The model performance was improved between 15 and 30% in the Cauvery and 7-30% in the Narmada when the regulated dams were considered. The model provides a more robust representation of the annual outflow volume from major dams, reducing the average bias from -17% to -1% in the Cauvery and from 14% to 3% in the Narmada. The daily dam releases were significantly improved in the Cauvery, approximately 26-164%. The improvement of the groundwater and dam routines in GWAVA proved successful in improving the overall model performance, the low-flow model skill and bias, and the inclusions allowed for improved traceability of simulated water balance components. It was found that the IMD rainfall within the high-altitude regions of the Western Ghats is underestimated, resulting in the under-simulation of streamflow in the Upper Cauvery. CHIRPS 0.25- and 0.05- degree, MSWEP and PERSIANN remotely sensed rainfall datasets were applied within this region. None of the individual rainfall datasets provided a more accurate representation of the rainfall than the commonly utilised IMD grids. However, using an ensemble of remotely sensed rainfall datasets, primarily the average ensemble, improved the accuracy of rainfall estimation in the catchment. The ‘off-the-shelf’ remotely sensed rainfall products provided a high variation in performance against the in-situ rain gauge data. The IMD grids provided the most accurate representation of rainfall compared to the individual remotely sensed rainfall datasets, despite underestimating the rainfall depths at high altitudes. In the case of the Upper Cauvery, the average ensemble provided a more accurate representation of the rainfall. An integrated large-scale hydrological model was developed to improve water resources assessments in a highly heterogeneous and data-scarce region whilst considering the major water resource challenges facing the Cauvery Catchment. The effects of runoff harvesting interventions, accounting for hard-rock aquifer groundwater processes and the impact of major dams were represented. The inclusion of these features improved the model performance throughout the Cauvery Catchment.
Development and assessment of regionalised approaches to design flood estimation in South Africa.
(2020) Calitz, Johannes Pieter.; Smithers, Jeffrey Colin.; Kjeldsen, Thomas Rodding.; Gericke, Ockert Jacobus.
Engineers rely on design hydrological information for the design of hydraulic structures, such as dams, bridges, and drainage culverts. No single Design Flood Estimation (DFE) method has been identified internationally as the most appropriate method to use and, in many texts and manuals, the use of a combination of these are recommended. In South Africa, some of the currently recommended and widely used methods were developed outside of South Africa with little or no local adaptation or assessment, and most of the recommended methods were developed prior to 1990. The development of new and updated methods can therefore benefit from the use of much longer observed data sets and new and innovative approaches applied internationally. Four Regional Flood Frequency Analysis (RFFA) approaches widely adopted internationally are direct quantile estimation methods, Probabilistic Rational Method (PRM), Index Flood (IF), and Regional Growth Curve (RGC) methods. The Standard Design Flood (SDF) method is a locally developed PRM. However, the method has been recommended for review in a number of studies, and the IF has been shown to have potential for implementation at a national scale in South Africa. The aim of this study was to develop and assess RFFA approaches for the estimation of design flood quantiles within South Africa utilising the currently available data. This process required the compilation of a hydrological descriptors database, including quality controlled gauged flow data. This data was then utilised to identify a suitable probability distribution for FFA in South Africa, which can be applied at a regional scale through the identification of homogeneous flood producing regions and regional flood models. DFE methods require a range of catchment descriptors to be determined for use in models. Considering the literature reviewed and the available datasets, 17 catchment descriptors were selected for inclusion in the study. The descriptors range from geographic and catchment descriptors to design rainfall quantiles. After data screening, a total of 383 stations were utilised, in the study. The available record lengths and number of gauges were compared to prominent studies undertaken previously and was found to be comparative to the data availability in Australia and the United Kingdom. Linear moments (LM) were adopted for the estimation of the distribution parameters. Five distributions were selected for evaluation based on local recommendations as well as recent international developments: (i) General Extreme Value (GEV), (ii) Generalised Pareto (GPA), (iii) 3-parameter Kappa (KAP3), (iv) Log Pearson Type III (LP3) and (v) Pearson Type III (PE3). The evaluation process relied on an iterative elimination approach, reviewing graphical fits to theoretical distributions, Goodness-of-fit (GoF) criteria, model fit criteria and model uncertainty to identify the most suitable distribution. The graphical fit favoured the GPA, KAP3 and LP3 distributions equally, with the GoF methods ranking LP3 as the most suitable method. Conversely, the GPA was ranked highest for the model fit criterion and displayed the least model uncertainty and is thus recommended as the most suitable distribution for general FFA in South Africa. Two regionalisation approaches were considered to undertake the formation of the pooling groups, i.e. Clustering, and Region of Influence (RoI). For each regionalisation approach the hydrological descriptors were grouped into parameter sets, that constituted all potential descriptor combinations, which were tested for homogeneity as a selection criterion. Using the RoI approach, a maximum of 51% of the regions identified were relatively homogeneous. The super region approach was also applied to identify five dominant regions within which the RoI was applied in an attempt to refine the RoI approach. Using the combination of super regions and RoI provided little additional benefit, increasing the percentage of relatively homogeneous regions identified to only 52.6%. Conversely, the Clustering approach was able to identify 42 relatively homogeneous clusters in South Africa. To assess the suitability of Quantile Regression Technique (QRT) and Parameter Regression Technique (PRT) models in South Africa, four models were developed: (i) a QRT model, (ii) IF with equal station weighting (IF1), (iii) IF with station weighting applied (IF2) and (iv) PRM. Regression models were developed at two scales to estimate the required Scaling Factors, i.e. national and regional, with regional models performing best based on the Nash- Sutcliffe model Efficiency (NSE) coefficient. Six key performance indicators were utilised to assess the quantile estimation of the developed models: (i) NSE, (ii) Relative Error (RE), (iii) Root Mean Square Error (RMSE), (iv) Relative RMSE (RMSEr), (v) BIAS, and (iii) BIASr. The models that performed best in the RE assessment were the IF1 for both regionalisation schemes and the IF2 and PRM models using the RoI. When comparing the BIAS and RMSE of the four best performing clustering and RoI based models, the IF1 and QRT using Clustering models are the dominant models when considering both the RMSEr and the BIASr, the models improved on the results of the remaining models by up to a factor of two. The IF1 and QRT using Clustering models are therefore the best performing models on a national scale. The IF1 however has the added advantage of being able to estimate the entire growth curve as to the predefined QRT models. The IF1 is therefore the recommended model at a national scale, however cognisance needs to be taken when applying the model on the eastern coast due to poor BIASr performance. The new knowledge generated by the study can be divided into data, in the form of potentially the largest database of design flood specific descriptors concentrating on South Africa, and theoretical applications thereof. The theoretical knowledge generated ranges from the investigation into the most suitable frequency distribution to use for FFA in South Africa, to the application of multi-variate regionalisation approaches, which have not been applied in South Africa before. However, one of the key contributions was the development and performance assessment of four DFE models at multiple scales for South Africa for the estimation of peak design flood values.
Development and assessment of rules to parameterise the ACRU model for design flood estimation.
(2015) Rowe, Thomas James.; Smithers, Jeffrey Colin.; Schulze, Roland Edgar.; Horan, Mark John Christopher.
Design Flood Estimation (DFE) is essential in the planning and design of hydraulic structures. Recent flooding in the country has highlighted the need to review the techniques used to estimate design floods in South Africa, where old and outdated methods are widely applied. In this study the potential of a Continuous Simulation Modelling (CSM) approach to DFE in South Africa is highlighted, identifying the benefits of a CSM approach over event based approaches. The daily time-step ACRU agrohydrological model has provided reasonable results for DFE in several pilot studies. A review on hydrological modelling and the links and similarities between the SCS-SA and ACRU models, however, highlighted that in terms of land cover information, the land cover classification used in the SCS-SA model accounts for different land management practices and hydrological conditions, which are not accounted for in the current versions of the ACRU land cover classification. Since the CNs used in the original SCS model were derived from observations, and the SCS-SA model is an accepted method of DFE in small catchments in South Africa (Schmidt and Schulze, 1987a; Schulze et al., 2004; SANRAL, 2013), it was assumed in this study that the design volumes simulated by the SCS-SA model are reasonable, and that the relative changes in design volumes simulated by the SCS-SA model as a consequence of changes in land management practice or condition are also reasonable. Based on these assumptions, the general approach to the study was to investigate how design volumes simulated by the SCS-SA model for various land management practices or conditions could be simulated by the ACRU model, and to derive classes in the ACRU hierarchical classification for land management practice and hydrological condition. Consequently, design runoff volumes and changes in design runoff volumes, for different management practices and hydrological conditions, as simulated by the SCS-SA model, were used as a substitute for observed data, i.e. as a reference, to achieve similar design runoff volumes and changes in design volumes in the ACRU model. This was achieved by adjusting relevant variables in the ACRU model to represent the change in management practice or hydrological condition, as represented in the SCS-SA model. After three initial attempts failed to produce comparable simulation results between the SCS-SA and ACRU models a sensitivity analysis of ACRU variables was conducted in order to identify which ACRU variables would represent SCS-SA Curve Numbers (CNs) best for selected land cover classes. The sensitivity analysis identified two ACRU variables best suited to achieve this task, namely QFRESP and SMDDEP. Calibration of QFRESP and SMDDEP values against CN values for selected land cover classes was performed. A strong relationship between these ACRU variables and CN values for selected land cover classes was achieved and consequently specific rules and equations were developed to represent SCS-SA land cover classes in ACRU. Recommendations, however, are suggested to further validate and substantiate the approach and developed rules and equations.
The development and assessment of techniques for daily rainfall disaggregation in South Africa.
(2005) Knoesen, Darryn Marc.; Smithers, Jeffrey Colin.
The temporal distribution of rainfall , viz. the distribution of rainfall intensity during a storm, is an important factor affecting the timing and magnitude of peak flow from a catchment and hence the flood-generating potential of rainfall events. It is also one of the primary inputs into hydrological models used for hydraulic design purposes. The use of short duration rainfall data inherently accounts for the temporal distribution of rainfall, however, there is a relative paucity of short duration data when compared to the more abundantly available daily data. One method of overcoming this is to disaggregate courser-scale data to a finer resolution, e.g. daily to hourly. A daily to hourly rainfall disaggregation model developed by Boughton (2000b) in Australia has been modified and applied in South Africa. The primary part of the model is the . distribution of R, which is the fraction of the daily total that occurs in the hour of maximum rainfall. A random number is used to sample from the distribution of R at the site of interest. The sample value of R determines the other 23 values, which then undergo a clustering procedure. This clustered sequence is then arranged into 1 of 24 possible temporal arrangements, depending when the hour the maximum rainfall occurs. The structure of the model allows for the production of 480 different temporal distributions with variation between uniform and non-uniform rainfall. The model was then regionalised to allow for application at sites where daily rainfall data, but no short duration data, were available. The model was evaluated at 15 different locations in differing climatic regions in South Africa. At each location, observed hourly rainfall data were aggregated to yield 24-hour values and these were then disaggregated using the methodology. Results show that the model is able to retain the daily total and most of the characteristics of the hourly rainfall at the site, for when both at-site and regional information are used. The model, however, is less capable of simulating statistics related to the sequencing of hourly rainfalls, e.g. autocorrelations. The model also tends to over-estimate design rainfalls, particularly for the shorter durations .
The development and evaluation of a radio frequency identification based cattle handling system.
(2013) Mutenje, Tendai Justin.; Smithers, Jeffrey Colin.; Simalenga, T. E.
Manual cattle handling systems are widely used in South Africa. A literature review and consultations were conducted with both producers and equipment manufactures, to assess the advantages and disadvantages of various cattle handling systems with the objective of developing a more efficient system that incorporates automation, electronics and Radio Frequency Identification (RFID) technology. In this study an automated, selective sorting (RFID) based cattle handling system was developed and assessed as an alternative to the widely adopted conventional manual management system practiced in South Africa. The system is still under research and not yet available on the market. This document describes the research and development process undertaken which included planning, literature review, consultation, design, fabrication, evaluation and discussions. The RFID based system developed consists of manual, semi- and fully automated components in the form of a neck-body clamp with through access, flow control double split gates and a weigh-identification-sort system. For the ease of comparison the system was developed with a manual by-pass as a control to compare the automated and manual systems in terms of establishment cost, handling duration including identification, weighing and sorting, and operator and animal stress levels which impact on business profitability and system efficiency. Both the manual by-pass and automated RFID-based systems were evaluated. The automated system resulted in reduced handling duration, operational costs and handling stress on both operator and the animal whilst enabling selective automated sorting. The infrastructure was designed to have a capacity to handle 500 animals per day with 5 handlers and a capital investment of R200 000 was required with an operational cost of R25 000 per month. After incorporating RFID, electronics and automation of the system it was established that, on average, cattle handling duration was reduced by 63%, incorrect sorting was reduced by 5.5%, man hours were reduced by 70% with 23% and 14% less fatigue and stress levels to the handler and the animals respectively, whilst achieving efficient selective sorting. A cost benefit analysis was undertaken for both systems with the aim of assessing and determining the most profitable system. An assumption was made that the cash flow pattern remains uniform for both systems over the entire evaluation period. This revealed that the introduction of RFID based technology as an alternative to a manual based system results in an increase in business profitability by 20% and shorten the payback period by 5 years. Although there is still need to further investigate the performance parameters under different environments, it can be concluded that the introduction of RFID, electronics and automation improves the overall system technical efficiency by 32% whilst enabling efficient selective handling.
The development and evaluation of an operating rule framework for the ACRU agrohydrological modelling system.
(2001) Butler, Andrew John Edward.; Smithers, Jeffrey Colin.; Jewitt, Graham Paul Wyndham.
Dams hold numerous benefits for society through their ability to store water on a long-term basis. However, it is well-known that there is a detrimental effect of dams on the rivers that they impound, and this has been taken into account by the South African National Water Act (1998). The Act specifies a two component Reserve to provide a basic water supply to humans and to provide protection to downstream rivers and their associated ecosystems. From an ecological perspective, emphasis is now placed on ensuring that flow in rivers is maintained in a state that closely mimics the natural flow regime in order to sustain the water resource and its associated aquatic ecosystems. The resulting challenge for water resources modelling is to develop operating rule frameworks that can account for water supply to multiple users, including the "environment" which represents downstream aquatic ecosystems. These frameworks need to consider both water stored in dams, as well as water in the river which has been allocated to different water uscrs. Such an operating rule framework has been implemented ID the daily time-step ACRU agrohydrological model in order to: (a) satisfy the requirements of water users in general, (b) (c) include the environment as a user of water, and thus attempt to satisfy the water requirements of rivers and their associated ecosystems by making artificial releases from dams using both a simple and a complicated approach for determining the environmental requirements. The framework identifies four types of water users, each of which are capable of requesting water from a water source. These users are: a domestic user, representing the basic human needs component of the Reserve, an environmental user, representing the ecological component of the Reserve, an industrial user and an irrigator. The environmental user can generate water requests using either a simple or a complex environmental request method. The simple approach has proved to be oversimplified while the complex approach is capable of producing a flow regime downstream of a dam that closely mimics the natural flow regime. Two operating rules are employed to supply water to the four users, a generic dam operating rule, which considers water requested from a dam, and a channel operating rule, which considers water requested from a river. The two operating rules determine the amounts of water that each user can receive through the use of a curtailment structure, where abstractions made by users are limited, based on the storage level in the dam. Extensive validation of the framework has taken place and a case study was undertaken on the Pongola-Bivane river system which includes the Paris Dam in order to run various real-life scenarios. The results obtained show not only that the operating rule framework is functioning correctly, but that the use of a curtailment structure holds advantages for increasing assurance levels of the water users. There is also evidence to suggest that future possibilities exist for practical application of the operating rule framework to "everyday" dam operations.
Development and evaluation of techniques for estimating short duration design rainfall in South Africa.
(1998) Smithers, Jeffrey Colin.; Schulze, Roland Edgar.; Pegram, Geoffrey Guy Sinclair.
The objective of the study was to update and improve the reliability and accuracy of short duration (s 24 h) design rainfall values for South Africa. These were to be based on digitised rainfall data whereas previous studies conducted on a national scale in South Africa were based on data that were manually extracted from autographic charts. With the longer rainfall records currently available compared to the studies conducted in the early 1980s, it was expected that by utilising the longer, digitised rainfall data in conjunction with regional approaches, which have not previously been applied in South Africa, that more reliable short duration design rainfall values could Ix: estimated. A short duration rainfall database was established for South Africa with the majority of the data contributed by the South African Weather Bureau (SAWB). Numerous errors such as negative and zero time steps were identified in the SAWB digitised rainfall data. Automated procedures were developed to identify the probable cause of the errors and appropriate adjustments to the data were made. In cases where the cause of the error could be established, the data were adjusted to introduce randomly either the minimum, average or maximum intensity into the data as a result of the adjustment. The effect of the adjustments was found to have no significant effect on the extracted Annual Maximum Series (AMS). However, the effect of excluding erroneous points or events with erroneous points resulted in significantly different AMS. The low reliability of much of the digitised SAW B rainfall data was evident by numerous and large differences between daily rainfall totals recorded by standard, non-recording raingauges, measured at 08:00 every day, and the total rainfall depth for the equivalent period extracted from the digitised data. Hence alternative techniques of estimating short duration rainfall values were developed, with the focus on regional approaches and techniques that could be derived from daily rainfall totals measured by standard raingauges. Three approaches to estimating design storms from the unreliable short duration rainfall database were developed and evaluated. The first approach used a regional frequency analysis, the second investigated scaling relationships of the moments of the extreme events and the third approach used a stochastic intra-daily model to generate synthetic rainfall series. In the regional frequency analyses, 15 relatively homogeneous rainfall clusters were identified in South Africa and a regional index storm based approach using L-moments was applied. Homogeneous clusters were identified using site characteristics and tested using at-site data. The mean of the AMS was used as the index value and in 13 of the 15 relatively homogeneous clusters the index value for 24 h durations were well estimated as a function of site characteristics only, thus enabling the estimation of 24 h duration design rainfall values at any location in South Africa. In 13 of the 15 clusters the scaling properties of the moments of the AMS were used to successfully estimate design rainfall values for duration < 24h, using the moments of the AMS extracted from the data recorded by standard raingauges and regional relationships based on site characteristics. It was found that L-moments scaled better and over a wider range of durations than ordinary product moments. A methodology was developed for the derivation of the parameters for two Bartlett-Lewis rectangular pulse models using only standard raingauge data, thus enabling the estimation of design values for durations as short as 1 h at sites where only daily rainfall data are available. In view of the low reliability of the majority of short duration rainfall data in South Africa, it is recommended that the regional index value approach be adopted for South Africa, but scaled using values derived from the daily rainfall data. The use of the intra-daily stochastic rainfall models to estimate design rainfall values is recommended as further independent confirmation of the reliability of the design values.
The development of a catchment scale irrigation systems model for sugarcane.
(2005) Moult, Nicholas Greig.; Smithers, Jeffrey Colin.
The implementation of the National Water Act (1998) requires significant changes in the institutional arrangements for water management and, to cater for human and environmental needs, as well as addressing historical inequities, water allocations to irrigated agriculture are likely to be affected. As a result, farmers are facing increasing pressure to use water more effectively, to justify existing water requirements and to budget and plan with growing uncertainty regarding water availability. Therefore, a tool to manage and assess catchment water supply and demand interactions and the associated impacts on the profitability of irrigated sugarcane would be of great value. Although there have been several independent model developments in the fields of water management and sugarcane growth, none provide the required management information in an integrated manner. However, these models provide the foundation for the development of the required modelling tool. An irrigation model for sugarcane, ACRUCane, was developed and incorporated into the ACRU2000 modelling system. The water budget simulated by ACRUCane is linked to a surrounding catchment, the hydrology of which is simulated by the ACRU model. In doing so, a tool has been developed that has the capacity to: • model the soil water balance at a field scale for irrigated areas and at a catchment scale for non-irrigated areas, • link an accurate estimation of crop water requirement for an irrigated area with the availability ofwater at a catchment scale, • explicitly account for the impact of the performance of different irrigation systems on the hydrology and, ultimately, on the sugarcane yield of an irrigated area, • assess the impact of different supply constraints on sugarcane yield, and • estimate both sugarcane and sucrose yield. Extensive verification of the model has been undertaken using data from an irrigation trial at La Mercy, South Africa and two separate trials conducted in the Lowveld of Zimbabwe, with the primary objective of the verification studies being to assess the model's ability to account for different scheduling strategies on sugarcane and sucrose yield. The results obtained show that the model accurately captured the relative differences in yield associated with different irrigation treatments and can thus be used evaluate the impact of different scheduling strategies. A case study was conducted where the feasibility of several hypothetical irrigation scenarios were compared. Different scenarios were created by varying application uniformity, scheduling strategies and system type. This case study illustrated how ACRUCane can be used to provide reliable decision support information to irrigators.