Reconstruction studies of seasonal rainfall utilizing stable isotope based proxy approach suffer from the limitations of time resolutions. Conventional methods and archives limit the achievable resolution to annual scales. However, high resolution reconstruction (seasonal to sub-weekly scale) can be achieved in proxy records where growth rates are high enough to leave spatial signatures in an organically or inorganically deposited layer such as growth bands. In this study, aragonitic skeleton of the gastropod Lissachatina fulica (Bowdich, Giant African Land Snails) is investigated with an aim to achieve sub-weekly scale reconstruction of the Indian monsoon rainfall. These terrestrial gastropods are native of Africa and highly invasive. Their evolution in the geological time period dates back to the Pliocene and is presently distributed across the tropical belt. They exhibit a high growth rate in the presence of water and high relative humidity in the environment. As a result, they are ideally suited for the task of palaeo seasonality reconstruction. The isotopic patterns recorded in their growth bands reveal composition of environmental water at seasonal time scales. In vitro studies were carried out on L. fulica to estimate their growth rates and growth responses to changes in the physical conditions within the culture chamber. The Indian monsoon rainfall exhibits characteristic dry spells that are generally sandwiched between periods of active phases of high rainfall during the South West monsoon season. These dry spells are typically characterized by rainfall with low intensity. Isotope fingerprinting of the rain water at daily time resolution, covering the years of 2007-10 exhibited distinct isotopic ratios for the dry and wet spells. Dry spells were clearly demarcated in the record with isotopically enriched signature. In addition, the study indentified the role of three distinct moisture sources on δ18O of rain water at Bangalore, India. The variability in the oxygen isotopic composition of the Indian monsoon rainfall is predominantly controlled by this source moisture variability at inter annual time scales, while temperature and amount of rainfall tend to dominate the variability in the precipitation isotopes at seasonal and weekly scales. Simultaneous isotopic analyses of both rainwater and shell carbonates growth bands were undertaken to understand their relationship to aid in high resolution reconstruction. Carbonate found in the growth bands of the gastropods, which is precipitated under equilibrium condition from rainwater, preserves the signature of rainfall. This provides an opportunity to reconstruct rainfall parameters (i.e. amount and moisture sources) knowing the variability in shell carbonates. Stable isotopic ratios measured across the growth bands of live shell specimens collected from the southern and eastern Indian regions (Bangalore and Kolkata, respectively) were compared with the rainfall isotope ratios at these two locations; signature of dry spells were clearly identified from the study of isotopic composition in the growth bands of the gastropod specimens. The approach was also extended to older samples from historical archives from eastern Indian region (Kolkata, East India). Individual specimens belonging to the same species of gastropod, which were collected during the monsoon season of the year 1918 were used for reconstructing the seasonal pattern in monsoon rainfall over the region. The record of variation in the isotopic composition seen in the shell was compared with the rainfall data from Indian Metrological Division observatory at Kolkata station. The year 1918 was characterized as a major drought year and the signature of dry period was seen preserved in the specimen. The work under taken in this thesis will widen the scope of seasonality reconstruction using terrestrial shell fossils from palaeo records, which have been rarely investigated in paleoclimate studies from the perspective of understanding the seasonal precipitation variability.

Reconstruction studies of seasonal rainfall utilizing stable isotope based proxy approach suffer from the limitations of time resolutions. Conventional methods and archives limit the achievable resolution to annual scales. However, high resolution reconstruction (seasonal to sub-weekly scale) can be achieved in proxy records where growth rates are high enough to leave spatial signatures in an organically or inorganically deposited layer such as growth bands. In this study, aragonitic skeleton of the gastropod Lissachatina fulica (Bowdich, Giant African Land Snails) is investigated with an aim to achieve sub-weekly scale reconstruction of the Indian monsoon rainfall. These terrestrial gastropods are native of Africa and highly invasive. Their evolution in the geological time period dates back to the Pliocene and is presently distributed across the tropical belt. They exhibit a high growth rate in the presence of water and high relative humidity in the environment. As a result, they are ideally suited for the task of palaeo seasonality reconstruction. The isotopic patterns recorded in their growth bands reveal composition of environmental water at seasonal time scales. In vitro studies were carried out on L. fulica to estimate their growth rates and growth responses to changes in the physical conditions within the culture chamber. The Indian monsoon rainfall exhibits characteristic dry spells that are generally sandwiched between periods of active phases of high rainfall during the South West monsoon season. These dry spells are typically characterized by rainfall with low intensity. Isotope fingerprinting of the rain water at daily time resolution, covering the years of 2007-10 exhibited distinct isotopic ratios for the dry and wet spells. Dry spells were clearly demarcated in the record with isotopically enriched signature. In addition, the study indentified the role of three distinct moisture sources on δ18O of rain water at Bangalore, India. The variability in the oxygen isotopic composition of the Indian monsoon rainfall is predominantly controlled by this source moisture variability at inter annual time scales, while temperature and amount of rainfall tend to dominate the variability in the precipitation isotopes at seasonal and weekly scales. Simultaneous isotopic analyses of both rainwater and shell carbonates growth bands were undertaken to understand their relationship to aid in high resolution reconstruction. Carbonate found in the growth bands of the gastropods, which is precipitated under equilibrium condition from rainwater, preserves the signature of rainfall. This provides an opportunity to reconstruct rainfall parameters (i.e. amount and moisture sources) knowing the variability in shell carbonates. Stable isotopic ratios measured across the growth bands of live shell specimens collected from the southern and eastern Indian regions (Bangalore and Kolkata, respectively) were compared with the rainfall isotope ratios at these two locations; signature of dry spells were clearly identified from the study of isotopic composition in the growth bands of the gastropod specimens. The approach was also extended to older samples from historical archives from eastern Indian region (Kolkata, East India). Individual specimens belonging to the same species of gastropod, which were collected during the monsoon season of the year 1918 were used for reconstructing the seasonal pattern in monsoon rainfall over the region. The record of variation in the isotopic composition seen in the shell was compared with the rainfall data from Indian Metrological Division observatory at Kolkata station. The year 1918 was characterized as a major drought year and the signature of dry period was seen preserved in the specimen. The work under taken in this thesis will widen the scope of seasonality reconstruction using terrestrial shell fossils from palaeo records, which have been rarely investigated in paleoclimate studies from the perspective of understanding the seasonal precipitation variability.

PhDRDV / Institute for Rural Development / Currently, there is limited understanding, appreciation and dissemination of indigenous raining making practices. Yet indigenous rain making is part of the rich African heritage. The current study was premised on the view that indigenous rain making practices can help combat the negative effects of climate change if properly integrated with western science. A mixture of exploratory and survey designs was adopted in this study, which sought to examine the common indigenous rainmaking practices in Chimanimani District of Zimbabwe prior to developing strategies for reducing the negative impacts of climate change on the livelihoods of rural households. Various studies with the following specific objectives were carried out: to analyze the general community perceptions on the potential of indigenous rain making practices in combating the negative effects of climate change; to examine the components of indigenous rainmaking practices; analyse the means of disseminating knowledge on indigenous rainmaking; to identify the negative effects of climate change on the livelihoods of rural households; to assess the effectiveness of existing strategies used by households to cope with the negative effects of climate change; and to propose strategies for utilizing indigenous rainmaking practices to counter the negative effects of climate change on the livelihoods of rural households. Semi-structured interview guides and a questionnaire requiring responses on a Likert-type scale were used to collect data. Key informants and ordinary community members were selected using judgmental, convenient and snowballing sampling techniques. The Thematic Content Analysis technique was used to draw meaning out of the qualitative data. Chi-Square tests for Goodness of Fit were conducted using the Statistical Package for Social Sciences (SPSS) to establish if there were significant relationships among perceptions. It was indicated that the shift in seasons as exemplified by the Nyamavhuvhu wind which now swept Chimanimani in September or October instead of end of July to August was evidence of climate change. Responses with respect to the negative effects of climate change included food insecurity, and drying up of streams and rivers. Availability of water for domestic, agricultural and animal use was becoming increasingly unreliable. The respondents argued that they believed in the effectiveness of indigenous rain making if it is conducted following local customs and traditions. Significant differences in the following perceptions were observed for “Besides makoto and Christian prayers there are other common rainmaking practices practiced in Chimanimani District” (p < 0.05). Similar results were observed with regard to “I believe indigenous and western knowledge of rainmaking can complement each other” (P < 0.001), and “There is increase in pests and plant diseases than before” (P < 0.01). Components of indigenous rain making v identified in the current study included rain making ceremonies (makoto), which entailed use of beer, sacrificial bird (normally a cock) and natural resources conservation such as keeping places for local rain making rituals sacred (zvitenguro), not destroying very big trees for example fig tree (muonde: Ficus capensis), mukute (Syzygium cordatum) and others, and treating forests as sacred. With respect to the negative effects of climate change, a highly significant difference was observed for duration of stay in relation to, “There is now a high risk in planting winter wheat due to changes in climate” (P < 0.01); “Wetlands are disappearing in our area” (P < 0.01); “There is general reduction in yields due to climate change” (P < 0.001) and “We are experiencing scarcity of water for domestic animals and for household use” (P < 0.05). Lastly, highly significant relationships between “Rivers are drying up in our area” and education (P < 0.01) and duration of stay (P < 0.001). Methods used to disseminate indigenous knowledge of rain making were said to be ineffective. Information was being passed on through oral means. It was indicated that better use of modern technology and social media, in particular radio, television, Twitter, WhatsApp and Facebook might enhance people’s knowledge on indigenous rain making. By so doing, the perception that indigenous rain making was merely history and not knowledge that can be used in people’s daily lives would be eliminated. Furthermore, current strategies utilized to combat the negative effects of climate change were reported to be unsustainable. Among these were reliance on harvesting wild fruits for sale and hunting. Human activities such as veld fires, deforestation and over harvesting of wildlife were viewed in negative light with respect to combating negative effects of climate change. It was proposed that communities should revert to respecting traditional beliefs of conserving forests. This said to be key in normalizing climate, attracting back the birds and animals that used to be key in weather forecasting. Replanting and indiscriminate cutting of trees along rivers as effective prevention of stream bank cultivation were proposed. Re-introduction of heavy fines by traditional leadership was suggested as a tried and tested strategy that was no longer being applied when implementing conservation initiatives. The observation made in this study that western science and indigenous rain making practices were similar in many respects, suggested that these were opportunities that could be used to anchor strategies for integrating them. In addition to this, the need for establishing collective deliberation or interface platforms coupled with continuous communication and careful management of intellectual property was obvious.

Issues arising from climate change and long-term natural climate variability have become the focus of much recent research. In this study, we specifically explore the impacts of long-term climate variability and climate changes upon flood frequencies. The analyses of the flood frequencies are carried out in a comparative manner in catchments located in semiarid-temperate and tropical landscapes in Australia, namely Perth, Newcastle and Darwin, using a process-based derived flood frequency approach. The derived flood frequency analyses are carried out using deterministic rainfall-runoff models that capture the intrinsic water balance variability in the study catchments, and driven by temporal rainfall event sequences that are generated by a stochastic rainfall model that incorporates temporal variabilities over a multiplicity of time scales, ranging from within-event, between-event to seasonal, multi-annual and multi-decadal time scales. Six climate scenarios are considered for Newcastle, that combine the ENSO (El Niño Southern Oscillation) and IPO (Inter-decadal Pacific Oscillation) modes of variability, and six different climate scenarios are considered for Perth and Darwin that combine these different ENSO modes and step changes in climate (upwards or downwards) that occurred in 1970 in both regions, which were identified through statistical analysis. The results of the analyses showed that La Niña years cause higher annual maximum floods compared to El Niño and Neutral years in all three catchments. The impact of ENSO on annual maximum floods in the Newcastle catchment is enhanced when the IPO is negative and for Perth, the impact of ENSO weakens in the post-1970 period, while it strengthens in Darwin in the same period. In addition, the results of sensitivity and scenario analyses with the derived flood frequency model explored the change of dominant runoff generation processes contributing to floods in each of the study catchments. These analyses highlighted a switch from subsurface stormflow to saturation excess runoff with a change of return period, which was much more pronounced in Perth and Darwin, and not so in Newcastle. In Perth and Darwin this switch was caused by the interactions between the out-of-phase seasonal variabilities of rainfall and potential evaporation, whereas the seasonality was much weaker in Newcastle. On the other hand, the combination of higher rainfall intensities and shallower soil depths led to saturation excess runoff being the dominant mechanism in Newcastle across the full range of return periods. Consequently, within-storm rainfall intensity patterns were important in Newcastle in all major flood producing events (all return periods), where they were only important in Perth and Darwin for floods of high return periods, which occur during wet months in wet years, when saturation excess runoff was the dominant mechanism. Additionally, due to the possibility of a change of process from subsurface stormflow to saturation excess when conditions suited this switch, the estimates of flood frequency are highly uncertain especially at high return periods (in Darwin and Perth) and much less in Newcastle (when no process change was involved).

South Africa is a semi arid country in which the average rainfall of 450mm/year is well below the world average of about 860mm/year. As a result, South Africa’s water resources are scarce in global terms and limited in extent. Current predictions are that demand will outstrip water availability in the next 15 years. A coordinated approach to improve both water quality and quantity is needed and in order to achieve that, it is crucial to strengthen capacities of local community involvement in identifying the problems that affect them and strategies to solve them. This research was undertaken to develop a deeper understanding of community learning processes in integrated water resources management (IWRM) practices. The study drew on situated and social learning theory which explains that knowledge and skills are learned and embedded in the contexts in which knowledge is obtained and applied in everyday situations. Multiple data collection techniques were used within a case study design and included document analysis, interviews, focus group discussions and field observations. Data analysis was done in three phases and involved uncovering patterns and trends in the data sets. In this context I discovered, through careful observation and interviews with members of the different communities of practice, that people are learning through social learning interactions with other community members as they engage in their daily water management and food production practices. Learning interactions take place through both informal and formal processes such as meetings, training workshops, conversations and interactions with outsiders. I also discovered that people learn from ‘external groups’ or training programmes which bring new knowledge and expertise, but this needs to be contextualised in the local communities of practice. The research has also shown that there are a number of challenges that appear to exist in these learning contexts. For instance it was found that participation and social learning processes and interactions are influenced by a range of causal mechanisms that are contextual. These insights into how communities learn, as well as the tensions and difficulties that are experienced in the learning processes are important for furthering learning and participation in community-based IWRM practices, projects and programmes.

Water is recognised as a key driver for social and economic development in the Zambezi basin. The basin is riparian to eight southern African countries and the transboundary nature of the basin’s water resources can be viewed as an agent of cooperation between the basin countries. It is possible, however, that the same water resource can lead to conflicts between water users. The southern African Water Vision for ‘equitable and sustainable utilisation of water for social, environmental justice and economic benefits for the present and future generations’ calls for an integrated and efficient management of water resources within the basin. Ensuring water and food security in the Zambezi basin is, however, faced with challenges due to high variability in climate and the available water resources. Water resources are under continuous threat from pollution, increased population growth, development and urbanisation as well as global climate change. These factors increase the demand for freshwater resources and have resulted in water being one of the major driving forces for development. The basin is also vulnerable due to lack of adequate financial resources and appropriate water resources infrastructure to enable viable, equitable and sustainable distribution of the water resources. This is in addition to the fact that the basin’s economic mainstay and social well-being are largely dependent on rainfed agriculture. There is also competition among the different water users and this has the potential to generate conflicts, which further hinder the development of water resources in the basin. This thesis has focused on the Zambezi River basin emphasising climate variability and climate change. It is now considered common knowledge that the global climate is changing and that many of the impacts will be felt through water resources. If these predictions are correct then the Zambezi basin is most likely to suffer under such impacts since its economic mainstay is largely determined by the availability of rainfall. It is the belief of this study that in order to ascertain the impacts of climate change, there should be a basis against which this change is evaluated. If we do not know the historical patterns of variability it may be difficult to predict changes in the future climate and in the hydrological resources and it will certainly be difficult to develop appropriate management strategies. Reliable quantitative estimates of water availability are a prerequisite for successful water resource plans. However, such initiatives have been hindered by paucity in data especially in a basin where gauging networks are inadequate and some of them have deteriorated. This is further compounded by shortages in resources, both human and financial, to ensure adequate monitoring. To address the data problems, this study largely relied on global data sets and the CRU TS2.1 rainfall grids were used for a large part of this study. The study starts by assessing the historical variability of rainfall and streamflow in the Zambezi basin and the results are used to inform the prediction of change in the future. Various methods of assessing historical trends were employed and regional drought indices were generated and evaluated against the historical rainfall trends. The study clearly demonstrates that the basin has a high degree of temporal and spatial variability in rainfall and streamflow at inter-annual and multi-decadal scales. The Standardised Precipitation Index, a rainfall based drought index, is used to assess historical drought events in the basin and it is shown that most of the droughts that have occurred were influenced by climatic and hydrological variability. It is concluded, through the evaluation of agricultural maize yields, that the basin’s food security is mostly constrained by the availability of rainfall. Comparing the viability of using a rainfall based index to a soil moisture based index as an agricultural drought indicator, this study concluded that a soil moisture based index is a better indicator since all of the water balance components are considered in the generation of the index. This index presents the actual amount of water available for the plant unlike purely rainfall based indices, that do not account for other components of the water budget that cause water losses. A number of challenges were, however, faced in assessing the variability and historical drought conditions, mainly due to the fact that most parts of the Zambezi basin are ungauged and available data are sparse, short and not continuous (with missing gaps). Hydrological modelling is frequently used to bridge the data gap and to facilitate the quantification of a basin’s hydrology for both gauged and ungauged catchments. The trend has been to use various methods of regionalisation to transfer information from gauged basins, or from basins with adequate physical basin data, to ungauged basins. All this is done to ensure that water resources are accounted for and that the future can be well planned. A number of approaches leading to the evaluation of the basin’s hydrological response to future climate change scenarios are taken. The Pitman rainfall-runoff model has enjoyed wide use as a water resources estimation tool in southern Africa. The model has been calibrated for the Zambezi basin but it should be acknowledged that any hydrological modelling process is characterised by many uncertainties arising from limitations in input data and inherent model structural uncertainty. The calibration process is thus carried out in a manner that embraces some of the uncertainties. Initial ranges of parameter values (maximum and minimum) that incorporate the possible parameter uncertainties are assigned in relation to physical basin properties. These parameter sets are used as input to the uncertainty version of the model to generate behavioural parameter space which is then further modified through manual calibration. The use of parameter ranges initially guided by the basin physical properties generates streamflows that adequately represent the historically observed amounts. This study concludes that the uncertainty framework and the Pitman model perform quite well in the Zambezi basin. Based on assumptions of an intensifying hydrological cycle, climate changes are frequently expected to result in negative impacts on water resources. However, it is important that basin scale assessments are undertaken so that appropriate future management strategies can be developed. To assess the likely changes in the Zambezi basin, the calibrated Pitman model was forced with downscaled and bias corrected GCM data. Three GCMs were used for this study, namely; ECHAM, GFDL and IPSL. The general observation made in this study is that the near future (2046-2065) conditions of the Zambezi basin are expected to remain within the ranges of historically observed variability. The differences between the predictions for the three GCMs are an indication of the uncertainties in the future and it has not been possible to make any firm conclusions about directions of change. It is therefore recommended that future water resources management strategies account for historical patterns of variability, but also for increased uncertainty. Any management strategies that are able to satisfactorily deal with the large variability that is evident from the historical data should be robust enough to account for the near future patterns of water availability predicted by this study. However, the uncertainties in these predictions suggest that improved monitoring systems are required to provide additional data against which future model outputs can be assessed.

The idea of time series forecasting techniques is that the past has certain information about future. So, the question of how the information is encoded in the past can be interpreted and later used to extrapolate events of future constitute the crux of time series analysis and forecasting. Several methods such as qualitative techniques (e.g., Delphi method), causal techniques (e.g., least squares regression), quantitative techniques (e.g., smoothing method, time series models) have been developed in the past in which the concept lies in establishing a model either theoretically or mathematically from past observations and estimate future from it. Of all the models, time series methods such as autoregressive moving average (ARMA) process have gained popularity because of their simplicity in implementation and accuracy in obtaining forecasts. But, these models were formulated based on certain properties that a time series is assumed to possess. Classical decomposition techniques were developed to supplement the requirements of time series models. These methods try to define a time series in terms of simple patterns called trend, cyclical and seasonal patterns along with noise. So, the idea of decomposing a time series into component patterns, later modeling each component using forecasting processes and finally combining the component forecasts to obtain actual time series predictions yielded superior performance over standard forecasting techniques. All these methods involve basic principle of moving average computation. But, the developed classical decomposition methods are disadvantageous in terms of containing fixed number of components for any time series, data independent decompositions. During moving average computation, edges of time series might not get modeled properly which affects long range forecasting. So, these issues are to be addressed by more efficient and advanced decomposition techniques such as Wavelets and Empirical Mode Decomposition (EMD). Wavelets and EMD are some of the most innovative concepts considered in time series analysis and are focused on processing nonlinear and nonstationary time series. Hence, this research has been undertaken to ascertain the predictability of nonstationary time series using wavelet and Empirical Mode Decomposition (EMD) based ARMA models. The development of wavelets has been made based on concepts of Fourier analysis and Window Fourier Transform. In accordance with this, initially, the necessity of involving the advent of wavelets has been presented. This is followed by the discussion regarding the advantages that are provided by wavelets. Primarily, the wavelets were defined in the sense of continuous time series. Later, in order to match the real world requirements, wavelets analysis has been defined in discrete scenario which is called as Discrete Wavelet Transform (DWT). The current thesis utilized DWT for performing time series decomposition. The detailed discussion regarding the theory behind time series decomposition is presented in the thesis. This is followed by description regarding mathematical viewpoint of time series decomposition using DWT, which involves decomposition algorithm. EMD also comes under same class as wavelets in the consequence of time series decomposition. EMD is developed out of the fact that most of the time series in nature contain multiple frequencies leading to existence of different scales simultaneously. This method, when compared to standard Fourier analysis and wavelet algorithms, has greater scope of adaptation in processing various nonstationary time series. The method involves decomposing any complicated time series into a very small number of finite empirical modes (IMFs-Intrinsic Mode Functions), where each mode contains information of the original time series. The algorithm of time series decomposition using EMD is presented post conceptual elucidation in the current thesis. Later, the proposed time series forecasting algorithm that couples EMD and ARMA model is presented that even considers the number of time steps ahead of which forecasting needs to be performed. In order to test the methodologies of wavelet and EMD based algorithms for prediction of time series with non stationarity, series of streamflow data from USA and rainfall data from India are used in the study. Four non-stationary streamflow sites (USGS data resources) of monthly total volumes and two non-stationary gridded rainfall sites (IMD) of monthly total rainfall are considered for the study. The predictability by the proposed algorithm is checked in two scenarios, first being six months ahead forecast and the second being twelve months ahead forecast. Normalized Root Mean Square Error (NRMSE) and Nash Sutcliffe Efficiency Index (Ef) are considered to evaluate the performance of the proposed techniques. Based on the performance measures, the results indicate that wavelet based analyses generate good variations in the case of six months ahead forecast maintaining harmony with the observed values at most of the sites. Although the methods are observed to capture the minima of the time series effectively both in the case of six and twelve months ahead predictions, better forecasts are obtained with wavelet based method over EMD based method in the case of twelve months ahead predictions. It is therefore inferred that wavelet based method has better prediction capabilities over EMD based method despite some of the limitations of time series methods and the manner in which decomposition takes place. Finally, the study concludes that the wavelet based time series algorithm could be used to model events such as droughts with reasonable accuracy. Also, some modifications that could be made in the model have been suggested which can extend the scope of applicability to other areas in the field of hydrology.

MESHWR / See the attached abstract below

MESHWR / Department of Hydrology and Water Resources / This study dealt with the influence of climate variability on flood and drought cycles and implications on rainy season characteristics in Luvuvhu River Catchment (LRC) in Limpopo of South Africa. Extreme weather events resulting in hazards such as floods and droughts are becoming more frequent due to climate change. Extreme events affect rainy season characteristics and hence have an influence on water availability and agricultural production. Annual temperature was obtained from Water Research Commission for stations 0723485W, 0766628W and 0766898W from 1950-2013 were used to show/or confirm if there is climate variability in LRC. Daily rainfall data was obtained from SAWS for stations 0766596 9, 0766563 1, 0723485 6 and 0766715 5 were used to detect climate variability and determine the onset, duration and cessation of the rainy season. Streamflow data obtained from the Department of Water and Sanitation for stations A9H004, A9H012, and A9H001 for at least a period of 30 years for each station were used for climate variability detection and determination of flood and drought cycles. Influence of climate variability on floods and droughts and rainy season characteristic were determined in the area of study. Trends were evaluated for temperature, rainfall and streamflow data in the area of study using Mann Kendall (MK) and linear regression (LR) methods. MK and LR detected positive trends for temperature (maximum and minimum) and streamflow stations. MK and LR results of rainfall stations showed increasing trends for stations 0766596 9, and 0766563 1 whereas stations 0723485 6 and 0766715 5 showed decreasing trends. Standardized precipitation index (SPI) was used to determine floods and droughts cycles. SPI results have been classified either as moderately, severely and extremely dry or, moderately, very and extremely wet. This SPI analysis provides more details of dominance of distinctive dry or wet conditions for a rainy season at a particular station. Mean onset of rainfall varied from day 255 to 297, with 0766715 5 showing the earliest onset compared to the rest of the stations. Cessation of rainfall for most of the hydrological years was higher than the mean days of 88, 83 and 86 days in 0766596 9, 0766563 1 and 0723485 6 stations. Mean duration of rainfall varied from 102 to 128, with station 0766715 5 showing shortest duration of rainfall. The results of the study showed that the mean onset, duration and cessation were comparable for all stations except 0766715 5 which had lower values. The study also found that climate variability greatly affects onset, duration and cessation of rainfall during dry years. This led to late onset, early cessation and relatively short duration of the rainfall season. Communities within the catchment must be educated to practice activities such as conservation of indigenous plants, reduce carbon dioxide emissions.

MESHWR / Department of Hydrology and Water Resources / This study was aimed at investigating the long term seasonal and annual changes in rainfall duration and magnitude at Luvuvhu River Catchment (LRC). Rainfall in this catchment is highly variable and is characterised of extreme events which shift runoff process, affect the timing and magnitude of floods and drought, and alter groundwater recharge. This study was motivated by the year to year changes of rainfall which have some effects on the availability of water resources. Computed long term total seasonal, annual rainfall and total number of seasonal rainy days were used to identify trends for the period of 51 years (1965- 2015), using Mann Kendal (MK), linear regression (LR) and quantile regression methods. The MK, LR and quantile regression methods have indicated dominance of decreasing trends of the annual, seasonal rainfall and duration of seasonal rainfall although they were not statistically significant. However, statistical significant decreasing trends in duration of seasonal rainfall were identified by MK and LR at Matiwa, Palmaryville, Levubu, and Entabeni Bos stations only. Quantile regression identified the statistically significant decreasing trends on 0.2, 0.5 and 0.7 quantiles only in the Palmaryville, Levubu and Entabeni Bos, respectively. Stations with non-statistically significant decreasing trends of annual and seasonal rainfall had magnitude of change ranging from 0.12 to 12.31 and 0.54 to 6.72 mm, respectively. Stations with non-statistically increasing trends of annual and seasonal rainfall magnitude had positive magnitude of change ranging from 1.51 to 6.78 and 2.05 to 6.51 mm, respectively. The Study recommended further studies using other approaches to determine the duration of rainfall to improve, update and compare the results obtained in the current study. Continuous monitoring and installation of rain gauges are recommended on the lower reaches of the catchment for the findings to be of complete picture for the whole catchment and to also minimize the rainfall gaps in the stations. Water resources should be used in a sustainable way to avoid water crisis risk in the next generations. / NRF