Indigenous Knowledge and Sustainable Development: The Case of Rwanda's Agricultural Sector.

The need for creating sustainable and relatable development projects has placed a sharp focus of the different approaches and methods of achieving development. Traditional development approaches such as top-down theory and the bottom-up theory of development have evolved over the years whilst recent approaches such as Randomised Controlled Experiments (RCE) have also emerged with the aim of creating sustainable and more relatable development projects. All these approaches of development have had their fair share of criticism and applauses in literature. The use of Indigenous Knowledge Systems (IK) as a factor of the bottom-up theory of development has been argued as an important element of advancing the developmental agenda and creating sustainable & relatable projects. Many scholars have conducted research around how IK can be incorporated in development projects around the world. Although research has been conducted, much is yet to be discovered around the actual impact or lack thereof of IK as a key factor of the bottom-up theory of development in development projects. This dissertation researched the impact of Rwanda's IK as a factor of the bottom-up theory of development with a focus on Rwanda's Land, Husbandry water harvesting and Hillside irrigation (LWH) project as a unit of analysis. Furthermore, the research assessed whether the Rwandan water harvesting, and irrigation IK played a role in the overall project conceptualization, design and implementation and if so, how this was incorporated in the overall project and finally what role (if any) this IK played in the overall outcomes of the LWH project. A qualitative case study research of the Rwanda's Land Husbandry, Water Harvesting and Irrigation Project was conducted within-depth questionnaires used as data collection instruments from farmers and project coordinators who were immensely involved in the design, development, implementation and monitoring of the project. Data analysis showed that most study participants agreed that the Rwandan water harvesting, and irrigation IK was incorporated in the LWH project and was a key success factor in the bottom-up theory used to implemented in the LWH project. The research found that the incorporation of IK as a factor of the bottom-up theory enabled quicker adoption of the project, increased levels of accountability and responsibility over the project by project beneficiaries and an accelerated attainment of project goals and objectives

Convective initiation and storm life‐cycles in convection‐permitting simulations of the Met Office Unified Model over South Africa

Convective initiation is a challenge for convection‐permitting models due to its sensitivity to sub‐km processes. We evaluate the representation of convective storms and their initiation over South Africa during four summer months in Met Office Unified Model simulations at 1.5‐km horizontal grid length. Storm size distributions from the model compare well against radar observations, but rainfall in the model is predominantly produced by large storms (50 km in diameter or larger) in the evening, whereas radar observations show most rainfall occurs throughout the afternoon, from storms 10‐50 km in diameter. In all months, modelled maximum number of storm initiations occurs at least 2 hours prior to the radar‐observed maximum. However, the diurnal cycle of rainfall compares well between model and observations, suggesting the numerous storm initiations in the simulations do not produce much rainfall. Modelled storms are generally less intense than in the radar observations, especially in early summer. In February, when tropical influences dominate, the simulated storms are of similar intensity to observed storms. Simulated storms tend to reach their peak intensity in the first 15 minutes after initiation, then gradually become less intense as they grow. In radar observations, storms reach their peak intensity 15‐30 minutes into their life cycle, stay intense as they grow larger, then gradually weaken after they have reached their maximum diameter. Two November case studies of severe convection are analysed in detail. Higher resolution grid length initiates convection slightly earlier (300 m cf. 1.5 km) with the same science settings. Two 1.5‐km simulations that apply more sub‐grid mixing have delayed convective initiation. Analysis of soundings indicates little difference in convective indices, suggesting that differences in convection may be attributed to choices in sub‐grid mixing parameters

Evaluating South African Weather Service information on Idai tropical cyclone and KwaZulu-Natal flood events

Severe weather events associated with strong winds and flooding can cause fatalities, injuries and damage to property. Detailed and accurate weather forecasts that are issued and communicated timeously, and actioned upon, can reduce the impact of these events. The responsibility to provide such forecasts usually lies with government departments or state-owned entities; in South Africa that responsibility lies with the South African Weather Service (SAWS). SAWS is also a regional specialised meteorological centre and therefore provides weather information to meteorological services within the Southern African Development Community (SADC). We evaluated SAWS weather information using near real-time observations and models on the nowcasting to short-range forecasting timescales during two extreme events. These are the Idai tropical cyclone in March 2019 which impacted Mozambique, Zimbabwe and Malawi resulting in over 1000 deaths, and the floods over the KwaZulu-Natal (KZN) province in April 2019 that caused over 70 deaths. Our results show that weather models gave an indication of these systems in advance, with warnings issued at least 2 days in advance in the case of Idai and 1 day in advance for the KZN floods. Nowcasting systems were also in place for detailed warnings to be provided as events progressed. Shortcomings in model simulations were shown, in particular on locating the KZN flood event properly and over/-underestimation of the event. The impacts experienced during the two events indicate that more needs to be done to increase weather awareness, and build disaster risk management systems, including disaster preparedness and risk reduction.Significance: This paper is relevant for all South Africans and the SADC region at large because it provides information on: the weather forecasting processes followed at the South African Weather Service, available early warning products in South Africa and for the SADC region made possible through the public purse, the performance of nowcasting and modelling systems in the case of predicting two extreme weather events that had adverse impacts on southern African society, and the dissemination of warnings of future extreme weather events

Sensitivity of tropical cyclone Idai simulations to cumulus parametrization schemes

Weather simulations are sensitive to subgrid processes, that are parameterized in numerical weather prediction (NWP) models. In this study, we investigate the response of tropical cyclone Idai simulations to different cumulus parameterization schemes, using the Weather Research and Forecasting (WRF) model with a 6 km grid length. Seventy-two hour (00 UTC 13 March to 00 UTC 16 March) simulations are conducted with the New Tiedtke (Tiedtke), New Simplified Arakawa Schubert (NewSAS), Multi-scale Kain Fritsch (MSKF), Grell-Freitas, and the Betts-Miller-Janjic (BMJ) schemes. A simulation for the same event is also conducted with the convection scheme switched off. The twenty-four hour accumulated rainfall during all three simulated days is generally similar across all six experiments. Larger differences in simulations are found for rainfall events away from the tropical cyclone. When the resolved and convective rainfall are partitioned, it is found that the scale-aware schemes (i.e. Grell-Freitas and MSKF) allow the model to resolve most of the rainfall, while they are less active. Regarding the maximum wind speed, and minimum sea level pressure (MSLP), the scale aware schemes simulate a higher intensity that is similar to the Joint Typhoon Warning Center (JTWC) data set, however the timing is more aligned with the Global Forecast System (GFS), which is the model providing initial conditions and time dependent lateral boundary conditions. Simulations with the convection scheme off were found to be similar to those with the scale-aware schemes. It is found that Tiedtke simulates the location to be farther south west compared to other schemes, while BMJ simulates the path to be more to the north after landfall. All of the schemes as well as GFS failed to simulate the movement of Idai into Zimbabwe, showing potential impact of shortcomings in the forcing model. Our study shows that the use of scale aware schemes allows the model to resolve most of the dynamics, resulting in higher weather system intensity in the grey zone. The wrong timing of the peak shows a need to use better performing global models to provide lateral boundary conditions for downscalers

Sensitivity of simulations of Zambian heavy rainfall events to the atmospheric boundary layer schemes

Weather forecasting relies on the use of Numerical Weather Prediction (NWP) models, whose resolution is informed by the available computational resources. The models resolve large scale processes, while subgrid processes are parametrized. One of the processes that is parametrized is turbulence which is represented in Planetary Boundary Layer (PBL) schemes. In this study, we evaluate the sensitivity of heavy rainfall events over Zambia to four different PBL schemes in the Weather Research and Forecasting (WRF) model using a parent domain with a 9 km grid length and a 3 km grid spacing child domain. The four PBL schemes are the Yonsei University (YSU), the nonlocal first-order medium-range forecasting (MRF), the University ofWashington (UW) and the Mellor–Yamada–Nakanishi–Niino (MYNN) schemes. Simulations are made for three case studies of extreme rainfall on 17 December 2016, 21 January 2017 and 17 April 2019. Use of the YSU produced the highest rainfall peaks across all three cases, however it produces performance statistics similar to UW that are higher than the two other schemes. These statistics are not maintained when adjusted for random hits indicating that the extra events are mainly random rather than being skilfully placed. UW simulated the lowest PBL height, while MRF produced the highest PBL height, but this is not matched by the temperature simulation. The YSU and MYNN PBL heights were intermediate at the time of the peak, however MYNN is associated with a slower decay, and higher PBL heights at night. WRF underestimates the maximum temperature during all the cases and for all PBL schemes, with a larger bias in the MYNN scheme. We support further use of the YSU scheme, which is the scheme selected for the tropical suite in WRF. The different simulations were in some respects more similar to one another than to the available observations. Satellite rainfall estimates and the ERA5 reanalysis showed different rainfall distributions, which indicate a need for more ground observations to assist with studies like this one

Evaluating South African weather service information on Idai tropical cyclone and KwaZulu- Natal flood events

Severe weather events associated with strong winds and flooding can cause fatalities, injuries and damage to property. Detailed and accurate weather forecasts that are issued and communicated timeously, and actioned upon, can reduce the impact of these events. The responsibility to provide such forecasts usually lies with government departments or state-owned entities; in South Africa that responsibility lies with the South African Weather Service (SAWS). SAWS is also a regional specialised meteorological centre and therefore provides weather information to meteorological services within the Southern African Development Community (SADC). We evaluated SAWS weather information using near real-time observations and models on the nowcasting to short-range forecasting timescales during two extreme events. These are the Idai tropical cyclone in March 2019 which impacted Mozambique, Zimbabwe and Malawi resulting in over 1000 deaths, and the floods over the KwaZulu-Natal (KZN) province in April 2019 that caused over 70 deaths. Our results show that weather models gave an indication of these systems in advance, with warnings issued at least 2 days in advance in the case of Idai and 1 day in advance for the KZN floods. Nowcasting systems were also in place for detailed warnings to be provided as events progressed. Shortcomings in model simulations were shown, in particular on locating the KZN flood event properly and over/underestimation of the event. The impacts experienced during the two events indicate that more needs to be done to increase weather awareness, and build disaster risk management systems, including disaster preparedness and risk reduction. Significance: This paper is relevant for all South Africans and the SADC region at large because it provides information on: • the weather forecasting processes followed at the South African Weather Service, • available early warning products in South Africa and for the SADC region made possible through the public purse, • the performance of nowcasting and modelling systems in the case of predicting two extreme weather events that had adverse impacts on southern African society, and • the dissemination of warnings of future extreme weather events.The Climate Research for Development (CR4D) Postdoctoral Fellowship CR4D-19-11 implemented by the African Academy of Sciences (AAS) in partnership with the United Kingdom’s Department for International Development (DfID) Weather and Climate Information Services for Africa (WISER) programme and the African Climate Policy Center (ACPC) of the United Nations Economic Commission for Africa (UNECA).http://www.sajs.co.zaam2022Geography, Geoinformatics and Meteorolog

Drought characterization in South Africa under changing climate

The outputs from the Global Climate Models (GCMs) and Regional Climate Models (RCMs) have been used worldwide to predict the evolution of extreme weather events such as floods and droughts. In this study the spatial and temporal characteristics of historical, current as well as future meteorological drought trends are computed using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Statistical and trend analysis done using SPI time series derived from rainfall observations have shown that most parts of South Africa experienced moderate to severe droughts between 1981 and 2015. Gridded monthly precipitation data from the Tropical Rainfall Measuring Mission (TRMM) satellite was used to compute the SPI at each grid point of the domain. The computed SPI was used to obtain drought monitoring indicators such as drought intensity (DI), drought severity (DS), drought duration (DD) and drought frequency (DF) for the period 1998-2015. Results have shown decreasing (negative) trends in drought intensity and duration over most parts of South Africa mainly in provinces such as Gauteng, Limpopo, Free State and North West province. Furthermore results shows that SPI/SPEI computed using data from in-situ observations as well as the SPI computed using data from TRMM reproduced most of the major drought episodes that occurred in South Africa during 1981-2015. Additionally, the ensemble mean of climate simulations obtained when the Rossby Centre for regional climate model (RCA4) is forced by nine GCM models was used to compute the Standardized Precipitation Evapotranspiration Index (SPEI) during the reference period (1971-2000) and future projections (2011-2040 and 2041-2070) under Representative Concentration Pathways (RCP 8.5). Statistical and trend analysis were done using drought intensity, severity, duration and frequency. Moreover, results show an overall increase in drought intensity, duration, severity and frequency during the two future periods 2011-2040 and 2041-2070 under RCP 8.5. Future studies will focus on the impact based assessment in order to complete the drought preparedness and mitigation plan.Dissertation (MSc)--University of Pretoria, 2018.Geography, Geoinformatics and MeteorologyMScUnrestricte

Characteristics of Droughts in South Africa: A Case Study of Free State and North West Provinces

The Free State (FS) and North West (NW) Provinces are often hard hit by droughts with impacts on water availability, farm production and livestock holdings. The South African government declared the two Provinces drought disaster areas in the 2015/2016 hydrological year. This is a major drawback, since both the Provinces play an important role to South African economy as they are a haven to agricultural production and have major water reservoirs in South Africa. This study was undertaken to investigate the historical evolution of drought within the FS and NW Provinces over the past 30 years. The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) calculated based on monthly meteorological data from 14 weather/climate stations within the FS and NW Provinces were used to explore and characterize variation in drought intensity, duration, frequency and severity in FS and NW Provinces during 1985–2015. Results indicate that there exist localized positive and negative trends with spatial dependence across the selected stations. In particular, about 60% of the weather stations exhibiting a decreasing trend are located in FS Province, suggesting that FS has being experiencing increasing drought during the analyzed period compared to NW Province. Results from the analysis of drought evaluation indicators (DEIs) calculated from SPEI suggest that drought severity and frequency was more pronounced in FS while the intensity of the drought was more in NW Province during 1985–2015. In addition, based on SPEI calculations, moderate drought occurrences increased during 1985–1994 and 1995–2004 periods and decreased thereafter (2005–2015) in both Provinces. Drought classification based on parameters derived from SPEI produced similar results for mild drought occurrences during the same time scales

Sensitivity of tropical cyclone Idai simulations to cumulus parametrization schemes

Weather simulations are sensitive to subgrid processes that are parameterized in numerical weather prediction (NWP) models. In this study, we investigated the response of tropical cyclone Idai simulations to different cumulus parameterization schemes using the Weather Research and Forecasting (WRF) model with a 6 km grid length. Seventy-two-hour (00 UTC 13 March to 00 UTC 16 March) simulations were conducted with the New Tiedtke (Tiedtke), New Simplified Arakawa– Schubert (NewSAS), Multi-Scale Kain–Fritsch (MSKF), Grell–Freitas, and the Betts–Miller–Janjic (BMJ) schemes. A simulation for the same event was also conducted with the convection scheme switched off. The twenty-four-hour accumulated rainfall during all three simulated days was generally similar across all six experiments. Larger differences in simulations were found for rainfall events away from the tropical cyclone. When the resolved and convective rainfall are partitioned, it is found that the scale-aware schemes (i.e., Grell–Freitas and MSKF) allow the model to resolve most of the rainfall, while they are less active. Regarding the maximum wind speed, and minimum sea level pressure (MSLP), the scale aware schemes simulate a higher intensity that is similar to the Joint Typhoon Warning Center (JTWC) dataset, however, the timing is more aligned with the Global Forecast System (GFS), which is the model providing initial conditions and time-dependent lateral boundary conditions. Simulations with the convection scheme off were found to be similar to those with the scale-aware schemes. It was found that Tiedtke simulates the location to be farther southwest compared to other schemes, while BMJ simulates the path to be more to the north after landfall. All of the schemes as well as GFS failed to simulate the movement of Idai into Zimbabwe, showing the potential impact of shortcomings on the forcing model. Our study shows that the use of scale aware schemes allows the model to resolve most of the dynamics, resulting in higher weather system intensity in the grey zone. The wrong timing of the peak shows a need to use better performing global models to provide lateral boundary conditions for downscalers.This research was partially funded through the Climate Research for Development (CR4D) fellowship grant number CR4D-19-11 managed by the African Academy of Sciences. The work is also supported by the South African Department of Science and Innovation to implement the SADC Cyber-Infrastructure FrameworkThe Climate Research for Development (CR4D) fellowship granthttp://www.mdpi.com/journal/atmospherepm2021Geography, Geoinformatics and Meteorolog