Effects of land use and land cover changes on water quality of the upper Umngeni River, KwaZulu-Natal Province, South Africa.

Doctor of Philosophy in Hydrology University of KwaZulu-Natal. Pietermaritzburg, 2017.Changes of land use and land cover are important drivers of the quality of water reaching a waterbody. These changes affect the catchment and modify the chemical composition of the atmosphere, and thus altering the cycle of nutrients and the flux of energy. With current developments in Geographic Information Systems (GIS) techniques, hydrological modelling and statistical analyses, one or a combination of many methods can be used to assess the relationships between land use and land cover (LULC) classes and water quality variables. However, all these approaches are reliant on the collection of field measurements, LULC data and water sampling. Typically funding for such long-term information is not generally available in Africa. A three-year study involving analysis of historical data, field work and desktop investigations was conducted in the upper reaches of the uMngeni Catchment (1653 km2), South Africa, to assess the spatial and temporal variation of land use and land cover and its influence on the flux of water, nutrients (nitrogen and phosphorus) and Escherichia coli (E. coli) in the catchment. This involved the analysis of historical land use and land cover information (1994, 2000, 2008 and 2011), analysis and processing of historical datasets of E. coli, electrical conductivity, ammonium, nitrate, soluble reactive phosphorus (SRP), total phosphorus (TP), total suspended solids (TSS), temperature and turbidity. A water quality index based on a long-term data base of water quality emanating from existing monitoring programmes was assessed. In addition, stations were established for river sampling (14) and collection of bulk atmospheric deposition (3) of ammonium, nitrates, SRP and TP, in the Midmar Dam catchment (927 km2). These were consolidated with the application and testing of the Hydrological Predictions for the Environment (HYPE) model in the catchment, in simulating streamflow, transport and dynamic of inorganic nitrogen and total phosphorus, resulting from LULC changes. Results showed that the natural vegetation declined by 17% between 1994 and 2011, coinciding with an increase in cultivated, urban/built-up and degraded lands by 6%, 4.5% and 3%, respectively. This resulted in high variability in the concentrations of water quality parameters, but Midmar and Albert Falls Dams retain over 20% of nutrients and sediment and approximately 85% of E. coli. It was concluded that these dramatic changes in LULC directly affect the chemical composition of water in the catchment. However, these linkages are complex, site-specific and vary from one sub-catchment to another and decision-making regarding water resources management in the catchment must recognise this. The level of E. coli in water is a major issue for human contact during recreational activities in the entire study area. Higher concentrations of E. coli, ammonium, nitrates, SRP and TP were attributed to the poor or lack of sanitation facilities in the informal settlements, dysfunctional sewage systems, effluent discharged from wastewater works, expansion of agricultural activities, as well as a runoff from livestock farming and urban areas. Moreover, water quality in the catchment ranged between “marginal” and “fair”, predominantly “marginal” in 90% of the sites and completely poorer in the Mthinzima Stream, an important tributary of Midmar Dam. A declining monitoring frequency and resultant poorly reporting of water quality in the catchment, led to a recommendation for the establishment of automatic or event-based samplers, which should provide the optimum information on nutrient loadings to the waterbodies. Bulk atmospheric deposition and river inflows into the Midmar Dam studies were conducted under severe drought conditions. Higher concentrations of NH4, NO3 and TP in precipitation samples than those of rivers were found because of the high retention of nutrients in the landscape. In terms of loading, the bulk atmospheric deposition provided significant quantities of NH4, while TP, SRP and nitrates were predominantly from river flows. Specific loads of DIN (nitrate + ammonium) and TP in the catchment were slightly higher that the previously reported values for the catchment and are comparable to the other human-disturbed catchments of the world. HYPE model has successfully simulated streamflow (1961-1999), DIN and TP (1989-1999). For simulations of streamflow NSE values = 0.7 in four out of the nine sites (at a monthly time-step) and NSE > 0 in eight out of nine sites (at a daily time-step). Major floods and drought events were represented very well in the model, with a general over-simulation of baseflow events. The water balance was captured well at calibration sites with over-simulation of streamflow on the Lions River (PBIAS=28%) and their under-simulation in outlet sub-catchments (PBIAS < 0). This is ascribed to the simplification of some processes in the model i.e. evapotranspiration, water release, water abstraction and inter-basin transfer. There has been good fit between the simulations and observations of TP and streamflow with a lagging of the observed values. However, mismatches were noted for DIN. Evaluation of seasonal distribution of DIN suggested that denitrification, crop uptake of DIN and dilution were intensive during the period of rainfall and high temperatures in the catchment, while TP was highly mobilised during rainfall events, due to its strong binding with the soil. The information from this study highlighted the current state of LULC changes, the sub-catchments with the potentiality to export high levels of DIN and TP, the complexity of the relationship between LULC-water quality, the gaps in existing data collection programmes, the catchment responses to LULC changes and the usefulness of hydrological models which may apply beyond the upper reaches of the uMngeni Catchment

Developing meaningful water-energy-food-environment (WEFE) nexus indicators with stakeholders: A Lake Victoria case study

The Upper White Nile (UWN) basin plays a critical role in supporting essential ecosystem services and the livelihoods of millions of people in East Africa. The basin has been exposed to tremendous environmental pressures following high population growth, urbanisation, and land use change, all of which are compounded by the threats posed by climate change and insufficient financial and human resources. The water-energy-food-environment (WEFE) nexus provides a framework to assess solution options towards sustainable development by minimising the trade-offs between water, energy, and food resources. However, the majority of existing WEFE nexus indicators and tools tend to be developed without consideration of practitioners at the local level, thus constraining the practical application within real-world contexts. To try to address this gap and operationalise the WEFE nexus, we examined how local stakeholders frame the most pressing WEFE nexus challenges within the UWN basin, how these can be represented as indicators, and how existing WEFE nexus modelling tools could address this. The findings highlight the importance of declining water quality and aquatic ecosystem health as a result of deforestation and increasing agricultural intensity, with stakeholders expressing concerns for the uncertain impacts from climate change. Furthermore, a review of current WEFE nexus modelling tools reveals how they tend to be insufficient in addressing the most pressing environmental challenges within the basin, with a significant gap regarding the inclusion of water quality and aquatic ecosystem indicators. Subsequently, these findings are combined in order to guide the development of WEFE nexus indicators that have the potential to spatially model the trade-offs within the WEFE nexus in the UWN basin under climate change scenarios. This work provides an example of how incorporating local stakeholder's values and concerns can contribute to the development of meaningful indicators, that are fit-for-purpose and respond to the actual local needs

Sensitivity analysis for water quality monitoring frequency in the application of a water quality index for the uMngeni River and its tributaries, KwaZulu-Natal, South Africa

Water quality indices are commonly used to provide summary information from water quality monitoring programmes to stakeholders. However, declining funding and changing mandates often result in reduced monitoring frequencies which could affect the accuracy of information provided. Thus, this study aimed to assess the effect of water sampling frequency on water quality index reporting using the the upper uMngeni catchment as a study site. A 28-year time series of water quality data from 11 sampling stations was assessed for pH, electrical conductivity, temperature, turbidity, total suspended solids, Escherichia coli counts, NH4-N, NO3-N, PO4-P and total phosphorus. Statistical packages were used to process the data and water quality indices (WQIs) for eutrophication and recreational water were calculated and their sensitivity to input parameters analysed. It was found that the higher the monitoring frequency, the lower the WQI calculated at all sites. This suggests that water quality, due to a declining monitoring frequency, is poorer than reported in the uMngeni catchment. The findings showed that Escherichia coli and turbidity are the most influential variables affecting the recreational and eutrophication WQIs, respectively. Although WQIs are considered a useful tool for monitoring the changes in water quality across space and over time in the uMngeni Catchment, their use should complement, and not substitute for, other, more comprehensive, water quality management tools

Spatio-temporal analysis of drought and return periods over the East African region using Standardized Precipitation Index from 1920 to 2016

© 2020 Elsevier B.V. East African region is susceptible to drought due to high variation in monthly precipitation. Studying drought at regional scale is vital since droughts are considered a ‘creeping’ disaster by nature with devasting and extended impact often requiring long periods to reverse the recorded damages. This study assessed drought exceedance and return years over East Africa from 1920 to 2016 using Climate Research Unit (CRU) precipitation data records. Meteorological drought, where precipitation is the central quantity of interest, was adopted in the work. Standardize Precipitation Index (SPI) was used to study long term meteorological droughts and also to assess drought magnitude, frequency, exceedance probability and return years using Joint Probability Density Function (JPDF). Also, Mann-Kendall trend analysis was applied to precipitation and SPI to investigate the trend changes. Results showed that years with high drought magnitude ranged from 1920−22, 1926−29, 1942−46 and 1947−51 with values corresponding to 2.2, 3.2, 3.4 and 2.6, respectively while years with low drought magnitude ranged from 1930−31, 1988−89 and 2001−02 with values as 0.2, 0.12 and 0.15, respectively. The longest droughts occurred from 1926−29, 1937−41, 1942−46, 1947−51, 1952−56, and 1958−61 with values in years as 3, 4, 4, 4, 4, and 3 years, respectively, while the shortest droughts occurred in time period of 1 year and ranged from 1930−31, 1964−65, 1979−80, 1981−82, 1983−84, 1988−89, 1991−92, 1993−94, 1996−97 and 2001−02. Also, it was demonstrated that probability of drought occurrence is high when severity is low and such droughts occur at short time intervals and not all severest drought took longer periods. The SPI trends indicate high positive (negative) pixels above (below) the zero-trend mark, indicating that drought prevails in both low and high elevation areas up to 2000 m. There was no direct link between ENSO and drought but arguably the association of drought in most El Niño and La Niña years suggests that the impact of ENSO cannot be ruled out since peak ENSO events occur during October to March periods which coincides with the short (SON) and long (MAM) rainy seasons of East Africa. The study is particularly relevant in being able to depict continuous and synoptic drought condition all over East Africa, providing vital information to farmers and policy makers, using very cost-effective method

Balancing nutrient inputs to Lake Kivu

The primary production in meromictic Lake Kivu is sustained by external nutrient inputs and by internal loading due to upwelling caused by sub-aquatic sources. We present here the results of external loading of phosphorus (P), nitrogen (N) and silica (Si) by rivers and atmospheric deposition measured from 2006 to 2008. These external inputs are compared to internal loading. The input of soluble-reactive P (SRP), supplied in equal parts from rivers and atmospheric deposition, adds up to 230 t P yr(-1), 20 times less than total P load. Ammonium (mainly via rainwater) and nitrate (mainly via rivers) are primary sources of the dissolved N load (5400 t N yr(-1)), with both species contributing similar to 50%. Dissolved Si input (40,000 t Si yr(-1)) is unique in that only similar to 60% enters by rivers, while the remaining similar to 40% comes from sub-aquatic sources and atmospheric deposition is negligible. Based oil the molar nutrient ratios, we identify P as the limiting factor for algae production. Despite the strong anthropogenic impact on the catchment and the high particle erosion (74 t km(-2) yr(-1)), the area-specific nutrient mobilization is rather low. The external nutrient input is therefore not the cause for the reported increase of methane production in the last decades. External loading to the epilimnion plays a lesser role for all three nutrients (similar to 10% for SRP, similar to 25% for dissolved N and similar to 45% for dissolved Si), as compared to the lake-internal loading by upwelling (90%, 75% and 55%, respectively). Lake Kivu, therefore, is similar to other East African large lakes in that the internal loading exceeds the external loading. Despite the substantial uncertainty of the load estimates of up to 50%, we can conclude that the observed nutrient input is consistent with the primary production of 260 g C m(-2) yr(-1) recently measured by Sarmento et al. (2006) and also consistent with the lake-internal fluxes established by Pasche et al. (in press). (C) 2009 Elsevier Inc. All rights reserved