Suspended Sediment Load Estimation in a Severely Eroded and Data Poor Catchment

Soil erosion rates are high in many parts of Southern Africa, and are likely to rise because of climate change. Suspended sediment loads (SSL) and yields (SSY) are used to measure and benchmark soil erosion and/or sediment transport rates and determine trajectories of change. Some modelled SSY are available for Southern African catchments, but there is a dearth of contemporary observed data. Northern hemisphere approaches to suspended sediment measurement and the calculation of loads and yields are often unsuited to Southern Africa: locally appropriate methods are required. The manual, flood-focused suspended sediment sampling programme that we implemented in the eroded and data-scarce Tsitsa River catchment (Eastern Cape, South Africa) monitored four sub-catchments from December 2015 to June 2019 at a sub-daily timestep. We used a discharge-weighted interpolation SSL estimator, investigating the effects of catchment area, hydrological regime, and sampling strategy on SSL, SSY, and variability, comparing our estimates with modelled results. Discharge increased with catchment area whilst flashiness (expressed by the Richards-Baker Flashiness Index) mainly decreased, and was similar to that of North American catchments. The sampling frequency required to maintain precision was inversely related to catchment area. Mean annual SSL ranged from 18 121 t year−1 in the 204 km2 Gqukunqa River catchment to 984 267 t year−1 in the 1452 km2 Inxu River catchment. Mean annual SSY ranged from 61 t km2 year−1 in the 432 km2 Pot River catchment to 678 t km2 year−1 in the Inxu River catchment. Data stratification to limit sampling to wet-season flows did not significantly impact SSL estimates, but year-round sampling is required to maintain the citizen-technician sampling network through regular income. Modelled SSY estimates were higher than our measured estimates. Our approach to suspended sediment sampling, load and yield estimation is robust, sustainable, precise, and can be adapted for similar, remote catchments

MIKE-SHE integrated groundwater and surface water model used to simulate scenario hydrology for input to DRIFT-ARID: the Mokolo River case study

A fully integrated, physically-based MIKE SHE/MIKE11 model was developed for the Mokolo River basin flow system to simulate key hydraulic and hydrologic indicator inputs to the Downstream Response to Imposed Flow Transformation for Arid Rivers (DRIFT-ARID) decision support system (DSS). The DRIFT-ARID tool is used in this study to define environmental water requirements (EWR) for non-perennial river flow systems in South Africa to facilitate ecosystembased management of water resources as required by the National Water Act (Act No. 36 of 1998). Fifty years of distributed daily climate data (1950 to 2000) were used to calibrate the model against decades of daily discharge data at various gauges, measurements of Mokolo Dam stage levels, and one-time groundwater level measurements at hundreds of wells throughout the basin. Though the calibrated model captures much of the seasonal and post-event stream discharge response characteristics, lack of sub-daily climate and stream discharge data limits the ability to calibrate the model to event-level system response (i.e. peak flows). In addition, lack of basic subsurface hydrogeologic characterisation and transient groundwater level data limits the ability to calibrate the groundwater flow model, and therefore baseflow response, to a high level. Despite these limitations, the calibrated model was used to simulate changes in hydrologic and hydraulic indicators at five study sites within the basin for five 50-year land-use change scenarios, including a present-day (with dam), natural conditions (no development/irrigation), and conversion of present-day irrigation to game farm, mine/city expansion, and a combination of the last two. Challenges and recommendations for simulating the range of non-perennial systems are presented.Keywords: hydrology, non-perennial, MIKE SHE, integrated surface and groundwater modellin

DRIFT-ARID: A method for assessing environmental water requirements (EWRs) for non-perennial rivers

Environmental water requirement (EWR) assessment methods, for ascertaining how much water should be retained in rivers to sustain ecological functioning and desired levels of biodiversity, have mostly been developed for perennial rivers. Despite non-perennial rivers comprising about 30–50% of the world’s freshwater systems, data on their hydrology, biota and ecological functioning are sparse. Current EWR assessments require hydrological and other data that may not be available for such rivers and some adaptation in the methods used seems necessary. DRIFT is an EWR method for perennial (or near-perennial) rivers that has been developed in South Africa over the past two decades and is now widely applied nationally and internationally. When applied to the semi-permanent Mokolo River, challenges particular to, or accentuated by, non-perennial rivers included the reliable simulation of hydrological data, the extent of acceptable extrapolation of data, difficulties in predicting surface-water connectivity along the river, and the location and resilience of pools, as well as whether it was possible to identify a reference (natural) condition. DRIFT-ARID, reported on here, is an adaptation of the DRIFT approach to begin addressing these and other issues. It consists of 11 phases containing 29 activities.Keywords: EWR, non-perennial, DRIFT, DS

A Social-Ecological Systems Understanding of Drivers of Degradation in the Tsitsa River Catchment to Inform Sustainable Land Management

Understanding the interactions of the social and biophysical drivers of land degradation is crucial for developing adaptive management actions for future sustainability. A research-praxis project, the ‘Tsitsa Project’ (TP), applies a social-ecological systems (SES) approach where researchers, natural resource managers, and residents collaborate to support sustainable livelihoods and improved natural resource management for the degraded Tsitsa River Catchment (TRC) in South Africa. A system diagramming approach was coupled with findings from interviews, workshops, literature, and two conceptual frameworks. Data inputs were qualitatively integrated to provide a systemic snapshot of how the context-specific social and biophysical drivers are interlinked and how they interact, revealing multiple processes that operate simultaneously to cause and exacerbate land degradation. Physical and climatic variables, changes in land use and cover, and overgrazing were identified as key factors leading to degradation. Additionally, poverty and disempowerment were also important. While little can be done to influence the physical aspects (steep topography and duplex soils) and climatic variables (extreme rainfall and drought), carefully planned changes in land use and management could produce dual-benefits for improving landscape conditions and sustainable livelihoods. This analysis will inform integrated planning processes to monitor, avoid, reduce and reverse land degradation

DRIFT-ARID: Application of a method for environmental water requirements (EWRs) in a non-perennial river (Mokolo River) in South Africa

Methods developed to determine the amount of water required (EWR) to sustain ecosystem services in non-perennial rivers need a different approach to those used in perennial rivers. Current EWR methods were mostly developed for use in perennial rivers. Non-perennial rivers differ from perennial ones in terms of variability in flow, periods of no-flow and related habitat availability. A DRIFT-ARID method (an adaptation of the Downstream Response to Imposed Flow Transformation (DRIFT) method) was developed, tested and adjusted, using the semi-permanent Mokolo River. Field data from five study sites was collected from April to May 2010 by a multidisciplinary team. The results were used in a DRIFT-ARID Decision Support System (DSS) to determine the impact of five chosen development scenarios in the Mokolo River Catchment. An integrated groundwater–surface water MIKE-SHE hydrological model was used to simulate the hydrology of the chosen scenarios. Specific non-perennial river indicators such as onset of dry phase were identified and included in the DRIFT-ARID DSS. DRIFT-ARID has the potential to be used in non-perennial rivers and, once set up, can provide results for future scenarios. The method now needs to be tested on other non-perennial river types, especially episodic rivers where data are scarce or non-existent.Keywords: DRIFT-ARID, non-perennial, EWR, flow method, Mokolo Rive