Gully dynamics evolution under environmental change pressures
| dc.contributor.advisor | De Clercq, W. P. | en_ZA |
| dc.contributor.advisor | Van De Wiel, Marco | en_ZA |
| dc.contributor.advisor | Fried, Jana | en_ZA |
| dc.contributor.advisor | Mashimbye, Eric | en_ZA |
| dc.contributor.author | Olivier, George | en_ZA |
| dc.contributor.other | Stellenbosch University. Faculty of Science. Dept. of Earth Sciences. | en_ZA |
| dc.date.accessioned | 2024-03-01T10:28:02Z | |
| dc.date.accessioned | 2024-04-26T21:56:55Z | |
| dc.date.available | 2024-03-01T10:28:02Z | |
| dc.date.available | 2024-04-26T21:56:55Z | |
| dc.date.issued | 2024-03 | |
| dc.description | Thesis (PhD)--Stellenbosch University, 2024. | en_ZA |
| dc.description.abstract | ENGLISH ABSTRACT: Gully erosion is a severe land degradation process, primarily impacting land resources on-site and water resources off-site. When active in a catchment, it can be the dominant driver of soil loss, causing significant environmental and socio-economic consequences. However, other soil erosion mechanisms remain at the forefront of research, which contributed to our inability to assess gully erosion on a catchment to regional scale. The current capability to model gully erosion on larger geographic extents remains limited due to the complexity of interactions of control factors and various sub-processes driving gully expansion. In this study, an approach to apply local case studies to inform on regional gully severity is introduced to address modelling shortcomings, and an initial scaled framework is provided, which could be implemented for future regional scale investigations and monitoring. South Africa has a long history of erosion problems and has been considered an area with high gully incidence. The “hotspot” perception, coupled with the diverse climatic and geo-environmental attributes exhibited in South Africa, motivated the use as the focal region for this study. Local case study sites were used to extract physiographic properties and gully severity to produce a susceptibility map for South Africa. Additional local sites were selected across the E-W climate gradient of South Africa to assess gully severity and to isolate climate and land use controls of gully erosion to provide clues on how environmental change may influence future gully erosion. The findings from the susceptibility map, which used secondary data from the literature, converged with the findings from primary data derived from sites located across the climate gradient of South Africa. Gully erosion severity increases eastwards towards the Grassland biome, in which gullying is most severe. Here, gully erosion resulted in soil losses of up to 17 t ha⁻¹ y⁻¹, which exceeds the baseline limit (27 times more) and is almost twice the sustainable limit calculated for South Africa when the upper thresholds for both these limits are used. Perceptions from landowners/ -users/ and -managers mostly align with gully concerns from the field sites, showing that their appraisals are concurrent with local gully severity. Remediation efforts are ongoing at several sites; however, measures focus on gully headcuts and do not consider vegetation establishment. Vegetation is considered critical, especially for long-term success rates of mitigation, and could be a reason for the lack of successful mitigation. The poor success rate is also disconcerting, as climate change will likely exacerbate gully erosion in South Africa. Although climate change is predicted to increase gully erosion due to larger storm magnitudes, the data presented here indicates that rainfall intensity is likely to play a secondary role in exacerbating gully erosion. Rainfall variability may be the principal driver of gully erosion. If climate change increases the frequency of El Niño Southern Oscillation events, gully erosion severity may increase and even reactivate previously stabilised gullies due to more intense rainfalls after periodic droughts. Continuous assessment and monitoring of gully extents are crucial to assessing where gullies are of concern and whether there is a change in severity. Manually digitising gullies or solely relying on fieldwork will not sufficiently address a need for monitoring via temporal data. Semi-automated detection strategies which are scaleable and transferrable would enable the extraction of gully dimensions unbiasedly and would allow to quantitively assess gully expansion (or contraction) by subtracting polygon- or raster-based output. A semi-automated approach that uses gully morphology to extract gully dimensions is developed and tested with datasets from South Africa, Namibia, Spain, and Australia. Initial assessment shows positive results, accurately predicting > 75.4% of the gullied area when scaling between small gullies (planimetric area of 1619 m²) to large gullies (planimetric area of 70246 m²). Regarding transferability to benchmark areas where other land uses were practised and where different spatial resolution data were used as input, the variance between 1.4% and 14.8% was determined, with producer accuracies above 84.5% and 70.6%. The semi-automated method has some shortcomings, with the requirement for manually digitising gully headcuts being the most pertinent. As a framework, regional assessments and monitoring should implement a scaled approach. The initial step should produce a susceptibility map using key variables associated with gullying. Following that, more computationally intensive detection strategies could be implemented, constrained to areas of most concern defined by susceptibility. Lastly, representative field sites can be identified from the detected gullies, where primary data can be retrieved to quantify gully processes, severity, and implications. Continued work is required to refine this framework, for example, refining semi-automated approaches to increase accuracy and increasing localised field sites in different geo-environments to improve trend analysis and better our understanding of how various controls interact to steer gully evolution. Lastly, this new information should yield data that can be used to build and calibrate models; such gully evolution modelling currently needs to be improved and is pivotal to further our understanding of how gully networks will react to climate and land-use changes. | en_ZA |
| dc.description.abstract | AFRIKAANSE OPSOMMING: Donga erosie lei tot ernsitge grond verlies, en het veral ‘n impak op grond hulpbronne waar erosie plaasvind, asook water hulpbronne elders in die opvangsgebied. In opvangsgebiede waar donga erosie aktief is, kan dit lei tot ernstige omgewings- en sosio-ekonomiese gevolge. Ander vorms van grond erosie bly egter aan die voorpunt van navorsing, wat ‘n rol gespeel het in die huidige onvermoë om donga erosie op groter skaal te analsieer. Ons vermoë om donga erosie suksesvol te modelleer is ook tans beperk, meerendeels as gevolg van komplekse interaksie tussen faktore wat dit dryf, asook verskeie sub-prosesse wat aanleiding gee tot die evolusie daarvan. Plaaslike gevallestudies word gebruik op ‘n streekskaal, om aan die terkortkominge van modelering, inligting te verskaf oor verspreiding van donga ersosie. ’n Initiële raamwerk word ook aanbeveel vir toekomstiges analises en monitering van donga erosie op streekskaal. Suid-Afrika het 'n lang geskiedenis van probleme wat geassosieer word met erosie, en word beskou as ‘n area met n hoë voorkoms van dongas. Hierdie “hotspot”-persepsie, tesame met die diverse klimaat- en geo- omgewingskenmerke wat in Suid-Afrika voorkom, was die motivering om dit as die fokus area te gebruik vir hierdie studie. Plaaslike gevallestudies was gebruik om die fisiografiese eienskappe en die graad van donga erosie te kombineer om ‘n donga vatbaarheidskaart vir Suid-Afrika te produseer. Bykomende plaaslike gevallestudies was ook gekies langs die Oos-Wes klimaatgradiënt van Suid-Afrika om die erns van donga erosie in Suid-Afrika te ondersoek. Die areas was strategies gekies om sodoende klimaat en landgebruik faktore wat dongas dryf te isoleer, om meer te leer van moontlike toekomstige veranderinge rakende klimaats- en landgebruiks-veranderinge. Bevindinge van die vatbaarheidskaart, wat sekondêre inligting gebruik, en die plaaslike gevallestudies, wat primêre inligting produseer het, stem ooreen met waar donga erosie die grootste probleem is. Die intensiteitsgraad van dongas neem ooswaarts toe in die rigting van die Grasveld bioom. Hier lei donga erosie tot 17 t ha⁻¹ j⁻¹, wat die basisvlak oorskry (27 keer meer) en byna twee keer die volhoubare limiet is wat vir Suid-Afrika bereken is wanneer die boonste drempels vir beide hierdie limiete gebruik word. Persepsies van grondeienaars, -gebruikers, en -bestuurders, stem meestal ooreen met wat in die veld bepaal is, wat n aaanduiding is dat hul persepsies in lyn plaaslike erosie vlakke. Remediëringspogings is aan die gang op verskeie gevallestudie areas; strategie fokus egter op die initlële inkloof area waar die donga begin. Strategië fokus op fisiese grondwerk en neem nie plantegroei in ag nie. Plantegroei word as krities beskou, veral vir suksesvolle langtermyn rehabilitasie en kan 'n rede wees vir die gebrek aan suksesvolle remediering. Die swak sukseskoers is ook problematies, veral omdat klimaatsverandering waarskynlik donga erosie in Suid-Afrika sal vererger. Alhoewel klimaatsverandering voorspellings toon dat dongas erosie sal verhoog as gevolg van groter stormsterktes, dui die data wat hier aangebied word dat reënvalintensiteit waarskynlik 'n sekondêre rol sal speel in die verergering van donga erosie. Die wisslevalligheid van reënval sal waarskynlik die hoofdrywer van donga erosie wees. As klimaatsverandering die frekwensie van El Niño Suidelike Ossillasie-gebeurtenisse verhoog, kan die intensiteit van donga erosie toeneem en selfs stabiele dongas heraktiveer as gevolg van meer intense reënval na periodieke droogtes. Deurlopende assessering en monitering van dongas is krities om te bepaal waar donga erosie begin toeneem. Om dongas met per hand te teken vanaf fotos of uitsluitlik op veldwerk staat te maak, sal nie monitering van dongas op grootskaal kan aanspreek nie. Semi-outomatiese strategiee om dongas te identifiseer word benodig, verkieslik metodes wat op verskillende skale asook in kontrasterende omgewings toegepas kan word. Sulke metodes sal ons in staat stel om donga afmetings op n onvooroordeelde manier te doen, en sodoende donga uitbreiding (of inkrimping) kwantitief te evalueer. Semi-outomatiese benadering word hier ontwikkel wat op die morfologie van dongas gebaseer is. Die metode is in Suid-Afrika ontwikkel, en getoets op dongas van verskeie skale en omgewings in Suid-Afrika, Namibië, Spanje en Australië. Aanvanklike assessering toon positiewe resultate, en voorspel dongas met groottes tussen klein- (planimetriese oppervlakte van 1619 m²) en groot- skaal (planimetriese oppervlakte van 70246 m²) met akkuraatheid wat 75.4% oorskry. Wanneer die metode getoets word op dongas met verskillende omgewingskarakteristieke, en vergelyk word met metodes wat spesifiek in daardie areas onwikkel was, is ‘n variansie tussen 1.4% en 14.8% bepaal. Die semi-outomatiese metode het 'n paar tekortkominge, met die mees beduidenste een die handmatige identifiesering van donga se inkerwingspunt waar die donga begin. ‘n Raamwerk om dongas op n streekskaal te evalueer en monitor word voorgestel. Die raamwerk se aanvanklike stap bestaan uit die produsering van n vatbaarheidskaart wat faktore wat dongas dryf te gebruik as insette. Daarna kan ‘n semi-automaties strategie geimplementeer word, wat tien teen een meer rekenaar intensiewe prosesse sal bevat, om dongas te karteer. Die semi-automatiese strategie kan beperk word tot hoë donga vatbaarheidsareas. Laastens kan verteenwoordigende plaaslike gevallestudies identifiseer word vanaf die gekarteerde dongas, waar primêre data ingewin kan word rakende intensiteit, prosesse, en gevolge van donga erosie. Verdere werk word vereis om die stappe binne hierdie raamwerk te verfyn, bv., die verfyning van semi-outomatiese benaderings om akkuraatheid te verhoog en om meer plaaslike gevalle studies te identifissser sodat n beter verspreiding van donga voorkoms in verkeie geo-omgewingsfaktore bepaal kan word. Hierdie verspreiding kan gebruik word om beter tendense vas te stel, asook hoe om die verskeie kombinasies van dryf faktore van dongas, die evolusie daarvan beinvloed. Laastens, kan die inligting wat ingewin word, gebruik word vir die ontwikkeling van modelle, asook die kalibrasie van moderlingsbevindinge. Met hierdie modelle kan ons begrip verbeter rakende hoe klimaat- en land gebruiks-veranderinge, donga evolusie kan beinvloed. | af_ZA |
| dc.description.version | Doctorate | en_ZA |
| dc.format.extent | xxvii, 322 pages : illustrations (some color), maps | en_ZA |
| dc.identifier.uri | https://scholar.sun.ac.za/handle/10019.1/130557 | |
| dc.language.iso | en_ZA | en_ZA |
| dc.language.iso | en_ZA | en_ZA |
| dc.publisher | Stellenbosch : Stellenbosch University | en_ZA |
| dc.rights.holder | Stellenbosch University | en_ZA |
| dc.subject.lcsh | Gully erosion | en_ZA |
| dc.subject.lcsh | Land degradation -- Environmental aspects | en_ZA |
| dc.subject.lcsh | Soil erosion prediction | en_ZA |
| dc.subject.lcsh | Soil erosion -- Climatic factors | en_ZA |
| dc.subject.lcsh | Climatic changes | en_ZA |
| dc.subject.lcsh | Global environmental change | en_ZA |
| dc.subject.lcsh | El Nino Current -- Climatic factors | en_ZA |
| dc.subject.lcsh | Southern oscillation -- Climatic factors | en_ZA |
| dc.subject.name | UCTD | en_ZA |
| dc.title | Gully dynamics evolution under environmental change pressures | en_ZA |
| dc.type | Thesis | en_ZA |
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