Comparison of stochastic streamflow generators and the use thereof within the water resources yield model and MIKE Hydro Basin

Maass, Lourens Francois (2017-12)

Thesis (MEng)--Stellenbosch University, 2017.

Thesis

ENGLISH ABSTRACT: The development and improvement of hydrological simulation software models is a continuous process. These software models, together with hydrological stochastic data generators enhances the ability to analyse a hydrological system and determine its reliability. Many different stochastic generators exist, but the two that are of interest in this research are monthly streamflow generators, namely STOMSA and SAMS. STOMSA is a stochastic streamflow generator developed for the Department of Water and Sanitation of South Africa, while SAMS is a stochastic streamflow generator developed in the United States of America. Both these generators are able to generate satisfying stochastic streamflow data, with the only concern being a high variance between the average annual streamflows of the different stochastic sequences generated by SAMS. Over time stochastic data generators became part of the hydrological analysis process. This led to the incorporation of stochastic data generators into hydrological simulation models. As is the case for stochastic streamflow generators many different hydrological simulation models are available, but the two that are of interest in this research are the WRYM and MIKE Hydro Basin. The WRYM is the hydrological simulation software model used by the Department of Water and Sanitation of South Africa. The model is used to do hydrological yield analyses for hydrological systems in South Africa. MIKE Hydro Basin is a hydrological simulation software model developed by the Danish Hydraulic Institute (DHI). The WRYM is able to do automated historical yield analyses and can calculate the historical firm yield of a hydrological system accurately. The WRYM also uses STOMSA as a built-in stochastic streamflow generator and uses the data generated by STOMSA to do a reliability of supply analysis for a hydrological system. MIKE Hydro Basin, however, is not able to generate stochastic streamflow data or do system yield analyses. It is used to simulate hydrological systems. When the practicality of the two models is considered, it is argued that MIKE Hydro Basin is more user-friendly than the WRYM. The WRYM is very technical and difficult to use without proper training or assistance. It should also be noted that the WRYM, , makes possible calculation errors in the reliability of supply analysis and results should be used with caution.

AFRIKAANSE OPSOMMING: Die ontwikkeling en verbetering van hidrologiese simulasie sagteware modelle is ’n deurlopende proses. Hierdie sagteware modelle tesame met hidrologiese stogastiese data generators dra by tot die vermo¨e om ’n hidrologiese stelsel te ontleed en die betroubaarheid vir die stelsel om water te lewer, te bepaal. Daar bestaan ’n wye reeks verskillende stogastiese generators, maar die twee wat van belang is in hierdie navorsing is die maandelikse stroomvloei generators, naamlik STOMSA en SAMS. STOMSA is ’n stogastiese stroomvloei generator wat ontwikkel is vir die Departement vanWater en Sanitasie van Suid-Afrika, terwyl SAMS ontwikkel is in die Verenigde State van Amerika. Beide hierdie generators is in staat om bevredigende stogastiese stroomvloei data te genereer. Die enigste bekommernis is ’n ho¨e afwyking tussen die gemiddelde jaarlikse stroomvloeie van die verskillende stogastiese reekse wat deur SAMS gegenereer is. Stogastiese data generators het met die verloop van tyd deel geword van die hidrologiese ontledingsproses. Dit het gelei tot die insluiting van stogastiese data generators in hidrologiese simulasie modelle. Daar bestaan ’n wye reeks verskillende hidrologiese simulasie modelle, maar die twee wat van belang is in hierdie navorsing is die WRYM en Mike Hydro Basin. Die WRYM is ’n hidrologiese simulasie sagteware model wat gebruik word deur die Departement van Water en Sanitasie van Suid-Afrika. Die model word gebruik om hidrologiese leweringsontledings vir hidrologiese stelsels in Suid-Afrika te doen, terwyl MIKE Hydro Basin ontwikkel is deur die Danish Hydraulic Institute (DHI). Die WRYM is in staat om die historiese veilige lewering van ’n hidrologiese stelsel akkuraat te bereken. Die WRYM gebruik ook STOMSA as ’n interne stogastiese stroomvloei generator, en gebruik die gegenereerde data om ’n betroubaarheidsontleding vir ’n hidrologiese stelsel te doen. MIKE Hydro Basin is egter nie in staat om stogastiese stroomvloei data te genereer of die lewerings van ’n stelsel te ontleed nie, en word slegs gebruik om hidrologiese stelsels te simuleer. Wanneer die praktiese funksionaliteit van die twee modelle oorweeg word, blyk dit dat MIKE Hydro Basin meer gebruikersvriendelik is as die WRYM. Die WRYM is baie tegnies en moeilik om te gebruik sonder behoorlike opleiding. Dit moet ook in ag geneem word dat die WRYM moontleke foute maak met die berekening van die betroubaarheid van ’n stelsel en resultate moet dus versigtig hanteer word.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/102670
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