Uncertain hydrological modelling: application of the Pitman model in the Great Ruaha River basin, Tanzania

2015

Hydrological Processes

Abstract:During the four decades of Keith Beven's career there have been many developments in the science of hydrological modelling. Some have focused on the links between hydrological process understanding and the structure and complexity of hydrological models, others on the related issues of modelling uncertainty. The southern Africa region continues to be generally less well endowed with the resources required to contribute to these research developments, but they are critical for successful water resources management decision-making in data scarce areas, and go beyond academic interest. Consequently, the focus in the region has been on adding a local context to northern hemisphere research as well as trying to put it into practice. The challenge in southern Africa has always been to extrapolate from published research ideas and decide how they can be effectively used in larger scale practical applications in data-poor areas. The paper examines the issues of model complexity, links with process understanding and the broad topic of model uncertainty estimation in the context of data scarce areas and how the science questions relate to improvements in water resources decision making. The conclusions suggest that the southern African region has benefited a great deal from several decades of northern hemisphere research (including those by Beven) and that some values have been added through the focus on practical implementation. The region should also embrace the opportunities presented by the need to link realistic uncertainty estimates with risk-based water resources decision-making, thereby contributing to the international debate on this important topic.

Section: Modelling Uncertaintymentioning

confidence: 99%

Hydrological modelling, process understanding and uncertainty in a southern African context: lessons from the northern hemisphere

2015

Hydrological Processes

“…There is also an option to include several ranges of output constraints (mean monthly stream flow and recharge, three % points of the flow duration curve and % of time of zero flows) that are used to limit the output ensembles to those that are behavioural relative to the input constraint boundaries. In this case the model is typically run 100 000 times or until 2 000 behavioural parameter sets are found (Hughes 2013, Tumbo andHughes 2014). Model assessments are based on four objective functions;…”

Section: And Uncertaintiesmentioning

confidence: 99%

Surface water–groundwater interactions in catchment scale water resources assessments—understanding and hypothesis testing with a hydrological model

Tanner

Hydrological Sciences Journal

2015

Self Cite

Interactions between surface and groundwater systems in fractured rock environments, covering large parts of southern Africa, are poorly understood, such that modelling the different water balance components is highly uncertain. Some of these uncertainties are highlighted and attempts are made to resolve them using hypothesis testing with an uncertain ensemble version of the widely used Pitman hydrological model that includes relevant groundwater components. Five study catchments are used to represent many of the major uncertainties in linking surface and groundwater resources, including the relative importance of deep unsaturated zone drainage, the balance between recharge and losses through riparian evapotranspiration and channel transmission losses.The study demonstrates that some uncertainties can be reduced, but this also involves making a number of assumptions about other aspects of a catchment water balance that can be conceptually supported but not completely validated with available data. The remaining uncertainties need to be resolved through improved process quantification and understanding, possibly using environmental tracers.A c c e p t e d M a n u s c r i p t 2 INTRODUCTIONThe interactions between surface water and groundwater (SW/GW) systems remain poorly understood in many catchments throughout the world and yet they are essential to effectively managing the quantity and quality of water resources. It has been well documented that these systems interact in a range of geological, topographical and climatic settings and that many surface water features, such as rivers, lakes, dams and wetlands will have varying degrees of connection with groundwater systems (Ivkovic 2009, Fleckenstein et al. 2010, Haria et al. 2013). There are a number of comprehensive reviews of the current understanding of the physical interactions that occur between groundwater and surface water systems (Winter 1999, Sophocleous 2002, Brunner et al. 2009, Unland et al. 2013, Lamontagne et al. 2014). Within South Africa the focus has tended to be more on management issues surrounding the interactions between surface and groundwater (Xu et al. 2002, Parsons 2004, Le Maitre and Colvin 2008, Hughes 2010, Levy and Xu 2011), while some contributions have focused on the physical processes behind the interactions, albeit through relatively small scale studies (Hughes and Sami 1992, Lorentz et al. 2004, Roets et al. 2008, Wenningger et al. 2008, Kelbe and Germishuyse, 2010). One of the limiting factorsin trying to understand and quantify interaction processes at scales appropriate for regional water resources management is the lack of direct data that is available to quantify almost all of the individual processes, from recharge, through vertical drainage, to the interactions between aquifers and river channels. This is particularly true for fractured rock aquifers that are highly heterogeneous and are the dominant aquifer type in southern Africa. A further limitation is the general lack of availability (for desktop studies at the catchm...

“…Given a basin setup that includes 30 sub-basins and a time series length of 85 years, the normal run time for the second step is approximately 4 h on a standard PC. Tristam et al (2014) demonstrated that this time could be drastically reduced by using graphics processers and re-coded software, while additional re-coding is underway to make use of the multiple processing cores on standard modern PCs. Initial trials suggest improvements in speed of about 3.5 times.…”

Section: Introductionmentioning

confidence: 99%

“…Tumbo and Hughes (2015) discuss some of the practical issues with setting up an uncertainty model of this type. These include ensuring that the constraints are compatible with each other, an example being to ensure that the groundwater recharge and low flow (Q 10 ) constraints are compatible.…”

Section: Introductionmentioning

confidence: 99%

“…One problem that emerged in large basins with multiple sub-basins was that downstream ensembles that fall within the constraint bounds could be made up of combinations of upstream ensembles that are both within and outside the constraint bounds. Tumbo and Hughes (2015) present a revised approach for the 86 000 km 2 Great Ruaha River basin in Tanzania. The first step uses regional or local (i.e.…”

Section: Introductionmentioning

confidence: 99%

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Scientific and practical tools for dealing with water resource estimations for the future

2015

Proc. IAHS

Abstract. Future flow regimes will be different to today and imperfect knowledge of present and future climate variations, rainfall-runoff processes and anthropogenic impacts make them highly uncertain. Future water resources decisions will rely on practical and appropriate simulation tools that are sensitive to changes, can assimilate different types of change information and flexible enough to accommodate improvements in understanding of change. They need to include representations of uncertainty and generate information appropriate for uncertain decision-making. This paper presents some examples of the tools that have been developed to address these issues in the southern Africa region. The examples include uncertainty in present day simulations due to lack of understanding and data, using climate change projection data from multiple climate models and future catchment responses due to both climate and development effects. The conclusions are that the tools and models are largely available and what we need is more reliable forcing and model evlaution information as well as methods of making decisions with such inevitably uncertain information.