Abstract
Study regionThe Rufiji basin, East Africa. Study focusRapid advances in global hydrological model (GHM) resolution, model features, and in situ and remotely sensed datasets are driving progress towards local relevance and application. Despite their increasing use, however, evaluation of local hydrological performance of GHMs is rare. In this paper, we examine the performance of a well-known GHM (LPJmL, recently modified to ∼9 km resolution) with and without modest steps to regionalise the model. We consider the Rufiji river basin, an economically important medium-size basin in eastern Africa. New hydrological insights for the regionOur results indicate that the unmodified GHM does provide a reasonable first approximation of spatial variability in mean flow conditions, but scores rather poorly on seasonal and inter-annual variability. For the model to achieve levels of performance indicators comparable with bespoke modelling, modifications to model inputs, additional runoff delay and wetland parameterization were required. The largest improvements are associated with adjustments in precipitation and enhanced runoff delay. With the modified version, as a proof of concept, we show that a well-known drying trend in a major tributary of the Rufiji can be explained by implementing irrigation abstractions in the model. Overall, the results suggest that with limited and fairly simple modification GHMs can be regionalised to allow their use for scenario testing and further exploration of key local processes in basins with limited observational data.
Highlights
Global hydrological and land surface models are undergoing rapid development – ever greater computational capacity and data storage, further supported by developments in remote sensing, the availability of gridded observation datasets and meteorological forcing data, have allowed model development at higher spatial resolution covering larger areas (e.g. Flörke et al, 2013; Sutanudjaja et al, 2017)
As global hydrological model (GHM) increase in spatial resolution, there is more potential to interpret their results at basin and subbasin scales, moving beyond continental and regional scale descriptions of water scarcity and climate change impacts to sectoral issues like national food security or hydropower potential, at levels of detail relevant for management applications
CHIRPS grid cell totals were compared with observed monthly precipitation data of 19 rain gauges obtained from the Rufiji Basin Water Board (RBWB) and the Climatic Research Unit (CRU) to obtain a first-order approximation of any bias
Summary
Global hydrological and land surface models (further GHMs) are undergoing rapid development – ever greater computational capacity and data storage, further supported by developments in remote sensing, the availability of gridded observation datasets and meteorological forcing data, have allowed model development at higher spatial resolution covering larger areas (e.g. Flörke et al, 2013; Sutanudjaja et al, 2017). While there is still debate on the importance of resolution over epistemic uncertainties (Beven and Cloke, 2012; Bierkens et al, 2015; Wood et al, 2012), both proponents and sceptics agree that moving to higher resolutions will provide better opportunity to compare multi-model output against local observations and knowledge of stakeholders (Beven and Cloke, 2012; Bierkens et al, 2015) Despite their increasing use and many high-impact publications based on GHMs (Elliott et al, 2014; Gleeson et al, 2012; Schewe et al, 2014) they are generally not extensively tested for hydrological performance. Trigg et al (2016) found in a comparison of flood hazard maps for Africa derived from six global models (recognising their limited validation) significant variations between flood hazard magnitudes, with important implications for model reliability and interpretation of results
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