Suitability of averaged outputs from multiple rainfall-runoff models for hydrological extremes: a case of River Kafu catchment in East Africa

Onyutha, Charles; Amollo, C. J.; Nyende, Jacob; Nakagiri, Anne

doi:10.1007/s42108-020-00075-4

Cited by 10 publications

(14 citation statements)

References 43 publications

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“…M8g, AWBM ranked third after SAC and Tank. In several past studies [36,81], AWBM exhibited superlative performances. On the other hand, SMAR exhibited unsatisfactory performance with NSE of 0.46, 0.28 and 0.44 for calibration, validation and entire period, respectively (Fig.…”

Section: Model Performance For the Calibration Validation And Entirementioning

confidence: 87%

“…However, in some studies, e.g. Onyutha et al [36], SMAR generally performed better than SAC and TANK models. This could be attributed to the varying spatial resolution of catchments such as the size, climate, geology, landscape and hydrological data [70,81].…”

Section: Model Performance For the Calibration Validation And Entirementioning

confidence: 90%

“…com/ site/ conyu tha/ tools-to-downl oad (accessed: 10 February 2021). These models were selected because they (1) are freely available online and (2) were found to be robust for rainfall-runoff modelling under various climatic conditions as demonstrated in several recent studies [27,36,[65][66][67][68][69].…”

Section: Rainfall-runoff Modellingmentioning

confidence: 99%

“…For instance, Grimaldi et al [32] applied the Continuous Simulation Model for Small Ungauged Basins (COSMO4SUB) to ungauged catchment and the results were comparable with the event-based approach. Similarly, several studies have reported superior performance of Artificial Neural Network (ANN) models [31, 33,34] Within Uganda (where the study area is located), several studies [35][36][37] have applied lumped conceptual hydrological models. However, it was noticeable that most studies applied a single hydrological model except for Onyutha et al [36] that compared the performance of seven lumped conceptual models in the simulation of daily River Kafu flows.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, several studies have reported superior performance of Artificial Neural Network (ANN) models [31, 33,34] Within Uganda (where the study area is located), several studies [35][36][37] have applied lumped conceptual hydrological models. However, it was noticeable that most studies applied a single hydrological model except for Onyutha et al [36] that compared the performance of seven lumped conceptual models in the simulation of daily River Kafu flows. However, this study was conducted in western Uganda and not in the eastern part of Uganda (where the study area is located).…”

Section: Introductionmentioning

confidence: 99%

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Performance of rainfall–runoff models in reproducing hydrological extremes: a case of the River Malaba sub-catchment

2021

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Daily River Malaba flows recorded from 1999 to 2016 were modelled using seven lumped conceptual rainfall–runoff models including AWBM, SACRAMENTO, TANK, IHACRES, SIMHYD, SMAR and HMSV. Optimal parameters of each model were obtained using an automatic calibration strategy. Mismatches between observed and modelled flows were assessed using a total of nine “goodness-of-fit” metrics. Capacity of the models to reproduce historical hydrological extremes was assessed through comparison of amplitude–duration–frequency (ADF) relationships or curves constructed based on observed and modelled flow quantiles. Generally, most of the hydrological models performed better for high than low flows. ADF curves of both high and low flows for various return periods from 5 to 100 years were well reproduced by AWBM, SAC, TANK and HMSV. ADF curves for high and low flows were poorly reproduced by SIMHYD and SMAR, respectively. Overall, AWBM performed slightly better than other models if both high and low flows are to be considered simultaneously. The deviations of these models were larger for high than low return periods. It was found that the choice of a “goodness-of-fit” metric affects how model performance can be judged. Results from this study also show that when focusing on hydrological extremes, uncertainty due to the choice of a particular model should be taken into consideration. Insights from this study provide relevant information for planning of risk-based water resources applications.

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Section: Model Performance For the Calibration Validation And Entirementioning

confidence: 87%

Section: Model Performance For the Calibration Validation And Entirementioning

confidence: 90%

Section: Rainfall-runoff Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Performance of rainfall–runoff models in reproducing hydrological extremes: a case of the River Malaba sub-catchment

2021

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Water availability trends across water management zones in Uganda

Onyutha

Asiimwe

Muhwezi

et al. 2021

Atmospheric Science Letters

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This study assessed trends in gridded (0.25 Â 0.25 ) Climate Forecast System Reanalysis (CFSR) precipitation, potential evapotranspiration (PET), and precipitation minus PET (PMP) across the four water management zones (WMZs) in Uganda including Kyoga, Victoria, Albert, and Upper Nile. The period considered was 1979-2013. Validation of CFSR datasets was conducted using precipitation observed at eight meteorological stations across the country.Observed precipitation trend direction was satisfactorily reproduced by CFSR data extracted at five out of eight stations. Negative (positive) values of longterm PMP mean were considered to indicate areas characterized by water scarcity (surplus). Areas with large positive PMP were confined to Lake Victoria and mountains such as Rwenzori and Elgon. The largest negative PMP values were in the arid and semi-arid areas of north and northeastern Uganda. The null hypothesis H 0 (no trend) was rejected (p < 0.05) for increasing annual precipitation trends across the various WMZs except in the extreme eastern parts of the Upper Nile, Kyoga, and Victoria WMZs (or areas along the boundary of Uganda and Kenya). The H 0 (no trend) was rejected (p < 0.05) for decreasing trends in annual PET over West Nile region of the Upper Nile, western parts of Victoria, and the Albert WMZs. For increasing trend in PMP, the H 0 (no trend) was rejected (p < 0.05) across the various WMZs except around the Mount Elgon area. The study findings are relevant for planning of water resources management across the different WMZs in the country.

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Pesticides monitoring in surface water of a subsistence agricultural catchment in Uganda using passive samplers

Oltramare

Weiss

Staudacher

et al. 2022

Environ Sci Pollut Res

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Pesticides are intensely used in the agricultural sector worldwide including smallholder farming. Poor pesticide use practices in this agronomic setting are well documented and may impair the quality of water resources. However, empirical data on pesticide occurrence in water bodies of tropical smallholder agriculture is scarce. Many available data are focusing on apolar organochlorine compounds which are globally banned. We address this gap by studying the occurrence of a broad range of more modern pesticides in an agricultural watershed in Uganda. During 2.5 months of the rainy season in 2017, three passive sampler systems were deployed at five locations in River Mayanja to collect 14 days of composite samples. Grab samples were taken from drinking water resources. In these samples, 27 compounds out of 265 organic pesticides including 60 transformation products were detected. In the drinking water resources, we detected eight pesticides and two insecticide transformation products in low concentrations between 1 and 50 ng/L. Also, in the small streams and open fetch ponds, detected concentrations were generally low with a few exceptions for the herbicide 2,4-D and the fungicide carbendazim exceeding 1 ug/L. The widespread occurrence of chlorpyrifos posed the largest risk for macroinvertebrates. The extensive detection of this compound and its transformation product 3,4,5-trichloro-2-pyridinol was unexpected and called for a better understanding of the use and fate of this pesticide. Graphical abstract

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Suitability of averaged outputs from multiple rainfall-runoff models for hydrological extremes: a case of River Kafu catchment in East Africa

Cited by 10 publications

References 43 publications

Performance of rainfall–runoff models in reproducing hydrological extremes: a case of the River Malaba sub-catchment

Performance of rainfall–runoff models in reproducing hydrological extremes: a case of the River Malaba sub-catchment

Water availability trends across water management zones in Uganda

Pesticides monitoring in surface water of a subsistence agricultural catchment in Uganda using passive samplers

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