Modelling the rainfall–runoff process of the Mara River basin using the Soil and Water Assessment Tool

Dessu, Shimelis Behailu; Melesse, Assefa M.

doi:10.1002/hyp.9205

Cited by 78 publications

(45 citation statements)

References 26 publications

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“…The large difference in the runoff components between the two sub-catchments, demonstrates a distinct difference in the fast response characteristics between the two. These findings are supported by previous studies done by [16]. These researchers found out that Nyangores had higher infiltration than Amala.…”

Section: Partitioning Of the Flow Hydrographsupporting

confidence: 90%

Analyzing the Mara River Basin Behaviour through Rainfall-Runoff Modeling

Birundu¹,

Mutua²

2017

IJG

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Hydrological models are considered as necessary tools for water and environmental resource management. However, modelling poorly gauged watersheds has been a challenge to hydrologists and hydraulic engineers. Research done recently has shown the potential to overcome this challenge through incorporating satellite based hydrological and meteorological data in the measured data. This paper presents results for a study that used the semi-distributed conceptual HBV Light Model to model the rainfall-runoff in the Mara River Basin, Kenya. The model simulates runoff as a function of rainfall. It is built on the basis established between satellite observed and in-situ rainfall, evaporation, temperature and the measured runoff. The model's performance and reliability were evaluated over two sub-catchments namely: Nyangores and Amala in the Mara River Basin using the Nash-Sutcliffe Efficiency which the model referred to as R eff and the coefficient of determination (R 2 ). The R eff for Nyangores and Amala during the calibration and (validation) period were 0.65 (0.68) and 0.59 (0.62) respectively. The model showed good flow simulations particularly during the recession flows, in the Nyangores sub-catchment whereas it simulated poorly the short term fluctuations of the high-flow for Amala sub-catchment. Results from this study can be used by water resources managers to make informed decision on planning and management of water resources.

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Section: Partitioning Of the Flow Hydrographsupporting

confidence: 90%

Analyzing the Mara River Basin Behaviour through Rainfall-Runoff Modeling

Birundu¹,

Mutua²

2017

IJG

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“…The modeling results indicated that SWAT performance at the Haean catchment relied heavily on the quality and more importantly abundance of discharge data, similar to the results of Dessu and Melesse (2012). The NSE score for monitoring locations S1, S4, S5, S6, and S7 ranged between 0.64 and 0.95 with an average score of 0.76 for the 2010 calibration period and between 0.40 and 0.98 for the validation period (Fig.…”

Section: Spatiotemporal Flow Partitioning With Respect To River Dischsupporting

confidence: 68%

Using the SWAT model to improve process descriptions and define hydrologic partitioning in South Korea

Shope

Maharjan

Tenhunen

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Watershed-scale modeling can be a valuable tool to aid in quantification of water quality and yield; however, several challenges remain. In many watersheds, it is difficult to adequately quantify hydrologic partitioning. Data scarcity is prevalent, accuracy of spatially distributed meteorology is difficult to quantify, forest encroachment and land use issues are common, and surface water and groundwater abstractions substantially modify watershed-based processes. Our objective is to assess the capability of the Soil and Water Assessment Tool (SWAT) model to capture eventbased and long-term monsoonal rainfall-runoff processes in complex mountainous terrain. To accomplish this, we developed a unique quality-control, gap-filling algorithm for interpolation of high-frequency meteorological data. We used a novel multi-location, multi-optimization calibration technique to improve estimations of catchment-wide hydrologic partitioning. The interdisciplinary model was calibrated to a unique combination of statistical, hydrologic, and plant growth metrics. Our results indicate scale-dependent sensitivity of hydrologic partitioning and substantial influence of engineered features. The addition of hydrologic and plant growth objective functions identified the importance of culverts in catchment-wide flow distribution. While this study shows the challenges of applying the SWAT model to complex terrain and extreme environments; by incorporating anthropogenic features into modeling scenarios, we can enhance our understanding of the hydroecological impact.

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“…Today, high-quality land cover types can usually be acquired via remote sensing technology developed after the 1980s. Hydrological models, such as the SWAT [17,18], TOPMODEL [19], and VIC [20], are commonly used to study the effect of climate change on the hydrological cycle. Based on physical mechanisms, hydrological models offer a framework for conceptualizing and investigating the relationships between climate, land cover, and hydrological processes in various categories of time and space [21,22].…”

Section: Introductionmentioning

confidence: 99%

Long Term Quantification of Climate and Land Cover Change Impacts on Streamflow in an Alpine River Catchment, Northwestern China

Yin¹,

Feng²,

Yang³

et al. 2017

Sustainability

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Abstract:Quantifying the long term impacts of climate and land cover change on streamflow is of great important for sustainable water resources management in inland river basins. The Soil and Water Assessment Tool (SWAT) model was employed to simulate the streamflow in the upper reaches of Heihe River Basin, northwestern China, over the last half century. The Sequential Uncertainty Fitting algorithm (SUFI-2) was selected to calibrate and validate the SWAT model. The results showed that both Nash-Sutcliffe efficiency (NSE) and determination coefficient (R 2 ) were over 0.93 for calibration and validation periods, the percent bias (PBIAS) of the two periods were-3.47% and 1.81%, respectively. The precipitation, average, maximum, and minimum air temperature were all showing increasing trends, with 14.87 mm/10 years, 0.30 • C/10 years, 0.27 • C/10 year, and 0.37 • C/10 years, respectively. Runoff coefficient has increased from 0.36 (averaged during 1964 to 1988) to 0.39 (averaged during 1989 to 2013). Based on the SWAT simulation, we quantified the contribution of climate and land cover change to streamflow change, indicated that the land cover change had a positive impact on river discharge by increasing 7.12% of the streamflow during 1964 to 1988, and climate change contributed 14.08% for the streamflow increasing over last 50 years. Meanwhile, the climate change impact was intensive after 2000s. The increasing of streamflow contributed to the increasing of total streamflow by 64.1% for cold season (November to following March) and 35.9% for warm season (April to October). The results provide some references for dealing with climate and land cover change in an inland river basin for water resource management and planning.

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Modelling the rainfall–runoff process of the Mara River basin using the Soil and Water Assessment Tool

Cited by 78 publications

References 26 publications

Analyzing the Mara River Basin Behaviour through Rainfall-Runoff Modeling

Analyzing the Mara River Basin Behaviour through Rainfall-Runoff Modeling

Using the SWAT model to improve process descriptions and define hydrologic partitioning in South Korea

Long Term Quantification of Climate and Land Cover Change Impacts on Streamflow in an Alpine River Catchment, Northwestern China

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