Assessing Digital Soil Inventories for Predicting Streamflow in the Headwaters of the Blue Nile

Adem, Anwar A.; Dile, Yihun T.; Worqlul, Abeyou W.; Ayana, Essayas K.; Tilahun, Seifu A.; Steenhuis, Tammo S.

doi:10.3390/hydrology7010008

Cited by 7 publications

(2 citation statements)

References 42 publications

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“…In South Africa, a study of urbanized catchments (640 km 2 , 550 km 2 , 54 km 2 ) also determined that hydropedological soil information improved modelling accuracy for all catchment sizes compared to readily available soil information [29]. Other studies, however, found that more detailed soil information did not statistically improve hydrological modelling accuracy [30][31][32][33]. However, none of these studies used hydrological soil information specifically created for modelling purposes.…”

Section: Introductionmentioning

confidence: 99%

Impacts of Soil Information on Process-Based Hydrological Modelling in the Upper Goukou Catchment, South Africa

Smit

Tol

2022

Water

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Although soils form an integral part of landscape hydrological processes, the importance of soil information in hydrological modelling is often neglected. This study investigated the impact of soil information on streamflow modelling accuracy and hydrological process representation. Two different levels of soil information were compared to long-term streamflow in the upper Goukou catchment (230 km2), South Africa, over a period of 23 years using the Soil Water Assessment Tool (SWAT+). The land-type soil map (LTSM) dataset was less detailed and derived from the best, readily available soil dataset for South Africa currently. The hydrological soil map (HSM) dataset was more detailed and was created using infield hydropedological soil observations combined with digital soil-mapping techniques. Monthly streamflow simulation was similar for both soil datasets, with Nash–Sutcliffe efficiency and Kling–Gupta efficiency values of 0.57 and 0.59 (HSM) and 0.56 and 0.60 (LTSM), respectively. It is, however, important to assess through which hydrological processes were these streamflow values generated as well as their spatial distribution within the catchment. Upon further assessment, the representation of hydrological processes within the catchment differed greatly between the two datasets, with the HSM more accurately representing the internal hydrological processes, as it was based on infield observations. It was concluded that hydropedological information could be of great value in effective catchment management strategies since it improves representation of internal catchment processes.

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Section: Introductionmentioning

confidence: 99%

Impacts of Soil Information on Process-Based Hydrological Modelling in the Upper Goukou Catchment, South Africa

Smit

Tol

2022

Water

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“…1b). Around 35 % of the Sudanese allocation of Nile water is consumed by the Gezira Scheme, which is supplied by the Sennar Dam (Adam et al, 2003). The Gezira Scheme, with a total area of 8800 km 2 , is regarded as one of the largest irrigation schemes in the world under a single management structure (Ahmed et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Inferring reservoir filling strategies under limited-data-availability conditions using hydrological modeling and Earth observations: the case of the Grand Ethiopian Renaissance Dam (GERD)

Ali,

Melsen,

Teuling

2023

Hydrol. Earth Syst. Sci.

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Abstract. The filling of the Grand Ethiopian Renaissance Dam (GERD) started in 2020, posing additional challenges for downstream water management in the Blue Nile River in the Republic of the Sudan, which is already struggling to cope with the effects of climate change. This is also the case for many transboundary rivers that are affected by a lack of cooperation and transparency during the filling and operation of new dams. Without information about water supply from neighboring countries, it is risky to manage downstream dams as usual, but operational information is needed to apply modifications. This study aims to develop a novel approach/framework that utilizes hydrological modeling in conjunction with remote-sensing data to retrieve reservoir filling strategies under limited-data-availability conditions. Firstly, five rainfall products (i.e., ARC2, CHIRPS, ERA5, GPCC, and PERSIANN-CDR; see Sect. 2.3 for more information) were evaluated against historical measured rainfall at 10 stations. Secondly, to account for input uncertainty, the three best-performing rainfall products were forced in the conceptual hydrological model HBV-light with potential evapotranspiration and temperature data from ERA5. The model was calibrated during the period from 2006 to 2019 and validated during the period from 1991 to 1996. Thirdly, the parameter sets that obtained very good performance (Nash–Sutcliffe efficiency, NSE, greater than 0.75) were utilized to predict the inflow of GERD during the operation period (2020–2022). Then, from the water balance of GERD, the daily storage was estimated and compared with the storage derived from Landsat and Sentinel imageries to evaluate the performance of the selected rainfall products and the reliability of the framework. Finally, 3 years of GERD filling strategies was retrieved using the best-performing simulation of CHIRPS with an RMSE of 1.7 ×109 and 1.52 ×109m3 and an NSE of 0.77 and 0.86 when compared with Landsat- and Sentinel-derived reservoir storage, respectively. It was found that GERD stored 14 % of the monthly inflow of July 2020; 41 % of July 2021; and 37 % and 32 % of July and August 2022, respectively. Annually, GERD retained 5.2 % and 7.4 % of the annual inflow in the first two filling phases and between 12.9 % and 13.7 % in the third phase. The results also revealed that the retrieval of filling strategies is more influenced by input uncertainty than parameter uncertainty. The retrieved daily change in GERD storage with the measured outflow to the Republic of the Sudan allowed further interpretation of the downstream impacts of GERD. The findings of this study provide systematic steps to retrieve filling strategies, which can serve as a base for future development in the field, especially for data-scarce regions. Locally, the analysis contributes significantly to the future water management of the Roseires and Sennar dams in the Republic of the Sudan.

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Evaluating the effects of DEM and soil data resolution on streamflow and sediment yield simulations in the Upper Blue Nile basin

Dile,

Bayabil,

Ayana

et al. 2023

Environ Monit Assess

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Assessing Digital Soil Inventories for Predicting Streamflow in the Headwaters of the Blue Nile

Cited by 7 publications

References 42 publications

Impacts of Soil Information on Process-Based Hydrological Modelling in the Upper Goukou Catchment, South Africa

Impacts of Soil Information on Process-Based Hydrological Modelling in the Upper Goukou Catchment, South Africa

Inferring reservoir filling strategies under limited-data-availability conditions using hydrological modeling and Earth observations: the case of the Grand Ethiopian Renaissance Dam (GERD)

Evaluating the effects of DEM and soil data resolution on streamflow and sediment yield simulations in the Upper Blue Nile basin

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