Investigation of changes in seasonal streamflow and sediment load in the Subarnarekha-Burhabalang basins using Mann-Kendall and Pettitt tests

Abstract. Many fields, such as drought-risk assessment or reservoir management, can benefit from long-range streamflow forecasts. Climatology has long been used in long-range streamflow forecasting. Conditioning methods have been proposed to select or weight relevant historical time series from climatology. They are often based on general circulation model (GCM) outputs that are specific to the forecast date due to the initialisation of GCMs on current conditions. This study investigates the impact of conditioning methods on the performance of seasonal streamflow forecasts. Four conditioning statistics based on seasonal forecasts of cumulative precipitation and the standardised precipitation index were used to select relevant traces within historical streamflows and precipitation respectively. This resulted in eight conditioned streamflow forecast scenarios. These scenarios were compared to the climatology of historical streamflows, the ensemble streamflow prediction approach and the streamflow forecasts obtained from ECMWF System 4 precipitation forecasts. The impact of conditioning was assessed in terms of forecast sharpness (spread), reliability, overall performance and low-flow event detection. Results showed that conditioning past observations on seasonal precipitation indices generally improves forecast sharpness, but may reduce reliability, with respect to climatology. Conversely, conditioned ensembles were more reliable but less sharp than streamflow forecasts derived from System 4 precipitation. Forecast attributes from conditioned and unconditioned ensembles are illustrated for a case of drought-risk forecasting: the 2003 drought in France. In the case of low-flow forecasting, conditioning results in ensembles that can better assess weekly deficit volumes and durations over a wider range of lead times.

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Monthly and seasonal streamflow forecasting of large dryland catchments in Brazil

Journal of Arid Land ◽

10.1007/s40333-021-0097-y ◽

2021 ◽

Vol 13 (3) ◽

pp. 205-223

Author(s):

Alexandre C. Costa ◽

Alvson B. S. Estacio ◽

Francisco de A. de Souza Filho ◽

Iran E. Lima Neto

Keyword(s):

Streamflow Forecasting ◽

Seasonal Streamflow

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Land-Use/-Cover Changes and Their Effect on Soil Erosion and River Suspended Sediment Load in Different Landscape Zones of European Russia during 1970–2017

Water ◽

10.3390/w13121631 ◽

2021 ◽

Vol 13 (12) ◽

pp. 1631

Author(s):

Artyom V. Gusarov

Keyword(s):

Soviet Union ◽

Suspended Sediment ◽

Sediment Load ◽

Gully Erosion ◽

European Russia ◽

Relative Reduction ◽

Forest Steppe ◽

Suspended Sediment Load ◽

Cultivated Land ◽

Study Region

Contemporary trends in cultivated land and their influence on soil/gully erosion and river suspended sediment load were analyzed by various landscape zones within the most populated and agriculturally developed part of European Russia, covering 2,222,390 km2. Based on official statistics from the Russian Federation and the former Soviet Union, this study showed that after the collapse of the Soviet Union in 1991, there was a steady downward trend in cultivated land throughout the study region. From 1970–1987 to 2005–2017, the region lost about 39% of its croplands. Moreover, the most significant relative reduction in cultivated land was noted in the forest zone (south taiga, mixed and broadleaf forests) and the dry steppes and the semi-desert of the Caspian Lowland—about 53% and 65%, respectively. These territories are with climatically risky agriculture and less fertile soils. There was also a widespread reduction in agricultural machinery on croplands and livestock on pastures of the region. A decrease in soil/gully erosion rates over the past decades was also revealed based on state hydrological monitoring data on river suspended sediment load as one of the indicators of the temporal variability of erosion intensity in river basins and the published results of some field research in various parts of the studied landscape zones. The most significant reduction in the intensity of erosion and the load of river suspended sediment was found in European Russia’s forest-steppe zone. This was presumably due to a favorable combination of the above changes in land cover/use and climate change.

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Estimation of sediment load and erosion of different geological units: A case study from a basin of north-eastern Iran

Journal of Mountain Science ◽

10.1007/s11629-020-6570-9 ◽

2021 ◽

Vol 18 (6) ◽

pp. 1591-1608

Author(s):

Maryam Tajbakhshian ◽

Abolfazl Mosaedi ◽

Mohamad Hosein Mahmudy Gharaie ◽

Sayyed Reza Moussavi Harami

Keyword(s):

Sediment Load ◽

Eastern Iran ◽

North Eastern ◽

Geological Units

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Using SWAT to Evaluate Streamflow and Lake Sediment Loading in the Xinjiang River Basin with Limited Data

Water ◽

10.3390/w12010039 ◽

2019 ◽

Vol 12 (1) ◽

pp. 39 ◽

Cited By ~ 2

Author(s):

Lifeng Yuan ◽

Kenneth J. Forshay

Keyword(s):

Soil Erosion ◽

River Basin ◽

Lake Sediment ◽

Sediment Yield ◽

Sediment Load ◽

Poyang Lake ◽

Sediment Source ◽

Sediment Loading ◽

Source Areas ◽

Annual Sediment

Soil erosion and lake sediment loading are primary concerns of watershed managers around the world. In the Xinjiang River Basin of China, severe soil erosion occurs primarily during monsoon periods, resulting in sediment flow into Poyang Lake and subsequently causing lake water quality deterioration. Here, we identified high-risk soil erosion areas and conditions that drive sediment yield in a watershed system with limited available data to guide localized soil erosion control measures intended to support reduced sediment load into Poyang Lake. We used the Soil and Water Assessment Tool (SWAT) model to simulate monthly and annual sediment yield based on a calibrated SWAT streamflow model, identified where sediment originated, and determined what geographic factors drove the loading within the watershed. We applied monthly and daily streamflow discharge (1985–2009) and monthly suspended sediment load data (1985–2001) to Meigang station to conduct parameter sensitivity analysis, calibration, validation, and uncertainty analysis of the model. The coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), and RMSE -observation’s standard deviation ratio (RSR) values of the monthly sediment load were 0.63, 0.62, 3.8%, and 0.61 during calibration, respectively. Spatially, the annual sediment yield rate ranged from 3 ton ha−1year−1 on riparian lowlands of the Xinjiang main channel to 33 ton ha−1year−1 on mountain highlands, with a basin-wide mean of 19 ton ha−1year−1. The study showed that 99.9% of the total land area suffered soil loss (greater than 5 ton ha−1year−1). More sediment originated from the southern mountain highlands than from the northern mountain highlands of the Xinjiang river channel. These results suggest that specific land use types and geographic conditions can be identified as hotspots of sediment source with relatively scarce data; in this case, orchards, barren lands, and mountain highlands with slopes greater than 25° were the primary sediment source areas. This study developed a reliable, physically-based streamflow model and illustrates critical source areas and conditions that influence sediment yield.

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