Linking Sediment Yield and Caesium-137 Spatial Distribution at Basin Scale

Beyond damage to rainfed agricultural and forestry ecosystems, soil erosion due to water affects surrounding environments. Large amounts of eroded soil are deposited in streams, lakes, and other ecosystems. The most costly off-site damages occur when eroded particles, transported along the hillslopes of a basin, arrive at the river network or are deposited in lakes. The negative effects of soil erosion include water pollution and siltation, organic matter loss, nutrient loss, and reduction in water storage capacity. Sediment deposition raises the bottom of waterways, making them more prone to overflowing and flooding. Sediments contaminate water ecosystems with soil particles and the fertilizer and pesticide chemicals they contain. Siltation of reservoirs and dams reduces water storage, increases the maintenance cost of dams, and shortens the lifetime of reservoirs. Sediment yield is the quantity of transported sediments, in a given time interval, from eroding sources through the hillslopes and river network to a basin outlet. Chemicals can also be transported together with the eroded sediments. Sediment deposition inside a reservoir reduces the water storage of a dam. The prediction of sediment yield can be carried out by coupling an erosion model with a mathematical operator which expresses the sediment transport efficiency of the hillslopes and the channel network. The sediment lag between sediment yield and erosion can be simply represented by the sediment delivery ratio, which can be calculated at the outlet of the considered basin, or by using a distributed approach. The former procedure couples the evaluation of basin soil loss with an estimate of the sediment delivery ratio SDRW for the whole watershed. The latter procedure requires that the watershed be discretized into morphological units, areas having a constant steepness and a clearly defined length, for which the corresponding sediment delivery ratio is calculated. When rainfall reaches the surface horizon of the soil, some pollutants are desorbed and go into solution while others remain adsorbed and move with soil particles. The spatial distribution of the loading of nitrogen, phosphorous, and total organic carbon can be deduced using the spatial distribution of sediment yield and the pollutant content measured on soil samples. The enrichment concept is applied to clay, organic matter, and all pollutants adsorbed by soil particles, such as nitrogen and phosphorous. Knowledge of both the rate and pattern of sediment deposition in a reservoir is required to establish the remedial strategies which may be practicable. Repeated reservoir capacity surveys are used to determine the total volume occupied by sediment, the sedimentation pattern, and the shift in the stage-area and stage-storage curves. By converting the sedimentation volume to sediment mass, on the basis of estimated or measured bulk density, and correcting for trap efficiency, the sediment yield from the basin can be computed.

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Scenario modelling of basin-scale, shallow landslide sediment yield, Valsassina, Italian Southern Alps

Natural Hazards and Earth System Science ◽

10.5194/nhess-5-189-2005 ◽

2005 ◽

Vol 5 (2) ◽

pp. 189-202 ◽

Cited By ~ 34

Author(s):

J. C. Bathurst ◽

G. Moretti ◽

A. El-Hames ◽

A. Moaven-Hashemi ◽

A. Burton

Keyword(s):

Sediment Yield ◽

Shallow Landslide ◽

Southern Alps ◽

Sediment Supply ◽

Channel Network ◽

Landslide Occurrence ◽

Sediment Yields ◽

Basin Scale ◽

Modest Reduction

Abstract. The SHETRAN model for determining the sediment yield arising from shallow landsliding at the scale of a river catchment was applied to the 180-km2 Valsassina basin in the Italian Southern Alps, with the aim of demonstrating that the model can simulate long term patterns of landsliding and the associated sediment yields and that it can be used to explore the sensitivity of the landslide sediment supply system to changes in catchment characteristics. The model was found to reproduce the observed spatial distribution of landslides from a 50-year record very well but probably with an overestimate of the annual rate of landsliding. Simulated sediment yields were within the range observed in a wider region of northern Italy. However, the results suggest that the supply of shallow landslide material to the channel network contributes relatively little to the overall long term sediment yield compared with other sources. The model was applied for scenarios of possible future climate (drier and warmer) and land use (fully forested hillslopes). For both scenarios, there is a modest reduction in shallow landslide occurrence and the overall sediment yield. This suggests that any current schemes for mitigating sediment yield impact in Valsassina remain valid. The application highlights the need for further research in eliminating the large number of unconditionally unsafe landslide sites typically predicted by the model and in avoiding large overestimates of landslide occurrence.

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A method for sea ice thickness and concentration analysis based on SAR data and a thermodynamic model

The Cryosphere ◽

10.5194/tc-6-1507-2012 ◽

2012 ◽

Vol 6 (6) ◽

pp. 1507-1526 ◽

Cited By ~ 23

Author(s):

J. Karvonen ◽

B. Cheng ◽

T. Vihma ◽

M. Arkett ◽

T. Carrieres

Keyword(s):

Spatial Distribution ◽

Sea Ice ◽

Thickness Distribution ◽

Added Value ◽

Ice Thickness ◽

Motion Field ◽

Sea Ice Thickness ◽

Automated Method ◽

Basin Scale ◽

Sar Data

Abstract. An analysis of ice thickness distribution is a challenge, particularly in a seasonal sea ice zone with a strongly dynamic ice motion field, such as the Gulf of St. Lawrence off Canada. We present a novel automated method for ice concentration and thickness analysis combining modeling of sea ice thermodynamics and detection of ice motion on the basis of space-borne Synthetic Aperture Radar (SAR) data. Thermodynamic evolution of sea ice thickness in the Gulf of St. Lawrence was simulated for two winters, 2002–2003 and 2008–2009. The basin-scale ice thickness was controlled by atmospheric forcing, but the spatial distribution of ice thickness and concentration could not be explained by thermodynamics only. SAR data were applied to detect ice motion and ice surface structure during these two winters. The SAR analysis is based on estimation of ice motion between SAR image pairs and analysis of the local SAR texture statistics. Including SAR data analysis brought a significant added value to the results based on thermodynamics only. Our novel method combining the thermodynamic modeling and SAR yielded results that well match with the distribution of observations based on airborne Electromagnetic Induction (EM) method. Compared to the present operational method of producing ice charts for the Gulf of St. Lawrence, which is based on visual interpretation of SAR data, the new method reveals much more detailed and physically based information on spatial distribution of ice thickness. The algorithms can be run automatically, and the final products can then be used by ice analysts for operational ice service. The method is globally applicable to all seas where SAR data are available.

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Predicting soil erosion and sediment yield at the basin scale: Scale issues and semi-quantitative models

Earth-Science Reviews ◽

10.1016/j.earscirev.2005.02.002 ◽

2005 ◽

Vol 71 (1-2) ◽

pp. 95-125 ◽

Cited By ~ 393

Author(s):

Joris de Vente ◽

Jean Poesen

Keyword(s):

Soil Erosion ◽

Sediment Yield ◽

Quantitative Models ◽

Basin Scale

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Environmental DNA analysis reveals the spatial distribution, abundance, and biomass of Japanese eels at the river‐basin scale

Aquatic Conservation Marine and Freshwater Ecosystems ◽

10.1002/aqc.3058 ◽

2019 ◽

Vol 29 (3) ◽

pp. 361-373 ◽

Cited By ~ 16

Author(s):

Hikaru Itakura ◽

Ryoshiro Wakiya ◽

Satoshi Yamamoto ◽

Kenzo Kaifu ◽

Takuya Sato ◽

...

Keyword(s):

Spatial Distribution ◽

River Basin ◽

Dna Analysis ◽

Environmental Dna ◽

River Basin Scale ◽

Basin Scale

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The influence of the spatial distribution of agricultural conservation practices on hydrological balance variables in a small basin

10.5194/egusphere-egu2020-993 ◽

2020 ◽

Author(s):

Nina Noreika ◽

Tomas Dostal ◽

Tailin Li ◽

David Zumr ◽

Josef Krasa

Keyword(s):

Spatial Distribution ◽

Cover Crops ◽

Water Conservation ◽

Crop Residues ◽

Swat Model ◽

Conservation Practices ◽

Discharge Data ◽

Hydrological Balance ◽

Agricultural Conservation ◽

Basin Scale

SWAT is perhaps the most widely-used basin-scale hydrological model discussed in modern literature. SWAT is typically used to model large basins (100+ km2) and has even successfully modeled basins at continental scales. Regardless of the typical scale that SWAT is used, SWAT has been shown to adequately model various hydrological processes at smaller scales, but this application is much less common in the literature. &#160;The aim of this study is to utilize SWAT+ in a small (<1 km2) agricultural basin (Nucice) approximately 30 kilometers southeast of Prague, Czechia to determine the effects of various spatial distribution patterns of agricultural conservation practices (no/reduced tillage, crop residues, cover crops, etc.) and their respective impacts on projected runoff, soil water retention, and evapotranspiration.We were able to successfully calibrate our SWAT+ model for the Nucice experimental catchment from 2014 through part of 2018 using discharge data and estimating ET via remote sensing. After successful calibration, we implemented 4 scenarios to analyze the effects of implementing agricultural conservation practices: 25% continuous in upper 50% of basin, 25% fragmented in upper 50% of basin, 25% continuous in lower 50% of basin, and 25% fragmented in lower 50% of basin.The adaptation pattern of agricultural conservation practices has significant and disproportionate effects on various hydrological balance parameters. Since it is rare that a single farmer manages an entire basin, this study shows that widespread adaptation of agricultural practices is necessary to maximize water conservation within a landscape. We intend to upscale this study (100+ km2 basins) and to compare basins across multiple climates to determine if these effects are universal.This research has been supported by project H2020 No. 773903 Shui, focused on water scarcity in European and Chinese cropping systems.

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Correcting basin-scale snowfall in a mountainous basin using a distributed snowmelt model and remote-sensing data

Hydrology and Earth System Sciences ◽

10.5194/hess-18-747-2014 ◽

2014 ◽

Vol 18 (2) ◽

pp. 747-761 ◽

Cited By ~ 24

Author(s):

M. Shrestha ◽

L. Wang ◽

T. Koike ◽

H. Tsutsui ◽

Y. Xue ◽

...

Keyword(s):

Spatial Distribution ◽

Snow Cover ◽

Search Algorithm ◽

Relative Volume ◽

Shortwave Radiation ◽

Topographic Effects ◽

Hydrologic Modelling ◽

Study Region ◽

Basin Scale ◽

Snowmelt Model

Abstract. Adequate estimation of the spatial distribution of snowfall is critical in hydrologic modelling. However, this is a well-known problem in estimating basin-scale snowfall, especially in mountainous basins with data scarcity. This study focuses on correction and estimation of this spatial distribution, which considers topographic effects within the basin. A method is proposed that optimises an altitude-based snowfall correction factor (Cfsnow). This is done through multi-objective calibration of a spatially distributed, multilayer energy and water balance-based snowmelt model (WEB-DHM-S) with observed discharge and remotely sensed snow cover data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The Shuffled Complex Evolution–University of Arizona (SCE–UA) automatic search algorithm is used to obtain the optimal value of Cfsnow for minimum cumulative error in discharge and snow cover simulations. Discharge error is quantified by Nash–Sutcliffe efficiency and relative volume deviation, and snow cover error was estimated by pixel-by-pixel analysis. The study region is the heavily snow-fed Yagisawa Basin of the Upper Tone River in northeast Japan. First, the system was applied to one snow season (2002–2003), obtaining an optimised Cfsnow of 0.0007 m−1. For validation purposes, the optimised Cfsnow was implemented to correct snowfall in 2004, 2002 and 2001. Overall, the system was effective, implying improvements in correlation of simulated versus observed discharge and snow cover. The 4 yr mean of basin-average snowfall for the corrected spatial snowfall distribution was 1160 mm (780 mm before correction). Execution of sensitivity runs against other model input and parameters indicated that Cfsnow could be affected by uncertainty in shortwave radiation and setting of the threshold air temperature parameter. Our approach is suitable to correct snowfall and estimate its distribution in poorly gauged basins, where elevation dependence of snowfall amount is strong.

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