Predicting Impacts of Land Use and Climate Change on Erosion and Sediment Yield in River Basins Using SHETRAN

Bathurst, James C.

doi:10.1002/9781444328455.ch14

Cited by 18 publications

(21 citation statements)

References 69 publications

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“…MUSLE and Zheng's model were found to produce less satisfactory predictions for low-magnitude events , 2011 ( Table 2). Nevertheless, on the Loess Plateau soil loss is dominated by large storms and small storms are less important for the soil loss.…”

Section: Prediction Accuracymentioning

confidence: 99%

Comparison of soil erosion models used to study the Chinese Loess Plateau

Holden

et al. 2017

Earth-Science Reviews

144

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The Loess Plateau suffers from severe soil erosion that leads to a series of ecological and economic problems such as reduced land productivity, exacerbated rural poverty, decreased biodiversity and sedimentation of the riverbed in the lower reaches of the Yellow River. Soil erosion models are commonly used on the Loess Plateau to help target sustainable land management strategies to control soil erosion.In this study, we compared eleven soil erosion models that were previously used on the Loess Plateau. We studied their prediction accuracy, process representation, data and calibration requirements, and potential application in scenario studies. The selected models consisted of a broad range of model types, structures and scales.The comparison showed that process-based and empirical models did not necessarily yield more accurate results over one another for the Loess Plateau.Among the process-based models, Si' model, WEPP and MMF had the highest prediction accuracy. However, some of the selected models were tested with total ACCEPTED MANUSCRIPT A C C E P T E D M A N U S C R I P T2 sediment load while others were tested with suspended sediment load (i.e. bedload is not included), which is subject to several drawbacks. Research questions that each of the models can address on the Loess Plateau were suggested. Further improvement of soil erosion models for the Loess Plateau should concentrate on enhancing the quality of data for model implementation and testing, incorporating key processes into process-based models according to their aims and scales, comparing models that address the same research questions, and implementing internal and spatial model testing.

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Section: Prediction Accuracymentioning

confidence: 99%

Comparison of soil erosion models used to study the Chinese Loess Plateau

Holden

et al. 2017

Earth-Science Reviews

144

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“…Work by [35] highlights the limitation of the approach to quantifying effects of urbanization on components of the hydrologic cycle. The above concerns over the paired watershed approach have inspired use of hydrologic models to assess effects of climate and land use change on watershed hydrology [36][37][38][39]. Although hydrologic models are cost and time savers, their relatively higher learning curve and their requirement for multiple data inputs provide challenges to water managers.…”

Section: Introductionmentioning

confidence: 99%

Consistency of Hydrologic Relationships of a Paired Watershed Approach

Ssegane¹,

Amatya²,

Chescheir³

et al. 2013

AJCC

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Paired watershed studies are used around the world to evaluate and quantify effects of forest and water management practices on hydrology and water quality. The basic concept uses two neighboring watersheds (one as a control and another as a treatment), which are concurrently monitored during calibration (pre-treatment) and post-treatment periods. A statistically significant relationship between the control and treatment watersheds is established during calibration period such that any significant shift detected in the relationship during treatment is attributed to the treatment effects. The approach assumes that there is a consistent, quantifiable, and predictable relationship between watershed response variables. This study tests the hypothesis that the hydrologic relationships between control and treatment watersheds for daily water table elevation (WTE) and daily flow data were similar without any statistically significant difference during two different calibration (1988-1989 and 2007-2008) and treatment periods (1995-1996 and 2009), when the control and treatment watersheds were interchanged. The watersheds are two artificially drained loblolly pine forests (D1: 24.7 ha and D2: 23.6 ha) located in coastal North Carolina. Results depicted significantly similar WTE regression relationships during the two calibration periods but significantly different WTE relationships during the two treatment periods with reversed control and treatment watersheds. Calibration and treatment flow relationships, and the mean treatment effects on WTE and flow, before and after treatment reversal were significantly different (α = 0.05). The study also discusses causes of differences in hydrologic relationships and treatment effects for such reversal of treatments during a 21-year span of the study on these two similar and adjacent watersheds. The observed differences in the hydrologic relationships between control and treatment watersheds before and after treatment reversal may be attributed to climate or hydrologic non-stationarity which may affect the reliability of paired watershed approach especially when the calibration periods are short.

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“…Zhang et al [28] performed sensitivity analysis of the parameters of the non-dominated sorting genetic algorithm-II (NSGA-II) [29] on the accuracy of a distributed hydrological model known as Systeme Hydrologique Européen-Transport (SHETRAN) [4,[30][31][32][33][34][35][36]. Simulated binary crossover (SBX) [37] and polynomial mutation (PM) [38] were used for the crossover and mutation, respectively, of three NSGA-II algorithms: the original NSGA-II, the reference point-based-NSGA-II (R-NSGA-II) [39], and the extension ER-NSGA-II [40].…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Automatic Parameter Calibration of a Hydrological Model

Jung

Choi

Kim

2017

Water

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This study proposes variable balancing approaches for the exploration (diversification) and exploitation (intensification) of the non-dominated sorting genetic algorithm-II (NSGA-II) with simulated binary crossover (SBX) and polynomial mutation (PM) in the multiobjective automatic parameter calibration of a lumped hydrological model, the HYMOD model. Two objectives-minimizing the percent bias and minimizing three peak flow differences-are considered in the calibration of the six parameters of the model. The proposed balancing approaches, which migrate the focus between exploration and exploitation over generations by varying the crossover and mutation distribution indices of SBX and PM, respectively, are compared with traditional static balancing approaches (the two dices value is fixed during optimization) in a benchmark hydrological calibration problem for the Leaf River (1950 km 2 ) near Collins, Mississippi. Three performance metrics-solution quality, spacing, and convergence-are used to quantify and compare the quality of the Pareto solutions obtained by the two different balancing approaches. The variable balancing approaches that migrate the focus of exploration and exploitation differently for SBX and PM outperformed other methods.

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Predicting Impacts of Land Use and Climate Change on Erosion and Sediment Yield in River Basins Using SHETRAN

Cited by 18 publications

References 69 publications

Comparison of soil erosion models used to study the Chinese Loess Plateau

Comparison of soil erosion models used to study the Chinese Loess Plateau

Consistency of Hydrologic Relationships of a Paired Watershed Approach

Multiobjective Automatic Parameter Calibration of a Hydrological Model

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