Simple Linear Modeling Approach for Linking Hydrological Model Parameters to the Physical Features of a River Basin

2015 ◽  
Vol 29 (9) ◽  
pp. 3265-3289 ◽  
Author(s):  
Chengcheng Huang ◽  
Guoqiang Wang ◽  
Xiaogu Zheng ◽  
Jingshan Yu ◽  
Xinyi Xu
Keyword(s):  
River Basin ◽  
Hydrological Model ◽  
Model Parameters ◽  
Linear Modeling ◽  
Modeling Approach ◽  
Physical Features

scholarly journals Modeling Groundwater-Fed Irrigation and Its Impact on Streamflow and Groundwater Depth in an Agricultural Area of Huaihe River Basin, China

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2220
Author(s):  
Yimeng Sun ◽  
Xi Chen ◽  
Xi Chen ◽  
Liu Yang
Keyword(s):  
River Basin ◽  
River Discharge ◽  
Hydrological Model ◽  
Groundwater Withdrawal ◽  
Groundwater Depth ◽  
Model Parameters ◽  
Agricultural Irrigation ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Single Objective

The amount of water taken from groundwater for agricultural irrigation is often not observed, while hydrological models have been extensively proposed to investigate the irrigation dynamics and impacts in agricultural areas. In this work, we propose an agro-hydrological model that integrates agricultural irrigation with the traditional Xin’anjiang (XAJ) hydrological model. In particular, the proposed model incorporates the FAO guidelines on crop evapotranspiration into hydrological routing of water balance and flow fluxes in unsaturated and saturated zones. The model was used to calibrate the groundwater irrigation amounts in terms of both the observed river discharge and the groundwater depth in the Xuanwu plain area of the Huaihe River Basin in China. The calibration and sensitivity analyses were performed by the shuffled complex evolution (SCE-UA) method. This method can be applied to a single-objective optimization of model parameters, based on either the river discharge or the groundwater depth, or to a multi-objective optimization of model parameters based on both of these objectives. The results show that the multi-objective calibration is more efficient than the single-objective method for capturing dynamics of the river discharge and the groundwater depth. The estimated means of the annual groundwater withdrawal for wheat and maize irrigations were found to be about 140.5 mm and 13.7 mm, respectively. The correlation between the groundwater withdrawal and the change in groundwater depth during crop growing seasons demonstrated that the groundwater withdrawal is the dominant factor for the groundwater depth change in the river basin, particularly in the winter wheat season. Moreover, model simulations show that the combined effects of the reduced precipitation and the increased groundwater withdrawal would lead to a decrease of the average annual runoff and an increase of the average groundwater depth. These estimates can greatly help in understanding the irregular changes in the groundwater withdrawal and offer a quantitative basis for studying future groundwater demands in this area.

scholarly journals Large-watershed flood forecasting with high-resolution distributed hydrological model

2017 ◽  
Vol 21 (2) ◽  
pp. 735-749 ◽  
Author(s):  
Yangbo Chen ◽  
Ji Li ◽  
Huanyu Wang ◽  
Jianming Qin ◽  
Liming Dong
Keyword(s):  
High Resolution ◽  
River Basin ◽  
Spatial Resolution ◽  
Hydrological Model ◽  
Threshold Model ◽  
Grid Cell ◽  
Flood Forecasting ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Computation Efficiency

Abstract. A distributed hydrological model has been successfully used in small-watershed flood forecasting, but there are still challenges for the application in a large watershed, one of them being the model's spatial resolution effect. To cope with this challenge, two efforts could be made; one is to improve the model's computation efficiency in a large watershed, the other is implementing the model on a high-performance supercomputer. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil and land use are downloaded from the website freely, and the model structure with a high resolution of 200 m  ×  200 m grid cell is set up. The initial model parameters are derived from the terrain property data, and then optimized by using the Particle Swarm Optimization (PSO) algorithm; the model is used to simulate 29 observed flood events. It has been found that by dividing the river channels into virtual channel sections and assuming the cross section shapes as trapezoid, the Liuxihe model largely increases computation efficiency while keeping good model performance, thus making it applicable in larger watersheds. This study also finds that parameter uncertainty exists for physically deriving model parameters, and parameter optimization could reduce this uncertainty, and is highly recommended. Computation time needed for running a distributed hydrological model increases exponentially at a power of 2, not linearly with the increasing of model spatial resolution, and the 200 m  ×  200 m model resolution is proposed for modeling the Liujiang River basin flood with the Liuxihe model in this study. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling the Liujiang River basin flood is a 500 m  ×  500 m grid cell, but the model spatial resolution with a 200 m  ×  200 m grid cell is recommended in this study to keep the model at a better performance.

scholarly journals Hydrological Similarity-Based Parameter Regionalization under Different Climate and Underlying Surfaces in Ungauged Basins

Water ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 2508
Author(s):  
Huaijun Wang ◽  
Lei Cao ◽  
Ru Feng
Keyword(s):  
River Basin ◽  
Hydrological Model ◽  
Poyang Lake ◽  
Underlying Surface ◽  
Model Parameters ◽  
Lake Basin ◽  
Ungauged Basins ◽  
Ungauged Basin ◽  
Spring Runoff ◽  
Poyang Lake Basin

Hydrological similarity-based parameter regionalization is the dominant method used for runoff prediction in ungauged basin. However, the application of this approach depends on assessing hydrological similarity between basins. This study used data for runoff, climate, and the underlying surface of the Hulan River Basin and Poyang Lake Basin to construct a novel physical hydrological similarity index (HSI). The index was used to compare the efficiency of transfer of the parameters of commonly used regionalization methods and to finally apply parameters to ungauged basins. The results showed that: (1) Precipitation is the main climatic factor regulating magnitude of runoff in the Poyang Lake Basin. Spring runoff in Hulan River Basin was regulated by precipitation and temperature. (2) The GR4J and CemaNeigeGR4J models achieved reasonable simulations of runoff of Poyang Lake Basin and Hulan River Basin. Although CemaNeigeGR4J considers snowmelt, the model simulations of spring runoff in the Hulan River Basin were not accurate. (3) There was a significant correlation between climate, the underlying surface, and hydrological model parameters. There were fewer significant correlations between environmental factors and between environmental factors and hydrological model parameters in the Hulan River Basin compared to those in the Poyang Lake Basin, possibly due to less sub-basins in the Hulan River Basin. (4) The HSI based on a combination of principal component analysis and the entropy method efficiently identified the most similar gauged basin for an ungauged basin. A significant positive correlation existed between the HSI and parameter transfer efficiency. The relationship between the HSI and transfer efficiency could be represented by logistic regression and linear regression in the Poyang Lake Basin and Hulan River Basin, respectively. The HSI was better able to quantify the hydrological similarity between basins in terms of climate and underlying surface and can provide a scientific reference for the transfer of hydrological model parameters in an ungauged basin.

scholarly journals Establishment and Analysis of Spatiotemporal Variation Hydrological Model of Distributed Rainfall and Evaporation in Biliu River Basin

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Qi Liu ◽  
Xiaolong Zhao ◽  
Hongyan Wang ◽  
Yongfeng Sun
Keyword(s):  
River Basin ◽  
River Runoff ◽  
Irrigation Water ◽  
Water Demand ◽  
Hydrological Model ◽  
Hydrological Cycle ◽  
Precipitation Process ◽  
Model Parameters ◽  
Runoff Simulation ◽  
Irrigation Water Demand

The Biliu River originates from the southern foot of Qinling Mountain in Gaizhou city, with an elevation of 1047 m, and is the largest river in Dalian. The hydrological elements mainly include rainfall, runoff, temperature, evaporation, and other time series associated with the hydrological cycle. Among them, runoff is the most visible output performance, and the direct source of runoff is during rainfall. This paper establishes a reservoir scheduling model that considers the influence of multiple uncertainty factors and analyzes the influence of mixed uncertainty on reservoir scheduling and Xingli’s objectives based on probability box theory. In terms of uncertainties, the uncertainty of hydrological model parameters and the randomness of precipitation processes are mainly considered, with the former having an impact on river runoff simulation and the latter having an impact on both river runoff simulation and crop irrigation water demand. In the case of the Jing River basin, for example, the results show that, compared to the stochasticity of the precipitation process, the variation in precipitation has a significant effect on irrigation water demand in maize, followed by the frequency of precipitation, and the interaction between the two is not significant.

scholarly journals Large watershed flood forecasting with high resolution distributed hydrological model

2016 ◽  
Author(s):  
Yangbo Chen ◽  
Ji Li ◽  
Huanyu Wang ◽  
Jianming Qin ◽  
Liming Dong
Keyword(s):  
High Resolution ◽  
River Basin ◽  
Spatial Resolution ◽  
Hydrological Model ◽  
Threshold Model ◽  
Grid Cell ◽  
Flood Forecasting ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Computation Efficiency

Abstract. Flooding is one of the most devastating natural disasters in the world with huge damages, and flood forecasting is one of the flood mitigation measurements. Watershed hydrological model is the major tool for flood forecasting, although the lumped watershed hydrological model is still the most widely used model, the distributed hydrological model has the potential to improve watershed flood forecasting capability. Distributed hydrological model has been successfully used in small watershed flood forecasting, but there are still challenges for the application in large watershed, one of them is the model’s spatial resolution effect. To cope with this challenge, two efforts could be made, one is to improve the model's computation efficiency in large watershed, another is implementing the model on high performance supercomputer. By employing Liuxihe Model, a physically based distributed hydrological model, this study sets up a distributed hydrological model for the flood forecasting of Liujiang River Basin in southern China that is a large watershed. Terrain data including DEM, soil type and land use type are downloaded from the website freely, and the model structure with a high resolution of 200 m * 200 m grid cell is set up. The initial model parameters are derived from the terrain property data, and then optimized by using the PSO algorithm, the model is used to simulate 29 observed flood events. It has been found that by dividing the river channels into virtual channel sections and assuming the cross section shapes as trapezoid, the Liuxihe Model largely increases computation efficiency while keeping good model performance, thus making it applicable in larger watersheds. This study also finds that parameter uncertainty exists for physically deriving model parameters, and parameter optimization could reduce this uncertainty, and is highly recommended. Computation time needed for running a distributed hydrological model increases exponentially at a power of 2, not linearly with the increasing of model spatial resolution, and the 200 m * 200 m model resolution is proposed for modeling Liujiang River Basin flood with Liuxihe Model in this study. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling Liujiang River Basin flood is 500 m * 500 m grid cell, but the model spatial resolution at 200 m * 200 m grid cell is recommended in this study to keep the model a better performance.

scholarly journals Climate Normalized Spatial Patterns of Evapotranspiration Enhance the Calibration of a Hydrological Model

2022 ◽  
Vol 14 (2) ◽  
pp. 315
Author(s):  
Julian Koch ◽  
Mehmet Cüneyd Demirel ◽  
Simon Stisen
Keyword(s):  
Spatial Pattern ◽  
River Basin ◽  
Spatial Patterns ◽  
Hydrological Model ◽  
Hydrological Cycle ◽  
Model Parameters ◽  
Climate Control ◽  
Spatial Efficiency ◽  
Senegal River ◽  
Senegal River Basin

Spatial pattern-oriented evaluations of distributed hydrological models have contributed towards an improved realism of hydrological simulations. This advancement has been supported by the broad range of readily available satellite-based datasets of key hydrological variables, such as evapotranspiration (ET). At larger scale, spatial patterns of ET are often driven by underlying climate gradients, and with this study, we argue that gradient dominated patterns may hamper the potential of spatial pattern-oriented evaluation frameworks. We hypothesize that the climate control of spatial patterns of ET overshadows the effect model parameters have on the simulated patterns. To address this, we propose a climate normalization strategy. This is demonstrated for the Senegal River basin as a modeling case study, where the dominant north-south precipitation gradient is the main driver of the observed hydrological variability. We apply the mesoscale Hydrological Model (mHM) to model the hydrological cycle of the Senegal River basin. Two multi-objective calibration experiments investigate the effect of climate normalization. Both calibrations utilize observed discharge (Q) in combination with remote sensing ET data, where one is based on the original ET pattern and the other utilizes the normalized ET pattern. As objective functions we applied the Kling-Gupta-Efficiency (KGE) for Q and the Spatial Efficiency (SPAEF) for ET. We identify parameter sets that balance the tradeoffs between the two independent observations and find that the calibration using the normalized ET pattern does not compromise the spatial pattern performance of the original pattern. However, vice versa, this is not necessarily the case, since the calibration using the original ET pattern showed a poorer performance for the normalized pattern, i.e., a 30% decrease in SPAEF. Both calibrations reached comparable performance of Q, i.e., KGE around 0.7. With this study, we identified a general shortcoming of spatial pattern-oriented model evaluations using ET in basins dominated by a climate gradient, but we argue that this also applies to other variables such as, soil moisture or land surface temperature.

scholarly journals Modeling of German Low Voltage Cables with Ground Return Path

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1265 ◽  
Author(s):  
Johanna Geis-Schroer ◽  
Sebastian Hubschneider ◽  
Lukas Held ◽  
Frederik Gielnik ◽  
Michael Armbruster ◽  
...  
Keyword(s):  
Low Voltage ◽  
Measurement Data ◽  
Analytical Calculation ◽  
Laboratory Measurement ◽  
Model Parameters ◽  
Calculation Methods ◽  
Modeling Approach ◽  
Measurement Results ◽  
Simulation Results ◽  
Return Path

In this contribution, measurement data of phase, neutral, and ground currents from real low voltage (LV) feeders in Germany is presented and analyzed. The data obtained is used to review and evaluate common modeling approaches for LV systems. An alternative modeling approach for detailed cable and ground modeling, which allows for the consideration of typical German LV earthing conditions and asymmetrical cable design, is proposed. Further, analytical calculation methods for model parameters are described and compared to laboratory measurement results of real LV cables. The models are then evaluated in terms of parameter sensitivity and parameter relevance, focusing on the influence of conventionally performed simplifications, such as neglecting house junction cables, shunt admittances, or temperature dependencies. By comparing measurement data from a real LV feeder to simulation results, the proposed modeling approach is validated.

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