Hydrodynamic River Model Research Articles

A Multiple Model Approach for Flood Forecasting, Simulation, and Evaluation Coupling in Zhouqu County

Flood disasters are considered to be one of the ten natural disasters that threaten the survival of mankind. They occur frequently and have a serious impact on the national economy. For quicker response to the sudden flood, in this paper, the relevant characteristics of flood forecasting and disaster assessment are comprehensively studied to establish the corresponding models, and a multi-objective culture shuffled complex differential evolution (MOCSCDE) algorithm is proposed to optimize the model parameters. It can achieve better convergence and significantly improve the model accuracy. Then, a river hydrodynamic model is established to simulate the flooding process, and the characteristics of flood evolution, such as water depth, flow speed, duration, and submerged area, are analyzed. Third, based on the above-mentioned flood forecasting and flood evolution calculations, the relative membership function (VFS) is determined via the set pair analysis method (SPA), and the variable fuzzy set model (SPAVFS) is used for flood risk assessment. Finally, through the study of flow forecasting at Zhouqu hydrological station, it is found that the accuracy of the forecast result of the built model is best compared with LSTM and XAJ model, the mean relative error is only 7.6%, and the certainty coefficient can reach 0.96, which surpass the baselines by 20% and 7.9%.

Co-occurrence of pluvial and fluvial floods exacerbates inundation and economic losses: evidence from a scenario-based analysis in Longyan, China

Hydrodynamics and socio-economic impacts of compound floods as the result of co-occurring pluvial and fluvial floods, have not been well studied, which challenges conventional urban flood risk management that treats different types of floods separately. This study generates a high-resolution land surface digital surface model based on images from unmanned aerial vehicles, and incorporates it into a combined flooding model that integrates the 1D river hydrodynamic model, 1D urban drainage hydrodynamic model and 2D overland flow model, in order to simulate the inundation characteristics of extreme floods when local pluvial floods coincide with upstream fluvial floods, and in a further step to quantify the direct economic losses on urban physical systems. As demonstrated by an empirical study of Longyan, China, the combination of pluvial and fluvial floods leads to substantial exacerbation in inundation extent and depth. Consequently, the joining of pluvial and fluvial floods greatly amplifies economic losses to urban physical systems, indicating that ignoring co-occurrence of different types of floods will potentially lead to underestimation of flood risk and insufficient adaptation. Our study emphasizes the need to account for the co-occurrence of multiple types of floods in flood risk assessment and management, to avoid the shortcomings of fragmented responses.

Risk assessment of harmful algal blooms (HAB) occurrence in the agroecosystem: A hydro-ecologic modeling framework and environmental risk matrix

This paper was aimed at assessing the risk of HAB occurrence in a highly cultivated watershed and evaluating the effectiveness of N and P fertilizer reduction practices in mitigating this risk under future climate projections. To achieve this objective, a modelling framework was developed for HAB risk assessment under different environmental stressors including climate changes and different land management practices. The modelling framework used a fully distributed physical-based hydrologic model, MIKE SHE, and a hydrodynamic river model, MIKE 11, coupled with ECO-Lab to simulate the fate and transport of different forms of N and P in the Upper Sangamon River Basin (USRB), a highly cultivated watershed in central Illinois. Three different land management scenarios based on the N and P reduction target in “The Gulf Hypoxia Action Plan” were simulated to assess the P nonpoint source behavior and HAB risk level in the USRB from 2020 to 2050 under extreme climate projections. Our results predicted that the HAB risk in USRB is relatively low even with increased bioavailable P (BAP) concentration and longer duration with high BAP concentration due to low water temperature. Reducing N or P application rates by 50% was able to offset the negative effects on HAB occurrence from extreme climate projections apart from spring. Within P and N, regulating P was found to be more effective in reducing HAB risks in the USRB while regulating N was more effective in controlling HAB downstream. Understanding the dynamics of N and P in causing the occurrence of HAB was expected to improve the mitigation measures that we implement at the field level.

Calibrating 1D hydrodynamic river models in the absence of cross-section geometry using satellite observations of water surface elevation and river width

Abstract. Hydrodynamic modeling has been increasingly used to simulate water surface elevation which is important for flood prediction and risk assessment. Scarcity and inaccessibility of in situ bathymetric information have hindered hydrodynamic model development at continental-to-global scales. Therefore, river cross-section geometry is commonly approximated by highly simplified generic shapes. Hydrodynamic river models require both bed geometry and roughness as input parameters. Simultaneous calibration of shape parameters and roughness is difficult, because often there are trade-offs between them. Instead of parameterizing cross-section geometry and hydraulic roughness separately, this study introduces a parameterization of 1D hydrodynamic models by combining cross-section geometry and roughness into one conveyance parameter. Flow area and conveyance are expressed as power laws of flow depth, and they are found to be linearly related in log–log space at reach scale. Data from a wide range of river systems show that the linearity approximation is globally applicable. Because the two are expressed as power laws of flow depth, no further assumptions about channel geometry are needed. Therefore, the hydraulic inversion approach allows for calibrating flow area and conveyance curves in the absence of direct observations of bathymetry and hydraulic roughness. The feasibility and performance of the hydraulic inversion workflow are illustrated using satellite observations of river width and water surface elevation in the Songhua river, China. Results show that this approach is able to reproduce water level dynamics with root-mean-square error values of 0.44 and 0.50 m at two gauging stations, which is comparable to that achieved using a standard calibration approach. In summary, this study puts forward an alternative method to parameterize and calibrate river models using satellite observations of river width and water surface elevation.

Impacts of climate change and sea level rise on catchment management: A multi-model ensemble analysis of the Nerang River catchment, Australia

Estimating the most likely impacts of climate change on the hydrological conditions of catchments is essential for efficient future water management. This is particularly important in Southeast Queensland, Australia, which is projected to be significantly impacted by climate change. We have developed an integrated catchment modelling framework for the Nerang River catchment that combines a hydrologic model, a reservoir operation model, and a hydrodynamic river model. The multi-model ensemble is used to investigate eight General Circulation Models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) under two representative concentration pathway scenarios (RCP 4.5 and RCP 8.5) over the baseline period (2000–2009) and one future period (2075–2084). Additionally, the tidal section of the Lower Nerang River was studied under coupled impacts of the RCP scenarios and sea level rise by 0.80 m. The ensemble projections over the future period present slight decreasing tendencies in the median of monthly long-term daily inflow to Hinze Dam in the upper Nerang River. Additionally, the average environmental releases of 7.25 ML/day are expected to reduce over the future period by 6.02% and 5.37% under RCP 4.5 and RCP 8.5, respectively compared to the baseline period. The hydrodynamic model results revealed that sea level rise is projected to have significant impact on water level variations at two river flooding alert sites, Carrara Alert and Evandale Alert. As a result, a 0.80 m sea level rise can increase ensemble water level projections by almost 0.75 m and 0.80 m at Carrara Alert and Evandale Alert sites, respectively, which will cause minor to major flooding events at Evandale Alert site. The outcomes of the present paper can assist the decision-makers and the community of the Nerang River catchment with a robust tool to evaluate climate change scenarios for sustainable future water resources management and allocation. • • An integrated catchment modelling framework was developed for SEQ, Australia. • • A hydrologic, reservoir, and a hydrodynamic river models were combined. • • Outputs from eight CMIP5 models and two RCPs were used for future projections. • • Slight decreases in dam inflow are projected in the future. • • Decreasing trends in environmental flow release are expected under climate change.

One dimensional hydrodynamic modelling of pamba river for identifying the flood vulnerability

Hydrodynamic modelling is a powerful tool to understand and analyse a river flow and its conditions. The identification of flood vulnerability areas of Pamba river helps to minimize the damages associated with the flood. A hydrodynamic river model was customised and calibrated for the river Pamba in Kerala using MIKE HYDRO River model. The model was calibrated using Manning’s roughness coefficient. In this study, we utilize the time series of daily discharge and water level of different gauging station of Centre Water Commission at Kallooppara, Malakkara, Thumpamon and water level data of Thottappalli spillway. The SRTM DEM was used to generate the flood model for the period June to August 2010. The model performance was assessed by comparing observed and stimulated water level at the upstream and downstream of the river. The correlation coefficient value obtained in the range of 0.53 to 0.94. The outcomes of the study can benefit future modelling effort through the provision of robust tool to predict water levels at various points of the river. This study can help the water resources policy makers for arriving at suitable mitigation measures.

Modeling field scale nitrogen non-point source pollution (NPS) fate and transport: Influences from land management practices and climate

The use of nitrogen (N) fertilizer marked the start of modern agriculture that boosted food production to help alleviate food shortages across the globe but at the cost of severe environmental issues and critical stress to the agroecosystem. This paper was aimed at determining the fate and transport of nitrite and ammonia under future climate projections by adapting the recommended land management practices that are supposed to reduce nitrate N in surface water to state government target. To accomplish these objectives, a fully-distributed physical-based hydrologic model, MIKE SHE, and a hydrodynamic river model, MIKE 11, were coupled with MIKE ECO-Lab to simulate the fate and transport of different forms of N in the agro-ecosystem in the Upper Sangamon River Basin (USRB). Twelve (12) combinations of land management and climate projections were simulated to evaluate the N fate and transport in the USRB from 2020 to 2050. Under the current land management, the nitrate concentration in surface water was expected to exceed the EPA limit of 10 ppm up to 2.5% of the days in the simulation period. Regulating the fertilizer application rates to approximately 50% of the current rate will ensure this limit will not be exceeded in the future. Implementing cover cropping alone can potentially decrease nitrate N concentrations by 33% in surface water under dry climate and in the saturated zone under future projections. By combining the cover cropping and regulated application rate management, the nitrate N concentration in the saturated zone was expected to decrease by 67% compared with historic baseline. The modeling framework developed and used in this study can help evaluate the effectiveness of different management schemes aimed at reducing future nutrient load in our surface water and groundwater.

Hydrodynamic modelling of a flood-prone tidal river using the 1D model MIKE HYDRO River: calibration and sensitivity analysis.

Hydrodynamic modelling is a powerful tool to gain understanding of river conditions. However, as widely known, models vary in terms of how they respond to changes and uncertainty in their input parameters. A hydrodynamic river model (MIKE HYDRO River) was developed and calibrated for a flood-prone tidal river located in South East Queensland, Australia. The model was calibrated using Manning's roughness coefficient for the normal dry and flood periods. The model performance was assessed by comparing observed and simulated water level, and estimating performance indices. Results indicated a satisfactory agreement between the observed and simulated results. The hydrodynamic modelling results revealed that the calibrated Manning's roughness coefficient ranged between 0.011 and 0.013. The impacts of tidal variation at the river mouth and the river discharge from upstream are the major driving force for the hydrodynamic process. To investigate the impacts of the boundary conditions, a new sensitivity analysis approach, based on adding stochastic terms (random noise) to the time series of boundary conditions, was conducted. The main purpose of such new sensitivity analysis was to impose changes in magnitude and time of boundary conditions randomly, which is more similar to the real and natural water level variations compared to impose constant changes of water level. In this new approach, the possible number of variations in simulated results was separately evaluated for both downstream and upstream boundaries under 5%, 10%, and 15% perturbation. The sensitivity analysis results revealed that in the river under study, the middle parts of the river were shown to be more sensitive to downstream boundary condition as maximum water level variations can reach 8%, 12%, and 15% under 5%, 10%, and 15% changes in the downstream boundary, respectively. The outcomes of the present paper will benefit future modelling efforts through provision of a robust tool to enable prediction of water levels at ungauged points of the river under various scenarios of flooding and climate change for the purpose of city planning and decision-making.

Modelling grass carp egg transport using a 3-D hydrodynamic river model: the role of egg retention in dead zones on spawning success

Invasive grass carp (Ctenopharyngodon idella) are known to spawn in the Sandusky River, Ohio, USA, within the Great Lakes Basin, and are threatening to expand throughout the Great Lakes. Successful spawning is thought to require that eggs remain in suspension until hatching, which depends on river hydrodynamics and temperature-dependent egg development. Previous modelling efforts used one-dimensional hydrodynamic models that simplify egg movement by not simulating low-velocity zones within the river. To examine the effect of low-velocity zones on egg transit times and hatching rates, we developed a novel coupling of a biophysical Lagrangian particle tracker and three-dimensional hydrodynamic model on the Sandusky River during a high-flow event. The model successfully predicted egg-capture data for a range of developmental stages and revealed a mechanism that resuspends eggs trapped in low-velocity zones. The resuspension mechanism increases the residence time of grass carp eggs in spawning tributaries and can lead to successful hatching occurring in shorter distances than previously estimated. Grass carp potentially spawning in shorter tributary lengths has widespread implications for efforts preventing establishment in the Great Lakes Basin.

Can regional to continental river hydrodynamic models be locally relevant? A cross-scale comparison

Regional to global river hydrodynamic models are now a reality, and have largely improved in the recent years due to increasing computation power, remote sensing datasets and new modeling methods. It is fundamental then to understand to which extent these models can provide locally relevant estimates of variables as discharge and water levels. It is addressed here by setting up three different versions of the large scale MGB hydrologic-hydrodynamic model with increasing spatial scale (global, regional and local), based on different topography datasets, cross section parameterization and reach lengths. These model versions are then compared to a detailed HEC-RAS model, set up with >620 locally surveyed cross sections in the Itajaí-Açu basin in Brazil. All models are run with calibrated rainfall-runoff parameters, so that effects of non-calibrated runoff fields or uncertain forcing data are not taken into consideration. To assist interpretation, three main requirements to define estimates from a river hydrodynamic model as locally relevant are defined: the model errors should be equal or smaller (i) than the accuracy requirement for a particular application and location, (ii) than typical local, reach scale models’ errors, and (iii) than observation uncertainties. Results then indicate that the regional and local MGB versions (and to a lesser extent, the global one) could estimate locally relevant discharges and water level anomalies for many parts of the basin. For absolute water levels, all models failed to provide RMSE smaller than 0.4 m basin-wide, although the local MGB model yields an average 2.1 m RMSE, in comparison to 4.4 m (regional) and 26.1 m (global). For flood extent, all model versions generally yielded unsatisfactory results with average Fit metric values smaller than 65%. Lastly, different setups of the regional MGB model were run to investigate the role of different factors in improving model estimates. Results showed that a coarse reach length (15 km) is unable to capture flood dynamics and water level variations in the basin, while a smaller 1 km long reach improves discharges, water level and flood extent. A locally derived DEM did not lead to significant improvements in relation to a global DEM. In turn, the smallest water level errors would be attained by using information from the in-situ cross sections in the regional models. This study’s outcomes are encouraging for the future development of regional to global hydrodynamic models, with new remote sensing techniques and higher computational power improving cross section estimation and model discretization.

Coupling of 1D models (SWAT and SWMM) with 2D model (iRIC) for mapping inundation in Brahmani and Baitarani river delta

River flooding has been causing extensive losses to life and property, which is a serious concern worldwide. To minimize these losses, suitable planning and management practices are required for the floodplain mapping. Flash floods occur almost every year in the deltaic region of Brahmani and Baitarani river basins in India, during the monsoon season. Generally, 1D modelling is considered as a regular practice. But nowadays, model formulations include 1D for the representation of river channels and 2D for representing river floodplains. In the absence of uniform observations, a hybrid model (1D–2D coupled model) has been developed for this deltaic region to identify the extent of inundation and its depth during the flooding, since 1D models alone do not provide detailed information of flooding. Thus, a well-known 2D river hydrodynamic model iRIC was externally coupled with 1D (SWAT and SWMM) models to simulate and visualize flood scenarios and to identify the flood-prone areas. The hydrological model SWAT was calibrated and validated for Brahmani river deltaic basin, with the observed discharge data available. However for Baitarani river basin, observed flow data were missing and only gauge data were available at few monitoring stations. Hence, for Baitarani river basin, the SWMM model was developed and calibrated with the help of Monte Carlo method. Finally, the SWAT- and SWMM-based tributary stream flow outputs were fed together into the iRIC hydrodynamic model as input for flood inundation mapping. The discharge and water gauge data were used for the calibration and validation. The results obtained from the coupled model were found to be in good agreement with the observed data (RMSE value is 0.77 and 0.79 during calibration and validation, respectively), which enabled identification of the flood-prone areas. The developed model may be used as a tool for effective planning and management of natural disasters such as flash floods.

Surrogate modeling-based calibration of hydrodynamic river model parameters

As opposed to other disciplines, automated calibration procedures are not common practice for full hydrodynamic river models, mainly because of the long computation times impeding the accurate assessment of parameter values. Default or text-book values are therefore often used. This paper introduces a methodology to optimize hydrodynamic model parameter values, based on the use of a surrogate conceptual model. Thanks to the spatial lumping and the explicit calculation schemes of these conceptual models, very short calculation times and a large number of simulation runs can be achieved. The surrogate model is coupled with the Shuffled Complex Evolution Metropolis algorithm of the University of Arizona (SCEM-UA) to identify the optimal parameter sets and their uncertainty. Afterwards, the optimized parameter values are transferred to the full hydrodynamic model. The methodology is demonstrated on a case study of the river Molenbeek in Belgium, using streamflow, water level and gate level observations. Results show a decrease of the hydrodynamic model residuals by about 60 percent.

Time of concentration for large catchment based on hydrodynamic modelling

Flood mitigation design requires accurate computation of discharge at any interest location to sustain the protection level. The design flood hydrograph generates from rainfall runoff model which used unit hydrograph method depends on the time of concentration (Tc) of the catchment. Common factors which influence Tc are the catchment properties including length, slope, soil properties and surface cover. However, when dealing with large catchment, more complex factors which also requires attention are the rainfall intensity, catchment wetness and initial water in the channel due to rain prior to the storm event. For large catchment, the travelling time which govern the Tc is more dominant in the channel rather than on the soil surface. Since water flowing in the river channel is unsteady and nonuniform, the use of Manning formula is inappropriate. This paper explains the application of hydrodynamic modelling approach to determine Tc for large catchment with long river channel. A hydrodynamic river model for Sg Relai, Kelantan with area of 460 km2 and covering 90 km distance was developed using InfoWorks ICM. Results shown that as the rain intensity increased, the travelling time will be shortened. The traveling time also reduce when initial water level in the channel increase which indicate that Tc will reduce if the catchment already received some rainfall prior to the storm event. Based on this analysis and results, the use of hydrodynamic model as part of the rainfall runoff model is significant for large catchment to handle complex factor such as wide range of rainfall intensity, spatial effect and catchment wetness.

A data assimilation system combining CryoSat-2 data and hydrodynamic river models

There are numerous hydrologic studies using satellite altimetry data from repeat-orbit missions such as Envisat or Jason over rivers. This study is one of the first examples for the combination of altimetry from drifting-ground track satellite missions, namely CryoSat-2, with a river model. CryoSat-2 SARIn Level 2 data is used to improve a 1D hydrodynamic model of the Brahmaputra River in South Asia, which is based on the Saint-Venant equations for unsteady flow and set up in the MIKE HYDRO River software. After calibration of discharge and water level the hydrodynamic model can accurately and bias-free represent the spatio-temporal variations of water levels. A data assimilation framework has been developed and linked with the model. It is a flexible framework that can assimilate water level data which are arbitrarily distributed in time and space. The setup has been used to assimilate CryoSat-2 water level observations over the Assam valley for the years 2010–2015, using an Ensemble Transform Kalman Filter (ETKF). Performance improvement in terms of discharge forecasting skill was then evaluated. For experiments with synthetic CryoSat-2 data the continuous ranked probability score (CRPS) was improved by up to 32%, whilst for experiments assimilating real data it could be improved by up to 10%. The developed methods are expected to be transferable to other rivers and altimeter missions. The model setup and calibration is based almost entirely on globally available remote sensing data.

Flood Response System—A Case Study

Flood Response System (FRS) is a network-enabled solution developed using open-source software. The system has query based flood damage assessment modules with outputs in the form of spatial maps and statistical databases. FRS effectively facilitates the management of post-disaster activities caused due to flood, like displaying spatial maps of area affected, inundated roads, etc., and maintains a steady flow of information at all levels with different access rights depending upon the criticality of the information. It is designed to facilitate users in managing information related to flooding during critical flood seasons and analyzing the extent of damage. The inputs to FRS are provided using two components: (1) a semi-automated application developed indigenously, to delineate inundated areas for Near-Real Time Flood Monitoring using Active Microwave Remote Sensing data and (2) a two-dimensional (2D) hydrodynamic river model generated outputs for water depth and velocity in flooded areas for an embankment breach scenario. The 2D Hydrodynamic model, CCHE2D (Center for Computational Hydroscience and Engineering Two-Dimensional model), was used to simulate an area of 600 km2 in the flood-prone zone of the Brahmaputra basin. The resultant inundated area from the model was found to be 85% accurate when validated with post-flood optical satellite data.

Depth-dependent hydraulic roughness and its impact on the assessment of hydropeaking

Hydrodynamic river models in combination with physical habitat modelling serve as the basis for a wide spectrum of environmental studies. Larvae, juvenile and spawning fish, redds and benthic invertebrates belong to the biological groups most heavily affected by rapid flow variations as a consequence of peaking energy production, or “hydropeaking”. As these species find their preferential habitat to a great extent in shallow regions, high prediction accuracy for these areas is essential to substantiate the use of hydrodynamic models. In this paper, a new formulation for the depth-dependent roughness originating from the boundary layer theory is derived. The modelling approach is based on the concept of a dynamic, spatio-temporal Manning's roughness which allows for considerable improvement in the accuracy of stationary and highly transient hydrodynamic simulations in shallow river areas. In addition, the approach facilitates more effective model calibration, as it allows for the preservation of the roughness sublayer thickness as a single calibration parameter for the entire range of hydropeaking discharges. The approach is tested and validated on a 7.5km long stretch of a middle-size gravel river affected by hydropeaking. Model results using conventional constant roughness and the proposed dynamic roughness approaches are compared. The implications for the stationary habitat assessment and calculation of dynamic hydropeaking parameters are analysed as well.

Accuracy Assessment of Very High-Resolution Multispectral Images Derived Data for River Flow Modelling

The increased frequency of disaster events and the need for a rapid response for the prevention and remediation of flood disasters require realization of flood risk maps with very good precision based on high performance hydrodynamic river models using advanced hydroinformatics tools. Modelling performance, topographical data quality and quantity, hydrological and hydro meteorological surveys as well have very important for correct understanding and interpretation of all hydraulic aspects for minor and major riverbed. These are key factors in the need for new sources of data for hydrological modelling and flood risks management process. In this regard the actually development of satellite sensors, data, availability, Geographic Information System (GIS), and on the Hydroinformatics based river flow modelling techniques gives new opportunities in the analysis of the floods phenomenon. Use of the Very High Resolution remote sensing raster images to derive data useful for hydrological modelling is inviting and the answer to the question of accuracy of the data derived from remote sensing images is very important.In the present paper is investigated the methodology for using of multispectral satellite images acquired by Worldview2, SPOT 6 and SPOT 7 sensors for deriving hydrological model data and its corresponding accuracies. A case study using multispectral images related to rivers Timiş, Bega and Timiş-Bega canal in Romania and river flow model is foreseen for the future to verify the results of the methodology.

Dealing with rainfall forecast uncertainties in real-time flood control along the Demer river

Real-time Model Predictive Control (MPC) of hydraulic structures strongly reduces flood consequences under ideal circumstances. The performance of such flood control may, however, be significantly affected by uncertainties. This research quantifies the influence of rainfall forecast uncertainties and related uncertainties in the catchment rainfall-runoff discharges on the control performance for the Herk river case study in Belgium. To limit the model computational times, a fast conceptual model is applied. It is calibrated to a full hydrodynamic river model. A Reduced Genetic Algorithm is used as optimization method. Next to the analysis of the impact of the rainfall forecast uncertainties on the control performance, a Multiple Model Predictive Control (MMPC) approach is tested to reduce this impact. Results show that the deterministic MPC-RGA outperforms the MMPC and that it is inherently robust against rainfall forecast uncertainties due to its receding horizon strategy.

Modelling the time variance of the river bed roughness coefficient for improved simulation of water levels

ABSTRACTAquatic macrophytes create seasonally variable changes in river bed roughness. These changes in roughness influence the hydrodynamic behaviour of the river, for example, elevated water levels for the same discharge. In most hydrodynamic river models, the roughness is assumed constant in time, which may lead to high errors in the river water level results. When the river water level results are applied to water quality studies, biased estimates may be obtained of river flow velocities, dilution and other water quality processes. This article investigates how models implemented in two common hydrodynamic modelling software packages (MIKE11 and InfoWorks RS) can be adopted to take into account the time-varying river bed roughness due to plant growth. Albeit the use of a different approach by the two models, it is shown that both can account for that influence. After application to the Grote Nete river catchment in Belgium, far more accurate river water level results are obtained. Overall, the increase in accuracy of the water level simulations outweighs the increase in model complexity required to enable simulation of the vegetation changes. The model results can also be used to correct discharge estimates based on the measured water levels as shown for this case study.

Development of a River Hydrodynamic Model for Studying Surface-Ground Water Interactions Affected by Climate Change in Heihe River, China

Zhu, F.; Huang, W.; Cai, Y.; Teng, F.; Wang, B., and Zhou, Q., 2014. Development of a river hydrodynamic model for studying surface-ground water interactions affected by climate change in Heihe River, China.Over the past 50 years, glacier area in Qilian Mountain of the Heihe River basin has decreased by 29.6%, mainly resulting from the climate change. Understanding the interactions of surface and ground water interaction will be very helpful for studying climate-change impact on Hehei River basin. This paper presents the development of one-dimensional river hydrodynamic model for surface and ground water interactions (RHM-SG). Surface-water flow is described by the modified one-dimensional Saint Venant equations, which is solved by Preissmann scheme. The flow exchange between surface and ground water is described by Darcy's equation. Five model validation tests include uniform flow over sloping bed, one flood process, and river flow with interactions of ground water. Model tests demonstrate that the model compares well with analytic solution, and reasonably characterize the interaction between river flow and ground water. The model has also been tested in the application to the middle reach of the Heihe River. By including surface-ground water interactions, the accuracy of model predicted flow substantially improves. The correlation coefficient increases from 0.89 to 0.98, and the root-mean-square reduces from 21.16 m3/s to 8.49 m3/s, respectively.