Anthropogenically induced land use/land cover(LULC)transformations and accelerating climatic variabilities have emerged as pivotal forces reshaping the hydrological equilibrium of fluvial systems,particularly in ecolo...Anthropogenically induced land use/land cover(LULC)transformations and accelerating climatic variabilities have emerged as pivotal forces reshaping the hydrological equilibrium of fluvial systems,particularly in ecologically sensitive basins.This study systematically interrogates the compounded ramifications of LULC dynamics and projected climate change on the hydrological response of the Upper Jemma Watershed an integral sub-catchment of the Upper Blue Nile River system.Employing the advanced QSWAT+hydrological modeling framework within a GIS interface,the analysis integrates bias‐corrected climatic projections under RCP 4.5 and RCP 8.5 scenarios alongside multi-temporal remote sensing‐derived land cover datasets.The findings unveil an unequivocal intensification of surface runoff and streamflow due to expansive agricultural encroachment,juxtaposed with a discernible decline in evapotranspiration and soil water retention.Climatic perturbations,notably temperature elevation and precipitation attenuation,further exacerbate these trends,with pronounced seasonality in hydrological fluxes.Importantly,synergistic interactions between land cover transformation and climatic anomalies manifest in nonlinear hydrological alterations,amplifying peak flows and diminishing baseflows.This underscores the riverine system's heightened vulnerability and the necessity for integrated watershed management strategies that account for multifactorial hydrological stressors.The study provides a robust empirical and modeling basis to inform adaptive water governance within transboundary river basins susceptible to environmental transitions.展开更多
It is an important standard to judge the flood disaster in the basin whether the rainfall at the flood-inducing interface is reached.In this paper,the Xin'anjiang model,Topmodel model and SCS model were selected t...It is an important standard to judge the flood disaster in the basin whether the rainfall at the flood-inducing interface is reached.In this paper,the Xin'anjiang model,Topmodel model and SCS model were selected to calculate and compare the rainfall at the flood-inducing interface in the Zhanghe Reservoir basin in Hubei Province.The results showed that average relative error and average absolute error of Xin'anjiang model were-3.36%and-21.46×10^(5)m^(3),which were the minimum,followed by Topmodel model with 5.72%and 26.22×10^(5)m^(3),SCS model with 11.33%and 58.13×10^(5)m^(3).The minimum absolute error of the three hydrological models in calculating the rainfall at the critical interface was 3.26 mm,while the maximum was 49.24 mm.When the initial water level exceeded 120 m,the difference among the three models in calculating the rainfall at the critical interface became more and more obvious.When the reservoir water level was lower than 120 m,it mainly referred to the calculation results of Xin'anjiang model.When the reservoir water level was higher than 120 m,it mainly referred to the calculation results of Topmodel model.The research conclusion can provide reference for small and medium-sized basins selecting hydrological model to calculate the rainfall at the flood-inducing interface.展开更多
Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global L...Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global Land Data Assimilation System (GLDAS),the Famine Early Warning System Network Land Data Assimilation System (FLDAS),the National Centers for Environmental Prediction (NCEP),and the WaterGAP Global Hydrology Model (WGHM).Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series,satellite gravity field Mascon solutions,and Global Precipitation Climatology Centre (GPCC) guide our assessment.Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP.In the Amazon River Basin,a 5-month lag between FLDAS,GLDAS,and satellite gravity results is observed.In eastern Asia and Australia,NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models.Three combined hydrological models (H-VCE,H-EWM,and H-CVM) utilizing Variance Component Estimation (VCE),Entropy Weight Method (EWM),and Coefficient of Variation Method (CVM) are formulated.Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%-17%.Correlation with precipitation increases by 25%-30%,and with satellite gravity,rises from 0.2 to 0.8 at maximum.The combined model eliminates time lag in the Amazon Basin TWSC analysis,exhibiting a four times higher signal-to-noise ratio than single models.H-VCE demonstrates the highest accuracy.In summary,the combined hydrological model minimizes discrepancies among individual models,significantly improving accuracy for monitoring large-scale TWSC.展开更多
Hydrological modeling plays a crucial role in efficiently managing water resources and understanding the hydrologic behavior of watersheds. This study aims to simulate daily streamflow in the Godavari River Basin in M...Hydrological modeling plays a crucial role in efficiently managing water resources and understanding the hydrologic behavior of watersheds. This study aims to simulate daily streamflow in the Godavari River Basin in Maharashtra using the Soil and Water Assessment Tool (SWAT). SWAT is a process-based hydrological model used to predict water balance components, sediment levels, and nutrient contamination. In this research, we used integrated remote sensing and GIS data, including Digital Elevation Models (DEM), land use and land cover (LULC) maps, soil maps, and observed precipitation and temperature data, as input for developing the SWAT model to assess surface runoff in this large river basin. The Godavari River Basin under study was divided into 25 sub-basins, comprising 151 hydrological response units categorized by unique land cover, soil, and slope characteristics using the SWAT model. The model was calibrated and validated against observed runoff data for two time periods: 2003-2006 and 2007-2010 respectively. Model performance was assessed using the Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R2). The results show the effectiveness of the SWAT2012 model, with R2 value of 0.84 during calibration and 0.86 during validation. NSE values also ranged from 0.84 during calibration to 0.85 during validation. These findings enhance our understanding of surface runoff dynamics in the Godavari River Basin under study and highlight the suit-ability of the SWAT model for this region.展开更多
Flood forecasting is critical for mitigating flood damage and ensuring a safe operation of hydroelectric power plants and reservoirs.This paper presents a new hybrid hydrological model based on the combination of the ...Flood forecasting is critical for mitigating flood damage and ensuring a safe operation of hydroelectric power plants and reservoirs.This paper presents a new hybrid hydrological model based on the combination of the Hydrologic Engineering Center-Hydrologic Modeling System(HEC-HMS)hydrological model and an Encoder-Decoder-Long Short-Term Memory network to enhance the accuracy of real-time flood forecasting.The proposed hybrid model has been applied to the Krong H'nang hydropower reservoir.The observed data from 33 floods monitored between 2016 and 2021 are used to calibrate,validate,and test the hybrid model.Results show that the HEC-HMS-artificial neural network hybrid model significantly improves the forecast quality,especially for results at a longer forecasting time.In detail,the Kling-Gupta efficiency(KGE)index,for example,increased from ΔKGE=16%at time t+1h to ΔKGE=69%at time t+6 h.Similar results were obtained for other indicators including peak error and volume error.The computer program developed for this study is being used in practice at the Krong H'nang hydropower to aid in reservoir planning,flood control,and water resource efficiency.展开更多
The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex s...The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects：uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.展开更多
The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission （TRMM） data with rain gauge data and further to use this TRMM data to drive a Dis- tributed Time-Variant Gain Model （DT...The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission （TRMM） data with rain gauge data and further to use this TRMM data to drive a Dis- tributed Time-Variant Gain Model （DTVGM） to perform hydrological simulations in the semi-humid Weihe River catchment in China. Before the simulations, a comparison with a 10-year （2001-2010） daily rain gauge data set reveals that, at daily time step, TRMM rainfall data are better at capturing rain occurrence and mean values than rainfall extremes. On a monthly time scale, good linear relationships between TRMM and rain gauge rainfall data are found, with determination coefficients R2 varying between 0.78 and 0.89 for the individual stations. Subsequent simulation results of seven years （2001-2007） of data on daily hydro- logical processes confirm that the DTVGM when calibrated by rain gauge data performs better than when calibrated by TRMM data, but the performance of the simulation driven by TRMM data is better than that driven by gauge data on a monthly time scale. The results thus suggest that TRMM rainfall data are more suitable for monthly streamfiow simulation in the study area, and that, when the effects of recalibration and the results for water balance components are also taken into account, the TRMM 3B42-V7 product has the potential to perform well in similar basins.展开更多
Actual evapotranspiration is a key process of hydrological cycle and a sole term that links land surface water balance and land surface energy balance.Evapotranspiration plays a key role in simulating hydrological eff...Actual evapotranspiration is a key process of hydrological cycle and a sole term that links land surface water balance and land surface energy balance.Evapotranspiration plays a key role in simulating hydrological effect of climate change,and a review of evapotranspiration estimation methods in hydrological models is of vital importance.This paper firstly summarizes the evapotranspiration estimation methods applied in hydrological models and then classifies them into the integrated converting methods and the classification gathering methods by their mechanism.Integrated converting methods are usually used in hydrological models and two differences exist among them:one is in the potential evaporation estimation methods,while the other in the function for defining relationship between potential evapora tion and actual evapotranspiration.Due to the higher information requirements of the Pen-man-Monteith method and the existing data uncertainty,simplified empirical methods for calculating potential and actual evapotranspiration are widely used in hydrological models.Different evapotranspiration calculation methods are used depending on the complexity of the hydrological model,and importance and difficulty in the selection of the most suitable evapotranspiration methods is discussed.Finally,this paper points out the prospective de velopment trends of the evapotranspiration estimating methods in hydrological modeling.展开更多
Considering a detailed hydrologic model in the land surface scheme helps to improve the simulation of regional hydro-climatology. A hydrologic model, which includes spatial heterogeneities in precipitation and infiltr...Considering a detailed hydrologic model in the land surface scheme helps to improve the simulation of regional hydro-climatology. A hydrologic model, which includes spatial heterogeneities in precipitation and infiltration, is constructed and incorporated into the land surface scheme BATS. Via the coupled-model (i.e., a regional climate model) simulations, the following major conclusions are obtained: the simulation of surface hydrology is sensitive to the inclusion of heterogeneities in precipitation and infiltration; the runoff ratio is increased after considering the infiltration heterogeneity, a result which is more consistent with the observations of surface moisture balance over humid areas; the introduction of the parameterization of infiltration heterogeneity can have a greater influence on the regional hydro-climatology than the precipitation heterogeneity; and the consideration of the impermeable fraction for the region reveals some features that are closer to the trend of aridification over northern China.展开更多
Accurate estimation of evapotranspiration(ET),especially at the regional scale,is an extensively investigated topic in the field of water science. The ability to obtain a continuous time series of highly precise ET va...Accurate estimation of evapotranspiration(ET),especially at the regional scale,is an extensively investigated topic in the field of water science. The ability to obtain a continuous time series of highly precise ET values is necessary for improving our knowledge of fundamental hydrological processes and for addressing various problems regarding the use of water. This objective can be achieved by means of ET data assimilation based on hydrological modeling. In this paper,a comprehensive review of ET data assimilation based on hydrological modeling is provided. The difficulties and bottlenecks of using ET,being a non-state variable,to construct data assimilation relationships are elaborated upon,with a discussion and analysis of the feasibility of assimilating ET into various hydrological models. Based on this,a new easy-to-operate ET assimilation scheme that includes a water circulation physical mechanism is proposed. The scheme was developed with an improved data assimilation system that uses a distributed time-variant gain model(DTVGM),and the ET-soil humidity nonlinear time response relationship of this model. Moreover,the ET mechanism in the DTVGM was improved to perfect the ET data assimilation system. The new scheme may provide the best spatial and temporal characteristics for hydrological states,and may be referenced for accurate estimation of regional evapotranspiration.展开更多
In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments （data are non-continuous and fragmental ...In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments （data are non-continuous and fragmental in some catchments）, we used non-continuous calibration periods for more independent streamflow data for SIMHYD （simple hydrology） model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization （PSO） method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years, randomly sampled, were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. In general, eight years of data are sufficient to obtain steady estimates of model performance and parameters for the SIMHYD model. It is also shown that most humid catchments require fewer calibration data to obtain a good performance and stable parameter values. The model performs better in humid and semi-humid catchments than in arid catchments. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.展开更多
An application of multi-objective particle swarm optimization （MOPSO） algorithm for optimization of the hydrological model （HYMOD） is presented in this paper. MOPSO algorithm is used to find non-dominated solution...An application of multi-objective particle swarm optimization （MOPSO） algorithm for optimization of the hydrological model （HYMOD） is presented in this paper. MOPSO algorithm is used to find non-dominated solutions with two objectives： high flow Nash-Sutcliffe efficiency and low flow Nash- Sutcliffe efficiency. The two sets＇ coverage rate and Pareto front spacing metric are two criterions to analyze the performance of the algorithms. MOPSO algorithm surpasses multi-objective shuffled complex evolution metcopolis （MOSCEM_UA） algorithr~, in terms of the two sets＇ coverage rate. But when we come to Pareto front spacing rate, the non-dominated solutions of MOSCEM_ UA algorithm are better-distributed than that of MOPSO algorithm when the iteration is set to 40 000. In addition, there are obvious conflicts between the two objectives. But a compromise solution can be acquired by adopting the MOPSO algorithm.展开更多
Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed...Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.展开更多
This study simulated and predicted the runoff of the Aksu River Basin, a typical river basin supplied by snowmelt in an arid mountain region, with a limited data set and few hydrological and meteorological stations. T...This study simulated and predicted the runoff of the Aksu River Basin, a typical river basin supplied by snowmelt in an arid mountain region, with a limited data set and few hydrological and meteorological stations. Two hydrological models, the snowmelt-runoff model （SRM） and the Danish NedbФr-AfstrФmnings rainfall-runoff model （NAM）, were used to simulate daily discharge processes in the Aksu River Basin. This study used the snow-covered area from MODIS remote sensing data as the SRM input. With the help of ArcGIS software, this study successfully derived the digital drainage network and elevation zones of the basin from digital elevation data. The simulation results showed that the SRM based on MODIS data was more accurate than NAM. This demonstrates that the application of remote sensing data to hydrological snowmelt models is a feasible and effective approach to runoff simulation and prediction in arid unguaged basins where snowmelt is a major runoff factor.展开更多
Intense human activities have greatly changed the flood generation conditions in most areas of the world, and have destroyed the consistency in the annual flood peak and volume series. For design flood estimation, coa...Intense human activities have greatly changed the flood generation conditions in most areas of the world, and have destroyed the consistency in the annual flood peak and volume series. For design flood estimation, coaxial correlation diagram and conceptual hydrological model are two frequently used tools to adjust and reconstruct the flood series under human disturbance. This study took a typical mountain catchment of the Haihe River Basin as an example to investigate the effects of human activities on flood regime and to compare and assess the two adjustment methods. The main purpose is to construct a conceptual hydrological model which can incorporate the effects of human activities. The results show that the coaxial correlation diagram is simple and widely-used, but can only adjust the time series of total flood volumes. Therefore, it is only applicable under certain conditions(e.g. There is a strong link between the flood peaks and volumes and the link is not significantly affected by human activities). The conceptual model is a powerful tool to adjust the time series of both flood peak flows and flood volumes over different durations provided that it is closely related to the catchment hydrological characteristics, specifically accounting for the effects of human activities, and incorporating expert knowledge when estimating or calibrating parameters. It is suggested that the two methods should be used together to cross check each other.展开更多
The Ganga River, the longest river in India, is stressed by extreme anthropogenic activity and climate change, particularly in the Varanasi region. Anticipated climate changes and an expanding populace are expected to...The Ganga River, the longest river in India, is stressed by extreme anthropogenic activity and climate change, particularly in the Varanasi region. Anticipated climate changes and an expanding populace are expected to further impede the efficient use of water. In this study, hydrological modeling was applied to Soil and Water Assessment Tool （SWAT） modeling in the Ganga catchment, over a region of 15 621.612 km2 in the southern part of Uttar Pradesh. The primary goals of this study are： ① To test the execution and applicability of the SWAT model in anticipating runoff and sediment yield; and ② to compare and determine the best calibration algorithm among three popular algorithms-sequential uncertainty fitting version 2 （SUFI-2）, the generalized likelihood uncertainty estimation （GLUE）, and par-allel solution （ParaSol）. The input data used in the SWAT were the Shuttle Radar Topography Mission （SRTM） digital elevation model （DEM）, Landsat-8 satellite imagery, soil data, and daily meteorological data. The watershed of the study area was delineated into 46 sub-watersheds, and a land use/land cover （LULC） map and soil map were used to create hydrological response units （HRUs）. Models utilizing SUFI- 2, GLUE, and ParaSol methods were constructed, and these algorithms were compared based on five cat-egories： their objective functions, the concepts used, their performances, the values of P-factors, and the values of R-factors. As a result, it was observed that SUFI-2 is a better performer than the other two algo-rithms for use in calibrating Indian watersheds, as this method requires fewer runs for a computational model and yields the best results among the three algorithms. ParaSol is the worst performer among the three algorithms. After calibrating using SUFI-2, five parameters including the effective channel hydraulic conductivity （CH_K2）, the universal soil-loss equation （USLE） support parameter （USLE_P）, Manning＇s n value for the main channel （CH_N2）, the surface runoff lag time （SURLAG）, and the available water capac-ity of the soil layer （SOL_AWC） were observed to be the most sensitive parameters for modeling the pre-sent watershed. It was also found that the maximum runoff occurred in sub-watershed number 40 （SW#40）, while the maximum sediment yield was 50 t.a ^1 for SW#36, which comprised barren land. The average evapotranspiration for the basin was 411.55 mm.a ^1. The calibrated model can be utilized in future to facilitate investigation of the impacts of LULC, climate change, and soil erosion.展开更多
The city of Bouaké, the second biggest city of Côte d’Ivoire, experienced a water shortage in 2018 that lasted four months due to the drying up of the Loka reservoir, which supplies two-thirds of the c...The city of Bouaké, the second biggest city of Côte d’Ivoire, experienced a water shortage in 2018 that lasted four months due to the drying up of the Loka reservoir, which supplies two-thirds of the city. The challenge of the Loka reservoir is that it is located in an ungauged basin where very few hydrological studies have been carried out, despite the recurrent problems of access to drinking water. In the purpose to better understand the phenomena that caused this temporary drying of the dam, the methodology implemented was based on agro-hydrological modeling with SWAT using a regionalization technique of a nearby watershed. The model performance was assessed using three statistical indices (the Nash-Sutcliffe coefficient (NS), the coefficient of determination (R<sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;">) and the percentage of bias (PBIAS)) and the visual appreciation of hydrographs for monthly series. The statistical indices appear satisfactory with a NS and R</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> ≥ 0.6 both for calibration and validation, and a PBIAS of </span><span style="font-family:;" "=""><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">11.2 and </span><span style="font-family:Verdana;">-</span><span><span style="font-family:Verdana;">3.8 respectively for calibration and validation. The hydrological modeling of Loka basin has shown the impact of climate change already reported by some authors as well as anthropization. Thus, while the reservoir records a decrease in its water volume estimated at 384,604 m</span><sup><span style="font-family:Verdana;">3</span></sup><span style="font-family:Verdana;"> each year, the water demand undergoes an increase of 122,033 m</span><sup><span style="font-family:Verdana;">3</span></sup><span style="font-family:Verdana;"> per year.</span></span></span>展开更多
Water is a vital resource, and can also sometimes be a destructive force. As such, it is important to manage this resource. The prediction of stream flows is an important component of this management. Hydrological mod...Water is a vital resource, and can also sometimes be a destructive force. As such, it is important to manage this resource. The prediction of stream flows is an important component of this management. Hydrological models are very useful in accomplishing this task. The objective of this study is to develop and apply an optimization method useful for calibrating a deterministic model of the daily flows of the Miramichi River watershed (New Brunswick). The model used is the CEQUEAU model. The model is calibrated by applying a genetic algorithm. The Nash-Sutcliffe efficiency criterion, modified to penalize physically unrealistic results, was used as the objective function. The model was calibrated using flow data (1975-2000) from a gauging station on the Southwest Miramichi River (catchment area of 5050 km2), obtaining a Nash-Sutcliffe criterion of 0.83. Model validation was performed using flow data (2001-2009) from the same station (Nash-Sutcliffe criterion value of 0.80). This suggests that the model calibration is sufficiently robust to be used for future predictions. A second model validation was performed using data from three other measuring stations on the same watershed. The model performed well in all three additional locations (Nash-Sutcliffe criterion values of 0.77, 0.76 and 0.74), but was performing less well when applied to smaller sub-basins. Nonetheless, the relatively strong performance of the model suggests that it could be used to predict flows anywhere in the watershed, but caution is suggested for applications in small sub-basins. The performance of the CEQUEAU model was also compared to a simple benchmark model (average of each calendar day). A sensitivity analysis was also performed.展开更多
The spatial distribution of soil physical properties is essential for modeling and understanding hydrological processes. In this study, the different spatial information (the conventional soil types map-based spatial ...The spatial distribution of soil physical properties is essential for modeling and understanding hydrological processes. In this study, the different spatial information (the conventional soil types map-based spatial information (STMB) versus refined spatial information map (RSIM)) of soil physical properties, including field capacity, soil porosity and saturated hydraulic conductivity are used respectively as input data for Water Flow Model for Lake Catchment (WATLAC) to determine their effectiveness in simulating hydrological processes and to expound the effects on model performance in terms of estimating groundwater recharge, soil evaporation, runoff generation as well as partitioning of surface and subsurface water flow. The results show that: 1) the simulated stream flow hydrographs based on the STMB and RSIM soil data reproduce the observed hydrographs well. There is no significant increase in model accuracy as more precise soil physical properties information being used, but WATLAC model using the RSIM soil data could predict more runoff volume and reduce the relative runoff depth errors; 2) the groundwater recharges have a consistent trend for both cases, while the STMB soil data tend to produce higher groundwater recharges than the RSIM soil data. In addition, the spatial distribution of annual groundwater recharge is significantly affected by the spatial distribution of soil physical properties; 3) the soil evaporation simulated using the STMB and RSIM soil data are similar to each other, and the spatial distribution patterns are also insensitive to the spatial information of soil physical properties; and 4) although the different spatial information of soil physical properties does not cause apparent difference in overall stream flow, the partitioning of surface and subsurface water flow is distinct. The implications of this study are that the refined spatial information of soil physical properties does not necessarily contribute to a more accurate prediction of stream flow, and the selection of appropriate soil physical property data needs to consider the scale of watersheds and the level of accuracy required.展开更多
Digital elevation models （DEMs） are widely used to define the flow direction in distributed hydrological models for simulation of streamflow. In recent decades, numerous methods for flow direction determination have...Digital elevation models （DEMs） are widely used to define the flow direction in distributed hydrological models for simulation of streamflow. In recent decades, numerous methods for flow direction determination have been applied successfully to mountainous regions. Nevertheless, some problems still exist when those methods are used for flat or gently sloped areas The present study reviews the conventional methods of determining flow direction for such landscapes and analyzes the problems of these methods. Two different methods of determining flow direction are discussed and were applied to the Xitiaoxi Catchment, located in the Taihu Basin in southern China, which has both mountainous and flat terrain. Both the agree method and the shortest path method use drainage networks derived from a remote sensing image to determine the correct location of the stream. The results indicate that the agree method provides a better fit with the DEM for the hilly region than the shortest path method. For the flat region where the flow has been diverted and rerouted by land managers, both methods require observation of the drainage network to determine the flow direction. In order to clarify the applicability of the two methods, both are employed in catchment hydrological models conceptually based on the Xinanjiang model and implemented with PCRaster. The simulation results show that both methods can be successfully applied in hydrological modeling. There are no evident differences in the modeled discharge when using the two methods at different spatial scales.展开更多
文摘Anthropogenically induced land use/land cover(LULC)transformations and accelerating climatic variabilities have emerged as pivotal forces reshaping the hydrological equilibrium of fluvial systems,particularly in ecologically sensitive basins.This study systematically interrogates the compounded ramifications of LULC dynamics and projected climate change on the hydrological response of the Upper Jemma Watershed an integral sub-catchment of the Upper Blue Nile River system.Employing the advanced QSWAT+hydrological modeling framework within a GIS interface,the analysis integrates bias‐corrected climatic projections under RCP 4.5 and RCP 8.5 scenarios alongside multi-temporal remote sensing‐derived land cover datasets.The findings unveil an unequivocal intensification of surface runoff and streamflow due to expansive agricultural encroachment,juxtaposed with a discernible decline in evapotranspiration and soil water retention.Climatic perturbations,notably temperature elevation and precipitation attenuation,further exacerbate these trends,with pronounced seasonality in hydrological fluxes.Importantly,synergistic interactions between land cover transformation and climatic anomalies manifest in nonlinear hydrological alterations,amplifying peak flows and diminishing baseflows.This underscores the riverine system's heightened vulnerability and the necessity for integrated watershed management strategies that account for multifactorial hydrological stressors.The study provides a robust empirical and modeling basis to inform adaptive water governance within transboundary river basins susceptible to environmental transitions.
基金Supported by Open Project Fund of China Meteorological Administration Basin Heavy Rainfall Key Laboratory(2023BHR-Y26)Innovation Project Fund of Wuhan Metropolitan Area Meteorological Joint Science and Technology(WHCSQY202305)+1 种基金Innovation and Development Special Project of China Meteorological Administration(CXFZ2022J019)Project of Huanggang Meteorological Bureau's Scientific Research(2022Y02).
文摘It is an important standard to judge the flood disaster in the basin whether the rainfall at the flood-inducing interface is reached.In this paper,the Xin'anjiang model,Topmodel model and SCS model were selected to calculate and compare the rainfall at the flood-inducing interface in the Zhanghe Reservoir basin in Hubei Province.The results showed that average relative error and average absolute error of Xin'anjiang model were-3.36%and-21.46×10^(5)m^(3),which were the minimum,followed by Topmodel model with 5.72%and 26.22×10^(5)m^(3),SCS model with 11.33%and 58.13×10^(5)m^(3).The minimum absolute error of the three hydrological models in calculating the rainfall at the critical interface was 3.26 mm,while the maximum was 49.24 mm.When the initial water level exceeded 120 m,the difference among the three models in calculating the rainfall at the critical interface became more and more obvious.When the reservoir water level was lower than 120 m,it mainly referred to the calculation results of Xin'anjiang model.When the reservoir water level was higher than 120 m,it mainly referred to the calculation results of Topmodel model.The research conclusion can provide reference for small and medium-sized basins selecting hydrological model to calculate the rainfall at the flood-inducing interface.
基金funded by the National Natural Science Foundation of China (42174030)Major Science and Technology Program for Hubei Province (Grant No.2022AAA002)+2 种基金Special fund of Hubei Luojia Loboratory (220100020)the National Natural Science Foundation of China under Grant 42304031the China Postdoctoral Science Foundation 2022M722441。
文摘Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global Land Data Assimilation System (GLDAS),the Famine Early Warning System Network Land Data Assimilation System (FLDAS),the National Centers for Environmental Prediction (NCEP),and the WaterGAP Global Hydrology Model (WGHM).Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series,satellite gravity field Mascon solutions,and Global Precipitation Climatology Centre (GPCC) guide our assessment.Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP.In the Amazon River Basin,a 5-month lag between FLDAS,GLDAS,and satellite gravity results is observed.In eastern Asia and Australia,NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models.Three combined hydrological models (H-VCE,H-EWM,and H-CVM) utilizing Variance Component Estimation (VCE),Entropy Weight Method (EWM),and Coefficient of Variation Method (CVM) are formulated.Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%-17%.Correlation with precipitation increases by 25%-30%,and with satellite gravity,rises from 0.2 to 0.8 at maximum.The combined model eliminates time lag in the Amazon Basin TWSC analysis,exhibiting a four times higher signal-to-noise ratio than single models.H-VCE demonstrates the highest accuracy.In summary,the combined hydrological model minimizes discrepancies among individual models,significantly improving accuracy for monitoring large-scale TWSC.
文摘Hydrological modeling plays a crucial role in efficiently managing water resources and understanding the hydrologic behavior of watersheds. This study aims to simulate daily streamflow in the Godavari River Basin in Maharashtra using the Soil and Water Assessment Tool (SWAT). SWAT is a process-based hydrological model used to predict water balance components, sediment levels, and nutrient contamination. In this research, we used integrated remote sensing and GIS data, including Digital Elevation Models (DEM), land use and land cover (LULC) maps, soil maps, and observed precipitation and temperature data, as input for developing the SWAT model to assess surface runoff in this large river basin. The Godavari River Basin under study was divided into 25 sub-basins, comprising 151 hydrological response units categorized by unique land cover, soil, and slope characteristics using the SWAT model. The model was calibrated and validated against observed runoff data for two time periods: 2003-2006 and 2007-2010 respectively. Model performance was assessed using the Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R2). The results show the effectiveness of the SWAT2012 model, with R2 value of 0.84 during calibration and 0.86 during validation. NSE values also ranged from 0.84 during calibration to 0.85 during validation. These findings enhance our understanding of surface runoff dynamics in the Godavari River Basin under study and highlight the suit-ability of the SWAT model for this region.
基金Vingroup JSCMaster,PhD Scholarship Program of Vingroup Innovation Foundation,Grant/Award Number:VINIF.2021.ThS.97。
文摘Flood forecasting is critical for mitigating flood damage and ensuring a safe operation of hydroelectric power plants and reservoirs.This paper presents a new hybrid hydrological model based on the combination of the Hydrologic Engineering Center-Hydrologic Modeling System(HEC-HMS)hydrological model and an Encoder-Decoder-Long Short-Term Memory network to enhance the accuracy of real-time flood forecasting.The proposed hybrid model has been applied to the Krong H'nang hydropower reservoir.The observed data from 33 floods monitored between 2016 and 2021 are used to calibrate,validate,and test the hybrid model.Results show that the HEC-HMS-artificial neural network hybrid model significantly improves the forecast quality,especially for results at a longer forecasting time.In detail,the Kling-Gupta efficiency(KGE)index,for example,increased from ΔKGE=16%at time t+1h to ΔKGE=69%at time t+6 h.Similar results were obtained for other indicators including peak error and volume error.The computer program developed for this study is being used in practice at the Krong H'nang hydropower to aid in reservoir planning,flood control,and water resource efficiency.
基金National Key Basic Research Program of China,No.2010CB428403National Grand Science and Technology Special Project of Water Pollution Control and Improvement,No.2009ZX07210-006
文摘The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects：uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.
基金National Key Technology P&D Program,No.2012BAB02B00The Fundamental Research Funds for the Central Universities
文摘The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission （TRMM） data with rain gauge data and further to use this TRMM data to drive a Dis- tributed Time-Variant Gain Model （DTVGM） to perform hydrological simulations in the semi-humid Weihe River catchment in China. Before the simulations, a comparison with a 10-year （2001-2010） daily rain gauge data set reveals that, at daily time step, TRMM rainfall data are better at capturing rain occurrence and mean values than rainfall extremes. On a monthly time scale, good linear relationships between TRMM and rain gauge rainfall data are found, with determination coefficients R2 varying between 0.78 and 0.89 for the individual stations. Subsequent simulation results of seven years （2001-2007） of data on daily hydro- logical processes confirm that the DTVGM when calibrated by rain gauge data performs better than when calibrated by TRMM data, but the performance of the simulation driven by TRMM data is better than that driven by gauge data on a monthly time scale. The results thus suggest that TRMM rainfall data are more suitable for monthly streamfiow simulation in the study area, and that, when the effects of recalibration and the results for water balance components are also taken into account, the TRMM 3B42-V7 product has the potential to perform well in similar basins.
基金CAS-CSIRO Cooperative Research Program,No.CJHZ1223National Basic Research Program of China,No.2010CB428406
文摘Actual evapotranspiration is a key process of hydrological cycle and a sole term that links land surface water balance and land surface energy balance.Evapotranspiration plays a key role in simulating hydrological effect of climate change,and a review of evapotranspiration estimation methods in hydrological models is of vital importance.This paper firstly summarizes the evapotranspiration estimation methods applied in hydrological models and then classifies them into the integrated converting methods and the classification gathering methods by their mechanism.Integrated converting methods are usually used in hydrological models and two differences exist among them:one is in the potential evaporation estimation methods,while the other in the function for defining relationship between potential evapora tion and actual evapotranspiration.Due to the higher information requirements of the Pen-man-Monteith method and the existing data uncertainty,simplified empirical methods for calculating potential and actual evapotranspiration are widely used in hydrological models.Different evapotranspiration calculation methods are used depending on the complexity of the hydrological model,and importance and difficulty in the selection of the most suitable evapotranspiration methods is discussed.Finally,this paper points out the prospective de velopment trends of the evapotranspiration estimating methods in hydrological modeling.
基金This work was jointly supported by the National Natural Science Foundation of China under Grant No. 40205012, and 40201048, the Chinese NKBRSF Project G1999043400 and the Foundation of the China Ministry of Education (Grant No. 20010284027). The computat
文摘Considering a detailed hydrologic model in the land surface scheme helps to improve the simulation of regional hydro-climatology. A hydrologic model, which includes spatial heterogeneities in precipitation and infiltration, is constructed and incorporated into the land surface scheme BATS. Via the coupled-model (i.e., a regional climate model) simulations, the following major conclusions are obtained: the simulation of surface hydrology is sensitive to the inclusion of heterogeneities in precipitation and infiltration; the runoff ratio is increased after considering the infiltration heterogeneity, a result which is more consistent with the observations of surface moisture balance over humid areas; the introduction of the parameterization of infiltration heterogeneity can have a greater influence on the regional hydro-climatology than the precipitation heterogeneity; and the consideration of the impermeable fraction for the region reveals some features that are closer to the trend of aridification over northern China.
基金National Key Basic Research Program of China(973 Program),No.2015CB452701National Natural Science Foundation of China,No.41271003+1 种基金No.41371043No.41401042
文摘Accurate estimation of evapotranspiration(ET),especially at the regional scale,is an extensively investigated topic in the field of water science. The ability to obtain a continuous time series of highly precise ET values is necessary for improving our knowledge of fundamental hydrological processes and for addressing various problems regarding the use of water. This objective can be achieved by means of ET data assimilation based on hydrological modeling. In this paper,a comprehensive review of ET data assimilation based on hydrological modeling is provided. The difficulties and bottlenecks of using ET,being a non-state variable,to construct data assimilation relationships are elaborated upon,with a discussion and analysis of the feasibility of assimilating ET into various hydrological models. Based on this,a new easy-to-operate ET assimilation scheme that includes a water circulation physical mechanism is proposed. The scheme was developed with an improved data assimilation system that uses a distributed time-variant gain model(DTVGM),and the ET-soil humidity nonlinear time response relationship of this model. Moreover,the ET mechanism in the DTVGM was improved to perfect the ET data assimilation system. The new scheme may provide the best spatial and temporal characteristics for hydrological states,and may be referenced for accurate estimation of regional evapotranspiration.
基金supported by the National Basic Research Program of China (the 973 Program,Grant No.2010CB951102)the National Supporting Plan Program of China (Grants No.2007BAB28B01 and 2008BAB42B03)the National Natural Science Foundation of China (Grant No. 50709042),and the Regional Water Theme in the Water for a Healthy Country Flagship
文摘In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments （data are non-continuous and fragmental in some catchments）, we used non-continuous calibration periods for more independent streamflow data for SIMHYD （simple hydrology） model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization （PSO） method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years, randomly sampled, were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. In general, eight years of data are sufficient to obtain steady estimates of model performance and parameters for the SIMHYD model. It is also shown that most humid catchments require fewer calibration data to obtain a good performance and stable parameter values. The model performs better in humid and semi-humid catchments than in arid catchments. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.
基金NSFC Innovation Team Project,China(NO.50721006)National Key Technologies R&D Program of China during the llth Five-Year Plan Period(NO.2008BAB29B08)
文摘An application of multi-objective particle swarm optimization （MOPSO） algorithm for optimization of the hydrological model （HYMOD） is presented in this paper. MOPSO algorithm is used to find non-dominated solutions with two objectives： high flow Nash-Sutcliffe efficiency and low flow Nash- Sutcliffe efficiency. The two sets＇ coverage rate and Pareto front spacing metric are two criterions to analyze the performance of the algorithms. MOPSO algorithm surpasses multi-objective shuffled complex evolution metcopolis （MOSCEM_UA） algorithr~, in terms of the two sets＇ coverage rate. But when we come to Pareto front spacing rate, the non-dominated solutions of MOSCEM_ UA algorithm are better-distributed than that of MOPSO algorithm when the iteration is set to 40 000. In addition, there are obvious conflicts between the two objectives. But a compromise solution can be acquired by adopting the MOPSO algorithm.
基金the National Natural Science foundation of China(Grant Nos.41690145 and 41670158)
文摘Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.
基金supported by the National Basic Research Program of China(Grant No.2006CB400502)the World Bank Cooperative Project(Grant No.THSD-07)the 111 Program of the Ministry of Education and the State Administration of Foreign Expert Affairs,China(Grant No.B08048)
文摘This study simulated and predicted the runoff of the Aksu River Basin, a typical river basin supplied by snowmelt in an arid mountain region, with a limited data set and few hydrological and meteorological stations. Two hydrological models, the snowmelt-runoff model （SRM） and the Danish NedbФr-AfstrФmnings rainfall-runoff model （NAM）, were used to simulate daily discharge processes in the Aksu River Basin. This study used the snow-covered area from MODIS remote sensing data as the SRM input. With the help of ArcGIS software, this study successfully derived the digital drainage network and elevation zones of the basin from digital elevation data. The simulation results showed that the SRM based on MODIS data was more accurate than NAM. This demonstrates that the application of remote sensing data to hydrological snowmelt models is a feasible and effective approach to runoff simulation and prediction in arid unguaged basins where snowmelt is a major runoff factor.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41130639, 51179045, 41201028)the Nonprofit Industry Financial Program of MWR of China (201501022)
文摘Intense human activities have greatly changed the flood generation conditions in most areas of the world, and have destroyed the consistency in the annual flood peak and volume series. For design flood estimation, coaxial correlation diagram and conceptual hydrological model are two frequently used tools to adjust and reconstruct the flood series under human disturbance. This study took a typical mountain catchment of the Haihe River Basin as an example to investigate the effects of human activities on flood regime and to compare and assess the two adjustment methods. The main purpose is to construct a conceptual hydrological model which can incorporate the effects of human activities. The results show that the coaxial correlation diagram is simple and widely-used, but can only adjust the time series of total flood volumes. Therefore, it is only applicable under certain conditions(e.g. There is a strong link between the flood peaks and volumes and the link is not significantly affected by human activities). The conceptual model is a powerful tool to adjust the time series of both flood peak flows and flood volumes over different durations provided that it is closely related to the catchment hydrological characteristics, specifically accounting for the effects of human activities, and incorporating expert knowledge when estimating or calibrating parameters. It is suggested that the two methods should be used together to cross check each other.
文摘The Ganga River, the longest river in India, is stressed by extreme anthropogenic activity and climate change, particularly in the Varanasi region. Anticipated climate changes and an expanding populace are expected to further impede the efficient use of water. In this study, hydrological modeling was applied to Soil and Water Assessment Tool （SWAT） modeling in the Ganga catchment, over a region of 15 621.612 km2 in the southern part of Uttar Pradesh. The primary goals of this study are： ① To test the execution and applicability of the SWAT model in anticipating runoff and sediment yield; and ② to compare and determine the best calibration algorithm among three popular algorithms-sequential uncertainty fitting version 2 （SUFI-2）, the generalized likelihood uncertainty estimation （GLUE）, and par-allel solution （ParaSol）. The input data used in the SWAT were the Shuttle Radar Topography Mission （SRTM） digital elevation model （DEM）, Landsat-8 satellite imagery, soil data, and daily meteorological data. The watershed of the study area was delineated into 46 sub-watersheds, and a land use/land cover （LULC） map and soil map were used to create hydrological response units （HRUs）. Models utilizing SUFI- 2, GLUE, and ParaSol methods were constructed, and these algorithms were compared based on five cat-egories： their objective functions, the concepts used, their performances, the values of P-factors, and the values of R-factors. As a result, it was observed that SUFI-2 is a better performer than the other two algo-rithms for use in calibrating Indian watersheds, as this method requires fewer runs for a computational model and yields the best results among the three algorithms. ParaSol is the worst performer among the three algorithms. After calibrating using SUFI-2, five parameters including the effective channel hydraulic conductivity （CH_K2）, the universal soil-loss equation （USLE） support parameter （USLE_P）, Manning＇s n value for the main channel （CH_N2）, the surface runoff lag time （SURLAG）, and the available water capac-ity of the soil layer （SOL_AWC） were observed to be the most sensitive parameters for modeling the pre-sent watershed. It was also found that the maximum runoff occurred in sub-watershed number 40 （SW#40）, while the maximum sediment yield was 50 t.a ^1 for SW#36, which comprised barren land. The average evapotranspiration for the basin was 411.55 mm.a ^1. The calibrated model can be utilized in future to facilitate investigation of the impacts of LULC, climate change, and soil erosion.
文摘The city of Bouaké, the second biggest city of Côte d’Ivoire, experienced a water shortage in 2018 that lasted four months due to the drying up of the Loka reservoir, which supplies two-thirds of the city. The challenge of the Loka reservoir is that it is located in an ungauged basin where very few hydrological studies have been carried out, despite the recurrent problems of access to drinking water. In the purpose to better understand the phenomena that caused this temporary drying of the dam, the methodology implemented was based on agro-hydrological modeling with SWAT using a regionalization technique of a nearby watershed. The model performance was assessed using three statistical indices (the Nash-Sutcliffe coefficient (NS), the coefficient of determination (R<sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;">) and the percentage of bias (PBIAS)) and the visual appreciation of hydrographs for monthly series. The statistical indices appear satisfactory with a NS and R</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> ≥ 0.6 both for calibration and validation, and a PBIAS of </span><span style="font-family:;" "=""><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">11.2 and </span><span style="font-family:Verdana;">-</span><span><span style="font-family:Verdana;">3.8 respectively for calibration and validation. The hydrological modeling of Loka basin has shown the impact of climate change already reported by some authors as well as anthropization. Thus, while the reservoir records a decrease in its water volume estimated at 384,604 m</span><sup><span style="font-family:Verdana;">3</span></sup><span style="font-family:Verdana;"> each year, the water demand undergoes an increase of 122,033 m</span><sup><span style="font-family:Verdana;">3</span></sup><span style="font-family:Verdana;"> per year.</span></span></span>
文摘Water is a vital resource, and can also sometimes be a destructive force. As such, it is important to manage this resource. The prediction of stream flows is an important component of this management. Hydrological models are very useful in accomplishing this task. The objective of this study is to develop and apply an optimization method useful for calibrating a deterministic model of the daily flows of the Miramichi River watershed (New Brunswick). The model used is the CEQUEAU model. The model is calibrated by applying a genetic algorithm. The Nash-Sutcliffe efficiency criterion, modified to penalize physically unrealistic results, was used as the objective function. The model was calibrated using flow data (1975-2000) from a gauging station on the Southwest Miramichi River (catchment area of 5050 km2), obtaining a Nash-Sutcliffe criterion of 0.83. Model validation was performed using flow data (2001-2009) from the same station (Nash-Sutcliffe criterion value of 0.80). This suggests that the model calibration is sufficiently robust to be used for future predictions. A second model validation was performed using data from three other measuring stations on the same watershed. The model performed well in all three additional locations (Nash-Sutcliffe criterion values of 0.77, 0.76 and 0.74), but was performing less well when applied to smaller sub-basins. Nonetheless, the relatively strong performance of the model suggests that it could be used to predict flows anywhere in the watershed, but caution is suggested for applications in small sub-basins. The performance of the CEQUEAU model was also compared to a simple benchmark model (average of each calendar day). A sensitivity analysis was also performed.
基金Under the auspices of Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin (No. IWHR-SKL-201111)National Natural Science Foundation of China (No. 41101024)
文摘The spatial distribution of soil physical properties is essential for modeling and understanding hydrological processes. In this study, the different spatial information (the conventional soil types map-based spatial information (STMB) versus refined spatial information map (RSIM)) of soil physical properties, including field capacity, soil porosity and saturated hydraulic conductivity are used respectively as input data for Water Flow Model for Lake Catchment (WATLAC) to determine their effectiveness in simulating hydrological processes and to expound the effects on model performance in terms of estimating groundwater recharge, soil evaporation, runoff generation as well as partitioning of surface and subsurface water flow. The results show that: 1) the simulated stream flow hydrographs based on the STMB and RSIM soil data reproduce the observed hydrographs well. There is no significant increase in model accuracy as more precise soil physical properties information being used, but WATLAC model using the RSIM soil data could predict more runoff volume and reduce the relative runoff depth errors; 2) the groundwater recharges have a consistent trend for both cases, while the STMB soil data tend to produce higher groundwater recharges than the RSIM soil data. In addition, the spatial distribution of annual groundwater recharge is significantly affected by the spatial distribution of soil physical properties; 3) the soil evaporation simulated using the STMB and RSIM soil data are similar to each other, and the spatial distribution patterns are also insensitive to the spatial information of soil physical properties; and 4) although the different spatial information of soil physical properties does not cause apparent difference in overall stream flow, the partitioning of surface and subsurface water flow is distinct. The implications of this study are that the refined spatial information of soil physical properties does not necessarily contribute to a more accurate prediction of stream flow, and the selection of appropriate soil physical property data needs to consider the scale of watersheds and the level of accuracy required.
基金supported by the Studies and Research in Sustainability Program (Deutscher Akademischer Austausch Dienst, DAAD)
文摘Digital elevation models （DEMs） are widely used to define the flow direction in distributed hydrological models for simulation of streamflow. In recent decades, numerous methods for flow direction determination have been applied successfully to mountainous regions. Nevertheless, some problems still exist when those methods are used for flat or gently sloped areas The present study reviews the conventional methods of determining flow direction for such landscapes and analyzes the problems of these methods. Two different methods of determining flow direction are discussed and were applied to the Xitiaoxi Catchment, located in the Taihu Basin in southern China, which has both mountainous and flat terrain. Both the agree method and the shortest path method use drainage networks derived from a remote sensing image to determine the correct location of the stream. The results indicate that the agree method provides a better fit with the DEM for the hilly region than the shortest path method. For the flat region where the flow has been diverted and rerouted by land managers, both methods require observation of the drainage network to determine the flow direction. In order to clarify the applicability of the two methods, both are employed in catchment hydrological models conceptually based on the Xinanjiang model and implemented with PCRaster. The simulation results show that both methods can be successfully applied in hydrological modeling. There are no evident differences in the modeled discharge when using the two methods at different spatial scales.
