Application of Developed Grid-GA Distributed Hydrologic Model in Semi-Humid and Semi-Arid Basin

A grid and Green-Ampt based （Grid-GA）distributed hydrologic physical model was developed for flood simulation and forecasting in semi-humid and semi-arid basin. Based on topographical information of each grid cell extracted fi＇om the digital elevation model （DEM） and Green-Ampt infiltration method, the Grid-GA model takes into consideration the redistribution of water content, and consists of vegetation and root interception, evapotranspiration, runoff generation via the excess infiltration mechanism, runoff concentration, and flow routing. The downslope redis- tribution of soil moisture is explicitly calculated on a grid basis, and water exchange among grids within runoff routing along the river drainage networks is taken into consideration. The proposed model and Xin＇anjiang model were ap- plied to the upper Lushi basin in the Luohe River, a tributary of the Yellow River, with an area of 4 716 km2 for flood simulation. Results show that both models perform well in flood simulation and can be used for flood forecasting in semi-humid and semi-arid region.

Discretization Approach in Integrated Hydrologic Model for Surface and Groundwater Interaction

The commonly used discretization approaches for distributed hydrological models can be broadly categorized into four types,based on the nature of the discrete components:Regular Mesh,Triangular Irregular Networks(TINs),Representative Elementary Watershed(REWs) and Hydrologic Response Units(HRUs).In this paper,a new discretization approach for landforms that have similar hydrologic properties is developed and discussed here for the Integrated Hydrologic Model(IHM),a combining simulation of surface and groundwater processes,accounting for the interaction between the systems.The approach used in the IHM is to disaggregate basin parameters into discrete landforms that have similar hydrologic properties.These landforms may be impervious areas,related areas,areas with high or low clay or organic fractions,areas with significantly different depths-to-water-table,and areas with different types of land cover or different land uses.Incorporating discrete landforms within basins allows significant distributed parameter analysis,but requires an efficient computational structure.The IHM integration represents a new approach interpreting fluxes across the model interface and storages near the interface for transfer to the appropriate model component,accounting for the disparate discretization while rigidly maintaining mass conservation.The discretization approaches employed in IHM will provide some ideas and insights which are helpful to those researchers who have been working on the integrated models for surface-groundwater interaction.

Integrated hydrologic modeling in the inland Heihe River Basin, Northwest China

As a typical inland river basin in arid Northwest China, having distinct hydrological characteristics and severe and repre- sentative water problems, the Heihe River Basin （HRB） has attracted considerable research interest worldwide and in 2007 became a pilot basin of the G-WADI network of UNESCO/1HR Many research programs have been conducted in the HRB since the 1980s, producing rich knowledge and data about the basin, which will be very helpful to further studies. This paper reviews research efforts related to hydrologic modeling and ongoing model integration studies performed in the HRB in re- cent years. Recently, an observation network covering the whole area and a Web-based data-sharing system have been estab- lished which can greatly improve data acquisition. This paper tabulates modeling activities in past years, including model ap- plications, model modifications and enhancements, and model coupling efforts. Also described is a preliminary modeling in- tegration tool designed to quickly build new models, which has been developed for hydrologic modeling purposes. Challeng- es and issues confronted in current studies are discussed, pointing toward key research directions in the future.

Hydrologic Modeling Impacts of Post-mining Land Use Changes on Streamflow of Peace River, Florida

Whether mining activity results in reduced flow of surface water in the Peace River Watershed of Florida has been the subject of much debate. With increased dependence of downstream users on surface water flow of the Peace River as a source of drinking water for four coastal counties in Southwest Florida and problems of water security, the debate has been intensified. It is possible to assess relationships of mining with streamflow in the upper reaches of the Peace River Basin using hydrologic modeling and identify mined sub-basins. In this work, land-use change impacts were simulated by the Hydrological Simulation Program--Fortran （HSPF） model based on geographical information system （GIS） tools, to compare pre- and post-mining streamflows at a study site of the Peace River in west-central Florida. The purpose of this study was to determine if land-use changes caused by mining have negatively impacted streamflow in the Peace River. Changes of land use were identified before and after mining activities. A coupled volume-water depth-discharge （V-h-Q） model based on stage/storage and stage/discharge was applied using HSPF for the pre-mining and post-mining models, respectively. Daily simulated post-mining hydrographs from HSPF were plotted with the calibrated pre-mining results and streamflow hydrographs from the 18 gauging stations, to compare timing of peaks, low fows and flow trends. Analyses of percent ex- ceedances of flow frequency curves of the streams indicated that most streams had similar distributions for mined （reclaimed） and pre- mining periods. In the streamflow change analysis, streamflows actually increased in mining-affected basins at nearly half the stations. Streamflows at other stations diminished. Overall from this comprehensive study, there were declines in streamflow at most gauging stations on the mainstem of the Peace River and its tributaries. The results of this study suggest that regional planning is urgently needed to propose reclamation schemes that enhance regional hydrology.

Assessing the Performance of Two Hydrologic Models for Forecasting Daily Streamflows in the Cazones River Basin (Mexico)

Floods have caused significant human and economic losses in the Cazones River Basin, located on the Gulf of Mexico. Despite this knowledge, steps towards the design and implementation of an early warning system for the Cazones are still a pending task. In this study we contributed by establishing a hydrological scheme for forecasting mean daily discharges in the Cazones Basin. For these purposes, we calibrated, validated and compared the HyMod model (HM) which is physics-based, and an autoregressive-based model coupled with the Discrete Kalman Filter (ARX-DKF). The ability of both models to accurately predict discharges proved satisfactory results during the validation period with RMSEHYMOD = 2.77 [mm/day];and RMSEARX-DKF = [2.38 mm/day]. Further analysis based on a Streamflow Assimilation Ratio (SAR) revealed that both models underestimate the discharges in a similar proportion. This evaluation also showed that, under the most common conditions, the simpler stochastic model (ARX-DKF) performs better;however, under extreme hydrological conditions the deterministic HM model reveals a better performance. These results are discussed under the context of future applications and additional requirements needed to implement an early warning hydrologic system for the Cazones Basin.

Comparative analysis of recent hydrological models and an attempt to generate new combined products for monitoring terrestrial water storage change

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.

Integrated Hydrological Modeling of the Godavari River Basin in Maharashtra Using the SWAT Model: Streamflow Simulation and Analysis

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.

Quantitative evaluation of NEXRAD data and its application to the distributed hydrologic model BPCC

The next-generation weather radar(NEXRAD) can generally capture the spatial variability of rainfall fields,but fails to provide accurate depth measurements.A systematic strategy to evaluate the accuracy of radar data in depth measurement and its performance in hydrologic model is outlined.Statistical evaluation coefficients are calculated by comparing NEXRAD data with individual raingauges as well as subbasin-averaged interpolations,and point-and surface-average factors are introduced to revise radar data successively.Hydrologic simulations are then performed with a distributed hydrologic model,called basin pollution calculation center(BPCC) with both raingauge observations and revised NEXRAD estimates inputs.The BPCC model is applied to Clear Creek Watershed,IA,USA,on an hourly scale,and the calibration and validation parameters are semi-automatically optimized to improve manual calibration shortcomings.Results show that hydrographs generated from both gauge and NEXRAD are in good agreement with observed flow hydrographs.Coefficient statistics reveal that NEXRAD contributes to model performance,indicating that NEXRAD data has the potential to be used as an alternative source of precipitation data and improve the accuracy of hydrologic simulations.

Hydrological characteristics and changes in the Nu-Salween River basin revealed with model-based reconstructed data

The Nu-Salween River(NSR),the longest free-flow river in Southeast Asia,plays an irreplaceable role in social development and ecological protection.The lower NSR region is particularly valuable as it is inhabited by approximately 6.7 million people.The basin has limited hydraulic conservancy infrastructure and insufficient ability to cope with climate change risks.Studying the hydrological characteristics and changes in the basin provides the scientific basis for rational protection and development of the basin.However,owing to the limitation of observation data,previous studies have focused on the local area and neglected the study of the lower reaches,which is not enough to reflect the spatial characteristics of the entire basin.In this study,the ECMWF 5th generation reanalysis data(ERA5)and Multi-Source Weighted-Ensemble Precipitation(MSWEP)were applied to develop a geomorphology-based hydrological model(GBHM)for reconstructing hydrological datasets(i.e.GBHM-ERA5 and GBHM-MSWEP).The reconstructed datasets covering the complete basin were verified against the gauge observation and compared with other commonly used streamflow products,including Global Flood Awareness System v2.1,GloFAS-Reanalysis dataset v3.0,and linear optimal runoff aggregate(LORA).The comparison results revealed that GBHM-ERA5 is significantly better than the other four datasets and provides a good reproduction of the hydrological characteristics and trends of the NSR.Detailed analysis of GBHM-ERA5 revealed that:(1)A multi-year mean surface runoff represented 39%of precipitation over the basin during 1980–2018,which had low surface runoff in the upstream,while areas around the Three Parallel Rivers Area and the estuary had abundant surface runoff.(2)The surface runoff and discharge coefficient of variations in spring were larger than those in other seasons,and the inter-annual variation in the downstream was smaller than that in the upstream and midstream regions.(3)More than 70%of the basin areas showed a decreasing trend in the surface runoff,except for parts of Nagqu,south of Shan State in Myanmar,and Thailand,where surface runoff has an increasing trend.(4)The downstream discharge has dropped significantly at a rate of approximately 680 million cubic metresper year,and the decline rate is greater than that of upstream and midstream,especially in summer.This study provides a data basis for subsequent studies in the NSR basin and further elucidates the impact of climate change on the basin,which is beneficial to river planning and promotes international cooperation on the water-and eco-security of the basin.

Quantitative comparison of semi- and fully-distributed hydrologic models in simulating flood hydrographs on a mountain watershed in southwest China

To investigate the performance of fully- and semi-distributed hydrologic models in simulating the process of transformation from rainfall to runoff in mountain areas, the fully-distributed models Basin Pollution Calculation Center （BPCC） and HEC- HMS are calibrated for the Zhenjiangguan watershed located in the upper stream of Minjiang River Southwest China using streamflow observations at the basin outlet. Semi-automatical optimization method is implemented to both models to improve simulated resuits by removing artificial errors. Based on the consistency of the simulated hydrographs with the observed ones, the statistical coefficients such as the relative error, the probability distribution and the correlation coefficient, are further introduced to evaluate quantitatively the performance of the two models. Analyses indicate that the hydrographs simulated by the BPCC are relatively closer to the observed ones than those simulated by the HEC-HMS in view of the spatial heterogeneity in terrain, soil texture, land cover and meteorological conditions in mountain areas.

Modelling Hydrological Consequences of Climate Change—Progress and Challenges

The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps： （1） use of general circulation models （GCMs） to provide future global climate scenarios under the effect of increasing greenhouse gases, （2） use of downscaling techniques （both nested regional climate models, RCMs, and statistical methods） for ＂downscaling＂ the GCM output to the scales compatible with hydrological models, and （3） use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales. Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change.

Simulations of a Hydrological Model as Coupled to a Regional Climate Model

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.

Effect of calibration data series length on performance and optimal parameters of hydrological model

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.

Hydrological Response to Environment Change in Himalayan Watersheds: Assessment from Integrated Modeling Approach

Land use changes such as deforestation,increase in cropping or grazing areas and built-up land, likely modify the water balance and land surface behavior in the Himalayan watersheds.An integrated approach of hydrological and hydraulic modeling was adopted for comparative analysis of hydrological pattern in three Himalayan watersheds i.e.Khanpur,Rawal and Simly situated in the Northern territory of Pakistan.The rainfall-runoff model SWAT- Soil and water assessment tool and Hydro CAD were calibrated for the selected watersheds.The correlation analysis of the precipitation data of two climate stations i.e.Murree and Islamabad, with the discharge data of three rivers was utilized to select best suitable input precipitation data for Hydro CAD rainfall-runoff modeling.The peak flood hydrograph were generated using Hydro CAD runoff to optimize the basin parameters like CN, runoff volume, peak flows of the three watersheds.The hydrological response of the Rawal watershed was studied as a case study to different scenarios of land use change using SWAT model.The scenario of high deforestation indicated a decline of about 6.3% in the groundwater recharge tostream while increase of 7.1% in the surface runoff has been observed under the scenario of growth in urbanization in the recent decades.The integrated modeling approach proved helpful in investigating the hydrological behavior under changing environment at watershed level in the Himalayan region.

Identification of Suitable Hydrologic Response Unit Thresholds for Soil and Water Assessment Tool Streamflow Modelling

Use of a non-zero hydrologic response unit(HRU) threshold is an effective way of reducing unmanageable HRU numbers and simplifying computational cost in the Soil and Water Assessment Tool(SWAT) hydrologic modelling. However, being less representative of watershed heterogeneity and increasing the level of model output uncertainty are inevitable when minor HRU combinations are disproportionately eliminated. This study examined 20 scenarios by running the model with various HRU threshold settings to understand the mechanism of HRU threshold effects on watershed representation as well as streamflow predictions and identify the appropriate HRU thresholds. Findings show that HRU numbers decrease sharply with increasing HRU thresholds. Among different HRU threshold scenarios, the composition of land-use, soil, and slope all contribute to notable variations which are directly related to the model input parameters and consequently affect the streamflow predictions. Results indicate that saturated hydraulic conductivity, average slope of the HRU, and curve number are the three key factors affecting stream discharge when changing the HRU thresholds. It is also found that HRU thresholds have little effect on monthly model performance, while evaluation statistics for daily discharges are more sensitive than monthly results. For daily streamflow predictions, thresholds of 5%/5%/5%(land-use/soil/slope) are the optimum HRU threshold level for the watershed to allow full consideration of model accuracy and efficiency in the present work. Besides, the results provide strategies for selecting appropriate HRU thresholds based on the modelling goal.

Optimization of the Hydrological Model Using Multi-objective Particle Swarm Optimization Algorithm

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.

Application of hydrological models in a snowmelt region of Aksu River Basin

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.

Projection of future streamflow of the Hunza River Basin,Karakoram Range(Pakistan)using HBV hydrological model

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.

Application and comparison of coaxial correlation diagram and hydrological model for reconstructing flood series under human disturbance

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.

A Comparison of SWAT Model Calibration Techniques for Hydrological Modeling in the Ganga River Watershed

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.