Rainfall-runoff hydrological models are important tools in water resources projects. Generally, performance of this group of models is dependent on the proper selection of parameters. Accordingly, several methods have been developed to estimate hydrological parameters. The present study aimed to compare the performance of conceptual hydrologic models such as TANK, SIMHYD and AWBM which benefit from the indirect model parameters estimation approach in discharge simulation of Babolroud watershed, Mazandaran province, Iran. The automatic calibration process of these models was designed using genetic evolutionary search algorithm and objective functions (NSE and RMSE) as error thresholds determinants. Hence, meteorological and hydrological data consist of temperature, evapotranspiration, precipitation and discharge (in daily scale) were gathered from authorities. Input data was also divided into warm-up, train and test steps after preliminary validation and recovery. Based on the results, NSE metric introduced TANK model as the best simulator respectively for train and test step (0. 59 to 0. 72). Depends on RMSE metric, SIMHYD (0. 83) and TANK (0. 15) models were introduced as the best simulator respectively for train and test step either. According to the catchment flow signatures, general simulation of low-flow (excluding the Model TANK), mean-flow and high-flow were conducted with acceptable agreement. While simulation of the flow duration curve slope which represents an intensity of changes (excluding TANK model in train step), did not provide acceptable results. Given the weaknesses and strengths of the proposed models, they can be used as an acceptable simulator in water resources management especially in terms of ungauged basins, after preliminary verification in different climatic conditions.

Utilizing hydrological models allows for the correct and sustainable planning of water resources management. In this research, with the aim of simulating the flow of the Aland watershed (located in the Aras river basin) as a watershed under the influence of human activities, the WEAP model was developed, calibrated and validated. For this purpose, an 11-year statistical period (2001 to 2011) was used to calibrate and a five-year period (2011 to 2016) was used to validate the model. The model simulation results at the basin outlet showed statistical indices of the coefficient of determination and Nash-Sutcliffe Efficiency (NSE) were 0. 96 and 0. 85, in the calibration period, respectively, and during the validation period there were 0. 79 and 0. 78, respectively. These results indicate the good performance of the WEAP model in simulating hydrologic behavior, including rainfall-runoff, base flow, groundwater and other components of the water balance of the Aland watershed. In this research, the simulation results of drinking water supply scenario from the Agh Chay Dam indicate a reduction in groundwater level drop and an increase in the volume of aquifer at an annual rate of 5. 4 million cubic meters.

Physical properties of watersheds are not uniform throughout the watershed. Distributed rainfall runoff models have been developed to account for spatial distribution of watershed characteristics on flood hydrographs. On the other hand, due to advances in geographical information systems (GIS), the possibility of using distributed rainfall-runoff models has become more feasible. This research studies the effect of grid cell size on flood hydrograph in Kan watershed with an area of 206 Km2 located North West of Tehran. A distributed hydrological model on the basis of SCS infiltration and Clark flow routing using Visual Basic programming language is developed. Landsat TM Color composites bands 1, 4, and 7 are used for lithology recognition by hard classify method in IDRISI software. For determining infiltration in each classified lithology, infiltration measurements by rainfall simulator are conducted in each lithology zone. The result of this research shows that with increasing cell size from 30 meter to 960 meter, maximum flood discharge decreases. The rate of decrease depends on the spatial variation of rainfall and physical properties of land in the basin. By decreasing spatial variation of rainfall and infiltration in the watershed, the variation of maximum flood discharge will decrease. The results of this research show that by increasing time step from 10 minutes to 30 minutes, the computer run time will decrease by more than 50%, while maximum flood discharge will decrease by about 0.5%.

An application of a spatially distributed hydrologic model WetSpa working on a daily time scale is presented in this paper. The model combines elevation; soil and land use data within GIS, and predicts flood hydrograph and the spatial distribution of hydrologic characteristics through a watershed. WetSpa model uses a modified rational method to calculate runoff. The runoff is routed through the basin along flow paths using a diffusive wave transfer model that depending upon slope, flow velocity and dissipation characteristic along the flow lines. The Chehel-chai basin is located in the east of Golestan Province with an area of 254.9 km2. Elevation rangs from 194 to 2547 m and a mean slope is 34%. The mean annual precipitation in the catchment is 766.5 mm. Daily hydrometeorological data from 2002 to 2006, including precipitation data from three stations (Lazoreh, Dozin, and Narab), temperature and evaporation data from two stations (Lazoreh, Dozin) were used as input to the model. Three base maps, i.e. DEM, land use and soil types are prepared in GIS form using 90×90 m cell size. Simulated hydrographs are compared with measured hydrographs which are available for the same 2 and 3 year periods. Results of the simulations show a rather good agreement between calculated and measured hydrographs. The model predicts the daily hydrographs with a rather good accuracy, more than 50 and 57% for calibration and validation periods respectively according to the Nash-Sutcliff criterion.

There is a wide agreement in the international scientific society that climate change will modify climatic variables and hydrological extremes. Increasing greenhouse gases in the atmosphere leads to changes in air temperature and precipitation. The changes in air temperatures and precipitation have significant effects on the hydrological cycle. Today, general circulation models (GCM) are the most powerful tools for evaluating the effects of climate change. The outputs of this model are presented as inputs of hydrological models. Hydrological models act as a valuable tool for assessing the hydrologic characteristics of diverse catchments and effective evaluation of the hydrologic consequences of climatic change. Amidst hydrological models, there is a physically-based model that does not require long-term data, and in small catchment areas, which do not have long recorded data, they can be used. No significant work has been done to simulation of climate change impact on water balance component of Kasilian representative basin. The Kasilian representative catchment is a part of the Kasilian basin with an area of 67 km2. The Kasilian River is considered as one of the headwaters of the Talar River that eventually flows into the Caspian Sea. The geology of the catchment is dominated by sedimentary rocks. The aim of this study was to simulate the role of climate change impacts on stream flow and water balance components in the Kasilian representative basin as a small and forested watershed. In order to find out the relationship between the rainfall-runoff process, the basin characteristics, and the parameters of a water balance model, the BROOK90 model has been implemented. The BROOK90 model is a physically-based, parameter-rich, hydrologic model written and supported by Anthony C. Federer. Below the ground, the model includes many soil layers ranging from 1 to 25, each with its own thickness and having different physical properties. The Penman-Monteith equation is used to estimate the rate of evapotranspiration. The model uses the Shuttleworth and Wallace (1985) method to separate the transpiration and the soil evaporation from sparse canopies. The soil water characteristics are defined using a modified approach of the Brooks and Corey (1964), and the Saxton et al. (1986) from 11 and 10 classified textural classes, respectively. The water movement through the soil is simulated using the Darcy– Richards equation. It considers water stored as intercepted rain, intercepted snow, snow on the ground, soil water in from one to many layers, and the groundwater. Snow accumulation and melt are controlled by a degree-day method with cold content. Evaporation is the sum of five components: the evaporation of intercepted rain and snow, snow and soil evaporation, and transpiration. The stream flow is generated using the following simplified processes: the stream flows by the source area flow or subsurface pipe-flow and delayed flow from the vertical or downslope soil drainage and the first-order groundwater storage. Further details are provided in the BROOK90 documentation manual (Federer, 2015). Twenty years of hydro-climatology observation data (1992– 2011) were used for setting the BROOK90 for the basin. The data from the period 1992– 1997 was used for calibration, and the interval 1998– 2000 was considered as the validation period. The calibration of BROOK90 and validation of model performance were based on daily discharge data from the catchment outlets and was done by trial and error. The visual inspection of the measured and simulated discharge curves, mean bias error (MBE), Correlation Coefficient, Coefficient of Determination, and Nash– Sutcliffe model efficiency coefficient were the indicators for model performance. Statistically downscaled GCM data were used to show hypothetical climate change scenarios. The hydrological responses of the catchment were simulated for several hypothetical climate change scenarios. The results were compared with the reference or base case (present climate conditions). The results of the simulation showed good accordance between the observed and simulated values with the final parameter sets using the BROOK90 model. The simulation results demonstrate that the model can give a fair estimation of the water balance components of this basin. The estimated increase of precipitation causes an increase in all water balance components, especially in runoff components. The estimated variation of precipitation (Sc1-Sc4) will considerably affect annual runoff in the future period. The increase in annual runoff based on model predictions was estimated to be 53. 3% for the Sc3 scenario at the catchment. Between the all runoff components, the SRFL component shows the most sensitivity to increasing precipitation. Evapotranspiration components do not show significant sensitivity to estimated variation of the precipitation. The estimated increase of temperature (Sc5-Sc7) will significantly affect the evapotranspiration rates and runoff in the future period. The increase in annual evapotranspiration based on the model predictions was estimated to be 13. 14% for the Sc7 scenario at the catchment. This would be a change from 654. 2 mm yr-1 in the control period (base run) to 730 mm yr-1 in the future (Sc7). The annual runoff at Kassilian was predicted to decrease from 363. 6 mm yr-1 in the control period to 238. 5 mm yr-1 or 34. 4% for Sc7 scenario in the future. These increases in winter minimum temperatures above the freezing point would be reflected in changes to the period of snow cover and mean lengths of snow cover. Based on the results, the BROOK90 featured its simplistic approach to simulate the role of climate change impacts on the stream flow and water balance components in a small and forested watershed. With an estimated increase in temperature, the annual runoff is expected to decrease, and the annual cycle will change significantly. The winter runoff is expected to increase, the runoff maximum will shift, and the spring and summer runoff will decrease notably. This condition plays an important role in increasing the potential of flooding and a decrease in the groundwater storage in the basin. The estimated increase of precipitation causes an increase in the all water balance components, especially in the runoff components. Therefore, it is possible to expect more flood and water shortage events in the future.

In this study, with the aim of improving river flow simulation, the effect of coupling between AtmosphereLand Surface Interaction Scheme (ALSIS) and HBV hydrological model in Karkheh Basin and its sub basins without considering South Karkheh basin was investigated. Before coupling, comparison between soil moisture of HBV model and ALSIS scheme was performed and the accuracy of soil moisture results of both models was evaluated with observational data. Some metrics such as NSE, RMSE, BIAS and RSR were used to compare the simulated and observed data. Comparison of simulated soil moisture results by ALSIS and HBV with observational data showed that in all sub-basins there was better agreement between ALSIS soil moisture and observational data (compared to HBV). The ALSIS scheme showed better simulation in wet seasons and high humidity and HBV model in dry seasons and low humidity. The ALSIS-HBV coupled model performed better than HBV in all sub-basins and the entire Karkheh Basin, especially at high flow. The best results were obtained for the Ghare Sou subbasin with NSE=0. 76 – 0. 88, RMSE=7. 7 – 4. 5 mm per month, and RSR=0. 49-0. 34. The greatest reduction in BIAS erroroccurred in the Kashkan subbasin, which decreased from 0. 24 to 0. 03.

This study assessed the satellite rainfall data as input for developing a reliable rainfall-runoff model to provide information for early warning flood in the Voshmgir Dam basin in Iran. Two satellite based rainfall estimates (TRMM and PERSIANN) were assessed to evaluate which rainfall product better represents the actual rainfall pattern and intensity of the basin. After evaluation based on statistical parameters such as the Root Mean Square Error (RMSE), Mean Average Error (MAE), Mean Bias Error (MBE) and Correlation coefficient (R2), TRMM were selected for rainfall-runoff simulations. Among six years of available discharge data from 2002 to 2007, period of 2002 to 2004 was used for calibration whereas data from 2005 to 2007 were used for validation. In additional to continuous daily rainfall-runoff model development using HEC-HMS, an event based flood model was also developed. Also simulations based on daily TRMM versus 3-hourly TRMM were compared to evaluate the effect of input time-step on the results. Results showed that the deficit constant loss method successfully predicted gauged catchment runoff and peak flows for calibration (NSE= 0. 413, R2=0. 482, RVE=-0. 246 %) and validation (NSE= 0. 621, R2=0. 670, RVE=-0. 329 %) periods. Also the developed model estimated the rainfall-runoff process for the monthly or longer time scales better than the daily scale. In addition, the event based HEC-HMS model developed using TRMM data with shorter time steps (3-hourly) showed good capability to simulate daily peak discharges. The study demonstrated the suitability of HEC-HMS for continuous runoff simulation in a complex watershed. Therefore, this work will have a significant contribution for the future development of water resources programs in this catchment in particular as well as in other data-scarce catchments.

Introduction Hydrological models are powerful tools for understanding and estimating the hydrological responses of a catchment. They play a crucial role in water resource management, river engineering, flood control, and flood storage. Evaluating the quantitative and qualitative aspects of hydrological models with a systematic approach is essential. The key variables affecting the hydrological cycle include precipitation, temperature, land use, soil texture, elevation, and evapotranspiration. The complex interactions among these variables make the hydrological cycle a relatively complicated process, necessitating the use of hydrological models for evaluation. The most important input parameter in hydrological simulation processes is precipitation. Availability of suitable precipitation data in different times and locations is very important. Currently, most precipitation data is collected from ground-based rain gauge stations or weather radars. However, precipitation monitoring networks, especially in developing countries like Iran, lack good spatial density. Issues like high costs, lack of monitoring equipment in remote areas, inappropriate distribution, short-term monitoring gaps, equipment malfunctions, and user errors are persistent problems for precipitation data users. Hence, the lack of reliable and complete precipitation data is a major challenge in hydrological analysis and forecasting for water resource management. Consequently, monitoring precipitation at short time scales and small spatial scales plays a crucial role in hydrological simulations and ultimately water resource management. In recent years, the use of remote sensing and satellite precipitation estimation algorithms has been developed and is being proposed as an alternative. These technologies have the potential to provide more comprehensive and accurate precipitation data, which can significantly improve the performance of hydrological models and enhance water resource management. Materials and Methods This study focuses on hydrological evaluation of four satellite precipitation products TMPA-3R42V7, TMPA-3B42RTV7, PERSIANN and PERSIANN-CDR in the modeling of rainfall runoff of Sheshpir river watershed (954/5 km2 ). The minimum elevation of the basin is 1527 meters and the maximum is 3666 meters above sea level. The hydrometric station is located at 51°43' east longitude and 30°01' north latitude, and has adequate daily discharge data for the river. To achieve the objectives of the research, the conceptual and continuous hydrological model of IHACRES was first extracted using measured ground-based rainfall and temperature information for the period September 22, 2004 through December 31, 2009 using calibrated observational data of Tolombe Hassani hydrometry station and model parameters. IHACRES model was then validated for the period January 1, 2010 through December 31, 2013. IHACRES is an integrated conceptual-metric model for rainfall-runoff simulation, developed through the collaborative efforts of hydrologists from the Integrated Catchment Assessment and Management (ICAM) Centre at the Australian National University and the Centre for Ecology and Hydrology (CEH) of the UK Natural Environment Research Council. IHACRES is a parsimonious, effective, and efficient model that has been applied in a wide range of climatic regions, including dry and semi-arid areas. The evaluation indices used in this study are: Coefficient of determination (R2), Nash-Sutcliffe efficiency (NSE), Root mean square error (RMSE), Logarithmic root mean square error (log RMSE). Results and Discussion Model calibration results for the Sheshpir and watershed showed acceptable performance, with statistical indices of Nash Sutcliffe Efficiency (NSE), and coefficient of determination (R2 ), 0.8 and 0.8, respectively, and validation results According to the above statistical indices, 0.62, and 0.66, respectively, indicate acceptable performance of the IHACRES hydrological model. Then, the satellite precipitation products that the purpose of this study was introduced as a substitute for stationary mean precipitation, according to statistical indices, results show higher abilities of PERSIANN-CRD in simulation of rainfall-runoff than other algorithms. The coefficient of determination for PERSIANN-CDR algorithm is 0.79 and for TMPA-3B42V7, TMPA-3B42RTV7, PERSIANN satellite algorithms are 0.67, 0.61, 0.1 respectively. Also, according to another statistical index under the name of NS, the evaluation of hydrological models in order to simulate the rainfall-runoff model with PERSIAN-CDR algorithm, is 0.7 in the calibration period and 0.69 in the validation period, which shows the proper performance of the IHACRES rainfall-runoff model with the PERSIANN-CDR precipitation algorithm. The PERSIANN-CDR algorithm has a higher capability than other algorithm; on the other hand, the error correction operation of the PERSIANN-CDR model is successful, but the use of the model with a time delay of TMPA-3B42V7 does not have a significant effect on the model close to the real time. In general, the IHACRES model, coupled with the PERSIANN-CDR satellite precipitation product, demonstrated promising results in simulating the rainfall-runoff processes in the Sheshpir watershed, which is located in a semi-arid climate region. The study highlights the potential of using satellite-based precipitation data as a viable alternative to ground-based observations for hydrological modeling in data-scarce regions. Conclusion The results of this research demonstrate the suitability and high capability of the IHACRES model in simulating watershed hydrology and estimating water flow in an integrated manner. The study also reveals the potential of satellite precipitation algorithms to replace ground observational data in cases where such data is scarce or unavailable. One of the key findings of the research is the impact of error adjustment operations on the performance of satellite precipitation products. The study shows that error adjustment in the Persiann-CDR product led to a noticeable improvement in its performance, while similar adjustments in the TMPA-3B42V7 product did not yield such significant results. The evaluation of the four satellite precipitation algorithms – PERSIANN, PERSIANN-CDR, TMPA-3B42V7, and TMPA-3B42RT – in the hydrological modeling context indicates that the PERSIANN-CDR algorithm has the highest capability . among the tested algorithms. In contrast, the performance of the PERSIANN algorithm was found to be very weak, suggesting that its use in hydrological modeling is not recommended. These findings have important implications for water resource management and decision-making. The ability to effectively utilize satellite precipitation data in hydrological modeling can be particularly valuable in regions with limited ground-based observational data. Additionally, the insights gained from the comparative analysis of the satellite precipitation algorithms can guide the selection and application of the most suitable product for specific hydrological modeling purposes. Overall, this research provides a comprehensive understanding of the suitability and performance of the IHACRES model and satellite precipitation algorithms in simulating watershed hydrology and estimating water flow.

Introduction: Musculoskeletal problems are the common complaints of patients refer to internal medicine clinics and the pain is the most important of them. There are different physiotherapy methods for reduction of pain and action potential simulation therapy (APS therapy) is one of newest methods. The aim of this study was to determine reduction of pain with APS therapy. Materials & Methods: In 47 patients with different musculoskeletal pain APS therapy performed in 6 days each for 16 minutes and with current of 0.7-1.2 mA. Pain (VAS), Global functional status (ACR) and relief of pain (VAS) before and after study compared.Results: APS therapy reduced pain (p<0.001) and increased Global functional status (p<0.001) and increased relief of pain (p<0.005) but there was not any correlation between this reduction of pain with APS therapy and educational status and past history of physiotherapy and duration of illness in these patients.Conclusion: APS therapy is a useful physiotherapy modality for reduction of pain in musculoskeletal problems.