Agricultural Meteorology
S. Pourentezari; K. Esmaili; A.R. Faridhosseini; E. Ghafari
Abstract
Introduction Precipitation is one of the most important input parameters of the hydrological models for rainfall-runoff simulation, which due to the lack of proper dispersion of rain gauge stations and the newly established some of these stations in most basins of the country, the use of these precipitation ...
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Introduction Precipitation is one of the most important input parameters of the hydrological models for rainfall-runoff simulation, which due to the lack of proper dispersion of rain gauge stations and the newly established some of these stations in most basins of the country, the use of these precipitation data faces serious challenges. Therefore, the use of remote-sensing methods is one of the ways that can be used for the streamflow simulation using hydrological models. Runoff is also one of the most important hydrological variables and rainfall-runoff modeling is one of the key items in hydrological sciences to estimate runoff characteristics such as volume, peak flow and arrival time to peak flow. In the present study, we used reanalyzed precipitation data and then evaluated the simulated streamflow using this precipitation data in the Zoshk subbasin. The precipitation data was validated with in situ data, of Kashafrood basin.Materials and Methods The reanalysis precipitation data was selected from the ERA5 precipitation data, and the HEC-HMS was used for the rainfall-runoff simulation. The basin parameters were calculated by the GIS menu. This menu is the newest option in the HEC-HMS software that needs only the DEM basin for calculating the basin parameters. In the present study, we should validate the ERA5 reanalysis precipitation data with in situ data, so we did that in the Kashafrood basin. The number of the rain gauge stations were 34, but some of the stations didn't have complete data and omitted them from the list of the rain gauge stations. For the validation ERA5 reanalysis precipitation data was used from the R, NSE, RMSE, Bias, FAR, POD and TS statistical indicators. These indicators were calculated by programming in EXCEL Visual Basic. The ERA5 precipitation data was evaluated for the Kashfarood basin at daily and monthly time steps. The DEM Zoshk was downloaded with the spatial resolution of 12.5 meters from ALOS-PALSAR satellite and then the basin parameters were calculated by the GIS menu. The SCS curve number was selected as a loss method. In this method, the calculations related to the percentage of impermeability and the average curve number of each sub-basin were obtained through land use and curve number layers, respectively. The SCS unit hydrograph was selected as a transform method. The recession method was selected as a base flow method. NSE and PBias were used for the calibration and validation events in HEC-HMS. In this way, at first the HEC-HMS model was calibrated by tow in situ rainfall-runoff events (91/1/11 and 91/2/6), and then validated by one in situ rainfall-runoff event (99/1/23). For validation streamflow of the ERA5 reanalysis precipitation data, the event on 99/1/23 was used and their streamflow hydrographs were evaluated with each other in Zoshk station.Results and Discussion The results showed that the reanalysis precipitation data of ERA5 had underestimation in daily and monthly time steps. Also in monthly time step, the accuracy of these precipitation dataset in detecting precipitation events (in terms of FAR, TS, and POD indices) was higher than a daily one. In addition, in monthly time steps it had worse accuracy in summer months than the rest of the year in detecting precipitation events (in terms of FAR, TS, and POD indices). For streamflow evaluation, in the calibration phase both NSE was in very good and good ranges, and PBias was in very good, good and acceptable ranges. In addition, the model underestimated the observational one. Finally the ERA5 reanalysis precipitation data was compared by 99/1/23 hydrograph event. The streamflow hydrograph from the ERA5 reanalysis precipitation data was underestimated due to ERA5 underestimation of the precipitation at the Zoshk rain gauge on the days corresponding to the 23/6/99 incident. The ERA5 reanalyzed precipitation data with NSE and Bias percentage coefficients in unacceptable range (NSE≤0.5 and PBias≤±25), compared to flow hydrograph obtained from Zoshk station precipitation data, the efficiency of this precipitation dataset is low. The range of the streamflow hydrograph from the ERA5 precipitation data was unsatisfactory in compared to the observational hydrograph (NSE = -0.47 and PBias = -55.16).Conclusion In general, the accuracy of the flow hydrograph of this product compared to the flow hydrograph of the precipitation data of Zoshk station (NSE = 0.64 and PBias = -15.82), cannot be a relatively reliable source instead of in situ rainfall data in hydrological simulation. The suggestion for future studies is to evaluate other rainfall data based on remote sensing methods in hydrological modeling.
M. Mahmoodi; M. Honarmand; F. Naseri; S. Mohammadi
Abstract
Introduction: Runoff estimation is one of the main concerns of hydrologists and plays a key role in various engineering calculations and designs. Many factors such as climate, topography, soil properties, land cover, etc, are involved in producing surface runoff. Land use and land cover changes have ...
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Introduction: Runoff estimation is one of the main concerns of hydrologists and plays a key role in various engineering calculations and designs. Many factors such as climate, topography, soil properties, land cover, etc, are involved in producing surface runoff. Land use and land cover changes have a direct impact on the hydrological cycle in the ecosystem. The most common model of surface runoff estimation is the curve number model developed by the US Soil Conservation Service (SCS-CN). Accurate estimation of its important parameters increases its precision and performance. Land use is one of the most important parameters of this model.Remote sensing (RS) and geographic information system (GIS) technologies are used in order to increase its speed and accuracy of estimation. One of the problems that have occurred in the Kashaf-Rood Basin is the extensive land use changes that may cause changes in peak discharge and surface runoff volume. In this study, due to the great importance and impact of land cover change on increasing flood risk, the effects of land use change over 28 years (from 1987 to 2015) on flood hydrograph characteristics were investigated.
Materials and Methods: The Kashaf-Rood basin is a part of the Ghara-Ghum basin. The total area of the basin is 16779 square kilometers with the highest and lowest elevation of 3235 and 378 meters above sea level, respectively . The length of the Kashaf-Rood River from the highest point to the outlet of the basin is about 374 km and its average and gross river slope are 0.0028 and 0.0043 m/m, respectively. The digital elevation model was used to calculate the topographical properties, hydrological properties and geometrical corrections required on satellite images. In this research, the data of the Global Digital Elevation Model (ASTER) with a spatial accuracy of 30 m was used. Also, the soil hydrologic group map prepared in Ghara-Ghum water resources balance studies was used. Since no land use change occurs in the short term and can be detected at long intervals, a 28-year interval was chosen for satellite imagery. In general, five images of Landsat satellite are needed for full coverage of the Kashaf-Rood Basin. For the oldest data, Landsat 5 images and for the latest data, Landsat 8 images were used. ERDAS IMAGINE 2014 software was used to digitally process satellite images. The images were classified in three methods: The Minimum distance, Mahalanobis distance and the Maximum Likelihood. In order to select the appropriate method, after applying different classification algorithms for the image of 2015, the accuracy of their classification was evaluated and, the image of 1987 was also classified based on the selected method. By combining soil hydrological group and land use map derived from Landsat satellite imagery using ArcGIS 10.3 software, the curve number maps for 1987 and 2015 were prepared. In the present study, the US soil conservation service standard curve number method (SCS-CN) was used to calculate the amount of rainfall and losses in the HEC-HMS model. For the calibration of the HEC-HMS model, four flood events at the bridge of Khatun Kashaf-Rood hydrometric station with relatively concomitant precipitation were selected. Three flood events were used for calibration and one flood event for validation.
Results and Discussion: The images were classified into three methods: The Minimum distance, Mahalanobis distance, and the Maximum Likelihood. Comparing the results of these three methods showed that their overall accuracy in evaluating and identifying land use was 78.5, 83.7 and 87.3, respectively. Thus, the maximum likelihood algorithm was used to classify the images and the image of the year 1987 was classified with this method. Ten land use classes were identified in the study area. The results showed that during the 28 years of study, the area of rocky lands and rangelands did not change. The highest percentage of change was due to water zones, poor rangelands and residential lands, which increased by 189, 143 and 50 percent, respectively. The highest amount of increase in the area occurred in the poor rangelands, which 1514 km2, and the highest decrease occurring in moderate rangelands which is 1278 km2. By combining soil hydrological group maps and land use maps in ArcGIS software and using standard tables, the curve number maps for 1987 and 2015 were prepared. The weighted average of the curve number in the mean moisture conditions for 1987 and 2015 was 77.5 and 78.4 units, respectively. After performing the calibration and validation steps, the HEC-HMS hydrological model was used to investigate the impact of land-use change on the flood hydrograph of the Kashaf-Rood River between 1987 and 2015. According to the results, in all four events which were studied, land-use changes have increased the peak of discharge and the flood volume over the 28 years of study. On average, the peak flood discharge in 2015 was 15.2% higher than the peak flood discharge in 1987, and similarly, the flood volume increased by 13.7% during the study period.
Conclusion: In conclusion, it can be derived that in recent decades, land-use changes which were caused by human interference, affected the flood characteristics and increased the risk of flooding in the Kashaf-Rood river. Therefore, land use must be managed and prevented further destruction of natural resources to prevent flooding in the area.
Khodayar Abdollahi; Somayeh Bayati
Abstract
Introduction: Curve number (CN) is a hydrologic parameter used to predict the direct runoff depth or the excessive rainfall that infiltrates into the soil. This parameter, which indicates surface water retention, is very important in the processes relating to flooding. Vegetation of the region is a major ...
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Introduction: Curve number (CN) is a hydrologic parameter used to predict the direct runoff depth or the excessive rainfall that infiltrates into the soil. This parameter, which indicates surface water retention, is very important in the processes relating to flooding. Vegetation of the region is a major factor affecting peak flow and flood volume. The peak flow is highly influenced by the land surface characteristics, for example at the time that vegetation coverage is naturally low or while vegetated areas are decreasing, the peak discharges increase as well. In this study, the flood hydrograph of Kareh-Bas Basin was simulated using the HEC-HMS model. The simulation was used to estimate the values of the annual curve number in the basin of interest.
Materials and Methods: Model data requirements for this study were temperature, precipitation, and evapotranspiration and discharge time series. The model was calibrated for the period 2000-2010. Then, the model was implemented independently for simulating of rainfall-runoff for each year without any change in the optimized parameters. The model was calibrated only by changing curve number. The average curve number of the basin for each year was computed using the weighted mean method. The MODIS leaf area index raster maps were downloaded from the Modis site. The maps were converted into ASCII format for spatial statistics and calculating the monthly spatial average. The correlation between the curve number and leaf area index was investigated by a nonlinear curve fitting. This lead to the development of a curve number as a function of the vegetation cover for each year. Finally, the accuracy of the developed relationship was investigated using the Nash-Sutcliffe efficiency coefficient by comparing the curve number obtained from the HEC-HMS model and the simulated values from the new relationship.
Results and Discussion: The obtained Nash-Sutcliff coefficient of 0.58 showed that the HEC-HMS model was capable to simulate the flood hydrograph with relatively good accuracy. The sub-basin spatial mean showed that the sub-basins 1 and 2 take the highest curve number values. This indicates that surface water retention in these sub-basins is less than the other sub-basins, which may lead to a sharper hydrological response or flood. In sub-basins 3 and 4, where vegetation density is higher thus land use acts as a predominant factor in hydrologicalbehavior of these sub-basins, the curve number was lower. The study shows the hydrological response depends on the temporal variation of the land cover, for instance in 2010, when the leaf area index increased by a factor of 1.4, the curve number has decreased to 47. As it is predictable with decreasing vegetation the peak discharge and flood volume was increasing. We found a direct nonlinear relationship between basin scale Leaf Area Index and Curve Number with a correlation coefficient of 0.7, indicating that the variation of the curve number is a function of the leaf area index. The developed model allows calculating curve number values based on the remotely sensed leaf area index. This relationship can be used as an auxiliary function for capturing the vegetation changes and dynamics. The accuracy of the derived equation was evaluated in terms of Nash-Sutcliffe's efficiency coefficient. A value of Nash-Sutcliff coefficient of 0.72 showed that this relationship is good enough for calculating basin or sub-basin curve number values capturing the dynamics of leaf area index.
Conclusions: The obtained Nash-Sutcliff efficiency coefficient from HEC-HMS showed that the model was able to simulate the flood hydrograph of Kareh-bas basin with relatively good accuracy. However, the visual interpretation shows there is a weakness in the simulation of the falling limb of the simulated hydrographs. This may be an indication that the drainage of stored water at the basin was not well-simulated by the model. In general, it can be said that peak discharge and flood volume were under-estimated. By increasing the curve number, the peak discharge values also were increasing. The pair data for spatially weighted values for curve number and averaged annual leaf area index showed that an increase in leaf area index leads to a lower value in obtained curve number. This may result in lower peak discharge and volume of the flood. Such relationships may be taken as a measure for flood control. Meanwhile remotely sensed leaf area index products may be considered as an opportunity to capture the dynamics of the land cover.
R. Garmeh; Alireza Farid-hosseini; majid hashemi nia; A. Hojjati
Abstract
Introduction: Planning and management of water resource and river basins needs use of conceptual hydrologic models which play a significant role in predicting basins response to different climatic and meteorological processes. Evaluating watershed response through mathematical hydrologic models requires ...
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Introduction: Planning and management of water resource and river basins needs use of conceptual hydrologic models which play a significant role in predicting basins response to different climatic and meteorological processes. Evaluating watershed response through mathematical hydrologic models requires finding a set of parameter values of the model which provides thebest fit between observed and estimated hydrographs in a procedure called calibration. Asmanual calibration is tedious, time consuming and requires personal experience, automaticcalibration methods make application of more significant CRR models which are based onusing a systematic search procedure to find good parameter sets in terms of at least oneobjective function.
Materials and Methods: Conceptual hydrologic models play a significant role inpredicting a basin’s response to different climatic and meteorological processes within natural systems. However, these models require a number of estimated parameters. Model calibration is the procedure of adjusting the parametervalues until the model predictions match the observed data. Manual calibration of high-fidelity hydrologic (simulation) models is tedious, time consuming and sometimesimpractical, especially when the number of parameters islarge. Moreover, the high degrees of nonlinearity involved in different hydrologic processes and non-uniqueness ofinverse-type calibration problems make it difficult to find asingle set of parameter values. In this research, the conceptual HEC-HMS model is integrated with the Particle Swarm Optimization (PSO) algorithm.The HEC-HMS model was developed as areplacement for HEC-1, which has long been considered as astandard model for hydrologic simulation. Most of thehydrologic models employed in HEC-HMS are event-basedmodels simulating a single storm requiring the specificationof all conditions at the beginning of the simulation. The soil moistureaccounting model in the HEC-HMS is the onlycontinuous model that simulates both wet and dry weatherbehavior.Programming of HEC –HMS has been done by MATLAB and techniques such as elite mutation and creating confusion have been used in order to strengthen the algorithm and improve the results. The event-based HEC-HMS model simulatesthe precipitation-runoff process for each set of parameter values generated by PSO. Turbulentand elitism with mutation are also employed to deal with PSO premature convergence. The integrated PSO-HMS model is tested on the Kardeh dam basin located in the Khorasan Razavi province.
Results and Discussion: Input parameters of hydrologic models are seldomknown with certainty. Therefore, they are not capable ofdescribing the exact hydrologic processes. Input data andstructural uncertainties related to scale and approximationsin system processes are different sources of uncertainty thatmake it difficult to model exact hydrologic phenomena.In automatic calibration, the parameter values dependon the objective function of the search or optimization algorithm.In characterizing a runoff hydrograph, threecharacteristics of time-to-peak, peak of discharge and totalrunoff volume are of the most importance. It is thereforeimportant that we simulate and observe hydrographs matchas much as possible in terms of those characteristics.
Calibration was carried out in single objective cases. Model calibration in single-objective approach with regard to the objective function in the event of NASH and RMSE were conducted separately.The results indicated that the capability of the model was calibrated to an acceptable level of events. Continuing calibration results were evaluated by four different criteria.Finally, to validate the model parameters with those obtained from the calibration, tests perfomed indicated poor results. Although, based on the calibration and verification of individual events one event remains, suggesting set is a possible parameter.
Conclusion: All events were evaluated by validations and the results show that the performance model is not desirable. The results emphasized the impossibility of obtaining unique parameters for a basin. This method of solution, because of non-single solutions of calibration, could be helpful as an inverse problem that could limit the number of candidates. The above analysis revealed the existence of differentparameter sets that can altogether simulate verificationevents quite well, which shows the non-uniqueness featureof the calibration problem under study. However, the methodologyhas benefited from that feature by finding newparameter intervals that should be fine-tuned further inorder to decrease input and model prediction uncertainties.The proposed methodology performed well in the automatedcalibration of an event-based hydrologic model;however, the authors are aware of a drawback of the presentedanalysis – this undertakingwas not a completely fair validationprocedure. It is because validation events represent possiblefuture scenarios and thus are not available at the time ofmodel calibration. Hence, an event being selected as a validationevent should not be used to receive any morefeedback for adjusting parameter values and ranges.However,this remark was not fully taken into consideration, mostlybecause of being seriously short of enough observed eventsin this calibration study. Therefore, the proposed methodology,although sound and useful, should be validated inother case studies with more observed flood events.
Z. Parisay; V. Sheikh; M. Ownegh; A. Bahremand
Abstract
Flood is one of the devastating phenomena which every year incurs casualties and property damages. Flood zonation is an efficient technique for flood management. The main goal of this research is flood hazard and risk zonation along a 21 km reach of the Gorganrud river in Bustan dam watershed considering ...
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Flood is one of the devastating phenomena which every year incurs casualties and property damages. Flood zonation is an efficient technique for flood management. The main goal of this research is flood hazard and risk zonation along a 21 km reach of the Gorganrud river in Bustan dam watershed considering two conditions: present landuse condition and scenario planning. To this end a combination of a hydrologic model (the distributed HEC-HMS with the Mod-Clark transform option) and a hydraulic model (HEC-RAS) were used. The required inputs to run the Mod-Clarck module of HEC-HMS are gridded files of river basin, curve number and rainfall with the SHG coordinate system and DSS format. In this research the input files were prepared using the Watershed Modeling System (WMS) at cell size of 200 m. Since the Mod-Clark method requires rainfall data as radar format (NEXRAD), the distributed rainfall mapseries with time intervals of 15 minutes prepared within the PCRaster GIS system were converted to the DSS format using the asc2dss package. also the curve number map was converted to the DSS format using HEC-GeoHMS. Then, these DSS files were substituted with rainfall and curve number maps within the WMS. After calibration and validation, model was run for return periods of 2, 5, 10, 25, 50, 100 and 200 years, in two conditions of current landuse and scenario planning. The simulated peak discharge data, geometric parameters of river and cross section (at 316 locations) data prepared by the HEC-GeoRAS software and roughness coefficients data, were used by the HEC-RAS software to simulate the hydraulic behavior of the river and flood inundation area maps were produced using GIS. The results of the evaluation showed that in addition to the percent error in peak flow, less than 3.2%, the model has a good performance in peak flow simulation, but is not successful in volume estimation. The results of flood zones revealed that from the total area in floodplain with return period of 200 years, 96.94% of the area is exposed to the return period of 25 years floods, and a main part of damages go to the floodplains which are under a return period of 25 years floods.
