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Automatic calibration of the tank model
Abstract
The automatic calibration is done not by a hill-top climbing method but by a trial and error method carried out automatically by a computer program. The feedback procedure is made by comparing some criteria obtained from the observed calculated hydrograph output from the working tank model. The two criteria are discharge volume and the shape of the hydrograph. The feedbacks of these two criteria correspond to displacement feedback and velocity feedback in automatic control. The feedback procedure starts from some initial model and converges very quickly after several (usually less than 15) iterations, and the result obtained is very good. -from Author
... It works on the principles of tank model for prediction of runoff while for flood routing it uses kinematic wave model. Tank model non-linear relationships, based on Manning and hyperbolic approximations, are used to calculate the outflow from each tank [16][17][18]. IFAS uses a four-layer non-linear tank structure to minimize the simulations time [15]. ...
... The tank model introduced by Sugawara [16] includes four tanks to analyse daily discharges. According to him, different hydrological processes occur in different tanks namely, surface tank, sub-surface tank, aquifer tank and river tank. ...
... This model can include infiltration, water storages, and percolation processes. It has been used by many investigators and researchers to simulate and analyse the rainfallrunoff processes in various basins for different periods [16][17][18][19][20][21][22]. Fig. 1 shows the illustration of Tank Model showing parameters and classification. ...
Integrated Flood Analysis System (IFAS) model, based on Tank model philosophy, is a widely used flood forecasting model that has the capability to simulate the catchment processes of any river system provided the surface and aquifer parameters of each sub-model are accurately calibrated. In this study, sensitivity analysis and optimization of hydrogeological parameters of Tank model have been performed to identify the key hydrogeological parameters and their significance in simulating the stream flows in the basins of two important rivers of Pakistan – Jhelum River and Chenab Rivers – respectively. IFAS includes a set of four sub-models namely: surface tank model, sub-surface tank model, aquifer tank model and river course model. Each of the sub-models simulates its own flow processes using surface/aquifer parameters. In this study, sensitivity analysis is performed to identify the parameters that significantly affect the model performance to simulate the flows in the river. Linear stochastic metamodels of Jhelum River and Chenab River Basins developed in this study played the role of metamodels or surrogate functions to determine the ranges of parameter values in different flow periods. The outcome demonstrates when the aquifer tank parameters values obtained from metamodels are applied, the simulation results in a nearly accurate calibration, which clearly indicates the efficiency of present methodology and the important role of hydrogeological parameters. Further, the analysis of the variability in the effectiveness of these parameters in different flow periods as well as for different catchments areas depicts spatial-temporal heterogeneous characteristics. This confirms that the analysis should be directed independently for each study basin because the results of sensitivity analysis are not transferable among catchments.
... Tank models are a type of lumped hydrological models, and they have been applied to study a wide range of watersheds owing to their computational and conceptual simplicity [8,13,36,37]. Tank models tend to have more parameters as compared to other parsimonious models because they are designed to represent non-linear responses of a watershed using multiple linear equations [8]. Thus, parameter calibration can be challenging, especially when streamflow observations are limited [36,37]. ...
... Tank models tend to have more parameters as compared to other parsimonious models because they are designed to represent non-linear responses of a watershed using multiple linear equations [8]. Thus, parameter calibration can be challenging, especially when streamflow observations are limited [36,37]. The models have been widely used in East Asia, including Korea, Japan, and Taiwan, and studies have demonstrated their accuracy and performance in applications for humid and mountainous watersheds [8,9,17,38,39]. ...
... The model parameters are estimated from the relationship between parameter values and watershed characteristics, which are developed using observations made in gauged watersheds. The Tank model was originally developed with four layers (4-Tank) [37], and the parameter values of the 4-Tank models were generally derived from selected watershed features in Japan and Germany [4,17]. MRE, MSE, and RMSE refer to mean relative error, mean square error, and root mean square error, respectively. ...
Regionalized lumped rainfall-runoff (RR) models have been widely employed as a means of predicting the streamflow of an ungauged watershed because of their simple yet effective simulation strategies. Parameter regionalization techniques relate the parameter values of a model calibrated to the observations of gauged watersheds to the geohydrological characteristics of the watersheds. Thus, the accuracy of regionalized models is dependent on the calibration processes, as well as the structure of the model used and the quality of the measurements. In this study, we have discussed the potentials and limitations of hydrological model parameter regionalization to provide practical guidance for hydrological modeling of ungauged watersheds. This study used a Tank model as an example model and calibrated its parameters to streamflow observed at the outlets of 39 gauged watersheds. Multiple regression analysis identified the statistical relationships between calibrated parameter values and nine watershed characteristics. The newly developed regional models provided acceptable accuracy in predicting streamflow, demonstrating the potential of the parameter regionalization method. However, uncertainty associated with parameter calibration processes was found to be large enough to affect the accuracy of regionalization. This study demonstrated the importance of objective function selection of the RR model regionalization.
... The tasks in relation to estimation runoff volumes and flood peaks can be, however, easily simplified by adopting a modelling concept understanding rainfall partitioning and the principal factors triggering runoff [3][4][5]. The rainfall-runoff modelling approach is most frequently used in hydrology for estimating the runoff signal which leaves the catchment from the rainfall signal received by the basin [6,7]. Different techniques of the hydrologic modelling approach have been so far adopted in different studies, with some of them focused on an empiricalbasis and other modelling approaches based on the distributed modelling concept [1,8]. ...
... Calibration and validation tasks are fundamental operations in many modelling studies, including hydrological studies [6,9,10,21,28]. Hydrological models basically need a series of runoff data for model calibration and validation purposes [20,30,33].The runoff data for this study (1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005) was taken from the Ethiopian Ministry of Water, Irrigation and Electricity and implemented while calibrating the parameters in the HEC-HMS model. ...
... Calibration and validation tasks are fundamental operations in many modelling studies, including hydrological studies [6,9,10,21,28]. Hydrological models basically need a series of runoff data for model calibration and validation purposes [20,30,33].The runoff data for this study (1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)) was taken from the Ethiopian Ministry of Water, Irrigation and Electricity and implemented while calibrating the parameters in the HEC-HMS model. ...
Estimation of runoff is vital forplanning activities in relation to integrated watershed management and flood protection measures. This research was conducted at one of the catchments in Abbay River (upper Blue Nile River) basin to assess the applicabilityof the Hydrologic Engineering Centre Hydrological Modelling Software (HEC-HMS) modelfor simulation of runoff. It was aimed at selecting the best loss and transform methods in the model, as well as testing the applicability of the calibrated model to ungauged watersheds. Two loss methods such as soil conservation service (SCS) and initial and constant methods with two transform methods including SCS and Clark unit hydrographs were considered in the study for selecting the best combinations applicable in the area. While comparing the simulation results of each combination, better results were obtained in the model set containing the initial and constant loss method and SCS unit hydrograph with a Nash-Sutcliff Efficiency (NSE) of 82.8%, R2 of 0.83, and 10.71% of relative bias errors, followed by initial and constant with Clarks unit hydrograph, and it can be used for similar ungauged watersheds.
... The Tank model estimates runoff from precipitation data (Sugawara, 1961(Sugawara, , 1972(Sugawara, , 1979Sugawara & Singh, 1995). It is a lumped hydrologic model that simulates the water balance of a basin using tanks or reservoirs arranged in a vertical series, where the storage of the first tank is determined by precipitation and the storage of the other tanks is determined by the infiltration from the upper tank (Sugawara and Singh 1995). ...
... It is a lumped hydrologic model that simulates the water balance of a basin using tanks or reservoirs arranged in a vertical series, where the storage of the first tank is determined by precipitation and the storage of the other tanks is determined by the infiltration from the upper tank (Sugawara and Singh 1995). For a better understanding of the Tank model structure, the reader could access Sugawara (1961Sugawara ( , 1972Sugawara ( , 1979, and Sugawara & Singh (1995). ...
Calibration of hydrologic models estimates parameter values that cannot be measured and enable the rainfall-runoff processes simulation. Multi-objective evolutionary algorithms can make the calibration faster and more efficient through an iterative process. However, the standard stopping criterion used to stop the iterative process is to reach a pre-defined number of iterations defined by the modeller. Alternatively, the Ticona stopping criterion is based on the minimum number of iterations required to achieve a determined number of non-dominated solutions in the Pareto front, resulting in a reduction of the computational time without losing performance during the calibration processes. We evaluated the Ticona stopping criterion in the Tank Model calibration. The calibration processes were performed using data from two river basins, with three genetic algorithms and two objective functions. The Ticona stopping criterion required a computational time 27.4% to 44.1% lower than using the standard stopping criterion and were obtaining similar results in simulated streamflow time series and similar values of the best set of parameters.
Keywords:
Multi-objective evolutionary algorithm; Tank model; Stopping criterion; NSGA-II; NSGA-III; SPEA-II
... Many rainfall-runoff models, such as HEC-HMS [27], TOPMODEL [28], Tank model [29] and others, which have been applied for runoff prediction, cannot compute flood inundation. Therefore, the RRI model, developed by Sayama et al. [20], was employed to simulate flood characteristics such as flood runoff, inundation depth, flood duration and extent areas. ...
... Flood Hazard Assessment and Impact Analysis205Many rainfall-runoff models, such as HEC-HMS[27], TOPMODEL[28], Tank model[29]and 206 others, which have been applied for runoff prediction, cannot compute flood inundation. Therefore, 207 the RRI model, developed by Sayama et al.[20], was employed to simulate flood characteristics such208 as flood runoff, inundation depth, flood duration and extent areas. ...
This study focused on the analysis of land-use/land-cover changes and their impact on flood runoff, flood hazards and inundation, focusing in the Pampanga River basin of the Philippines. The land-cover maps for the years 1996 and 2016 were generated using Landsat images, and the land cover changes were analyzed using TerrSet Geospatial Monitoring and Modeling System (TGMMS). Based on an empirical approach and considering variable factors, the land-cover maps for the future were predicted using Land Change Modeler (LCM). After preparation of land-cover maps for past and future years, flood characteristics were analyzed using a distributed hydrological model named the rainfall runoff inundation (RRI) model with a land-cover map for different years. The impacts of land cover changes on flood runoff, flood volume and flood inundation were analyzed for 50- and 100-year floods. The results show that flood runoff, flood inundation volume and flood extent areas may increase in the future due to land-cover change in the basin.
... A water balance analysis of each reservoir was performed using the Daily Irrigation Reservoir Operation Model (DIROM). The DIROM simulates daily inflow and the release rate for an irrigation reservoir based on the tank model (a typical conceptual rainfall–runoff model)[51]to estimate inflow into the reservoir and watershed runoff using watershed area and land‐use as watershed characteristic factors. The data used in the daily water balance models for the irrigation reservoirs were categorized into the following three groups: meteorological data, irrigation regional data and reservoir specifications data. ...
... A water balance analysis of each reservoir was performed using the Daily Irrigation Reservoir Operation Model (DIROM). The DIROM simulates daily inflow and the release rate for an irrigation reservoir based on the tank model (a typical conceptual rainfall–runoff model)[51]to estimate inflow into the reservoir and watershed runoff using watershed area and land-use as watershed characteristic factors. The data used in the daily water balance models for the irrigation reservoirs were categorized into the following three groups: meteorological data, irrigation regional data and reservoir specifications data. ...
Reservoirs are principal water resources that supply irrigation water to paddy fields and play an important role in water resources management in South Korea. For optimal irrigation reservoir operation and management, it is necessary to determine the duration of irrigation water shortages. Management of reservoir operation and irrigation scheduling should take into consideration essential variables that include the water supply in a reservoir and the water demand in the associated irrigation district. The agricultural water supply and demand show different patterns based on the variability and uncertainty of meteorological and hydrological phenomena. The duration of excessive water supply can be quantitatively determined through analysis of deviations and changes in the timing of agricultural water supply and demand. In this study, we introduce an approach to assess the vulnerable seasons of paddy irrigation to enable more effective operation and management of reservoirs. The vulnerable seasons were evaluated through comparison of the potential water supply capacity and irrigation water requirements based on water budget analysis via a time series change analysis. We have assessed the changing in the total duration and duration shifts of the vulnerable irrigation seasons for four agricultural reservoirs using past observed data (1981–2010) from meteorological stations maintained by the Korea Meteorological Administration (KMA) and projected climate change scenarios (2011–2100) as depicted by the Representative Concentration Pathways (RCPs) emission scenarios. For irrigation vulnerable seasons under both the RCP 4.5 and RCP 8.5 scenarios, the results showed periods of significant increases in which total vulnerable seasons compared to the historical period; the longest duration of vulnerability occurred during the 2071–2100 period under the RCP 8.5. Identification of the vulnerable seasons for paddy irrigation can be applied in agricultural water management to more effectively manage reservoir operation during irrigation periods with climate changes.
... Conceptual models have taken a large part in modeling this relationship. The ''tank model'' Sugawara [1,2 ] is one of these methods. Indeed, the major difficulty in this model is the calibration of parameters in order to achieve a good estimate of the observed data. ...
... Ii =Bi Hi (2) where Ii is the infiltration from tank i to lower tank i+1 in height (unit length/time), and Bi the infiltration outlet coefficient. ...
Modeling the rainfall-runoff relationship with conceptual models has always been a fascinating subject for hydrologists in view of its practical importance and complexity. This study presents a comparative assessment of the performance of two well established rainfall-runoff conceptual models. A first model called: Model ‘Genie Rural’ (i.e. Agricultural Engineering) and abbreviated GR, developed by Cemagref has been extensively tested in the Mediterranean watersheds and some basins in African countries. When applied to Algerian basins, the different version of the GR model gave satisfactory results, particularly for long time steps (monthly and annual data). In this work, the tank Model by Sugawara using Kalman filter for adaptive calibration is developed and tested for the first time to assess rainfall-runoff in Algerian basins. The results appear to be very prominent and far better than those given by the GR models including daily time steps. Indeed, a comparison between the two models established for daily and monthly data was performed on the three (03) Algerian Basins (i.e. Isser, Zardezas basin and Cheffia). Calibration of the Tank model parameters was performed by Kalman filter. Furthermore, the structure of tank model (i.e: number of tanks, number of outlets in each tank, and their location) was determinated for the studied basins.
... However, in order to establish the extent to which this approach is ro-bust to such errors, a more extensive analysis than that presented here is needed. Flow-duration curves have previously been used in model calibration by Sugawara (1979), Yu and Yang (2000), as one of the criteria considered by Refsgaard and Knudsen (1996) and by Blazkova and Beven (2009), and as a qualitative measure of model performance, e.g. by Houghton-Carr (1999), Kavetski et al. (2011), and Son and Sivapalan (2007). ...
... FDCs have been used previously in model calibration and evaluation (Blazkova and Beven, 2009;Son and Sivapalan, 2007;Sugawara, 1979;Yu and Yang, 2000). The novel aspect of our use of the FDC is that it takes account of uncertainty in the discharge data and at the same time shows that the FDC can work surprisingly well as a single criterion in some cases. ...
The degree of belief we have in predictions from hydrologic models depends on how well they can reproduce observations. Calibrations with traditional performance measures such as the Nash-Sutcliffe model efficiency are challenged by problems including: (1) uncertain discharge data, (2) variable importance of the performance with flow magnitudes, (3) influence of unknown input/output errors and (4) inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. A new calibration method using flow-duration curves (FDCs) was developed which addresses these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs) of the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested – based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WASMOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments without resulting in overpredicted simulated uncertainty. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application e.g. using more/less EPs at high/low flows. While the new method is less sensitive to epistemic input/output errors than the normal use of limits of acceptability applied directly to the time series of discharge, it still requires a reasonable representation of the distribution of inputs. Additional constraints might therefore be required in catchments subject to snow. The results suggest that the new calibration method can be useful when observation time periods for discharge and model input data do not overlap. The new method could also be suitable for calibration to regional FDCs while taking uncertainties in the hydrological model and data into account.
... If the interest is primarily in the discharge simulation only, these models can provide good simulations as physically based distributed models (Pechlivanidis et al. 2011). Sacramento Model (SAC) (Burnash et al. 1973), Xin'anjiang Hydrological Model (Zhao 1992) and Tank Model (Sugawara 1979) are some typical lumped hydrological models. For distributed models, parameters can easily vary in space at the desired resolution. ...
Flood simulation in sub-humid regions is one of the difficult issues in hydrology. Liulin experimental watershed, a typical sub-humid region in northern China, was selected for flood simulation. 20 rainfall–runoff events from 1995 to 2021 were selected to calibrate and validate the sub-distributed HEC-HMS model. The applicability of the model to flood simulation in the Liulin experimental watershed was explored. The influences of different runoff generation methods (SCS-CN method and initial constant method) and simulation time steps (1 h and 30 min) on flood simulation were compared. The applicability of the model to different antecedent moisture conditions and different flood characteristics was also analyzed. The results showed that all the schemes of rainfall–runoff models with different runoff generation methods and time steps have satisfactory performance in simulating floods. When the time step is 1 h, the initial constant runoff generation method was more suitable for runoff simulation, however, when the time step is 30 min, the SCS-CN runoff generation method was more robust. As the simulation time step decreased, the model performance was improved, but the improvement amplitude was greater when the SCS-CN method was used. In addition, the model performed better when antecedent moisture was higher, and the flood was single-peak. When the measured peak discharge was lower than 100 m³/s, the model could simulate the peak discharge and peak time better, and conversely, the model could simulate the flood volume and flood hydrograph better. This study is valuable for flood forecasting in sub-humid areas.
... Flow rate and water temperature were estimated by a hydrological model based on Suzuki et al. (2022), which considers differences in groundwater discharge depending on catchment geology (see Appendix 1 for details). Briefly, the daily flow rate on the stream in each 1 km mesh was reproduced by four-layered tank models (Sugawara 1979), and the flow and heat flux were tracked along the streamflow. Importantly, different tank parameters were given for the volcanic areas and other areas, based on validation using measured water temperature data from field surveys at multiple sites in the study area. ...
Context
Global climate change poses a significant threat to the habitat connectivity of cold-water-adapted organisms, leading to species extinctions. If gene flow can be modeled by landscape variables, changes in connectivity among populations could be predicted. However, in dendritic and heterogeneous stream ecosystems, few studies have estimated the changes in gene flow from genetic data, in part due to the difficulty in applying landscape genetics methods and accessing water temperature information.
Objectives
Inferring the determinants and future changes of the gene flow in the cold-water adapted fluvial sculpin Cottus nozawae using a recently developed model-based riverscape genetics technique and a hydrological model for estimating water temperature.
Methods
The strength of gene flow on each stream section was modeled by watershed-wide riverscape variables and genome-wide SNP data for C. nozawae in the upper reaches of the Sorachi River, Hokkaido, Japan. Future changes in gene flow were inferred by this model and hydrologically estimated water temperatures under the high greenhouse gas concentration scenario (IPCC RCP8.5).
Results
Stream order, water temperature, slope, and distance were selected as riverscape variables affecting the strength of gene flow in each stream section. In particular, the trend of greater gene flow in sections with higher stream order and lower temperature fluctuations or summer water temperatures was pronounced. The map from the model showed that gene flow is overall prevented in small tributaries in the southern area, where spring-fed environments are less prevalent. Estimating future changes, gene flow was predicted to decrease dramatically at the end of the twenty-first century.
Conclusions
Our results demonstrated that the connectivity of cold-water sculpin populations is expected to decline dramatically in a changing climate. Riverscape genetic modeling is useful for gaining information on population connectivity that does not fully coincide with habitat suitability.
... The daily basin-average rainfall was estimated using the Thiessen polygon method. Linear correlation between rainfall and surface runoff, which was calculated using three-stage tank model [45] Gunay et al. [44] reported a non-significant trend and large variability of rainfall in the watershed. To neglect the effect of such great variability in precipitation, only the datasets collected during the wet months were considered. ...
Soil water storage properties, which are affected by land management practices, alter the water balance and flow regimes in watersheds; thus, it is highly plausible to clarify the influence of such management practices on the water storage condition by analyzing the long-term variations in discharge. In this study, the changes in soil water storage characteristics of the Ogouchi Dam watershed, which had undergone intensive forest management through the decades, were investigated using two approaches. Reported results from the rainfall-runoff correlation analysis show a gradual and steady increase in the soil water storage capacity at weaker continuous-rainfall events, i.e., uninterrupted wet days accumulating less than 70 mm. Meanwhile, the second approach utilizing the parameter calibration in the SWAT discharge model illustrated a constant trend in the runoff potential and the high possibility of a steady improvement in the soil available water capacity. Overall, the established decadal trends were able to prove the capability of sustainable forest management, i.e., thinning, regeneration cutting, multi-layer planting, deer-prevention fences, and earth-retaining fences (lined felled trees), in improving the water conservation function of the catchment.
... A rainfall-streamflow model uses rainfall data as input to simulate the streamflow in a specific section of a river. Examples of rainfall-streamflow models commonly used are Soil Moisture Accounting Program -SMAP (Lopes et al. 1981); Tank Model (Sugawara 1961); self-calibrating hydrological model -MODHAC (Lanna and Schwarzbach 1989); and Soil and Water Assessment Tool -SWAT (Arnold et al. 2012). Lately, models based on artificial neural networks (ANN) have already been used to model the rainfall-streamflow relationship (Hsu et al. 1995;Jain et al. 2004;Farias et al. 2013;Da Silva Filho and Farias 2018;Santos et al. 2019); for river inflow prediction (Campolo et al. 1999;Kisi 2004;Kumar et al. 2004;Ciğizoğlu and Kisi 2005;Honorato et al. 2018;Santos et al. 2019); for precipitation forecast (Hall et al. 1999;Silverman and Dracup 2000;Freiwan and Cigizoglu 2005;Mirabbasi et al. 2018); for groundwater modeling (Coulibaly et al. 2001;Nayak et al. 2006;Mohanty et al. 2010); for water quality modeling (Singh et al. 2009;Gazzaz et al. 2012); for evapotranspiration estimation (Kumar et al. 2002;Trajkovic et al. 2003;Zanetti et al. 2007;Adeloye et al. 2011); and for sediment transport (Nagy et al. 2002;Ciğizoğlu and Alp 2006;Melesse et al. 2011;Farias and Santos 2014). ...
Hydrological data provide valuable information for the decision-making process in water resources management, where long and complete time series are always desired. However, it is common to deal with missing data when working on streamflow time series. Rainfall-streamflow modeling is an alternative to overcome such a difficulty. In this paper, self-organizing maps (SOM) were developed to simulate monthly inflows to a reservoir based on satellite-estimated gridded precipitation time series. Three different calibration datasets from Três Marias Reservoir, composed of inflows (targets) and 91 TRMM-estimated rainfall data (inputs), from 1998 to 2019, were used. The results showed that the inflow data homogeneity pattern influenced the rainfall-streamflow modeling. The models generally showed superior performance during the calibration phase, whereas the outcomes varied depending on the data homogeneity pattern and the chosen SOM structure in the testing phase. Regardless of the input data homogeneity, the SOM networks showed excellent results for the rainfall-runoff modeling, presenting Nash–Sutcliffe coefficients greater than 0.90.
Graphical Abstract
... Researchers have implemented hydrological models to investigate the complex hydrological processes on mountainous glacierized catchments around the world (Li et al., 2019, Liu et al., 2018a, Liu et al., 2018b, Nepal, 2016, Nolin et al., 2010, Soncini et al., 2016, Zhang et al., 2016b, including studies focusing on the main headwaters of the Tarim River , He et al., 2015, the Amudarya (Wang et al., 2016), the Syrdarya (Gan et al., 2015) and the Himalayan region Bierkens, 2012, Immerzeel et al., 2010). These studies have used different hydrological models, such as Xinanjiang (Zhao, 1980, Zhao, 1992, Tank (Sugawara, 1979), GR4J (Nepal et al., 2017), FLEX G (Gao et al., 2017, Gao et al., 2018, HBV (Braun et al., 1993, Konz et al., 2007, Soil and Water Assessment Tool (SWAT) (Douglas-Mankin et al., 2010, J2000 (Krause, 2002, Shen et al., 2018, Weather Research and Forecasting-Hydrology (WRF-Hydro) (Arnault et al., 2019, Xie et al., 2020 and Variable Infiltration Capacity (VIC) (Dang et al., 2020, Liang et al., 1994. However, many hydrological processes are simplified or ignored in hydrological models, which are the main obstacles to developing hydrological simulations in the headwaters of the Tarim River (Biskop et al., 2016, Ragettli et al., 2013. ...
Understanding hydrological changes, especially those of snow and/or glacier melt-induced floods, is vital for early flood warnings in alpine regions. However, there is limited information available regarding warming-induced changes in hydrological and flooding processes in high-mountain regions owing to data scarcity and inadequate considerations within hydrological models. This study aims to improve streamflow and flood simulations in three high-mountain headwater catchments of the Tarim River in northwest China. An improved scheme for calculating glacier melt (GM2) was coupled in the Variable Infiltration Capacity model (named VIC-GM2). Driven by bias-corrected meteorological data, VIC-GM2 exhibited good performance, as evidenced by NS, KGE and PBIAS values between the simulated and observed daily streamflow ranging from 0.69 to 0.79, 0.70 to 0.81 and -2.68% to 19.6%, respectively. In addition, annual contributions of glacier melt and snow melt to total streamflow were greater than 80% and less than 16% among the three catchments, respectively. The flood characteristics were inconsistent among the three catchments, except that flooding mainly occurred in summer. The MAF (mean annual flood) in the Yarkand River was largest, followed by that in the Yurungkax River and the Qaraqash River. The FPOT (frequency of peak over threshold) and FQ99 (frequency of Q99) (times/year) fluctuated within 1 – 1.75 and 0.25 – 1 in the three catchments, respectively. This study provides references for understanding cryosphere hydrological processes and quantifying the contribution of different components (i.e., glacier melt, snow melt and rainfall) to streamflow under a changing climate in the upper Tarim River.
... Though many studies have been done on the application of flood forecasting models from sophisticated models such as Infoworks TM to simple stage-regression flood models, the Tank model has the advantage of being practical, less expensive and yet reasonably accurate. Since its initial conceptual development in the early 1960's, the Tank model [4,5,6] has been modified based on some considerations including land use, urbanization factor and lag time. Development of PC based Tank Model real time flood forecasting system for Upper Klang Catchment had been studied by [7] using ground-based rainfall data. ...
... The rainfall patterns prior to the landslide occurrence were analysed and the soil water index (SWI) were calculated. The SWI is calculated using the tank model developed by Sugawara (1961) where the soil water index equals to the total storage volume of tanks laid vertically in series. The function of SWI is used to give an indication on the level of soil moisture in the area of landslide. ...
Nowadays, concrete is globally famous as one of the most consumed construction materials. Therefore, based on demand and the expanded concrete usage, the necessity of performing investigation about behavior, and the compelling factors on its behavior is apparent. In order to estimate the performance requirements and strength during concrete curing, it is necessary to pay more attention to its construction. Researchers provided different mathematics techniques for estimation of concrete behaviour, so that, the Fuzzy series theory is a handy tool for modelling and analyzing of vague and imprecise concepts. Here in the present article, it is aimed to predict the 28-day strength of concrete containing Metakaolin, micro-Silica, rice husk ash, and zeolite based on 7-day compressive strength using fuzzy logic. In this study we have used 5, 7.5, 10, 12.5 and 15 percent Pozzolan (by weight of cement) and we acquired 20 mix proportions together with one control mix which is free from any Pozzolan. All tests performed under the tests related to concrete workability (slump test) and the test related in hardened concrete (compressive strength) in 7, 28, and 42-day. Finally, 28-day compressive strengths were predicted using linear regression and different methods of fuzzy logic. It is found that generalized nearest neighbourhood clustering method has the most accurate prediction
for 28-day compressive strength.
... Application of the tank model for sediment yield, with analysis using 3 (three) cascade tank arrangements and the same tank model parameters [16], both for surface ruoff analysis in the form of discharge [17][18][19][20], and analysis of sediment results, namely discharge multiplied by sediment concentration. The application of the tank model to the sediment yield assumes that sediment concentrations undergo infiltration, percolation, and actual conditions are unlikely to occur in such a process, this is a weakness in the model. ...
Environmental degradation as a result of deforestation carried out in the Catchment resulted in a decrease in its ability to store water. This has the effect of increasing the amount of sediment discharge. The process of estimating sediment discharges is very difficult because the data input variables are many and varied, usually, the data are very limited, because the erosion process occurs until the sediment discharge mechanism is quite complex. The process of sediment discharges in Catchment s is influenced by rain and surface runoff and is represented in the storage type. In this study, an approach using the Tank Model was conducted. The purpose of this study is to develop a tank model for sediment discharge analysis in disaster mitigation. The steps are setting the field experiment for collecting rain and discharge sediment data as the model input and setting the model analysis by making the structure and formulation of the tank model. There are 3 proposed tank models namely Tank Model 1 (three tanks, series, and cascade), Tank Model 2 (two cascade tanks), and Tank Model 3 (three cascade tanks). Model parameters are determined using the Genetic Algorithm (AG) method optimization approach. The analysis shows that Tank Model 3, composed of 3 (three) cascade tanks, represents a Catchment better than the other 2 tank models. This can be seen from the value of the accuracy of the model, namely the value of volume error (VE), the value of relative error (RE), the value of the mean least square error (RMSE), and the value of the correlation coefficient (R). But still has a range of differences for the value of sediment discharges, the cause may be a factor in the pattern of rain spread in the hydrological process, synchronization of the measurement process and data length, and the possible assumptions of the model parameters.
... Numerous studies have used the HEC-RAS model for flood hazard simulation [17][18][19]23,28,30,34], but it requires upstream and/or downstream boundary conditions of flood hydrograph that must be obtained either from observations or simulated from other hydrological models. Reviewing the previous literature also shows that rainfall-runoff hydrological models such as HEC-HMS [40], WEB-DHM [41], the integrated flood analysis system [42], TOPMODEL [43], and the tank model [44], which have been used widely for runoff prediction, cannot generate flood inundation. Among those hydrological and hydraulic models, the rainfall-runoff-inundation (RRI) hydrological-hydraulic model developed by Sayama et al. [45], which is a grid-based distributed hydrological-hydraulic model, can simulate the rainfall-runoff processes including infiltration, flood routing in the river, and flood inundation in the flood-prone areas simultaneously. ...
Because property damage and loss of life owing to floods have increased in many countries in recent years, accurate assessment of flood risk is urgently needed for effective flood management. Improving the assessment of flood risk requires considering the impact of dam operation for flood control because dams and reservoirs play important roles in the assessment of flood hazards and associated damage. However, the impact of dam operation on flood hazards and associated damage was not considered well in previous assessments of flood risk. This paper focused on the quantitative assessment of flood hazard and risk, including the effectiveness of dam operation for flood prevention. The grid-based approach integrating the following was applied for analysis: (i) a hydrological–hydraulic model, (ii) a method considering the dam operation for flood control, and (iii) an assessment of flood damage. To assess the risk, flood characteristics were computed using the rainfall–runoff–inundation hydrological–hydraulic model, and flood damage was estimated by integrating the flood characteristics, flood damage curves, exposure characteristics, and property values. The risk was assessed by focusing on flood damage to residential buildings and assets and agricultural sectors for the largest recent floods and flood events with different return periods. This study considered the Bago River Basin of Myanmar. Results show that the dam operation for flood control in the study area reduces the flood inundation area by approximately 10% and flood damage to buildings, assets, and agriculture by approximately 40%, 60%, and 10%, respectively.
... Sugawara (Sugawara, 1979), in 1979, introduced the tank model. It consists of four tanks namely; surface, sub-surface, aquifer and river tanks, adds to the flow in the river. ...
One of the impacts of climate change is an increase in the frequency of floods. The efficient and optimized flood analysis system needs to be used for the reliable flood forecasting. The credibility and the reliability of the flood forecasting system is depending upon the framework used for its parameter optimization. A comprehensive framework for optimizing the input parameters of the computationally extensive distributed hydrological model has been presented.
A large river basin has the high spatio-temporal heterogeneity of aquifer and surface properties. Estimating the parameters in fully distributed hydrological model is a challenging task. The parameter optimization becomes computationally more demanding when the model input parameters (30 to 100 even greater) have multi-dimensional parameter space, many output parameters which make the optimization problem multi-objective and large number of model simulations requirement for the optimization. Aforementioned challenges are met by introducing the methodology to optimize the input parameters of fully distributed hydrological model, following steps are included (1) screening of the parameters through Morris sensitivity analysis method in different flow periods, so that optimization would be performed for sensitive parameters, different scalar output functions are used in this regard (2) Surrogate models or meta-models are used to simulate the hydrological response of a dynamic model (3) sampling of parameters values using the optimized ranges obtained from the meta-models developed from multivariate regression adaptive splines (MRAS); the results are evident that the parameter optimization using the proposed framework is efficient can be effectively performed. The efficiency and performance of the proposed framework has been demonstrated through the accurate calibration of the model with fewer model runs. This study also demonstrates the importance and use of scalar functions in calculating sensitivity indices, when the model output is temporally variable.
... Some of them are empirical (e.g. Tank Model, Sugawara, 1979), while others are lumped (e.g., HEC-HMS, Feldman, 2000), semi-distributed (e.g., SWAT, Arnold et al., 1998;Srinivasan et al., 1998), or fully distributed (e.g., BTOPMC, Takeuchi et al., 1999). However, application for a specific purpose and for a typical study area depends upon several factors. ...
Study region
Karnali-Mohana (KarMo) river basin, Western Nepal.
Study focus
This study has developed a hydrological model using multi-site calibration approach for a large basin, the Karnali-Mohana (KarMo) in Western Nepal, which has a lot of potential for water resources development and contribute to the national prosperity. It further applies the model to characterize hydrology and water resources availability across spatio-temporal scales to enhance understanding on water availability and potential uses. The newly developed hydrological model in Soil and Water Assessment Tool (SWAT) is capable of reproducing the hydrological pattern, the average flows, and the flow duration curve at the outlet of the basin and five major sub-basins.
New hydrological insights for this region
The model simulated results showed that about 34 % of average annual precipitation in the KarMo basin is lost as evapotranspiration, but with a large spatio-temporal heterogeneity. The Hills and Tarai are relatively wetter than the Mountains. The average annual flow volume at the basin outlet is estimated as 46,250 million-cubic-meters (MCM). The hydrological characterization made in this study are further used for climate change impact assessment (Part-B in the same journal), environmental flows assessment and evaluating trade-offs among various water development pathways, which are published elsewhere. This model, therefore, has potential to contribute for strategic planning and sustainable management of water resources to fuel the country’s prosperity.
... Numerous studies have used the HEC-RAS model for flood hazard simulation [17][18][19]23,28,30,34], but it requires upstream and/or downstream boundary conditions of flood hydrograph that must be obtained either from observations or simulated from other hydrological models. Reviewing the previous literature also shows that rainfall-runoff hydrological models such as HEC-HMS [40], WEB-DHM [41], the integrated flood analysis system [42], TOPMODEL [43], and the tank model [44], which have been used widely for runoff prediction, cannot generate flood inundation. Among those hydrological and hydraulic models, the rainfall-runoff-inundation (RRI) hydrological-hydraulic model developed by Sayama et al. [45], which is a grid-based distributed hydrological-hydraulic model, can simulate the rainfall-runoff processes including infiltration, flood routing in the river, and flood inundation in the flood-prone areas simultaneously. ...
Floods are the most frequently occurring water-related disasters in the river basins of many countries, and the impact of floods is becoming greater due to their increasing frequency and scale of flood events, and the concentration of population and economic activities in the river basins. Flood disasters can cause serious damage such as loss of lives and destruction of infrastructures and properties. Therefore, flood disaster risk mitigation plans should be properly prepared and implemented for future floods. However, such mitigation plans require analysis of flood hazards and quantification of risk for mitigating and managing flood risk for the future. In this context, this study focused on assessment of flood risk by quantifying flood damage in the Bago River basin of Myanmar, which is one of the most flood-prone river basins in Myanmar. Assessment of flood hazard and risk in the Bago River basin is very important since this basin plays an important role in economical contribution in the country’s economy through agriculture production. Flood risk in the basin was thus assessed by quantifying flood damage to house building/assets and agriculture using hydrological and damage estimation models. Flood characteristics such as flood depth and duration were computed using hydrological model called Rainfall-Runoff-Inundation model, and flood damage was quantified based on available damage curves for the areas. Flood hazard and risk were assessed quantitatively for past largest flood and for different return period cases. Identifying areas of risk based on flood damage quantification provides essential information for designing future development activities. The results of risk assessment can also be useful to establish preventive measures, adaptation measures and policies required for flood damage reduction.
... The review of previous literature shows that there are many rainfall-runoff models applied to runoff prediction, such as the HEC-HMS (Scharffenberg 2016), the Integrated Flood Analysis System (IFAS Model) (Sugiura et al. 2009), TOPMODEL (Beven et al. 1995), and the tank model (Sugawara 1979). However, these models cannot generate flood inundations. ...
This study focused on flood damage assessment for future floods under the impact of climate change. Four river basins of Southeast Asia were selected for the study. They included the Pampanga River Basin (PRB) in the Philippines, the Solo River Basin (SRB) in Indonesia, the Lower Mekong River Basin (LMRB) in Cambodia and Vietnam, and the Chao Phraya River Basin (CPRB) in Thailand. Flood damage to rice crops was assessed by flood damage functions considering flood depth and duration and the growth stage of rice plants. Flood characteristics such as flood depth, duration, and distribution were computed using the rainfall–runoff–inundation model to assess flood hazards under the present and future climatic conditions produced by MRI-AGCM3.2S. The damage assessment methodology for rice crops employed in this study was verified using data on past flood events. Then, flood damage assessment was conducted for both the present climate (1979–2003) and future climate (2075–2099) conditions, using MRI-AGCM3.2S precipitation datasets. Flood damage was assessed for worst cases chosen from each climate period and for floods of 50- and 100-year return periods with different rainfall patterns chosen from each climate scenario. The results of flood hazard and damage assessment show that the flood inundation area for a 100-year flood may increase in the future by 20% in PRB; by 66% in SRB; by 27% in LMRB; and by 27% in CPRB. The flood damage area of paddy fields for a 100-year flood may also increase in the future by 16% in PRB; by 55% in SRB; by 23% in LMRB; and by 13% in CPRB.
... Tank model atau model tanki adalah model yang mampu mentranformasi data hujan menjadi data debit, dan model ini memerlukan parameterisasi sebelum digunakan. Tank model tersusun oleh beberapa tanki penampung air imaginer yang dapat disusun secara paralel ataupun seri (Sugawara 1979, Takanashi et al. 2011. Model ini menurut Takanashi et al. (2011) telah digunakan dalam sejumlah studi, dan dalam studi ini digunakan empat tanki imaginer. ...
em>Generally, reservoir can overcome problem of water availability in particular region. The reservoir collects excess water during rainy season to be used at the time of water shortage during dry season. In Pidie, the largest water sources are from Krueng Baro Geunik and Krueng Tiro. The reservoir is located at Krueng Rukoh with Krueng Tiro as the source of water supply. The reservoir provides water for irrigating and supplying domestic water in Baro (11.950 ha) and Tiro (6.330 ha) areas. There are 13 districts (216718 inhabitants) use the water from this reservoir. Given the population growing at rate of 0.52% then the water demand in the region increases. The aim of study was to estimate the volume of water entering the reservoir using the tank model. Calibration curve between the tank model output and observation data showed good correlation (R<sup>2</sup> = 0.7). The calibrated model was then used to calculate the discharge at Krueng Baro Geunik. A water balance analysis showed that the highest deficit occurred in September and the highest surplus in November. Based on this analysis, the capacity of Krueng Rukoh reservoir is able to fulfill its function assuming the rate of population growth and the irrigation area are constant.</em
... The soil water index (SWI) is then calculated using the tank model developed by Sugawara [27] where the SWI equals to the total storage volume of tanks laid vertically in series. The function of SWI is used to give an indication on the level of soil moisture in the area of landslide. ...
This study was carried out in mountainous areas of Ranau, Sabah. This area is known to be extremely prone to landslides as it experiences landslide almost every year. The paper is aimed to investigate the correlation between the effective working rainfall and soil water index (SWI) methods of the landslide events in Ranau, Sabah. In this study 10 landslide events that occurred in Ranau area between years 2007 to 2015 were investigated and analyzed using rainfall thresholds based on effective working rainfall and soil water index (SWI) methods. The analysis results showed that both short-intense rainfall (i.e., 1-day) and prolonged antecedent rainfall (i.e., 14, 30-day) played a significant role of the landslide initiations in Ranau, Sabah area. Overall results indicated that these methods can illustrate the rain infiltration response by the level of soil moisture in the area of landslide. However, these rainfall thresholds were statistically based and were not defined hydrological response of rainfall to the soil, as well as other geological conditions associated with slopes.
... Tank model has proven more capable than many other models in modeling the hydrologic responses from a wide range of humid watershed. Many hydrologists are using this model (Sugawara 1967(Sugawara , 1979(Sugawara , 1984(Sugawara , 1995 due to its simple analytical structure and computation while achieving forecasting accuracy comparable with more sophisticated models. Department of Irrigation and Drainage Malaysia (DID) used Tank model to forecast flood levels of the Kelantan River at the Guillemard Bridge during the Northeast Monsoon. ...
... This method required much time and effort to obtain better results owing to the need of calibrating a large number of parameters in the model. Sugawara [2] had developed a computer program to determine the model parameters automatically using trial and error method. However, the calibration of the model is quite difficult where it involved a lot of mathematical formulation and hydrological judgment. ...
... However, this method required much time and effort to calibrate large number of parameters that will provide best fit between observed and simulated runoff. Suguwara [17] had developed a computer program to determine the model parameters automatically using trial and error method. However, this computer model is not friendly to use as it involved a lot of mathematical formulation and hydrological judgment. ...
... Numerous conceptual hydrological models have been developed over the past decades and applied in the hydrological simulation. Some of these models are Stanford Watershed Model (U.S.A) (Crawford and Linsley, 1966), Sacramento (U.S.A) (Burnash et al., 1973), Tank model (Japan) (Sugawara, 1979), HBV model (Sweden) (Bergström, 1976), Xin'anjiang model (China) (Zhao, 1992), IHACRES (Jakeman et al., 1990;Littlewood et al., 1997), SIMHYD (Chiew et al., 2002) The simulation results projected a slight increase in streamflow during the start of the century, especially for the B1 scenario. By the late the century, all scenarios revealed negative trends in summer streamflow and positive trends in winter. ...
... However, it has been observed that nitrate concentration at observation wells was associated with the rainfall intensity in Kumamoto, Japan, therefore a simple model that easily uses accessible data would be preferable and valuable to simulate the nitrate concentrations. Sugawara (1979Sugawara ( , 1995 proposed the Tank Model, a lumped model that uses several tandem tanks to describe each element (such as water storage, runoff, and infiltration) in the rainfall-runoff process directly, without reference to detailed watershed properties. As a result, it is easy to extend the hydrogeographic process simulation by combining these elements with geographic processes (Lee and Singh 2005). ...
Modeling of the nitrate concentration in groundwater can help ensure proper groundwater management and utilization, especially as a drinking water supply. Here, a groundwater nitrate tank model (GNTM) is proposed to simulate nitrate concentrations in groundwater. The variables used to calibrate and validate the model were daily rainfall and weekly nitrate concentration data recorded from June 2012 to February 2016 at two representative observation wells (W1 and W2) in Kumamoto, Japan. The observed nitrate concentrations range from 4.46 to 6.02 mg-N=L, and 8.60 to 24.56 mg-N=L inWells W1 and W2, respectively. The Shuffled Complex Evolution-University of Arizona algorithm was used to determine the best-fit parameter values according to the root-mean-square error (RMSE). Calibration and validation results were evaluated by calculating the Nash-Sutcliffe efficiency coefficient (NSE) and the RMSE. The GNTM accurately reproduced nitrate concentration fluctuations: during the validation period the values of RMSE were 0.135 and 1.432 and NSE were 0.821 and 0.661 in Wells W1 and W2, respectively. These results indicate that this model provides a simple way to accurately simulate nitrate concentrations in groundwater.
... Ensemble of simulations from the hydrologic model, obtained by using rainfall and meteorological data from the 5 GCMs is used to evaluate the hydrologic impact of climate change in the catchment by comparing hydrologic responses in the future time periods with that obtained under 20C3M scenario. When the temporal periods do not overlap, FDCs are commonly used for comparing the flow regimes in the hydrologic analyses (Sugawara, 1979;Yu and Yang, 2000;Westerberg et al., 2011). Since the temporal periods of the 20C3M and the future scenarios do not overlap, FDCs of annual and monsoon flows are used here for the comparison. ...
This work evaluates the impact of climate change on the water balance of a catchment in India. Rainfall and hydro-meteorological variables for current (20C3M scenario, 1981-2000) and two future time periods: mid of the 21st century (2046-2065) and end of the century (2081-2100) are simulated using Modified Markov Model-Kernel Density Estimation (MMM-KDE) and k-nearest neighbor downscaling models. Climate projections from an ensemble of 5 GCMs (MPI-ECHAM5, BCCR-BCM2.0, CSIRO-mk3.5, IPSL-CM4, and MRI-CGCM2) are used in this study. Hydrologic simulations for the current as well as future climate scenarios are carried out using Soil and Water Assessment Tool (SWAT) integrated with ArcGIS (ArcSWAT v.2009). The results show marginal reduction in runoff ratio, annual streamflow and groundwater recharge towards the end of the century. Increased temperature and evapotranspiration projects an increase in the irrigation demand towards the end of the century. Rainfall projections for the future shows marginal increase in the annual average rainfall. Short and moderate wet spells are projected to decrease, whereas short and moderate dry spells are projected to increase in the future. Projected reduction in streamflow and groundwater recharge along with the increase in irrigation demand is likely to aggravate the water stress in the region under the future scenario.
Streamflow prediction (SFP) constitutes a fundamental basis for reliable drought and flood forecasting, optimal reservoir management, and equitable water allocation. Despite significant advancements in the field, accurately predicting extreme events continues to be a persistent challenge due to complex surface and subsurface watershed processes. Therefore, in addition to the fundamental framework, numerous techniques have been used to enhance prediction accuracy and physical consistency. This work provides a well-organized review of more than two decades of efforts to enhance SFP in a physically consistent way using process modeling and flow domain knowledge. This review covers hydrograph analysis, baseflow separation, and process-based modeling (PBM) approaches. This paper provides an in-depth analysis of each technique and a discussion of their applications. Additionally, the existing techniques are categorized, revealing research gaps and promising avenues for future research. Overall, this review paper offers valuable insights into the current state of enhanced SFP within a physically consistent, domain knowledge-informed data-driven modeling framework.
Pertencente ao grupo de poluentes orgânicos persistentes (POPs), as Bifenilas Policloradas (PCBs), conhecidas no Brasil pelo nome comercial Ascarel, estão com a produção e o comércio proibidos a nível global, dado seu potencial de contaminação ambiental. Embora a Ecotoxicologia seja uma área do conhecimento capaz de auxiliar na obtenção de repostas científicas mais precisas sobre os impactos sistêmicos dos PCBs no meio natural, estudos com esse enfoque ainda são escassos. O presente trabalho objetivou rever a literatura de forma sistemática visando identificar os estudos científicos publicados internacionalmente que envolveram avaliações ecotoxicológicas de compartimentos ambientais contaminados por PCBs. Para tanto, foi utilizada a base de dados da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). Os oito artigos selecionados demonstraram que a integralidade das pesquisas foi
esenvolvida na Eurásia, mediante a realização de bioensaios agudos e crônicos. A maioria dos testes ecotoxicológicos contemplaram a análise de solos e sedimentos e foi realizada com apenas uma espécie de organismo-teste, sendo que somente dois autores utilizaram análises multiespécies. Também restou evidenciado que estudos com essa abordagem ainda são escassos e recentes em todo o mundo, embora o interesse pelo tema
tenha aumentado nos últimos anos.
Four data-driven hydrological flood forecasting methods are applied at 20 locations in Pahang River basin, Malaysia (area 30 000 km²). Models are calibrated and validated using historical monsoon flood data. To improve real-time forecast accuracy with 48-h lead time, continuous error correction is applied. An analysis of model performance above the alert water level shows that key forecast points along the main reach are best predicted using a stage regression method, whereas the upstream-most stations are best modelled using rainfall-stage correlation. The unit hydrograph method and Sugawara’s tank model perform well in the intermediate tributaries. Contrary to applying a single model to multiple points of interest or an ensemble model which requires evaluation of multiple models during operation, the multi-model approach allows the practical use of only the best-performing primary or secondary models at different points of interest within a large river basin to produce a reliable overall forecast with equal lead time.
Quantifying reservoir water balance is an essential process for the efficient management of water resources. Water level records are often the only data available for reservoir analysis, which causes an ill‐posed problem in water resource system planning. This study proposes an analytical framework to estimate reservoir inflow and outflow from water level observations using hydrological models and reasoning carefully derived from expert knowledge and soft data. Partial reservoir inflow hydrographs were constructed from water level observations using a continuity equation and knowledge‐based constraints developed for periods of no spillway discharge. A bucket‐type rainfall‐runoff model was then calibrated to the partial inflow hydrographs. Finally, a complete reservoir inflow hydrograph was constructed using the calibrated models, which were then employed to estimate detailed reservoir outflow components under a full water balance relationship between inflow, outflow, water levels, and reservoir operation rules. The proposed solution for the ill‐posed water balance equation outperformed conventional (benchmark) approaches in accuracy and uncertainty in its application to agricultural reservoirs. This study demonstrates how hydrological modeling and reasoning, which are discreetly designed based on expert knowledge, can help to solve the ill‐posed water balance equation by creating supplementary information regarding the problem. The proposed framework is expected to assist in reconstructing reservoir routing processes using water level observations for hydrological analysis and water resource management planning.
Multi-model ensembles enable assessment of model structural uncertainty across multiple disciplines. Bayesian Model Averaging (BMA) is one of the most popular ensemble averaging approaches in hydrology but its predictions are easily impacted by the type of ensemble members selected. Here, we propose a regression-based ensemble approach, namely a Variational Bayesian Long Short-Term Memory network (VB-LSTM) to address this issue. In this approach, a state-of-the-art variational inference (VI) algorithm that is faster and more scalable than Bayesian Markov chain Monte Carlo (MCMC) is employed to approximate the posterior distributions of thousands of parameters in the LSTM networks. To interpret the behavior of deep learning methods, the Permutation Feature Importance (PFI) algorithm is introduced to understand the degree to which VB-LSTM relies on each ensemble member. Twenty conceptual hydrological models are considered to evaluate BMA and VB-LSTM in four catchments from China. Four scenarios with different ensemble members are established to investigate the impacts of ensemble members on model results. Our results show that compared with BMA, VB-LSTM improves deterministic and probabilistic predictions by approximately 10%–30% in terms of Mean Absolute Error (MAE), Sharpness and Continous Ranked Probability Score (CRPS). In addition, the VB-LSTM predictions are more robust and less impacted by the selection of ensemble members. Furthermore, our study encourages the use of Bayesian deep learning in hydrology as an alternative to other approaches tackling model structural uncertainty.
Ensemble forecasting applied to the field of hydrology is currently an established area of research embracing a broad spectrum of operational situations. This work catalogues the various pathways of ensemble streamflow forecasting based on an exhaustive review of more than 700 studies over the last 40 years. We focus on the advanced state of the art in the model‐based (dynamical) ensemble forecasting approaches. Ensemble streamflow prediction systems are categorized into three leading classes: statistics‐based streamflow prediction systems, climatology‐based ensemble streamflow prediction systems and numerical weather prediction‐based hydrological ensemble prediction systems. For each ensemble approach, technical information, as well as details about its strengths and weaknesses, are provided based on a critical review of the studies listed. Through this literature review, the performance and uncertainty associated with the ensemble forecasting systems are underlined from both operational and scientific viewpoints. Finally, the remaining key challenges and prospective future research directions are presented, notably through hybrid dynamical ‐ statistical learning approaches, which obviously present new challenges to be overcome in order to allow the successful employment of ensemble streamflow forecasting systems in the next decades. Targeting students, researchers and practitioners, this review provides a detailed perspective on the major features of an increasingly important area of hydrological forecasting.
External nutrient loadings to Lake Biwa were estimated using a combined tank model and loading-discharge curve approach. The model was applied to collective drainage basins of the lake’s Imazu (northwest), Hikone (northeast), and Otsu (south) areas. The hourly model was conducted using particular discharges from Kita (Ado) river, Takatoki (Ane) river, and Yasu River to obtain loading curves for phosphate (PO4) and silica (SiO2) by assimilating measured concentrations (2002–2003). The tank model was updated by adding an evapotranspiration routine and direct paths of groundwater discharges to the lake floor. The daily model was calibrated through analysis of water budget among the basin, inflow, lake and outflow, and then validated. The model was established and combined into a loading-discharge curve to determine the long-term external nutrient loadings entering the lake (1980–2017). Seasonal variation in nutrient loadings increased during spring and summer and decreased during winter. Annual phosphate-phosphorus (PO4-P) loading ranged from 217 to 296 tons yr–1 in the North Basin and 45 to 76 tons yr–1 in the South Basin, while SiO2 loading fluctuated from 16,027 to 32,655 tons yr–1 and 2,518 to 5,490 tons yr–1 in the North and South Basins, respectively.
The change of groundwater levels after the 2016 Mw 7.0 Kumamoto crustal earthquake was evaluated using a simple conceptual hydrological model in an attempt to show the presence, intensity, and probable mechanism of water level rise observed in Kumamoto where a comprehensive observation-well network exists. A tank model was applied to verify 16 wells in the study field. In the model groundwater levels were first calibrated for the periods in ca. 2 years before the main shock using several hydrological parameters including precipitation, evapotranspiration, water recharge and discharge, and artificial recharge by irrigation. Water levels were then simulated by extrapolating this law of water fluctuating patterns for ca. 2.5 years after the main shock of the earthquake, without considering hydrogeological changes due to the earthquake. A difference in groundwater levels between observation and simulation results yields a degree of coseismic water level rises for each well. The coseismic abnormal water level increase was calculated to be ~11 m in 4–5 month after the main shock and was most significantly on the western slope of the Aso caldera rim mountains. The spatial distribution of the coseismic water increases clarified that the most dominate increasing anomalies prevail at mountain feet surrounding the plains, suggesting the occurrence of coseismic mountain water release resulting in the rise of water levels in downslope aquifers. Identified coseismic water level increases still continue up to 2.5 years after the earthquake, probably because changes in hydrogeological properties in mountain aquifers, i.e., permeability, are still sustained. Our forecasting water recovering trends require ca. 3.5–5 year after the earthquake for complete recovery to the original conditions. We demonstrated that our approaches are capable of describing coseismic water level changes and could potentially be applied to other fields.
The Public Works Research Institute Distributed Hydrological (PWRI-DH) for flood modeling is a combination of the tank model and the kinematic wave method. In the PWRI-DH model, fitting the required parameters plays a fundamental role. The developers of the PWRI-DH model have introduced the capability of obtaining parameters automatically using the baseline parameters; however, the results are not always the expected results because they depend on several factors and must be calibrated manually. The last issue has limited the interest of researchers regarding in the usage of the PWRI-DH model. In this paper, we present a methodology to obtain the parameters required for the PWRI-DH model that enables to focusing only on the key parameters. First, a parametric study is performed by identifying the influence of each parameter in the discharge. From this study, we found that only four parameters play a fundamental role in the flood modeling using the PWRI-DH model. Five flood events in the Upper Aikawa River basin are used to calibrate the model. The results showed that the proposed methodology is suitable and improve the efficient on the flood simulation of Aikawa River and similar rivers, when using the PWRI-DH model.
Abstract. This paper introduces the HydrOlOgical Prediction LAboratory (HOOPLA) developed at Université Laval for ensemble lumped hydrological modelling. HOOPLA includes functionalities to perform calibration, simulation, and forecast for multiple hydrological models and various time steps. It includes a range of hydrometeorological tools such as calibration algorithms, data assimilation techniques, potential evapotranspiration formulas and a snow accounting routine. HOOPLA is a flexible framework coded in MATLAB that allows easy integration of user-defined hydrometeorological tools. This paper also illustrates HOOPLA's functionalities using a set of 31 Canadian catchments.
Mathematical models with small numbers of parameters are useful for hydrological analyses and water resources planning as they are easier to prepare, use, and interpret compared to more complex models. Many simple model structures and simulation strategies have been developed, but there is still substantial room for improvement in the efficiency of daily rainfall-runoff modeling. This study proposes daily rainfall-runoff models that require only two to four parameters yet are capable of predicting peak discharge and baseflow. Parsimonious model structures were obtained using the hyperbolic tangent function and combining it with one subsurface layer and two parameters of a Tank model. The daily rainfall-runoff models proposed based on the Two-Parameter Hyperbolic Model (TPHM) and Tank model were applied to 41 watersheds throughout South Korea. Model accuracy was evaluated by comparing observed and simulated watershed streamflow and compared with that of a nine-parameter Tank model. The original TPHM and its variants yielded slightly better efficiency with a smaller number of parameters than the Tank model when reproducing high flows on a daily basis. The accuracy of low flow and flow duration curve predictions provided by the TPHM-based models was higher in watersheds with relatively large baseflow temporal variability. The results suggested that the TPHM-based structures be alternative parsimonious daily rainfall-runoff simulation models. This study demonstrates that daily high streamflow can be efficiently simulated using a two-parameter hydrological model, and daily baseflow simulation can be improved by adding two additional parameters to the model.
An accurate prediction of the flow of rivers is of great value in several areas, among which stand out hydrology, civil construction and the environment. The search for prior knowledge of the characteristics of the flow of a river has been studied since the Ancient Age of human society. In the recent decades, there were several mathematical models that sought to solve, accurately, the rainfall-runoff process through the use of conceptual models. This research uses an empirical model of Artificial Neural Networks - ANNs to forecast, in the short-term, the flow of rivers. More precisely, the forecasting period studied was from 1 to 7 days and, to make such a prediction, was selected the Tibagi River Basin, which is located in the north region of the Paraná State. Differently from what happens with the rainfall-runoff models, the model proposed in this study consider as input information only past or current data of the flow and rainfall to estimate the future value of the flow. It stands out, also, that the rainfall data are of low spatial resolution, these being of continental proportions and not linked only to the area of the considered basin. The measurements references for the results were: the RMS error, the relative error, the coefficient of Nash-Sutcliffe, and the correlation between forecasts and the actual
observed values. Besides these measurements references, the results obtained by applying the model of ANN were compared with results obtained from the estimates by persistence. The results of this study suggests that the forecasts of the river flow of the River Tibagi for 1 and 2 days were very good and that for 3 and 4 days satisfactory. The forecasts for periods of 5, 6 and 7 days were considered unsatisfactory.
Conservation of forest water catchment is an important aspect of sustainable forest
management. With a total of about 94,851 ha. of forest water catchment, the state of Johor has among the largest inland water bodies and, thus, water resource in Malaysia. Water resource is a valuable environmental asset and, thus, should have value attachment to reflect its importance to the society. Valuation of water resources should become a planning tool in forest management. However, valuation of water resources is rather undeveloped in many parts of the world, especially in the developing economies. Increasing population and urbanization are the impending factors on sustainable management of water resources and, thus, conservation of forest water catchments. As a tool that sends scarcity signals to the society, mapping of abundance/scarcity value of water resource is proposed as an innovative component in forest management. This is a neglected aspect of natural resource management. This study introduces hydro-economics approach to water resource management of forest catchments based on statewide Cobb-Douglas translog production function and residual methods, by taking the state of Johor, Malaysia, as a case study. Data on Gross Domestic Product (GDP), labour (L), capital (K), water (W), energy (E), and raw materials (M) are collected for the state of Johor from various secondary sources. Prior to this analysis, the basic hydrologic characteristics of river basins are analysed. The resulting per capita value of water abundance/scarcity is then mapped across the geographic areas, after taking into account population size and river basin’s flow. The map spatially classifies geographic areas in terms of per capita water abundance/scarcity value into “high”, “medium”, “low”, and “critical” zones. This information is generated to provide evidence to the state authority to further envisage resource management decision-making related to water resource use
Rainfall–runoff modelling has long been a special subject in hydrological
sciences, but identifying behavioural parameters in ungauged catchments is
still challenging. In this study, we comparatively evaluated the performance of
the local calibration of a rainfall–runoff model against regional flow
duration curves (FDCs), which is a seemingly alternative method of classical
parameter regionalisation for ungauged catchments. We used a parsimonious
rainfall–runoff model over 45 South Korean catchments under semi-humid climate. The
calibration against regional FDCs was compared with the simple
proximity-based parameter regionalisation. Results show that transferring
behavioural parameters from gauged to ungauged catchments significantly
outperformed the local calibration against regional FDCs due to the absence
of flow timing information in the regional FDCs. The behavioural parameters
gained from observed hydrographs were likely to contain intangible flow
timing information affecting predictability in ungauged catchments.
Additional constraining with the rising limb density appreciably improved the
FDC calibrations, implying that flow signatures in temporal dimensions would
supplement the FDCs. As an alternative approach in data-rich regions, we
suggest calibrating a rainfall–runoff model against regionalised hydrographs
to preserve flow timing information. We also suggest use of flow signatures
that can supplement hydrographs for calibrating rainfall–runoff models in
gauged and ungauged catchments.
In order to contribute to the establishment of an adequate framework for water resource management in the Mekrou catchment, nine (9) rainfall-runoff hydrological models (1 physically based and eight (8) conceptual models) were tested to reproduce flow at the outlet of Kompongou. These models are GR4J, AWBM, TANK, Sacramento, HBV, SMAR, IHACRES, SimHyd and ModHyPMA (physically based model). Four (4) criteria (Nash Criterion, the coefficient of determination, the Root-Mean-Square Error and the Mean Absolute Error) were used to quantify the performance of simulations. The results show the superiority of ModHyPMA, AWBM and HBV on the other models. Although the GR4J, SimHyd and TANK models have performance below those of ModHyPMA, AWBM and HBV, these models also showed high quality of robustness in the basin. But SMAR, IHACRES and Sacramento models have poorly performed, mostly in validation for the two last models. The multi-model approach developed from several combinations of five models has enabled a considerable improvement in the performance of calibration and validation models.
Keywords: rainfall-runoff modeling; conceptual models, physically based models and multi- model.
This paper outlines the design and experimentation of an Empirical Multistructure Framework (EMF) for lumped conceptual hydrological modelling. This concept is inspired from modular frameworks, empirical model development, and multimodel applications, and encompasses the overproduce and select paradigm. The EMF concept aims to reduce subjectivity in conceptual hydrological modelling practice and includes model selection in the optimisation steps, reducing initial assumptions on the prior perception of the dominant rainfall-runoff transformation processes. EMF generates thousands of new modelling options from, for now, twelve parent models that share their functional components and parameters. Optimisation resorts to ensemble calibration, ranking and selection of individual child time series based on optimal bias and reliability trade-offs, as well as accuracy and sharpness improvement of the ensemble. Results on 37 snow-dominated Canadian catchments and 20 climatically-diversified American catchments reveal the excellent potential of the EMF in generating new individual model alternatives, with high respective performance values, that may be pooled efficiently into ensembles of seven to sixty constitutive members, with low bias and high accuracy, sharpness, and reliability. A group of 1446 new models is highlighted to offer good potential on other catchments or applications, based on their individual and collective interests. An analysis of the preferred functional components reveals the importance of the production and total flow elements. Overall, results from this research confirm the added value of ensemble and flexible approaches for hydrological applications, especially in uncertain contexts, and open up new modelling possibilities.
In an operational context, efficient decision-making is usually the ultimate objective of hydrometeorological forecasts. Because of the uncertainties that lay within the forecasting process, decisions are subject to uncertainty. A better quantification of uncertainties should provide better decisions, which often translate into optimal use and economic value of the forecasts. Six Early Warning Systems (EWS) based on contrasted forecasting systems are constructed to investigate how the quantification of uncertainties affects the quality of a decision. These systems differ by the location of the sources of uncertainty, and the total amount of uncertainty they take into account in the forecasting process. They are assessed with the Relative Economic Value (REV), which is a flexible measure to quantify the potential economic benefits of an EWS. The results show that all systems provide a gain over the case where no EWS is used. The most complex systems, i.e. those that consider more sources of uncertainty in the forecasting process, are those that showed the most reduced expected damages. Systems with better accuracy and reliability are generally the ones with higher REV, even though our analysis did not show a clear-cut relationship between overall forecast quality and REV in the context investigated.
ABSTRAK Hubungan curah hujan-limpasan merupakan fenomena hidrologi yang kompleks, sehubungan dengan adanya proses yang tidak linier, bervariasi terhadap waktu dan merupakan distribusi yang spasial. Hubungan curah hujan limpasan ini sangat penting artinya dalam bidang manajemen sumber daya air. Dengan mengetahui data hujan di stasiun – stasiun penakar hujan yang berpengaruh pada DAS yang ditinjau, maka dapat dicari hubungan antar hujan yang jatuh dan limpasan aliran yang terjadi. Penelitian ini disusun untuk pengaplikasian model dalam mentransformasikan curah hujan limpasan menjadi debit aliran sungai. Model Hidrograf Regresi Linier adalah metode yang digunakan untuk menentukan fungsi linier yang paling sesuai dengan kumpulan titik data (curah hujan dan debit) yang diketahui dengan menggunakan persamaan yang sudah ditentukan untuk memberikan hasil perbandingan simulasi dengan data aktual. Model Tangki adalah salah satu model hidrologi yang gunanya untuk menganalisis karakteristik aliran sungai dimana dalam hal ini adalah limpasan air sungai yang terjadi. Model ini menerima masukan data harian hujan, evapotranspirasi dan debit sungai dalam satuan mm/hari sebagai parameter tank model. Data yang diperoleh dari 3 stasiun air hujan yaitu di Tampaksiring, Tegalalang dan Ubud sehingga didapat hasil rata-rata dengan metode Polygon Thiessen yang dikombinasi dengan data debit dan Evapotranspirasi. Penyusunan Hidrograf Regresi Linier dengan menggunakan sebaran titik-titik data dari hasil pengukuran pada bidang x-y didapat rumus persamaan dengan y=8.2678x+0.5878, dimana (y) debit simulasi dan (x) intensitas curah hujan dan penyusunan tangki pada DAS Tukad Petanu WS 03-01.A3.223 di daerah hilir merupakan daerah persawahan. Secara umum, daerah persawahan memiliki tanah keras dan memiliki 2 Model Tangki dalam Parameternya. Hasil pengamatan untuk Hidrograf Regresi Linier dengan nilai koefesien korelasi (r) dari tahun 1994 sebesar 0.92, tahun 1995 s/d 1998 nilai (r) tidak diketahui ini disebabkan karena adanya data observasi yang tidak akurat, dengan menunjukkan data yang bisa dipakai untuk mendekati dengan data observasi adalah tahun 1994. Dan untuk Model Tangki nilai koefesien korelasi (r) tahun 1994 sebesar 0.97, tahun 1997 sebesar 0.62, dan tahun 1995, 1996, dan 1998 nilai (r) tidak diketahui ini disebabkan juga data observasi yang tidak akurat, dan hasilnya menunjukkan data yang bisa dipakai untuk mendekati dengan data observasi adalah tahun 1994 dan 1997. Dengan kata lain untuk rata-rata nilai (r) Hidrograf Regresi Linier sebesar 0.18 dari tahun (1994 s/d 1998) dan Model Tangki sebesar 0.32 dari tahun (1994 s/d 1998). ini menunjukkan bahwa model tangki lebih bisa diterima dalam menghasilkan data debit permodelan. Karena model Tangki memiliki data input masukan yang lebih banyak dari pada model Hidrograf Regresi Linier. Kata kunci: Curah Hujan Limpasan, Hidrograf Regresi Linier, Model Tangki.
Abstract:To synthesize recession coefficients in the Xinanjiang model, this paper presents a relationship of the coefficients versus the time interval and storage coefficient for linear reservoirs based on the linear reservoir theory, and discusses potential uncertainties due to longer time intervals and input variability within the intervals. For the recession coefficient of channel water, which is very difficult to calibrate in daily rainfall-runoff analysis, a new approach is adopted to replace its direct calibration by synthesizing the storage coefficients of linear reservoirs. Results show that the new approach is very successful in the estimation of the hourly recession coefficients of 13 small basins of areas in the range of 100 to 3000 square kilometers and has achieved their values with an average error of 0.005 and a standard deviation of 0.022. This approach allows a new way to synthesize the recession coefficients in the Xinanjiang model based on vast previous studies about river concentration.
Key words:Xinanjiang model; routing parameters; recession coefficients; linear reservoir; storage
coefficient; uncertainty; parameter synthesization
摘 要：为了探讨新安江模型汇流参数中河网蓄水消退系数规律，本文从线性水库理论出发得到消退系数和蓄泄系数的关系，明确消退系数是反映流域特征的蓄泄系数和计算时段长度的函数。并在此基础上讨论了时段长度过长、时段内入流分布可能带来的不确定性。对于日降雨—径流分析很难求得的河网蓄水消退系数，本文提出了通过蓄泄系数参数规律来间接推求河网蓄水消退系数的新方法。以极简单的Simas公式为例探讨其地理因子的适用性，发现即使是这样简单的公式也可以得到较高的精度。面积在100 ~ 3000 km2的13个流域的时消退系数的平均误差为0.005，标准偏差为0.022。有了这样的思路，我们可以借鉴地表水汇流特性研究工作的庞大知识积累，研究各种地理因子及水力因子的更有综合代表性的组合。
关键词：新安江模型；汇流参数；消退系数；线性水库；蓄泄系数；不确定性；参数规律
中图分类号：P333.2 文献标志码：A DOI: 10.11660/slfdxb.20160901
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