scholarly journals Simulating the regional water balance through hydrological model based on TRMM satellite rainfall data

2015 ◽  
Vol 12 (2) ◽  
pp. 2497-2525 ◽  
Author(s):  
D. Li ◽  
X. Ding ◽  
J. Wu
Keyword(s):  
Water Balance ◽  
Water Resource Management ◽  
Hydrological Model ◽  
Model Performance ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Hydrological Models ◽  
Runoff Simulation ◽  
Hydrological Simulation

Abstract. Spatial rainfall is a key input to Distributed Hydrological Models, which is the most important limitation for the accuracy of hydrological models. Model performance and uncertainty could increase when rain gauge is sparse. Satellite-based precipitation products would be an alternative to ground-based rainfall estimates in present and the foreseeable future, however, it is necessary to evaluate the products before further implication. The objective of this paper is to provide assessments of: (a) the Tropical Rainfall Measuring Mission (TRMM) rainfall product using gauge data, (b) the TRMM rainfall as forcing data for hydrological simulation, and (c) the role of satellite data in calculating water balance and water management. TRMM rainfall data show reasonable performances at monthly and annual scales, fitting well with surface observation-based histogram of precipitation. Satisfactory performances in monthly runoff simulation (NS = 0.50 ~ 0.70, R2 = 0.73 ~ 0.85) observed in our study indicate that the TRMM rainfall data have potential applications in driving hydrological model, water balance analysis, and basin water resource management in developing countries or remote locations, where precipitation gauges are scare.

scholarly journals Rainfall-Runoff Modelling of the West Rapti Basin, Nepal

2020 ◽  
Vol 2 (1) ◽  
pp. 99-107
Author(s):  
Bibek Thapa ◽  
Anusha Danegulu ◽  
Naresh Suwal ◽  
Surabhi Upadhyay ◽  
Bikesh Manandhar ◽  
...  
Keyword(s):  
River Basin ◽  
Water Resource Management ◽  
Hydrological Model ◽  
Model Performance ◽  
Rain Gauge ◽  
Army Corps ◽  
Distributed Hydrological Model ◽  
Rainfall Runoff ◽  
The West ◽  
Us Army

A hydrological model helps in understanding, predicting, and managing water resources. The HEC-HMS (Centre for Hydrological Engineering - Hydrological Modelling Systems, US Army Corps of Engineers) is one of the hydrological models used to simulate rainfall-runoff and routing processes in diverse geographical areas. In this study, a semi-distributed hydrological model was developed using HEC-HMS for the West-Rapti river basin. The model was calibrated and validated at each outlet of sub-basins and used to simulate the outflow of each sub-basins of the West Rapti river basin. A total of eight rain gauge stations, five meteorological stations, and three hydrological stations, within the basin, were used. The simulated results closely matched the observed flows at the three gauging stations. The Nash-Sutcliffe Efficiency indicated the good model performance of the simulated streamflow with the observed flow at two stations and satisfactory model fit at one station. The performance based on percentage bias and root mean square error was good. This model provides a reference to study water balance, water resource management, and flooding control of the West Rapti basin and can be replicated in other basins.

scholarly journals Predicting Rainfall and Runoff Through Satellite Soil Moisture Data and SWAT Modelling for a Poorly Gauged Basin in Iran

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 594 ◽  
Author(s):  
Majid Fereidoon ◽  
Manfred Koch ◽  
Luca Brocca
Keyword(s):  
Soil Moisture ◽  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Rainfall Data ◽  
Coefficient Of Determination ◽  
Hydrological Models ◽  
Streamflow Prediction ◽  
Soil Moisture Data ◽  
Monthly Runoff

Hydrological models are widely used for many purposes in water sector projects, including streamflow prediction and flood risk assessment. Among the input data used in such hydrological models, the spatial-temporal variability of rainfall datasets has a significant role on the final discharge estimation. Therefore, accurate measurements of rainfall are vital. On the other hand, ground-based measurement networks, mainly in developing countries, are either nonexistent or too sparse to capture rainfall accurately. In addition to in-situ rainfall datasets, satellite-derived rainfall products are currently available globally with high spatial and temporal resolution. An innovative approach called SM2RAIN that estimates rainfall from soil moisture data has been applied successfully to various regions. In this study, first, soil moisture content derived from the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) is used as input into the SM2RAIN algorithm to estimate daily rainfall (SM2R-AMSRE) at different sites in the Karkheh river basin (KRB), southwest Iran. Second, the SWAT (Soil and Water Assessment Tool) hydrological model was applied to simulate runoff using both ground-based observed rainfall and SM2R-AMSRE rainfall as input. The results reveal that the SM2R-AMSRE rainfall data are, in most cases, in good agreement with ground-based rainfall, with correlations R ranging between 0.58 and 0.88, though there is some underestimation of the observed rainfall due to soil moisture saturation not accounted for in the SM2RAIN equation. The subsequent SWAT-simulated monthly runoff from SM2R-AMSRE rainfall data (SWAT-SM2R-AMSRE) reproduces the observations at the six gauging stations (with coefficient of determination, R² > 0.71 and NSE > 0.56), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation compared to the SWAT model with ground-based rainfall input. Additionally, rainfall estimates of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model after bias correction. The monthly runoff predictions obtained with 3B42- rainfall have 0.42 < R2 < 0.72 and−0.06 < NSE < 0.74 which are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SWAT-SM2R-AMSRE. Therefore, despite the aforementioned limitations, using SM2R-AMSRE rainfall data in a hydrological model like SWAT appears to be a viable approach in basins with limited ground-based rainfall data.

scholarly journals Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

2016 ◽  
Vol 20 (2) ◽  
pp. 903-920 ◽  
Author(s):  
W. Qi ◽  
C. Zhang ◽  
G. Fu ◽  
C. Sweetapple ◽  
H. Zhou
Keyword(s):  
Hydrological Model ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Precipitation ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Precipitation Product ◽  
Physically Based ◽  
Precipitation Estimation ◽  
Discharge Simulation ◽  
Fine Resolution

Abstract. The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation – Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash–Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based products, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and very beneficial for precipitation product applications.

scholarly journals Satellite-Based Precipitation Estimation for Hydropower Development

2013 ◽  
Vol 12 ◽  
pp. 52-58 ◽  
Author(s):  
Bijaya Tamrakar ◽  
Knut Alfredsen
Keyword(s):  
Water Balance ◽  
Rain Gauge ◽  
Water Balance Model ◽  
Balance Model ◽  
Precipitation Data ◽  
Runoff Simulation ◽  
Ungauged Catchments ◽  
Statistical Parameters ◽  
Additional Advantage ◽  
Planning Stage

Runoff is one of the major factors that govern the capacity of a hydropower project. Precipitation data are needed for estimation of runoff through runoff simulation using a hydrological model. Dense setup of rain gauge network in a mountainous topography is difficult and expensive. An alternative for this problem is the use of Satellite precipitation data with high spatial and temporal resolution. They have an additional advantage that they represent areal precipitation. But, these data should be duly evaluated before using them. In this study, Tropical Rainfall Measuring Mission (TRMM 3B42) precipitation data are evaluated using ground based precipitation stations over Nepal and fed in a rainfall-runoff model to estimate monthly discharge through four of the major basins of Nepal. A simple water balance model has been used, initially developed by Thornthwaite. Statistical parameters showed significant under-estimation of precipitation over major areas of Nepal. The results from the water balance model presented quiet a good estimation of discharge through basins with an average Nash Sutcliffe Efficiency (R²) value of 0.8. This implies that TRMM data can be used for runoff simulations over Nepal. The TRMM satellite data can be used during the planning stage of hydropower projects as well as on ungauged catchments. Hydro Nepal: Journal of Water, Energy and Environment Vol. 12, 2013, January Page: 52-58DOI: http://dx.doi.org/10.3126/hn.v12i0.9033 Uploaded Date : 10/29/2013

scholarly journals Scale effect challenges in urban hydrology highlighted with a distributed hydrological model

2018 ◽  
Vol 22 (1) ◽  
pp. 331-350 ◽  
Author(s):  
Abdellah Ichiba ◽  
Auguste Gires ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Schertzer ◽  
Philippe Bompard ◽  
...  
Keyword(s):  
Scale Effect ◽  
Hydrological Model ◽  
Scale Effects ◽  
Model Performance ◽  
Scale Dependence ◽  
Urban Hydrology ◽  
Distributed Data ◽  
Hydrological Models ◽  
Multi Scale ◽  
Scale Modelling

Abstract. Hydrological models are extensively used in urban water management, development and evaluation of future scenarios and research activities. There is a growing interest in the development of fully distributed and grid-based models. However, some complex questions related to scale effects are not yet fully understood and still remain open issues in urban hydrology. In this paper we propose a two-step investigation framework to illustrate the extent of scale effects in urban hydrology. First, fractal tools are used to highlight the scale dependence observed within distributed data input into urban hydrological models. Then an intensive multi-scale modelling work is carried out to understand scale effects on hydrological model performance. Investigations are conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model is implemented at 17 spatial resolutions ranging from 100 to 5 m. Results clearly exhibit scale effect challenges in urban hydrology modelling. The applicability of fractal concepts highlights the scale dependence observed within distributed data. Patterns of geophysical data change when the size of the observation pixel changes. The multi-scale modelling investigation confirms scale effects on hydrological model performance. Results are analysed over three ranges of scales identified in the fractal analysis and confirmed through modelling. This work also discusses some remaining issues in urban hydrology modelling related to the availability of high-quality data at high resolutions, and model numerical instabilities as well as the computation time requirements. The main findings of this paper enable a replacement of traditional methods of “model calibration” by innovative methods of “model resolution alteration” based on the spatial data variability and scaling of flows in urban hydrology.

Multi-objective calibration of a distributed eco-hydrological model using several remotely sensed information

2020 ◽  
Author(s):  
Félix Francés ◽  
Carlos Echeverría ◽  
Maria Gonzalez-Sanchis ◽  
Fernando Rivas
Keyword(s):  
Remote Sensing ◽  
Model Calibration ◽  
Hydrological Model ◽  
Model Performance ◽  
Temporal Information ◽  
Temporal Data ◽  
Hydrological Models ◽  
Validation Period ◽  
Spatio Temporal ◽  
Calibration Approach

&lt;p&gt;Calibration of eco-hydrological models is difficult to carry on, even more if observed data sets are scarce. It is known that calibration using traditional trial-and-error approach depends strongly of the knowledge and the subjectivity of the hydrologist, and automatic calibration has a strong dependency of the objective-function and the initial values established to initialize the process.&lt;/p&gt;&lt;p&gt;The traditional calibration approach mainly focuses on the temporal variation of the discharge at the catchment outlet point, representing an integrated catchment response and provides thus only limited insight on the lumped behaviour of the catchment. It has been long demonstrated the limited capabilities of such an approach when models are validated at interior points of a river basin. The development of distributed eco-hydrological models and the burst of spatio-temporal data provided by remote sensing appear as key alternative to overcome those limitations. Indeed, remote sensing imagery provides not only temporal information but also valuable information on spatial patterns, which can facilitate a spatial-pattern-oriented model calibration.&lt;/p&gt;&lt;p&gt;However, there is still a lack of how to effectively handle spatio-temporal data when included in model calibration and how to evaluate the accuracy of the simulated spatial patterns. Moreover, it is still unclear whether including spatio-temporal data improves model performance in face to an unavoidable more complex and time-demanding calibration procedure. To elucidate in this sense, we performed three different multiobjective calibration configurations: (1) including only temporal information of discharges at the catchment outlet (2) including both temporal and spatio-temporal information and (3) only including spatio-temporal information. In the three approaches, we calibrated the same distributed eco-hydrological model (TETIS) in the same study area: Carraixet Basin, and used the same multi-objective algorithm: MOSCEM-UA. The spatio-temporal information obtained from satellite has been the surface soil moisture (from SMOS-BEC) and the leaf area index (from MODIS).&lt;/p&gt;&lt;p&gt;Even though the performance of the first calibration approach (only temporal information included) was slightly better than the others, all calibration approaches provided satisfactory and similar results within the calibration period. To put these results into test, we also validated the model performance by using historical data that was not used to calibrate the model (validation period). Within the validation period, the second calibration approach obtained better performance than the others, pointing out the higher reliability of the obtained parameter values when including spatio-temporal data (in this case, in combination with temporal data) in the model calibration. It is also reliable to mention that the approaches considering only spatio-temporal information provided interesting results in terms of discharges, considering that this variable was not used at all for calibration purposes.&lt;/p&gt;

scholarly journals Calibration of hydrological model parameters for ungauged catchments

2007 ◽  
Vol 11 (2) ◽  
pp. 703-710 ◽  
Author(s):  
A. Bárdossy
Keyword(s):  
Hydrological Model ◽  
Model Performance ◽  
Model Parameters ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Ungauged Catchments ◽  
Rainfall Runoff Model ◽  
Climate Statistics ◽  
Runoff Model ◽  
German Part

Abstract. The parameters of hydrological models for catchments with few or no discharge records can be estimated using regional information. One can assume that catchments with similar characteristics show a similar hydrological behaviour and thus can be modeled using similar model parameters. Therefore a regionalisation of the hydrological model parameters on the basis of catchment characteristics is plausible. However, due to the non-uniqueness of the rainfall-runoff model parameters (equifinality), a workflow of regional parameter estimation by model calibration and a subsequent fit of a regional function is not appropriate. In this paper a different approach for the transfer of entire parameter sets from one catchment to another is discussed. Parameter sets are considered as tranferable if the corresponding model performance (defined as the Nash-Sutclife efficiency) on the donor catchment is good and the regional statistics: means and variances of annual discharges estimated from catchment properties and annual climate statistics for the recipient catchment are well reproduced by the model. The methodology is applied to a set of 16 catchments in the German part of the Rhine catchments. Results show that the parameters transfered according to the above criteria perform well on the target catchments.

scholarly journals Effect of length of the observed dataset on the calibration of a distributed hydrological model

2015 ◽  
Vol 368 ◽  
pp. 305-311 ◽  
Author(s):  
X. Cui ◽  
W. Sun ◽  
J. Teng ◽  
H. Song ◽  
X. Yao
Keyword(s):  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Discharge Data ◽  
One Year ◽  
Parameter Values ◽  
Discharge Measurements

Abstract. Calibration of hydrological models in ungauged basins is now a hot research topic in the field of hydrology. In addition to the traditional method of parameter regionalization, using discontinuous flow observations to calibrate hydrological models has gradually become popular in recent years. In this study, the possibility of using a limited number of river discharge data to calibrate a distributed hydrological model, the Soil and Water Assessment Tool (SWAT), was explored. The influence of the quantity of discharge measurements on model calibration in the upper Heihe Basin was analysed. Calibration using only one year of daily discharge measurements was compared with calibration using three years of discharge data. The results showed that the parameter values derived from calibration using one year’s data could achieve similar model performance with calibration using three years’ data, indicating that there is a possibility of using limited numbers of discharge data to calibrate the SWAT model effectively in poorly gauged basins.

scholarly journals Dynamics of hydrological model parameters: calibration and reliability

2019 ◽  
Author(s):  
Tian Lan ◽  
Kairong Lin ◽  
Xuezhi Tan ◽  
Chong-Yu Xu ◽  
Xiaohong Chen
Keyword(s):  
Hydrological Model ◽  
Model Performance ◽  
Dynamic Parameter ◽  
Model Parameters ◽  
Hydrological Models ◽  
State Variables ◽  
Individual Parameter ◽  
Calibration Scheme ◽  
Response Modes ◽  
Abrupt Shifts

Abstract. It has been demonstrated that the dynamics of hydrological model parameters based on dynamic catchment behavior significantly improves the accuracy and robustness of conventional models. However, the calibration for the dynamization of parameter set involves critical components of hydrological models, including parameters, objective functions, state variables, and fluxes, which usually are ignored. Hence, it is essential to design a reliable calibration scheme regarding these components. In this study, we compared and evaluate five calibration schemes with respect to multi-metric evaluation, dynamized parameter values, fluxes, and state variables. Furthermore, a simple and effective tool was designed to assess the reliability of the dynamized parameter set. The tool evaluates the convergence processes for global optimization algorithms using violin plots (ECP-VP), effectively describes the convergence behaviour in individual parameter spaces. The different types of violin plots can well match to all possible properties of fitness landscapes. The results showed that the reasons for poor model performance included time-invariant parameters oversimplifying the dynamic response modes of the model, the high-dimensionality disaster of parameters, the abrupt shifts of the parameter set, and the complicated correlations among parameters. The proposed calibration scheme overcome these issues, characterized the dynamic behaviour of catchments, and improved the model performance. Additionally, the designed ECP-VP tool effectively assessed the reliability of the dynamic parameter set, providing an indication on recognizing the dominant response modes of hydrological models in different sub-periods or catchments with the distinguishing catchment characteristics.

scholarly journals Impact of Rain Gauges Distribution on the Runoff Simulation of a Small Mountain Catchment in Southern Ecuador

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1169 ◽  
Author(s):  
Adrián Sucozhañay ◽  
Rolando Célleri
Keyword(s):  
Hydrological Modeling ◽  
Rainfall Variability ◽  
Model Performance ◽  
Rainfall Data ◽  
Model Structure ◽  
Mountain Regions ◽  
Rainfall Estimation ◽  
Runoff Simulation ◽  
Rain Gauges ◽  
The Impact

In places with high spatiotemporal rainfall variability, such as mountain regions, input data could be a large source of uncertainty in hydrological modeling. Here we evaluate the impact of rainfall estimation on runoff modeling in a small páramo catchment located in the Zhurucay Ecohydrological Observatory (7.53 km2) in the Ecuadorian Andes, using a network of 12 rain gauges. First, the HBV-light semidistributed model was analyzed in order to select the best model structure to represent the observed runoff and its subflow components. Then, we developed six rainfall monitoring scenarios to evaluate the impact of spatial rainfall estimation in model performance and parameters. Finally, we explored how a model calibrated with far-from-perfect rainfall estimation would perform using new improved rainfall data. Results show that while all model structures were able to represent the overall runoff, the standard model structure outperformed the others for simulating subflow components. Model performance (NSeff) was improved by increasing the quality of spatial rainfall estimation from 0.31 to 0.80 and from 0.14 to 0.73 for calibration and validation period, respectively. Finally, improved rainfall data enhanced the runoff simulation from a model calibrated with scarce rainfall data (NSeff 0.14) from 0.49 to 0.60. These results confirm that in mountain regions model uncertainty is highly related to spatial rainfall and, therefore, to the number and location of rain gauges.

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