scholarly journals Validation of the modified Témez rational model in the watersheds of Norte de Santander, Colombia

2021 ◽  
Vol 2073 (1) ◽  
pp. 012017
Author(s):  
N J Cely-Calixto ◽  
G A Carrillo Soto ◽  
D Becerra-Moreno
Keyword(s):  
Multivariate Regression ◽  
Flow Measurement ◽  
Hydrological Modeling ◽  
Hydrological Cycle ◽  
Drainage Network ◽  
Hydrological Models ◽  
Rational Model ◽  
Flow Rates ◽  
Statistical Verification ◽  
Made In

Abstract Physics includes the study and investigation of the phases that make up the hydrological cycle, including the estimation of flow rates in river basins, most of which are not instrumented, i.e., they lack historical records of circulating flows. For this situation, the application of hydrological models can allow flow estimates to be made. In the Department of Norte de Santander, Colombia, some watersheds do not have instrumentation for flow measurement or hydrological modeling methodologies appropriate to the site. Therefore, methods such as the modified rational model of Teméz are used, even without knowing the relevance of its applicability to the site conditions. Consequently, for the present research, the Teméz model was validated in watersheds of the Norte de Santander Department to estimate the values of extreme flows with a return period of 100 years. In this sense, 11 watersheds were selected, which contained historical rainfall data greater than 20 years and a drainage network of fewer than 1000 Km2. It was found that the Teméz model overestimates the real flows of the 11 hydrological basins, where the climatological parameters used in the application of the Fhrüling factor and its statistical verification using multivariate regression did not achieve an acceptable correlation.

scholarly journals Production of a Curve Number map using GIS Techniques in the watershed of the high Sebou (Morocco)

2020 ◽  
Vol 150 ◽  
pp. 03003
Author(s):  
Btissam Jabri ◽  
Mohammed Abdelbaset Hessane
Keyword(s):  
Geographical Information Systems ◽  
Hydrological Modeling ◽  
Curve Number ◽  
Geographical Information ◽  
Automatic Extraction ◽  
Drainage Network ◽  
Hydrological Models ◽  
Digital Terrain ◽  
Terrain Models ◽  
In The Beginning

This work focusing on the collection and preparation of necessary data for hydrological modeling of High Sebou watershedupstream of the dam Allal El Fassi. It describes a methodology for combining space technologies, including geographical information systems (GIS), remote sensing and digital terrain models (DTM), with hydrological models with a view to prepare for a spatial hydrologic modeling whose used for flood forecasting. The methodology for conducting this study comes in several parts: The collection and processing of geographic data constituted the first part of this project. This approach is, in the beginning, to automatic extraction of sub-basins and drainage network, then the formatting of data for the mapping of the basin and finally, the preparation of the land use and soil for the development of a map of Curve Number (CN).

scholarly journals The Capacity of the Hydrological Modeling for Water Resource Assessment under the Changing Environment in Semi-Arid River Basins in China

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1328 ◽  
Author(s):  
Xiaoxiang Guan ◽  
Jianyun Zhang ◽  
Amgad Elmahdi ◽  
Xuemei Li ◽  
Jing Liu ◽  
...  
Keyword(s):  
Water Resource ◽  
Human Activities ◽  
Hydrological Modeling ◽  
Environmental Changes ◽  
Hydrological Cycle ◽  
Resource Assessment ◽  
Hydrological Models ◽  
Runoff Series ◽  
Water Resource Assessment ◽  
Semi Arid

Conducting water resource assessment and forecasting at a basin scale requires effective and accurate simulation of the hydrological process. However, intensive, complex human activities and environmental changes are constraining and challenging the hydrological modeling development and application by complicating the hydrological cycle within its local contexts. Six sub-catchments of the Yellow River basin, the second-largest river in China, situated in a semi-arid climate zone, have been selected for this study, considering hydrological processes under a natural period (before 1970) and under intensive human disturbance (2000–2013). The study aims to assess the capacity and performance of the hydrological models in simulating the discharge under a changing environment. Four well-documented and applied hydrological models, i.e., the Xin’anjiang (XAJ) model, GR4J model, SIMHYD model, and RCCC-WBM (Water Balance Model developed by Research Center for Climate Change) model, were selected for this assessment. The results show that (1) the annual areal temperature of all sub-catchments presented a significant rising trend, and annual precipitation exhibited insignificant decline trend; (2) as a result of climate change and intensive human activities, the annual runoff series showed a declining trend with abrupt changes mostly occurring in the 1980s with the exception of the Tangnaihai station; (3) the four hydrological models generally performed well for runoff simulation for all sub-catchments under the natural period. In terms of Nash–Sutcliffe efficiency coefficient, the XAJ model worked better in comparison to other hydrological models due to its detailed representations and complicated mechanism in runoff generation and flow-routing scheme; (4) environmental changes have impacted the performance of the four hydrological models under all sub-catchments, in particularly the Pianguan River catchment, which is could be attributed to the various human activities that in turn represent more complexity for the regional hydrological cycle to some extent, and reduce the ability to predict the runoff series; (5) the RCCC-WBM model, well known for its simple structure and principles, is considered to be acceptable for runoff simulation for both natural and human disturbance periods, and is recommended for water resource assessment under changing environments for semi-arid regions.

scholarly journals Rainfall-Runoff Modelling of a River Basin Using HEC HMS: A Review Study

2021 ◽  
Vol 9 (9) ◽  
pp. 506-508
Author(s):  
Padala Raja Shekar
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Soil Type ◽  
Hydrological Modeling ◽  
Hydrological Cycle ◽  
Meteorological Data ◽  
Physical Parameters ◽  
Army Corps ◽  
Hydrological Models ◽  
Rainfall Runoff

Abstract: A hydrological model helps in understanding of the hydrological processes and useful to measure water resources for effective water resources management. Hydrological cycle describes evaporation, condensation, precipitation and collection of earth water and on again. Hydrological models have been used in different watersheds across the world. The runoff estimation process is the most complex in nature that depends on the meteorological data and also on the various watershed physical parameters. To generate runoff data for a particular watershed it is needed to find out various parameters related to precipitation models. The HEC HMS (a Centre for Hydrological Engineering and Hydrological Modelling Systems introduced by the US Army Corps of Engineers) is a popularly used watershed model to simulate rainfall runoff process. The input variables used by hydrological models are rainfall data, runoff data, wind speed, relative humidity, soil type, catchment properties, hydrogeology and other properties. The Hydrological Modeling can also be an event based or may be continuous. This model is used to predict future impacts of the climate changes on the runoff of River basin and it is used to simulate runoff in ungauged watershed. This literature review represents that application of rainfall runoff modelling using HEC HMS is helpful in prediction of flood, water management and socio-economic development as well as food security. Keywords: HEC-HMS, hydrological modeling, rainfall-runoff simulation, soil type.

scholarly journals Hunting for Information in Streamflow Signatures to Improve Modelled Drainage

Water ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 110
Author(s):  
Raphael Schneider ◽  
Simon Stisen ◽  
Anker Lajer Højberg
Keyword(s):  
Large Scale ◽  
Agricultural Land ◽  
Hydrological Cycle ◽  
Drainage System ◽  
Water Model ◽  
Generation Process ◽  
Hydrological Models ◽  
Drainage Patterns ◽  
Drain Flow ◽  
Set Up

About half of the Danish agricultural land is drained artificially. Those drains, mostly in the form of tile drains, have a significant effect on the hydrological cycle. Consequently, the drainage system must also be represented in hydrological models that are used to simulate, for example, the transport and retention of chemicals. However, representation of drainage in large-scale hydrological models is challenging due to scale issues, lacking data on the distribution of drain infrastructure, and lacking drain flow observations. This calls for more indirect methods to inform such models. Here, we investigate the hypothesis that drain flow leaves a signal in streamflow signatures, as it represents a distinct streamflow generation process. Streamflow signatures are indices characterizing hydrological behaviour based on the hydrograph. Using machine learning regressors, we show that there is a correlation between signatures of simulated streamflow and simulated drain fraction. Based on these insights, signatures relevant to drain flow are incorporated in hydrological model calibration. A distributed coupled groundwater–surface water model of the Norsminde catchment, Denmark (145 km2) is set up. Calibration scenarios are defined with different objective functions; either using conventional stream flow metrics only, or a combination with hydrological signatures. We then evaluate the results from the different scenarios in terms of how well the models reproduce observed drain flow and spatial drainage patterns. Overall, the simulation of drain in the models is satisfactory. However, it remains challenging to find a direct link between signatures and an improvement in representation of drainage. This is likely attributable to model structural issues and lacking flexibility in model parameterization.

scholarly journals Multi-source data assimilation for physically-based hydrological modeling of an experimental hillslope

2018 ◽  
Author(s):  
Anna Botto ◽  
Enrica Belluco ◽  
Matteo Camporese
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Hydrological Modeling ◽  
Nonlinear Models ◽  
Pressure Head ◽  
Richards Equation ◽  
Hydrological Models ◽  
Filter Performance ◽  
Trade Offs ◽  
Source Data

Abstract. Data assimilation has been recently the focus of much attention for integrated surface-subsurface hydrological models, whereby joint assimilation of water table, soil moisture, and river discharge measurements with the ensemble Kalman filter (EnKF) have been extensively applied. Although the EnKF has been specifically developed to deal with nonlinear models, integrated hydrological models based on the Richards equation still represent a challenge, due to strong nonlinearities that may significantly affect the filter performance. Thus, more studies are needed to investigate the capabilities of the EnKF to correct the system state and identify parameters in cases where the unsaturated zone dynamics are dominant, as well as to quantify possible tradeoffs associated with assimilation of multi-source data. Here, the model CATHY (CATchment HYdrology) is applied to reproduce the hydrological dynamics observed in an experimental two-layered hillslope, equipped with tensiometers, water content reflectometer probes, and tipping bucket flow gages to monitor the hillslope response to a series of artificial rainfall events. Pressure head, soil moisture, and subsurface outflow are assimilated with the EnKF in a number of scenarios and the challenges and issues arising from the assimilation of multi-source data in this real-world test case are discussed. Our results demonstrate that the EnKF is able to effectively correct states and parameters even in a real application characterized by strong nonlinearities. However, multi-source data assimilation may lead to significant trade-offs: the assimilation of additional variables can lead to degradation of model predictions for other variables that were otherwise well reproduced. Furthermore, we show that integrated observations such as outflow discharge cannot compensate for the lack of well-distributed data in heterogeneous hillslopes.

scholarly journals Data assimilation of GRACE terrestrial water storage estimates into a regional hydrological model of the Rhine River basin

2015 ◽  
Vol 19 (4) ◽  
pp. 2079-2100 ◽  
Author(s):  
N. Tangdamrongsub ◽  
S. C. Steele-Dunne ◽  
B. C. Gunter ◽  
P. G. Ditmar ◽  
A. H. Weerts
Keyword(s):  
Correlation Coefficient ◽  
River Basin ◽  
Hydrological Cycle ◽  
Water Storage ◽  
Model Parameters ◽  
Hydrological Models ◽  
Rhine River ◽  
Terrestrial Water Storage ◽  
Grace Data ◽  
Terrestrial Water

Abstract. The ability to estimate terrestrial water storage (TWS) realistically is essential for understanding past hydrological events and predicting future changes in the hydrological cycle. Inadequacies in model physics, uncertainty in model land parameters, and uncertainties in meteorological data commonly limit the accuracy of hydrological models in simulating TWS. In an effort to improve model performance, this study investigated the benefits of assimilating TWS estimates derived from the Gravity Recovery and Climate Experiment (GRACE) data into the OpenStreams wflow_hbv model using an ensemble Kalman filter (EnKF) approach. The study area chosen was the Rhine River basin, which has both well-calibrated model parameters and high-quality forcing data that were used for experimentation and comparison. Four different case studies were examined which were designed to evaluate different levels of forcing data quality and resolution including those typical of other less well-monitored river basins. The results were validated using in situ groundwater (GW) and stream gauge data. The analysis showed a noticeable improvement in GW estimates when GRACE data were assimilated, with a best-case improvement of correlation coefficient from 0.31 to 0.53 and root mean square error (RMSE) from 8.4 to 5.4 cm compared to the reference (ensemble open-loop) case. For the data-sparse case, the best-case GW estimates increased the correlation coefficient from 0.46 to 0.61 and decreased the RMSE by 35%. For the average improvement of GW estimates (for all four cases), the correlation coefficient increases from 0.6 to 0.7 and the RMSE was reduced by 15%. Only a slight overall improvement was observed in streamflow estimates when GRACE data were assimilated. Further analysis suggested that this is likely due to sporadic short-term, but sizeable, errors in the forcing data and the lack of sufficient constraints on the soil moisture component. Overall, the results highlight the benefit of assimilating GRACE data into hydrological models, particularly in data-sparse regions, while also providing insight on future refinements of the methodology.

Downstream implications of ultra-low flush WCs

2007 ◽  
Vol 2 (2) ◽  
Author(s):  
K. Littlewood ◽  
F.A. Memon ◽  
D. Butler
Keyword(s):  
Water Demand ◽  
Demand Management ◽  
Drainage Network ◽  
Design Rules ◽  
Flow Rates ◽  
Solids Transport ◽  
Transport Distance ◽  
Drainage Design ◽  
Drainage Pipe ◽  
Flush Toilet

This paper examines some of the issues associated with the impacts of water demand management on the drainage network. In particular, it is argued that with the advent of lower water use WCs, much lower volumes and flow rates will be available to transport gross solids in sewers. The paper reports some of the results of a study to evaluate the performance of one such ultra-low flush WC in terms of limiting solids transport distance. It was found that the ultra-low flush toilet performed as well as a conventional WC, but only when connected to a 50mm diameter drainage pipe. The implication is that for best use of this technology, and other innovative devices, new building drainage design rules will need to be devised.

Comparison between dynamic and static sensitivity analysis approaches for impact assessment of different potential evapotranspiration methods on hydrological models performance

2021 ◽  
Author(s):  
Rodric Mérimé Nonki ◽  
André Lenouo ◽  
Christopher J. Lennard ◽  
Raphael M. Tshimanga ◽  
Clément Tchawoua
Keyword(s):  
Sensitivity Analysis ◽  
Impact Assessment ◽  
Hydrological Modeling ◽  
Potential Evapotranspiration ◽  
Model Performance ◽  
Estimation Methods ◽  
Model Parameters ◽  
Hydrological Models ◽  
Sensitivity Approach ◽  
Static Sensitivity

AbstractPotential Evapotranspiration (PET) plays a crucial role in water management, including irrigation systems design and management. It is an essential input to hydrological models. Direct measurement of PET is difficult, time-consuming and costly, therefore a number of different methods are used to compute this variable. This study compares the two sensitivity analysis approaches generally used for PET impact assessment on hydrological model performance. We conducted the study in the Upper Benue River Basin (UBRB) located in northern Cameroon using two lumped-conceptual rainfall-runoff models and nineteen PET estimation methods. A Monte-Carlo procedure was implemented to calibrate the hydrological models for each PET input while considering similar objective functions. Although there were notable differences between PET estimation methods, the hydrological models performance was satisfactory for each PET input in the calibration and validation periods. The optimized model parameters were significantly affected by the PET-inputs, especially the parameter responsible to transform PET into actual ET. The hydrological models performance was insensitive to the PET input using a dynamic sensitivity approach, while he was significantly affected using a static sensitivity approach. This means that the over-or under-estimation of PET is compensated by the model parameters during the model recalibration. The model performance was insensitive to the rescaling PET input for both dynamic and static sensitivities approaches. These results demonstrate that the effect of PET input to model performance is necessarily dependent on the sensitivity analysis approach used and suggest that the dynamic approach is more effective for hydrological modeling perspectives.

scholarly journals Improving Meteorological Seasonal Forecasts for Hydrological Modeling in European Winter

2020 ◽  
Vol 59 (2) ◽  
pp. 317-332
Author(s):  
Nicky Stringer ◽  
Jeff Knight ◽  
Hazel Thornton
Keyword(s):  
North Atlantic ◽  
Large Scale ◽  
Hydrological Modeling ◽  
Strongly Correlated ◽  
Hydrological Models ◽  
Seasonal Forecasts ◽  
The North ◽  
Ensemble Mean ◽  
The North Atlantic Oscillation ◽  
Correlation Skill

AbstractRecent advances in the skill of seasonal forecasts in the extratropics during winter mean they could offer improvements to seasonal hydrological forecasts. However, the signal-to-noise paradox, whereby the variability in the ensemble mean signal is lower than would be expected given its correlation skill, prevents their use to force hydrological models directly. We describe a postprocessing method to adjust for this problem, increasing the size of the predicted signal in the large-scale circulation. This reduces the ratio of predictable components in the North Atlantic Oscillation (NAO) from 3 to 1. We then derive a large ensemble of daily sequences of spatially gridded rainfall that are consistent with the seasonal mean NAO prediction by selecting historical observations conditioned on the adjusted NAO forecasts. Over northern and southwestern Europe, where the NAO is strongly correlated with winter mean rainfall, the variability of the predicted signal in the adjusted rainfall forecasts is consistent with the correlation skill (they have a ratio of predictable components of ~1) and are as skillful as the unadjusted forecasts. The adjusted forecasts show larger predicted deviations from climatology and can be used to better assess the risk of extreme seasonal mean precipitation as well as to force hydrological models.

scholarly journals Flow structure around an actual willow patch under different depth conditions

2018 ◽  
Vol 40 ◽  
pp. 02049
Author(s):  
Chanjoo Lee ◽  
Donggu Kim ◽  
Sungjung Kim ◽  
Un Ji ◽  
Jihyun Kim ◽  
...  
Keyword(s):  
Flow Measurement ◽  
Flash Flood ◽  
Experimental Studies ◽  
Hydrodynamic Modelling ◽  
Snow Melt ◽  
Key Factors ◽  
Environmental Aspects ◽  
Real Scale ◽  
Natural Channel ◽  
Made In

Vegetation is one of the key factors in river management where environmental aspects as well as flood protection should be taken into consideration. Because of this, numerous studies have been done including experiments and hydrodynamic modelling. Because most of experimental studies were made in indoor laboratory flumes with artificial trees, there are still limitations in transfer of their result to actual channels. REC (River Experiment Center) of Korea has been operating three real-scale, nature-like outdoor experimental channels. In a straight channel, several 4x2 m actual willow patches were planted and have been grown last three years for studies on flow vegetation interaction. A set of intensive flow measurement was made around the first upstream willow patch using ADVs together with measurement of vegetation properties. The experiments were made under several different depth conditions simulating snow-melt and flash-flood. Distribution of flow around and through the patch was characterized along with vertical profiles. The results of the experiment enhance understanding on interaction of flow and actual vegetation in a natural channel and may also provide information on flow resistance used for hydrodynamic modelling and validation.

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