Estimation of flow in ungauged catchments by coupling a hydrological model and neural networks: case study

2011 ◽  
Vol 42 (5) ◽  
pp. 386-400 ◽  
Author(s):  
A. H. Saliha ◽  
S. B. Awulachew ◽  
J. Cullmann ◽  
Hans-B. Horlacher
Keyword(s):  
Regional Model ◽  
Homogeneous Group ◽  
Low Flow ◽  
Model Parameters ◽  
Watershed Model ◽  
Ungauged Catchments ◽  
Kohonen Neural Network ◽  
Catchment Characteristics ◽  
Ungauged Basin ◽  
Distributed Hydrological Models

The prediction of hydrological variables for ungauged basins is still a big challenge. Regionalization is the most widely used method to date, which relates parameters of watershed models to catchment characteristics. Relating catchment characteristics to watershed model parameters is too difficult for distributed hydrological models, due to the heterogeneous nature of catchments. A regional model was proposed by coupling a Kohonen neural network (KNN) and distributed Water Balance Simulation Model (WaSiM-ETH) to estimate flow in ungauged basin. KNN was used to delineate a hydrological homogeneous group based on predefined physical characteristics of catchments and WaSiM-ETH was applied to generate daily stream flow. Twenty-six subcatchments of the Blue Nile River basin, Ethiopia, were grouped into five hydrological homogenous groups, each with its own full set of optimized WaSiM-ETH parameters. In the regional model, the KNN assigned the ungauged catchment into one of the five hydrological homogenous groups. The whole set of optimized WaSiM parameters from the homogeneous group (which the ungauged river belongs to) were transferred to the ungauged river and WaSiM-ETH was used to compute the flow for this ungauged river. The regional model generally overestimated the low flow. In general, the results for validation subcatchments showed the regional model is satisfactory in transferring information from data-rich to data-poor catchments.

scholarly journals A trading-space-for-time approach to probabilistic continuous streamflow predictions in a changing climate – accounting for changing watershed behavior

2011 ◽  
Vol 15 (11) ◽  
pp. 3591-3603 ◽  
Author(s):  
R. Singh ◽  
T. Wagener ◽  
K. van Werkhoven ◽  
M. E. Mann ◽  
R. Crane
Keyword(s):  
Spatial Relationship ◽  
Model Performance ◽  
Climate Scenario ◽  
Hydrologic Model ◽  
Climatic Conditions ◽  
Low Flow ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Watershed Model ◽  
The Impact

Abstract. Projecting how future climatic change might impact streamflow is an important challenge for hydrologic science. The common approach to solve this problem is by forcing a hydrologic model, calibrated on historical data or using a priori parameter estimates, with future scenarios of precipitation and temperature. However, several recent studies suggest that the climatic regime of the calibration period is reflected in the resulting parameter estimates and model performance can be negatively impacted if the climate for which projections are made is significantly different from that during calibration. So how can we calibrate a hydrologic model for historically unobserved climatic conditions? To address this issue, we propose a new trading-space-for-time framework that utilizes the similarity between the predictions under change (PUC) and predictions in ungauged basins (PUB) problems. In this new framework we first regionalize climate dependent streamflow characteristics using 394 US watersheds. We then assume that this spatial relationship between climate and streamflow characteristics is similar to the one we would observe between climate and streamflow over long time periods at a single location. This assumption is what we refer to as trading-space-for-time. Therefore, we change the limits for extrapolation to future climatic situations from the restricted locally observed historical variability to the variability observed across all watersheds used to derive the regression relationships. A typical watershed model is subsequently calibrated (conditioned) on the predicted signatures for any future climate scenario to account for the impact of climate on model parameters within a Bayesian framework. As a result, we can obtain ensemble predictions of continuous streamflow at both gauged and ungauged locations. The new method is tested in five US watersheds located in historically different climates using synthetic climate scenarios generated by increasing mean temperature by up to 8 °C and changing mean precipitation by −30% to +40% from their historical values. Depending on the aridity of the watershed, streamflow projections using adjusted parameters became significantly different from those using historically calibrated parameters if precipitation change exceeded −10% or +20%. In general, the trading-space-for-time approach resulted in a stronger watershed response to climate change for both high and low flow conditions.

scholarly journals Exploring hydrologically similar catchments in terms of the physical characteristics of upstream regions

2017 ◽  
Vol 49 (5) ◽  
pp. 1467-1483 ◽  
Author(s):  
Yi Jin ◽  
Jintao Liu ◽  
Lu Lin ◽  
Aihua Wang ◽  
Xi Chen
Keyword(s):  
Hydrologic Model ◽  
Physical Characteristics ◽  
High Flow ◽  
Low Flow ◽  
Model Parameters ◽  
Physical Factors ◽  
Ungauged Catchments ◽  
Response Factors ◽  
Average Annual Runoff ◽  
Huai River

Abstract Catchment classification strategies based on easily available physical characteristics are important for extrapolating hydrologic model parameters and improving hydrologic predictions in ungauged catchments. In this study, we conduct an experiment of catchment classification and explore the feasibility of characterizing hydrologically similar catchments using certain physical characteristics in upstream regions of the Huai River Basin. The similarity metrics of hydrologic response factors (high flow, low flow and average annual runoff) and physical factors (topography, shape, soil and vegetation) are fed into the K-means algorithm for catchment classification. All the catchments are classified into two classes regardless of the types of metrics used. By comparing the overlap coefficient (η) and Rand index (RI) between any two classification results, we found that the topography classification displays the highest concordance with the high flow classification (η = 79.2% and RI = 0.66) among all metrics. Including more metrics would not produce consistently better classification results. The optimal combination of metrics, with η = 87.5%, is the high flow metrics (Q10%, SFH and MAX90) with the topography metrics (AS and HI). The results indicate that the physical metrics adopted for hydrologic classification should be determined carefully in terms of specific hydrologic characteristics.

Exploring elevation zone similarity in large case studies for the semi-distributed regionalisation of the HBV model parameters

2020 ◽  
Author(s):  
Mattia Neri ◽  
Elena Toth ◽  
Juraj Parajka
Keyword(s):  
Similarity Measures ◽  
Model Parameters ◽  
Runoff Generation ◽  
Ungauged Catchments ◽  
Typical Application ◽  
Distributed Structure ◽  
Ungauged Basin ◽  
Basin Scale ◽  
Rainfall Runoff Model ◽  
Different Altitudes

<p>The study aims to propose and test the performance of a group of techniques for transposing rainfall-runoff model parameters to ungauged catchments, especially adapted to the semi-distributed structure (the catchment is split into different altitude zones) of the HBV-based TUWien model.</p><p>The methods are tested for two large, but deeply different, datasets: the first is a very densely gauged set of more than 200 catchments across Austria, while the second refers to more than 500 US watersheds (part of the CAMELS dataset) covering most of the country, including wider variety of hydrological conditions and catchment characteristics.</p><p>The potential of the semi-distributed structure is fully exploited: first in the model calibration, where, differently from the typical application of the model, the parameters controlling the runoff generation are allowed to vary over the different elevation zones.</p><p>Secondly, in the regionalisation procedure, the parameters of each specific altitude zone in any ungauged catchment are estimated based on the parameters obtained for the same altitude zones of the donors. The rationale is to implement a procedure that operates at sub-basin level, in order to have a better simulation of the different hydrological processes taking place at different altitudes.</p><p>The set of regionalisation approaches includes both i) “parameters averaging”, where each parameter is obtained as a weighted (according to donors’ similarity) average of the parameters of the donor catchments (independently from each other) and ii) “output averaging”, where the model is run over the ungauged basin using the entire set of parameters of each donor basin and the simulated outputs are then averaged to estimate the target simulated streamflow.</p><p>The measure of similarity needed for implementing the regionalisation procedure is of course applied at sub-basin scale, testing geo-morphological and climatic catchment descriptors characterising the elevation bands. One of the main focus is the study of such similarity in order to asses which attributes are more influential at different altitudes.</p><p>The performance of the proposed approaches and similarity measures is assessed by jack-knife cross-validation against the observed daily runoff for all the study catchments.</p><p>Finally, the resulted regionalisation efficiencies are compared to those obtained by applying the same methods with the typical lumped calibration-regionalisation procedure, thus assessing the potential of the semi-distributed regionalised parameterisation.</p>

scholarly journals Regionalisation for lake level simulation – the case of Lake Tana in the Upper Blue Nile, Ethiopia

2011 ◽  
Vol 15 (4) ◽  
pp. 1167-1183 ◽  
Author(s):  
T. H. M. Rientjes ◽  
B. U. J. Perera ◽  
A. T. Haile ◽  
P. Reggiani ◽  
L. P. Muthuwatta
Keyword(s):  
Water Balance ◽  
Model Calibration ◽  
Lake Level ◽  
Regional Model ◽  
Model Parameters ◽  
Ungauged Catchments ◽  
Time Step ◽  
Lake Tana ◽  
Multi Objective ◽  
Objective Model

Abstract. In this study lake levels of Lake Tana are simulated at daily time step by solving the water balance for all inflow and outflow processes. Since nearly 62% of the Lake Tana basin area is ungauged a regionalisation procedure is applied to estimate lake inflows from ungauged catchments. The procedure combines automated multi-objective calibration of a simple conceptual model and multiple regression analyses to establish relations between model parameters and catchment characteristics. A relatively small number of studies are presented on Lake Tana's water balance. In most studies the water balance is solved at monthly time step and the water balance is simply closed by runoff contributions from ungauged catchments. Studies partly relied on simple ad-hoc procedures of area comparison to estimate runoff from ungauged catchments. In this study a regional model is developed that relies on principles of similarity of catchments characteristics. For runoff modelling the HBV-96 model is selected while multi-objective model calibration is by a Monte Carlo procedure. We aim to assess the closure term of Lake Tana's water balance, to assess model parameter uncertainty and to evaluate effectiveness of a multi-objective model calibration approach to make hydrological modeling results more plausible. For the gauged catchments, model performance is assessed by the Nash-Sutcliffe coefficient and Relative Volumetric Error and resulted in satisfactory to good performance for six, large catchments. The regional model is validated and indicated satisfactory to good performance in most cases. Results show that runoff from ungauged catchments is as large as 527 mm per year for the simulation period and amounts to approximately 30% of Lake Tana stream inflow. Results of daily lake level simulation over the simulation period 1994–2003 show a water balance closure term of 85 mm per year that accounts to 2.7% of the total lake inflow. Lake level simulations are assessed by Nash Sutcliffe (0.91) and Relative Volume Error (2.71%) performance measures.

scholarly journals A Model-Based Tool for Assessing the Impact of Land Use Change Scenarios on Flood Risk in Small-Scale River Systems—Part 1: Pre-Processing of Scenario Based Flood Characteristics for the Current State of Land Use

Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 102
Author(s):  
Frauke Kachholz ◽  
Jens Tränckner
Keyword(s):  
Land Use ◽  
River Flow ◽  
Land Use Changes ◽  
Small Rivers ◽  
Small Scale ◽  
Model Parameters ◽  
Ungauged Catchments ◽  
Model Based ◽  
Current State ◽  
The Impact

Land use changes influence the water balance and often increase surface runoff. The resulting impacts on river flow, water level, and flood should be identified beforehand in the phase of spatial planning. In two consecutive papers, we develop a model-based decision support system for quantifying the hydrological and stream hydraulic impacts of land use changes. Part 1 presents the semi-automatic set-up of physically based hydrological and hydraulic models on the basis of geodata analysis for the current state. Appropriate hydrological model parameters for ungauged catchments are derived by a transfer from a calibrated model. In the regarded lowland river basins, parameters of surface and groundwater inflow turned out to be particularly important. While the calibration delivers very good to good model results for flow (Evol =2.4%, R = 0.84, NSE = 0.84), the model performance is good to satisfactory (Evol = −9.6%, R = 0.88, NSE = 0.59) in a different river system parametrized with the transfer procedure. After transferring the concept to a larger area with various small rivers, the current state is analyzed by running simulations based on statistical rainfall scenarios. Results include watercourse section-specific capacities and excess volumes in case of flooding. The developed approach can relatively quickly generate physically reliable and spatially high-resolution results. Part 2 builds on the data generated in part 1 and presents the subsequent approach to assess hydrologic/hydrodynamic impacts of potential land use changes.

Estimating low flow characteristics in ungauged catchments

1992 ◽  
Vol 6 (2) ◽  
pp. 85-100 ◽  
Author(s):  
Rory J. Nathan ◽  
Tom A. McMahon
Keyword(s):  
Flow Characteristics ◽  
Low Flow ◽  
Ungauged Catchments

scholarly journals Uncertainty analysis in model parameters regionalization: a case study involving the SWAT model in Mediterranean catchments (Southern France)

2014 ◽  
Vol 18 (6) ◽  
pp. 2393-2413 ◽  
Author(s):  
H. Sellami ◽  
I. La Jeunesse ◽  
S. Benabdallah ◽  
N. Baghdadi ◽  
M. Vanclooster
Keyword(s):  
Model Prediction ◽  
Hydrological Model ◽  
Swat Model ◽  
Behavioral Model ◽  
Model Parameters ◽  
Ungauged Catchments ◽  
Southern France ◽  
Model Parameter ◽  
Ungauged Catchment ◽  
Prediction Uncertainty

Abstract. In this study a method for propagating the hydrological model uncertainty in discharge predictions of ungauged Mediterranean catchments using a model parameter regionalization approach is presented. The method is developed and tested for the Thau catchment located in Southern France using the SWAT hydrological model. Regionalization of model parameters, based on physical similarity measured between gauged and ungauged catchment attributes, is a popular methodology for discharge prediction in ungauged basins, but it is often confronted with an arbitrary criterion for selecting the "behavioral" model parameter sets (Mps) at the gauged catchment. A more objective method is provided in this paper where the transferrable Mps are selected based on the similarity between the donor and the receptor catchments. In addition, the method allows propagating the modeling uncertainty while transferring the Mps to the ungauged catchments. Results indicate that physically similar catchments located within the same geographic and climatic region may exhibit similar hydrological behavior and can also be affected by similar model prediction uncertainty. Furthermore, the results suggest that model prediction uncertainty at the ungauged catchment increases as the dissimilarity between the donor and the receptor catchments increases. The methodology presented in this paper can be replicated and used in regionalization of any hydrological model parameters for estimating streamflow at ungauged catchment.

scholarly journals Conditioning rainfall-runoff model parameters for ungauged catchments and land management impacts analysis

2009 ◽  
Vol 13 (6) ◽  
pp. 893-904 ◽  
Author(s):  
N. Bulygina ◽  
N. McIntyre ◽  
H. Wheater
Keyword(s):  
Parameter Space ◽  
Land Management ◽  
Base Flow ◽  
Distributed Model ◽  
Flow Index ◽  
Model Parameters ◽  
Ungauged Catchments ◽  
Management Interventions ◽  
Simulated Event ◽  
Base Flow Index

Abstract. Data scarcity and model over-parameterisation, leading to model equifinality and large prediction uncertainty, are common barriers to effective hydrological modelling. The problem can be alleviated by constraining the prior parameter space using parameter regionalisation. A common basis for regionalisation in the UK is the HOST database which provides estimates of hydrological indices for different soil classifications. In our study, Base Flow Index is estimated from the HOST database and the power of this index for constraining the parameter space is explored. The method is applied to a highly discretised distributed model of a 12.5 km2 upland catchment in Wales. To assess probabilistic predictions against flow observations, a probabilistic version of the Nash-Sutcliffe efficiency is derived. For six flow gauges with reliable data, this efficiency ranged between 0.70 and 0.81, and inspection of the results shows that the model explains the data well. Knowledge of how Base Flow Index and interception losses may change under future land use management interventions was then used to further condition the model. Two interventions are considered: afforestation of grazed areas, and soil degradation associated with increased grazing intensity. Afforestation leads to median reduction in modelled runoff volume of 24% over the simulated 3 month period; and a median peak flow reduction ranging from 12 to 15% over the six gauges for the largest simulated event. Uncertainty in all results is low compared to prior uncertainty and it is concluded that using Base Flow Index estimated from HOST is a simple and potentially powerful method of conditioning the parameter space under current and future land management.

scholarly journals Estimation of baseflow parameters of variable infiltration capacity model with soil and topography properties for predictions in ungauged basins

2011 ◽  
Vol 8 (4) ◽  
pp. 7017-7053 ◽  
Author(s):  
Z. Bao ◽  
J. Liu ◽  
J. Zhang ◽  
G. Fu ◽  
G. Wang ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Model Simulation ◽  
Parameters Estimation ◽  
Model Parameters ◽  
Ungauged Basins ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Ungauged Catchments ◽  
Vic Model ◽  
Predictions In Ungauged Basins

Abstract. Equifinality is unavoidable when transferring model parameters from gauged catchments to ungauged catchments for predictions in ungauged basins (PUB). A framework for estimating the three baseflow parameters of variable infiltration capacity (VIC) model, directly with soil and topography properties is presented. When the new parameters setting methodology is used, the number of parameters needing to be calibrated is reduced from six to three, that leads to a decrease of equifinality and uncertainty. This is validated by Monte Carlo simulations in 24 hydro-climatic catchments in China. Using the new parameters estimation approach, model parameters become more sensitive and the extent of parameters space will be smaller when a threshold of goodness-of-fit is given. That means the parameters uncertainty is reduced with the new parameters setting methodology. In addition, the uncertainty of model simulation is estimated by the generalised likelihood uncertainty estimation (GLUE) methodology. The results indicate that the uncertainty of streamflow simulations, i.e., confidence interval, is lower with the new parameters estimation methodology compared to that used by original calibration methodology. The new baseflow parameters estimation framework could be applied in VIC model and other appropriate models for PUB.

scholarly journals Hydrologic responses of the Zwalm catchment using the REW model: incorporating uncertainty of soil properties

2006 ◽  
Vol 3 (1) ◽  
pp. 69-114 ◽  
Author(s):  
A. El Ouazzani Taibi ◽  
G. P. Zhang ◽  
A. Elfeki
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Hydraulic Conductivity ◽  
Model Parameters ◽  
Watershed Model ◽  
The Monte Carlo Method ◽  
Physically Based ◽  
Hydrologic Responses ◽  
High Influence ◽  
Model Approach

Abstract. The research presented in this paper focuses on an application of a newly developed physically-based watershed model approach, which is called Representative Elementary Watershed (REW) approach. The study stressed the effects of uncertainty of input parameters on the watershed responses (i.e. simulated discharges). The approach was applied to the Zwalm catchment, which is an agriculture dominated watershed with a drainage area of 114.3 km2 located in East-Flanders, Belgium. Uncertainty analysis of the model parameters is limited to the saturated hydraulic conductivity because of its high influence on the watershed hydrologic behavior. The assessment of outputs uncertainty is performed using the Monte Carlo method. The ensemble statistical watershed responses and their uncertainties are calculated and compared with the measurements. The results show that the measured discharges are falling within the 95% confidence interval of the modeled discharge.

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