Transferability of the Xin'anjiang model based on similarity in climate and geography

Abstract Hydrological experiments are essential to understand the hydrological cycles and promoting the development of hydrologic models. Model parameter transfers provide a new way of doing hydrological forecasts and simulations in ungauged catchments. To study the transferability of model parameters for hydrological modelling and the influence of parameter transfers on hydrological simulations, the Xin'anjiang model (XAJ model), which is a lumped hydrologic model based on a saturation excess mechanism, and has been widely applied in different climate regions of the world, was applied to a low hilly catchment in eastern China, the Chengxi Experimental Watershed (CXEW). The suitability of the XAJ model was tested in the eastern branch catchment of CXEW and the calibrated model parameters of the eastern branch catchment were then transferred to the western branch catchment and the entire watershed of the CXEW. The results show that the XAJ model performs well for the calibrated eastern branch catchment at both daily and monthly scales on hydrological modelling with the NSEs over 0.6 and the REs less than 2.0%. Besides, the uncalibrated catchments of the western branch catchment and the entire watershed of the CSEW share similarities in climate (the precipitation) and geography (the soil texture and vegetation cover) with the calibrated catchment, the XAJmodel and the transferred model parameters can capture the main features of the hydrological processes in both uncalibrated catchments (western catchments and entire watershed). This transferability of the model is useful for a scarce data region to simulate the hydrological process and its forecasting.

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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 ◽

10.3390/hydrology8030102 ◽

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.

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Calibration and evaluation of a semi-distributed watershed model of Sub-Saharan Africa using GRACE data

Hydrology and Earth System Sciences ◽

10.5194/hess-16-3083-2012 ◽

2012 ◽

Vol 16 (9) ◽

pp. 3083-3099 ◽

Cited By ~ 40

Author(s):

H. Xie ◽

L. Longuevergne ◽

C. Ringler ◽

B. R. Scanlon

Keyword(s):

Regional Scale ◽

Water Storage ◽

Hydrologic Model ◽

Sub Saharan Africa ◽

Model Parameters ◽

Total Water ◽

Discharge Data ◽

Model Based ◽

Grace Data ◽

Sub Saharan

Abstract. Irrigation development is rapidly expanding in mostly rainfed Sub-Saharan Africa. This expansion underscores the need for a more comprehensive understanding of water resources beyond surface water. Gravity Recovery and Climate Experiment (GRACE) satellites provide valuable information on spatio-temporal variability in water storage. The objective of this study was to calibrate and evaluate a semi-distributed regional-scale hydrologic model based on the Soil and Water Assessment Tool (SWAT) code for basins in Sub-Saharan Africa using seven-year (July 2002–April 2009) 10-day GRACE data and multi-site river discharge data. The analysis was conducted in a multi-criteria framework. In spite of the uncertainty arising from the tradeoff in optimising model parameters with respect to two non-commensurable criteria defined for two fluxes, SWAT was found to perform well in simulating total water storage variability in most areas of Sub-Saharan Africa, which have semi-arid and sub-humid climates, and that among various water storages represented in SWAT, water storage variations in soil, vadose zone and groundwater are dominant. The study also showed that the simulated total water storage variations tend to have less agreement with GRACE data in arid and equatorial humid regions, and model-based partitioning of total water storage variations into different water storage compartments may be highly uncertain. Thus, future work will be needed for model enhancement in these areas with inferior model fit and for uncertainty reduction in component-wise estimation of water storage variations.

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Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

Natural Hazards and Earth System Science ◽

10.5194/nhess-12-3719-2012 ◽

2012 ◽

Vol 12 (12) ◽

pp. 3719-3732 ◽

Cited By ~ 4

Author(s):

L. Mediero ◽

L. Garrote ◽

A. Chavez-Jimenez

Keyword(s):

Data Assimilation ◽

Genetic Programming ◽

Real Time ◽

High Performance ◽

Forecast Model ◽

Flood Forecasting ◽

Distribution Functions ◽

Model Parameters ◽

Hydrological Process ◽

Model Based

Abstract. Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

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On the selection of precipitation products for the regionalisation of hydrological model parameters

Hydrology and Earth System Sciences ◽

10.5194/hess-25-5805-2021 ◽

2021 ◽

Vol 25 (11) ◽

pp. 5805-5837

Author(s):

Oscar M. Baez-Villanueva ◽

Mauricio Zambrano-Bigiarini ◽

Pablo A. Mendoza ◽

Ian McNamara ◽

Hylke E. Beck ◽

...

Keyword(s):

Hydrological Model ◽

Model Performance ◽

Temporal Distribution ◽

Hydrological Regime ◽

Hydrologic Model ◽

Spatial Proximity ◽

Model Parameters ◽

Ungauged Catchments ◽

Water Balance Components ◽

Feature Similarity

Abstract. Over the past decades, novel parameter regionalisation techniques have been developed to predict streamflow in data-scarce regions. In this paper, we examined how the choice of gridded daily precipitation (P) products affects the relative performance of three well-known parameter regionalisation techniques (spatial proximity, feature similarity, and parameter regression) over 100 near-natural catchments with diverse hydrological regimes across Chile. We set up and calibrated a conceptual semi-distributed HBV-like hydrological model (TUWmodel) for each catchment, using four P products (CR2MET, RF-MEP, ERA5, and MSWEPv2.8). We assessed the ability of these regionalisation techniques to transfer the parameters of a rainfall-runoff model, implementing a leave-one-out cross-validation procedure for each P product. Despite differences in the spatio-temporal distribution of P, all products provided good performance during calibration (median Kling–Gupta efficiencies (KGE′s) > 0.77), two independent verification periods (median KGE′s >0.70 and 0.61, for near-normal and dry conditions, respectively), and regionalisation (median KGE′s for the best method ranging from 0.56 to 0.63). We show how model calibration is able to compensate, to some extent, differences between P forcings by adjusting model parameters and thus the water balance components. Overall, feature similarity provided the best results, followed by spatial proximity, while parameter regression resulted in the worst performance, reinforcing the importance of transferring complete model parameter sets to ungauged catchments. Our results suggest that (i) merging P products and ground-based measurements does not necessarily translate into an improved hydrologic model performance; (ii) the spatial resolution of P products does not substantially affect the regionalisation performance; (iii) a P product that provides the best individual model performance during calibration and verification does not necessarily yield the best performance in terms of parameter regionalisation; and (iv) the model parameters and the performance of regionalisation methods are affected by the hydrological regime, with the best results for spatial proximity and feature similarity obtained for rain-dominated catchments with a minor snowmelt component.

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Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale

Hydrology and Earth System Sciences ◽

10.5194/hess-10-353-2006 ◽

2006 ◽

Vol 10 (3) ◽

pp. 353-368 ◽

Cited By ~ 116

Author(s):

J. Parajka ◽

V. Naeimi ◽

G. Blöschl ◽

W. Wagner ◽

R. Merz ◽

...

Keyword(s):

Soil Moisture ◽

Regional Scale ◽

Hydrologic Model ◽

Hydrologic Models ◽

Ungauged Catchments ◽

Soil Moisture Dynamics ◽

Model Efficiency ◽

The Relationship ◽

Runoff Model ◽

Moisture Dynamics

Abstract. This paper examines the potential of scatterometer data from ERS satellites for improving hydrological simulations in both gauged and ungauged catchments. We compare the soil moisture dynamics simulated by a semidistributed hydrologic model in 320 Austrian catchments with the soil moisture dynamics inferred from the satellite data. The most apparent differences occur in the Alpine areas. Assimilating the scatterometer data into the hydrologic model during the calibration phase improves the relationship between the two soil moisture estimates without any significant decrease in runoff model efficiency. For the case of ungauged catchments, assimilating scatterometer data does not improve the daily runoff simulations but does provide more consistent soil moisture estimates. If the main interest is in obtaining estimates of catchment soil moisture, reconciling the two sources of soil moisture information seems to be of value because of the different error structures.

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Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-2-2739-2005 ◽

2005 ◽

Vol 2 (6) ◽

pp. 2739-2786 ◽

Cited By ~ 3

Author(s):

J. Parajka ◽

V. Naeimi ◽

G. Blöschl ◽

W. Wagner ◽

R. Merz ◽

...

Keyword(s):

Soil Moisture ◽

Regional Scale ◽

Hydrologic Model ◽

Hydrologic Models ◽

Ungauged Catchments ◽

Soil Moisture Dynamics ◽

Model Efficiency ◽

The Relationship ◽

Runoff Model ◽

Moisture Dynamics

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Temporal changes in rainfall intensity-duration thresholds for post-wildfire flash floods and sensitivity to spatiotemporal distributions of rainfall

10.5194/nhess-2021-157 ◽

2021 ◽

Author(s):

Tao Liu ◽

Luke A. McGuire ◽

Nina Oakley ◽

Forest Cannon

Keyword(s):

Rainfall Intensity ◽

Flash Flood ◽

Flash Floods ◽

Temporal Changes ◽

Hydrologic Model ◽

Model Parameters ◽

Hydrologic Models ◽

Time Intervals ◽

Long Duration ◽

Better Than

Abstract. Rainfall intensity-duration (ID) thresholds are commonly used to assess flash flood potential downstream of burned watersheds. High-intensity and/or long-duration rainfall is required to generate flash floods as landscapes recover from fire, but there is little guidance on how thresholds change as a function of time since burning. Here, we force a hydrologic model with radar-derived precipitation to estimate ID thresholds for post-fire flash floods in a 41.5 km2 watershed in southern California, USA. Prior work in this study area constrains temporal changes in hydrologic model parameters, allowing us to estimate temporal changes in ID thresholds. Results indicate that ID thresholds increase by more than a factor of 2 from post-fire year 1 to post-fire year 5. Thresholds based on averaging rainfall intensity over durations of 30–60 minutes perform better than those that average rainfall intensity over shorter time intervals. Moreover, thresholds based on the 75th percentile of radar-derived rainfall intensity over the watershed perform better than thresholds based on the 25th or 50th percentile of rainfall intensity. Results demonstrate how hydrologic models can be used to estimate changes in ID thresholds following disturbance and provide guidance on the rainfall metrics that are best suited for predicting post-fire flash floods.

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Rainfall-runoff simulations in the Lukovska River Basin with the HEC-HMS model

Glasnik Sumarskog fakulteta ◽

10.2298/gsf1919033e ◽

2019 ◽

pp. 33-60

Author(s):

Ranka Eric ◽

Andrijana Todorovic ◽

Jasna Plavsic ◽

Vesna Djukic

Keyword(s):

River Basin ◽

Optimal Parameter ◽

Hydrologic Model ◽

Model Parameters ◽

Rainfall Runoff ◽

Flood Events ◽

Runoff Generation ◽

Hydrologic Models ◽

Generation Mechanisms ◽

Event Based

Hydrologic models are important for effective water resources management at a basin level. This paper describes an application of the HEC-HMS hydrologic model for simulations of flood hydrographs in the Lukovska River basin. Five flood events observed at the Mercez stream gauge were available for modelling purposes. These events are from two distinct periods and two seasons with different prevailing runoff generation mechanisms. Hence the events are assigned to either ?present? or ?past?, and ?spring? or ?summer? group. The optimal parameter sets of each group are obtained by averaging the optimal parameters for individual events within the group. To assess model transferability, its applicability for simulation of flood events which are not considered in the model calibration, a cross-validation is performed. The results indicate that model parameters vary across the events, and that parameter transfer generally leads to considerable errors in hydrograph peaks and volumes, with the exception of simulation of summer events with ?spring? parameters. Based on these results, recommendations for event-based modeling are given.

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

Hydrology Research ◽

10.2166/nh.2017.191 ◽

2017 ◽

Vol 49 (5) ◽

pp. 1467-1483 ◽

Cited By ~ 2

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.

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Comparison of hydrological model ensemble forecasting based on multiple members and ensemble methods

Open Geosciences ◽

10.1515/geo-2020-0239 ◽

2021 ◽

Vol 13 (1) ◽

pp. 401-415

Author(s):

Jie Wang ◽

Guoqing Wang ◽

Amgad Elmahdi ◽

Zhenxin Bao ◽

Qinli Yang ◽

...

Keyword(s):

Water Resource Management ◽

Ensemble Methods ◽

Ensemble Method ◽

Water Volume ◽

Hydrological Process ◽

Efficiency Coefficient ◽

Hydrologic Models ◽

Runoff Forecasting ◽

Artificial Neural Network Ann ◽

Xin’Anjiang Model

Abstract Ensemble hydrologic forecasting which takes advantages of multiple hydrologic models has made much contribution to water resource management. In this study, four hydrological models (the Xin’anjiang model (XAJ), Simhyd, GR4J, and artificial neural network (ANN) models) and three ensemble methods (the simple average, black box-based, and binomial-based methods) were applied and compared to simulate the hydrological process during 1979–1983 in three representative catchments (Daixi, Hengtangcun, and Qiaodongcun). The results indicate that for a single model, the XAJ model and the GR4J model performed relatively well with averaged Nash and Sutcliffe efficiency coefficient (NSE) values of 0.78 and 0.83, respectively. For the ensemble models, the results show that the binomial-based ensemble method (dynamic weight) outperformed with water volume error reduced by 0.8% and NSE value increased by 0.218. The best performance on runoff forecasting occurs in the Hengtang catchment by integrating four hydrologic models based on binomial ensemble method, achieving the water volume error of 2.73% and NSE value of 0.923. Finding would provide scientific support to water engineering design and water resources management in the study areas.

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