Comparing Statistical and Semi-Distributed Rainfall–Runoff Models for a Large Subtropical Watershed: A Case Study of Jiulong River Catchment, China

In this contribution, the authors present their preliminary investigations into modeling the rainfall–runoff generation relation in a large subtropical catchment (Jiulong River catchment) on the southeast coast of China. Previous studies have mostly focused on modeling the streamflow and water quality of its small rural subcatchments. However, daily runoff on the scale of the whole catchment has not been modeled before, and hourly runoff data are desirable for some oceanographic applications. Three methods are proposed for modeling streamflow using rainfall outputted by the Weather Research Forecast (WRF) model, calculated potential evaporation (PET), and land cover type: (i) a ridge regression model; (ii) NPRED-KNN: a nonparametric k-nearest neighbor model (KNN) employing a parameter selection method (NPRED) based on partial information coefficient; (iii) the Hydrological Simulation Program-Fortran (HSPF) model with an hourly time step. Results show that the NPRED-KNN approach is the most unsuitable method of those tested. The HSPF model was manually calibrated, and ridge regression performs no worse than HSPF based on daily verification, whilst HSPF can produce realist daily flow time series, of which ridge regression is incapable. The HSPF model seems less prone to systematic underprediction when replicating monthly-annual water balance, and it successfully replicates the baseflow index (the flow intensity) of the Jiulong River catchment system.

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Rainfall-Runoff Modeling Using the HEC-HMS Model for the Al-Adhaim River Catchment, Northern Iraq

Hydrology ◽

10.3390/hydrology8020058 ◽

2021 ◽

Vol 8 (2) ◽

pp. 58

Author(s):

Ahmed Naseh Ahmed Hamdan ◽

Suhad Almuktar ◽

Miklas Scholz

Keyword(s):

Geographical Information Systems ◽

Hydrological Model ◽

Daily Rainfall ◽

Curve Number ◽

Geographical Information ◽

Coefficient Of Determination ◽

Rainfall Runoff ◽

Time Step ◽

River Catchment ◽

Northern Iraq

It has become necessary to estimate the quantities of runoff by knowing the amount of rainfall to calculate the required quantities of water storage in reservoirs and to determine the likelihood of flooding. The present study deals with the development of a hydrological model named Hydrologic Engineering Center (HEC-HMS), which uses Digital Elevation Models (DEM). This hydrological model was used by means of the Geospatial Hydrologic Modeling Extension (HEC-GeoHMS) and Geographical Information Systems (GIS) to identify the discharge of the Al-Adhaim River catchment and embankment dam in Iraq by simulated rainfall-runoff processes. The meteorological models were developed within the HEC-HMS from the recorded daily rainfall data for the hydrological years 2015 to 2018. The control specifications were defined for the specified period and one day time step. The Soil Conservation Service-Curve number (SCS-CN), SCS Unit Hydrograph and Muskingum methods were used for loss, transformation and routing calculations, respectively. The model was simulated for two years for calibration and one year for verification of the daily rainfall values. The results showed that both observed and simulated hydrographs were highly correlated. The model’s performance was evaluated by using a coefficient of determination of 90% for calibration and verification. The dam’s discharge for the considered period was successfully simulated but slightly overestimated. The results indicated that the model is suitable for hydrological simulations in the Al-Adhaim river catchment.

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A Novel Integrated Rainfall-Runoff Model Based on TOPMODEL and Artificial Neural Network

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.423-426.1405 ◽

2013 ◽

Vol 423-426 ◽

pp. 1405-1408 ◽

Cited By ~ 2

Author(s):

Shuang Liu ◽

Jing Wen Xu ◽

Jun Fang Zhao ◽

Yong Li

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Optimization Technique ◽

Integrated Model ◽

Physical Models ◽

Efficiency Coefficient ◽

Rainfall Runoff ◽

Runoff Generation ◽

Time Step ◽

Artificial Neural

Conventional process-based rainfall-runoff models are difficult to catch the non-linear factors and to take full advantages of previous information of rainfall and runoff. However, these factors are closely related to the initial watershed average saturation deficit at each time step. Therefore, in order to address the issue, this study selected the parameter about initial underground flow in TOPMODEL (TOPOgraphic driven Model) as the breakthrough point. Then we used the previous two-day observed runoff and rainfall data as the inputs of an artificial neural network (ANN) and initial subsurface flow of present day as an output, then integrated ANN into runoff generation module in TOPMODEL and finally applied the integrated model for daily runoff modeling in Yingluoxia watershed with 10009km2, China. In addition, this work also utilized particle swarm optimization technique (PSO) to avoid the local optimization, especially for the integration of black-box and physical models. The result shows that during the validation period the Nash-Sutcliffe efficiency coefficient (NE) and root mean square error (RMSE) of TOPMODEL are 0.45 and 3.88×10-4m respectively while the NE of 0.70 and RMSE of 2.85×10-4m for the integrated model. Significantly, the integrated model performs much better than the traditional model. Hence, this new method of integrating ANN with the runoff generation module of TOPMODEL is promising and easily extended to other process-based rainfall-runoff models as well.

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A Comparative Study of Different Hydrological Model and their Application in Little River Catchment

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.641-642.9 ◽

2014 ◽

Vol 641-642 ◽

pp. 9-13

Author(s):

Shu Yan ◽

Zhong Yuan Zhang ◽

Feng Lin Zuo ◽

Wei Hua Zhang

Keyword(s):

Hydrological Model ◽

Rainfall Runoff ◽

Runoff Generation ◽

Optimal Model ◽

Humid Climate ◽

Tank Model ◽

Southeastern Usa ◽

River Catchment ◽

Total Runoff ◽

Error Coefficient

Sacramento, SimHyd and Tank model were selected and their structure, principles and characteristics were briefly described. Then by taking Little River Catchment in Georgia, USA as an example, the rainfall-runoff process was simulated by using the Rainfall Runoff Library. The results showed that: Nash-Sutcliffe coefficient reached more than 80% and RE (relative error coefficient of the total runoff) of Sacramento model also meets the requirements. Considering the Sacramento model is the best one on the Nash-Sutcliffe coefficient, the model is selected as the optimal model of Little River Catchment in this study.As the catchment is located in the southeastern USA, with humid climate, and saturated storage-based runoff generation, which is similar to Chongqing region, it provides relatively good reference for Chongqing as well as the entire southwestern region.

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SHETRAN and HEC HMS Model Evaluation for Runoff and Soil Moisture Simulation in the Jičinka River Catchment (Czech Republic)

Water ◽

10.3390/w13060872 ◽

2021 ◽

Vol 13 (6) ◽

pp. 872

Author(s):

Vesna Đukić ◽

Ranka Erić

Keyword(s):

Soil Moisture ◽

Czech Republic ◽

Hydrological Model ◽

Flash Flood ◽

Model Performance ◽

Rainfall Runoff ◽

The Czech Republic ◽

River Catchment ◽

Hydrological Variable ◽

Model Structures

Due to the improvement of computation power, in recent decades considerable progress has been made in the development of complex hydrological models. On the other hand, simple conceptual models have also been advanced. Previous studies on rainfall–runoff models have shown that model performance depends very much on the model structure. The purpose of this study is to determine whether the use of a complex hydrological model leads to more accurate results or not and to analyze whether some model structures are more efficient than others. Different configurations of the two models of different complexity, the Système Hydrologique Européen TRANsport (SHETRAN) and Hydrologic Modeling System (HEC-HMS), were compared and evaluated in simulating flash flood runoff for the small (75.9 km2) Jičinka River catchment in the Czech Republic. The two models were compared with respect to runoff simulations at the catchment outlet and soil moisture simulations within the catchment. The results indicate that the more complex SHETRAN model outperforms the simpler HEC HMS model in case of runoff, but not for soil moisture. It can be concluded that the models with higher complexity do not necessarily provide better model performance, and that the reliability of hydrological model simulations can vary depending on the hydrological variable under consideration.

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Analyzing catchment behavior through catchment modeling in the Gilgel Abay, Upper Blue Nile River Basin, Ethiopia

Hydrology and Earth System Sciences ◽

10.5194/hess-14-2153-2010 ◽

2010 ◽

Vol 14 (10) ◽

pp. 2153-2165 ◽

Cited By ~ 46

Author(s):

S. Uhlenbrook ◽

Y. Mohamed ◽

A. S. Gragne

Keyword(s):

Water Resources ◽

Model Performance ◽

Computation Time ◽

Hydrological Processes ◽

Runoff Generation ◽

Time Step ◽

Blue Nile ◽

Model Transferability ◽

Catchment Modeling ◽

Data Limitations

Abstract. Understanding catchment hydrological processes is essential for water resources management, in particular in data scarce regions. The Gilgel Abay catchment (a major tributary into Lake Tana, source of the Blue Nile) is undergoing intensive plans for water management, which is part of larger development plans in the Blue Nile basin in Ethiopia. To obtain a better understanding of the water balance dynamics and runoff generation mechanisms and to evaluate model transferability, catchment modeling has been conducted using the conceptual hydrological model HBV. Accordingly, the catchment of the Gilgel Abay has been divided into two gauged sub-catchments (Upper Gilgel Abay and Koga) and the un-gauged part of the catchment. All available data sets were tested for stationarity, consistency and homogeneity and the data limitations (quality and quantity) are discussed. Manual calibration of the daily models for three different catchment representations, i.e. (i) lumped, (ii) lumped with multiple vegetation zones, and (iii) semi-distributed with multiple vegetation and elevation zones, showed good to satisfactory model performances with Nash-Sutcliffe efficiencies Reff > 0.75 and > 0.6 for the Upper Gilgel Abay and Koga sub-catchments, respectively. Better model results could not be obtained with manual calibration, very likely due to the limited data quality and model insufficiencies. Increasing the computation time step to 15 and 30 days improved the model performance in both sub-catchments to Reff > 0.8. Model parameter transferability tests have been conducted by interchanging parameters sets between the two gauged sub-catchments. Results showed poor performances for the daily models (0.30 < Reff < 0.67), but better performances for the 15 and 30 days models, Reff > 0.80. The transferability tests together with a sensitivity analysis using Monte Carlo simulations (more than 1 million model runs per catchment representation) explained the different hydrologic responses of the two sub-catchments, which seems to be mainly caused by the presence of dambos in Koga sub-catchment. It is concluded that daily model transferability is not feasible, while it can produce acceptable results for the 15 and 30 days models. This is very useful for water resources planning and management, but not sufficient to capture detailed hydrological processes in an ungauged area.

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Modelling monthly runoff generation processes following land use changes: groundwater–surface runoff interactions

Hydrology and Earth System Sciences ◽

10.5194/hess-8-903-2004 ◽

2004 ◽

Vol 8 (5) ◽

pp. 903-922 ◽

Cited By ~ 13

Author(s):

M. Bari ◽

K. R. J. Smettem

Keyword(s):

Land Use ◽

Water Balance ◽

Surface Runoff ◽

Land Use Changes ◽

Annual Rainfall ◽

Rainfall Runoff ◽

Runoff Generation ◽

Mean Annual Rainfall ◽

Monthly Runoff ◽

Stream Bed

Abstract. A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall–runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, "Ernies" (control, fully forested) and "Lemon" (54% cleared) are in a zone of mean annual rainfall of 725 mm, while "Salmon" (control, fully forested) and "Wights" (100% cleared) are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall–runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i) immediately after clearing due to reduced evapotranspiration, and (ii) through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i) an upper zone unsaturated store, (ii) a transient stream zone store, (ii) a lower zone unsaturated store and (iv) a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and predicted monthly hydrographs. The observed and predicted monthly runoff for all catchments matched well with coefficients of determination (R2) ranging from 0.68 to 0.87. Predictions were relatively poor for: (i) the Ernies catchment (lowest rainfall, forested), and (ii) months with very high flows. Overall, the predicted mean annual streamflow was within ±8% of the observed values. Keywords: monthly streamflow, land use change, conceptual model, data-based approach, groundwater

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Effects of Geological Structures on Rainfall-Runoff Processes in Headwater Catchments in a Sedimentary Rock Mountain

10.5194/egusphere-egu21-63 ◽

2021 ◽

Author(s):

Jun Inaoka ◽

Ken'ichirou Kosugi ◽

Naoya Masaoka ◽

Tetsushi Itokazu ◽

Kimihito Nakamura

Keyword(s):

Sedimentary Rock ◽

Flow Direction ◽

Storm Runoff ◽

Rainfall Runoff ◽

Runoff Generation ◽

Geological Structures ◽

Headwater Catchments ◽

Average Flow ◽

Bedding Planes ◽

Hydraulic Anisotropy

<p>To clarify rainfall-runoff responses in mountainous areas is essential for disaster prediction as well as water resource management. Runoff is considered to be affected by many factors including evapotranspiration, rainfall, topography, geology, vegetation, and land use. Among them, topography is said to be the most affectable factor. However, previous studies focused on geologies revealed that though catchments in crystalline mountains have less differences among runoffs, catchments in sedimentary rock mountains show great variation in their runoffs. To explain this difference, the geological structures were expected to be the key of runoffs in sedimentary rock mountains. In other words, particularly in headwater catchments located in sedimentary rock mountains, dips and strikes may significantly affect rainwater discharge. Moreover, the groundwater system can significantly be affected by the hydraulic anisotropy originated from geological stratigraphy. Additionally, in sedimentary rock mountains, previous studies suggested convergence of groundwater flows in the direction of strikes, but the effects of dips and strikes on rainfall-runoff responses were not investigated. Furthermore, none of these previous studies focused on the effects of geological structures on storm runoff responses. Therefore, based on the simultaneous observation of twelve catchments that lie radially from a single, isolated mountain peak, this study aims to clarify the effects of dips and strikes, which characterize sedimentary rock mountains, on water discharge.</p><p>The results obtained were as follows: (1) Even though the topographic wetness index (TWI) distributions of the twelve catchments were similar, there were significant differences in their runoff characteristics; (2) Catchments with average flow direction oriented toward the strike direction (strike-oriented catchments) are characterized by large baseflows; (3) Catchments with average flow direction oriented toward the opposite dip direction (opposite dip-oriented catchments) are steep, and this results in quick storm runoff generation; (4) Catchments with average flow direction oriented toward the dip direction (dip-oriented catchments) are gentle, and this results in delayed storm runoff generation. It was supposed that in strike-oriented catchments, large quantities of groundwater flowing along the bedding planes owing to hydraulic anisotropy, exfiltrate and sustain the large amount of the observed baseflow, i.e., in strike-oriented catchments, runoff is directly controlled by geological structures. On the other hand, in opposite dip-oriented and dip-oriented catchments, runoff is indirectly controlled by geological structures, i.e., geological structures affect slope gradients, which result in differences in storm runoff generation. Thus, this study clearly explains that geological structures significantly affect rainfall-runoff responses in headwater catchments located in sedimentary rock mountains.</p>

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Rapid changes in snow cover at low elevations in the Sierra Nevada, California, U.S.A.

Annals of Glaciology ◽

10.3189/s0260305500014294 ◽

1997 ◽

Vol 25 ◽

pp. 367-370 ◽

Cited By ~ 4

Author(s):

Richard Kattelmann

Keyword(s):

Snow Cover ◽

Sierra Nevada ◽

Mountain Range ◽

Rainfall Runoff ◽

Runoff Generation ◽

Distributed Models ◽

Rapid Changes ◽

Spatially Distributed ◽

Precipitation Type ◽

River Forecasting

Snow cover in the intermittent snow zone of the Sierra Nevada can occupy more than 10 000 km2 of the mountain range, but it has received relatively little attention in river forecasting. Snow is deposited at lower elevations only during the cold storms of winter, and remains there only for a few days or weeks. When cold storms have created a thin snow cover at low elevations, a subsequent warm storm can melt this snow in just a few hours and increase the runoff response dramatically. Operational hydrological models and river-forecasting procedures have tended to overlook contributions from the intermittent-snow zone, focusing instead on rainfall-runoff or melt from the snowpack zone at higher elevations. Data-collection efforts are minimal in this zone, too. Ideally, spatially distributed models of snowmelt and runoff generation are needed to account for the typically large differences in snow cover on different aspects in the intermittent snow zone. Although aircraft and satellite imagery would be most desirable to monitor the distribution of snow cover in the intermittent-snow zone, even a few climate stations that report precipitation type and snow presence would be a major improvement over the present situation in the Sierra Nevada.

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A Statistical Vertically Mixed Runoff Model for Regions Featured by Complex Runoff Generation Process

Water ◽

10.3390/w12092324 ◽

2020 ◽

Vol 12 (9) ◽

pp. 2324

Author(s):

Peng Lin ◽

Pengfei Shi ◽

Tao Yang ◽

Chong-Yu Xu ◽

Zhenya Li ◽

...

Keyword(s):

Spatial Heterogeneity ◽

Mixed Model ◽

Soil Surface ◽

Extreme Rainfall ◽

Distributed Model ◽

Generation Process ◽

Efficiency Coefficient ◽

Rainfall Runoff ◽

Runoff Generation ◽

Runoff Model

Hydrological models for regions characterized by complex runoff generation process been suffer from a great weakness. A delicate hydrological balance triggered by prolonged wet or dry underlying condition and variable extreme rainfall makes the rainfall-runoff process difficult to simulate with traditional models. To this end, this study develops a novel vertically mixed model for complex runoff estimation that considers both the runoff generation in excess of infiltration at soil surface and that on excess of storage capacity at subsurface. Different from traditional models, the model is first coupled through a statistical approach proposed in this study, which considers the spatial heterogeneity of water transport and runoff generation. The model has the advantage of distributed model to describe spatial heterogeneity and the merits of lumped conceptual model to conveniently and accurately forecast flood. The model is tested through comparison with other four models in three catchments in China. The Nash–Sutcliffe efficiency coefficient and the ratio of qualified results increase obviously. Results show that the model performs well in simulating various floods, providing a beneficial means to simulate floods in regions with complex runoff generation process.

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A Long–Term Response-Based Rainfall-Runoff Hydrologic Model: Case Study of The Upper Blue Nile

Hydrology ◽

10.3390/hydrology6030069 ◽

2019 ◽

Vol 6 (3) ◽

pp. 69 ◽

Cited By ~ 2

Author(s):

Eatemad Keshta ◽

Mohamed A. Gad ◽

Doaa Amin

Keyword(s):

River Flow ◽

Hydrologic Model ◽

Initial Assessment ◽

Rainfall Runoff ◽

Time Step ◽

Data Set ◽

Blue Nile ◽

Catchment Areas ◽

Surface And Groundwater

This study develops a response-based hydrologic model for long-term (continuous) rainfall-runoff simulations over the catchment areas of big rivers. The model overcomes the typical difficulties in estimating infiltration and evapotranspiration parameters using a modified version of the Soil Conservation Service curve number SCS-CN method. In addition, the model simulates the surface and groundwater hydrograph components using the response unit-hydrograph approach instead of using a linear reservoir routing approach for routing surface and groundwater to the basin outlet. The unit-responses are Geographic Information Systems (GIS)-pre-calculated on a semi-distributed short-term basis and applied in the simulation in every time step. The unit responses are based on the time-area technique that can better simulate the real routing behavior of the basin. The model is less sensitive to groundwater infiltration parameters since groundwater is actually controlled by the surface component and not the opposite. For that reason, the model is called the SCHydro model (Surface Controlled Hydrologic model). The model is tested on the upper Blue Nile catchment area using 28 years daily river flow data set for calibration and validation. The results show that SCHydro model can simulate the long-term transforming behavior of the upper Blue Nile basin. Our initial assessment of the model indicates that the model is a promising tool for long-term river flow simulations, especially for long-term forecasting purposes due to its stability in performing the water balance.

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