scholarly journals Hydrological modelling of the karst Ljubljanica River catchment using lumped conceptual model

2018 ◽  
pp. 87-100 ◽  
Author(s):  
Cenk Sezen ◽  
Nejc Bezak ◽  
Mojca Šraj
Keyword(s):  
Water System ◽  
Flow Simulation ◽  
Resource Planning ◽  
Base Flow ◽  
Low Flow ◽  
Flow Index ◽  
Rainfall Runoff ◽  
River Catchment ◽  
Simulation Performance

Modelling rainfall runoff is important for several human activities. For example, rainfall runoff models are needed for water resource planning and water system design. In this regard, the daily runoff was modelled using the Genie Rural, a 4-parameter Journalier (GR4J), Genie Rural, a 6-parameter Journalier (GR6J), and the CemaNeige GR6J lumped conceptual models that were developed by the IRSTEA Hydrology Group. The main difference among the tested models is in the complexity and processes that are considered in the various model versions. As a case study, the non-homogeneous mostly karst Ljubljanica River catchment down to the Moste discharge gauging station was selected. Models were evaluated using various efficiency criteria. For example, base flow index (BFI) was calculated for the results of all tested models and observed discharges in order to compare low flow simulation performance. Based on the presented results we can conclude that in case of the non-homogeneous and karst Ljubljanica catchment the CemaNeige GR6J yields better modelling results compared to the GR4J and GR6J models. Compared to the GR6J and GR4J model versions, the CemaNeige CR6J also includes the snow module and improved methodology for the low-flow simulations that are also included in the GR6J model version.

scholarly journals Multiple causes of nonstationarity in the Weihe annual low-flow series

2018 ◽  
Vol 22 (2) ◽  
pp. 1525-1542 ◽  
Author(s):  
Bin Xiong ◽  
Lihua Xiong ◽  
Jie Chen ◽  
Chong-Yu Xu ◽  
Lingqi Li
Keyword(s):  
Frequency Analysis ◽  
Driving Forces ◽  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Base Flow ◽  
Low Flow ◽  
Distribution Model ◽  
Flow Index ◽  
Explanatory Variables ◽  
Distribution Parameters

Abstract. Under the background of global climate change and local anthropogenic activities, multiple driving forces have introduced various nonstationary components into low-flow series. This has led to a high demand on low-flow frequency analysis that considers nonstationary conditions for modeling. In this study, through a nonstationary frequency analysis framework with the generalized linear model (GLM) to consider time-varying distribution parameters, the multiple explanatory variables were incorporated to explain the variation in low-flow distribution parameters. These variables are comprised of the three indices of human activities (HAs; i.e., population, POP; irrigation area, IAR; and gross domestic product, GDP) and the eight measuring indices of the climate and catchment conditions (i.e., total precipitation P, mean frequency of precipitation events λ, temperature T, potential evapotranspiration (EP), climate aridity index AIEP, base-flow index (BFI), recession constant K and the recession-related aridity index AIK). This framework was applied to model the annual minimum flow series of both Huaxian and Xianyang gauging stations in the Weihe River, China (also known as the Wei He River). The results from stepwise regression for the optimal explanatory variables show that the variables related to irrigation, recession, temperature and precipitation play an important role in modeling. Specifically, analysis of annual minimum 30-day flow in Huaxian shows that the nonstationary distribution model with any one of all explanatory variables is better than the one without explanatory variables, the nonstationary gamma distribution model with four optimal variables is the best model and AIK is of the highest relative importance among these four variables, followed by IAR, BFI and AIEP. We conclude that the incorporation of multiple indices related to low-flow generation permits tracing various driving forces. The established link in nonstationary analysis will be beneficial to analyze future occurrences of low-flow extremes in similar areas.

scholarly journals Improved Curve Number Estimation in SWAT by Reflecting the Effect of Rainfall Intensity on Runoff Generation

Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 163 ◽  
Author(s):  
Dejian Zhang ◽  
Qiaoyin Lin ◽  
Xingwei Chen ◽  
Tian Chai
Keyword(s):  
Rainfall Intensity ◽  
Assessment Tool ◽  
Flow Simulation ◽  
Daily Rainfall ◽  
Curve Number ◽  
Base Flow ◽  
Data Sets ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
The Relationship

Determining the amount of rainfall that will eventually become runoff and its pathway is a crucial process in hydrological modelling. We proposed a method to better estimate curve number by adding an additional component (AC) to better account for the effects of daily rainfall intensity on rainfall-runoff generation. This AC is determined by a regression equation developed from the relationship between the AC series derived from fine-tuned calibration processes and observed rainfall series. When incorporated into the Soil and Water Assessment Tool and tested in the Anxi Watershed, it is found, overall, the modified SWAT (SWAT-ICN) outperformed the original SWAT (SWAT-CN) in terms of stream flow, base flow, and annual extreme flow simulation. These models were further evaluated with the data sets of two adjacent watersheds. Similar results were achieved, indicating the ability of the proposed method to better estimate curve number.

scholarly journals Performance Evaluation of Mike Nam Rainfall-Runoff (R-R) Model in Daily Flow Simulation (Case Study: Gonbad Catchment in Hamedan)

2020 ◽  
Vol 10 (1) ◽  
pp. 1-6
Author(s):  
Yasamin Sajadi Bami ◽  
Jahangir Porhemmat ◽  
Hossein Sedghi ◽  
Navid Jalalkamali
Keyword(s):  
Flow Rate ◽  
Model Performance ◽  
Flow Simulation ◽  
Coefficient Of Determination ◽  
Rainfall Runoff ◽  
Mean Flow ◽  
Rainfall Runoff Model ◽  
The Right ◽  
Runoff Model

AbstractNowadays, many hydrological rainfall-runoff (R-R) models, both distributed and lumped, have been developed to simulate the catchment. However, selecting the right model to simulate a specific catchment has always been a challenge. A proper understanding of the model and its advantages and limitations is essential for selecting the appropriate model for the purpose of the study. To this end, several studies have been carried out to evaluate the performance of hydrological models for specific areas (mountainous, marshy and so on). This study was conducted aimed at evaluating the performance of MIKE11 NAM lumped conceptual hydrological rainfall-runoff model in simulation of daily flow rate in Gonbad catchment. The NAM model was calibrated and validated using flow rate data of three hydrometric stations of the Gonbad catchment. The model performance was evaluated using Percent bias (PBIAS) and the coefficient of determination or Nash-Sutcliffe coefficient. A Nash Sutcliffe efficiency (NSE) of 0.80, 0.89 and 080 were obtained during calibration, whereas, for the validation period, NSE of 0.81, 0.87 and 0.71 were obtained for Nemooneh sub catchment, Shahed sub catchment and Gonbad catchment respectively. Percent bias of -0.6, 1.5 and 6.3 were achieved for calibration, while -2.7, 7.6 and -4.2 were acquired during validation for Nemooneh sub catchment, Shahed sub catchment and Gonbad catchment respectively. Based on the results, the MIKE 11 NAM lumped conceptual model was capable of simulating daily mean flow rate and mean flow volume.

scholarly journals Dominant Influencing Factors of Groundwater Recharge Spatial Patterns in Ergene River Catchment, Turkey

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 653 ◽  
Author(s):  
Emmanuel Rukundo ◽  
Ahmet Doğan
Keyword(s):  
Land Use ◽  
Groundwater Recharge ◽  
Principal Component ◽  
Base Flow ◽  
Balance Model ◽  
Flow Index ◽  
Model Calculations ◽  
River Catchment ◽  
Total Runoff ◽  
The Difference

Groundwater is of great significance in sustaining life on planet earth. The reliable estimation of groundwater recharge is the key understanding the groundwater reservoir and forecasting its potential accessibility. The main objective of this study was to assess the groundwater recharge and its controlling factors at the Ergene river catchment. A grid-based water balance model was adopted to determine the spatially distributed long-term groundwater recharge and other water budget components, relying upon the hydro-climatic variables, land-use, soil, geology, and relief of the investigated area. The model calculations were performed for the hydrological reference horizon of 20 years at a spatial resolution of 100 × 100 m. The base flow index (BFI) separation concept was applied to split up the simulated total runoff into groundwater recharge and direct runoff. Subsequently, the statistical methods of Pearson product–moment correlation and principal component analysis (PCA) were combined for identifying the dominant catchment and meteorological factors influencing the recharge. The average groundwater recharge over the investigated area amounts to 95 mm/year. The model validation and statistical analysis indicate that the difference between simulated and observed total runoff and recharge values is generally under 20% and no significant inconsistency was observed. PCA indicated that recharge is controlled, in order of significance, by land-use, soil, and climate variables. The findings of this research highlight the key role of spatial variables in recharge determination. In addition, the generated outputs may contribute to groundwater resource management in the Ergene river catchment.

scholarly journals Estimating nutrient concentrations from catchment characteristics across the UK

2007 ◽  
Vol 11 (1) ◽  
pp. 550-558 ◽  
Author(s):  
H. Davies ◽  
C. Neal
Keyword(s):  
Water Framework Directive ◽  
Base Flow ◽  
Geographical Information ◽  
Nutrient Concentrations ◽  
Flow Index ◽  
Effective Rainfall ◽  
Rainfall Runoff ◽  
Catchment Characteristics ◽  
Land Use Types ◽  
The Uk

Abstract. Within a Geographical Information System (GIS) framework, the distributions of nitrate and orthophosphate concentrations at monitoring sites across the UK were examined and empirical relationships with catchment characteristics were established. The mean orthophosphate concentrations were linked strongly with the urban component, and less significantly with effective rainfall and agricultural coverage. This is of strategic importance in relation to phosphorus and the Water Framework Directive. Correspondingly, mean nitrate concentrations were linked to land-use types, base flow index and effective rainfall. Within-catchment residence times and effective-rainfall (runoff) were important in relation to nitrate. The issue of nitrate and the Water Framework Directive is more complex than that for orthophosphate and involves a strong agricultural as well as an urban component.

scholarly journals Which objective function to calibrate rainfall–runoff models for low-flow index simulations?

2017 ◽  
Vol 62 (7) ◽  
pp. 1149-1166 ◽  
Author(s):  
Florine Garcia ◽  
Nathalie Folton ◽  
Ludovic Oudin
Keyword(s):  
Objective Function ◽  
Low Flow ◽  
Flow Index ◽  
Rainfall Runoff ◽  
Low Flow Index

scholarly journals Continuous Modeling of the Mkurumudzi River Catchment in Kenya Using the HEC-HMS Conceptual Model: Calibration, Validation, Model Performance Evaluation and Sensitivity Analysis

Hydrology ◽  
2018 ◽  
Vol 5 (3) ◽  
pp. 44 ◽  
Author(s):  
Wendso Ouédraogo ◽  
James Raude ◽  
John Gathenya
Keyword(s):  
Sensitivity Analysis ◽  
Stream Flow ◽  
Model Performance ◽  
Base Flow ◽  
Low Flow ◽  
Coefficient Of Determination ◽  
Flow Index ◽  
Model Parameters ◽  
Time Step ◽  
Continuous Modeling

The Mkurumudzi River originates in the Shimba hills and runs through Kwale County on the Kenyan Coast. Study on this river has been informed by the many economic activities that the river supports, which include sugarcane plantations, mining, tourism and subsistence farming. The main objective of this study was to use the soil moisture accounting (SMA) model specified in the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) settings for the continuous modeling of stream flow in the Mkurumudzi catchment. Data from past years were compared with observed stream flow data in order to evaluate whether the model can be used for further prediction. The calibration was performed using data from 1988 to 1991 and validation for the period from 1992 to 1995 at a daily time step. The model performance was evaluated based on computed statistical parameters and visual checking of plotted hydrographs. For the calibration period of the continuous modeling, the performance of the model was very good, with a coefficient of determination R2 = 0.80, Nash-Sutcliffe Efficiency NSE = 0.80, index of agreement d = 0.94, and a Root Mean Squared Error (RMSE)/observations’ standard deviation ratio—RSR = 0.46. Similarly, the continuous model performance for the validation period was good, with R2 = 0.67, NSE = 0.65, RSR = 0.62 and d = 0.88. Based on these performance results, the SMA model in the HEC-HMS was found to give a satisfactory prediction of stream flow in the Mkurumudzi Catchment. The sensitivity analysis of the model parameters was performed, and the different parameters were ranked according to their sensitivity in terms of percent change in simulated runoff volume, peaks, Nash-Efficiency, seven-day low flow and base flow index. Sensitivity analysis helped to understand the relationships between the key model parameters and the variables.

Sign in / Sign up

Export Citation Format

Share Document