Hydrological Modelling in Arid and Semi-Arid Areas (International Hydrology Series)
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In order to measure the model performance, many researchers have used a standard set of criteria comprising a combination of numerical measures and graphical plots.
Hydrological modelling of stream flows in the Rmel watershed using SWAT model
Different criteria assess the performance in different ways. The coefficient of efficiency Figure 2 E Bormann et al. As analyses are improved from basic hydrologic prediction to scenario-based studies, Bormann et al. The performance of several well-known models in the estimation of runoff is described in Table 3 , whilst a graphical representation is given in Figure 2. The present review is concerned with the modeling approaches to assess the impact of land use changes on hydrologic response at catchment scale and also discusses the importance of scenario-based studies.
In addition, a brief description about model comparison in order to identify uncertainties is also provided. From the literature, it is clear that human activities are the major drivers leading to dynamic changes in land use and climate, which in turn makes it very difficult to fully understand the hydrologic response, since the hydrologic components are distributed heterogeneously.
In order to model the complex system many models have been developed which range from lumped conceptual models all the way to physically based distributed models. Among them, the physically based models are capable of representing the physical characteristics of watershed in an explicit way. In contrast, the semi-distributed and fully-distributed models are efficient in representing the spatial heterogeneity of the watershed. Most of the studies have evaluated the impact of land use change by considering catchments in a single climatic condition.
However, it is equally important to analyze the variation in the hydrologic response in catchments with different land use characteristics and climatic conditions. Several studies revealed that the conversion of forest land to grass land or crop land leads to reduction in ET value and an associated increase in surface flow.
Recently, Legesse et al. The results of climate scenario study showed that the influence of climate variability is more significant when compared to land use change. These scenario-based studies do not try to project the real future changes, but are attempts to assess the implications of possible future changes. This shows that, more emphasis is necessary towards the development of models which can predict future changes in climate and land use pattern in more realistic manner. Lin et al. Since, LUCC models are reasonably good at forecasting the near-future changes in LULC pattern by considering drivers such as demographic, socio-economic, national policies, etc.
However, many researchers preferred scenario-based forecasting due to difficulties and uncertainties associated with downscaling techniques and representation of detailed spatial features in climate models. On the other hand, the integration of variety of models is an improvement over the use of single scenario. Also, the present study has reviewed the importance of comparison of models in identifying possible sources of uncertainties in hydrologic modeling.
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Based on the present review, it can be concluded that the variation between the simulating efficiency of the models can be attributed to uncertainty in the calibration strategy, model input and structure and parameterization. When the aim of the study is to tackle different aspects in single modeling framework, then it is more appropriate to integrate two or more models with different functionalities.
In the present review, an attempt has been made to understand the importance of hydrologic models in simulating hydrologic responses such as stream flow, ET, ground water flow, subsurface flow, etc. Based on this review, the following important points are highlighted: 1 The physically based semi-distributed and distributed hydrologic simulation models are more suitable for studying the effect of land use change, as land use pattern is heterogeneous in nature.
The integration of land use change models and climate change models GCM and RCM with hydrologic models can improve the efficiency of predicting the hydrologic response. Since, these models are capable of providing more realistic forecasts. All the models are associated with uncertainties; therefore, the comparison of models based on the evaluation criterion can help in identifying the uncertainties. The accurate estimation of model parameters plays critical role by influencing the accuracy of model prediction.
To date, studies have been conducted to know the hydrologic changes in single hydroclimatic condition; very few studies have been carried out related to comparative evaluation in different hydroclimatic conditions. Therefore, it is equally important to analyze the variation in the hydrologic response in catchments with different land use characteristics and climatic conditions.
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Cite this article as:. Article Figures and tables References.
Abstract Abstract Hydrologic modeling plays a very important role in assessing the seasonal water availability, which is necessary to take decisions in water resources management. Public Interest Statement The conservation of land and water resources is significant for the sustainable development of mankind. Introduction Water is one of the essential components of the environment and requires proper planning and management to achieve its sustainable utilization. Table 1.
Scenario-based simulation of hydrological response in a catchment It is of interest to simulate the effect of possible changes in climate variables and land use that may occur in the near-future by considering scenario conditions. Table 2.
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Author s name Scenario details 1 Thanapakpawin et al. Model comparison and performance evaluation The comparison of models enables the identification of possible sources of uncertainty in hydrologic modeling and acts as valuable basis for the investigation of the effects of different model structures on model prediction Cornelissen et al.
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Table 3. The performance of different models in estimating the runoff Serial No. Discussion The present review is concerned with the modeling approaches to assess the impact of land use changes on hydrologic response at catchment scale and also discusses the importance of scenario-based studies. Conclusions In the present review, an attempt has been made to understand the importance of hydrologic models in simulating hydrologic responses such as stream flow, ET, ground water flow, subsurface flow, etc.
UFZ - Publikationsverzeichnis - Helmholtz-Zentrum für Umweltforschung UFZ
Funding Funding. The authors received no direct funding for this research. References Abushandi, E. Water Resources Management , 27 , — SHE: Towards a methodology for physically-based distributed forecasting in hydrology. Journal of Applied Remote Sensing , 6 , 63— Uncertainty assessment through a precipitation dependent hydrologic uncertainty processor: An application to a small catchment in southern Italy.
Journal of Hydrology , , 38— Advances in Water Resources , 32 , — An evaluation of the impact of model structure on hydrological modelling uncertainty for streamflow simulation. Journal of Hydrology , , — Using artificial neural network approach for modelling rainfall—runoff due to typhoon. Journal of Earth System Science , , — The best relationship between lumped hydrograph parameters and urbanized factors. Natural Hazards , 56 , — Modeling the potential impacts of climate change on streamflow in agricultural watersheds of the Midwestern United States.