Predictive uncertainty in hydrological modelling is quantified by using post-processing or Bayesian-based methods. The former methods are not straightforward and the latter ones distribution-free (i.e. assumptions on probability distribution of model's output necessary). To alleviate possible limitations related to these specific attributes, this work we propose calibration model quantile loss ...

In this paper, the modeling is based on division of the catchment into a grid mesh. Each cell has a unique response function independent of the functioning of other cells Summation of the flow responses from the cells, result the flow hydrograph from this area basin.A method is presented to simulation the flow hydrograph within a river basin using the hydrological model WetSpa. WetSpa is a GIS-b...

Aims: This paper is aimed to assess the future impact of climate change on some selected climatic variables and surface runoff from Myponga catchment, South Australia.
 Methodology: The six global models recommended for Australia were compared among each other based their performance simulate observed climates in study area. monthly average statistically downscaled evapotranspiration rainf...

An operational hydrological ensemble forecasting system based on a meteorological ensemble prediction system (M-EPS) coupled with a hydrological model searches to capture the uncertainties associated with the meteorological prediction to better predict river flows. However, the structure of the hydrological model is also an important source of uncertainty that has to be taken into account. This...

Mangrove restoration projects, aimed at restoring important values of mangrove forests after degradation, often fail because hydrological conditions are disregarded. We present a simple, but robust methodology to determine hydrological suitability for mangrove species, which can guide restoration practice. In 15 natural and 8 disturbed sites (i.e. disused shrimp ponds) in three case study regio...

In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal...

Rapid advancements in Earth-observing sensor systems have led to the generation of large amounts of remote sensing data that can be used for the dynamic monitoring and analysis of hydrological disasters. The management and analysis of these data could take advantage of distributed information infrastructure technologies such as Web service and Sensor Web technologies, which have shown great pot...

It is essential to consider the acceptable threshold in the assessment of a hydrological model because of the scarcity of research in the hydrology community and errors do not necessarily cause risk. Two forecast errors, including rainfall forecast error and peak flood forecast error, have been studied based on the reliability theory. The first order second moment (FOSM) and bound methods are u...