Time series of daily rainfall, river stage and groundwater levels obtained by a local community in Dangila woreda, northwest Ethiopia, have passed accepted quality control standards and have been statistically validated against formal sources.
The inputs to the ANN model consisted of weekly rainfall, evaporation, river stage, water level in the drain, pumping rate of the tubewells and groundwater levels in these wells at the previous time step.
We also removed the head variations caused by regional stimuli (e.g., rainfall and river stage) from the original head variations of all the wells to better characterize the local stimuli features (e.g., pumping and tide).
Starting in the mid-to-late 1990s, QPFs were used within hydrologic forecast models to simulate impact of rainfall on river stages.
In each permanent plot, we collected soil samples in winter (December March) to reduce temporal variation due to vegetation phenological stage and rainfall events.
The system uses a physics-based distributed (PBD) hydrologic model, Vflo, together with radar rainfall input to predict stage and discharge at 222 locations in real-time.
Nevertheless, in a natural ecosystem it is difficult to assess the effect of vegetation on the rhizosphere bacterial communities, especially in high mountain environments characterized by variable environmental parameters (successional stage, pH, rainfall, moisture, mineral composition, sampling season, and slope) within a size-limited area typical of early and transitional successional stages.
It formed on March 27 in the northern portion of the channel, and in its formative stages brought rainfall to coastal Mozambique.
Growth of the bog does not necessarily stop at this stage for, if rainfall is sufficient, the water-retaining properties of Sphagnum are sufficient to maintain a wet, stagnant environment above the original water table represented by the lake surface.
Most of the pollutant runoffs take place at the initial stage of the rainfall.
This section describes the training stage results of rainfall downscaling, using the MLP-based ANN on different model configurations as mentioned in Table 3.
