IDENTIFYING SUITABLE LOCATIONS FOR MANGROVE PLANTATION USING GEOSPATIAL INFORMATION SYSTEM AND REMOTE SENSING

We developed three deep learning models (CNN, LSTM, and combined CN-LSTM networks) to predict breakup ice-jam events to be used as an early warning system of possible flooding in rivers. In the models, we used hydro-meteorological data associated with breakup ice jams. The models show excellent performance, and the main finding is that the CN-LSTM model is superior to the CNN-only and LSTM-only networks in both training and generalization accuracy.

This paper uses the Budyko method to investigate mean annual streamflow changes, due to climate variation and human influence, in the important Karkheh River Basin in western Iran. The results show that the observed streamflow decrease in the Karkheh River is associated with both climate variation and human influence. The combination of increased irrigated area, reduction of forests and decreasing annual precipitation has significantly reduced streamflow in the basin.