NS Coefficient is a fitness statistic that is used extensively in hydrology, but it is a generic statistic like R2 to test goodness of fitness of data in other disciplines. There are some applications in Ecology, forestry, sustainable development, etc. 

Hello Sourav,

Why not? The Nash-Sutcliff index can be used to evaluate the model performance (with continuous ordinates). See the attached links.

It's better to provide more information about the nature of your model outputs.

https://www.researchgate.net/post/what_is_the_best_metric_to_evaluate_the_quality_of_a_prediction

https://www.researchgate.net/post/How_to_compare_Hydrological_Model_Results

Sure, It can. It shows the percentage of the variability represented by the model. 100% means perfect model. 0% means the model always returns the mean value. A minus NS shows the model is worse than a model only returning mean value.

Thanks everyone for your quick responses.

Dr. Raoof

I am trying to predict structural response parameters of RC buildings.

Thank you.

Yes!!

NSE is to check the performance of model so we can compare the result of any other model rather than the hydrological model. I appreciate the other comments for sharing the papers in which NSE ha been used. 

We have been using NS coefficient as a representative of goodness-of-fit in simulations of breakthrough curves which are in some ways similar to hydrographs within hydrology context. Its performance is quite good for this purpose. However, for other types of observations curves such as particle size evolution, I have found when the distances between observation data and the horizontal axis are totally small, the performance of NS determination coefficient decreases. This is because even though the two curves (observation and model outputs) match, NS coefficient does not give a value near one which we expect from it.