S/N Statistical Measures FORMULA References 1. Root Mean Squared Error $RMSE={\left[\sum _{i=1}^{N}\frac{1}{N}{\left(M{R}_{exp,i}-M{R}_{pre,i}\right)}^{2}\right]}^{\frac{1}{2}}$ [19] 2. Mean Bias Error $MBE=\frac{1}{N}\sum _{i=1}^{N}\left(M{R}_{pre,i}-M{R}_{exp,i}\right)$ [107] 3. Chi Squared or Reduced Chi Squared ${x}^{2}={\sum _{i=1}^{n}\frac{\left(M{R}_{exp,i}-M{R}_{pre,i}\right)}{N-n}}^{2}$ [19] 4. Mean Relative Deviation Modulus $P\left(%\right)=\frac{100}{N}\sum _{i=1}^{N}|\frac{M{R}_{Qi}-M{R}_{ei}}{M{R}_{ei}}|$ [108] 5. Coefficient of Determination ${R}^{2}=1-\frac{\sum _{i=1}^{n}{\left(M{R}_{exp,i}{}_{i}-M{R}_{pre,i}\right)}^{2}}{\sum _{i=1}^{n}{\left(M{R}_{exp,i}-M{R}_{pre,i}\right)}^{2}}$ [29] 6. Sum Square Error $SSE=\frac{1}{N}\sum _{i=1}^{N}{\left(M{R}_{exp,i}-M{R}_{pre,i}\right)}^{2}$ [109] 7. Modelling Efficiency $EF=\frac{\sum _{i=1}^{N}{\left(M{R}_{i,\mathrm{exp}}-M{R}_{i,ex{p}_{mean}}\right)}^{2}-\sum _{i=1}^{N}{\left(M{R}_{i,pre}-M{R}_{i,exp}\right)}^{2}}{\sum _{i=1}^{N}{\left(M{R}_{i,exp}-M{R}_{i,ex{p}_{mean}}\right)}^{2}}$ [90] 8. Correlation coefficient $r=\frac{N\sum _{i=1}^{N}M{R}_{pre,i}M{R}_{exp,i}-\sum _{i=1}^{N}M{R}_{pre,i}\sum _{i=1}^{N}M{R}_{exp,i}}{\sqrt{\left(N\sum _{i=1}^{N}M{R}_{pre,i}^{2}-{\left(\sum _{i=1}^{N}M{R}_{pre,i}\right)}^{2}\right)\left(N\sum _{i=1}^{N}M{R}_{exp,i}^{2}-{\left(\sum _{i=1}^{N}M{R}_{exp,i}\right)}^{2}\right)}}$ [16] 9. Mean Relative Deviation $E\left(%\right)=\frac{100}{N}\sum _{i=1}^{N}|\frac{\text{Experimentalvalue}-\text{Predictedvalue}}{\text{Experimentalvalue}}|$ [43] 10. Residual Sum of Squares $RSS=\sum _{i=1}^{N}{\left(M{R}_{exp,i}-M{R}_{pred,i}\right)}^{2}$ [85]