# Qom--A New Hydroologic Prediction Model Enhanced with Multi-Objective Optimization
## 5 Experimentation
### Results After Choosing Solutions
\begin{table}
\begin{tabular}{l r r r r r} \hline \hline
**Problem Instance** & **Data Series** & **Time Period** & **\# Registries** & **NSE** & **PBIAS** \\ \hline \multirow{4}{*}{1 (Asua river)} & 1.1 CC \(\Delta_{t}\) = 24 h & 05-02-2007:10-08-2007 & 187 & 0.82 & 8.7\% \\  & 1.2 CV \(\Delta_{t}\) = 24 h & 06-06-2005:08-01-2007 & 582 & 0.56 & 9.4\% \\  & 1.3 CV \(\Delta_{t}\) = 24 h & 09-09-2007:11-4-2009 & 581 & 0.75 & 9.4\% \\  & 1.4 CV \(\Delta_{t}\) = 24 h & 08-06-2009:30-09-2009 & 115 & 0.82 & 18.0\% \\ \hline \multirow{4}{*}{2 (Artibai river)} & 2.1 CV \(\Delta_{t}\) = 10 min & 17-06-2002:31-12-2002 & 29,224 & 0.63 & 23.9\% \\  & 2.2 CV \(\Delta_{t}\) = 10 min & 01-02-2003:04-03-2003 & 4588 & 0.68 & 0.5\% \\  & 2.3 CV \(\Delta_{t}\) = 10 min & 01-04-2003:08-01-2004 & 40,747 & 0.53 & 12.8\% \\  & 2.4 CC \(\Delta_{t}\) = 10 min & 17-06-2002:21-06-2002 & 637 & 0.85 & 22.3\% \\ \hline \multirow{4}{*}{3 (San Antonio, Loop 410)} & 3.1 CC \(\Delta_{t}\) = 15 m & 15-11-2010:21-12-2010 & 300 & 0.85 & 24.6\% \\  & 3.2 CV \(\Delta_{t}\) = 15 min & 17-11-2009:12-06-2012 & 94,315 & 0.43 & 0.5\% \\  & 3.3 CV \(\Delta_{t}\) = 15 min & 04-06-2013:24-03-2016 & 98,328 & 0.64 & 53.3\% \\ \hline \multirow{4}{*}{4 (San Antonio, Goliad)} & 4.1 SC \(\Delta_{t}\) = 24 h & 15-10-1998:02-11-1998 & 19 & 0.85 & 4.3\% \\  & 4.2 SV \(\Delta_{t}\) = 24 h & 23-06-2002:31-08-2002 & 70 & 0.91 & 4.5\% \\  & 4.3 SV \(\Delta_{t}\) = 24 h & 09-03-2007:09-03-2007 & 18 & 0.84 & 6.2\% \\ \hline \multirow{4}{*}{5 (Juquia, 4F-018R)} & 5.1 CC \(\Delta_{t}\) = 1 h & 09-07-2005:09-07-2005 & 2,351 & 0.79 & 5.0\% \\  & 5.2 CV \(\Delta_{t}\) = 1 h & 17-10-2005:04-01-2006 & 1634 & 0.40 & 3.7\% \\ \cline{1-1}  & 5.3 CV \(\Delta_{t}\) = 15 min & 01-05-2013:13-06-2013 & 3987 & 0.10 & 6.6\% \\ \cline{1-1}  & 5.4 CV \(\Delta_{t}\) = 15 min & 11-08-2013:22-12-2013 & 17,551 & 0.60 & 1.05\% \\ \hline \multirow{4}{*}{6 (Bermejo river, Balapuca)} & 6.1 CC \(\Delta_{t}\) = 24 h & 01-12-1971:02-07-1972 & 214 & 0.89 & 1.3\% \\ \cline{1-1}  & 6.2 CV \(\Delta_{t}\) = 24 h & 02-07-1972:31-08-2015 & 15,766 & 0.26 & 1.9\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Objective values NSE and PBIAS of selected solutions according to each data series, time period, and registry. More in depth, when focusing on a specific solution for a river basin, a series of hydrologic results are extracted, which leads the expert to define a hydrology engineering project. An example of these values are shown in Tables 4 and 5, which include the specific mass balance obtained by Qom-Clark and estimated peak values with relative errors for problem instance 6.2 CV (Rio Bermejo, Argentina), and data period 1971 09:00 to 3 April 2014 09:00 step 24.0 h.  
From a visual perspective, it is possible to check the quality of the hydrographic models obtained by plotting the hyteographs, which represent the humidity losses (HL) and excesses (HE) values from input data, together with the hydrographs, with observed (QO) and estimated (QE) outputs. In this way, Figure 8 shows the resulting rainfall and streamflow by means of the hyteograph and hydrograph of the 1.1 CC (Asua river basin) calibration data series, where we can observe the high correspondence between water losses/excesses and the predicted series (estimated data), which indeed fits the curve of observed data. For validation data series 1.3 CV, a similar plot is made in Figure 9 to better show the precision in estimated streamflow (QE), so even for external data (not used in calibration) a high prediction can be reached with the proposed approach.