Sexualidad Infantil

3.4.1.1 Tile drainage and percolating flow simulation

MACRO was used to simulate tile drainage and percolating flow within the Wensum catchment. Figure 3-6 shows the hydrograph from the initial uncalibrated simulation.

Results showed estimation of the flow in periods of high flow. The largest over-estimation was observed from November 2006 to March 2007 (up to a factor of 2.1) whereas for the remainder of the period only a few peaks were over-estimated but to a lesser degree (up to a factor of 1.3). The simulated hydrograph had a smooth behaviour in periods of low flow compared to the observed data. The simulation suggested that most of the peaks in periods of high flow corresponded to drain and percolating flow. Table 3-21 shows the simulated drain and percolating volume for each hydrological year and for the whole simulation period, together with observed and total simulated volume from MACRO at the catchment outlet. Similar proportions for drain flow and percolating volumes were simulated between years but percolation was simulated in larger amounts for all periods, ranging between 54.2 and 64.0% year of the total flow from MACRO. The simulated flow between 2006 and 2011 from MACRO accounted for 85.9% of the total observed volume;

however, the model matched observed volume in 2006-2007, exceeding the observed volume by 0.6%.

Figure 3-6 Observed and simulated flow using MACRO.

Table 3-21 Observed water volume and simulated drainage, leaching volume from MACRO and including the runoff from the development areas (MACRO + Urban runoff) together with the estimated runoff from the development areas (Urban runoff) and its percentage simulated from the observed volume from each hydrological year.

Hydrological

3.4.1.2 Runoff from developed areas

Runoff coming from developed areas (urban runoff) was calculated and added to the simulation from MACRO. The resulting hydrograph is compared to the initial simulation and the observed flow in Figure 3-7. The runoff added a large number of small peaks to the hydrograph particularly during low flow periods in contrast to the smooth curve of the

increased for 2006, exceeding the observed flow by 7.2% (Table 3-21). To this point, without including other sources of surface runoff, the simulation accounted for 91.0% of the observed flow. The missing simulated flow compared to the observed data between 2007 and 2011 varied between hydrological years from 4.0% (2007-2008) to 27.8% (2008-2009).

Figure 3-7 Observed and simulated flow from MACRO with (MACRO + Urban runoff) and without (MACRO) the runoff from development areas.

3.4.1.3 Groundwater mixing model simulation

The effect of adding the groundwater mixing (GW) model to the simulation is presented in Figure 3-8; a closer behaviour to a typical hydrograph including baseflow was observed particularly at the beginning of the low flow periods. However, at the end of these periods the flow took a longer time to recover which suggests delays to the normal wetting up of the soil. Instead of the symmetric shape in the hydrograph during low flow periods, a more asymmetrical shape was observed characterized by a gradual decrease in the curve flow until reaching a minimum value and then followed by an under-estimate of flow at the beginning of high flow periods. The GW model also had a varied effect on the total simulated volume for the hydrological years (Table 3-22); the simulated volume in

2006-0 5 10 15 20 25 30 35 40

Water flow (m3/s)

Date

MACRO + Urban runoff MACRO

Observed flow

2007, 2009-2010 and for the overall simulation period (2006 – 2011) was reduced while for the rest of the hydrological years an increased volume was observed. Over-estimation for 2006-2007 decreased from 7.2 to 1.9% compared to the observed volume. The simulated volume for the period 2006 – 2011 was 89.5% of the observed volume.

Figure 3-8 Comparison of the simulation from MACRO with (MACRO + urban runoff + GW) and without (MACRO + urban runoff) the groundwater mix model together with the observed flow.

Table 3-22 Observed water volume and that simulated from MACRO including the runoff from the development areas (MACRO + urban runoff) together with the simulation including the volume from the GW model and its percentage simulated from the observed volume from each hydrological year

Figure 3-9 shows the effect of the GW model on the model residuals. The residuals for the initial simulation exhibited a sinusoidal pattern with large positive and negative values due to under-estimation of the flow at the end of low flow periods and over-estimation during periods of great flow, respectively. The GW model showed a great reduction in the magnitude of negative residuals as well as for some large positive ones. However, the large negative values were still observed in 2006-2007. A non-random behaviour in the residuals was also observed for the simulation including the GW model but with a different pattern;

the residuals tended to behave with a “U-shape” for each hydrological year due to the sustained under-estimation of flow at the beginning of the winter.

Figure 3-9 Comparison of the residuals from the simulations with and without the GW model.

The Nash-Sutcliffe model efficiency coefficients (E) were calculated for individual hydrological years, for the overall simulation (2006 – 2011), and for high (1 November – 30 April) and low flow periods (1 May – 31 October) for both simulations: with and without the GW model (Table 3-23). The simulation without the GW model showed negative values of model efficiency for most of the hydrological years as well as for low and high flow periods. The exceptions were for the hydrological years 2007-2008 and 2009-2010 and for the high flow period 2007-2008 were positive but small values were observed. The use of the GW model greatly improved the simulation; positive values were achieved for the entire

-25 -20 -15 -10 -5 0 5 10 15 20 25

Residual (m3/s)

Date

without GW with GW

simulation period (E = 0.35) and for all the hydrological years varying between 0.04 (in 2006-2007) and 0.64 (in 2009-2010). The best model efficiencies were obtained for 2007-2008 and 2009-2010 (E = 0.61 and 0.64, respectively). The worst model efficiency was obtained for 2006-2007 due to the over-estimation of the flow. Negative efficiency values were obtained for some high and low flow periods but positive values were achieved for both overall simulations (E = 0.11 and 0.20, respectively). Better results were generally obtained for high than for low flow periods; apart from 2008-2009. The best model efficiency in the simulation was obtained for the high flow period in 2007-2008 (E = 0.73).

Table 3-23 Nash-Sutcliffe model efficiency coefficients for the simulated flow with and without the GW model for each hydrological year as well as for the high and low flow periods.

Simulation without the GW model Simulation with the GW model Hydrological