Licence Application Yield Assessment 1200 1000 800 600 400 200 - PowerPoint PPT Presentation

Kings Fleet & Falkenham IDB Abstraction Licence Application Yield Assessment 1200 1000 800 600 400 200 0 29/01/2016 00:00 03/02/2016 00:00 08/02/2016 00:00 13/02/2016 00:00 18/02/2016 00:00

Conjunctive use or Farm reservoir – yield Dependent Current Constraints Estimated average yield 1500- • 2000Ml. 600-800 Ml demand for irrigation • 1000Ml+ demand for P.W.S • 188 Ml currently licenced • Design year yield unknown • Lack of local reliable flow data • Currently two pumping stations • Kings fleet and Falkenham Possible to move water from Kings • Fleet to Falkenham Water Quality constraints • Freshwater flow to Estuary •

Assessing Yield Hydrological models Catchment Hydrology Available Methods include Low • Flows Enterprise; NEAC model ; Catchment comparison; Rainfall run off modelling . Catchmod Rainfall runoff • modelmost suited to this  application . Catchment divided into • hydrological zones. Water moves vertically through a • series of conceptual stores in each zone Inputs Potential Evaporation and • Rainfall 1970-2015. Calibrated with catchment • observed flow data

Kings Fleet – Falkenham model Build Inputs Potential Evaporation MORECS • weekly . 1970-2015 Rainfall Locally gauged • for Calibration – Levington for P.O.R. (inc other gauges for infilling). Flows – gauged at Falkenham and • kings fleet Pumps . Check with other gauges , Holesley, Brantham, Playford etc. Hydrological zones; superficial • Aquifer 35%, Alluvium 32%, London clay 25%, Hard surface rapid 8% Single unit calibration •

IDB Pump data Significant periodicity @ 24 hour • Kings fleet hourly Discharge 01/01/2016 to 11/03/2015 and 7 day – not hydrological – cost 1200 minimisation Series1 Correction required for calibration 168 per. Mov. Avg. (Series1) • 24 per. Mov. Avg. (Series1) . Maximum period of 7 day 1000 selected as filter . Model output's reported to 7 day • 800 rolling output . Uncertainty regarding the more • 600 rapid response functions of the catchment . 400 Local gauge and model checks • indicate good accuracy of gauged data (next slide) 200 0 01/01/2016 00:0006/01/2016 00:0011/01/2016 00:0016/01/2016 00:0021/01/2016 00:0026/01/2016 00:0031/01/2016 00:0005/02/2016 00:0010/02/2016 00:0015/02/2016 00:0020/02/2016 00:00

IDB Gauging Plausibility checks Kings Fleet & Falkenham IDB pumped cumulative runoff compared to L.F.E. Mean monthly runoff. Data shown for Time period September Early monitoring data Sep 2015 – • 2015 to March 2016 - 96 % L.T.A. Rainfall Mar 2016 run off compared to 120 450 gauge and existing steady state models . L.F.E gauged 400 L.T.A. Rainfall 2015/2016 Rainfall 100 Sep 2015 – Mar 2016 Rainfall 96 % • Series5 Poly. (L.F.E) 350 of L.T.A. Poly. (L.T.A. Rainfall) Poly. (2015/2016 Rainfall) 80 300 Sep 2015 – Mar 2016 Measured run • off 99 % L.T.A compared to L.F. E 250 runoff mm model . (95mm) 60 200 Very encouraging checks for • accurate metering . 40 150 100 20 50 0 0 15/07/2015 03/09/2015 23/10/2015 12/12/2015 31/01/2016 21/03/2016 10/05/2016

IDB Pump Totals 2015-2016 Cumulative Pumped Volume • Total Measured discharge 01/08/2015 to 2000000 31/06/2016. Approx. 1800000 Kings fleet Falkenham 2 Falkenham 1 2800000m3 1600000 1400000 • Runoff 57 % Kings fleet: 1200000 43% Falkenham CUBIC METRES 1000000 • Area 61% king fleet: 39% 800000 Falkenham 600000 • Rainfall Aug to June 114 400000 % L.T.A. 200000 0

Catchmod Rainfall runoff model Calibration Calibrate to individual • Contribution to Flows by Area (Kings fleet) hydrological zones . 0.30 0 20 Soil moisture profiles • 0.25 40 Flow statistics including flow • 60 duration curves . 0.20 80 Catchment yield. • Flow (cumecs) Rainfall (mm) 0.15 100 Total flow • 120 0.10 140 160 0.05 180 0.00 200 Observed Rainfall Simulated Area 1: Gravel crag Area 2: Alluvium Area 3: London clay Date Area 4: Urban 8 per. Mov. Avg. (Observed) 7 per. Mov. Avg. (Simulated)

Total flow Calibration 7 day rolling output to remove • Model Fit (Kings Fleet & Falkenham) periodicity. 1.00 0 0.90 20 Removes probable urban • peaks- attenuated by storage 0.80 40 0.70 60 Good calibration of observed • aquifer baseflow trends. 0.60 80 Flow (cumecs) Rainfall (mm) 0.50 100 Probable 10-15 % • underestimate of long term 0.40 120 average yield 0.30 140 Underestimate associated with 0.20 160 • run off from marsh area , too 0.10 180 high S.M.D. in shoulder months. 0.00 200 ? • Date Observed Rainfall Simulated Flow 7 per. Mov. Avg. (Observed ) 7 per. Mov. Avg. (Simulated Flow)

Catchmod calibration ‘v’ existing models. L..F E Good calibration of seasonal • Modelled Run off M3/s/km2 - L.F.E. and Catchmod runoff with steady state models . 0.007 0.007 Baseflow months Consistently • 0.007 10-15 % lower . Runoff 0.006 0.006 dominated months 10-15 5 0.005 0.005 0.005 higher. 0.005 0.005 0.005 Consistent with • 0.004 0.004 conceptualisation that L. f. E. 0.004 0.003 model overestimates baseflow 0.003 0.003 0.003 0.003 0.003 0.003 index @ 0.82 . 0.002 0.002 0.002 APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEB MAR Catchmod Low Flows Enterprise

Calibration flow Duration statistics Catchmod and L.F.E. Mean Daily flow Duration curves Good Calibration with • observed 0.400 Modelled and observed flow • Modelled 1973-2015 L.F.E 0.350 expected to exceed L.T.A. model calibration 7 day IDB gauged 7day Monitoring period generated • 0.300 significantly more run off than 0.250 Long term 1970-2014 modelled m3/sec 0.200 Long term modelled conforms • to conceptualisation of 0.150 greater runoff and lower baseflow relative to existing 0.100 model . 0.050 Catchmod Modelled mean • yield believed to be 10-15 % 0.000 0.000 10.000 20.000 30.000 40.000 50.000 60.000 70.000 80.000 90.000 100.000 below actual . Percentile

Catchmod Aquifer zone Calibration • Aquifer 35 % of total Catchmod Calibration - Aquifer flows and Observed groundwater hydrographs runoff. Major summer 9.9 component . Gravel sim flows elm cottage levels 0.140 • Longer term Calibration Mill lane Boyton 9.4 0.120 with local groundwater 8.9 levels , extends 0.100 modelled flow m3/sec calibration period Groundwater Level Maod 8.4 beyond flow monitoring 0.080 . 7.9 0.060 • Very good trend 7.4 calibration with Elm 0.040 6.9 Cottage Hollesley and mill Lane Boyton. 0.020 6.4 0.000 5.9 18/02/1982 11/08/1987 31/01/1993 24/07/1998 14/01/2004 06/07/2009 27/12/2014 18/06/2020 • Axis Title

Catchmod Final Calibration Kings Fleet modelled Total flow and Crag/gravel Baseflow Mean Daily flow data sets 1970- • 2015 ( calibrated to weekly) 1.000 Winter run off more significant than 0.900 • other models B.F.I. 0.62 ‘v’ 0.85 L.F.E 0.800 Vulnerability to dry winters • 0.700 Significant hard surface runoff • 0.600 component. m3/sec 0.500 Crag/gravel baseflow providing • 0.400 significant summer yield . Model believed to underestimate crag 0.300 flows in dry years . Q(bf) mean = 0.200 0.025m3/sec . Probable 0.030m3/sec 0.100 Calibration Mean run off - low • 0.000 01/05/1970 01/05/1971 01/05/1972 01/05/1973 01/05/1974 01/05/1975 01/05/1976 01/05/1977 01/05/1978 01/05/1979 01/05/1980 01/05/1981 01/05/1982 01/05/1983 01/05/1984 01/05/1985 01/05/1986 01/05/1987 01/05/1988 01/05/1989 01/05/1990 01/05/1991 01/05/1992 01/05/1993 01/05/1994 01/05/1995 01/05/1996 01/05/1997 01/05/1998 01/05/1999 01/05/2000 01/05/2001 01/05/2002 01/05/2003 01/05/2004 01/05/2005 01/05/2006 01/05/2007 01/05/2008 01/05/2009 01/05/2010 01/05/2011 01/05/2012 01/05/2013 01/05/2014 119mm, MORECS/HOST gridded 127mm (baseflow component)

• Highest 5141 Ml in 2000 • Lowest 661Ml in 1990 • Modelled mean yield • IDB estimated mean Design Year IDB pumped Catchment 1930 Ml yield 2000 Ml 1 9 7 0 2481 2551 1 9 7 1 1 9 7 2 978 1 9 7 3 866 IDB Estimated Mean yield Catchmod Mean Gross yield Modelled gross yield 2050 1 9 7 4 1 9 7 5 1365 IDB POTENTIAL GROSS YIELD KINGS FLEET & FALKENHAM 2354 1 9 7 6 1 9 7 7 1285 1909 1 9 7 8 1 9 7 9 1550 1 9 8 0 1591 1833 1 9 8 1 1 9 8 2 1447 1657 1 9 8 3 1 9 8 4 2199 1 9 8 5 1741 2053 1 9 8 6 1 9 8 7 4618 1902 1 9 8 8 1 9 8 9 1035 732 1 9 9 0 1 9 9 1 870 1 9 9 2 1191 2302 1 9 9 3 1 9 9 4 2542 1135 1 9 9 5 1 9 9 6 661 1013 1 9 9 7 1 9 9 8 1422 1 9 9 9 1563 5141 2 0 0 0 2 0 0 1 2793 2613 2 0 0 2 2 0 0 3 1112 1419 2 0 0 4 2 0 0 5 778 2 0 0 6 2253 2291 2 0 0 7 2 0 0 8 2747 1636 2 0 0 9 2 0 1 0 1623 2 0 1 1 803 2 0 1 2 3846 2 0 1 3 2620 3555 2 0 1 4 2 0 1 5 2524

Scheme Reliability Yield /Probability Curve - 1970-2015 Assuming Resource can be • 6000 fully optimised. Unrestricted Irrigation Only Scheme Multi use Scheme infrastructure capability 5000 Multi use Scheme – 2100 Ml- 65 • % chance of non-availability 4000 in any year. Potential yield Ml Irrigation Scheme – 800 Ml - 4 • 3000 % risk of non- availability. Irrigation Scheme – 600 Ml – • 2000 100 % reliable. Precautionary model • 1000 calibration Reasonable assumption to increase dry year yield by 10-15% 0 0.0 20.0 40.0 60.0 80.0 100.0 120.0 % Probability Of Available yield