2c:null 2d:["$","title",null,{"children":"Recent Years Hydrology and Power & Energy | Western Power | Observable"}] 32:T41a,

The Ngonye Falls Hydroelectric Project is a 180MW run-of-river electricity generation project on the Zambezi River in western Zambia currently under development by Western Power Company.

The energy generation potential of the Ngonye Falls project depends on the hydrology of the Zambezi River at the project location. An analysis of historic Zambezi River hydrology was completed by Mott MacDonald in 2018, using data provided by the Zambezi River Authority, in the feasibility study report for the project: Ngonye Falls Hydropower Project - 2018 Feasibility Study Update - Final Report (Version D) June 2019.

This feasibility study report also presented the results of capacity optimisation and power and energy modelling based on the proposed power station design. Western Power have subsequently prepared a power and energy model for the project which provides consistent results to the Mott MacDonald model.

33:T65a,{ var from = 2010 //var flow_years=hydrologyYearly.filter(v=>v.waterYear>=from) var energy_years=energyYearly.filter(v=>v.waterYear>=from) var data = [{ y: energy_years.map(yr=>yr.riverVolumePctVariation), x: energy_years.map(yr=>yr.waterYear), text: energy_years.map(yr=>d3.format('.0%')(yr.riverVolumePctVariation)), showlegend:true, name: 'Annual volume', hoverinfo:'x+text', textposition:'auto', marker: {color: energy_years.map(yr=>yr.waterYear>2016?colr_b(1,0.7):colr_b(1,0.3))}, type: 'bar' }, { y: energy_years.map(yr=>yr.energyPctVariation), x: energy_years.map(yr=>yr.waterYear), text: energy_years.map(yr=>d3.format('.0%')(yr.energyPctVariation)), showlegend:true, name: 'Annual energy', hoverinfo:'x+text', textposition:'outside', textfont:{color: colr(1)}, marker: {color: energy_years.map(yr=>yr.WaterYear>2016?colr(1,0.7):colr(1,0.3))}, type: 'bar' } ]; var layout = { width: width>800?770:width-30, height:300, font: font, showlegend: true, margin: {t:5,b:40,l:70,r:5}, legend: {orientation: 'v', x: 0, xanchor: 'left', y: 0}, xaxis: { showgrid: true, zeroline: false, dtick:1, ticks:'outside', range:[from-0.5,2023.5], }, yaxis: { title: '', showgrid: false, zeroline: true, tickformat: ',.0%', showline: false }, }; const div=container('Fig 3. Percentage variation from the long term average of annual volume and annual energy 2010 to date.') plt.newPlot(div, data, layout, {displayModeBar: false}); return div }34:T4f9,{ var flow_years=hydrologyYearly.filter(v=>v.waterYear>2016) var data = [{ y: flowAnnualExceedance2024.map(f=>f.flowMean), x: flowAnnualExceedance2024.map(f=>f.exceedance), mode: 'lines', hoverinfo:'none', line: {shape: 'spline', color: colr_b(1)}, type: 'scatter' }]; data.push({ y: flow_years.map(f=>f.flowMean), text: flow_years.map(f=>f.waterYear), x: flow_years.map(f=>f.flowMeanExceedance), hoverinfo:'x+y', mode: 'markers+text', textposition:['bottom','bottom','top', 'bottom','bottom','top'], marker: {color: colr_b(5), size: 8}, type: 'scatter' }) var layout = { height: 250, width: width>800?770:width-30, font: font, showlegend: false, margin: {t:5,b:50,l:70,r:5}, xaxis: { showgrid: true, zeroline: false, tickformat: ',.0%', ticks:'outside', dtick:0.1, title:'Exceedance' }, yaxis: { title: 'Mean Annual Flow (m\u00B3/s)', tickformat: ',.0f', zeroline: false, showline: false, separatethousands:true, } } const div=container('Fig 4. Seven most recent water years plotted on the mean annual flow exceedance curve.') plt.newPlot(div, data, layout,{displayModeBar: false}) return div }35:T500,{ var energy_years=energyYearly.filter(v=>v.waterYear>2016) var data = [ { y: energyAnnualExceedances.map(f => d3.format(',.0f')(f.energy)), x: energyAnnualExceedances.map(f => f.exceedance), mode: 'lines', hoverinfo:'none', line: {shape: 'spline', color: colr(1)}, type: 'scatter' }] data.push({ y: energy_years.map(f=>f.energy), text: energy_years.map(f=>f.waterYear), x: energy_years.map(f=>f.energyExceedance), hoverinfo:'x+y', mode: 'markers+text', textposition:['top ','top right','top', 'top','bottom'], marker: {color: colr_b(5), size: 8}, type: 'scatter' }) var layout = { height: 250, width: width>800?770:width-30, font: font, showlegend: false, margin: {t:5,b:50,l:70,r:5}, xaxis: { showgrid: true, zeroline: false, tickformat: ',.0%', ticks:'outside', dtick:0.1, title:'Exceedance' }, yaxis: { title: 'Energy (GWh)', zeroline: false, showline: false,tickformat: ',.0f', separatethousands: true } }; const div = container('Fig 5. Energy production from the last seven water years plotted on the long term energy exceedance curve.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }36:T4ab,fdcChart=function(xRange, cap){ function slic(dat){ return dat.filter(v=>v.exceedance>xRange[0]).filter(v=>v.exceedanceMath.round(f.flow)), x: slic(fdc2016).map(f=>f.exceedance), mode: 'lines', name: '1924 to 2017', line: {shape: 'spline', color: colr_b(1)}, type: 'scatter' },{ y: slic(fdc2024).map(f=>Math.round(f.flow)), x: slic(fdc2024).map(f=>f.exceedance), mode: 'lines', name: '1924 to 2024', line: {shape: 'spline', color: colr_b(7), dash:'dash'}, type: 'scatter' } ]; var layout = { height: 220, width: width>800?770:width-30, font: font, showlegend: true, legend: {orientation: 'v', x: 1, xanchor: 'right', y: 1}, margin: {t:5,b:cap?50:30,l:70,r:5}, xaxis: { showgrid: true, zeroline: false, tickformat: ',.0%', ticks:'outside', title:cap?'Exceedance':'' }, yaxis: { title: 'Flow (m\u00B3/s)', zeroline: false, showline: false, separatethousands:true, } }; const div=container(cap) plt.newPlot(div, data, layout,{displayModeBar: false}); return div }37:T7be, function yearVariation(year, showLegend = false) { var months_energy = energyMonthly.filter(v=>v.waterYear==year) var months_flow = hydrologyMonthly.filter(v=>v.waterYear==year) var varEnergy = months_energy.map((d, i) => (d.energy-energyCalmonthly[i].energyMean)/energyCalmonthly[i].energyMean) var varFlow = months_flow.map((d, i) => (d.flowMean-hydrologyCalmonthly[i].flowMean)/hydrologyCalmonthly[i].flowMean) var varHead = months_energy.map((d, i) => (d.HeadTurbine1-energyCalmonthly[i].HeadTurbine1_mean)/energyCalmonthly[i].HeadTurbine1_mean) var data = [] data.push({ y: varEnergy, text: varEnergy.map(v=>d3.format('.0%')(v)), x: months_energy.map(d => (d.waterMonth)), showlegend:showLegend, hoverinfo:'name+text', type:'bar',name: 'Energy', marker: {color: colr(2,0.4)}, },{ y: varFlow, text: varFlow.map(v=>d3.format('.0%')(v)), x: months_flow.map(d => (d.waterMonth)), showlegend:showLegend, hoverinfo:'name+text', type:'bar',name: 'Flow', marker: {color: colr_b(2,0.4)}, },{ y: varHead, text: varHead.map(v=>d3.format('.0%')(v)), x: months_energy.map(d => (d.waterMonth)), showlegend:showLegend, hoverinfo:'name+text', type:'bar',name: 'Head', marker: {color: '#AAA'}, }) var layout = { height: 220, font: font, showlegend: showLegend, margin: {t:5,b:40,l:70,r:50}, legend: {orientation: 'h', x: 0, xanchor: 'left', y: 0.2}, xaxis: { showgrid: false, zeroline: false, ticks:'outside', range: [0.5, 12.5], tickvals:[1,2,3,4,5,6,7,8,9,10,11,12], ticktext:['Oct','Nov','Dec','Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep'] }, yaxis: { title: 'Variation',showgrid: false, zeroline: true, tickformat: ',.0%', showline: false, range:[-0.7,0.9] } }; const plDiv=DOM.element('div') plt.newPlot(plDiv, data, layout, {responsive: true, displayModeBar: false}); return plDiv } 38:T85f,function annualChart (series, parm, label, unit, yRange, cols) { let per1 = series.filter(yr=>yr.waterYear<2017) let per2 = series.filter(yr=>yr.waterYear>2016) let mean = d3.mean(series.map(yr=>yr[parm])) let per1_mean = d3.mean(per1.map(yr=>yr[parm])) let per2_mean = d3.mean(per2.map(yr=>yr[parm])) let movingAv = movingAverage(series.map(yr=>yr[parm]), 20) let sd = d3.deviation(per1.map(yr=>yr[parm])) var data = [{ y: per1.map(yr=>yr[parm]), x: per1.map(yr=>yr.waterYear), text: per1.map(yr=>d3.format('.0f')(yr[parm]) + unit), showlegend:false, name: '', hoverinfo:'x+text', marker: {color: cols(1,0.3)}, type: 'bar' },{ y: per2.map(yr=>yr[parm]), x: per2.map(yr=>yr.waterYear), text: per2.map(yr=>d3.format('.0f')(yr[parm]) + unit), showlegend:false, name: '', hoverinfo:'x+text', marker: {color: cols(1,0.8)}, type: 'bar' },{ y: movingAv, x: series.map(yr=>yr.waterYear), name:'20yr Moving Average', mode: 'lines', hoverinfo:'none', line: {width:2,color: cols(4,0.7)}, type: 'scatter' },{ x: [1924, 2017], y: [per1_mean, per1_mean], mode: 'lines', line: {color: 'rgba(0,0,0,0.8)', width:1, dash:'dashdot'}, type: 'scatter', hoverinfo:'none', name: '1924-2017 Mean ' + d3.format(',.1f')(per1_mean) + unit },{ x: [2017, 2022], y: [per2_mean, per2_mean], mode: 'lines', line: {color: 'rgba(0,0,0,0.8)', width:2, dash:'dashdot'}, type: 'scatter', hoverinfo:'none', name: '2017-2024 Mean ' + d3.format(',.1f')(per2_mean) + unit }]; var layout = { width: width-50, height:300, font: font, showlegend: true, margin: {t:5,b:40,l:70,r:5}, legend: {orientation: 'h', x: 0, xanchor: 'left', y: -0.1}, xaxis: { showgrid: false, zeroline: false, ticks:'outside', range:[1923,2024]}, yaxis: { title: label + ' ' + unit,range: yRange, zeroline: false, tickformat: ',.0f', showline: false}, }; const div=DOM.element('div') plt.newPlot(div, data, layout, {displayModeBar: false}); return div }39:T4c7,function yearDetail(year, captionText, legend) { let energy = energyYearly.filter(v=>v.waterYear==year)[0] let flow = hydrologyYearly.filter(v=>v.waterYear==year)[0] const div = html`

${year}

Mean flow: ${d3.format(',.0f')(flow.flowMean) + cumec}, ${(flow.flowMean - flow_mean)>0?'+':''}${d3.format(',.0%')((flow.flowMean - flow_mean)/flow_mean)} of longterm mean
Energy: ${d3.format(',.0f')(energy.energy)}GWh, ${(energy.energy - model2024.energyAnnualMean)>0?'+':''}${d3.format(',.0%')((energy.energy - model2024.energyAnnualMean)/model2024.energyAnnualMean)} of longterm mean

${yearVariation(year, legend)}

${yearFlowEnergy(year, legend)}

` if (captionText) { const caption=DOM.element('figcaption') caption.setAttribute("style","max-width:100%") caption.append(captionText) div.append(caption) } return div }3a:T8ec,function yearFlowEnergy(year, showLegend = false) { var months = energyMonthly.filter(v=>v.waterYear==year) var months_flow = hydrologyMonthly.filter(v=>v.waterYear==year) var data = [] data.push({ y: months.map(d => d.energy/1000), text: months.map(d => d3.format(',.0f')(d.energy/1000) + 'GWh'), x: months.map(d => (d.waterMonth)), yaxis: 'y2', name:year + ' Energy', showlegend:showLegend, hoverinfo:'text', type:'bar', marker: {color: colr(2,0.3)}, }) let hydrologyWeeks = hydrologyWeekly.filter(d=>d.waterYear===year) data = data.concat( { y: hydrologyWeeks.map(d => d.flowMean), x: hydrologyWeeks.map(d => ((d.waterWeek-1)/52*11)+1), showlegend:true, hoverinfo:'none', name: year + ' flow', mode:'lines', line: {shape:'spline', color: colr_b(1,0.8), width: 4} } ) data.push({ y: hydrologyCalmonthly.map(d => d.flowMean), x: hydrologyCalmonthly.map(d => (d.waterMonth)), showlegend:showLegend, hoverinfo:'none',name: 'Av flow', mode:'lines', line: {shape:'spline', color: colr_b(1), width:2, dash:'dot'}, }) data.push({ y: energyCalmonthly.map(d => d.energyMean/1000), x: energyCalmonthly.map(d => (d.waterMonth)), yaxis: 'y2', showlegend:showLegend, hoverinfo:'none', type:'scatter',mode:'lines', name: 'Av energy', line: {shape:'hvh', color: colr(1), width:2, dash:'dot'}, }) var layout = { height: 300, font: font, showlegend: showLegend, margin: {t:5,b:40,l:70,r:50}, legend: {orientation: 'v', x: -0.15, xanchor: 'left', y: 1.05}, xaxis: { showgrid: false, zeroline: false, ticks:'outside', range: [0.5, 12.5], tickvals:[1,2,3,4,5,6,7,8,9,10,11,12], ticktext:['Oct','Nov','Dec','Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep'] }, yaxis: { title: 'Flow ' + cumec,showgrid: false, zeroline: false, tickformat: ',.0f', showline: false }, yaxis2: { title:'Energy GWh', overlaying: 'y', showgrid: false, side: 'right',zeroline: false, tickformat: ',.0f', showline: false, range:[0,130] } }; const plDiv=DOM.element('div') plt.newPlot(plDiv, data, layout, {displayModeBar: false, responsive: true}); return plDiv } 3b:[] 30:{"id":"87d1c353630d46a5","slug":"recent-years-hydrology-and-power-energy-2024","title":"Recent Years Hydrology and Power & Energy","thumbnail":"5708c6f6e046995b9dca9e0e4fa6659cdcf030e41882f1309e991331eda68dea","access_level":"public","create_time":"$D2025-01-10T11:33:22.583Z","update_time":"$D2025-07-20T19:27:07.474Z","view_time":null,"first_public_time":"$D2025-01-10T14:34:26.842Z","fork":true,"stars":0,"starred":false,"owner":{"type":"team","id":"3aaf4970407a12be","login":"westernpower","name":"Western Power","avatar_url":"https://avatars-next.observableusercontent.com/0c11a3086911e8caa71a7767a24de09ff93d85f36798166fa6c2d0b61107b761","tier":"starter_2024"},"version":1515,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"96924893937b5930","login":"andyflem","name":"Andy Fleming","avatar_url":"https://avatars-next.observableusercontent.com/fd3844143a4c29872f0df28a8ebce77bb56cebf2fa74bb669872e4def82ad809","tier":null}],"members":[{"type":"individual","id":"96924893937b5930","login":"andyflem","name":"Andy Fleming","avatar_url":"https://avatars-next.observableusercontent.com/fd3844143a4c29872f0df28a8ebce77bb56cebf2fa74bb669872e4def82ad809","tier":null,"role":"editor"},{"type":"team","id":"3aaf4970407a12be","login":"westernpower","name":"Western Power","avatar_url":"https://avatars-next.observableusercontent.com/0c11a3086911e8caa71a7767a24de09ff93d85f36798166fa6c2d0b61107b761","tier":"starter_2024","role":"viewer"}],"comments":[],"custom_thumbnail":false,"trashed":false,"subscribed":null,"forks":0,"collection":{"id":"042ea7275c7e9c32","slug":"ngonye-falls","title":"Ngonye Falls","owner":{"id":"3aaf4970407a12be","login":"westernpower","name":"Western Power"}},"type":"notebook","body":{"title":"Recent Years Hydrology and Power & Energy","cells":[{"id":0,"value":"html`\n

Recent Years Hydrology and Power & Energy

Ngonye Falls Hydroelectric Project

\n
\n${book_index('recent-years-hydrology-and-power-energy-2024')}\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":895,"value":"$32","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":938,"value":"The current analysis uses 7 years of additional daily hydrology records up to 30th September 2024, the end of the 2023/24 water year and includes reanalysis of the hydrology and an extension of the power and energy model.","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":264,"value":"{\n const div=container('Fig 1. Total annual volume of water passing Ngonye Falls. New data 2017-2023 water years highlighted at far right.',width-10)\n div.prepend(annualChart(hydrologyYearly, 'volumekm3','Volume','km\\u00B3',[null,null], colr_b))\n return div\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":946,"value":"Fig 1. summarises the full 98 years of hydrology data from 1924 to 2023/24 on an annual, total volume basis. The 20 year moving average shows a cyclic pattern with a period of around 70 years. The average total volume for the original analysis period, 1924 to 2017 is shown separately from the 2017 to 2024 period average. Despite 2018 and 2023/24 being a drought years, the overall average for the seven most recent years is only very slightly lower (1.7%) than the long term average. ","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":290,"value":"{\n const div=container('Fig 2. Simulated total annual energy generation for the Ngonye Falls project for historic hydrology.',width-10)\n div.prepend(annualChart(energyYearly, 'energy','Energy','GWh',[0,1450],colr))\n return div\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":953,"value":"

\nFig 2. shows the results for power and energy modelling for the Ngonye Falls project over the full period of hydrology data. Because of the unique hydraulic characteristics for the project, where generation head is inversely proportional to flow (described in more detail here), the variation in annual energy generation is significantly less than the variation in total volume shown in Fig 1.

\nThe simulated average energy generation for the 1924-2017 period is 843GWh and despite the droughts in 2018/19 and 2023/24, the average energy production for the seven years from 2017 to 2024 is only 1.2% lower at 832.5GWh.

\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":581,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":760,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1089,"value":"Fig 4. shows that the five most recent water years included a significant variation in average hydrology ranging from very wet 2017 (P10) to the very dry year in 2018 (P96). 2021 was very close to average hydrology and 2019 and 2020 were relatively wet (P25).","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":828,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1094,"value":"Fig 5. shows the simulated energy output for the seven most recent year on an exceedance basis. Because of the unique hydraulic characteristics of the project the energy exceedance curve is very flat and the 2018 energy production of 727GWh (P95) is only 15% lower than the P50 annual energy. \n

\nFig 5.shows a consistent spread of energy outputs across the exceedance curve in the previous five years. There is no clustering of energy outputs that might indicate a shift in hydrology due to climate change or cyclic variability. \n

\nFig 4 and Fig 5. show how flood years with relatively high flows - eg 2017, P10 flow - do not produce the highest energy output - eg 2017, P55 energy - as very high flood flows lead to lower generation head and reduced power output. ","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":1104,"value":"

Annual Flow, Head and Energy

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":689,"value":"yearDetail(2017 ,'Fig 6a. 2017 was a wet year with flows 50% over average from Feb to July. However, these high flows led to low generation head and power and energy output was curtailed in Mar, Apr and May.',true)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":866,"value":"perf_2018=yearDetail(2018, 'Fig 6b. 2018 was a consistently very dry year (P96) leading to low energy output (P95).')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":868,"value":"perf_2019=yearDetail(2019, 'Fig 6c. 2019 was similar to 2017 with a relatively wet year (P23), although only from Mar onwards, leading to low head curtialment in Apr and May and reduced overall production (P70).')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":872,"value":"yearDetail(2020, 'Fig 6d. 2020 was a wet year early in the season but flows reverted close to the mean from Apr. Higher than average flows on the shoulders of the hydrograph, Jan and Jun/Jul produce over average energy production (P15).')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":874,"value":"yearDetail(2021, 'Fig 6e. 2021 was close to average hydrology but slightly reduced flows Jan to Mar and Jun led to higher than average head and power output.')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1284,"value":"yearDetail(2022, 'Fig 6f. 2022.')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1286,"value":"perf_2023=yearDetail(2023, 'Fig 6g. 2023.')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":367,"value":"

Flow Duration Curves

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":30,"value":"fdcChart([0,1])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":36,"value":"fdcChart([0.3,0.5], 'Fig 7. Flow duration curves for the period 1924 to 2017 - used in the Ngonye Falls power station feasibility study - and for 1924 to 2022, including the most recent five years.')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":55,"value":"{\n \n var data = [\n {\n y: fdcRelativeDiff.map(f=>f.relativeDifference),\n x: fdcRelativeDiff.map(f=>f.exceedance),\n mode: 'lines', \n line: {shape: 'spline', width:2,color: colr_b(5)},\n type: 'scatter'\n } \n ];\n \n var layout = {\n height: 230, width: width>800?770:width-30,\n font: font,\n showlegend: false,\n margin: {t:5,b:50,l:70,r:5}, \n xaxis: {\n showgrid: true,\n zeroline: false,\n tickformat: ',.0%',\n ticks:'outside',\n title:'Exceedance'\n },\n yaxis: {\n title: 'Relative difference',\n tickformat: ',.0%',\n zeroline: true,\n showline: false,\n separatethousands:true,\n }\n };\n \n const div=container('Fig 8. Relative difference between the previous 1924 - 2017 and extended to 2022 flow duration curves. Positive values mean flows are increased with the extended period.')\n plt.newPlot(div, data, layout,{displayModeBar: false});\n return div\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1185,"value":"The flow duration curves for the previous historic period and for the entire available data including the past five years show a very high degree of correlation. In the central section of the flow duration curve highlighted at the bottom of Fig 7 it can be seen that the latest five years of hydrology data has led to an increase in flows. In this central section flows have increased between 1% and 4%.","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":1202,"value":"

\n

Appendix

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":1360,"value":"

Charts

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":5,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":315,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":82,"value":"$38","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":683,"value":"$39","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":636,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1331,"value":"

P&E

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":486,"value":"energyCalmonthly = await d3.csv(peFolder2024 + peModel2024 + \"_pe_calmonthly.csv?\" + Math.floor(Math.random() * 1000),d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":433,"value":"energyMonthly = await d3.csv(peFolder2024 + peModel2024 + \"_pe_monthly.csv?\" + Math.floor(Math.random() * 1000),d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":830,"value":"energyAnnualExceedances = await d3.csv(peFolder2024 + peModel2024 + \"_pe_annualexceedances.csv?\" + Math.floor(Math.random() * 1000),d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":178,"value":"energyYearly = await d3.csv(peFolder2024 + peModel2024 + \"_pe_yearly.csv?\" + Math.floor(Math.random() * 1000),d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1440,"value":"model2024=models.find(md=>md.modelRef==peModel2024)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1445,"value":"model2016=models.find(md=>md.modelRef==peModel2016)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1433,"value":"models = (await d3.csv(server + '/ngonyePlantModels/models/modelStatistics.csv?' + Math.floor(Math.random() * 900),d3.autoType))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1325,"value":"

Hydrology

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":336,"value":"waterYears = [2017,2018,2019,2020,2021,2022,2023]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1311,"value":"flow_mean=d3.mean(hydrologyYearly,v=>v.flowMean)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1499,"value":"hydrologyYearly=hydrologyYearly_raw.map(v=>{\n v.volumekm3=v.volume/1000000\n return v\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":75,"value":"hydrologyYearly_raw = (await d3.csv(hydrologyFolder2024 + \"yearly.csv?\" + Math.floor(Math.random() * 10000),d3.autoType))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":653,"value":"hydrologyMonthly = (await d3.csv(hydrologyFolder2024 + \"monthly.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":374,"value":"hydrologyWeekly = (await d3.csv(hydrologyFolder2024 + \"weekly.csv?\" + Math.floor(Math.random() * 100),d3.autoType))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":399,"value":"hydrologyCalmonthly = (await d3.csv(hydrologyFolder2024 + 'calMonthly.csv?' + Math.floor(Math.random() * 1000),d3.autoType))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1396,"value":"

FDCs

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":1481,"value":"flowAnnualExceedance2024 = (await d3.csv(hydrologyFolder2024 + 'annualExceedance.csv?' + Math.floor(Math.random() * 1000),d3.autoType))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":51,"value":"fdcRelativeDiff=fdc2016.map((v,i)=>{\n return {\n exceedance: v.exceedance,\n difference: v.flow - fdc2024[i].flow,\n relativeDifference: d3.min([(fdc2024[i].flow - v.flow)/v.flow,0.05])\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":19,"value":"fdc2016 = (await d3.csv(hydrologyFolder2016 + 'fdc.csv?' + Math.floor(Math.random() * 1000),d3.autoType))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1265,"value":"fdc2024 = (await d3.csv(hydrologyFolder2024 + 'fdc.csv?' + Math.floor(Math.random() * 1000),d3.autoType))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1315,"value":"

Sources

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":167,"value":"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1273,"value":"baseFolder=\"https://gis.westernpower.org/data/output_data/2024/\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1365,"value":"

Sources

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":1378,"value":"peFolder2024 = `${server}/ngonyePlantModels/models/${peModel2024}/`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1375,"value":"peFolder2016 = `${server}/ngonyePlantModels/models/${peModel2016}/`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1419,"value":"peModel2024 = 'sh_2024_7.8mhead'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1421,"value":"peModel2016 = 'sh_2016_7.8mhead'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1371,"value":"hydrologyFolder2024 = `${server}/syntheticFlowSeries/2024/processed/`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1369,"value":"hydrologyFolder2016 = `${server}/syntheticFlowSeries/2016/processed/`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1363,"value":"server='https://data.westernpower.org'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1318,"value":"

Library

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":1052,"value":"function movingAverage(values, N) {\n let a = new Array(Math.floor((N-1)/2)).fill(NaN)\n let b = new Array(N-Math.round((N-1)/2)).fill(NaN)\n return a.concat(windows(values,N).map(v=>d3.mean(v))).concat(b);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1021,"value":"function windows(inputArray, size) {\n return Array.from(\n {length: inputArray.length - (size - 1)}, //get the appropriate length\n (_, index) => inputArray.slice(index, index+size) //create the windows\n )\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1023,"value":"function movingSD(values, N) {\n let a = new Array(Math.floor((N-1)/2)).fill(NaN)\n let b = new Array(N-Math.round((N-1)/2)).fill(NaN)\n return a.concat(windows(values,N).map(v=>d3.deviation(v))).concat(b);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":362,"value":"highlight='#d87d71'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":531,"value":"function colr_b(i = 1, a = 1) {\n return d3hsv.hsv(215, 1, ((6 - i + 1.5) * 15)/120, a).toString();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":128,"value":"expanding_mean = function(elems) {\n return elems.map((e,i) => {\n return d3.mean(elems.slice(-(elems.length-(i))))\n })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1230,"value":"import {book_index} from \"@westernpower/commonlibrary\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":17,"value":"import {plotTitle} from \"@andyflem/commonlibrary\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":15,"value":"import {margin} from \"@andyflem/commonlibrary\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":13,"value":"import {font} from \"@andyflem/commonlibrary\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":11,"value":"function colr(i = 1, a = 1) {\n return d3hsv.hsv(26, 0.85, ((6 - i + 1.5) * 15)/100, a).toString();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":229,"value":"import {format_flow} from \"@westernpower/commonlibrary\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":224,"value":"cumec=`m\\u00b3/s`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":222,"value":"container = function(captionText, width_over) {\n const div=DOM.element('div')\n div.setAttribute(\"class\",\"border m-2 p-2\")\n div.setAttribute(\"style\",`width: ${width_over?width_over:(width>800?800:width)}px`)\n if (captionText) {\n const caption=DOM.element('figcaption')\n caption.setAttribute(\"style\",\"max-width:100%\")\n caption.append(captionText)\n div.append(caption)\n }\n return div\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":220,"value":"make_trans=function(col,opacity) {\n let c=d3.color(col)\n c.opacity=opacity\n return c.formatRgb()\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":239,"value":"html`\n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":218,"value":"style=html`css `","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":516,"value":"d3hsv = require(\"d3-hsv@0.1\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":9,"value":"d3 = require(\"d3@5\",\"d3-hsv@0.1\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":7,"value":"plt = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"}],"files":"$W3b","stdlib":"1","titling":"auto"}} 31:"$30:body"