Drivers of Spatial and Temporal Variability of Streamflow in The

Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , 2 , G. W. P. Jewitt 1,3 8880 8879 , S. Uhlenbrook 1 2 cient of variation of annual flows in the range of 1 to 3.6. , I. Masih ffi 1,2 , and E. Riddell 1,3 In this study, long-term rainfall and streamflow records were analysed. Statistical This discussion paper is/has beenSciences under (HESS). review Please for refer the to journal the Hydrology corresponding and final Earth paper System in HESS if available. UNESCO-IHE, Institute for Water Education,Centre P.O. Box for 3015, Water 2601 Resources DA Research, Delft, School the of Netherlands Agriculture, Earth andDelft Environmental University of Technology, Department of Water Resources, P.O. Box 5048, Observed flow data fromtors of 33 Hydrologic gauges Alteration wasidentify (IHA) temporal/spatial screened variability approach. and and Long-term trends analyzed,ity in analyses streamflow using was were records. high, the conducted Temporal variabil- with to Indica- Significant the declining coe trends intified October at flows, and most low gaugingno flows stations trends indicators of were were the evident also Komati onmapped, iden- the and using other Crocodile parameters, GIS sub-catchments, including and however highsults were flows. suggest compared The that trends to land were historical use and and current flow regulation land are use. larger These drivers re- of temporal changes analysis, using annual anomalies, wasof conducted on 1950 20 to rainfall 2011. stations,at for The the annual Spearman period and Testconfirmed was monthly used to time to be scales. identifyfall high, The any data both trends variability revealed intra- in no of and the significant rainfall records trend inter-annually. across The of the increase statistical or basin analysis decrease was of for rain- the studied period. of these demands, relative tospite the being natural a flow relatively regime, appear well-gaugedits significant. basin spatial However, in and de- temporal South variability Africa,resulting are the in poorly natural a understood flow and limited regimedecisions. remain knowledge and Thus, poorly base there described, for is an waterderpinned opportunity resources by to planning a improve and water better management, management and scientific if variability understanding it in can of the be catchment. the un- drivers of streamflow availability The Incomati is avariability semi-arid of trans-boundary streamflow river and basinergy, competing in forestry water southern and demands industries. Africa, These from withsic sectors irrigated a human compete agriculture, high water with en- needs, environmental resulting flows in and a ba- “stressed” water resources system. The impacts Abstract Hydrol. Earth Syst. Sci. Discuss.,www.hydrol-earth-syst-sci-discuss.net/11/8879/2014/ 11, 8879–8921, 2014 doi:10.5194/hessd-11-8879-2014 © Author(s) 2014. CC Attribution 3.0 License. 1 2 Science, University of KwaZulu-Natal,3 Private Bag X01, 3209 Scottsville, South2600 Africa GA Delft, the Netherlands Received: 16 June 2014 – Accepted: 11Correspondence July to: 2014 A. – M. Published: L. 29 Saraiva July Okello 2014 Published ([email protected]) by Copernicus Publications on behalf of the European Geosciences Union. P. van der Zaag Drivers of spatial and temporalof variability streamflow in the IncomatiA. River M. L. Basin Saraiva Okello 5 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ect of climate change are ff 8882 8881 What are the implications of these trends for water management? Does the analysis oftrends? precipitation and streamflow records revealWhat any are persistent the drivers of these trends? – – – The goal of this paper is to determine whether or not there have been significant The Incomati is a semi-arid trans-boundary river basin in southern Africa, which is In southern Africa, these pressures have led to dramatic changes in natural stream- Climate change intensifies the global hydrological cycle, leading to more frequent Water is critically important to the economies and social well-being of the predom- The variability and changespossible of rainfall drivers and of streamflow records changes were were analysed identified and the from the literature, as well as from the changes in rainfall andpotential streamflow reasons dynamics and during implications of theare: such time changes of are. record, The and main research what questions the (DWAF, 2009d; TPTC, 2011).flow The regime, impact is of significant.ment, Hence, these if there demands, a is better relativecan an scientific to be understanding opportunity provided the of (Jewitt, to natural water 2006a). improve resources water availability manage- and variability such changes and what theimpact main of drivers climate are change (Hughes onSchulze et the (2012) al., water 2014). and resources Projections of some2001), on South analysing the research Africa streamflow has trends were in investigated beenare by other available done southern for Africa (Love the rivers, Incomati et but Basin. no al., such 2010; studies Fantawater-stressed et because al., of highagriculture, competing forestry, demands energy, from, environmental amongst others, flow irrigated and basic human needs provision steadily over the past decades.ous Urbanization areas also and brings the with increased itpurposes abstraction of an (Schulze, water increase 2011). for in domestic, impervi- municipal and industrial flow patterns. However, not many studies are available concerning the magnitude of et al., 2012, 2010). Areas of irrigated agriculture and forestry have been expanding the increased pressures on landconsequent and water requirements use, for owing food, to increased fuel population and and fibre the (Rockström et al., 2009; Warburton while a substantial amountcountries of of foreign the income region is (Hughes et derived al., from 2014). wildlife tourismand in variable extremes. some For southernoccurrence Africa, of drought recent due studies to forecast decreasedet an rainfall al., events increase (Lennard 2009; in et the Rouault al.,rise, 2013; et and Shongwe al., thus 2010). theand Furthermore, hydrological Shongwe, processes it 2004; driven is Schulze, by expected temperature 2011). that will Compounding temperatures intensify the will (Kruger e sues are increasinglywhere coming data into are conflict alsoAfrican with scarce. communities The human are local strongly developmentfisheries, dependent economies and objectives water on and and availability rain-fed, livelihoods remainsAfrica or of one (Jewitt, irrigated, of 2006a; many the Pollard agriculture southern and main and du constraints Toit, to 2009). Hydro-power development is in also locally important, Global changes, such asdevelopment and climate the expansion change, of population agriculture,particularly put growth, huge water pressure (Miao urbanization, on et industrial natural al.,2010; resources, 2012; Montanari Milly et et al., al., 2008;important 2013). Jewitt, In to 2006a; order Vörösmarty have et to a al., the manage sound variability water understanding in in of time a and the2004; sustainable space Hu manner, processes and et it that al., our is control 2011; ability Hughes its to et existence, quantify al., that 2014; variabilityinantly Montanari (Jewitt et rural et al., populations al., 2013). within southern Africa, where environmental sustainability is- commercial forestry and irrigated agriculture have increased over four times. 1 Introduction in the streamflow than climatic forces. Indeed, over the past 40 years, the areas under 5 5 25 20 10 15 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 2 ), low 1 ) in the 1 − − ) and high (61.4 %) in 1 2 − falls entirely 1 − , of which 2 560 km 2 C) and lower potential evapora- ◦ ), which represents 51 % of the aver- ); 1 1 − − a 3 m 6 8884 8883 C) and lower rainfall (400 to 800 mm a ). ◦ 1 − (33.2 %) in Mozambique and 28 681 km 2 ); 1 − C), with rainfall that reduces towards the east (400 to 800 mm a ◦ Coastal plain, located mostly in(mean Mozambique, annual average with of relatively 20 higher towest, temperatures 26 increasing eastward towardsevaporation the (2200 to coast, 2400 where mm a there is also high potential to 22 potential evaporation (2000 to 2200 mm a Highveld and middleLebombo Lowveld, Mountains, warmer which than the lies escarpment between (mean annual the average Drakensberg of 14 and the High-lying escarpment, with atemperatures (mean relatively annual high average of rainfalltion 10 (800 (1600 to to to 16 2000 mm 1600 a mm a – – – The level of water abstraction in the Incomati River is very high and the actual water 2011; DWAF, 2009d; Van der Zaag and Vaz, 2003). Since 1950s the area of irrigated demand is projected toopment increase and population in growth the (NkomoPollard future, and et as van der a al., Zaag, result 2011).1880 2004; of million LeMarie The cubic further et consumptive metres al., economic per useage 2006; devel- annum amount of of (10 surface surface water generatedmajor water in the water amounts basin consumers (Van to der (see Zaagwater more Tables and 1 uses, Vaz, than 2003). are and The the 2), irrigationfers accounting and to for forestry the 91 % sectors, Umbeluzi followed of Basin by all and inter-basin consumptive water the trans- Olifants Catchment in the Limpopo Basin (TPTC, the Lowveld (DWAF, 2009d; Riddellsugarcane and et subsistence farming al., dominate. 2013). Adeclared substantial a In conservation part the area, of which the Mozambican includes basinestablished the coastal has Great Kruger been Limpopo plains, National Park Transfrontier Park and (TPTC, the recently 2011). The complex geology ofand the dolomitic rocks, basin as is well as characterized2003). quaternary The by and soils sedimentary, recent in volcanic, deposits theloam (Van granitic der basin in Zaag are the and highly west, Vaz, variable, todeep ranging moderately clayey from soils deep moderately in sandy the deep loam east. clayey forestry The in (pine, dominant eucalyptus) the land in central uses the areas escarpment inin and the region, the dryland catchment moderately are crops Highveld (maize) commercial region and grazing and irrigated agriculture (sugarcane, vegetables and citrus) in from a warm toAfrica a in hot the humid west.during climate the The in summer Mozambique mean months to (October annualgraphically to a and precipitation March). cooler climatically The of divided dry Incomati about into (see climate three Fig. 740 in areas mm 1) a (TPTC, South can 2011): be topo- intonto, Uanetze and Mazimechopesmati, Rivers Crocodile and and the Sabiethe estuary are natural (TPTC, discharge, the 2011). with main Thethe an sub-catchments, mountains Ko- area (2000 contributing m of a.s.l.) about inMozambique. 61 % 94 the The % of general west of climate of the in the basin. the basin The Incomati and Incomati River drops Basin River to is the rises semi-arid, coastal in and plain varies in 2 Methodology 2.1 Study area The Incomati River Basin isby located the in Kingdom the of south-eastern Swaziland,Africa part the (Fig. of Republic Africa 1). of and Mozambique The(5.5 it and total %) is the is basin shared in Republic area Swaziland, of 15 is South 510South km approximately Africa. 46 The 750 Incomati km watercourse includes the Komati, Crocodile, Sabie, Mass- the area. The spatial variationthe of main trends drivers on are streamflow analysed.improved and Based water their on resources possible the management linkages and findings, with planning approaches are and proposed. alternatives for further analysis of the water resources assessment reports previously conducted in 5 5 25 20 10 15 20 25 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | airs) is the custodian of 104 gaug- ff 8886 8885 tests on the change in the mean and the variance. A probability T and F tests at 95 % confidence level. The annual and monthly time series were also T and The spatial and temporal heterogeneity in rainfall across the study area was char- timing of extreme flow events,(5) (4) the frequency rate and and duration frequency of of changes high in low flows. flow pulses, and 2.2.3 Indicators of Hydrologic Alteration The US Naturetors Conservancy of developed Hydrologic a Alteration”ties statistical (IHA), have method changed for flow assessing known regimes.et the The as al., IHA degree 1996, the method 2003) to is (Richter “Indica- based which andized upon human Thomas, by the 2007; concept activi- five that Richter ecologically-relevant hydrologic regimes(2) attributes: can (1) magnitude be character- magnitude and of duration monthly of flow extreme conditions, flow events (e.g. high and low flows), (3) the (Richter and Thomas, 2007; Richter etterns al., 1996, and 2003) trends and summarized, of toseries the identify and pat- streamflow for record the (a periodture single of on period 1970–2011), the analysis as streamflow for welldevelopment). (two-period the as to analysis, entire assess time before the and impact after of the infrastruc- major infrastructure ing stations in South Africa.tions In and Mozambique, flow ARA-Sul data isfrom from the the two custodian of gauges gauging gauging was stationsfrom sta- acquired from 1909 for the to this DWA 2012, study.series database, The length, was discharge influence with collected of data time-series infrastructure andtions (dams, lengths screened. canals) were ranging and Based selected spatial on for distribution,is 33 the detailed sta- highly analysis quality modified, (see of Tableinterventions. very data, 3 An few time and analysis stations Fig. of could 2). the As be 33 this indicators considered catchment of least hydrologic impacted alteration was by conducted human v.1.5.1.0B (Guzman and Chu, 2004). 2.2.2 Streamflow In the Incomati Basin, DWA (Department of Water A analysed for the presence of serial correlation. Tests were carried out using SPELL-stat F and monthly rainfall from each2003), station in order was to subjected identify toPettitt any the Test trends (Pettitt, Spearman for 1979) Test the (McCuen, was periodries. also of The 1950–2000 used, and test to 1950–2011. detect determinesknown The abrupt the as changes a timing in “change of hydrologicaldivides point” a se- the (Love change series et in into al.,sessed the 2 2010; by distribution sub-series. Zhang The et ofthreshold al., significance a of 2008). of time 0.8 The the series, was change change used point point for is the Pettitt then test as- to identify the change points, followed by the basin were selectedthe for percentage detailed of analysis. good The observedseries percentage data were of over extended reliability the up entire represents to time 2012, series. using Eight new of data the collectedacterised 20 from using time the statistical SAWS. analysis and annual anomalies. The time series of annual Rainfall data of the annual,of monthly 1905 and daily to rainfall 2000 forsists Southern was of Africa daily extracted precipitation for from the recordsquality the period for was over Lynch 12 checked 000 (2003) and stations database. somedata in data are The Southern was SAWS Africa, database (South patched. and con- Africa data Thesearch Institute) Weather main and Service), custodians ISCW SASRI of (Institute (Southof the for Soil Africa 374 rainfall Climate Sugarcane available and Re- for Water).of About Incomati, 20 reliable with stations data the out indicated best on quality the data database) (evaluated and by the the representative percentage spatial coverage of systems, as can be seen on Table 2. 2.2 Data and analysis 2.2.1 Rainfall agriculture and forestry has increased steadily, particularly in the Komati and Crocodile 5 5 20 25 10 15 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | value, P test in the F test and T 8888 8887 0.05 were considered significant trends. The value of the ≤ P ected by data infilling procedures. The existence of a serial correlation on annual Figure 4 shows, for example, the anomalies of annual rainfall and the moving average Mussá et al. (2013) studied the trends of annual and dry extreme rainfall, using The investigation of trends on the annual time series revealed no significant trends on The IHA software was used to identify linear trends of the streamflow time series, Table 4 shows the hydrological parameters analysed within each indicator group. ff the Standardized Precipitation Index (SPI)annual and rainfall precipitation also extremes found across no the significant Crocodile trends sub-catchment. on the at 95 % confidence level.change Only towards 2 a stations wetter regime out (Riverbank of and the Manhica). twenty studiedfor the showed stations significant of Machadodorp andclear Alkmaar. trend Monthly rainfall of also an doesthe increase not larger exhibit or any scale decrease analyses in conductedet most by al. Schulze of (2009) (2012) for the for Southern stations. South Africa. This Africa is and consistent Shongwe with with low percentage ofa reliability, thus it isand monthly possible time that series the waschange also trend points investigated, were identified but identified was could using not(Table the be found 5). Pettitt to Test, The mostly be on significance present. the ofchange Some years the 1978 of and mean change 1971 and was the assessed variance with of the sub-series obtained from the change points, be high, both intra- and inter-annually,to with note a wide that range this between variability years.due It is to is higher interesting for the the elevationillustrated stations by gradient. located the on The box the plot variability mountainous of across areas, Fig. 3. the basinmost stations is using the also Spearman significant, Trend Test,investigated at as 95 stations % showed confidence level. significant Only(3 5 trends of stations). of the 20 However, increase the (2 stations stations) that and presented decrease significant trends are also stations 3.1 Rainfall Statistical analysis was conductedthe on period the of 20 1950 rainfall to stations 2011. The described variability in of Table rainfall 5, across for the basin was confirmed to 3 Results are available only fromalready a established. period Additionally, a when2004 map most were of of compared current theWhere with land current the the occurrence use forestry of maps (2011) trends plantationsuse, of in and were flow this trends regime land was was of use consistent furtherchange. with indicators of the investigated, of changes by in hydrologic land looking alteration. at temporal evolution on the land use information was compiled forusing the ArcGIS various 9.3. hydrological indicators and plotted spatially, 2.2.4 Land use analysis Land use analysis was conducted, based on secondary data, as remote sensing maps the case of the presentmagnitude study, and the indicators duration of of magnitude extremein of water the monthly conditions, same water as conditions, period welldecrease (1970–2011), as of timing the to flow were assess metrics analysed whether were consistent present. trends ofbased increase on or the regressionand of only least trends squares.slope with This of the trend trend is line evaluated indicated with whether the the trend was increasing or decreasing. This Analyses are basedIncomati on Basin availability were analysed of withmethodology this daily method. of flow Many “Indicators studies data, successfullystreamflow of so applied caused the Hydrologic by selected anthropogenic Alteration”, drivers gauges2007; (Taylor in et from Maingi al., order 2003; the and Mathews to Marsh, and access 2002; Richter, De impacts Winnaar on and Jewitt, 2010; Masih et al., 2011). In 5 5 25 20 10 15 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | val- cient P ffi (75th per- = ect of flow regulation and water abstractions ff 8890 8889 than Komati and Crocodile. This is the case be- ff ered due to flow regulation, or because high streamflow cient of dispersion (CD) is defined as CD ff ffi erent hydrologic indicators were compiled as an output of the ff 25th percentile)/50th percentile. The higher the CD, the higher the variation of − The cross-compensation can also be observed at basin-scale on the Sabie, where Table 7 illustrates that many of the trends observed in the Sabie sub-catchment are The significant trends (95 % confidence level) occurring on the various indicators This trend is consistent with the decreasing trends of minimum flows, as exempli- Another aspect to note is that the flows of February are likely to be higher than The flow patterns are consistent with the summerA rainfall comparison regime, of with the highest flow flow normalized by area (Fig. 5) for the main sub-catchments curs because the majority ofNational the Park Sabie falls (KNP) under andbeen the playing therefore conservation an area no important of role major thewhich in Kruger abstractions the concern catchment occur the management here. fora provisionmaintenance set The of up of KNP environmental by ecosystem the minimum has ICMA, andet flows, al., biodiversity in 2013). in order the to Park ensure (Pollard the etcontrary al., to 2012; Riddell those observedlikely that in the the trends Komati observed and in Crocodile downstream E43 sub-catchments. - Thus, Magude, it in is Mozambique, are as is that some ofoccurring the on trends the tributaries cross-compensate of each thebaseflow other. Crocodile, are for Some cancelled example, of the as October the we Median move positive Flow downstream trends and the main stem. the trends of decreasing flows are not so frequent or significant. It is likely that this oc- increased significantly in many gauges,of which low indicates flows. the Another moresals striking frequent of occurrence trend almost all is stations, the indicating(reversals the occur significant e when increase an of increasing the flow rate number changes of to rever- awere decreasing counted flow rate). perthe station map and is plotted thatsystems, more on which significant are the decreasing also the map trends most occur in stressed in sub-catchments. Fig. Another the interesting 7. Komati aspect and The Crocodile salient pattern on is when more water stressmonth is experienced, of which the is start explainedwater by of requirements the the are fact that highest rainy this (DWAF, 2009c; season, is ICMA, when the 2010). the damfied levels are by lowest the and 7 irrigation day minimum. In contrast, it can be seen that the count of low pulses Crocodile and the Komati. This means that along the entire basin the month of October sub-catchment. The first observationOctober is a in significant almost trend all of decreasing stations, mean especially flow the in ones located on the main stem of the extremes are not fully captured by the current monitoring3.3 network. Trends in streamflow In Fig. 6, theselected plot hydrological of indicator. trends Forthe indicated comparison, periods by 1970–2011 the the (Fig. sameare slope 6a) highlighted indicators of and with are the for a trendues 1950–2011 plotted circle. for line (Fig. for Table the 7 is 6b). gauges presents The presented located the significant per at slope trends the of outlet, the or trend the lines most and downstream point of each main cause the observed streamflows includeflow the reduction impact of activities, watercatchments which abstractions (Mallory and are and stream- Hughes, more 2012; Hughes intense and in Mallory, 2008). theobserved Komati records, but and are bu Crocodile sub- of dispersion), because thepositively hydrological skewed. time The series coe centile are not normally distributed,the but parameter will be. and rainfall events associated with tropical cyclone activity in January–March. reveals that Sabie yields a higher runo The metrics of theIHA di analysis. The resultsdownstream) for of the each gauging mainThe sub-catchment stations variability are located is presented at in described, the Table using outlet 6, (or non-parametric as the an statistics most example. (median and coe 3.2 Variability of streamflow 5 5 25 20 10 15 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ect is ff ects of flow reg- ff ect of the conservation approach of KNP on ff 8892 8891 ect of flow reductions in the Crocodile and the Komati. ff erent parts of the world (Maingi and Marsh, 2002; Richter et al., 1998; Bunn and ff It can be seen that this reservoir is managed to augment the low flows and attenuate It is important to note that these trends are even more pronounced, when longer time From Table 7 and Fig. 7, it can be seen that the Komati sub-catchment (at Tonga observed upstream. of the flow regime, asin a di result of damArthington, operation. 2002; Similar Birkel impacts et were al., found 2014). in studies floods. This change in theof flow the regime Crocodile influences River, thereduced. but streamflow At the as along outlet the tributaries in main Tenbosch,ulation join X2H016 stem (Fig. and it, 7 water and and Table abstractions water 7), the have is e already abstracted, counter-balanced the the e contrasting trends regime, which are reversed seasonality,on the low dampening flow of and peak flows baseducted and flow by Riddell an indices. et increase These al. results (2013),in which are the found Crocodile consistent significant Basin with alterations over of the thehistorical natural past analysis flow 40 compliance con- regime years. They with developed a environmental methodologya water to high allocations, assess incidence and of reported non-compliance, that reduction of there low is flows and some homogenisation 3.3.2 Impact of the Kwena DamThe on Kwena streamflows Dam is of the the maincatchment, Crocodile reservoir River commissioned on the in Crocodile 1984. system, The locatedply dam upstream of in is the water used for tois irrigation improve the located purposes assurance few in of a the sup- 1986–2011) kilometres catchment. downstream analyses The of illustrated Montrose this Gauge the dam. (X2H013) The main two-period impacts (1959–1984 of and Kwena Dam on the river flow irrigated agriculture. Duringder the forestry, namely, 1970s Eucalyptus there (DWAF, 2009c).water Commercial was forestry through also consumes evaporation more than aSouth the great native African increase vegetation National of it Wateruser, replaces, area which Act, therefore, is un- under commercial termed the a forestry Streamflow must Reduction be Activity (SFRA) licensed (Jewitt, as 2002, 2006b). a water of mean monthly flows during the 1960s coincides with an increase of the area under illustrates the comparison of medianysis monthly of flows land for use the two changes periods. over From time the (Table anal- 2), it can be seen that the sharp decrease frastructure being constructed (DWAF,of 2009b). Kaapsehoop The (0518455W) records does ofwhich not nearby show suggests rainfall a the station significant reductionchange, trend namely, conversion observed of to decrease in forestry of and streamflowin irrigated rainfall, all land. could The months, be decreasing but trends aber are occur (Fig. result more 9) pronounced of and during October. landand There low is an use flow a increase months, significant of particularly decrease1949–1974 extreme of Septem- low and high flows. flows 1978–2011 and The small shows annual floods flow a duration dramatic curve decrease for the in periods annual flows. Figure 10 3.3.1 Example of decreasing trends: NoordThe Kaap X2H010 Noord Kaapcatchment showed Gauge the most intriguing (X2H010), trends.had Out located of 12 the 33 on significant indicatorsregime trends, (IHA), a this over 10 gauge the tributary of period of of them analysis. negative, the However, there which Crocodile is indicate no sub- a record of major a shift dam in or major flow in- The Kaap and Elandstrends on tributaries their mean of monthlyKwena the flows, as Dam, Crocodile well which as River is on located haveto the on augment low significant the flows. the main On decreasing flows stem the duringlow other of the flow hand, the dry months. the Crocodile, season. is This managed results in in a increasing way flows duringseries the are considered. Two examples from the Crocodile Basin are presented below. the Sabie, and the negative e Gauge, X1H003) is wherethe most months of negative October, trends Junethe occur, and trends July. are particularly In not significant visible, the because Crocodile during a (at lot of Tenbosch Gauge, cross-compensations have X2H016) already occurred. a result of a combination of the positive e 5 5 25 20 10 15 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | erent riparian ff ect the streamflow regime, the water ff 8894 8893 Decreasing trends ofmonths, the e.g. October), magnitude minimumoccurrence of flow of (1, high monthly 3, flow pulses; flow 7, 30 (significant and for 90 day low minimum) and flow the – Another challenge is the disparity of data availability across the di Some gauges are from nested catchments. A lot of trends and alterations counter- On the Komati, the strategic water uses, which have first priority (such as water On the Crocodile, however, irrigated agriculture, forestry and urbanization were the 4.2 What are the most strikingThe trends analysis and resulted where in do the they identification occur? of major trends, such as: balance each other, ascases can of be contradictory seen trends that clearlyof occurred measurement in could equipment the and possibly the Crocodile be adjustmentthe explained system. of by best the However, the quality flow some change rating stations curves. andto An a analysis avoid number of this of pitfall. stations in the same system was conducted, period of common datadevelopments. followed the construction of a lot of impoundmentscountries. and In other Mozambique, onlyrepresenting the two entire gauges Lower hadMazimechopes, Incomati reliable in system. The flow Mozambique rivers dataa do Massintonto, for need not Uanetze to this and have strengthen analysis, activethe the basin, flow as hydrometric gauges. well monitoring as There network on is the in tributaries the definitely originating Mozambican in part the Kruger of National Park. 4.1 Limitations of this study The available data series had someof gaps, this, especially the during analysis high of flow high periods. flow Because extremes is highly uncertain. For the trend analysis, the 4 Discussion transfer to ESKOM plants in(Nkomo the and Olifants van Catchment der and Zaag,Because to 2004; of irrigation DWAF, other 2009d), in water have thetrends allocations, a for of Umbeluzi) high irrigation, decreasing impact flows forestry on could andronmental streamflows. flows be other and identified. industries, cross-border requirements This steady are is(Pollard often and not another met du system during Toit, where the 2011a; dry the Riddell season envi- et al., 2013; Mukororira, 2012). has important implications when environmentalborder flow flows requirements need and to minimum be cross- adheredhave to. Pollard demonstrated and du that Toit (2011a) and therequirements Riddell during et Crocodile most al. River (2013) of the is dry not season at complying the to outlet. environmental flow of mean, annual andbe low explained flows by do the not factthe show that significant period most trends of of (see the analysisproportion Table forestry of 7). for area the This trends was Sabie can already sub-catchment (1970–2011)game is established reserves) (DWAF, under during 2009a). also conservation plays The land an use fact important (KNP role that and in other a maintainingmost large the natural important flow regime. anthropogenicquantity drivers. and They possibly the a water quality as well (beyond the scope of this analysis). This As can be seen fromoperation water and use water information, the abstractionson impacts are the of the land Incomati. main use However, change,system, the drivers reservoir in situation of spite is changes of variable great in areas along the of the flow commercial catchment. forestry regime In in the the headwaters, Sabie the indicators 3.3.3 Impact of anthropogenic actions 5 5 20 10 15 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | cult ffi ciency and to munic- ffi 8896 8895 Some gauges showed no significantparameters change analyzed. or no These clear are pattern1970 mainly of had gauges change established located the on current the on land the use Sabie, seen which to the by present day. Significant increasing trendsSeptember) in of some locations the inof the flow magnitude Crocodile reversals and basin of Sabie, wide; and monthly on the occurrence flow (August and – – Given the likely expansion of water demands, due to urbanization and industrial de- This study also shows the complexity of water resource availability and variability. For the management of water resources in the basin, it is important to note that there To some extent, dams do provide storage and attenuate floods in the basin, but In the Sabie system, most gauges did not show varied significant trends. This is In the Crocodile system the flow regulation, through the operation of the Kwena Dam, This is even more relevant, considering that this is a transboundary basin and that basin in future, such asdesign aquifer of storage, operation artificial rules recharge,variability. rainfall for harvesting, dams etc. should The also aim at mimicking thevelopment, it system’s is natural also important thatmeasures water are demand management better and implemented water conservation to in reward the users that basin. use For technologyipalities example, to that there improve encourage their could their water users be use to e systems have lower water demands. not only the magnitude of flows, but their duration andhave timing impacts as downstream, well. suchseasonality, which us can the hamper the changeother health of of possibilities ecosystems mean of downstream monthly water of storage flows the should dams. and So be reverse further investigated and adopted in the influence the flow regime. are some clear patterns illustrated bygenerated the Sabie, in Crocodile and the Komati. The upperthe Sabie Kruger flows parts National of Parkinfluence, the or the flows catchment Catchment are persist, Management highlyapproach whilst Agency modified. through Forum in the is This other Strategic less suggestsvery rivers, Adaptive of that beneficial where Management an the to of keep use the environmental KNP of flows and the in ICMA conservation the can system. be It is important to consider When the analysis of trends isthat combined with the the land majority use of ofor the gauges basin irrigated with (Fig. 8), decreasing it agriculture is trendsare clear dominate are less located the prevalent. in land The areas use presence were forestry of and water where management conservation infrastructure approaches (dams) highly 4.3 Implications of this findings for water resources management a headwater tributary of theflows, shown Crocodile, in there the is monthly a flow,This the significant change flow and duration is dramatic curves compared, reduction andarea by the of under inference, low forestry flow using in parameters. land the use sub-catchment, as data, well with as themost with increase the likely increase in due in the to irrigation. and fewer larger disturbances: areas under lower conservation. waterno During clear demands, the impacts less period of from water climatic 1970 abstractions change to (in 2011, terms there of were rainfall) on the streamflow. for example, has impactedare on reduced the and the attenuation low of flowsstream extreme generally of increase, flow leading the events. to Kwena The reverseof seasonality Dam. high water down- The flows for dam irrigation purposes is in used the to catchment. improve However, on the X2H010 assurance – of Noord the Kaap, supply In the Komati system, thepacts flow on streamflow. regulation Most and gauges water areto abstractions already characterize severely have natural impacted very flow and strong conditions. itand im- Flow is minimum regulation quite flows. has di In highest thesugar-cane. impact Komati, The on there upstream low is dams flow of significantto Nooitgedacht irrigated and supply agriculture, Vygeboom cooling particularly are water also toexported mainly ESKOM and used power not stations used outside within the the basin; basin. thus, the water is 5 5 25 20 10 15 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 10.1007/s00267- harvesting in the ff erent riparian countries. ff ected sub-catchments and main ff 8898 8897 , 2014. , D.: Assessing the cumulative impacts of hydropower ff airs and Forestry: Inkomati Water Availability Assess- airs and Forestry: Inkomati Water Availability Assess- ff ff , 2010. 10.1002/rra.2656 The authors would like to thank UNESCO-IHE Partnership Research , 2002. 10.1016/j.pce.2010.07.009 Considering the high spatial variability in the observed changes, no unified approach The study therefore recommends that conservation approaches to water manage- The statistical analysis of rainfall data revealed no consistent significant trend of in- There is a great discrepancy of data availability between di ment Study, Hydrologyvironmental, of Engineering Crocodile River andPWMA 05/X22/00/1508, Volume Pretoria, Management 1, 2009b. Consultants, prepared SRK by: Water Consulting for and Africa CPH20, En- regulation on theAppl., flow 30, characteristics 456–475, doi: of a large atlanticflow Salmon regimes river for aquatic system,002-2737-0 biodiversity, River Environ. Res. Manage., 30, 492–507, doi: headwaters of thedoi: Thukela River basin, South Africa, Phys.ment Chem. Study, Earth, Hydrologyvironmental, 35, of 634–642, Engineering Sabie andPWMA 05/X22/00/1608, Pretoria, River Management 2009a. Volume Consultants, 1, SRK prepared Consulting and by: CPH20, Water for Africa En- will work, but the specificcatchments. interventions for Future the investigations most a derived should from conduct water use a should beare careful done, indeed in assessment the order most to of beneficial; assess this if benefits should the first be priority done water basin uses wide. work closely with the waternatural variability. management institutions, to keep flow regime close to the agriculture have increased over four times, increasing the water use,ment, basin such wide. as strategicand Inkomati adaptive Catchment management Management Agency, adopted should beWater by further demand the deployed management in Kruger the and basin. the National water development conservation Park of should be dams,basin. alternative and Land options should use to be practices,pact further particularly on investigated forestry water and and quantity of established agriculture, the in have basin; a the therefore, significant stakeholders im- from these sectors should crease or decrease for the studiedrevealed period. significant The decreasing analysis trends of of streamflow, on streamflowmonthly the indicators, flows other of particularly end, September the and median October,that and low land flow use indicators. This and studybasin. flow concludes Indeed, regulation over the are past 40 larger years drivers the areas of under trends commercial forestry in and the irrigated streamflow in the on the state of water resources.more The monitoring attention, of with hydrological focus extremes should on receive increasing the accuracy of recording the flood5 events. Conclusions The research conducted showsthat important are interactions complex and of intertwined, the often dynamics working of simultaneously within streamflow a river basin. mum development levels that have toand be van adhered to der (Pollard Zaag, and 2004; Toit, 2011a, Riddell b; et Nkomo al., 2013). It is very important thatorder to Mozambique, better in assess particular, the improves impact its of monitoring various network, management in activities occurring upstream there are international agreements regarding minimum cross-border flows and maxi- DWAF – Department of Water A De Winnaar, G. and Jewitt, G.: EcohydrologicalDWAF implications – of Department runo of Water A Birkel, C., Soulsby, C., Ali, G., and Tetzla Bunn, S. E. and Arthington, A. H.: Basic principles and ecological consequences of altered References sources Commission of South Africa,ing, through which Project is K5/1935 appreciated. also All contributedincluding additional partners the fund- of reference the group RISKOMAN are projectwas thanked (UKZN, for kindly ICMA, their provided KOBWA, valuable UEM) by inputs. DWA, Streamflow UKZN and and rainfall SAWS. data Fund (UPaRF), through the RISKOMAN project, for funding of this research. 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Total TotalTributaryKomatiKomati 3476 CountryKomatiKomatiLomati South Africa Major damCrocodile South Africa Nooitgedacht 248Crocodile Swaziland VygeboomCrocodile SwazilandSabie Maguga South South Africa AfricaSabie Sand South river Africa 1962 Kwena Driekoppies Year commissionedSabie South Africa Witklip Storage capacity 1971 (10 Klipkopje South Africa 1614 South Africa 2002 Da 1998 Gama 1966 Mozambique Injaka Corumana 81 1984 1979 1979 84 365 1979 332 251 1988 49 2001 155 12 12 2227 14 879 120 KomatiCrocodileSabieMassintotoUanetse 1332 1124Mazimechopes 41Lower 20 Incomati 668Mozambique 258 33 141.5South 74.7 Africa 325Swaziland 2663 0.3 0 30 1.5 488 0.3 621 482 0 98 0 412.8 0 117 158 412.8 961 240 0 0 879.5 90 714.7 0 0 414.3 218 0.3 0 0.3 10 Table 1. Zhang, X., Zhang, L., Zhao, J., Rustomji, P., and Hairsine, P.: Responses of streamflow to Warburton, M. L., Schulze, R. E., and Jewitt, G. P. W.: Confirmation of Warburton, M. L., Schulze, R. E., and Jewitt, G. P. W.: Hydrological impacts of land Vörösmarty, C. J., McIntyre, P., Gessner, M. O., Dudgeon, D., Prusevich, A., Green, P., Glid- Van der Zaag, P. and Vaz, A. C.: Sharing the Incomati waters: cooperation and competition in TPTC – Tripartite Permanent Technical Committee: Tripartite Technical Committee (TPTC) be- 5 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 1950’s 1970’s 1996 2004 ) for trends Data 2 ) 0 0 0.5) 0.5 0.1 7.5) 19.8 0 22.3 0 0 0 1 1 1 − − − Area (km a a a 3 3 3 m m m 6 6 6 ) 0.5 7.7) 15.5 19.7 ) 3 12.2 33.6 2.4 52.4 5.3 13 26.7 ): 1 1 1 8906 8905 1 − − − − a a a a 3 3 3 3 m m m m 6 6 6 6 )) 247 377) 661 801 375 1550 1811 1941 428 729 708 853 2 2 2 )) 92.8 365.8 427 510.7 27.7 68.4 113.4 127.6 ) 17.6 144.1 385.1 512.4 2 2 2 elspruit @ Doornpoort 581 1970 – 2012 1970–2011 (42 years) 3.4 % ff orested area (km orested area (km orested area (km 25.0925.09 30.7824.99 30.7825.08 30.81 Sabie25.03 River 31.13 @ Sabie Klein24.77 Sabie 31.13 River @ Sabie Mac-Mac24.89 River 31.39 @ Geelhoutboom Noordsand25.15 River 31.09 @ De Rust Sabie24.97 River 31.94 @ Perry’s Farm Sand River 31.52 @25.44 Exeter 52 Marite River @25.03 Injaka 31.99 Sabie River @ Lower 55 Sabie 32.65 Sabie Rest River Camp @ 174 Kruger Gate 200 5714 Incomati River @ 1948 766 Ressano Garcia Incomati River @ – Magude 1963 2012 1948 1986 1948 – 1970–2011 – (42 years) 21 1064 – 200 – 1958 2012 2012 212 2407 0.5 % 2012 2012 – 1970–2011 (42 years) 1970–2011 (42 1988–2011 years) 1970–2011 (24 2000 (42 years) years) 1948 0.4 % 0.8 1967 % 1970–1999 8.2 3.9 % (30 % – years) 37 500 1990 – 1978 2.6 2011 % – 2011 – 1970–2011 (42 years) 2012 1968–2011 (43 1952 2012 years) 9.0 1991–2011 % (21 – 1979–2011 years) 15.5 % (32 years) 2011 10.8 % 7.6 % 1970–2011 (42 years) 3.5 % 26.0425.68 31.0025.67 31.7825.95 31.58 Komati26.01 River @ 30.57 Hooggenoeg Komati River @ 31.0825.43 Tonga Mlumati River @25.47 Lomati 30.97 Bu 25.79 31.09 Mtsoli River @25.61 Diepgezet 30.92 5499 Nels25.65 River 30.87 @ Boschrand Krokodil25.66 River 30.28 @ Karino Queens25.45 River 30.26 @ Sassenheim Noordkaap 190925.38 River 8614 30.71 @ Bellevue 1119 Elands –25.49 River 30.70 @ Geluk Dawsons 201225.36 Spruit 295 30.70 @ Geluk Krokodil 1970–201125.54 River (42 31.96 @ years) 1939 Montrose Houtbosloop 196825.71 642 @ 180 31.32 Sudwalaskraal 8.0 – % Elands –25.73 River 5097 30.84 @ 2012 126 Lindenau Krokodil 1975 201225.51 River 30.98 @ 1970–2011 Tenbosch (42 years) Kaap – 1978–201125.44 River (34 31.22 years) @ Dolton 1929 6.8 1948 Suidkaap 2012 % 25.40 River 0.5 31.98 @ % 1929 250 Glenthorpe – – 91 Suidkaap 1976–2011 40225.61 1948 River (36 1518 years) 31.61 @ – Bornmans 2012 Drift 2012 Krokodil – River 2.7 30.40 @ % 2012 Weltevrede 1970–2011 1970–2011 Komati (42 years) 2012 (42 River years) @ 1970–2011 Komatipoort (42 1554 years) Krokodil 10365 0.8 1970–2011 River % 1958 0.5 (42 @ % 1959 years) Riverside 1956 0.1 Swartkoppiesspruit 262 % 1956 80 @ – Kindergoed – 5.7 % – – 2012 2012 1999 1960 1959 2012 1970–2011 1639 1970–2011 (42 5397 years) 1957–1999 (42 – years) (43 – 1970–2011 years) (42 years) 110 1966 5.1 21 % 2012 1.6 481 % 2012 0.9 % 1964 0.3 % – 1970–2011 1970–2011 (42 years) (42 – 8473 years) 1960 2012 1968 5.6 2012 % 3.1 1982 % – 1966–2011 – (46 years) 1985 1970–2011 – (42 2012 years) 2012 5.0 – % 2012 1985 1970–2011 1.7 1970–2011 % (42 (42 years) 2012 years) 1983–2011 – (28 years) 5.7 1986–2011 2.4 % % (26 years) 2012 4.1 % 2.2 1986–2011 % (26 years) 2.0 % ff ff ff − − − − − − − − − − − − − − − − − − − − − − − − − − − − − − − − − Domestic water use (10 Industrial and mining water use (10 A Domestic water use (10 Industrial and mining water use (10 A Domestic water use (10 Industrial and mining water use (10 A Water Transfers out (10 To Power stations in South AfricaTo irrigation in Swaziland 3.4 103 0 98.1 104.7 111.8 122.2 121.8 Hydrometric stations analyzed, location, catchment area, data length and missing Land use and water use change from 1950’s to 2004 in Komati, Crocodile and Sabie X3H002 X3H003 X3H004 X3H006 X3H008 X3H011 X3H015 X3H021 Station Latitude Longitude River and location Catchment Data Available Period analysed Missing X1H003 X1H014 X1H016 X1H021 X2H006 X2H008 X2H010 X2H011 X2H012 X2H013 X2H014 X2H015 X2H016 X2H022 X2H024 X2H031 X2H032 X2H036 X2H046 X2H047 Crocodile Irrigation area (km Sabie Irrigation area (km Komati Irrigation area (km Incomati E43 Lower E23 Sabie X3H001 Crocodile X2H005 Komati X1H001 Table 3. data. Table 2. sub-catchments. Source: adapted from TPTC (2011). Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | a a a a b a b test T ] Spearman 1 − ] [mm a 1 − erences between consecutive daily ff Analysis for the period 1950 to 2011 values No. of rises and falls one, three,day(s) seven, mean thirty and ninety mum and minimum Mean duration of highwithin and each year low (days) pulses di Reliable Mean St.Dev. Trend Pettitt P test of stability of variance. F 8908 8907 [m a.s.l.] [mm] [%] [mm a reliable is the percentage of reliable data for the rainfall station, as assessed by Lynch (2003) for the P Regime CharacteristicsMagnitude timing HydrologicalMagnitude parameters duration Mean value for each calendar month Annual minima and maxima based on TimingFrequency and duration No.Rates of of high change and of low frequency pulses each year Means of Julian all date of each positive annual 1 and day maxi- negative test of stability of mean. test of stability of mean and T T , the standard variation, and detection of trend (confidence level 1 − test of stability of variance). 25.6725.97 30.2525.58 30.5724.98 30.7725.15 1563 30.8225.45 1165 30.8325.80 781 1564 30.8324.83 829 1443 1295 30.9525.17 79.6 1463 1395 31.0725.67 90.6 1161 31.18 78.525.97 715 75.1 31.2325.00 796 830 68.5 31.2525.42 773 778 787 31.5824.40 817 625 1461 982 95.2 31.6025.82 134 1501 583 707 92.2 1029 31.7824.78 153 286 1197 82.4 683 1024 31.8325.37 287 300 60.0 31.8725.60 266 315 874 560 70.5 31.90 40.125.07 257 775 547 32.23 Decr25.40 256 172 919 568 63.1 32.87 262 185 734 591 66.5 32.80 192 1075 297 782 540 42.1 Decr (1975) Decr 108 (1978) 188 584 63.4 315 163 566 632 18 66.1 520 62.9 33 Decr 853 Incr 140 602 63.9 883 187 594 76.2 151 544 Decr Decr 86.2 (1978) (1978) 145 590 Incr (1977) Incr 134 633 Decr 147 773 185 903 Incr 241 (1971) Decr (1978) 275 Incr (1971) Incr (1970) F − − − − − − − − − − − − − − − − − − − − Description of rainfall stations analyzed for trends, also the long term Mean Annual Hydrologic parameters used in Range of Variability Approach (Richter et al., 1996). Indicators of Hydrologic Alteration Group Group 1: Magnitudewater conditions of monthly Group 2: Magnitude andof duration annualtions extreme water condi- Group 3:treme Timing water conditions ofGroup annual 4: Frequency ex- andof duration high/low pulses Group 5: Rate/Frequency of water condition changes Significant change with 2.5 % significanceSignificant level change with with 2.5 % significance level with Machadodorp 0517430 W Badplaas (Pol)KaapsehoopMac 0518088 Mac W (Bos)Spitskop (Bos) 0518455 W 0594539 W Oorschot 0555579 W Bosbokrand (Pol) 0595110 W Riverbank 0518859 W Riverside 0519310 W SataraFig Tree 0557115 W Moamba 0639504Xinavane W 0520589 W Manhica P821 M P10 M P63 M Name Station ID LatitudeAlkmaar Longitude Altitude MAP Pretoriuskop 0555567 W Piggs Pig 0556460 W Skukuza 0519448 A Tsokwane 0596179 W Krokodilbrug 0596647 0557712 W W a b Explanatory Note: MAP is theperiod Mean 1905 Annual to Precipitation, 1999. and Thetrend mean significant refers at to 95 % thedirection confidence average of of level change are total and indicated annual year with precipitation are Decr for indicated, the or as period Incr, well corresponding of as to 1950 the decreasing to significance or 2011. of increasing On the trend, the change respectively. column On point. trend the Spearman column only Pettitt, stations the that had Table 5. Table 4. Precipitation (MAP) in mm a of 95 % using Spearman Test) andof occurrence stability change of point mean (using Pettitt and Test followed by Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | value 2.01 1.21 1.49 2.90 1.35 3.21 2.32 2.03 1.86 1.44 1.47 1.41 1.11 1.48 1.76 1.61 1.37 1.38 1.80 1.74 1.56 1.45 1.32 0.21 0.14 1.33 2.09 0.75 1.03 1.43 –2.31 0.49 0.005 0.5 0.05 0.5 0.05 0.5 0.25 0.5 0.5 0.001 0.5 0.25 0.1 0.025 0.05 0.5 0.025 0.5 0.05 0.005 0.001 0.5 0.5 0.25 0.5 0.5 0.5 0.5 0.05 0.5 0.5 0.5 0.25 P 0.764 0.007 0.103 0.068 0.602 0.043 0.617 0.080 0.007 1.374 2.147 3.400 0.054 0.054 0.094 0.127 0.139 0.039 0.090 0.166 0.045 0.365 0.195 1.346 0.960 0.087 0.165 0.313 0.6278 –0.034 –9.254 –6.722 –2.847 − − − − − − − − − − − − − − − − − 47.44 8.72 16.14 22.91 37.96 45.09 51.75 34.90 17.85 14.04 10.41 8.46 7.06 2.49 2.71 3.01 4.84 8.14 381.5 344.1 273.7 156.7 102 290.5 39.5 3 6.75 4 8.5 1.058 − 86 –10.580 2.31 0.92 1.09 1.49 1.35 1.84 2.30 1.13 1.64 1.25 1.18 1.08 1.15 1.13 1.08 1.16 1.12 1.23 2.51 2.60 2.27 1.93 1.47 0.06 0.17 1.00 1.69 0.69 2.10 1.12 –1.10 0.29 value Slope 0.5 0.5 0.5 0.5 0.25 0.25 0.5 0.5 0.25 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.25 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.25 0.5 0.5 0.25 0.5 0.5 0.5 P 0.2398 17.35 3.08 4.81 10.83 18.52 16.33 19.51 13.69 7.04 5.64 3.79 3.40 2.69 1.45 1.53 1.60 2.01 3.02 113 87.62 62.55 37.66 28.06 278.5 20.5 4 6.5 4 5 0.404 − 95 0.560 0.012 0.017 0.144 0.096 0.297 0.185 0.288 0.001 0.420 0.032 0.934 3.742 0.092 8.171 0.038 0.033 0.004 0.004 0.003 0.312 0.218 0.171 0.470 0.788 1.532 0.112 0.486 1.979 0.783 0.020 0.017 12.070 − − − − − − − − − − 2.11 1.87 3.88 2.63 1.52 2.80 1.90 2.13 2.16 2.45 2.28 1.35 1.51 5.29 3.76 4.35 2.08 2.09 1.00 1.15 1.13 1.33 1.71 0.15 0.19 1.55 0.71 0.95 1.28 1.38 –1.28 0.18 value Slope 0.5 0.5 0.5 0.25 0.5 0.1 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.1 0.25 0.1 0.1 0.1 0.25 0.5 0.5 0.5 0.5 0.25 0.5 0.5 0.25 0.5 0.5 0.5 P 1.38 34.28 2.24 7.09 18.79 34.47 29.77 42.15 24.10 9.98 7.10 4.72 2.51 2.24 0.14 0.25 0.33 1.29 3.17 274.3 232.9 201.4 109.6 68.69 281.5 35.5 5 3.5 5 4.5 1.161 − 121 0 0.723 0.007 0.005 1.081 0.023 0.669 0.045 3.222 0.004 0.548 0.789 0.014 0.662 2.743 1.379 0.131 0.058 0.064 0.061 0.061 0.134 0.081 0.219 0.270 0.416 0.899 0.390 0.544 1.493 0.199 0.263 0.017 8910 8909 − − − − − − − 1.97 1.88 2.35 1.48 1.47 2.01 1.63 1.37 1.68 1.62 1.48 1.71 1.81 2.64 2.16 2.88 1.79 1.34 1.38 1.33 1.20 1.28 1.16 0.12 0.11 1.63 1.60 1.25 2.13 0.98 –0.78 0.42 0.61 value Slope 21.35 2.54 5.75 15.07 20.68 31.37 27.15 19.82 9.11 5.66 4.56 2.63 2.08 0.24 0.32 0.40 1.52 3.45 142.2 126.9 107.4 76.98 45.08 274 33 4 5 4 4 0.64 − 113 0.01 0.05 0.5 0.01 0.5 0.5 0.001 0.5 0.5 0.5 0.5 0.5 0.25 0.25 0.25 0.25 0.25 0.25 0.5 0.25 0.25 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.25 0.5 0.5 0.5 P 0.5 0.927 0.023 0.090 0.006 0.052 1.083 0.008 0.007 0.140 0.238 0.347 0.000 0.354 0.005 0.576 2.427 1.023 5.425 3.670 0.059 0.025 0.015 0.015 0.015 0.105 0.134 0.060 0.059 0.045 0.007 0.397 –0.013 –1.263 − − − − − − − − − − − − − − − − − − − − − 2.14 1.47 1.94 2.09 1.82 1.95 1.74 1.74 1.41 1.90 1.98 1.63 1.47 4.04 3.38 2.55 2.13 1.47 1.26 1.50 1.59 1.45 1.33 0.10 0.16 1.63 1.41 0.75 1.31 1.39 –0.98 0.26 cient of variation were used. ffi 0.7295 value Slope Median CD Median CD Median CD Median CD Median CD 861416.94 10 365 21 481 5714 37 500 3.95 5.72 11.46 17.26 25.09 18.33 11.64 8.03 4.96 3.77 2.67 2.43 0.31 0.38 0.59 1.46 3.69 134.4 102.9 81.79 54.39 39.19 0.7095 − 0.1 0.5 0.5 0.5 0.005 0.5 0.1 0.5 0.25 0.5 0.25 0.25 0.25 0.25 0.25 0.25 0.01 0.025 0.05 0.025 0.025 0.1 0.5 0.005 0.025 0.1 0.5 0.5 0.1 0.5 0.5 0.1 0.05 P 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 − − − − − − − − − − − − − − − − − − − − − − − − − s s s s s s s s s s s s s s s s s s s s s s s s s 2 0.007 0.001 0.686 0.671 2.361 1.022 5.143 3.749 0.074 0.029 0.225 0.082 0.360 1.027 0.437 0.194 0.254 Slope 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 –0.127 –0.115 –0.069 –0.038 –0.029 –0.027 –0.179 –0.215 –0.285 − − − − − − − − − − − − − − − − − m ] 8614 10 365 5714 21 481 37 500 2 Trends of the hydrological indicators for the period 1970–2011. In bold are significant Hydrological indicators of main sub-catchments. ∗ On the annual statistics mean and coe Annual STREAMFLOWINDICATORSPeriod of Analysis: UNITSDrainage area KOMATI km 1970–2011 (42 X1H003 years) – TONGA 1970–2011 (42 years) CROCODILE 1983–2011 X2H016 (28 years) – TENBOSH X2H036 – KOMATIPOORT X3H015 1988–2011 – INCOMATI (24 LOWER years) SABIE E43 – MAGUDE 1970–2011 (42 years) SABIE INCOMATI Oct m Nov m Dec m Jan m Feb m Mar m Apr m May m Jun m Jul m Aug m Sep m 1 day minimum m 3 day minimum m 7 day minimum m 30 day minimum m 90 day minimum m 1 day maximum m 3 day maximum m 7 day maximum m 30 day maximum m 90 day maximum m Date of minimum Julian Date 275 Date of maximum Julian Date 38.5 Low pulse count No 6 Low pulse duration Days 5.5 High pulse count No 6 High pulse duration Days 4 Rise rate m Fall rate m Number of reversals No 111.5 Number of reversals 0.574 Fall rate 0.003 Rise rate High pulse duration 0.029 High pulse count Low pulse duration 0.068 Low pulse count 0.132 Base flow index Date of minimum Date of maximum 0.817 Number of zero days 0.690 90 day maximum 7 day maximum 30 day maximum 1 day maximum 3 day maximum 90 day minimum 30 day minimum 7 day minimum 3 day minimum Aug Sep 1 day minimum Jul Jun May Apr Mar Feb Jan Dec Nov Oct Drainage area [km STREAMFLOWINDICATORSPeriod of Analysis: KOMATI 1970–2011 (42 X1H003 years) – TONGA 1970–2011 (42 years) X2H016 – TENBOSH 1988–2011 (24 years) CROCODILE X3H015 – LOWER SABIE 1983–2011 (28 years) X2H036 – KOMATIPOORT SABIE E43 – MAGUDE 1970–2011 (42 years) INCOMATI INCOMATI ∗ trends at 95 % confidence level. Table 7. Table 6. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | S S S " " " 0 0 0 ' ' ' 0 0 0 ° ° ° 5 6 4 2 2 2 e E E " " 0 0 u ' ' 0 0 ° ° 3 3 q 3 3 0 i 1 P ected by the b " ) 3 s 6 r ff P e i " ) t m t e a a m m o z l 3 s o i

4 #

E 2012 e c o 0 K

2011 1969 p Witklip 0 n

W W W

1 o

2010 1968

r M

2009

e 1967

2008 1966

e w

2007

o 1965

2006 i 1964 L

2005 1963

a e

o 2004 1962 1 Nooitgedacht t s

M N N

t 2003 8 1961 o

P t e

2002 " ) 1960

n n

i 2001 1959 a Klipkopje

s K K K K K

0 2000 1958 G Inyaka Maguga, U

5 U

M M I I I

1999 R 1957 a

1998 L 1956 I M

E E E

D " " 1997 1955 6 Driekoppies N 0 0 ' ' 3

3 A

0 0 0 1996 2 1954 K 5 # ° ° E # W H 1 E

O 2 2

E 2 K 0 1995 # 1953 3 3 R 5 R 6 # X H

1 T 3 1994 1952 S 2 A 0 " )

X T

I 1993 1951 A Ngodwana " ) 2 F

T X

3 1992 " ) 1950 A 0

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1991 H 1949

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1990 X 1948 A

Z 1989 1947 6 Corrumana 0 N U 4

A K 0 1988 1946 B U H

R 2 1987 K 1945 E X S

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V 1986 E 1944 I " ) # 1

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2 1985 1 1943 S 0 X

# R E 1984 1942 Kwena H Longmere n H E 3

N 1

L L K K K K K L L L K

V X 1983 N 1941 I X a K

A 8 P R

A 1982 2 1940 0 K l O 2

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K 0 1981 1939 # Transf Mhlume P i L H A

8912 8911 S H

e 3

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2 U i 1980 X 1938 I P R z G X (

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N 1978 1936 R 3 E 4 A " ) S

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h K w 2

H c 1976 " ) 1934 O X 6 3 t

B i X

S 1975 0 1933 1 T S 1 # 1 6 #

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C 3 H " ) 1973 S 1931 O o 1 E E 2 S X " "

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0 O R Primkop 1970 X 1928 0 S # H M A H 0

T P P P P P 8 1 I A E H 0 C X 4 P S # 2 M 0 A 2 S 0 P X K H 0 ) M 1 A L # " ) " ) 2 2 1 L 3 0 H " ) A A # 0 0 X 0 2 O H 0 ® 0 K 0 X 2 P # # H H ( H " ) 3 X

3 4 3 3 1 Developments S 1 X X 0 X A 0 # H # # A 5 H 2 L 1 2 X 0 P X H D 2 A X B 6 # " ) 1 0 e H l 1 i X d 7 Incomati River @ Magude data continuous Good data data/no Missing limit gaps/gauge data Major gaps data Minor Swartkoppiesspruit @ Kindergoed @ Swartkoppiesspruit Incomati River @ Magude (Continued) Place Kindergoed @ Swartkoppiesspruit Place Komati River @ Tonga Mlumati River @ Lomati Doornpoort @ Buffelspruit Mtsoli River @ Diepgezet Nels River @ Boschrand Krokodil River @ Karino Hooggenoeg @ River Komati Komati River @ Tonga Sabie River @ Sabie Klein Sabie River @ Sabie Mac-Mac River @ Geelhoutboom Rust De @ River Noordsand Farm Perry's @ River Sabie Sand River @ Exeter Marite River @ Injaka Komati River @ Hooggenoeg @ River Komati Sabie River @ Sabie Klein Sabie River @ Sabie Mac-Mac River @ Geelhoutboom Rust De @ River Noordsand Farm Perry's @ River Sabie Sand River @ Exeter Marite River @ Injaka Sabie River @ Lower Sabie Rest Camp Sabie River @ Kruger Gate Incomati River @ Ressano Garcia Mlumati River @ Lomati Queens River @ Sassenheim Noordkaap River @ Bellevue Elands River @ Geluk Geluk @ Spruit Dawsons Krokodil River @ Montrose Sudwalaskraal @ Houtbosloop Lindenau @ River Elands Krokodil River @ Tenbosch Doornpoort @ Buffelspruit Mtsoli River @ Diepgezet Nels River @ Boschrand Krokodil River @ Karino Queens River @ Sassenheim Noordkaap River @ Bellevue Elands River @ Geluk Geluk @ Spruit Dawsons Krokodil River @ Montrose Sudwalaskraal @ Houtbosloop Lindenau @ River Elands Krokodil River @ Tenbosch Kaap River @ Dolton Glenthorpe @ River Suidkaap Drift Bornmans @ River Suidkaap Krokodil River @ Weltevrede Komati River @ Komatipoort Kaap River @ Dolton Glenthorpe @ River Suidkaap Drift Bornmans @ River Suidkaap Krokodil River @ Weltevrede Komati River @ Komatipoort Krokodil River @ Riverside Krokodil River @ Riverside Sabie River @ Lower Sabie Rest Camp Sabie River @ Kruger Gate Incomati River @ Ressano Garcia 4 o 0 # 1 H c s 1 s 2 t 0 o X n k i m s H r r r X1H003 X1H014 X1H016 X1H021 X2H005 X2H006 Station X1H001 X1H003 X2H047 X3H001 X3H002 X3H003 X3H004 X3H006 X3H008 X3H011 E43 Stations Stations Incomati Station X1H001 X2H047 X3H001 X3H002 X3H003 X3H004 X3H006 X3H008 X3H011 X3H015 X3H021 E23 E43 X1H014 X2H008 X2H010 X2H011 X2H012 X2H013 X2H014 X2H015 X2H016 X1H016 X1H021 X2H005 X2H006 X2H008 X2H010 X2H011 X2H012 X2H013 X2H014 X2H015 X2H016 X2H022 X2H024 X2H031 X2H032 X2H036 X2H022 X2H024 X2H031 X2H032 X2H036 X2H046 X2H046 X3H015 X3H021 E23 e 2 t e n e a X t C a o m d # s i P r t

# h y l " ) 2 s P m o a c s 1 a t t n R

0 B o s r n a

O o

H l i e c o 2 D t c K i

a i v t 3 X O a i r y n t t r a 7 D r

s o i i A e 2 a i

t t N l t H

l 2 d a a r m 0

a C E E

a : " " n e o s : A f

n 0 0 m m

' ' r o r g M n h 0 0 Map of location of the study area, illustrating the main sub-catchments, the hydro- o o i m c d Streamﬂow data used on this study, with indication of time series length, data qual- ° ° w e u g t c c 0 0 a y a i e r o d 3 3 n n n R H I I S I D K H L n e e u M l g E " ) # a e L D V S S S " " " 0 0 0 ' ' ' 0 0 0 ° ° ° 5 6 4 2 2 2 developments by the initial letter of the dam. Figure 2. ity, missing data. Majorline developments on in the the year basin, they such were as commissioned; dams, indication are is on made the of top horizontal the gauges a Figure 1. metric and rainfall stations analyzed, and the basin topography and dams.

rainfall [mm a [mm rainfall ]

1 - 1 -

year moving average 0f annual annual 0f average moving year - 5 year moving average 0f annual annual 0f average moving year - 5

2000 1500 1000 500 0 2000 1500 1000 500 0 Manhica

2010 2010

Xinavane

Moamba

2011)

Krokodilbrug

2000 2000

Tsokwane

Tree Fig

Riverside

1990 1990

Skukuza

Pig Piggs

1980 Pretoriuskop 1980

8914 8913

(Pol) Bosbokrand

MACHADODORP ALKMAAR

Oorschot

1970 1970

Alkmaar

(Bos) Spitskop

Variation on Annual Rainfall per station (1950 - per station on AnnualRainfall Variation

(Bos) Mac Mac

1960

(Pol) Badplaas

Machadodorp

1950

500 1950

2500 2000 1500 1000

] a [mm Rainfall

1 -

0% 0% 400% 300% 200% 100% 100% 200% 300% 400% 400% 300% 200% 100% 100% 200% 300% 400% ------

Box plot illustrating the spatial variation of annual rainfall across the Incomati Basin Annual rainfall anomalies (blue bars), computed as the deviation from the long-term anomaly rainfall Annual anomaly rainfall Annual Figure 4. average 1950–2010 and the 5right). year moving average of annual rainfall (black line, legend on the Figure 3. (median, 25 %, 75 % arestations shown are by presented the from green west and to red east, boxes; along the the lines basin illustrate proﬁle. the range). The Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

for period

(b) September

MAGUDE

- August

July INCOMATI E43 INCOMATI

June

LOWER SABIE for period 1970–2011;

May - (a)

April SABIE X3H015

March 8916 8915

TENBOSH

- February

January

CROCODILE X2H016

December

erent indicators of streamﬂow: TONGA

- b) a) ﬀ

November

October KOMATI X1H003

9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0

Median of observed daily streamﬂow for the gauges located at the outlet of major

Trends of di 10.0 Median Streamflow [mm per month] per [mm Streamflow Median

Figure 6. Figure 5. sub-catchments Komati, Crocodile, Lower Sabie1970 and to Incomati 2011). (based on daily time series from 1950–2011. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | S S S " " " 0 0 0 ' ' ' 0 0 0 ° ° ° 5 6 4 2 2 2 e E E " " 0 0 u ' ' 0 0 ° ° q 3 3 i s 3 3 r e b t i e t m m a o l a i m # 0 K z 0 o 1 o c n M I

r e w o L 0 5 E E " " # 0 0 # ' ' 5 # 0 0 2 ° ° ! ( 2 2 3 3 # # 0 ! ( e i # b a # S d # n a # l

! ( a # i 8918 8917 h c z ! ( t i # a u r f w # o # # # # ! ( S S A E E ! ( " " # 0 0 # ' ' # 0 0 ! ( ° ° # ! ( 1 1 3 3 # # ! ( # # # # # # ! ( ! ( ! ( # ® e l i d # o i t c a o # r r e r r # b m e e o b b t C i o o s r c o t t i r r I c c O m r

i I e r

e O O s i t r

K r g I d s s m s r r e i I y n r d d e

e d r m s y e i I n n g

a l r r

E E r o m m r r e e r a " " T r r D I M e e C E

r m m

w 0 0 T T v g u s ' ' i o p p t n m l n p p t m o r g d n l n o o n a i 0 0 e l u o o a C E o d i i n r r n

o r r i t t s a ° ° n a i o n M N C a t s e e r a a C C c l a

C C n 0 0 F i a

r r l a a n n g f s l n s e u i t t m m n n 3 3 r h h e e k h e i i s a a a a e u t t n n T o r o o c s s r c s r

a a a b n i C C t a a g v a c c c i r r r e a a i u r i a u i l / / r d n n n r I D S I I B B C C C G G G I M P P R S S U W W n # e g e # ! ( L S S S " " " Land use land cover map of Incomati (ICMA, 2010; TPTC, 2011) and streamflow 0 0 0 ' ' ' Count of significant trends. Declining trends are in red and increasing trends in green. 0 0 0 ° ° ° 5 6 4 2 2 2 Figure 8. trends in the month of October. Figure 7. The size of the pie is proportional to the total number of significant trends. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Pre-Impact Flows (1949-1974) Post-Impact Flows (1978-2011) 8920 8919 X2H010 Noord Kaap Monthly Flow Alteration (1949-2011) Plot of median monthly flows for 2 periods (1949–1974 and 1978–2011) on the 1

October November December January February March April May June July August September

Plot of median monthly ﬂows for September for the entire time series (1949–2011) 1.3 1.2 1.1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 Median Flows (m3/s) Flows Median Figure 10. Noord Kaap Gauge, located on the Crocodile sub-catchment. Figure 9. on the Noord Kaap Gauge, located on the Crocodile sub-catchment. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Pre-Impact Flows (1959-1984) Post-Impact Flows (1986-2011) 8921 X2H013 Montrose Monthly Flow Alteration (1959-2011) Monthly Flow Alteration Impact of Kwena Dam (commissioned in 1984) on streamﬂows of the Crocodile

9 8 7 6 5 4 3 2 1 0

October NovemberDecember January February March April May June July August September 10 Median Flows (m3/s) Flows Median Figure 11. River, Montrose Gauge X2H013.