Characteristics and estimated onsite costs of sediment lost by runoff from Mizewa catchments, Blue Nile Basin


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Poster prepared by Getnet Taye, Enyew Adgo and Teklu Erkossa at the Nile Basin Development Challenge (NBDC) Science Workshop, Addis Ababa, Ethiopia, 9–10 July 2013

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Characteristics and estimated onsite costs of sediment lost by runoff from Mizewa catchments, Blue Nile Basin

  1. 1. Abstract This study was conductedin Mizewa watershedwhich is located in Blue Nile Basin (BNB) to quantify and characterize the suspendedsediment(SSL) and to estimateonsite financial cost of erosion in terms of yield reductiontaking maize as representativecrop. For this purpose,discharge measurementand runoff samplingwas madeduring the rainy seasonof 2011 at the outletof three subwatersheds(lower Mizewa (MZ 0), UpperMizewa (MZ 1) andGindenewur(GN 0)). The samples were filtered to separate the sediment which was sub sampled for determinationof suspended sediment concentration(SSC), total Kjeldal nitrogen (TN),organic carbon (OC),NO 3 -,NH 4 +and available phosphorous(P) content. The onsite cost of erosion was estimatedbasedon productivity changeapproach(PCA) focusingon available NP losses. The resultrevealedthattheSSC andits NP contentvaried in spaceandtime, in which lower SSC occurredtowardstheendof therainy season. The meanseasonaldischargewas found to be 2.12±0.75,1.49±0.52 and 0.57±0.20 m3/sec at MZ0, MZ1 and GN0 stationsin thatorder while the correspondingsedimentconcentrationwas 510±370 mg/l, 230±190 mg/l and 370±220 mg/l. This lead to the total suspendedsedimentloss (SSL) of 4 ton/ha/year,2 ton/ha/yearand3 ton/ha/yearfrom therespectivesubwatersheds. The on-site financial cost due to N and P lost associatedwith SSL was estimatedto be 200$/ha, 186$/ha and 227$/ha from MZ0, MZ1 andGN0 watershedsrespectively. The studyrevealedthattheeconomicimpactsof soil erosion which is variable based on the characteristics of the land resources and management practicesdeservedueattention. The result may helpin sensitizingbothfarmers anddecisionmakers abouttherisk of soil erosionandin targetingmanagementpracticestoovercomethechallenges. Keywords : Blue Nile basin, Soil Erosion, Runoff, Sedimentconcentration,Nutrientloss Introduction Blue Nile Basin is heavily affected by land degradation problems. Overpopulation, poor cultivation and land use practices are the major cause, which resulting in significant loss of soil fertility, rapid degradation of the natural eco-systems, significant sediment and nutrient depositions in lakes and reservoirs (Tamene et. al,2006).To supplement rainfed agriculture with irrigation, a massive surface water harvesting effort has been undertaken in the dry lands of Ethiopia in the last few years. However, most of the water harvesting schemes is under serious siltation and dry up (Amanul, 2009) due to upstream land degradation mainly soil erosion. Circumstances in turn lead to a reduction of productivity because of risky land use exercise. This study was conducted in Mizewa catchment to determine loss of SSL with associated nutrients in runoff, input to the NBDC Program on Water and Food being implemented in the BNB. The result was helpful for estimating productivity loss and corresponding economic cost which provide crucial evidence to inform the land users and policy makers to take actions. Taking this into considerations, it is essential to design and implement suitable land management practices to curtail optimum utilizations of resources. Therefore, this study was conducted to quantify suspended sediment as well as nutrient loss and to estimate impact of nutrient lost on crop yield along with its financial cost in Mizewa catchments. Results & Discussion The averagedischargewas 2.12±0.75, 1.49±0.52 and 0.57±0.20 m3/sec with total flow volume of 18.34(106m3), 12.87(106m3), and4.92(106m3) per seasonat MZ0, MZ1 andGN0 rivers respectively. Peak daily dischargewas observedaroundAugust17- August26 in thethreestations,may bedueto excess in saturationand full vegetationland coverage. Mean flow rate was statistically significant betweensites (t=2.68 andP≤0.025 betweenMZ0 andMZ0, t = 6.58 andP≤0.000 betweenMZ0 and GN0 andt=5.54 andP≤0.000 betweenMZ1 andGN0 rivers. Mean SSC duringtherainy seasonwas 510±370 mg/l, 230±190 mg/land370±220 mg/lfrom MZ0, MZ1 andGN0 stationsrespectivelyandsignificant variationswas observedbetweentimeandspace. In MZ0 mean SSC varied from 67 mg/l to 900 mg/l per decade. SSC coefficient of variation betweenperiodswas 73%, 82 % and 61% for MZ0, MZ1 and GN0 stations,respectively implying thatSSC in MZ1 was morevariable over timethanMZ0 andGN0 rivers. Statistical testfor temporal and spatial variability of mean SSC (mg/l) over decades has shown that there is a significant variation betweenperiods(F=4.51 andp≤0.0032) andsites (F=5.61 andp≤0.013) betweenthethree sites. From thegeneraltrendof hysteresisloop, it is possibleto concludefor MZ0 andMZ1 stations for a given runoff discharge,lower SSC values occur towardstheendof therainy seasonthanat the beginning. This may be due to an increase in vegetationcover which decreasedsedimentsources; though,dischargehas positive correlation to SSC (Amanuel, 2009). Walling (1977) indicatedthat scatterSSC –Q relationshipis typical of ‘supply-limited’ or sedimentsourcesconditionsin its upper catchmentswhich can be explainedby clockwise hysteresis effects of sedimenttransportsystems. This is mostly attributedto sedimentdepletionin upperslopesof a basin, sometimesevenbeforethe runoff has peakedsedimentis derivedfrom thebedandbanksof thechannelor areasadjacentto the channel(Ongley,1996). GN0 stationdisplay counterclockwisehysteresisloop early in runoff (from D1 to D4) reversing to clockwise afterward. This may be causedby a variety of factors relatedto sedimentsourcesanddischargeconditions; initial sedimentcontributionfrom thestreambedandits banks, a delayedcontributionof sedimentfrom subcatchmentandoccurrenceof dry periods(Seeger etal., 2004). Mean clay, silt andfine sandcontentof sedimentwas 42±10, 39±5, 20±15% for MZ0; 37±13, 36±4, 27±17% for MZ1 and40±1138±3, 22±15 % for GN0 stationrespectively. In this studyconcentration of silt and clay have a decreasing trained with time; while, the proportionof fine sand in the sedimentincreasestowardsendof runoff sedimentmonitoringseasons(Amanul,2009). Particle size was highly relatedto thesedimentloss, this is becausetheactive fractionof sedimentis usually cited as thatportionwhich is smaller than63µm (silt + clay) (Lal, 998). Statistically textural contentof suspendedsedimentwas not significant (P<=0.05) betweenthe stations. Significant correlation of sedimenttexture was observed with all NC and SSC in all stations. This implies that fine soil particles play greatrole in theprocessof erosionin thewatershed(Lal, 1998); reflects therate and severity of erosion in the study watershedand it was a challenge for the livelihood of the poor farmers. This is because nutrients are strongly adsorbed to the finer soil fractions, which are preferentiallytransportedby thesedimentationprocessesbecauseof theirhighspecific surface areas (Haregeweynet al.2008). Mean soil loss from MZ0 catchmentusing RUSEL modelwas estimated to be13.21 ton/ha/year,nearly 80 % of soil loss was from 15 - 50 % slopeclass dominatedby finger millet, nigger seed and teff cultivation, and this is above tolerable soil los limit in Ethiopia. Cultivated land use system contributingmore than 60% of total soil los (mean=20.4 ton/ha/year) which was about1.5 timesmeanannualsoil loss ratein Mizewa. Seasonal OC concentration was 23.8±10.1 g/kg(CV=42%) in MZ0 (Fig.2.a), 19.76±9.44 g/kg(CV=48%) in MZ1 (Fig.2.b) and 10.37±6.12 g/kg (CV= 59%) in GN0 (Fig.2.c) monitoring stations. This OC lost revealedthatarea specific organiccarbonloss of 97 kg/ha,35 kg/haand30.4 kg/ha from the respective watersheds. This may result in a serious detrimental effect land productivityin bothshortandlong termsin which threateningthefood security of thelocal people, this is becausein the process of erosion, loss of OC leads to depletionof soil and other nutrients associated with the organic fraction (Lal, 1998). In addition to OC loss, TN concentrationsin suspendedsedimentwas vary from 0.43 g/kg in MZ1 (Fig.2b) to 4.46 g/kg at MZ0 (Fig.2a) with meanvalue of 2.05±0.87 in MZ0 (CV= 42%), 1.68±0.85 in MZ1 (CV= 50%) and0.88±0.47 in GN0 (CV= 54%) stations. Area specific TN lost throughrunoff sedimentin each monitoringstationwas 8.4 kg/ha at MZ0, 3.1 kg/ha at MZ1 and 2.5 kg/ha at GN0 only in monitoringperiod. Significant plantavailable nutrientswere lost in associatedwith runoff and sediment. Mean area specific plant available NP lost was (2.3 kg N/ha, 4.0 kg P2O5/ha), (1.6 kg N/ha, 4.1 kgP2O5/ha) and(2.3 kg N/ha, 4.8 kgP2O5/ha) from MZ0, MZ1 and GN0 catchmentsrespectively. Statically, there was a clear difference in the concentrationof sedimentnitrate(F=6.23, p=0.006) and NH4 + (F=3.85, p=0.034) across stationsduring the study period. There was no temporalvariation in available plantnutrient concentrationregardlessof thestationsexceptonly for soluble phosphate(F=10.47, p≤0.000). This available nutrientspecies compositionand magnitudevaried widely within the watershedwhich could be causedby several factors thatneedsfurther researchand detail data to come up the with controlvariablesfor thesedifferencesamongstations. In this study, plant available N and P lost throughrunoff suspendedsedimentwas responsiblefor significant economic onsite costs, and this was reflected in maize grain yield reduction during monitoringseason. Regression equationsd betweenmaize grain yield and additional N and P2O5 application based on Tilahun Tadesse (2007) data source was used as a bridge to link soil nutrientlost with grain yield loss of maize crop. R2 (in theequationsshowsa wide variationof yield responseto thealmostequivalentamountof fertilizer level. The show thatmeangrain yield with no P andN fertilizers were 2691kg/haand2537kg/ha,respectively. Correspondingly,thelost netmaize grain yield due to the loss of available N and P were (134 kg/ha, 320 kg/ha, total 453 kg/ha) from MZ0, (93 kg/ha, 328 kg/ha, total421 kg/ha) from MZ1 and(134 kg/ha,382 kg/ha, total453 kg/ha) from GN0 watersheds. Taking 20 quintal/ha averagemaize grain yield productivityin thestudyarea (accordingto CSA, 2011), thelost maize yield dueto available N andP2O5 account23%, 21% and 26% productivity reductionfrom MZ0, MZ1 and GN0 watershedscorrespondingly. This effect of soil erosionon grain yield is abovetheestimatesof (Helmecke, 2009) cereal (10%), pulse(5%) and root (12%) crops productionloss estimatedat global scale. As a result a farm enterprisehaving a hectareof landwith maize cultivationin thestudyareahas a profit loss of about200$/hafrom MZ0, 186$/hafrom MZ1 and227$/hafrom GN0 watershedin consequenceof plantavailable N andP lost throughrunoff soil erosionprocessonly in oneparticularrainy season. CHARACTERISTICS AND ESTIMATED ONSITE COSTS OF SEDIMENT LOST BY RUNOFF FROM MIZEWA CATCHMENTS, BLUE NILE BASIN CHARACTERISTICS AND ESTIMATED ONSITE COSTS OF SEDIMENT LOST BY RUNOFF FROM MIZEWA CATCHMENTS, BLUE NILE BASIN Getnet Taye 1, Enyew Adgo 1, Teklu Erkossa 2 1 Bahir Dar University, collage of Agriculture and Environmental science, P.O.Box 78, 2 International Water Management Institute, Adiss Ababa, Ethiopia, P.O.Box 5689 Getnet Taye 1, Enyew Adgo 1, Teklu Erkossa 2 1 Bahir Dar University, collage of Agriculture and Environmental science, P.O.Box 78, 2 International Water Management Institute, Adiss Ababa, Ethiopia, P.O.Box 5689 Methods The study was conductedat Mizewa catchment; Fogera, Northwest of Ethiopia, drained by Mizewa River a tributaryof the Rib River thatfeeds to Lake Tana; covering a total area of 2664 ha, located between latitude 11.88°–11.94°N and longitude 37.78°-37.86°E. Chromic- Luvisols,Chromic Vertisols and Leptosols are the most common soil types with basaltic rock formations(Birhanu,2012). Mixed crop-livestock farming system with maize, rice, finger millet, teff, groundnutand barley are the principal crops grown in the area (Birhanu,2012). Urea and DAP are the commonly used chemical fertilizers. Mizewa lie between1852m and 2360m, dominatedby hill to rolling undulatingplain land forms and characterizedby unimodal rain fall (mean,1204mm) pattern,peaksaroundAugust 20th.Mean annualtemperaturerangesfrom 16.730C to19.320C. Flow height(h), surface flow velocity (Vs) measurementand suspendedsedimentsamplingwere conductedat thethreemonitoringstationsthreetimes a day from July8, 2011 throughOctober16, 2011 to calculate discharge (Q), suspendedsedimentconcentration(SSC), suspendedsediment load (SSL), nutrientconcentration(NC) and nutrientloss (NL) . Fertilizer maize grain yield (GY) response data were obtained from research results under similar agro-ecological conditions. Surface flow velocity was measuredusing a plastic bottleand convertedto the averagevelocity (V) using Graff methoda (1996). Record of h was convertedinto flow cross-sectional area (A) usingan empirical relationshipb betweenh andA. The volumeof water(Q) passinga cross section per unit of time was calculated using the area-velocity methodc (Hudson, 1993). Sample runoff sedimentwas bulkedin to oneas decade(D) accordingto thedateof samplingstartingfrom July8, 2011 throughOctober 16, 2011 in order to have enoughsedimentfor laboratoryanalysis and to reducecost of laboratory. A compositesub-sampleof onelitter was takenfrom bulkedsamplesfor analysis. In the laboratory, the decade runoff sediment sample was filtered using Whatman (0.42mm) filter paper to have SSC . The filtered water was analyzed for dissolved nitrate and dissolved phosphate. The sedimentleft on the filter paperwas air dried and weightedto analyze texture,OC, TN, NO- 3, NH+ 4, andavailable P concentration. In laboratory,OC was assessedusing Walkley and Black (1934), texture of sediment was determined using hydrometer method following Sahlemedhin and Taye (2000), Jackson (1958) method was used for TN, while Gregorich and Ellert(1993) methodwas applied for NO- 3 and NH+ 4 analysis and Olsen (1954) procedurewas applied for available P. Dissolved nitrate and dissolved Phosphatewere determinedusingspectrophotometer(Bache andWilliams, 1971). Load of sediment(SSL), load of dissolved NO3 -and PO4 3- load was productof Q(m3/D) and their concentrationin mg/l. Sediment boundedloads of OC, TN, NH4 +, NO3 - andavailable P was theproductof mg/kgof each species with SSL massin Kg/D. Seasonalloadwas thesumof 10 decadesof eachspecies. RUSLE modelestablishedby Wischmeier andSmith (1978) was appliedto identify hotspotareas for sedimentsources. Hysteresis loop was developingto assess the temporaleffect on sediment and dischargeinteractionover time. Productivity changeapproach(PCA) techniqueBojo (1995) was used to estimate on-site cost of soil erosion. Available NP lost with runoff suspended sediment,NP fertilizers responseof maize GY andmarketprice of GY werethebasic datasources for evaluatingthecost of nutrientloss throughrunoff soil erosion. Effect of soil loss on crop yield andits onsitefinancial cost estimationwas calculatedtakingtheloss of available NP nutrientsand puta value onit usingtheequivalentestimatednetmaize grain yield loss. Effect on cropyield was simply calculatedas thenetgrain yield lost betweenpotentialgrain yield dueto lost available NP onfittingcurve andmeangrainyield with noNP fertilizers. Statistical comparisons were performed using SPSS 16. Analyses were performed to make comparison with in groups of runoff sediment and nutrient loss between sites and decades. Significance differences in sedimentload, rate of discharge, and nutrientloss betweensites was determinedby t-test at 95% confidence limit. Pearson correlation analysis was done for effect analysis amongsedimentparameters. Conclusions & Recommendations During water which understand during study downstream The OC/ha, 3 2 GN transport, measuring sediment The characterized great and the indicated the though natural This and MZ to nutrient considered The an same study benefit letting measures, Therefore national to impact productivity expedite prevent Acknowledgements This Challenge References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. Conclusions & Recommendations During the monitoringperiod 18.34x106m3, 12.87x106m3 and 4.92x106m3 of water was lost from MZ0, MZ1 and GN0 watershedsin the form of runoff which has a potentialto irrigate a significant hectareof land, so thatonecould understandthe valuable benefits gained by farmers if this water was used duringdry seasonthroughwaterharvestingtechnologiesthoughit needsdetail study for recommendations,as the off-site costs from sedimentationand other downstreamimpactswerenotinvestigatedin this paper. The meanSSL of 4 ton/ha,2 ton/haand 3 ton/hain associationwith ((97 kg OC/ha, 8.4 kg TN/ha, 2.3 kg available N/ha, and4 kg P2O5/ha), (35 kg OC/ha, 3.1 kg TN/ha, 1.6 kg available N/ha, and4.1 kg P2O5/ha) and(30.4 kg OC/ha, 2.5 kg TN/ha, 2.3 kg available N/ha, and4.8 kg P2O5/ha)) from MZ0, MZ1 and GN0 watershedsrespectively. The sediment lost did not consider bed-load transport, which might be important in the Mizewa catchments. Hence, measuringbedload in futureis importantin orderto obtainmorerealistic total sedimentandnutrientloadcalculation. The relationshipbetweendischarge and suspendedsedimentconcentrationis characterizedby clockwise hysteresis for MZ0 and MZ1 stations, despitethe great differences betweenthe decades,i.e. differences in terms of pre-decade anddecade. Estimatedsedimentloss (RUSEL, 13.2 ton/ha/year)dataregarding the loss of SSL and associated plant nutrientsduring the monitoringperiod indicatedthattheridges of MZ1 andGN0 rivers alongwith themiddlepartof thewatershedandlower partof MZ0 werethemostcritical sourceof sediment; thoughit needsfurther investigationas of the complex interactionof multiple naturalandanthropogenicfactors. This study concludethat, a reductionin maize gain productivityof 23%, 21% and 26% and equivalentfinancial cost of 200$/ha, 186$/ha and 227$/ha from MZ0, MZ1 andGN0 catchmentsrespectivelywas estimated. However, in order to obtain a better picture of erosion impacts in the area, studies on other nutrient losses like calcium and magnesium, off-site effects need to be considered. The study also recommenda detail study as of runoff water harvestingalso is an opportunityfor enhancingrural livelihoods and food security and at the same time minimizes the risk of erosion in the Mizewa watershedsand as the study translatesthe onsiteeffect of soil erosion into economicterms; this will benefitthe understandingof the problemby land users and/orpolicy makers, letting them see the need to promote and/or implement soil conservation measures,as thatis thelanguagethattheyusually understandbest. Therefore, the researcher recommends considering cost of soil erosion in nationaleconomyaccountingis importantto show significance of soil erosion to policy makers andto land users; evenif, moreeconomicandenvironmental impact analyses at the country level are neededto help set priorities for land productivityissues, to assess the costs and benefitsof policy decisions, and to expedite identification of the type of investments that will be required to preventlandresourcesdegradationandincreaseproduction. Acknowledgements This paper presents findings from IWMI Nile4 project of the CGIAR ChallengeProgramonWater andFood ; Blue Nile Basin, East Africa, Ethiopia. References 1. AmanuelZ., 2009.Assessment of spatial and temporal variability of river discharge, sediment yield and sediment-fixed nutrient export inGeba river catchment, northern Ethiopia, PhD thesis, Department of Earth and Environmental Sciences, K.U. Leuven. 2. Bache,B.W.and Williams, E.G. 1971.Aphosphatesorptionindex for soils. J. Soil Sci. 22: 289–301. 3. Birhanu Zemadin, Matthew McCartney, and Bharat Sharma, 2012. Establishing Hydrological and Meteorological Monitoring Networks in Jeldu, Diga and FogeraDistricts of theBlue Nile Basin, Ethiopia. IWMI . 4. Bojo J., 1995. Land degradation and rehabilitation in Ethiopia, a reassessment. AFTES Working Paper No. 17. The World Bank, WashingtonDC. 5. CSA, 2011.Central Statistical Agency of Ethiopia Agricultural Sample Survey 2010; Volume I: ReportonArea andProductionof Crops. 6. Graff de J. 1996. The Price of Soil Erosion: An Economic Evaluation of Soil Conservationand WatershedDevelopment. PhD Thesis. Agricultural University; Wageningen. 7. Gregorich, E.G. and Ellert, B.H. 1993. Light fraction and macroorganic matterin mineralsoils. In M.R. Carter, Ed., Soil SamplingandMethodsof Analysis. Canadian Society of Soil Science. Lewis Publishers, Boca Raton, FL, pp. 397–407. 8. Haregeweyn, N., Poesen, J., Deckers,J., Nyssen, J., Haile, M., Govers, G.,Verstraeten, G., Moeyersons, J., 2008a. Sediment-boundnutrientexport from micro-dam catchmentsin Northern Ethiopia. Land degradationand Development,19: 136-152. 9. Hudson, H. R., 2003. A case study of approachesfor determiningdiffuse suspendedsediment sources and processes. In R. F. Hadley, & E. D. Ongley, Sediment and the environment(p.85–94). Wallingford: IAHS (PublicationNo. 184). 10. LAL, R. 1998. Soil Erosion Research Methods,2d edition,St. Lucie Press, Delray Beach, FL, 340 pp. 11. Ongley E., 1996. Water Quality Monitoring - A Practical Guide to the Design andImplementationof FreshwaterQuality Studies andMonitoring Programmes. United Nations EnvironmentProgramand theWorld Health Organization. 12. SahilemedhinSertsu and Taye Bekele, 2000. Determinationof inorganic nitrogen, Procedures for soil and plant analysis. Ethiopian Agricultural Research Organization.Addis Ababa, Ethiopia. 13. Seeger,M., Errea, M.P., Begueria, S.,Marti, C., Garzia-Ruiz, J.M., Arnaez, J., 2004. Catchment soil moisture and rainfall characteristics as determinantfactorsfor discharge/suspendedsedimenthystereticloopsin a small headwatercatchmentin theSpanish Pyrenees. Journal of Hydrology 288, 299–311. 14. Tamene.L.,S.J.Park;R.Dikau;P.L.G.Vlek .2006.Reservoir siltation in Ethiopia: Determinates, source areas, and management options. In UNESCO -Chair in water resource proceedingof internationalsediment initiatives conference,12-15 Nov.2006,Khartoum, Sudan. 15. Tilahun Tadesse, Minale Liben, Alemayehu Assefa and Abreham Marie, 2007; Maize fertilizer response at the major maize growing areas of northwestEthiopia. 16. Walling D.E., 1977. Limitation of theratingcurve techniquefor estimating suspendedsediment loads, with particular reference to British rivers; InternationalAssociation of Hydrological SciencesWallingford; 3448. Nile a V=0.6*Vs, b A=5.5h2+3.6h for MZ0 , A=2.9h2+0.95h+0.05 for MZ1 andA=9.95h2+7.44h for GN0, c Q=V*A d GY =-0.29N2+58.6N+2537.3(R2=0.75) and GY= -0.55(P 2 O 5 )2+82.25P 2 O 5 +2690.7 (R2=0.88) regression equations between GY of maize to N and P 2 O 5 . This document is licensed for use under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 UnportedLicense July 2013