ssessment of soil nutrient balance approaches and methodologies docx

‘on the limited literature avaiable, so-called “enrichment factor” was established, As the finest soil particles are the ist tobe dislodged during erosion eroded soil material tends to c

Assessment of

soil nutrient balance

Approaches and methodologies

Copies of FAO publications can be requested from: SALES AND MARKETING GROUP

Assessment of

soil nutrient balance

Approaches and methodologies

14

The designation xplays a the rsa neil in th information rod de mot ipl he spec of ny option whsunerer om ce the Food and Apelor Oanation the iat Nason conccrtig he tear deren sate ol any comin ttn cy oreo fh bri srconceming he deinanton of ar busi

A its eer: Repotcion and dst of atl in ths ofemtion Jrhes bn cle or ther perteael pipest ec uae orton

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Vi le Te i CaaeleO159 Rome uy

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Contents

‘stom flows and estimations

Assumptions — their validity and rally margins

Upsealing ands validity

Soil autriencbolance study outer Mali 8

‘Sub-Saharan Aries soil utrien-halanee study, FAO, 2008 +

mm =—

'NUTMON _ nutienl monilvine [or rpisslTanaine syuens 46

Panicipatory nutrient management in sober Mali 3

‘ution balances for niche management SI

"

am

Usefulness for polgg-makers Persona = Si

‘Specific problems foreach gale level 82

aa

List of tables

1_Ausibates of land use systems and their specification 5 Tut and ouput factors governing nutrient ows in the oi 6 3._Weighting factors for calelating mineral fertilizers UNI) perTandluse Siem z Chemical composition of manure land water classes 1

5 Contibution of scattered nes and of non-sìmbioue-TxaUon1abiloais]

(6 “Base denvifcation per land water clase 0

7 Nutrient eontens of eroded soil at ree levels oT so Tei ụ

‘Average nutrient balances of some sub-Šaharan Atiiean sountie> 1B

9 Average level of NPK balances, 1995-95 19

TW Nutrient input and output flows in arable farming fa China, 1997 29

20-“Type of data required and quaniiction method Torte four np

processes employed in calculating N and P balances 2

24, Type of data requted and quantification method lor hee wpat

processis emploved in caleulaing N and P balances 59

22, Farm nutrient balances for different household groupe 33 Nutrient flows ot farm ls ‘

25 Nutrient balance for major erops 66

2 Nutrient balance and soi nutrient content ofa sa Rel 19Gh— [990 đi

25 Observed diferences between 1wo villages, Mali 69

235 Partial auient balanoes for two villages, Mali oI

230 Published values oFN ows into and out of ferilived ce ago-eosytems 0

530 Agro ecological performance indicators forfour Palippine smallholder

farm systems

3L Approximate calbes forte relative eons of Nand P alan of Tas,

tenement

Nitrogen balances for China, 1961-1997 29 E._Overal nitrogen flows for Ghana, Kenya and Mali 5

9, Nitrogen balance per km grid eel for Ghana 3

11 Nitrogen halance per crop with probable, optimistic and pessimistic views 2

12, Overview of the NUTMON approach and the role of the NUTMON toolbox a8

13, The farm concept as used in NUTMON 30

15, Participatory Learning and Action Research process 4

11 ECOPATH flow diagram of a theortcal LAA far system, ke Niba'year T0

18, Time scale of nutrient deficiencies in Baneladesh 1

9 Trends in vield and nutrient stocks for wo sil ypes 16

Preface

Agricultural intensification without adequate restoration of sil ferilty may threaten the sustainability of agriculture, Quantitative estimation of plant nutrient depletion fears sols is sell for comprehending te state of soil degradation ad for devising corrective measures Nutrent-balanee exercises serve as instruments to proside indicators ofthe sustainability of agricularal systems

‘methodolog from September 2002 to fly 2003, The electronic conference enabled insiuions

!gencies and scientists to share infrmation an exchange ideas, views and experiences on the subject background document reviewing known appeosthes and methodologies was made svalable to the participants a a starting point fr discussion,

‘omparisogs among them, and highlights he inypeovements made al he sex that ae stil 10 beaddresed categorizes case stlies into macrolel,mesoleel and mictoleve lasses The meratevel i used for national continental and global farmng-system levels The mesolevel coincides with the evel ofthe province, district and agro-eeological one, The micrlevel is largely defined asthe frm or village level Por each case, the sty explains the methodological spproaches, the elements of the nutrient balance, and the calculation ofthe sutient flows Furthermore it als discusses knowledge gaps and caveats that wattatatention

Acknowlegements

‘This document has benefited from contributions made by participants daring the electronic

Their contributions are highly acknowledged, Special thanks are extended to RIN, Roy and RN Mise for their contribution tothe conceptalization, organization

‘ofthe electron conference and initiation ofthis eview Thanks are due oJ Poulisse for his caontrutive suggestions Thanks are also duc to EIMA, Smaling and J.P Lesschen le thee suggestions and conteibutions

conference on the suhje

Executive summary

Soil nutrientbolance eversises based on sate modelling systems and lingat upscaling ave {devoid ofthe dynamies and the imeracting proveses involved Methodological estimations are ugh with problems such as mized dats availability at spatial scales, seale-pecitic spatial

‘aiation of rutient-blanee input data, no-liserityin upscaling, and ack of reliable upscaling techniques Eatraolating present balances into the future and ensuring thei saliity forthe Faure presents practical problems Ther ss nes fora mone simple and reliable madel‘spproach

‘that is readily saplable to various situations tn spite of various kiniations, nutrient-balsnee assessments do delineate the consequences of arming fe soi etlity, OF farther release is their emergence asa reliable tol lor devising time-wale soil Fertility interventions based ona sound poly framework

‘The mesolevel offers a suitable entry point for policy interventions

Although macroleel uncertainties ned to be minimized and validations improved tmay'not

be possible to validate all the nulrient flows: one ean Focus om valida

regarded as most important A purticipaory approach forthe development and validation of locally specitie packages needs to be promoted Larger pools and volumes of data may facilitate refinement ofthe models and make them more scalable,

Presentation of the assessment outcomes in Lerms of yield loss oF monetary values enables policy-makers to understand the issues more readily Programmes to assist national

"novermmenis in enhancing their socio-economic and policy envisiment for sil mproensent (ith the alm of promoting productive and sustainable agriculture) would be ptoen and desirable proposition,

cee Cation exchange epaciy

CMDE Compagnie Malienne our le Dveloppement des Textiles DEM Digital levaton model

EUROSTAT — Susilo ofthe European Communities

Fes Farmer fed schoo!

FSU Farm seston wit

ais Geographic information sytem

IAA Integrated agriculture aguacultice

{GRAF international Center for Research in Agroforestry

tev loterational Ferilzer Development Center

aR) Intemational Livestock Research neue

NM Integrated natrent management

ISRIC Internation Sit Reference and Infomation Cente

NUTMON Natit monitoring

ECD Organisation fr Economic Co-operation and De

P Phosphionis

Per Potent erapranspiation

PLAR ———Paricipatoryleming and ection research

Pru Primary production unt

PRA, Pansipotor rural appraisal

QUEFTS —Quanatve Evaluation ofthe Feri of Feopical Soils

Ru Redisnbution unit

s Sulphur

Sau Sevonary prodveton anit

SSA Sub Shhann Afries

USLE Univers Soi Los Equation

WISE World Inventory of Sol Emission potentials database

iaments to provide indicators forte stssinaility oF agricultural ystems, Nutrient

‘but and ntrient-halance approaches have been applied widely in recent years, Stdies have

‘heen undertaken ata varity of levels: plot, farm, reson national and continent Widespre

‘oceurene of ratrent mining and sil fenility decline has been reported

“questions remain concerning the validity of such assumptions, tei reliably nd heircapablty

tw provide insight into dynarsi processes and lend support fr extrapolation Also pertinent is

‘the iste as 10 which new approaches’ directions, investigations an extra eons are required and feasible i onda w enhance the validity ofthe assumptions and ndings Questions hae

‘been raise as to whether nutrient budgets provide te information requited for understanding the stalus and dynansis of soil fertility across farming systems and whether such analysis

‘may provide reliable direction and support to poliey formulation on sil Fertility management (Senone and Touhnin, 1998),

‘Spsris AND TEMPORAL CONTENT

‘Spatial and temporal variations in autient ows and budget estiosations ate impertant For assessment proses, itm usta considered a unit even though farms comprise dierent

‘ilaypeentiis and management regimes, Landscapesare often charcteiza hy theirdiversiy interms of physical atibutesand manggement Costeating sil slopes drainage patter and ưep husbandry stations are encountered in indivi watersheds Diversity at vil

isalso evident While field budgets could be ncpative, mainly because of exop harvest

‘urient budgets may tam positive a village level because of reasons sch as manure imports,

In agropastoral stings, the lationship betwen crop and rangeland becomes mone important, tiêm to model such systems ate fraught with problems und eompesities especialy in the

‘context oF assumptions but variables,

In spite of sch spatial and temporal dienensions, most stades opt fr “quichfind” exercises

‘based on averages, which may hase Fit relevanice to the rei picture Thus, sampling becomes

‘eri ctor and one beset with problems for nutren-budget exercises In addition to soi

2 Avsessmen fl marie balance appraches and mediates

‘management factors, identification ofthe major land types, landscapes an thee variability is

‘crucial to reliable sampling procedure simple summing-up of areas covered by major soil {types may not provide the attibuies ofthe diversity that exists in the farming systems

SysTEN fous ayn ESTIMATIONS

tdent' inputs and outputs in various subcomponents ofa hounded system is

‘the nial step in most nteient-udget exercises, The system boundary, ls subcomponents and

‘the various nutrient inputs and ourpurs are define

‘exercises, whereby balances are calculated through summing totals for each of the nutrients

"— VALADIY AND RELIABILETY

Nutrent-budget and n slance models have wo rely ona series oF assumptions i onder

to deal with complex nutrient systems, Many nutrient budgeting exercises teat soil<dynamics processes asa “black bow" The basi data for nutrient inputs and oulpts are usualy selected From literature and praduction statistics, Data from literature pertain to various sites, but may not nocessrily be representative for the selected area, Some studies base thee calculations

‘on secondary’ data derived From eemtain assumptions The datasources used for such analyses have diferent confidence tints attached to them, Where resource flows ate translated ino nutrient contents, uncertainties shout data estimates also arise owing to variability in

‘estimation procedures

‘The types of input and ousput data that sre relatively easy to measure inclade Rows of materials, such as fenlize, manure, erop residues and harvested grains Several of the

“environmental” variables contibuting to nurien-balance calculations have t be estimated

im sesondarylierauưe.Siailafy, value or (he expost of nutrients in the harvested produet tre usally derived from secondary data relating o yields and nutrient contents in the harvested pars, Plant species rev! substantial aritions in nutrient uptake, These depend on a namiser

ft faciors such a8 climate, sei properties and Farmers erp management Export of natients

‘in erop resides varies depending on rese management by the farmer, Which differs greatly between and within countries, A Tiited umber of systematic studies have examined the leaching of nitrogen (N) and potassium (K) Leaching losses have been estimated through rultiple regression Here again, there is scope for approximation and erors Gaseous losses refer to N and may comprise denitrification and volatilization, There are few reliable data on denitrification and volatilization for the various agro-sol-climate situations Estimates ave ben mace dsing variables and multiple regressions Processes such a erosion account for some

Df the important exports of soil natiems Substinting transfer equations trom ater studies sometioes leads to 2 wide range of resuls,

Chapter $— rraduction a

Issues oF quantification and onserainty sueround many’ of the nurient tansfes, Thể

‘methodologies fr ctu field measurements of nutrient stocks are often based on nutes in

a given soil depth increment or on the concentration of natrcns in a given depth sample The inaccuracies of the methods may reslt in mis-assessens Exact determination of differnt sal nutrient pools is dificult heeause ofthe complex, dynamic and stochastic nature of nutien- traostormation prosesses in the soil system Changes i sol nutrient stocks overtime ca be

‘measured in onder to form an idca abou the extent of oteent mining, However, many’ soil test methods donot readily reveal nutrient mining because the “available” figtion extracted

js bulered well by supply’ hom other nutrient pools as soften seen fr K Date asaibility

‘only allows fora rough estimation of rates of changes in soil nutrient stocks, I does m0 permit long-term forecasts of soil nutrient stacks, Prognoses for the effect of sol nutrient depletion

‘on Future agricultural proton ate even sae difficult establish

Urscauine avo rts vatapity

Problems arse when the scale i enlarged further toa distriet, atonal or continental scale The sggregation of nutrient lances at field level leads to farm balances Th

complexity ofthe firm system and its achiteture negatively alfects the reliably of marin balance caleulations Varios parameters introduce elements of uncertainty into the overall rutrent balance,

‘The largest unit for which soil nutrient balances can be quantified is he fel Larger spatial

‘an only be deal with through generalization and aggresations Land use spstems ina Jon are generalize into a typology with 2 known or unknossn variation Aggregations then how the generalized, lager ‘uniform’ units ate added together co yield ane overall soil autien balance forthe rgion, Aggregation isa dlcate sse as the bance ise is made lupo Several parameters that are in some cases cuteomes of regression analysis an mee basic prirameters, Mode! validation becomes ilu because af the lack of independent data sels {tha metal the input requtersents

Soct

‘Much ofthe soil uti debate jgnores the roe that farmers play in shaping the processes of

‘environmental change, Hosever despite broadly sila access escurees and opportunities,

‘marked differences often exist withina single sting n whic solely handle by different farmers Among diferent fants and hotcen ates, the relative value of lad, labour and

*apitalendossments ove ine may have important implications forthe form and efjcieney of any farm-level aunt evel

‘Non-consideration of soeio-economie aspects i nutrient budget and balance studies may lead

to the exclusion oF many relevant factors,

Although plausie solutions may be elusive, sil nutrien-balanee sedis do dlineate the

For soil erty: Whats furtberrequeed, and possibly more relevant _stme-scale plan fr extemal interventions based ona sul policy framework: this in ation 'w-a more simple and reliable mad approach thats realy adaptable to vatios stations,

an indication ofthe order of magnitude The macrlevel is used for national, continental and tlobal farming-system level The mesolevel coincides with he moxineeldierieUAEZ level Tecan also be deined as an agro-gconomic emily, eg collon-bised or dairy-based farming systems Finally, the microevel is defined as the fan o village level, bat it ean be extended

to nutrient management proup oF gender

“This report does not attempt lis al Ye mutient-halance stds from over the yeas, The selection ofthe cases is bused on the diferent approaches of nurient-balance calculations sand on thei innovaive character For the micrlevel, several cases desribe a specific niche

‘management where some feldscroplanascape units ae cherished at the expense of others Alltneselecid eases have been published in international jourals orbooks Various books and journals provide farheriormation om nutrient Balance and soil eri olted esearch Smaling, 1998; Sevones and Toulmin, 1999; Smaling, Oenema and Fresco, 1999; Vanlauve eral, 2002),

nce study, PAO, 1983-2000

“Thẻ hudy assesses the sta of soil trent depletion in sub-Saharan Africa (SSA) ai 1983 an

2000 (Stoorvogel and Smaling, 1990) Itpeovides dataon the net cemoval of the macronutrients

1 phosphorus (P) snd K fiom the raotale soil layer an a country-by-country basis

‘erly dynanmes ina LUS are governed by five input (IN) and ve naa (OUT) factors

Methodology

Assumptions had to be made for Tae

Geseribing and quantifying the Atvibutes of tang use systoms andthe specficsion

mechanisms dat comribue to the Row [Abate Socio:

of, Pand Kintoand out ofthe sil This | FA8BTR ——”RMesofmriwEimmsee)

was the pivnlal sage ofthe exercise An S0USAI4(F) Cases tt: 2st: 9-Nah iimporantdecision inthistespect was the | Warsganort iene new Aone Furie subdivision of LWVCs ino Luss |

AMLUS isdefinedasawelldfined tact | Feleerue —Waphing tae) 0-20, rte to

‘of Land with its pertineat land ase type: aa

ALUT) (FAO 1976) This study included | jana ve E0 1:0071.280180890%/0) the further assumption that an LUS is 8 | lemon Sumgaracn

Ihomogoncousentty Thisformed thehasis | Risiawerencil ot op wads nove tom te

_ Sass omasnateat

‘Table [lists theatnbues ofan LUS | Gore Nhớ

Each LWC comprises ane or more LUSS

“The desertion af an LUS is based on

relevant, county-speciti erature

At any one time a certain amount of onznie and inorganie N P and Ks preset in the sil in sable o labile plantavaiale forms, When measured ane year ae: these amounts re

‘ Ataetonet [với nunign lance approaches and methodologies

Tame? rot necessarily the same, This is besause Input and output factors governing mutant ows, arius processes cause nutes to fo ints into and out ofthe rootable soil layers In

[weet EM site the ance nature ofthe many

WT Mieateats OUT Fareed factors ating si eit, a reatvely

ne Maru đun ene | Simple mod! should serve the purpose of

Simulating the processes The five inp

eS ee ae ee: and five output factors considered in this

fmt gouges UTE cmeomtones | quấy are sted in Table? and presented

IS Secimentaton OUTS Erosion 8e

Eight factors have a clear role in

enriching (IN) or depleting (QUT) the

sl, As livestock in Afi fee largely on crop residues, the two factors IN2 and OUT2 can interact Consequently, pat ofthe erop residues is removed temporarily, to be returned later

Mineral fr

“The FAO database contained information on actual total fenilizer consumption per erop pet county for 1983 and projections for 2000 However, these dala were not specified per LWVC, Hence, the total amount needed tobe distributed over the LWCS Two situations arose:

1 The literature provided raw data onthe regional distribution of Fetlizers within a county

‘where's, these data were used

Chapter 2— Meladulogle ly hueuing si nuyiện haancex 7

2 Where such information was not Tames

available, the assumption was thatthe Wetghting factors fr ealeulating mineral fertilizers

tse of ferilizes was not distributed) ete une aya

‘evenly within a country, and each LUS [Wena — faior T] ae |

received a weighing fitoras indicated —

recor ng Ñ | Maar 2) te

ood iat (6) 10 20 Although livestock isan essential element | Somme tp a

of Afvican farming, the study did not | (eum nae

consider entensive grazing: it considered | {i sẽ 12

‘only arable land However, two forms of

‘manuring occur in the LUS desertion

Although the chemical composition of fesh manure varies widely according to its nature and moisture content, for calculation purposes it must be set at constant values for groups of LLWCs, Table 4 was constructed on the searee information available in the literature

For B), where livestock Feed an erp residues let on the fel, some of the manure input is realized ‘during grazing’ Three questions arose

1 What is the ration of the erop residues tat is waz?

2, How many hours a day do the animals spend on the grazed fc?

53, What is the faction ofthe nutrients that remains inside the animals?

“The answers were stipulated as follows

1 This differs foreach LUS and i indicated a

12 hours (xed ue fo all LUS) uch in its desertion,

10 percent (fixed value forall LUS)

8 Arsesument of wil murient blance approaches and methadoocies

Deposition (IN3)

‘The processes of wet and dry deposition supply considerable amounts of nutrients to soils Because of an uneven distribution of data over the continent, the ealeulation procedure was split into to, relating to:

1 Areas within Harmattan influence (West Africa: the literature provided sufficient point data

to allow interpolation

2 Areas outside Harmattan influence: dataon the fctors were scarce, but here wasa correlation With ainfal; regression analysis fr the different nutrients resulted in the equations listed below They were used to calculate the contribution to soil frility by FN3 for ateas outside Harmattn itlvens

Biological N fication (INA)

An important souree of Nin several agricultural systems iN, from the atmosphere Leguminous species and wetland rice draw considerably Irom this source Based on information fom the literature, thee stipulations could be presented, depending on total N demand by erops:

1 OF the total N demand of leguminous crops (soybean, groundnuts and pulses),

Contibation of scatered tees and of non- $2 Pent issuppledthrowgh symbiotic

“Symbiotic xatln to blogleal Ngon N fixation (Rhizobia

Tanwar Twat] 2 Of the total N demand of wetland rice

Aghayewl | _ CLWC, naturally flooded and irigated

To ea 7 ) 80 percent is supplied through Uncen ata + chemo-autotropic N Bxatien (Azdll sesame : ‘other algae), up toa maximum of30 kg Peiomawe > 1200 0m ae 8 bayer, Higher upakes are drain fom

: soil N, sateen 3, Allerops benefit om Nhat isixednon- amen es 4 symbiovialy (Azotobacter, Bejrinkia

and Clostridium) or by N-fixing tees

-_ ‘that ate left on the field (Rhizobia and

Methodologies for assessing soil muri lulncsx

sssumplion on the importance ofthis input fator The group of experts reached consensus on

‘nutrient balance being in equilibrium inthis LW fy and output actors were eleulated, bout the deficit (INS) was assumed tobe supplied by the Hoodwater and is sediment

In LIVC “invigated ares’ the autint content ofthe tigation water wasalso considered 30 Input factor Literature and consultations le to the assumption talon average, 300 ma yea

‘of igation water is supplied to eigated ln The ealeuation oP INS was nose governed by the concentration of the three macronatrieas in ths ammount of wa

‘his aspect indicated thatthe Following

Harvested prnduct (OUT)

Different crops withdraw different amounts ofthe varius nutints rom the soil A considerable amount of literatures available on his subject Average valu foreach crop (esclding nutes)

‘were compiled In order to obtain an estimate of OUT, these data needed 1 be combined with the production fgutes provided hy FAO

tarwa = content» yield)

Crop resis (OUT,

Án dimat ofthe amount of erup residues removed from the arable Feld was obned fom the literature I was found that Farmers’ atitudes towards utilizing crop residues dillered considerably among and within the countries studied The aca removal i given inthe LUS description, The removal ean be complete (eg used for fuel, roofing oF manutaeturing) of incomplete te grazed or hurnt) Where there Was grazing tis was mentioned inthe LUS

<eseriptio, IN2 outlines the effect of grazing oo sil Frit Buring prativs ate dificult wo portray ona continental scale Inthe std only the resides oF cotton Were assumed to Be burt completely far ressons of field ygiene, Removal oF Nand K throug burning was eloulated

in OUTS and OUTS

‘of management and thus the LU description were use The lover value ofthe ran

nutrients in residue per tonne of harvested product) rpesents 3 i h

‘whereas the higher value represents low level of management Moge favourable grainsta ratios related to genetic improvements ae th explanation for these differences To ealulate (OUT2 the formal was:

(are content * yield)

ses ama Fatoe our

“ Asesoment of i nutrient balumre qppnuachex pai mtồodologics

+eaching (OUT3)

‘Leaching isa signiieant loss mechanism for some nutrients In tropical sil, Pi often bound Viphtly by soil particles Therefor, this study assumed that leaching only played a part with respect to Nand K Research on leaching is confined mainly to point observations, which have

‘an uneven distribution over the continent These few dala ae not enough o support a model that should have a spatial significance Therefore, the iterate was reviewed extensively Together

‘wit expert consultations, ths review provide clus for corelation, Multiple regresion showed leaching wo correlate positively with:

‘© R: rainfall (annual aver

mm),

‘© sl fenlity class (1 - low: 2- moderate: 3 - high),

INI +1N2:toual application of fertilizer and manure (LUS-specifc, in kgalyear),

and negatively with

+ UN UK: total uptake of Nand KO respectively (crop and yield specifi, in kha yea, The following regression equations were found (in kilograms per hectare per yea:

ours Ẳ

ours KO)

[3+ (0.0021 + 0.0007 » F) + R-+0.3 «(INI + IN2)-0.1 * UN 16-+(0.0011 + 0.002 » F)» +05 «(INT + IN2)-0.1 «UK

Gaseous losses (OUT4)

Tame N Is lost to the atmosphere by two

"Base denitefiation perlandwater class processes denitiication and volatilization Lanai cass DBentrfesion] Denitrification takes place under anaerobic

aravea | conditions A soil does not have to be

tr ¬ entirely saturated for denitrification to cern fccur A moist soil already loses nitrate

00 through microbial processes in wet films

¬ 2 and pockets The loss through denitrification

ipa aha i is expected to be greatest in wet climates,

ad Bgdef 2 on highly fertilized and elayey soils, and thản: a for crops that withdraw relatively small [roe ở j amounts of N Ammonia volatilization

plays role mainly in alkaline environments Because such soils are not eommon in SSA,

‘olailization and denitefcaion were not rated separately

In general, information on both factors was scar and unevenly distributed Therefore, corelations were again sought, Multiple regression analysis provided the following equation For the outpt factor (in kilograms per hectare per yea):

OUTS (N)="Base’ +2.5 « F-+0.3 «(INT +IN2)-0.1 «UN

where:

"Base": a constant value, covering relative wetness of the soils specific for LWCs

(Table 6), F: soil ferility clas (1 low; - moderate; 3 - high),

INI +1N2: total application of fenilizr and manure {LUS-spccilc:n kg ha year), uy: total uptake of N (ecop and yield specifi; in ky/ha'year)

assessing so rien balances "

Erosion (OUTS)

Research ndings onsoillossthougherosion Tame 7

were reasonably well documented for most Nuttent contents of eroded sol at thre levels

SẺ se tà min ct, ae the rome gen hed re

ofeach LUS.A sol witha high fertility has ee

‘more to lose than a poor soil, Table 7 lists | ` vas 688 8g

fu pel Oth ee BH đe |3 oz yo

These classes were indicated in the LUS

description, They were also used to assess OUTS (leaching) and OUTA (gaseous oss)

‘Thedifficult part was the assessment ofthe nutrient content inthe eroded soil material Based

‘on the limited literature avaiable, so-called “enrichment factor” was established, As the finest soil particles are the ist tobe dislodged during erosion eroded soil material tends to contain

‘more nutrients than the original soil Inthe study the enrichment factor was set at 2.0 for N, and K, implying that a rato of two beeen the nutrient content ofthe eroding soil material and the nutrient content of the original soil material

Crmpping intensity

‘The FAO database provided the area values of both harvested land and total arable land for cach LLWC The rato between the two, expressed as a percentage, is alle the “etopping intensity (C) Where ths ratio was less than 100 percent, part ofthe arable land was considered

Is area was calculated a fallow

Fallow area =((100/CH - 1) = harvested area (ha) During fallow potiod, a gradual buildup of nutrients takes place, IN3, IN4and INS provide extemal contributions fo oi ett: In addition, part othe plan-avaiable nuients is retained inthe fallow biomass instead of being leached or eroded During years of falls, while the

‘ongoing processes of weathering and mineralization donot inerease the total amount of nutrients inthe soil they do replenish the labile pools ofthe nutrients

(On the other hand, woody species from a fallow ate often used asa source of fel or sokd along the roadside (OUT fllow is pay depleted by grazing animals that donot return all {hey have taken (OUTS ~IN2).and the slash and bur praties prior to cultivation enhance the loss processes OUT3-OUTS strongly: Inadltion, extra input in West rica through deposition

of dust (IN3) is offset by extra output owing othe searcty of fuelwood (OUT)

‘These considerations, combined with findings in literature and exper consultations, led

to the decision to set the nutrient input by fallow at ied values of 2 kyhayear for N 2 ke halyear for P.O,, and | kwha/year for K,0 imespectve ofthe LUS Where cropping intensity

‘equalled 100 percent, the fallow acreage was set at 0 ha Where the eropping intensity exceeded

100 percent, maine eroping took place and itwas assumed that there was no Fallow I this

Brin

Bi ver tion

case, the harvested areas and yields of the annual crops were adapted so thatthe total area

‘equalled the arable area, and the otal production remained the same

Results

“The results ofthe study showed N, Pand K balances by land use system and by country They revealed a generally downward trend in soil feility in Aftica Densely populated and hilly e0untes in the Rift Valley area (Kenya, Ethiopia, Rwanda and Malai) ha the most negative values Figuee 2), osing to high ratios of “cultivated land to “total arable land’ relatively high

‘crop yields and erosion, For SSA asa whole, the nuvient balances were: -22 kg/ha in 1983 and

26 kg/ha in 2000 for N:-2.5 kya in 1983 and -3.0 in 2000 For P; and -15 kg ban 1983 and

“19 kg/ha in 2000 foe K Table 8 lists nutrient balances for several SSA counties, The prediction For 2000 was fora more negative nutrient balance for almost all countries This was influenced

by the optimistic FAO estimates for crop production in 2000 (high OUT!) and the expected dercase in fallow areas in 2000

Discussion

Following earlier work by Pieri (1985), this study was the ist with a clearly defined nutrient balance and quantified nutrient ows It has formed the basis for most subsequent nutrient- balance studies, The basis ofthe nutrient balance with five inflows and five outlows has been used widely However, ther studies with different data availability and objetives have modified the caleulation of some flows

Chapter 2— Methodtoses for assessing sil muriem balances 2

‘Nutrient-batance studies in Africa, IFDC approach

The methodological approach used by the Intemational Fertilizer Development Center GEDC) w estimate nutrient balances, depletion rates and requirements combines information

‘on agricultural production, soil characteristics and biophysieal constraints with methods and procedures designed for making such estimates (Henao and Baanante, 1999) The information

an dal related to agricultural production include land use, popalation-supperting capacity of land, erop production, and use of mineral and organic fertilizers The approach uses attribute and geographic database systems in conjunction with empirical and mechanistic models to produce information for analyses and monitoring

‘The approach builds upon previous work on nutrient balances (Stoorvogel and Smaling 1990; Smaling and Fresco, 1993; Smaling Sloorvogel and Windmeijer, 1993) Ths building on previous work involves the linking of methods and procedures for estimating nutrient balances with attribute databases and geographic information systems (GIS) It integrates data and {information ina common geo-referenced base, and illustrates in the form of maps and graphs estimates of nutrient balances and rates of nutrient depletion from soils of agricultural Inds

a country and regional levels Figure 3 presents a lowschart of the approach used to integrate the various components into a geo-reerenced system for estimating autient depletion and rutrentrequitements

Attribute data include crop areas and levels of production, as wel as nutrient uptake fr ten rop groups that include 99 major food and industrial crops The eops include in the database sccount for about 95 percent of the total cultivated area in Aftica Uptake rates for N, Pand K for each erop a estimated using data from fed studies The database includes me series data

‘on erop production and areas for the period 1961-1995 (FAO, 1994) and on mineral fenlizer consumption by country and region for the period 1985-1995 Information on organic featlizer use and practices is also a component of the database, Combined sith information on crop

and soil management systems soil constraints, soil characteristics and imate by region and

‘country, these data have been assembled into database management system,

Methodology

A simple specification ofthe balance of nutrients (N, Pand K) in soils of agro-eeosystems ata

‘country o regional scale s given bythe following equation:

where: s the quantity of inorganic and organic nutrients remaining in the silat ime

‘m; AP, is the Soil inorganic and organic nutrients present at time f4R, isthe inorganic and organic nutrients added or retumed othe sil during the time interval Ar The RM, estimate

is the plant nutrients removed with the harvested produet and residue management during the time interval Av, and £, isthe inorganic and organie nutrients lost during the ime interval 1

‘The valve of s represents the beginning time period n presents the ending time period and Avis the time interval benween / and on

Equation | states that if the amounts of nutrients removed from the soil (outflows) are treater than the additions (inflows) ether by fertilization oF management practices, then the reservoir or stock of nutrients within the soil poo! will decline, Exact determination of diferent soil nutrient pools is ifieult because ofthe complex dynamic and stochastic nature of nutient transformation processes in the soil sytem

‘The production of erop outputs and residues is used to calculate total erop nutrient uptake From soils Nutrient depletion and requirements are assessed by calculating and using estimates of

Empirical nutrient loss models and transfer functions are estimated and used wo eaelare removal and asess nutrient losses throuzh various mechanisms and processes Furr research and improvements in dala should enhance the reliability ofthese models as predictors of nent Uransfers and losses through various processes The specification and estimation ofthese odels are described belo

Harvested product (iy

The harvest of erop outputs and removal (export) of erop residues are major mectanisms of nutrient removal Average values of N P.O, and K,O uptake were obined fom the literature and experimental data The notriest upiake (Nu in harvested product j and country # was talelated by mallplying total erop production (Cp, ) by the erop tient uptake inde (N2), fxpressed in kilograms per tonne

Chup residues (Xe)

Indices of conten of N P.O, and K,0 in ep residues were obtained from references a fle studies The nttient remosed from the sol by rop residues was caleuated by mallplying the nutrient content inthe residue (NF) by the crop preduction data (Cp) Tor countries and regions, the harvest index (1 and the approximated percentage of reside Ltt om the sal le úp hoevesting (Ref) Thus, the amount of nutrient uptake i the residue removed from sơi fora

ven erop (na country region (is determined by

where Nr represents the nutrient uptake in erop

depending on the crop prodicion valu, Estimates of the amount of resis

after harvesting and grazing were obtained rom references and country tepor's, The harvest index (FF) measures the proportion ofthe ssonomically produced part ofthe biomass this acwally harvested

Leaching of rients (ty

‘Most of he literature on nutrient aching is confined to information on point observations for Nand K which are variable and difil to extrapolate The literature reveals that N leaching

‘san be predict reliably in an Alriean environment on thế bisis of information om rafal, soil moisture coptent and nutrient cortent ofthe soils Regression madels have Been estimated

to prediet nutrient leaching at country and regional levels The generat specification of this model includes as variables the Fert ofthe sels expressed as soil eriy lass (Fe), the

6 Asse mint al hes and methdelonies

rainfall (8 for the regionisite, and the nan

a Follows ents applied (Cn), The model was specifi’

XI =a + (8, ~B, 8) Bí + B,lngHÐ +, Có e “

where: 100 < R <3 300; NF, i the amount of leaching of N oF K at ste 4 expressed

as percentage of the quantity applied: the parameter estimates a 8 B., and B, measure the effects of site manayement, sol frilly elass (Fe) rainfall (R), and matient applied in the form of mineral snd onganie sources (Cn), respectively The soil ferility class Fs included to account for de fealty and management of the sil as determined by sol classification and the availability of soil utrents This is assessed broadly as: = lon; 2~ moderate; and 3 = high,

“The patamete ¢, isthe enor associated withthe estimation ofthe mod

10 account fr oil tr an the guany of ments applied as a proxy oF N aalaiiy

‘The estima mode! use has the sme oem as that a Equation N Tose in the model ae imessred as percentage ofthe total N upaks Parameter estimates BBB an, have 3 Similar mterretation and mcaning asim Equation 4 but, fr his purpose, wih respect ta the measure of N los i)

Soil erosion Ne}

‘Theres abundant information inthe iterate on the amount of soil eroded by water in diferent areas and soil types of Aiea Many’ different Factors interact to determine the amount of sei lossoeeunrng alaparicular time and place, The Univers Soil Loss Equation (USLE) describes the impact of the most important factors (Wisehmeier and Smith, 1978), Estimates of soil srosion have been oblaned by using the USLE and available daa This madel estimates soi} tfosion in tonnes per acre per year asa unctin of fall eosivity inde, a soil erodibility factor, topographic factors of slope gradient and length, and a land cover and crop management factor The eropping and management factor is a composite of: the elfcts oF crops and crop

tillage practices and the interaction hencen these Factors and the timing of rainfall

‘ete years function ofa sil erodibility inde, soi-idge roughness facto, a elimate factor,

‘he Fed ength along the prevailing wind erosion direction, and a index of vegetative cover

Chapter 3— Mellalugi for assessing si urint balances „

losses to nutrient losses Estimates oF nuns losses due to erosion were obtained for county sind regional Teves by using the following regression function made evadjust an peedit the amount of nuteient eroded (Ne}

where: Ne isthe percentage of nutrient loss through soil erosion inthe selected crop region; and «, 8, and 8, are parameters measuring the eflets of factors that are 9 included in the models hut characterize the Sudano-Sahclian, humid, and subhumid regions, respective!

‘These fetors characterize and ate specific to each of the counties regions, The parameters B,.B and B, measure the effects of the soil feriiy class (Fe) and the sineral and organic nutrients applied each eropping season (Cn) on the amount of nutrient eroded The variable ©

fssessment of nutrient inputs and inflows

In onder to assess the use of mineral fetlizers (MA information on nutrient applications por

‘county’ tonnes of P.O, and K,O as obizined from the FAO database (FAO, 1999),

‘Weighting factors snd GIS routines were used to calculate ferilizer use at higher levels of sggregation (region, sol eas, land use class AEZ, ete)

Tho data requieed 1 ealelate organic nutrient inputs (OP (mainly in the for oF animal

‘mane include: the livestock popultion: the amoual of manure reaching arabe land: and the hutrent content ofthe manure tthe time of aplication However, additonal information is regtieel la estimate recycling of household waste and industrial refs, Some ofthese data are often not readily available at country and regional levels

{Information from the literature on type of manure and onganie products, rates of application

by farmers, and livestock production practices in selected regions and countries Was used 19 estimate the amounts of nuient inputs provide by the use a organi Fertilizers,

CCountry-}evel estimates ofthe smount oF nutrient returned to the soi in the Form of solid

‘manute were calculate on the bass of the amount of resid felt om the field that is grazed the nutrient content ofthe

Inside the animal The value of tis fraction used in the estimations presented in tis paper Was

10 perent

‘The amounts of nutrients that return to the sol by deposition (Nd) are dificult estimate Deposition is associated mainly with the levels of nutrients use and preuced) and with the amount of rainfall Wet and dry depositions wers evaluated for select sites using transfer funetions, A meade as estimated hy using Forms of empirical fonctions fom other studies {Stoorvoyel and Sosalng, 199M; Smaling and Fresco, 1993), ln hose sais nutrient deposition 'sspoetied as funtion ofthe sqeate ro o erage anna rafal, Thereore, the folowing model was estinated and evaluated in this shy

8 Assermen of sil marin balance ~ approaches mu mghuddlgier

‘The mechanism concerning inputs of ausients de oso sedimentation (Xs) particulary

‘important in itrgated areas and on narally aoded soils Quanifiation is uifcul ta bocause ofthe lack of sulicient information on the nutrient content of semen, Bosause of this imitation, values kilograms per hectare per yea f the amounts of nutients in ivigation water were used for selected regions and erop system,

Regarding N inputs du 0 N fistion, information inthe literature about the nature of N uptake by crops was used to identify three basic distinctive scenarios determined by the lure

Assevsment of matrient depletion and requirmens

The gusty o rate oF nutrient depletion is estimated asthe difference between the amount

of nutrients exported annually from cultivated fields and the amount added or imported annually in the form of Fertilizers, manure, fixation, and the physical processes of deposition and sedimentation, The balance of trent inflows and outflows (Nb) per year oF muti

‘eptetion in kilograms per hectare por yer fora country ()and crop) isassessed and estimated 1s follows:

Nh

(MF, OF, Nh) +B, (Nad, Ny (2, (Me, No) £E (ML, Nig, Ned) 0

‘Tho caleulaion of nusiont requirement is indiated by

ur, = 3, (Cp, il) “8,7, +, (1, Ne, Ney 6

‘The nutrient requirement (Nur) i calculated a6 the amount of natientupiake required to schievea pectic inet yield without depleting the sol nutrient The calculated nutrient uptake eguiremens are misimum requiemens crop could take up more than Nur and this would result in increased production or yield or improved quality ofthe product As necessary the model

‘sadjusted by the available sol nutrient content Furthermore, inorder estimate the amount ofa Feilizer product required, the nutrient requirement s adjusted io account propery For the fiaotion of Fortier nutsont that actually taken up bythe crop (Tertlizer use eficieney)

Average rats of nutrient depletion and nutrient requirements were estimated initially at

a macroseale for each coumy in Afeca, Because of significant variability withia counties, estimates were calculated for seleted areas within counties using more elaborated transfer fimetions, empirical response madels, and goostait

Chapter 2 Mehodolosies for asessing sll nutrient balnces 0

sion D086) Federation 3) TiaNBKhsyem)

tương: Mecanique Cope vere Amase

Dom Rep Congo Seog com Meeces

‘easier and faster, Calculations can be made foreach yearas the data is based only on FAOSTAT and GIS maps, while Stoorvogel and Smaling (1990) used a nique data set with soilwater

‘lasses and LUSs, However, the calculation is sill ona counteybasis and differences within the

‘country are not shown, The GIS and database system offer the possibility ta link with decision support systems and erop growth models, but this has not been done yet

National sol surface nitrogen balances, OECD

‘Theissue of agricultural nutrient use has been a priority issue fr the Organisation for Beonomic Co-operation and Development (OECD) in developingaset of agr-enviroamenta indicators as pat of the analysis ofthe interactions between agriculture and the environment and the impact

ot changes in agricultural policy onthe environment

‘The major envieonmental issues associated with N surpluses ftom agriculture include pollution of surface water, groundwater andait However, a deiciney of soil N can also impair the resource sustainability of agriculture through soil degradation and sol mining esuting in ing ferility in ateas under erop or forage production In cooperation with the statistical

‘of the European Communities (EUROSTAT), the OECD is inthe process of improving and updating the N balances presented here (OECD, 2001), The work is als being extended

to cover Palaces,

20 Asesament of i ntriem balance — approaches and methodologies

“The estimate ofthe annual ol quantity of N inputs for he soil surface N balance includes

‘the addition of

‘inorganic or chemical N fenilizer: quantity consumed by agriculture;

‘livestock manure N production: total numbers of live animals (cattle, pigs, sheep, et.) in terms of diferent categories according o species (eg chickens, turkeys), sex, age and

‘purpose (eg milk cow, beef eat), multiplied by respective coefficients ofthe quantity of

‘N contained in manure pe animal per yer:

+ atmospheric deposition of N: total agricultural land area muiplid by a single cosfi

‘of N deposited per hectare

+ iological nitrogen fixation (BNF): planted area of legume erops or pasture (eg field beans soybeans, clover, alfalla and pasture) muliplied by respective coefficients of N fixation pet hectare plus the N fixation by free-living soil organisms compute from the total agricultural lad arca multiplied by a single coefficient ofN fixation per hectare:

Chapter 2— Methdologies for asvessng sil marie balances a

tao |[ tuesssx |[ 38283 l[gueae|[ oae || 5

đglae || mac || in ||fapesion || se || 22mg Nitrogen inputs

‘© N from reeyeled organic matter: quantity of sewage sludge applied to agricultural land

‘multiplied by a single coefficient ofN content of sewage sludge:

‘+N contained in seeds and planting materials: quantity of seeds and planting materials cereals and potato tubers) multiplied by respective coefficient of N content of seeds per planting materials

‘The estimate of the annual total quantity of N outputs, oF N uptake, forthe sol surface N inches the addition of:

‘harvested crops: quantity of harvested crop production (e.g cereals, oot crops, pulses, fait ctgps, vegetables and industrial erops) multiplied by respective coefficients of N uptake to produce a tonne of harvested ero:

+ harvested forage erops: quantity of harvested forage crop production (e.g, fodder beets, hay and silage) and grass consumption from temporary and permanent pasture multiplied by respective coefficients oN uptake to produce a tonne of forage

‘The OECD soil surface balance caleulaton is not a gross eaeulation ofall N losses from agriculture (Figure 5), This because the oeus ison N losses to soil and water as volatilization

‘oFammonia from stored manure and livestock housing is excluded From the calelation,

‘Thebasic data the database are preliminary and data definitions may vary across counties following the definitions inthe orignal surveys For example, although erop production data generally refer tothe normal state ofthe specific erp unless otherwise sated (e.g dry weight for cereals, fresh weight for vegetables), forage production may reer to weights with different

‘moisture contents across countries,

The coefficients used for the calculation are preliminary and their derivation may vary across countries In any ease, the definition of coefficients should meet the definition of the

‘corresponding basic daa,

The database consists of four parts (Figure 6):

+ fenilizerneadagelcrops: basic data to caelate the N balance, covering the N inputs and

‘oulputs in the soil surface balance:

Assessmen of soil murien lance approaches and methodolies

Xaneoomopnadir_ TH iHmmiMMmm | Money

_ iin Tan hạn nan | teweueesbiEse

‘coefficients: to convert basic data (e.g livestock numbers) into N equivalents;

‘© quanity of Nontent, involving the multiplication ofthe basi data by theN coefficients,

to provide the total N content forthe N input and ouput

Disaggregated data are provided where possible, especially for erp and livestock series,

in onder to facilitate a more accurate estimate of the N balance (eg piglets and sows), plus the relevant subtotal (e toal pigs) However, where disaguregated data do not exist, then aggrgated data are provided (eg, total pig numbers), ogeter withthe eorespending coeicients

to convert these data into N composition and quantities

‘Countries use different classification systems to record the numbers of ive animals especially for cate, pigs and poultry

Fertilizers

‘This category covers data on apparent inorganic fertilizer consumption and on other

‘organic fertilizers applied to agricultural land, excluding livestock manure, which is treated separately,

CChupr3— Melioldlogie or tuc túng vài mui balances 2

Inorganie ferilizer consumption includes:

++ nitrogenous fertilizers covering consumption af nitrogenous feritizers, expressed in

(Organic felizes include:

‘+ sewage shdge, covering use of treated publi sewage sludge

+ urban compost, covering use oF urban compost om public refuse calletion;

+ industrial waste products, covering use of industrial ase, such as product fom the food Processing industry

+ exter products, covering othe organic products use as entlizes

Livestock numbers

This eatogory covers the tol livesloek inventory of ive animals required in the ealeuation

‘of the N content of Hivestock manure production, The numbers of live animals include those recoded for given census day inthe year, aa donot include the total numbers oF annals slaughtered in a given year The total numbers of livestack slayghtered i a year are reflected inthe eneticiens used to convert livestock aurthers nto N content mane The livestoek

‘ategoris cover incu:

+ cattle, covering beet calle, dairy eatle and calves

+ is, covering pigs of various ranges of weights;

+ sheep and goats, covering sheep, lambs and goats:

+ poultry covering chickens for broilers and layers, and other poultry, such as dicks and turkeys;

* ater livestock, covering other livestock, such as horses and donkeys,

Momive withdrawals, stocks avd lnporis

ony covers data om: livestock manure withdrawn and not wsed on

1g manure experi the increase oF destease oF manure stocks inened for tục on agricultural land; and manure imported into 8 countey’ for use on agriculoral Tan This information provides the basis fo cteulating the “net input oF livestock mane on agricul land in given year as Follows

Net input = livestock production - withdrawals rhage in stocks + imports

Manure withdrawals represents the amount of manure withgrawn from agriculture and not applied to agricultural land, The voaulizacion of armenia and mineralization of N ater applying manute tothe soil are regarded ssa pan of nutrient losses for natrent surplus) and are not included in ths category: On the other hand, destruction of manure and volaiiation ammonia from stored manure, vestock housing and manuite-spreading operations are excluded From the halance, The manure categories ae

4 destruction und evaporation, cover

that occurs From stored manure,

Jstruction of manure and volatilization of ammonia

‘stock housing and manure-spreading operation

‘+ non-agrcultuea use of manure covering ares suc as private gardens:

1 processed as industial waste, covering man

plant and nov used on agricul fn cessed as indusisial wast ina processing

“ Assesment i muti balance —apprnaches nd methodoloes

‘+ exported onganie fenilize

‘country: manure and other onganicfetlizers exported from

+ other withdrawals, covering her manure withdeawals

+ change in manurestocks, covering change in livestock manure stocks blaine by deducting the opening stocks from the closing stocks

+ imported onzanicfeilizers covering manure and other organic ferilizrs imported,

Harvested crops and forage

This category covers dats on: harvested erap proiction from arable Held erops (ee cereals) permanent crops (ex citrus fruits): forage predction, including both harvested fodder crops

te fodder bees); and pasture prduction from temporary grassland and permanent pasture

“The definitions snd vategories at crops and forage follow closely those used by FAO While

‘many’ countries have disaggregated truit and vexetable production data these are included

‘only where coefficients exist to convert the particular uit or vegetable into is nutrient content

Harvested crops regatdiess of their final destination, include those fr humen consumption, livestock fee industrial use and seeds

+ cereals, covering wheat, ive and course grains:

+ oilerops, covering annually sow oilerops (e soybeans}, perennial oil erops eg ives), and el erops, such as suybeans, used for purposes oer than the production of vegetable bil sich as for animal feed and processed Foods:

+ dried polses and beans, in dry weight, covering beans, broad beans, peas, chickpeas snd lentils but excluding soybeans;

+= root crops, covering mainly crops use for food and industrial use (eg potatoes), but

‘excluding roo eros grown principally lar feed, such as foider beets:

‘© trut, covering annually sown fruit erops (e.g strawberries) and fruit tree crops

eg apples:

ables vegetables covering leaf (e.g cabbage), vine (e.g, lomatees) and root v

by livestock, However, sass are more sammenly available on pasture area and pasture

hpi 2 eden for asessing so trie Balalre+ 25

prodiction, which includ both pastre vegetation consumed by Hvesock amd that remaining in the field For those counties with data on poste area alae, pasture production was estimated sing an assumed pasture yield figure

For most contre, pasture consumption was estimated using the number of grazing livestock

‘and average consuinption levels per animal, oF using pasture production and the consumption production rain

The inchasion of erap residues ithe soil surface N balance requires fuer esearch panicular, examination is reguted with respect to the use of N conversion cosiiems, ie Uptake coelfcientx cover the N content not only in harvested cereal grains but aso in other prs of the plant, which may of may nt be removed fem the field Data are not pronied in this ey at this stage of OLCD work on the balanees

Seeds and planting materials

ol suc as for animal feed and process Foss

+ cool crops, cavering mainly craps used for food and industrial use (e.g, potatoes), but

‘excluding roo eps grown principally Tor Fed, sued 48 Fide boos;

‘other crops, covering any ater craps

Biological miengen fasion

“This category covers the planted ena of legume eraps that contribute to BNF mainly pases, saybeans, clover an lla It is te planted area and not the harvested area of legumes tha

is relevant 2s BNF occurs regerdess of whether the crop is harvested or not For example leguminous eraps ate often not harvested but ploughed into the field io provide soil N,

‘While naionat eeftctens are used where possible, coelicemss fra eomparable' country reused in the absence of national eoetcients

28 Assesment of sui ron lance — approaches and ago siex

Fertizers

This category provides the N composition eoeticionts fo convert quantities oF inorganic and

‘owganicFenlizers From sts definition (expressed in N contents, notin wight of Fetzer hitrogenous inorganic ferlizer has fsed N conversion coefficient of | 000 kane Livestock

‘manne isnot included in tis category

Livestock manure production

This category’ provides the coeiciemss «convert ixestok numbers a N composition in nausl manu production, However, regarding these coelicients

‘© Inserms ofthe level of disaggregation, the set of N conv

slosely as possible co te dat Fr livestock numbers, sion soefcints corresponds

' The eooiciens take into account the slanghtering oF animals ina given year

Manure withdrawals, stocks and imports

‘This category provides N composition coeticiens for manure withdrawals (nehuding manure exponts, changes in stocks and imports

Harvested erp and forage

‘Thiscategory provides the N uptake coelicens for converting the prducion of harvested crops tnd forage ino quantities of N uplake from the field However, reganlng these coeficientx

‘+ In erms ofthe level of disagprepation, the set of N conversion coefficients correspond as clusely as posible tothe data for erp and forage production

‘Where eoeticents are not available for certain erops,N coefficients that are available for similar erops are use provisionally (eg applying the eoeticint for haley’ To a)

1 As N uptake includes the N content in op resi remain in the fel, Further

‘methodological work is required to consider this aspect propery

Seed al planting materials

This category proves caeflicients for converting the quantities of sods and planing materials Ito their N composition Cetliciems in this yroup afe not the same as those for eops, wich

do not concern N compasition but uptake {including uprake for by-preucts, such as stems and leaves)

Biological mivngen fication

‘This category provides coeticient for calculating the BNF from the planted stea oF leguminous raps and BNF by soil mierorgsnismns on all agrieultral and

Atonospheri position

This eaeyory provides the coeflicients for calelating atmospheric deposition of N on all sgneutunl land

Meshodolosies for assessing vá nưyiem bon m

Denirsfcation

“The denitrification prosess on agriculral ants important for Ja an the Korea Penns, where rice prdtion is dominant in the agricultural systems, This process iste release of mineralized nitrogen as gaseous niteagen (N,) which s deemed to be harmless othe environment asit isa major eomponent of the atmosphere

Quant of nimgen

This category provides the otal N content of the inputs an! outputs inthe sol surface balance

in terms of tonnes of N, The N content data in these tables are derived basically from the ultipication ofthe basie data (ertlizersTeadageevops) by the N coeMeients

The eateulation ofthe sil suriee N balance i

+ Ninput tonnes} = feilizers~ net inputof livestock manure +other ston inputs (seeds and planting materials, BNF and aospheric deposition

+ N pH tonnes N} = total harvested erops + total forage

+N balance (tonnes N) = N outputs -N inp:

‘+N blance per hectare of agricultural land (kgsha} = N balanee (ones NI! toal area oF agricultural lard (ha)

‘On the ouput side, OUTS (leaching) OUT (gaseous losses) and OUTS ferosion) are not included, which makes the figures in the balance strongly positive For gaseous losses, slenititication is taken into account, but N.O and NH, losses trom animals, volatilization and huring are not included, On the ether hand, sevage sludge and seed an planting material are ined

” Assexsmen of xui marin blonce approaches and methdolgies

Methodology

Conceptually, the model i a mass balance in which nutrients exported in ops and livestock are compared with nutrients imported into the sol Ht considers the following ootputs arable ops arable crop resides, animal products and livestock excreta Inputs are: miner ferizer,

rp residues, manure, animal feeds, non-livestock waste, BNF and atmospheric deposition, Ovisined som FAOSTAT databases, the input information included annual erop produeton for both the arable and livestock sectors etilizers land use nd population

‘The model defines nutrient efieeney asthe percentage of nutrients input that i recovered 2s nutrient output in the crop A nutrient halance is achieved when nutrient ouput no longer Increases with increasing teen nput The sadly estimated nuteent efficiency using input and jutpot data from the mode Based on nutrient audits for 197 counties for 1996, the nutrient, efleiency for China fo N, P and K was set at S0, 40 and NO percent, respectively

Ofte crop esdues twas estimated that 40 percent as retumed, 25 percent was consumed

‘ts animal fodder and 35 percent eno other uses oF was lot frm the oil nutrient cycle N fixation was estimated at 68 percent ofthe otal N uptake for pulses and groundnut and 80 pereent {or soybean For green manure, 0.6 percent of the foal N input was estimated N fixation by

‘rola in paddy rice was neglected Atmospheric deposition was considered ony for Nand as, set at 20 ky ayeat, Non-ivesock waste was estimated as funetion of population: { 000 Ky 250g Pand 280 ky K per 1600 people

"Ni losses such leaching, gaseous losses and erosion ate not estimated ditetl the

‘model, but calulated a the aiference berweon nutrient inputs plus nttients depleted trom the sei and nutrienc outputs inthe crop, After nutrient depletion rates have ben deterined From the model, the total aunt loss ean be callie,

Results

‘he N balance for China was caleulated between 196 and 1997 Figute 7) Fest thee was an Jncreasing depletion of N, but owing othe use of large quaaities of Kerilizers this depletion subsequently decreased and came more oF les into equilibrium For Pan expecially K the halanees grew ineceasingly negative K depletion increased from 28 kya in 1961 to 62 kyha

in 1997, Table 10 shows the nuieninpat and output lows For China, From the table, appears {at K depletion is highest a1 percent oF tal K inp

“while, far example, erap residues of cereals are generally used more intensively than those of