research report 11 - Water and Land Resources Centre (WLRC)

Provisional Military Government of Socialist
Ethiopia
Ministry of Agriculture
Soil and Water Conservation Department
Soil Conservation Research Project
RESEARCH
REPORT
11
Land Use, Production and Land Distribution
in the Agucho Valley, Ethiopia
by
Kuno Schlafli
1985
~
~
1'- - -
University of Bern, Switzerland
in association with
The United Nations University, Tokyo
@
LAND USE.
PRODUCTION
IN THE AGUCHO
AND LAND DISTRIBUTION
VALLEY.
Io..'UNOSCHLAEFL
1985
ETHIOPIA
I
Address
of the autor:
Kuno SchUHl
i
Geographisches
Hallerstr.
3012 Bern
12
Institut
der Universitat
Bern
Preface
Research
report
Distribution
lIon
"Land use, Production
in the AGUCHO-Valley,
contribute in some aspects
and Land
Ethiopia"
to the results
shall
of the research
programme of the Soil Conservation Research Project (SCRP).
The data were assessed in Suke area, one of the research
sites of this project.
took place
The field stay for data assessment
from September
1983 to March
The field stay and research
during
activities
that time were made possible
1984.
I carried
by a research
ship offered by the SCRP. At this place
thank
for the opportunity
experiance
which
out
I would
fellow-
like to
to make this unforgettable
is and will be in future very important
for me.
This work would
ending
not have been possible
support by the following
without
persons,
the never-
to whom
I want to
express my deep gratitude:
Dr. Hans Hurni,
project
manager
of the SCRP, and his
family:
Prof. B. Messerli,
Institute
of Geography
of the Univer~ity
of Berne:
Michele
during
Galizia,
social anthropologist
the field stay:
the people
of Suke area who sustained
sence and nevertheless
and Ethiopians,
Abrahim,
but especially
Research
my disturbing
fully cooperated
and last but not least all employees
without
and my companion
Assistants
with me:
of the SCRP, Sw~ss
Derebe Mekonen
and Jemal
of the SCRP in Suke,
whose help this study would never have been
possible.
pre-
-
1 -
~
Contents
Preface
Contents
1
2
Figures
Tables
Maps
Abbreviations
Abstract
1. Introduction
1.1 The location
of the Suke test area in Harerge
region
2. Land use
2.1 The agricultural year and t~e cropping calendar
2.2 Yields of main crops
2.2.1 Metho&of
crop yield measurements
2.2.2 Method of sweet potatoe yield measurement
2.2.3 Main results and summary of interpretation
explanation
3
4
7
8
9
10
12
and
14
2.3 The influence of some natural factors on th~yields
2.3.1 Dependency between sorghum and maize yields in
mixed cultivations
2.3.2 The factors soil depth, slope gradient,chem.
soil 16
fertility, plant available water capacity, phosphorus content, and bulk density of the soils
17
2.3.2.1 Crop specific linear regressions
2.3.2.2 Crop specific multiple linear regression 24
25
2.3.3 Summarizing interpretation of the results
2.4 Land cover mapping
2.4.1 Method far land cover mapping
2.4.2 The cultivated area of the map
2.4.3 The non-cultivated area of the map
2.5 The agricultural production
2.5.1 The food production
2.5.2 The biomass
production
2.5.3 Sorghum straw for firewood
supply
3. Land distribution
3.1 Method of mapping
3.2 The average farm size
3.3 Farm size and crop diversification
4. Food supply
4.1 The average
farm production
28
29
31
33
34
35
37
39
in 1983
5~ Considerations
for soil conservation
5.1 Contour bunds and "fanya yuu" graded
42
bunds
5.2 Loss of cultivableland due to conservation
-
26
43
5.2.1 Loss of cultivable land through conservation in the
Suke case study (March 1984)
5.2.2 Loss of cultivable land if conservation is carried45
out as recommended by SCRP
5.3 Remarks
and conclusions
46
48
References
Appendices
1 - 6
50
- 2 -
Figures
Figure
page
1: The cropping
2: Yields
10
12
calendar
of main crops
3: Correlation
yield
sorghum yield-maize
4:
5: Corr. yield/9m2
(in smh-fields)
lS
(in sm -fields}
16
17
18
(smb) - slope gradient
6:
- soil depth
7:
8:
9:
10:
20
21
22
- chem. soil fertility
- plant avail. water
- phosphorus
capacity
content
23
- bulk density
28
29
11: The
cropping area
12: Non-cul tivated area
13: Production
14: Field
in Suke area
32
36
(1983)
size per household
15: Cross-section
of ItFanya juult conservation
42
bund
Tables
Table 1: Cropping area of the mainly cultivated
Harerge,
crops in Suke,
28
for the main crops 1983
2: Use of non-cultivated
3: The biamass
area in Suke, Harerge,
for 1983
production
4: Distribution
of cultivated
5: The average
farm production
6: The farm production
land in Ethiopia
in Suke, Harerge,
in calories
for 1983
for Suke, Harerge,
1983
30
33
37
39
39
Maps
Map
1: Highland
2: Location
area and location of SCRP research sites
of Suke research unit in the Chercher Hountains
3: Conservation measures
Harerge, .region
in Hunde
4: Land Use and Land Distribution
lafto-Tullo
wereda-
in the Agucho
Valley
8
8
41
56
- 3 -
Abbreviations
EHRS
FAO
MoA
PA
RA
rest cr
Ethiopian
Highlands
Reclamation
Food and Agriculture
United Nations
Study
Organisation
of the
Ministry of Agriculture
Peasant Association
Research
Assistant
rest crops: beans,
linseed,
peas, barley,
wheat,
lentils,
tef
SCRP
sm
Soil Conservation
sInh
sorghum-maize-haricot
sorghum-maize
Research
Project
mixed cultivation
bean mixed cUltivation
- 4 -
A b s t r act
This report
harvest
presents
yields,
basic data and information
land distribution
have been collected
lands,
around
tion Research
The harvest
Extended
Project
mixed cropping,
beans
(smh), which
can give higher
yields
and lentils vary between
for the phosphorus
like soil depth,
city, and bulk density
content
work
the availability
input,
(like oxen, man power,
degradation
by higher
on
his
means of production
much more to the amount
the effects
can be hidden
of land
for a long time
until the soil is almost
area: 72,4% = 81.05 ha. The total cropping
7,7 ha, sweet potatoes
Emmer wheat,
linseed
The non-cultivated
for cutting
of the
area is
area of 234 ha. Other
beans are peas
3,5 ha, and barley,
11,8 ha, beans
lentils,
chat,
and tef.
area is divided
28,8 ha, shrubland
and fallow
122 ha
capa-
influence
beans make the largest portion
crops than sorghum-maize-haricot
grass
water
for surplus production,
112 ha, or 47,8 % of the total catchment
bushland
n~tural
removed.
Sorghum/maize/haricot
cropping
Emmer wheat,
tested
available
As a consequence,
labour,
The yields
barley,
of the soils,
of different
due to soil erosion
t of
and 200 kg/ha.
motivation
inputs of mainly
completely
beans).
peas,
etc.) contribute
of a fields production.
in
(t/ha) is the
of the soils have little
The farmer's
planted
bean-fields(1.35
slope gradient,
the yields.
Sorghum,
than each crop culti-
249 kg of haricot
800 kg/ha
and
from 3mx3m plots,
2,3 tons per hectare
714 kg of maize,
beans,
are usually
yield of sorghum-maize-haricot
factors
maize,
yields vary highly.
of other crops like tef, horse beans,
Except
out in the whole
crops were collected
in monoculture:
sorghum,
High-
1983/84.
were carried
The measured
and haricot
average
in the Harerge
of the Soil Conserva-
1983: 350 samples of sorghum,
dried and analysed.
vated
Station
The data
yields
all other cultivated
maize,
valley
(SCRP), during
yield measurements
cultivated
and farm income.
for the Agucho
the Suke Research
on land use,
into. past ural land 51,7 ha,
combined
18,3 ha (controlled
land 6,8 ha. Altogether
(=52,2 % of the catchment
with pasture
16,7 ha~
bv peasant
association
the non cultivated
area).
PA),
area makes
- 5 -
The aqricultural
production
Calculated
from yields
production
in 1983 was 110 metric
57 t, of haricot
of barley
Lentils,
2 t.
beans
tons, the production
of sweet potatoe
and tef amount
of sorghum
a remarkable
areas the sorghum
grain
of maize
10 t, of peas 7 t, of horse beans
An estimate
linseed,
The biomass
and cultivated
around
straw, which
is 12 t.
1000 kg altogether.
is used for firewoorl, lasts
246 days for an average
the whole year are bushes
children.
production
5 t, and
family. The remainder
and trees collected
by-women
for
and
Land distribution
The average
of grass,
farm size is 0,85 ha of cultivable
pastoral
After GALIZIA
therefore
(1985) one family consists
the share for one person
grass and pastoral
cultivated
on other
need other means of income
is 3.1 h~while
The largest
25 % of all recorded
like
farm
farms have
land.
have shown that the large farms are suffering
from worsening
.
and
farms are around 0,2 ha,
farms or selling artifacts-
more than 1 ha cultivated
Calculations
of 5.3 persons,
is not enough to feed a family. As a
the family members
in the catchment
shrublan~.
is 0,29 ha of cultivable,
land. The smallest
lan~which
consequence,
working
and bush land, including
land plus 0,71 ha
environmental
conditions,
less
not only due to ge-
nerally higher production but also because more land offers the
opportunity
to plant more different
cultivations,
adapted
crops.
In diversified
parts of the fields (or some crops) are better
to the specific conditions,
giving the farmer less
ecological risks and more flexibility for marketing. During
problem years there exists the risk that "rich" farmers get
"richer"
while poor
controlled
Food
by the peasant
stagnate
in wealth,
if this is not
association.
supply
The average
farm production
440 kg of maize,
Beans
farmers
76 kg of haricot
(39 kg), barley
contributed
Converted
in 1983 was 832 kg of sorghum,
beans and 55 kg of peas.
(16 kg), and sweet potatoes
(42 kg)
only a small part.
into
calories
per day at it's disposal
until the 1984 harvest,
the average
family member
(FAO requirement
had 2414 cal.
for Ethiopia:
it nothing would have been sold.
2330 cal.
)
- 6This doesn't
say anything
about the diversity
of the food, and the under-average
even in calorie
amonnt.
family will be under-fed
The data were assessed
production year, which was a year with
amounts than normal.
Considerations
For certain
from the 1983
slightly
higher
rain-fall
for soil conservation
reasons
of conservation
conditions.
and the quality
it can be advisable
measures
to use different
to cope with the specific
The SCRP therefore
initiated
types
environmental
a trial in one of it's
research
sites, Suke area, with an other conservation
in Kenya
("fanya yuu" graded bunds).
type used
We found in Suke area that the actual loss of cultivable
land through
conservation
measures
with IIfanya yuU" graded bunds
level bunds.
This figures
sures with
and 5.3% in the area treated with
refer to the actually
slight
was 7.~~ in the area conserved
carried
according
the soil loss would have been
15.7%
land and therefore
ving
acceptance
(llfariyayuu" graded bunds)
from the farmers,
crop production
effect
(e.g. by planting
the agricultural
and drainage
respectively,
the loss of
must be compensated
the value of the bunds beyond
improving
to SCRP recommendations,
(level bunds).
In order to achieve
proving
mea-
irregularities.
If the area had been conserved
and 14.~~
out conservation
the soil and water
of fodder grass or trees)
potential
stridiy
by im-
through
adapted
conserand by
water conservation
to the local conditions.
- 7 -
1.
Introduction
Knowledge
of agriculture
condition for working
water conservation.
and land use practices
out appropriate
The SCRP
(Soil Conservation
research
programme
country
Research
measures
Project)
in now six research
in order to assess detailed
is a fundamental
for soil and
maintains
a
units spread over the
data in the field of the
framework
peasant
systems.
This includes
runoff,
sediment
load and soil loss, and the significance
different
cultivation
for erosion
employees
yield measurements
units.
This report
(mapping,
methods
and erosion
produce
of the economical
ecological
natural-physical
data on climate,
(crops, working
control.
a precise
etc.)
production
come of the local peasant
factors
lable water capacity
in all research
and precise
judgement
by applying
it shall give information
and the agricultural
data,
unitsl
of the reliability
above mentioned
on the land use system
in Suke area and the farm in-
population
for a sample year
like soil depth,
slope gradient,
of the soils, etc. are tested
(1983).
avai-
for their
on the yie1ds.
A final aim was the calculation
fields
of
the project
for one of th~ research
of the research results assessed
"minimum input" methods.
influence
season
more detailed
yield measurements)
natural
methods,
In this context
for every crop'ping
im order to make possible
Various
precipitation,
land use sketch maps and carry out harvest
shall produce
Furthermore,
-
for the sample year
of a family's
income
from it's
(food production).
lSuke station in the Harerge highlands: Suke is the local
name for a kind of herbs, giving the geographical name to
the whole valley
- 8 -
1. 1 The location
of the Suke test Area in Harerqe
"
'
Reqion
Suke station
-
Eth10p1a - Locat10n 0f Suke
.
Research Stat10n
is situated
370km E of Addis Abeba,
near Debeso
:rokm
0
catchment
is drained
by
the Agucho-River to the
Wabe Shebele-Basin.
rs:sJ H:i.gh.land
J..:(X) rn Area
.
to Harer.
on the road
?
The 2,34 krn-
s:::RPResearch
The research
Units
selected
tative
to be represen-
for the Chercher
Mountains
between
area was
and is situated
1950 m and 2300 rn
as!.
l!Highland area and location of SCRP research
sites
Map 2 shows the
exact location of the
9'
-2007
unit in the Chercher'
1448
.
Mountains.
source:Eth~opian
Mapping
Agency,SerJ.esEMA 3,
Sheet NC 37-12, Ed. 1,
Dire
Dawa
'-~'
~~
~.
~
~
~
A2~fu1 \~o~
I ---
,
I
':I
dO...
-0
0
0
-
.
or
5
IOkm
Map
2:Location of Suke research
in the Chercher Mountains
unit
- 9 2.
Land use
2.1. The aqricultural
The
farmers
of the
year and the cropping
Chercher-Mountains
calendar
divide
the
year
in
-.
to four parts:
n?
BEGA
(Dez.-Jan.
nl\
BELG
'r1Lr'1'
KREMT
(March-April-May)
(June-July-Aug.)
small rainy season
main rainy season
TSEDEY
(Sept.-Okt.-Nov.)
end-rainy
eq.
The agricultural
year begins
-Feb.)
dry
after the harvest
December/January with a period of time (BEGA)
has only
vities,
few duties
to accomplish.
ceremonies,
season
season
of sorghum
in
where the peasant
This is the time for festi-
and for construction
or repairing
of
houses.
In BELG every third to fourth year
rainfall
is sufficient.
Before
crops can be grown, when
sowing the fields the fallow
land must be dug with the help of digging
because
the soil covered
sticks
(dongora)
by grass is too hard for plouging
with the oxen-plough.
Cultivated
land is then ploughed
February/March
harvested
barley
and Emmer wheat
in July. On the
other pulses
two to three times.
are sown and will be
same small fields beans,
main crops sorghum
After plouging,
period
ripening
and maize
sorghum
in the main rainy
and maize varieties
follow
with the
season only.
with a longer
of April.
Faster
in May.
and sowing, the fields must be reploughed
again in May and June for thinning
From June onward,
crop culture
is cultivated
are sown at the beginning
varieties
After planting
crops.
peas, or
can be grown again in the big rainy season, Krernt.
The major part of the fields, however,
growing
In late
consisting
haricot
out too densly
beans complete
of sorghum,
maize
standing
the mixed
and haricot
beans(smh).
After June, the rest of the fields not yet occupied
by smh-
crops is planted with other pulses
(horse)
beans,
peas,
lentils, " linseed,
and cereals
barley,
or
tef.
like
- 10 All crops except peas
weeded)
(not weeded)
should be weeded
and smh (two to three times
at least once during their growing
period.
In September
plant
(Tsedey), many farmers prepare
sweet potatoes.
wide bunds
October
The crop is being planted
smh-fields.
for harvesting
In November,
maize,
follow, while the harvest
take place
CROPPING
CALENDAR
in the
VALL"Y
---
IIARtCOT
is by far the most
M
ETHIOPIA
J
J
A
S
-- -1--
H:ANS
0
N
D
-1--
--
PEAS
-
HEANS
--
LENTIL
--
FLAXSEED
BARLEY
-
EMMER WHEAT
-
SWEET
will
or in January.
....- -'--
MAI7.J::
pulses
in the Chercher~ountains,
HAlERC"
M A
beans out of the
and the different
of sorghum which
in late December
ACUCRO -
haricot
barley
crop for subsistence
J F
SOIt'iIiUM
into one meter
formed out of topsoil.
is the time
important
a small field to
POTATOE
-
-
I
/TtR
IYF~ATIT
IMPr.ABIT
1"IAZIo\
ICFJlBOT
IS~:NE
IIIAKU!
I"EllASIE IHI'.S(F.R~/TIUHT
IHIDAI
Fig. 1: Cropping calendar in Suke, central Chercher mountains,
Harerge region. The time of planting is dashed, the
growing period in solid line, and the harvesting time
again dashed.
2.2.
Yields
2.2.1
Methods
For assessing
of main crops
of crop yield measurements
the agricultural
production
catchment,
231 sample
cultivated
area were demarcated.
smh-fields,
sites distributed
Around
the rest of the samples
was
in the Agucho
river
at random over the
135 were
taken
situated
in
from other crops.
I TAHISAS
- 11 -
The samples
from a plot
time, packed
in plastic-sacks,
tion and exposed
winnowed
sized 3 by 3 meters
transported
to the sun for drying.
and weighed
with
were
cut at harvest
to the research
Then they were
spring-balances
sta-
threshed,
of 1000 g and 10 kg
capacity.
Around
100 samples
in Addis Abeba
vested
sample
storageable
didn't
dried
times harvesting
Foto
exceed
(appendix
(around 100 smh-sample
because
content
of the har-
the limit of 15 % of the weight
grain ~r seed
to the owners
:Oor example
in SCRP headquarters
to be sure that the moisture
The 350 samples
back
were moisture-tested
of different
for
1).
sites required
ripening
three
times)were
given
after analysing.
of yield'
registr~~ion
l:Research assistant \'lubishet Foto
threshing a sorghum sample
form see appendix
6.
2; Sorghum samples drying i~
front of the main house
of Suke Research Statior.
- 12 2.2.2 Method
of sweet potato~ield
Sweet potatoes
are not a seasonal
measurement
crop, since harvest
is possible
after some monthe or only after twelve months
depending
mate and variety.
difficult,
another method
We determined
This made yield assessments
than 3x3m plot harvesting
the weight
on cliand
had to found:
of an average tuber at harvest
time
(fresh). Then the roots and the tuber system in the planting
row on a length of one meter were dug out. The number
and potential
(after a time of ripening)
by the determined
yield"
average tuber weight.
from one meter
to each sweet potatoe
of actual
tubers were multiplied
This "potential
sweet pot. planting
harvest
row was extrapolated
field or the total length of planting
rows in one field respectively.
This method
of assessing
is naturally
less exact than the plot
harvesting,
so that the results are used with the term "estimation"
(fig. 13).
2.2.3 Main results and summary of interpretation
explanation
Fiq.2
~/9m!
224
2 UOO .1..<O,249t/
,..)
64'1
(0.714t/
,..)
YIELDS OF HAIN CROPS ( Gramm/9
and
..2)
lEI
El6B7
~
(0, 763tlta.l
LeRend
sta:xiard deyjatior
1500
.......
~139J
1219
(1.35t!
1.1)
.
(t SIoOt/to)
I!]
IUOO
n
m
Ita)
Ita)
(O,8S9t1'I (O,28
';00
(O'
np
I
(O,683t
be 614
Ita)
size
?c:
fIJ1.
I
538
(O,fa)
t/!B)
(O Ita) III (O;) ;1
III
"
:':1
:D5
(0.339
t/ha)
I
c:
Sorghlm.'1-bize/
Ihricot Beans
(smh)
- SJq)le
",
';;"
I c::
Eimer I.heat
(sm)
(t)
(p/be)
(ba)
(be)
(p)
(aj)
(I)
(f1 )
I<S
Fiq. 2 shows that the yields of fields with sorghum-maize-haricot beans
mixed cultivation are much higher than the yields of fields planted
with other crops. It shows also that mixed cultivation brings higher
production than monocultures: Compare (smb) with (sm), and (p/be)
with (p) and (be).
- 13 -
Comment
to yield of sorqhum
In fig. 2 we can see two average yields
tons per hectare
everyone
haricot
with 25 samples,
all of them containing
ex-
sorghum and maize.
The lower yield
which
1,54 metric
(t/ha) and 1,35 t/ha. The larger figure resulted
from the calculation
clusively
for sorghum,
figure was calculated
contained
beans.Though
the above mentioned
the three crops sorghum, maize
here the sorghum yield
sorghum-maize
per area
(9 m2) is considerably
culture.
Intercropping
For economic
out of 49 samples of
obvionsly
calculations
samples,
higher
and
is lower than from
the total grain yield
in the fully intercropped
raises the yield per acreage.
I used the figure of 1,35 t/ha, since
this average yield may be the most relevant
for most farms and
households.
Crop rotation
The farmers know about the advantage
significance
the yield
for the yields.
for a sorghum
of crop rotation
If all other
and it's
factors remain
fi~ld will be higher
stable
if the last crop
grown on the field was a pulse than if the crop on the fieln
was grain sorghum for the fifth year in sequence.
Since my primary
duction
the variations
be compensated
sites.
option was the assessment
crop rotations
by the spatial distribution
In an attempt
cord the position
standardises
due to different
of the total proof the sample
to deal with the problem
of a field in the rotation
interviews,
will
I tried to recycle by making
but in this way reliable
was not to be achieved:
The farmers
unprecise
like: For the time J can remember
in statements
there was always sorghum
cultivation
therefore
answered
information
in this field..."
was beyond my temporal
very vaguely
This aspect of
capacities
and
was neglected.
Since in almost
in sequence,
all fields sorghum is grown for many years
this factor of influence
and
may not be decisive.
-
2.3
The influence
14 -
of some natural
factors on ~e
yields
2.3.1 Dependency between sorghum and maize yields in mixed
cUltivations
As the results of calculations (see app.5 ) show, yields in
Suke vary considerably. Some fields produce 250 kg/ha sorghum
while
in other fields
farmers can harvests
up to 4800 kg/ha
(PC "K'apsomulis").
Where
do these enormous variations
see that most of the cropping
maize-haricot-beans,
to varying
result
from? First we must
area is cultivated
and that the variations
ratios of components.
vice
A first hypothesis
analysed
the slope function
yield and the sorghum yield.
(I didn't
I tried to
of maize yields
versa".
I statistically
cultivated
cot beans.
sorghum"-
may partly be due
verify was the following:
"Yields of sorqhum
increase with the decrease
and
with
exclusively
between
the maize
I u~ed 49 samples taken from fields
with s!l crops sorghum,
maize and hari-
use any of the samples that were extrapolated
ding to the number of stubbles
period.
70r correction
from plants cut during
of these measurements
see appendix2
).
accorthe growing
-
15
-
ETHIOPIR: LRNQ USE QRTR 1963/1964
><
?!i
N
N
-co
'D
-
-.:r
N
II
I
I
0
CO
I
I
I
.,I
-D
-.:r
N
I
I
I
I
I
2 4
I
I
I
II
I
2
I
I
I
I
6 8 10 12 14 16 18 X> 22 24 26 28 3) 32 34 36 38 40
x l(i
.
Fig.
3:
Correlation
sorghum
yield-maize
X
y
:
:
SOR
MAlZ
yield in sorghum-
maize-haricot bean-cultivation, showing tendency of weak
but positiv correlation.
n = 49
x = sorghum sample (g/9m~)
(SOR)
(g/9m ) (MA1Z)
y = maize sample
x
Y
= 1219
= 643
s = 699
sx= 480
RY= 0.1154
A = 546.387
B = 0.079
The variance analysis showed no significant slope function
between
x and Y at a critical
us to make the statement
and maize
value of 5%. That result
of a dependency
between
(y),at least not of a kind that higher
would mean
lower maize yields
Since haricot beans
slope function
calculations
with
sorghum
(x)
sorghum yields
and vice versa.
in the intercropped
between
forbids
culture may change
the
sorghum and maize yields, .1 carried
out
samples taken in fields with sorghum-maize
crops only. The results were the following:
- 16 ETHIOPIR:
LRND
uSE
DRTR
1963/1984
1a
><
c:!i
gj
00
.-t
'"
.-t
.-t
N
.-t
.-t
0
00
'"
1
1
N
2
4 6
Fig.
4:
1
I
I
I
I
I
I
8 10 12 14 16 18 20 22 24 26 28 3J 32 34 :p ~ QO X :
xl<f
y :
Correlation
sorghum yield-maize
yield
in sorghum-maizefields
showing
slightly
more dependency
than in sorghum
maize-haricot-bean-fields,
yet not significant.
n =
x =
y =
x =
Y =
s =
sX=
RY=
A =
B =
The
slope
results
function
rises
25
sorghum sample
maize sample
1390
686
690
656
0.2160
400.101
0.206
(g/9m2)
(g/9m2)
(SOR)
(MAIZ)
very little comparedto the
above, though the variance
prove a significant
dependency
analysis
between
Result: First hypothesis
2.3.2
SOR
MAIZ
does still not
the two factors.
was not confirmed.
The factors soil depth, slope gradient chern soil fertility,
plant available water capacity,
bulk density of the soils
The soil depth
were measured
(in centimeter)
cont.,' and
and the slope gradient
for the different
drill and an inclinometer
phosphorus
sample
sites with a soil
respectively.
--
(in %)
----
..
- 17 ~.J~:J. _c~oE .!p~cif:lc_lin~a~ !:egr~s~i2nli
In order
to
achieve
reliable
results
adressing
of yield
from gradient
and soil
depth,
form categories for different crops.
IA) Yields
the
dependency
have to
we necessarily
of smh-fieldsl
This category
maize,
and/or
contains
haricot
Yield - slope
qradient
all yields
of fields
beans respectively.
n
x
Y
x
=
92
=
yield
=
test plot
20.23
= slope
gradient
of
all
with
sorghum,
(%) (SLOP)
smh-crops
inside
9m2
(g) (GRAIN)
y = 2015
s = 9.72
sx= 1056
RY= - 0.1815
A
B
~
~
)(
ETHIOPIA;
LAND
USE
= 2414
= - 19.71
OATA 1ge3/1ge~
S
:R
~
~
:$
~
~
~
~
?1i
~
\D
~
N
~
co
~
4 8 12 16 :!) 24 2B 32 36 lIJ 44 48 52 56 00 64 68 72 76
Fig.
5 :
results,
very
(F
=
slope gradient
decreasing.
small
3.06)
SLOP
Y:
GRAIN
Correlation sorghum-maize-haricot-bean-yield/9m2slope gradient,showing no significant
dependency
between the two factors.
increasing
With
X:
(-0.18)
doesn't
the yield is according
The correlation
but
negative,
coefficient
though
show any significance.
the
to these
R however
variance
is
analysis
18 -
Yield-soil
depth
n
= 92
x
= soil
y
=
x
= 53.91
Y =
s =
sX:
AY=
B =
yield
depth
(em) (DEPH)
of all smh-crops
inside
9 m2testplot (g) (GRAIN)
2015
29.39
1056
1644.5
6.88
~)(
ETHIOPIA:
lAND
USE
DATA 1983/198.
s
~
~
~
:j
9
~
N
<""1
~
~
~
-,-
-
-.D
N
to
..;f
1') :;r!
Fig.
25 3) 35 lIJ 45:0 55 ro 65 70 75 00 85 CXJ95 100
6:
x:
DEPH
Y:
GRAIN
Correlation
sorghum-maize-haricot
bean yield/9m2soil depth, showing
again only unhardened
tendency of dependency.
Again we have a very small positive
and an unproved
dependency
Yield
-
The
Soil Fertility
II
110
chemical
between
correlation
(0.19)
x and y (F=3.42).
soil fertility
Map of the Suke Catchment"
in prep.) was the basis for these calculations.
the agricultural
classes:
coefficent
area is divided
(by G. Weigel,
In this map
into four soil fertility
-
19
-
1: low soil fertility
2: low to medium
3: medium
soil fertility
soil fertility
(incl. area defined
"medium soil fertility
high soil fertility
as:
in years with much rainfall,
in dry years")
4: high soil fertility
from this map I extracted
the fertility
class corresponding
in each case with the sample plot location.
This soil fertility
W. SEILER
(1983). The soil depth is rated as main
(indicating
rooting
hazard
map is based on the soil map of R.BONO
the water and nutrient
exceeding
are rated as secondary
factors.
The nutrient
contents
stoniness
as well as
and flooding
of the soils are only rated if they are
extremely low. A general
included because
-
factor
storage capacity
depth). Waterlogging,
and
rating of the nutrient
levels was not
the very limited number of samples made a statement
of the sptial distribution
of nutrient
levels doubtful;
- there was no investigation on the correlation
nutrient levels and yields in the area;
between
- the majority of the nutrient problems in the Suke area
could be solved by the ocal farmers, whereas the soil
depth can not be improved.
The slope gradient
was not included
there were no data available
and
in the rating because
on the correlation
between
slope
yields.
Results
of linear regression:
n
= 92
x
y
= soil fertility class 1
= yield of all smA-crops
x
Y
= 2.75
= 2015
sx=
sx=
R =
A =
1.05
1056
0.0057
1999.6
B = 5.68
plot
- 4 (FE)
2
inside 9 m test
(g) (GRAIN)
-
-
-
20
'b
ETHIOPIR:
><
LRND
USE
DRTR
1963/1964
~
~
N
In
~
:g
@II
~
~
~ II
Ci!i
~
-
\0
,I
N
-
co
-.:t
1
Fig.
2
7: Correlation
chern. soil
R (0.0057)
as well
3
- plant
FE
GRAI N
sorghum-maize-haricot
bean-yield/9m2
fertility
showing no relation
as the
variance
prove no signifacance
in the
and soil fertility classes.
Yield
X:
Y:
available
ananlysis
slope
water
function
capacity
-
(F= 0.0029)
between
in top
yields
SO cm
The data on plant
available
water capacity
were calculated
out
of the data on pore size distribution
for the different
soil
horizons
in top
50 cm, drawn of the SCRP report
on "The Soils
of Suke
Defined
pores".
-
Harerge
Research
as "available
for
Unit/Ethiopia"
by R. BONO/W.SEILER:
plants
were "fine pores"
and "medium
n = 77
x = plant
y
=
yield
x
= 88.34
Y
=
s
available
of all
1996.2
= 21.05
sx=
RY=
A =
B =
998.6
-0.1144
2475.7
-5.43
water
smh-crops
test
plot
capacity in top
(cm)
inside (WATER~
9 rn
(g)
(GRAIN)
50cm
-
co
....
-
21
ETHIOPIA:LANDUSEDATA1983/1984
><
9
N
11"1
:$
9
N
C""I
I
.
.
\D
....
I
2 I
I
N
....
I
I
I
I
II
I
I
a)
..;t II
43 4a 53 58 63 6i373 78 83 00 93
'
.
103 113
. . . I
123
133
x:
Y :
Fig.
WRTER
8RRIN
8 : Correlation sorghum-maize-haricot
bean-yield/9
plant available water capacity in top 50 cm,
showing tendential dependency.
R (O.ll) indicates
that the yields rather decrease
m2 -
with increasing
available water capacity of the soil, but since R is very small
and the variance analysis shows no significance (F = 0.9943),
it is not possible
of dependency
to give a positive
between
x and y. However,
could mean waterlogging
problems
crop yields,
maize.
Yield
especially
- phosphorus
content
The data on phosphorus
Because
answer to the. question
high water availability
which negatively
affect
of the soils
content
I also took from BONO~SEILER,
1983.
there were very often no data listed for 50 cm soil depth,
I used the value appearing
n
= 77
x
= plant
y
=
x
Y
= 5.2692
= 2026
= 2.4689
s
sx=
RY=
A =
B =
next to this depth.
available
water
yield of all smh-crops
1027
0.2224
1539
92.53
capacitiy
in top 50 cr.\
(cm) (WATER)
inside 9 m2 testplot
(g) GRAIN)
- 22 -
-
NO
ETHIOPIR: LRND USE DRTR 1983/198.
)(
~
~
N
U"\
?f
~
9
~
~
~
~
~
II
I
<
- I
\0
-
JI
~
11
~
~
ex)II
...:t
0.5
Fig.
9:
1.5
Correlation
phosphorus
dependency.
R (0.22)
Though
phosphorus
yields.
Yield
Data
2.5
is
content
3.5
7.5
6.5
sorgh~-maize~haricot
content
of the soils,
rather
small,
produces
The variances
-
5.5
4.5
analysis
the
bulk
density
of
the
soils
on bulk
density
of
the
soils
9.5
show that
influence
a significant
from
X:
Y:
PHOS
GRRIN
bean-yield/9m2showing
significant
results
a siqnificant
gives
8.5
the
on the
value
for
BONO/SEILER, 1983
n = 58
x = Weight of 1 cm2 of soil (BULK)
y = yield
of all
smh-crops
inside
9 m2 testplot
(g) (GRAIN)
x = 1.1.086
Y
= 1902
sx= 0.0849
s = 889.22
RY= 0.0968
A = 778.04
B = 1014
F.
-
-
-
23
co
ETHIOPIR: LAND USE DRTR 1963/1964
x
9
If\
9
.
.
--
I
..0
I
N
co
I
..;t
~
Fig.
10:
The bulk
ficance
IB)
;1J,92 f)4 ,%,~
Correlation
bulk density,
density
for
of
the
The categorie
linseed,
in
Suke:
1,P4
1,(E
the
soils
yields
" rest
cr"
comprises
Peas,
beans,
beans
(if
31.45
542.03
14.33
339.54
0.1366
440.29
3.24
of
not
in
is
"rest
the
barley,
cr - slope
n = 91
x = slope
Y = yield
x =
Y =
s =
sx=
RY=
A =
B =
UO
seem to
The F = value
the
rest
1,16
doesn't
with
haricot
1,12
],24
x:
Y:
BULK
GRR]~
sorghum-maize-haricot
bean-yield/9m2showing
no dependency.
yields.
Calculations
vated
1,00
I
not
be of
any
signi-
significant.
crops "I
following
Emmer wheat,
6mb-mixed
crop),
crops
culti-
lentils,
and tef.
qradient
gradient
(%) (SLOP)
of all
rest
crops in
9m2 testplot
(GRAIN)
(g)
- 24 -
rest cr - soil depth
n
= 91
x
=
y
=
soil depth
(cm) (DEPH)
yield of all rest crops
x
= 35.49
Y
=
sx=
sy=
R =
A =
B
in 9 m2 testplot
542.03
23.09
339.54
0.0449
518.62
= 0.66
rest cr
chemical
-
soil fertility
n
= 91
x
= soil fertility class 1 - 4
= yield of all rest crops in
Y
x
Y
s
(g)
(GRAIN)
(FE)
9 m2 testplot
(g)
(GRAIN)
= 2.6374
=
542.03
= 0.9834
Sx= 339.54
Ry= - 0.0121
A
B
= 553.03
=-
4.1699
In any case the linear regressions
dependency
1.1.1.
~
of the yields
<l.ro.:e§-ee£i.!i_c
Yield of smh-crops
do not prove any significant
from any of these factors.
IDu1,t;p!e_l;...nejlr-
(dependent variable)
;:.eg:r~s§~°B.
with
-slope gradient(SLOP)
-soil depth (DEPH)
-avo water capacity
(WATER)
-phosphorus content
(PHOS)
undependent variables
M~asures
of descriptive
statistics
~
GRAIN
SLOP
PHOS'
DEPH
WATER
2026.28
20.72
18.03
51.86
87.94
standard deviation
1027.01
9.87
13.08
27.05
21.26
- 25 Correlation matrix
GRAIN
GRAIN
SLOP
PHOS
DEPH
WATER
1.0
0.18
0.05
0.21
0.16
-
WATER
E!!22.
1.0
0.05
1.0
- 0.47 - 0.02
0.11
0.03
1.0
0.004
1.0
Reqression
reqression
GRAIN
SLOP
PHOS
DEPH
WATER
F-value
coefficient
2574.21
8.86
3.24
6.27
7.18
Standard
0.44
0.13
1.66
1.71
1014.34
error of estimate
Coefficientof determination
multiple correlationcoefficient
Variance
analysis:
When the yields
calculations.
F-value
the multiple
analysis
2.3.3 Summarizinq
(4,73)
in categories
correlation
as we see in above
coefficient
gives no significant
interpretation
If we take all 183 samples
cant dependency
0.075
0.2742
.= 1.4839
are compiled
and the variance
in~o
remains
small
result.
of the results
account we get a signifi-
of the yield from the factors
and "slope gradient".
73
73
73
73
1,
1,
1,
1,
This dependency
"soil depth"
is feigned through
the
descent of yields from smh fields (samples 1 - 92: m=2014 g/9m2)
to pulses
fields
(samples 93 - 183: m
If we carry out these calculations
in two categories
= 542
g/9m2).
with the yields compiled
(A) "smh" and (B) "rest cr", the
results
come out quite differently:
In the cateqorv
"smh" except from the phosphorus
is no significant
chemical
soil fertility,
plant available
Reason:
dependency
slope gradient,
water capacity
Generally
there
from soil depth,
bulk densitiv,
and
of the soils to be confirmed.
grown ou good soils:
In the other cateqory
than smh-fields
of the yields
content
"rest cr" for yields
there is no significant
In the interpretation
from all other
dependency
to see.
of these results we must conclude
that
- 26 -
not the tested natural
yields,
factors are of great importance
but other factors are decisive.
Motivation,
for the
know-how,
and above all the means of production
(oxen) and the working
power
and harvesting
for ploughing,
sowing, weeding,
disposal are more important
activities in time.
Human
and social factors
yields
and production
natural
2.4.
factors
are therefore
more
the farming
important
for
of the fields than the above considered
(see also M. GALIZIA,
1985).
Land cover mapping
2.4.1 Method
for Land cover mappinq
For the sketching
of a land use map of the research
had a base map 1:5000
different
(verified
heliographies
with conventional
These mappings
months
in order to accomplish
at a farmer's
area I
in 1983) at my disposal.
In
drawn from this map I put the fields
signs for the different
were overworked
crops,
in pencil.
again and again during the
of the. field stay (Map 3, P
Since I could only estimate
and specifically
the sizes of the mapping
the sizes of the fields~ I measured
units
together
with a research assistant 87 lengthsand widths of fields by
meterband. These measurements were compared statistically
with the converted
mapped
lengths and widths.
The results
showed that the big fields were drawn only very little too
large while the small fields were overestimated
It became
clear that the assessments
of field-lengths
less correct than those of field-widths.
Correlation
of mapped
and measured
n
= 47
x
y
= mapped
x
Y
s
=
measured
= 44.45
= 34.98
= 32.23
field lenqths
(MMV) (m)
(MRV) (m)
sx= 29.01
RY= 0.9086
A = 1.37
B = 0.82
F-value: 213.03
= significant
(I,
by some 30%.
45
were
- 27 Correlation
of mapped
n
x
y
and measured
field widths
= 36
= mapped (MMH) (m)
= measured (MRH) (m)
x = 51.92
Y = 45.17
s = 29.98
sx= 26.66
RY= 0.8724
A = 4.90
B = 0.78
F-value: 108.33
= significant
(1, 34)
The sizes of the fields were counted out by using a grid
with one millimeter
according
squares.
to the results
of a computer
These values were corrected
of above's calculations
programme.
In the enclosed map which was to be printed
of 1:10'000
--.1
by means
the originally
in the scale
drawn fields were left untouched.
Map "LANDUSE ANDLANDDISTRIBUTION IN THE AGUCHOVALLEY"
see
p.
56
.
I List of plot holders see appendix4
- 282.4.2 The ~ultivated
Fig.
area of the map
11: CROPPING AREA
Lentils
Chat
\
Emmer Wheat/HaricotBeans/Flaxseed
"
Barley...
"
.....
Sweet
Potatoes...
Peas
Sorghum/Maize/Haricot
Beans
TOTAL
ISOrghumlMaiZelHaricot
Peas
Beans (s)
(p)
Beans
(be)
Sweet Potatoes
72.4
10.9
%
%
(B1.0Sha)
(11.
84ha )
6.9 %
3.1 %
(7.69ha)
( 3.45ha)
2.7
(2.99ha)
Barley
(sp)
(ba)
Lentils
(1)
1.75%
(1.96ha)
Chat
(ch)
1.34%
(1.50ha)
Emmer Wheat
(aj)
0.60"10
(0.61ha)
Haricot
(A)
o. 30% (0.
(f1)
0.25"10
(t)
0.19%
Beans
Tef
IF1axseed
Tab. 1:Cropping
Harerge,
area of the mainly
%
for the main crops 1983
I
32ha)
(0.21ha)
(O.28ha)
cultivated
111,9ha
I
crops in Suke,
- 29 -
The figures
area
in table 1 show that most part of the cultivated
(72%) is used for sorghum-maize-haricot
culture.
Sorghum
are generally
is staple
food, and therefore
maize
The people
from their fields.
planted
the better
the next harvest,
when the supplies
can, im this case, early harvest
fresh
Roughly
are
in half of the smh-area
estimated,
haricot beans
(=40.5 ha). Haricot
beans
grown as cash crops by very poor as well as by wealthier
Peas make up to 10.9% of the cultivated
the other
"small crops",
Sweet potatoes
crop production,
in September.
farmers.
the diet.
less area than recorded
is that in expectancy
in this
of an unsufficient
So part of the 3.45 ha recorded
to the harvest
are
area and are used, like
the farmers planted more sweet potatoE
do not contribute
fields.
for enriching
make generally
map for 1983. The reason
usually
soils
used for this crop. Maize can serve for bridging
over the food shortage before
are finished.
beans in mixed
fields than
in the map
of 1983 but are freshly planted
They will give food after 4-5 months,
which will be in a
time when no other crop of the new season can have ripened yet.
2.4.3 The non-cultivated
area of the map
Fig. 12:~cultiva~ed
area
Pasture
open
Shrubland
and Pasture
Bushland
TOTAL
122,lha
- 30 -
The not cultivated area comes to 122.1 ha, which
of the total surface area.
I
I
Bushland
28.8
ha
Pasture
51. 7 ha
(afforested:
23.6 ha)
Open shrubland and pasture
16.7 ha
Long grass for cutting (PA) 11.5 ha
Open shrubland and.long
grass (PA) 6.8 ha
Fallow
122.1
6. 8 ha
ha
Tab. 2: Use of non-cultivated
for 1983
Pasture
is 52,2 %
is mostly
I
I
area in Suke, Harerge,
used for small stock like sheep and goats and
not for cattle. Boys and girls who are not yet integrated
other work take care of the animals.
The bushland
supplement
wood
serves as a reservoir
the sorghum
supply
throughout
and braches
quires
therefore
mountains),
more attention
from the cook especially
is strongly bound to the fire to attend
grazing,
straw by wood
and controlled
is prohibited
people
houses.
in 1983. Various
Since
at the
time. The cook
it. If she can replace
she gains more free time ro fulfill
by the peasant
association.
for covering
There pasture
Fallow
land
political
the room a newly constructed
makes 6.8 ha. I defined
"fallow"
but was not taken u~der the plough
and economical
factors
for the amount of fallow area and therefore
of the
for boi-
(11.5 ha) was spared out in 1983 from
as land which once was cultivated
covery
It re-
in order to grow long grass. This long grass is later
sold to private
or repaired
stock
a "straw fire".
ling and cooking meals which need a long cooking
A part of the qrassland
col-
straw when burnt has the disadvan-
down very fast, likewise
partly the sorghum
other duties.
fire-
the girls and women
of trees to extend the sorghum
the year. Sorghum
tage of burning
supply to
straw stocks. For this traditional
(in the Chercher
lect bushes
for firewood
in
are important
for the possible
re-
soils:
present
time
the
peasants
are
still
passing
through
- 31 the
process of redistribution of land, be it as receivers, be it
as beeing
forced to hand over part of the land because
the average
enough
farm size, everybody
it exceeds
prefers not to show that he has
land to allow part of it to lie fallow. This would be
interpreted
as a sign of wealth,
association
official
distribution
this problem
since every landlord
shift or scamper
fear of having
or agent had unlimited
all land available
the peasants
it for re-
unknown
power to
peasants.
So this
and produces
still
for leaving part of the soil fallow
for cultivation).
for re-
space for not having
Instead of leaving
to use
fallow
sow peas which don't need much care; ploughing
weeding
is not necessary.
Another
reason
Leavinq
rightless
the land taken away produced
(in case there is the economic
constraint
could request
existed in a nowadays
away the absolutely
now an unwillingness
covery
(e.g. the chairman)
peasant
e.g. to a newly founded household.
Before revolution
dimension
and the responsible
and
for sowing peas is the lack of oxen, a major
for poor peasants.
fallow
is a method
used by peasants
for improving
the soil's fertility
for many years in the past. WESTPHAL
(1975:112)
writes that as a rule sorghum is cultivated as long as the soil
is not exhausted. Then the fields should be left fallow for
two or three years,
pulses'
only
turn, followed
cycle is completed
I could not observe
again by sorghum.
pressure
2.5
Then it is the
This crop rotation
after 12 to 15 years.
nor interview
three years. A 6hortening
occured
used for pasture.
a fallow period
of the crop rotation
in the recent past, possibly
in the research
The agricultural
of two or
cycle must have
due to rising population
area.
production
2.5.1 The food production
Sorqhum
and maize
For assessing
harvest
yields
the samples
the total grain production,
I used the average
(sorghum: 1350 kg; maize:714
containing
kg) resulting
all three crops sorghum,
from
maize and hari-
cot beans.
The sample size of 135 for an area of 234 ha produ-
ces aquite
dense sample distribution
and allows the use of the
- 32 average yield for calculating
the cropping area.
the total crop production
For crops other than sorghum, maize and haricot
multiplied.the average
yield by the cultivated
Fi~:PRODUCTION
IN surE AREA (1983)
Sorghum: 110' 226 kg
(Sweet Potatoes:12'240
Maize:56'978
Haricot
kg;Estimation)
kg
Beans: 10'085 kg
Peas: 7246 kg
Beans:5145
kg
Bar1ey:2096
kg
Lentils:664
kg
Emmer Wheat: 365 kg
Fiqure
13: Total production of the Agucho
catchment, Suke, Harerge, for the
main crop 1983
out of
beans I also
area.
- 33 In Suke every third or fourth year a production
rainy season, can be achieved.
ful. CountrYWide
the main
only barley
In Belg 1984 sowing was not success-
the area cultivated
season cropping
area
in Belg makes around
(MINISTRY OF AGRICULTURE).
and Emmer wheat could contribute
tion: A successful
in Belg, the small
Belg production
4~sof
In Suke
to the Belg produc-
can add two to three metric
tons of grain to the main Kremt production.
2.5.2 The biomass
Method
production
of assessment
The straw and roots of a number of sorghum and maize plants
were weighed
drying.
in the field at harvest
After 14 days it was reweighed
loss. The weight
The samples
reduction
3: The biomass
Sorghum
Maize
Haricot beans
Peas
Beans
Barley
umtils
Emmer wheat
Linseed
Tef
was 38%.
at the research
together
station.
1350 kg/ha on 81.05 ha
110'226 kg
714 kg/ha on 81.05 ha
249 kg/ha on 40.5 ha
56'978 kg
612 kg/ha on 11.84 ha
669 kg/ha on 7.69 ha
683 kg/ha on 2.99 ha
1,96 ha
339 kg/ha on
600 kg/ha on 0.61 ha
206 kg/ha on 0.28 ha
7'246 kg
10'085 kg
5'145 kg
2 '096
The part of the grassland
365 kg
58 kg
0.21 ha
3.45 ha
186 kg
12'240 kg)
which was secured
was used to assess grassland
grass and pasture
could be harvested
productivity.
when treated
in the
from pasture
The prqduction
area of 11.5 ha amounted
land in the catchment
kg
669 kg
Biomass sample weight and total production
Agucho catchment, Suke, Harerge, for 1983
from the protected
with the
production
859 kg/ha on
3548 kg/ha on
(Sweet potatoes
)
estimation, see p.
Tab. 3:
for
to assess the moisture
of the other crops were harvested
straw and analysed
Tab.
time and left there
7820 kg. From all
35.2 tons of grass
in the same way.
2.5.3
Sorqhum
Without
straw
roots
meter.
34
for firewood
sorghum
plants
For the total'sorghum
for firewood
-
amounted
supplv
produce
area of 81.05 ha the straw usable
405.25 metric
quent use of the roots
usually
Provided
sorghum
fodder,
or maize
for 110 families
have
around
half of their
fields
In this case the demand
out of other
from trees.
sources
and to make
3: Collecting
is ~ask
of women
78 families
that
border)
davs.
the people
during
bushes
and rare branches
feed a very
the growing
small part of the
period
of the sorghum
the time to be covered
wood then, but collect
to replenish
for firewood
to sorghum
of 1983 could be
the catchment
straw
and children.
by other
straw supply
throughout
the straw supply
it last until the next harvest.
bushes
supplement
the supply
inside
out too den-
are fed.
don.t use up first all their
and start to collect
year bushes
which
and
for 121 days would have to be covered
plants. which still prolongs
firewood-sources.
In fact the people
for firewood
fully plus
like collecting
In realit¥
straw to their cattle
246
152.7 tons.
after thinning
plants,
(67 families
for
Foto
except
as it is the cus-
add another
employed
all straw is used for burning
used
whole
would
straw is generally
not for cattle
sely standing
tons in 1983. The conse-
for the same purPOse,
tom in some parts of the country,
In Suke sorghum
500 g of straw per square
the
in this way
- 35 -
3.
Land distribution
3.1 Method
of mapping
The precise knowledge
of the research
assistants
(RAs) about
the farmers land and fields made it possible to produce a map of
all the fields in the catchment and to allocate the farmers
living
from them. In the lower parts of the valley
research
assistants'knowledge
was sufficient,
medium and upper parts inquiries
had to be made.
The first list of holders
that some names occured
the
while
in the
from the local population
contained
frequently
142 names.
Soon we noticed
but stood for the same
person. The mentioned list showed the name "Mehammed" or
"Ahmed" 21 times. If the holders of this name had also the
same father's
name, the allocation
of the plots to the holders
was really complicated.
Another problem arose with the young farmers who cultivated
their own fields but lived with their families and added the
production
the
of their
father's
fields to the fathers production.
In such cases
and the son's fields were added together
in
order to get the total farm size one family had to live on.
A considerably
the catchment
high number of farmers cultivates
area as well as outside.
inside
It was not possible
assess the size and crops of the fields outside
so that I had to exclude these farmers
fields
to
the boundary,
from the analysis
of
the mapping.
Information on the fields outside.
the mapped area but cultiliving inside the area was obtained from
vated by farmers
M. Galizia
(1985).
At the end there remained
farm sizes were record~d
the map
a list of 68 farmers whose
total
and their land size calculated
from
(list of field sizes and map see app. 4)
3.2 The average
farm size
How many hectares
can a locally well-off
farmer cultivate,
how many a locally poor farmer?
The average
farm size is 0.8514 ha cultivated
land
(without
pasture etc.), as calculated from the plots of the 68 fully
recorded farmers. The standard deviation is 0.513. Seventeen
and
- 36 farms
(1/4) show an area of more than one ha; the largest
farm was 3.1, the smallest
0.2 ha. Naturally
a family can not
live from a 0.2 ha farm, so that the family members
work
on other farms or need other means
their income
ners,
Number
(like handicrafts,
skills for constructing
for completion
production
houses,
have to
of
of woodden
contai-
just to mention
a few).
of Households
14
13
Fig.
14: ~I~~])_SIZEPER HOUSEHOLD
12
11
10
9
5
7
.
6
5
4
3
2
Field Size
(ha)
0-<J.2
0.41-0.6
0.81-1.0
1.21-1.4
1.61-1.8
2.01-2.2
0.21-0.4 0.61-0.8
1.01-1.2 1.41-1.6
1.81-2.0 2.21-3.1
Figure
14: Distribution of the size of cultivated
household in Suke, Harerge, 1983.
In Africa
farmland
fallow
the farm size per person
and non-cultivated
is 0.58 ha (including
land like woods,
land) In Suke we find 5.3 members
1985), the farm size per person beeing
vated plus 0.71 ha pastoral
For comparison:
America.
0.3 ha/pers.
---------
land per
per family
and
(GALIZIA
0.29 ha (0.85 ha culti-
and bushland
in Asia,
pasture,
per family).
1.13 ha/pers.
in Latin
- 37 Tab. 4: Distribution
According
of cultivated
to the MoA in Ethiopia
1,5 % of the farms are smaller
20.7
26.1
27.5
25.3
%
%
%
%
land in Ethiopia
are between
are between
are between
are
0.11 ha
0.51 ha
1.01 ha
larger than
not included are Tigray, Wello
lack of data
than 0.1 ha
and 0.5 ha,
and 1 ha,
and 2 ha,
2.01 ha
and Eritrea because
of
MeA, Statistics Section, Planning and
Programming Department, Addis Abeba, 1977
3.3. Farm size and crop diversification
The advantages
crop rotation
are well-known.
the following
of a diversified
for maintaining
soil nutrients
of crops
such as
and fertility
With the help of my data I tied to verify
postulate:
"A large farm area enables
crops.
cultivation
the farmer to cultivate
Farmers with more land have more security
climatic
variations
different
extent".
which can affect different
x = field size (FIELDS) (m2)
y = number of cultivated crops
n
68 (sample size)
=
x
Y
= 4.514
= 8514.0
sx=
sy=
R =
A =
B =
1.791
5128.4
0.605
691.9
1732.6
diversified
in cases of
crops to a
(PLANTS)
- 38 -
Averagely
a farmer cultivates
crops. The correlation
differenciation
varieties.
coefficient
in Fig.
has been made between
would
certainly
(R=O.6) proves
more different
crops,
ecoloqicallv:
requirements.
different
and that the farmers
there
the correlation
But still this
Crops have different
in Suke take this
environmental
crops insure the farmer to have
to the non prdictable
natural
with
a successful
factors,
this only counts between
certain
much damaged
(and some varieties
limits.
If
But if there
particularly
due to it's drought-resistence,
suffer heavy yield reductions.
crop,
be they as they
is no rain, there is also no plant growth.
is little rain, sorghum
to plant
that can be drawn out of these possibi~
Many different
come. Of courses
sorghum
field area allows
at least part of his fields cultivated
fitting
4.51 different
19 is 0.6. No
be even higher.
that a larger
chance. The advantages
lities are twofold.
First,
ha with
If this would have been possible,
coefficient
result
0.8514
is
but maize may
That leads to the second point
of advantage.
Economically:
If there is always one crop in your field with
at least medium yield,
prices
you are not as dependent
on market
like a farmer with two crops which might. both be
strongly
reduced
in harvest.
If a farmer can decide himself
about the time for selling his crops, heis not subjected
blackmail
Summing
bility
by the market
to
conditions.
up, the farmers who have larger farms have the possito plant more varieties
gives them the opportunity
and more different
to better
react to varying
factors or at least not to be so heavyly
conditions
on market
(rain). Furthermore
variability.
differences
get richer
crops.
affected
That
natural
by changing
this makes them less dependent
All in all, high land distribution
result in rising wealth
during problem
and the poor get poorer.
situations
polarisation:
The "rich"
like insufficient
rain,
- 39 4.
Food supply
4.1 The averaqe
For assessing
cropping
farm.,production in 1983
the farm production
areas by their specific
I multiplied
average
the different
yields.
Tab. 5: The averaqe farm production in Suke. Harerqe. for 1983
crop
fi?Jyield
% of cult. av. farm 2
land
area in m
Sorghum/maize/haricot beans (72.4%) 6164 m
902 m 2
(10.6%)
( 6.9%)
( 2.7%)
( 1.4%)
peas
beans
barley
sweet pot.
rest
2
587 m2
230 m2
118 m2
513 m2
8514 m2
832
440
76
55
39
kg sorghum
kg maize
kg haricot beans
kg
kg
16 kg
42 kg
1500 kg
;===============::-:=
Table 5 shows that an average farming family in Suke can harvest
8.3 quintals of sorghum, 4.4 quintals of maize and between 16 kg
and 76 kg of other crops like peas, beans, barley, and' sweet pota-
toes.
Tab. 6: The farm production in calories for Suke. Harerqe, 1983
crop
cal./loo g eatable
substance
cal. amount
sorghum
maize
309
327
2'570'880
haricot beans
341
337
340
262
97
259'160
1851350
peas
beans
barley
sweet pOtatoes
1'4381800
1321600
41'920
40'740
6Iq
(ca1./loog substance' out of v. BLANKENBURG/CR1ER,
Table 6 shows that the total production
in 1983 amounted 416691450 cal.s.
1971)
of an average
farm
- 40 -
After GALIZIA
persons.
lories
(1985) the average
For Ethiopia
5.3
of 2330 ca-
per day.
calorie
. 4'669'450
in Suke numbers
FAO states a requirement
for one person
The disposable
family
:
number per person
5.3
=
365
:
.
in Suke is therefore:
2414
cal.
,
number of: days of a
of average farm pro- I family/
I year
duction for one year: members:
total amount of cal-
1983's
slightly
sufficient
:
under-average
Kremt harvest
is therefore
to satisfy the needs of an average
family.
This statement doesn't include the quality and completeness
of the food, which would have to be further examined.
The population's
weather
reduced
resistance
to diseases
and the still high infant mortality
possible
qualitative
malnutrition
and harsh
give sigh of a
even in noncatastrophic
years.
In fact, the farmers
reaction
after having harvested
sorghum
in January
1984 shows that at least for many of them the
production
of the fields was not considered
Many
sold part of their cattle or smallstock
money
for paying
sufficient:
in order to get
the tax of 20.- Birr. In years of good har-
vest they don't sell cattle, but only of the field production
for paying
taxes.
Early 1984 was the beginning
yields
situation.
The
in Belg and Kremt 1984, the year after the measured
harvest,
were very
to 170.-
(Jan. 84:40.-),
during
of a worsening
1984 through
low. The prince
for a quintal
sorghum rose
showing the severe shortage
1985, which could eventually
averall
famine also in Chercher
duction
fails.
mountains
of food
lead to an
if the 1985 pro-
- 42 -
5.
Considerations
5.1 Contour
bunds
Conservation
for soil conservation
and "fanva vuu" graded bunds
measures
in the Chercher
were carried
mountains
part of the countrywide
nity Forests
decreasing
January
and May 1984, as
conservation. campaign
and Soil Conservation
of the Ministry
The farmers
between
out in the AGUCHO-Valley
of the Commu-
Development
Department
of Agriculture.
in the Suke area face not only the problem
soil depths
to soil erosion,
fight the problem
and chemically
degrading
but in parts of the valley
of waterlogging
This is due to the widespread
of
soils due
also have to
during the rainy season.
vertisols
with high contents
of Montmorillonite-clays.
Waterlogging of more than one day
can be hazardous to maize
(EDWARDS 1981:110).
In order to find a solution
Suke catchment
conservation
developed
is primarily
1: The graded
waterway
part of the
area was treated with a different
It has two fundamental
bund which
for that problem,
ditch
in Kenya:
type of
The "fanya yuu" graded bund.
differences
compared
to the contour
used in Ethiopia:
(in Suke 5%) shall drain the water to a
instead of collecting
and forcing
it to infiltrate
into the soil, as the contour bunds do; this is specifically
advisable
for humid zones of the country
a low water holding
and for soils with
capacity.
FiRure 15: Cross-section
of "Fanya juun conservation bund
with excavated soil thrown upslope and the basin below
the bund.
H.HURNI, 1983
- 43 -
2: The wall is hillside
of the ditch and not vice versa
("fanya yuu" = "throwing
shorten
up" in Kiswahili
of forming
the processes
tal bunds by eroding and accumulating
than with contour bunds.
5.2 Loss of cultivable
The peasants
were generally
two horizon-
soil matter
more quickly
not delighted
measure.
their repulsion
by the construction
The argument
mostly
heard
of "fanya yuu" was that the construc-
tion of "fanya yuu" graded bunds
therefore
This will
between
land due to conservation
of the new conservation
to explain
language).
terraces
loss of valuable
needs more
cultivable
space,
and that
land is higher
with
"fanya yuu" bunds than with contour bunds.
Since this could become
a very important
lem possibly
decisive
the farmers,
the space requirements
vation
methods
compared
width
for the acceptance
socio-economic
prob-
of the measures
by
of the two different
(contour bunds versus
"fanya yuu" bunds)
conserwere
in this study.
of wall/ditch
combinations
(as carried
out in Suke
catchment)
(Mean of different
contour
measurements)
bunds
"fahya yuu" graded bunds
waterway
(used in
"fanya yuu" conservation)
According
to the results
the average
1.8 m
1.58 m
3.36 m
of my measurements
contour bund nee~more
by meterband,
space than the average
"fanya yuu". Of course this statement refers to the conservation measures carried out in Suke area in Spring 1984.
In other parts of the country,
Sh~a
R~gion,
amounts
needed
wider basins
of precipitations
like in Debre Berhan
are needed to cope with higher
so that more cultivable
for the conservation
area in
land is
works.
.
"Fanya yuu" conservation requires waterways to dispose the
water. At a width of 3.36 m they make a considerable part
of the actual
immediate
land loss.
44 -
-
5.2.1 Loss of cultivable
Suke case study
land through
conservation
in the
(March 1984)
Case Study AGUCHO Valley,
Harerqe
Reqion
Method
Above
calculations
vation
ness
measures
have been made with data on the conser-
as carried
(distance between
out in Suke, with
bund, width of bund,
kes as they may occur in most conserved
field conditions.
The assessed
the map,
conservation
including
its imperfectetc.) and mista-
areas under average
area of 121.4 ha was measured
some uncultivated
or very small parts of bushland
area as houses,
inside a cultivation
from
rivers,
area.
Results
LEVEL BUNDS
Total
length of wall/ditch
by width
comb.
35'525 m
of 1.58 m
63'945
m2
30'921
m2
"FANYA yuu" qraded bunds
Total
length of wall/ditch
by width
total
comb.
19'570 m
of 1.58 m
1'640 m
length of waterways
by width
5'502 m2
of 3.36 m
36'423 m2
"Fanya yuU" graded bund conservation covers
an area of 45.6 ha, level bund conservation
covers
an area of 121.4 ha.
percentual
loss of cultivable
"fanya yuu" graded bunds
level bunds
Total
loss of cultivable
carried
36'423 m
land by conservation
measures
7.8 %
5.3 %
land by conservation
measures
out in Suke area in 1984:
2
("fanya yuu") + 63'945 m
2
(level bunds)
= 100'360 m
2
- 45 -
If we divide
this area according
of the cultivated
measured
crops,
to the assessed
and calculate
proportions
it by average
yields
in Suke area in 1984, we find that the main crops on
the lost area give a production
-
sorghum
of
9'810 kg, in market prices of Jan.
84:
E Birr 3924.-
J
maize
5'188 kg, in market prices of Jan. 84:
E Birr 1297.annual
(There may be increased
compensating
The vertical
According
measures
distance
to HURNI
J
=
loss
5221 E Birr
yields between
the bunds,
the loss to some extent.)
between
the bunds
(pers. corn.) the"fanya
in Suke are not ideally
yuu" conservation
spaced, because
the vertical
interval is too large. The appropriate distance between the
bunds should be the s~~e as for the level bund conservation
namely twice the soil depth in order to enable terrace
formation.
If this would be done, the loss of cultivable
7.8 % for the conserved
effectively.
The total
or in annual monetary
land loss in Suke would then be 130'536 m2,
loss 6791 E Birr.
out as recommended
land if conservation
optimal
con-
I used a defined part of the" fanya Yuu" conserv.ed
(l8'850m2)
recommended
is carried
by SCRP
In order to find out the loss of land through
area
amount
area of 45.5 ha, instead of 5.3 % as
5.2.2 Loss of cultivable
servation.
land would
and carried out the calculations
dimensions.
for such
- 46 -
loss by bunds
2386 m2
517 m2
(length 1510 m)
loss by waterway
(length 170 m)
2957 m2
The recommended
the conserved
Itfanya yuU" conservation
cultivable
These
conservation
are relevant
measures
development
if the walls
conserve
whole
but wider
with the assumption
are being maintained
effect will
and ditches
Since the farmer's
problem
waterway,
of the
and conclusions
figures
terrace
need 15.7 % of
land for the construction
measures (for level bunds, without
wall/ditch cOmbination: 14.8 %)
5.3 Remarks
would
is not yet developed
seen in Wollo
before.
of the erosion-conservation
enough
for motivating
his fields on his own initiative,
activities
every year. A
result after 20 to 40 years,
are not destroyed
awareness
is very much dependent
Region that 14 months
on this factor.
therefore
seems
loss of crop production
by higher yields
of
in to regain
aspect.
The loss of land and the resulting
must be compensated
cultivable area.
I have
after the construction
loss of land by conservation
to be a very important
him to
the success of the
conservation measures the ditches were ploughed
cultivable land and to reduce the lost area.
The immediate
that the
on the remaining
- 47 This could be achieved
by the conservation
itself. Primarily
1 see three possibilities:
1.
By accompanying
slopes with
2.
shallow
(level bunds on steep
soils)
problem
(18fanya yuu18 on rather flat lands with soils of high
By draining
of water where waterlogging
clay content.
3.
water conservation
By improving
e.g. vertisols)
the value of bunds
the soil conserving
construction
In general
effect:
or firewood,
the conservation
in Ethiopia
farmer
at the moment,
example.
1 would
1m Maybahr
trees
as they are carried
technoc,ratic
into a wide rural development
to the other
In concluding
e.g. by planting
works
are not a part of agriculture
connected
for the farmer beyond
but ~
possibly
solution
which
ecologically,
the peasant
are, for the
1 like to give a final illustrating
in Wello Region conservation
1984 1 noticed
was carried
that in the flatter
did a fine job and conserved
economically,
and accusto-
and socially
more acceptable
to
did after the conservation
the walls
in the flatland.
team
This was
in order to save their crops from waterlogging.
It will be necessary,
cution,
the whole
and its environment.
had left was to destroy
measures,
instructed
ditches.
they didn't try to find local solutions,
The first thing the peasants
possibly
not
more urgent.
with the level bunds they were
med to. However,
and
scheme. They
parts of the area most bunds were cut by drainage
valley
out
single measure,
farming problems
out 2~ years ago. In March
The MoA technicians
for
or fodder grass.
today are a rather
not integrated
is a
to include
therefore,
local peasants
and to create higher
soil erosion
to try to find more adapted
in general.
in the planning
awareness
and exe-
of the problem
of
- 48 References
AEBI, H./MESSERLI, B., 1980: Die Dritte Welt und wir, Berner
Universitatsschriften,
Verlag Paul Haupt, Bern
BENZING,
B./KAHSAI WOLDE GIORGIS, 1980: Das neue Aethiopien,
Pahl-Rugenstein Verlag, Koln
Berner
Beitrage zur Afrikaforschun,
1983: Jahrbuch der
Geographischen Gesellschaft von Bern, Geographisches
Institut der Universitat Bern, Bern
von BLANCKENBURG, P./CREMER, H.-D., 1971: Handbuch der Landwirtschaft und Ernahrung in den Entwicklungslandern,
Eugen Ulmer Verlag, Stuttgart
BONO. R./SEILER, W., 1983: The soils of Suke - Harerge research
unit (Ethiopia), research report 2, SCRP, Addis Abeba
BRHANE GEBREKIDAN, ca. 1975: The status of sorghum improvement
in Ethiopia, Addis Abeba
CONSTABLE, M., 1984: Resources for rural development
MoA, LUPRD, FAC, EHRS, Addis Abeba
DAMON,
E.G., 1962: The cultivated sorghums of Ethiopia, Experimental Station Bulletin No.6,
Imperial Ethiopian
College of Agriculture and Mechanical Arts, Addis Abeba
EDWARDS,
S., 1981: Crop environmental
FAO, UNDP, Addis Abeba
requirements
ERNI, T.,Landcover estimates with Landsat
report 6, SCRP, Addis Abeba
FAO, 1978:Plant
FAO,
in Ethiopia
and protection
for Ethiopia,
pictures,
research
paper 12: crop calendars,
1979:Plant and protection paper 19: elements
control of sorghum pests, Rome
Rome
of integrated
FAO, 1980:Land resources for population of the future, report
on the second FAO/UNFPA expert consultation, Rome
FRANKE,W.,1976:
Nutzpflanzenkunde,
Georg Thiema Verlag, Stuttgart
GALIZIA,
M., 1985, in prep.: Sozialanthropologische
Mensch-Umwelt-Beziehung
in den westlichen
Bergen, Aethiopien (Arbeitstitel)
GALIZIA,
M., 1985, in prep.: Social anthropological
studies
soil conservation: Man-environmental
relationships
the western Chercher mountains, Ethiopia, research
report 12, SCRP
GOETZ,
A./KONRAD, J., 1978: Pflanzenbau,
Stuttgart
for
in
Eugen Ulmer Verlag,
HALLIDAY,F./MOLYNEUX,
M., 1981: The Ethiopian
editions and NLB, London
HURNI,
Studien:
Chercher-
revolution,
Verso
H~1982: Klima und Dynamik der Hohenstufung von der letzten Kaltzeit bis zur Gegenwart, Geographische Gesellschaft von Bern, Bern
HURNI,H.,in
prep.:
Soil erosion
and conservation
in Ethiopia
- 49 -
KAZMIN,
MESFIN
V., 1973: Geological map of Ethiopia 1:2'000'000,
geological survey of Ethiopia, Ministry of Mines,
Addis Abeba
WOLDE MARIAM, 1972, An introductory geography of Ethiopia,
Brhane Selam H.S.I. Printing Press, Addis Abeba
MESSERLI,
B./HURNI, H., 1981: Mountain research for conservation
and development in Simen, Ethiopia, in: Mountain
research and development, vol. 1., No. 1., pp.49-54
MESSERLI,
B./AERNI, oK., 1978.t Carthography and its application
for geographical and ecological problems, Geographisches Institut der Universitat Bern, Bern
MILLER,
L.F.,1965: Input-output data for chat and sorghum production, Harar-Highlands,
Ethiopia,College
of Agriculture,H.S.I. University, Addis Abeba
MoA,
1977:
Land utilization and crop production. Report on the
second small-scale agricultural sample census 1976/77
vol. 1., Planning and Programming Department,
Statistics Section, Addis Abeba
MoA,
1979:
Area, production and yield of major crops for the whole
country and by region in 1974/75-1978/79,
Planning
and Programming Department, Statistics Section,
Addis Abeba
PURSEGLOVE,
J.W., 1968-1982: Tropical crops-dicotyledons,
Longman Group Limited, London
PURSEGLOVE,
J.W., 1972-1979: Tropical crops-monocotyledons,
Longman Group Limited, London
SCRP, 1982: Inception
report,
SCRP, 1982: First progress
Ethiopia,
report,
vol. 1, Bern
Ethiopia,
vol.
2, Bern
SCRP, 1982: Special issue: summary report,. Ethiopia, Bern
SCRP, 1983: Second progress report, Ethiopia, vol. 3, Bern
SCRP, 1984: Third progress
report,
Ethiopia,
vol. 4, Bern
SPECK, H.,
1983: Soils of the regional
report 1, SCRP, Addis Abeba
TAGOE,
1983: A tentative review of agriculture in the highlands, working paper 1, MOA, LUPRD, FAO, EHRS,
Addis Abeba
WEIGEL,
C.,
G., in prep.: An agroecological
Suke area (Harerge research
report 10, SCRP
WESTPHAL,
E.,1975:
Agric.
-- -
research
units,
research
development plan for the
unit, Ethiopia), research
Agricultural systems in Ethiopia, Centre
Publishing and Documentation, Wageningen
- .
---
for
- 50-
App.
Moisture
1.:
Phaseo1us
n
=
content of seed 14 days after harvest
vu1qaris
55
; x =15.88
%
; Sx = 2.06
Sorqhum bico1or
n = 15
Zea
n
; x
=
12.60
%
; Sx = 2.76
; x
=
12.74
%
; Sx = 3.85
mays
=
10
Lens escu1enta
n
=
-
4
; x
=
9.43 %
; Sx = 0.64
; x
= 11.63 %
; Sx = 0.32
=
; Sx = 0.23
Vicia faba
n
=
8
pisum sativum
n
= 2
Hordeum
n
= 5
; x
11. 62
%
vu1qare
; x = 9.72 %
; Sx = 0.63
(sundried)
- 51 Appendix
2
Correction
of sample weiqht
The farmers,
kids or women use to take plants
above all fresh maize
during
for roasting,
the last months
a number
test plots,
of the test plots the measured
plants
had to be extrapolated
weight
of the before
counted
period
of the plants.
For assessing
weight
calculated
the
of the remaining
by adding the supposed
cut plants,
So
at the of harvesting,
of plants had been removed before.
production
fruit,
from the fields continously
of the growing
from some of the 3x3 m marked
and their
average
from the stubbles
in the test plot at the time of harvesting
the sample.
Ex.: Measured sample weight: 1200 g produced by 28 plants.
Counted stubbles in the plot: 8
Correction of the 3x3 m sample weight: 1200 g : 28x36=1543 g
Key to tab.: (1) test plot number
(2) crop:
s
= sorghum,m= maize
(3) measured weight of harvested sample
(4) corrected sample weight
Correction of sample weiqhts
ill ill
m
8
m
13
m
25
m
31
m
35
m
51
54
m
m
60
m
65
70
s
79
m
m
84
m
92
m
100
108
m
m
11
115
m
m
119
s
127
m
128
ill
ill
532
380
85.2
730
1670 2147
380
415
360
180
780
826
180
252
275
110
150
188
1000 1355
GOO
667
510
603
717
430
270
480
195
130
240
80
2360 2472
795 1101
600
400
180
120
ill ill
10
m
In
16
26
m
m
33
41
m
m
52
s
55
m
62
m
68
m
70
80
m
87
m
m
93
m
103
m
111
114
s
117
m
m
125
127
m
127a m
ill
380
300
160
400
100
110
530
570
225
240
500
490
220
855
340
430
320
350
195
75
ill
853
600
267
500
150
248
644
665
450
360
667
613
377
27
1020
741
480
408
390
113
ill ill
11 m
24 m
28 m
34 m
50 m
53 s
58 m
64 m
69 m
72 m
83 m
90 s
94 m
106 m
112 s
114 m
118 m
126 m
128 s
ill
75
1160
1000
150
1265
2045
560
1215
220
60
110
20
190
250
1670
250
240
130
1100
ill
122
1371
1200
225
1546
2095
747
1443
330
1
303
53
290
393
1968
321
300
195
1189
- 52 Appendix
3
.
The biomass
of different
x
=
y
sx, sy
=
n
=
=
T
CA
=
=
crops
weight seed (ear, panicle) with husk (mean)
(mean)
weight straw
standard deviation
sample size
weight of total biomass / 9 m2
weight
of total biomass
on cultivated
area
Phaseo1us vu1Qaris
x
Y
=
=
299
65
Sx
c
Sy =
120
43
n
= 49
T
CA
=
=
364 g
16'377 kg
Vicia faba
= 598
Y = 929
sx = 424
n = 23
Sy = 498
T
= 1527 g
CA =
13'047 kg
Hordeum vu1Qare
x = 736
y = 1466
Sx = 317
n = 18
= 2202 g
CA =
7'316
n = 3
T
- 4900 g
CA
=
T
=
T
Sy = 683
kg
Eraqrostis tef
x = 3243
y = 1657
Sx = 698
Sy = 617
1'143 kg
Triticum farrum Bav1e Bar
x
-
=
608
Y = 1043
sx
=
51
Sy = 83
n
=
4
CA =
1651 g
1'119 kg
Linum usitatissimum
x = 177
-
Y = 943
sx = 75
Sy = 228
n= 4
T
= 1120 g
CA
=
348kg
Appenx
3 (cont.)
- 53 -
pisum sativum
CA
=
=
12'735 kg
T
=
=
1058 g
CA
T
=
CA
=
T
=
CA
= 705'783 kg
T
n
=
33
n
=
17
Lens escu1enta
968 g
2'293 kg
Zea mays
x
-Y
=
=
563
583
sx
= 404
Sy
= 265
n
=
16
n
=
45
n
=
13
1357 g
1221205
kg
weight roots and straw:
-x
=
794
Sx
= 725
Sorqhum bico1or
7837 g
The biomass has been measured after a drying period of 14 days.
4
APpendix
Key
to Map
"Land Use and Land Distribution in the AGUCHO Valley, Ethiopia"
List of plot holders
(1) :field number
(2) : holders name
(3):field size in m2
(1)
(2)
1
Adem Bu1e
2
Musa Abrahim
3
Ma::laye Tadesse
4
Kasim Usman
5
.Lenuna Imro
6
Kamaro Beker
7
Dule Grincho
8
Idris Haso
9
Mehamed Beker
10
Lulu Begashaw
11
Momed A1iy
12
Bushra Arnede
Beker Arned
13
14
Teshome Alemu
15
Mehamed Nur Haso
16+47 Abdelahi Mehamed
17
Meliwon Gebreves
18
Mekuriya W/medin
19
Kebret Kasa
20
Mehamed Aliyu
21
Silashi Mekuriya
Arne Musa
22
?3
Jemal Arnede
24
Abdela Sa1i
25
A1iyu Usman
(when all parcels inside catchment border)
(3)
3'098
3'391
5'519
9'697
10'129
8'797
6'406
12'656
5'827
7'887
17'219
3'734
4'741
9'679
(1)
(2)
26
Jemal l.fumed
27
Ingida Asfaw
28 + 48 Ibro Abde1a
29
Abde1a Becker
30
Mehamed Usman
31
Abrahim Usman
32 + 58 Hashim Abdu1ani
33
Ibro Yusuf
34
Adem Tahir
35
A1emu Tefera
36
Debebe Kidane
37
Mumed A1iyi
38
Abdurehman Ibro
39
Mehamed Ibro
40
Damtewu Damenu
"41
Bzhune Fanta
42
Amed Ume
43 +142 Beker Arnede
44
Arned Mumed
45 + 46 Musa Boru
47
Abde1ahi Mehamed
Dawit Mume
49
50 +136 Abdo Mume
51 +109+ 126 Mehamed Kasim
52
Abdurezhak Abdule
(3)
17'766
3'897
9'916
30 '110
9'442
3'963
9'813
5'563
8'306
9'963
3'775
7'823
13'029
7'065
19'859
7'599
4'725
I
U1
.e:.
I
APpendix
(2)
(1)
53
54
55
56
57
59
60
61
62
63
64
65
66
67
68
(cont. )
.4.-
Arned Mumed
Mumed Mu1eta
Abrahim Orner
+123 Omar Kasim
+ 96 Husen Abdukarim
Yusuf Ibro
+103 Bayu Haile
+129 Abdule Yusuf
Seifu Gebreyes
Adem Beker
Abdela Beker
Begashaw Haile
Zhe1eke Mengesha
Hay1e Worku
Mekonen Te1ahun
(3)
81
14'403
20'149
7'048
7'846
5'642
14'947
11'629
2'590
69 +110 Beker Arned
70
71
72
Usmai1 Mumed
Umer Abdu1e
75
Abde1a Mumed
76
Arned A1i
77
78
79
Abde1a Hassen
Mume Ao
Harned Ibro
73 + 86 + 134 Arned A1i
74 +113 Abibeker Aliyi
80
Li1i Ademe
Yonis Sa1i
(1)
9'136
14'948
7'993
3'633
3'074
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105 +133
106
107
(2)
Girma Aye1e
Arned Seid
Abaye Negatu
Si1ashi Ishete
( 3)
8'490
15'364
6'726
Arned Sa1i
Mume Arned
Haso Mu1eta
Kebede Mengistu
13'852
10'329
Yuya Arned
Mehamed Amed
Arned Seid
Mohamed Abdu1e
Hay1u Tefera
Osman Adem
Tadu Bayu
Husen Abdukarim
A1emu Tefera
Isak Abrahim
10'891
1'007
3'981
VI
Mumed Beker
Legese Mekuriya
Seifu Dejene
Abdosh
Arnede
7'064
Beke1e Bayu
Arnede Kebira
Jema1 Mumed
Kidane Shewareged
Uso Mumed
U1
9'325
2'953
4'425
Af!pend 1x
(1 )
108
109+126
III
112
114
115
116
117
118
119
120
4
(cont.
(2)
)
(3)
4'847
Jibril Mumed
Kasim Roba
A1iy Musa
Gezhahenge Mengistu
7'273
Amedin Hassen
Gebeyehu Mekeriya 13'997
Abdele Dadi
9'481
Aberra W/Semeyat
Abdurehman Kasim
3'900
5'926
Hasen Seido
2'399
Adem Amed
(2)
(1)
122
Menazu Begasha\~
124 + 132 Abdu1a Amed
125
Feka<1u Cherenet
127
Mohamed Abdu1e
128
Me1iwon ~'ekadu
130
Niguse Ishete
131
Kami1 Abdu1ahi
135
Abde1e A1iyi
137
Mayrnuna Abde1a
Yusuf Ao
138
139
Amed Seido
140
Indeshaw Fantaye
141
Sali A1iyi
142
+ 43
Beker Amede
(3)
4'322
12'044
5'112
6'314
4'498
I
U1
0\
I
A1!.Q~!!!jj ~
- 2
~!!~ U:~la.ta
1
GRAIN
<I;
1160
1520
E 1669
U)
990
2200
1032
3272
1660
1610
1875
4630
2210
200
2725
3270
IHO
4927
3781
2160
2250
3970
:3't2 0
1620
11,05
2400
Ei40
4535
2810
2140
300
)155
11\95
3860
23/10
1526
858
2505
1562
1584
2060
2330
2477
20 1,0
12/.5
3171
231>8
2
WATER
113.5
113.5
82
99
99
99
99
99
99
99
99
131
33.6
67.5
110
II 0
52
82
52
82
000
3
BULK
1. 06
1. 06
1. 09
1. 24
1. 24
1. 24
1. 24
1. 24
1. 24
1. 24
1. 24
0.86
0
0
0
0
0
1. 09
0.86
1. 09
000
5
4
PHOS SLOP
20
10.4
50
10.4
40
15.8
20
18.0
5
18.0
15
18.0
18.0
15
18.0
10
18.0
20
15
18.0
18.0
15
18.8
25
20
14.3
30
12
25
14.2
30
14.2
9.5
15
10
15.8
9.5
20
10
15.8
000
000
000
000
82
1. 09 15.8
82
1. 09 15.8
1. 09 15.8
82
6.4
60 000
14.3
33.6000
1. 14 14.1
102
0
0
0
106
1. 05 28.1
82
1. 09 15.8
1. 09 15.8
82
60
0
6.4
82
1. 09 15.8
16.7
124
0
0
0
0
82
1. 09 15.8
82
1. 09 15.8
102
1. 14 14.1
102
1. 14 14.1
1. 14 14.1
102
82
1. 09 15.8
102
1. 14 14.1
0
9.5
52
0
9.5
52
15.8
82
1. 09
7
6
DEPH FE
40
3
50 3
30 3
100
3
3
100
100
3
70 3
100
3
55
3
3
100
50 4
25 4
30 3
1
40
35 2
20 2
100
3
60
3
100
3
60 3
15
100
15
25
20
25
25
15
25
20
30
45
30
15
30
10
35
20
15
15
20
30
15
25
30
25
10
15 .3
40 3
50 3
35 3
1
20
50 1
35 3
80 4
25
3
20
3
25 3
60
1
3
20
4
100
20
1
30 3
75 3
40
3
35 3
25
1
3
60
(.0 3
30
1
30 3
40 3
3
8
MAIS
390
180
HO
200
640
122
852
000
600
475
2150
1215
000
2675
1540
280
2147
1371
160
1200
900
1800
500
225
360
460
4535
160
2080
0
675
650
1140
1000
826
248
250
252
700
820
1090
747
100
665
1443
188
9
SOR
600
1189
1180
530
1360
910
2420
1500
1010
1400
2090
800
200
000
1220
11 00
2780
2410
2000
980
10
A
170
300
000
260
200
000
000
160
280
000
390
195
000
50
510
000
000
000
000
70
2850
220
1420
1120
1180
1700
780
ODD
200
000
000
HO
300
000
100
60
0
0
305
0
160
180
200
160
280
240
10
180
280
300
0
0
0
2550
300
480
940
2120
1220
520
410
2095
1030
6(,4
1230
1060
1450
1640
600
1730
2180
11
14
12 13
MRV MMV MRH MMH
106 100
51 25
13 48 35 25
40 21
30
21
35
13
15 26
25
35 80 26
90
95 16
105
30 25
12 20
60
111 110 61
75 85 147 180
16 40
14 25
38
13
18 36
25
30
19 25
50
48
19 25
57 45
32 20
28
60 69 80
30 60
96 105
30 17
18
23
30 45
13 30
12
15 30 40
60 40
55
25
15
HOS
15
40
47
28
21
20
37
38
16
35
33
21
7
26
31
34
41
19
16
PLANTS
5
3
3
3
5
6
3
3
3
5
8
2
3
6
6
4
5
10
2
4
35
47
1
50
15 20 45
30 33
37 40
15 40 36 50
60
90 38 55
20
25 30 28
32
18 32 50
30 60
30
29
13 20 30
35
25
20 147 180
75
14
15 46
9 25 54 65
50
88 115 40
35 120 110
40
27
35 66 65
50
84 110 25
21
20 55 50
11 20 35 45
75
82 120 38
35 34 35
30
16 15 56 60
18 20
21 25
23 40
11 15
35
30
28
22
20
26
15
3
4
6
6
4
6
5
8
4
1
7
4
7
5
1
7
3
3
7
4
5
4
1
3
6
13
25
27
73
20
27
23
24
28
11
12
42
47
17
45
30
32
52
15
10
34
17
BEAN
110
530
400
550
600
600
130
700
18
PEA
775
230
60
40
280
140
200
300
19
20
WURZ WCUT
3100
7300
2000 7000
4100
9800
2500
1350
7700
2000
4850 14500
4000 11000
3850
7700
4000
6700
6000
5000
5200
2800 5000
2400
1300
1600
4000
2050 4000
2600
8700
21
W140
5000
HOO
7300
1400
4500
71 00
7500
4300
3300
4400
4000
3050
3200
22
FI ELOS
3098
3391
5519
9697
10129
8797
6406
12656
5827
7887
17219
3734
4741
9679
17766
3897
9916
30110
9442
VI
3963
......
9813
5563
8306
9963
3775
7823
13029
7065
19859
7599
4725
14403
20149
7048
7846
5642
14947
11629
2590
9136
14948
7993
3633
3074
8490
15364
App.
Basi c _data
5
(coot.)
L
<>:
E
(f)
1 --,
-I-<
960
350
U
+J
220
60
690
220
530
490
250
220
350
120
150
430
670
580
1000
85
560
160
830
170
460
90
270
1200
970
140
1200
480
590
540
540
990
260
230
885
180
590
760
1220
620
1050
590
480
I-<
.2.
1
25
20
20
35
30
35
35
50
30
20
35
35
35
65
55
20
u
30
30
45
20
20
15
35
15
15
10
30
10
40
40
30
35
40
25
35
30
35
50
15
30
70
25
35
1
.L
100
35
50
50
20
20
30
25
30
100
35
20
30
20
10
10
20
35
15
15
35
60
35
50
40
85
70
100
55
30
15
20
35
15
10
20
30
15
20
25
30
20
40
40
10
4
3
3
3
3
2
2
2
3
4
1
3
3
1
3
2
3
5
3
3
3
3
3
3
4
2
4
4
4
3
3
3
3
3
1
3
1
1
1
1
3
3
1
4
3
ill
230
140
130
800
290
580
220
230
980
30
200
240
670
590
755
410
820
880
430
1300
740
330
390
940
260
450
1000
160
690
1000
460
620
1780
580
430
550
90
590
620
280
440
790
560
730
1030
5
25
25
50
30
45
30
30
25
1
25
10
20
25
35
25
60
40
25
35
30
25
30
20
35
30
45
25
15
15
60
45
30
40
45
40
50
80
30
45
30
40
25
55
15
15
10
6 7
554
20
20
10
30
30
30
25
40
40
50
20
30
25
35
30
25
20
35
40
40
25
100
10
40
30
40
40
100
30
30
100
20
30
10
15
15
20
20
50
15
25
40
90
50
60
3
3
4
1
2
2
2
3
1
4
1
3
3
3
3
3
3
3
3
2
3
3
1
3
3
1
3
3
3
4
4
1
4
4
1
3
3
1
1
3
1
1
3
3
3
VI
(X)
I
App.
5
1
1130
1470
2920
1845
2025
1280
1420
3167
1445
953
970
600
553
2000
880
3320
2695
1400
2435
3990
1110
940
}(f70
2237
490
570
1040
1390
3090
2208
640
1132
2602
1990
1360
3185
2450
23ft8
1585
1463
1620
2680
560
3890
810
4340
Basic
data (cont.)
2
3
82
82
102
102
124
82
82
82
106
60
100
77
77
60
77
77
77
82
82
82
100
82
0
82
96
0
0
52
124
99
87
0
90
99
124
0
131
99
124
82
0
0
0
0
0
52
1.09
1. 09
1.14
1.14
0
1. 09
1. 09
1. 09
1. 0:;
0
1. 09
1. 07
1. 07
0
1. 07
1. 07
1. 07
1. 09
1. 09
1. 09
1. 09
1. 09
0
1. 09
1.11
0
0
0
0
1. 24
1. 08
0
0
1. 24
0
0
0.86
1. 24
0
1. 09
0
0
0
0
0
0
4
15.8
15.8
14.1
14.1
16.7
15.8
15.8
15.8
28.1
6.4
31.5
30.6
30.6
6.4
30.6
30.6
30.6
15.8
15.8
15.8
31.5
15.8
0
15.8
23.8
0
0
9.5
16.7
18.0
15.6
0
17.2
18.0
16.7
0
18.8
18.0
16.7
15.8
0
0
0
0
0
9.5
L
25
40
55
15
25
25
5
20
15
5
25
20
20
10
10
10
15
20
20
20
15
30
30
40
20
25
20
20
15
10
30
5
20
15
15
25
20
20
20
15
10
10
10
10
15
1
6
7
EL
60
30
40
40
100
35
65
30
2U
30
40
45
40
60
100
40
50
45
100
100
100
50
25
25
15
15
20
25
45
100
20
100
70
50
40
40
30
65
35
55
100
100
100
100
100
100
3
3
3
3
4
3
3
3
j
1
4
4
4
4
4
3
3
3
3
3
3
3
1
3
3
1
1
3
3
3
3
4
4
3
4
4
4
3
4
3
0
0
0
0
0
3
170
0
450
330
360
0
0
667
790
613
425
290
200
240
290
L
760
1420
2440
1215
1355
1140
1420
2200
615
220
365
120
53
1560
440
1390 1700
55 2340
990
280
865
1230
640 3010
480
630
720
180
350 1030
927 1310
0 490
570
0
140
900
195 1055
1350 1530
240 1968
140
500
741
321
2472 130
480 1510
300 1060
1150 1555
670 1780
408 1620
195 1080
113 1350
0 1620
0 2680
0
560
0 3890
0 810
0 4340
lL
200
50
30
300
310
140
0
300
40
120
180
190
300
240
150
230
300
130
340
340
0
40
90
0
0
0
0
140
210
0
0
70
0
0
0
480
0
320
310
0
0
0
0
0
0
0
1..L 11.
23 30
!i
26
30
43
18
42
27
47
40
27
19
18
10
21
37
33
31
45
23
55
24
20
26
33
57
36
43
24
35
20
31
5
32
38
27
38
53
31
53
18
32
45
32
30
!.!>
3
5
4
5
2
4
5
5
3
5
8
5
5
6
4
4
4
4
6
3
4
3
6726
13852
10329
10891
1007
3981
7064
9325
2953
4425
4847
7273
13997
9481
3900
5926
2399
4322
12044
5112
6314
4498
I
t61
\Q
I
60 -
Appendix
5
Explanation
(cont.
)
of svrnbols
1: GRAINS: Weight of total crop production of all crops inside
3x3 m test plot in sorghum/maize/haricot beans(smA)fields in grarnrn
or weight of
total production
of all crops in test plots
other crops
(rest cr) in grarnrnresp.
2: WATER:
Plant available
3: BULK:
Bulk density
4: PHOS:
Phosphorus
5: SLOP:
Slope gradient
6: DEPH:
7: FE
in fields of
water
in top 50 cm
of the soils
content
of the soils
in percent
Soil deph in cm
:
8: MAIS:
Soil fertility
Weight
acc. to the map of G.WEIGEL;
of maize production
see p...
in test plot in smA-fields
in 9
9: SOR
10:
:
A:
Weight
Weight
of sorghum production
in test plot in smA-fiedls
of haricot beans production
smA-fields
11:MRV:
Meters
real vertical:
13:MRH:
Meters
mapped vertical:
mapped
and converted
Meters
real horizontal:
measured
l4:MMH:
in 9
slope vertical
measure
12:MMV:
in 9
in test plot in
lenght of fielo,
by meter band
slope vertical
length of field,
to meters
slope horizontal
width
my meter band
Meters
mapped
horizontal:
slope horizontal
width
mapped
and converted
15:NOS:
Number
of sorghum
16:
Number
of all crops grown in a farmers
l7:BEAN:
Weight
of bean sample
18:BEA:
Weight
of pea sample from rest plot in bean/pea
19 :WURZ:
Root weight
20:WCUT:
Straw weight
21:W14D:
Straw
22:FIELDS:
Farm area in m2
PLA...1\JTS:
of field,
of field,
to meters
sticks
in test plot
field
from test plot in bean/pea
of sorghum
of sorghum
field
field
sample, dug out at harvest
sample, cut at harvest
time
time
-'-
fVet
(JJW
.--- Name
-."
-
--
-
1,d
R3
V
n_'.
of,'. Farmer:----,'
AIM,
Field
Character
Lllllt.
Slope
Grad.
in
%
L.-JJl wvI
pqt
,H,I
9f
-
.-.--.
If>>fl!bpr pf
Ptr::>t (33m)
. --
; (1
116
t
,,"I
Weip;hts in
Grain
Grain
with
only
Cover
lAf"
stl1.'
14 frM;-
amm(sun-dried)
WhOle 'Biomass
Straw
A7..
'Length
of
Plant
:
Fertilizer
Date of
Sowing
in em
Prize
per
Quintal
b
'/
{36o)-,""
-----
White l('!!. N:-
..--
White Sp0rt
-
:i:
Haricot Bean
--.--------.--'
]I()
1- If)
I
0\
'. I-'
I
HCl'90 Bean
Field
Pea
--
-.
--Le!1til
--
S.,,]ut Pott'toes
..:
Fcnucek
Appendix
-
6
Ch,"'l
-
--
Field data registration form
Wheat
-
Em1cr-Whcat
.-',..
, ,
;
--
i! '.
.
.':
I;' '
'-'.
-
..". ...-.
---.. ,-----..-,
' Hamlet:
--,----..,-,..._-n....--..._------ .-'
.
Nr.
of
Plants
}
--."-
..
"rve1;:j.fH!
,I
---;rt.AI( ! 1
4'1a1ze: Rea 11.
§t,.Ugn ,,qm:;
f9!m<t'!
Jp4 .i.trtHI.
Soil
Depth
in
em
Crop
..qcqhum
-'_..mn
-
.