Ivi] C* a National Meteorological Services Agency

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No. 3 May 1996 *•

Elhiopc, A«riciiHc'r. Research ilr.il . \ ^/LIu/t^KY rh. t v \ Y ^tu-.v rr “Vrt hA ft CUMJkTl! OliASSiriCJI

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by Lemma Gonfa

METEOROLOGICAL RESEARCH REPORT SERIES

ADDIS ABABA, ETHIOPIA <3 I & J C/tK

Oiiaate Cla^ficjitiorts $f Bthhpu

Lemma Gonfia

National Meteorological Services Agency

Agricultural Hu&carch Organ; &1I101 «n;r.J LIHKAKV r h . * r * r -mu:*.' c x c 'g * Ill-

February, 1996 First published in 1996 by the National Meteorological Services Agency (NMSA), P.O.Box 1090, Tel 512299, Fax 517066 Addis Ababa, Ethiopia

This research report which contains research conducted at the National Meteorological Services Agency (NMSA) was edited by the Research and Editorial Board of the NMSA before publication. Reported views, opinions, conclusions and recommendations in this report are those of the author and Are not necessarily those of the Agency. Any inquiries should be directed to the General Manger of NMSA.

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form, with out prior permission o f NMSA in writing. However, permission to use figures, tables and brief excerpts from this publication in scientific and/or educational work i.s hereby granted provided the source is acknowledged.

Author Lemma Gonfa NMSA P.O.Box 1090 Addis Ababa, Ethiopia

Title: Climatic Classifications of Ethiopia

Printed and hound in Ethiopia Preface

In this work an attempt is made to identify and delineate climatic regions of the country using the well known methods for climate classification. It is intended to be used by scientists, policy makers and the public at large.

I hope the result presented here will be useful to raise various points for discussion in understanding the climatic realities of the country. This work is far from complete and is anticipated to be improved as more data and comments on the work become available.

I gratefully acknowledge Ato Eshetu Habtemariam, the former general manager of the National Meteorological Services Agency who had suggested and encouraged the work of these climatic classifications to appear in its present stage.

I am indebted to the Research and Editorial Board members of the NMSA for their valuable comments and help in improving the format and presentation of the report.

I also acknowledge the computer Section of NMSA, especially Ato Wasihun Andualem who had facilitated this work by preparing computer program for various mathematical computations which would otherwise be difficult and time consuming. It is the result o:: his cooperation that the work is finished with in a short time.

My special thanks also goes to Ato Girma Teklemariair who carried out the drawing on climatic maps.

I finally thank all those who participated on the data processing and tabulation for the Koeppen's system.

Lemma Gonfa February U*96

II Foreword

One of the duties of the National Meteorological Services Agency is to encourage the application of weather and climate information by producing and disseminating research reports like this one.

Climate is one component of natural resources of a country and has to be exploited rationally and effectively. In this research report the climates of Ethiopia are presented using the widely used methods namely Koeppen, Thornwaite and Budyko-Lattau so that users can apply climate information according to their needs.

I hope this report will be of great help to a wide spectrum of users. I take this opportunity to appreciate Mr.Lemma Gonfa for his enthusiasm and dedicated hard work in producing this report.

I also would like to extend my thanks to members of the Agency's Research and Editorial Board (Mr Abebe Tadege, Mr Engida Mersha, Mr Tsegaye Tadesse and Mr Abebe Yeshanew) for their efforts in editing the report. Tesfay Haile General Manager February 1996 CONTENTS

PAGE Preface...... ii Foreword...... iii Contents...... iv

Chapter 1

Climatic Classification of Ethiopia Using Koeppen's System

1.1 Introduction ...... 1 1.2 Data Set Characteristics...... 1 1.3 Methodology ...... 2 1.3.1 Highlights of Koeppen's Climate Classification Method...... 3 1.4 Results and Discussion ...... 8 1.4.1 Climatic Groups of Ethiopia ...... 8 1.4.2 General Remarks Concerning the Climatic Subdivisions of Ethiopia...... 10 1.5 Conclusion ...... 12 1.6 References ...... 13

Chapter 2

Distribution of Dryness Ratio in Ethiopia

2.1 Introduction ...... 16 2 . 2 Data Used ...... 16 2.3 Methodology ...... 16 2 4 Results And Discussion ...... 19 2.5 Conclusion ...... 25 2.6 Reference ...... 25

Chapter '3 Climatic Classification Using Moisture Index

3.1 Introduction...... 27 3.2 Data used ...... 27 3.3 Methodology ...... 27 3.4 Result and Discussion ...... 31 3.5 Conclusion...... :...... 34 3.6 Reference...... 7 8

IV Chapter 1

CLIMATIC CLASSIFICATION OF ETHIOPIA USING KOEPPEN’S SYSTEM

1.1 Introduction

The general purpose of this classification is to arrange climatic information from past recorded and archived climatic data in a simplified and comprehensible form so as to assist various climatic users.

The use of climatic classification is for better understanding and utilization of the climatic resources of a given region. In general Climate affects all of us everyday in relation to the crops we grow, the water we drink, the place where we live, the clothes we wear, the energy we use in heating or cooling our house, our health, the quality of the environment, our national economy and in countless other ways. Understanding the climatic reality of a place, a region or a country enabls man to do a better job of weather sensitive activities. In general climate is a major natural resource which can benefit nearly all human activities. On the other hand climatic events such as drought, floods or severe cold spells can adversely affect human activities. Therefore to propose future directions mainly for practical applications such as agriculture, health, settlement of people and also for planning, short, medium and long term economic planning like designing hydrodams, residential areas and recreational facilities requires better climatic information. As a result of recurring drought mainly during the last two decades in some parts of Ethiopia climatic information has become more demanding than ever before for the purpose of making better decisions. Thus to generalize the climatic types and boundaries throughout the country, koeppen system has been applied on the existing climatological data to produce a meaningful climatic map.

1.2 Data set characteristics

This study was based on rainfall and temperature data from 388

1 stations. The data quality control were carried out by sen.or staffs of development team. Data processing up to 1983 were accomplished by junior staffs. The period of the records were o:: a different time series. Very few stations were having records fo:r a longer period more than 30 years. The majority of the stations ware having short and medium length of time, the reason is that it is only during the last decades that National Meteorological Services Agency has carried out systematic observations of meteorological elements and records are kept. At present the density of the network of the stations have been steadily increasing.

The length of the records both for temperature and rainfall were as follows.

Year No of the stations

2 - 5 141 6 - 1 0 117 11 - 15 75 16 - 20 27 21 - 30 16 > - 30 12

As far as data utilized are concerned averages of 20 years and more are considered to be a bench mark reference for climatic zonation. Data of short averages were used as a complement to fill the scarcity of data gap to minimize the uncertainty of subjective judgment for depicting the climatic boundaries.

1.3 Methodology

Among the outstanding modern climate classifications, koeppen's method is more functional in identifying the climatic types quantitatively with available records of temperature and rainfall. His method defines the climatic types according tc the values of temperature and rainfall regardless of the geographical locations of regions. Since the combination of these two variables identify the natural vegetation types such as rainforest, savanna, steppe, desert, snow forest and tundra, Koeppen has developed suitable criteria to characterize the climatic types with related vegetation by using these two variables. The choice of this

2 methodology is largely intended by the purposes for which the limitation of these two variables has met the requirement for the growth of a certain plant and the real difference in vegetation types also characterize the boundaries of the climatic type. But, individually these two variables can not give any satisfactory idea of the climate of a place. The same amount of rainfall may have a very different effect on natural vegetation growth depending on the regions where it falls for example in a hot climate v/ith high evaporation or cold climate with low evaporation. Similarly if two places are having a very similar temperature but, a very different amounts of rainfall their climatic types and the growth of natural vegetation types are dissimilar.

1.3.1 Highlights of Koeppen's Climate classification Method

Koeppen has grouped the world climate into five categories, which are designated by capital letters A, B, C, D, E. These five climatic groups are each sub-divided into three or more principal climatic types.

2 Table 1.2.

Criteria for classification of principal climatic typei in modified Koeppen system (Critchfield 1961, Lowry, 1972) .

Based on mean annual and mean monthly values of rainfall, in cm. and temperature in °c.

Letter symbol Explanation

1st 2nd 3rd

Average temperature of coolest month 18°c or higher.

Rainfall in the driest month at least 6.0 cm

m Rainfall in the driest month less than 6.0 cm. but equal to or greater than 10 - r/25

w rainfall in the driest winter month less than 10-r/25 i.e. winter dry.

rainfall in the driest summer month less than 10-r/25 i.e summer dry. Letter symbol Explanation

1st 2nd 3rd

B - 70% or more annual rain falls in summer months, r less th^n 2 (t + 14)

- 70% or more annual rain falls in winter months, r less than 2t.

- Neither half of year with more than 70% of annual rainfalls r less than 2 (t + 7) .

w - r less than 1/2 upper limit of applicable requirement for B.

- r less than upper limit for B but more than 1/2 that amount.

h - t greater than l8°c k - t less than 18°c

- Average temperature of the coldest month less than 180c and greater than -3°C - Summer dry, rainfall of driest summer month less than 1/3 of rain fall of the wettest winter month.

w - Winter dry, rainfall of the,driest winter month less than 1/10 of rainfall of the wettest summer month

5 Letter symbol Explanation

1st 2nd 3rd

f - With out distinct dry season, rainfaM of driest summer month greater than 1/3 of rainfall of the wettest winter month and rainfall of driest winter month greater than 1/10 of rainfalls of the wettest summer month.

a - Average temperature of warmest month 22°c or above.

b - Average temperature of each of four months 10°c or more, c - Average temperature of from one to three months 10°c or above temperature of warmest month below 22°c.

D - Average temperature of warmest month greater than 10°c and of coldest month -3°C or below.

s - Same as under C w - Same as under C f - Same as under C a - Same as under C b - Same as under C c - Same as under C d - Average temp, of Coldest month below - 38°C.

6 Letter symbol Explanation

1st 2nd 3rd

E - Average temperature of the warmest month below 10°c. T - Average temperature of the warmest month between 10°c and 0°c. F - Average temperature of Warmest month 0 or below

H - Temperature requirements same as E, but due to altiti-de

N.B in formula t is the average annual temperature in °c. , r is average annual precipitation in cm.

- Summer is April through September in Northern Hemisphere.

- Winter is October through March in Northern Hemisphere. The reverse is in southern Hemisphere.

7 1.4 Result and Discussion

1.4.1 Climatic groups of Ethiopia

The actual application of the Koeppen system to climatologi^al statistics show that the climate of Ethiopia are grouped into three main categories, namely A, B and C types. These three groups ar^ each sub divided into three or more types making a total of eleven principal climatic types (table 1.3).

Climatic groups A and C are called tree climate because "he combination of heat and moisture within these climatic types are suitable to grow trees. The boundaries of these two climates ( A & C ) are separated from each other by the temperature of the coldest month, i.e if the temperature of the coldest month is less than : 8°c it is C type; if more it is A type.

The tree climates A & C are distinguished from dry climate B by the mean annual rainfall amounts compared with the equation 2 (t + 14 ) i. e if r < 2 (t + 14 )...... 'B' climate.

The tree vegetation changes to the steppe type of vegetation (BS) as: - r < 2 ( t + 14 ) .

The steppe type changes to barren or sparse (BW) owing to the lack of water a s :- r < t + 14

The tree climates A & C are each subdivided according to the seasonal rainfall distribution criteria given on table 1.2.

The dry climate B is also sub-divided according to the degree of dryness criteria given in table 1.2.

a Table 1.3. Sample from each climatic types

Station Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec ANN type

GINDA r 10.1 1-0.8 7.1 3.8 2.3 1.0 7.3 5.5 2.1 3.1 6.8 10.3 70.2 t 20.0 19.7 21.3 25.3 27.0 28.0 28.5 28.7 26.7 26.0 23.0 21.8 24.9 AS

ASMARA r 0.3 0.2 1.3 3.3 4.3 4.1 18.7 15.5 2.4 1.1 1.9 0.5 53.8 t 14.3 15.4 17.0 17.7 18.4 18.4 16.6 16.0 16.4 15.4 14.6 14.1 16.1 BSK

GODE r 0.0 0.5 1.9 9.1 6.9 0.1 0.0 0.0 0.7 5.9 4.6 0.3 30.0 t 28.2 29.1 30.2 29.6 28.9 28.9 28.0 28.1 29.0 28.5 27.7 27.7 28.6 BWh

BEBEKA r 4.7 6.3 13.9 25.7 24.6 21.9 22.6 21.4 22.3 17.9 13.7 9.4 204.4 t 22.6 23.1 23.4 22.3 21.9 21.4 20.9 20.5 21.0 21.7 21.9 22.1 21.9 Am

DIREDAWA r 1.7 3.6 5.8 5.9 3.9 2 3 9.3 13.7 6.2 1 6 1.6 1.0 56.4 t 21.7 22.7 24.8 25.7 27.2 28 1 26.7 25.2 25.9 25 0 22.7 21.3 24.7 BSh

ASOSA r 0.1 0.6 2.4 6.2 11.9 18 0 25.0 23.7 20.3 13 9 2.6 2.8 127.5 t 21.2 22.9 23.5 22.8 21.6 19 5 18.9 19.1 19.4 19 8 20.5 20.9 20.8 Aw

ADDIS ABABA r 2.2 3.5 6.9 8.9 7.4 12.0 25.5 25.5 17.3 4.0 1.1 1.1 115.4 t 15.5 16.6 17.5 17.5 16.9 16.7 15.4 15.3 15.3 15.5 14.9 14.9 16.0 Cwb

JIMMA r 3.1 5.6 9.4 13.9 16.3 21.4 21.9 21.3 18.0 9.1 5.7 4.6 150.3 t 17.9 19.0 20.5 20.2 20.0 19.1 18.6 21.4 19.2 18.8 17.8 17.1 19.1 Cfb

K/MENGIST r 2.1 2.2 9.3 19.4 21.8 7.5 3.4 4.0 8.2 17.1 8.1 1.6 103.6 t 18.7 19.6 20.0 20.2 19.8 18.9 18.2 18.9 19.3 19.2 18.4 18.2 19.1 Aws

YABEliLO r 2.8 4.6 7.4 13.2 11.8 2.9 1.6 2.2 2.7 8.9 6.3 1.9 66.1 t 20.6 20.9 20.9 19.4 18.3 17.9 17.4 18.0 19.1 18.7 18.5 20.0 19.1 Cws

VIEGEZEZ r 2.2 5.0 7.4 12.8 3.7 4.8 21.8 23.4 12.1 3.6 5.8 0.8 103.4 t t 8.0 7.2 8.8 7.6 8.6 8.6 7.7 7.1 7.1 5.3 5.2 6.3 7.3 H

9 1.4.2 General remarks concerning the climatic Subdivision of Ethiopia.

Based on the Koppen's Climatic classification method, eleven climatic types were identified for Ethiopia (Fig. 1).

The following are the details.

Bwh:- Hot arid climate

Generally barren to sparse vegetation. In this region the trean annual temperature is between 27 - 32°C and the mean annual rainfall is less than 45 cm. It is usually characterized by strong wind, high temperature low relative humidity and little cloud amounts. Evaporation is ten to twenty times more in excess of annual rainfall in some places.

Bsh:- Hot semi-arid climate

Steppe type vegetation. In this region the mean annual temperature is between 18 - 27°C and mean annual rainfall is between 41-82 cm. The rainfall is highly variable from year to year. Since evaporation exceeds rainfall permanent streams do not originate. Grasses are less tall, coarse and edible but during the dry seasons it is not highly palatable, as a result wild games and cattle at such times rely largely on the tender fresh grasses along water courses. This region is intermediate between the hot arid and the humid climate.

Bsk:- Cool semi-arid climate

Steppe type vegetation mainly over the southern highlands of Eritrea and the adjoining highlands of Tigrai. The mean annual temperature is between 12 - 18°C and mean annual rainfall is between 40-62 cm. Evaporation is less than Bsh, due to low temperature of this region and hence less arid than Bsh. The region is encircled by Bsh climate. A s :- Tropical rainy climate

This region has dry months in summer. The mean temperature of the coldest month is above 18°C. and mean annual rainfall is between 68-120 cm. This region is confined in a very small area between Asmara and Massawa.

Aw:- Tropical rainy climate

This region has dry months in,winter. The mean temperature of the coldest month is above 18°° and mean annual rainfall is between 68-200 cm. This climate prevails up to an elevation of 1750 meters above mean sea level. The length of the wet and dry periods vary considerably from the western parts of the country to the Northern and Eastern parts of the country. Tall grass characterizes this climatic types. Usually grass and trees are intermingled.

Am:- Tropical rainforest climate

The temperature of the coldest month is above 18°C and mean annual rainfall is between 120 - 280cm. It differs from Aw climate by the higher amounts of rainfall during the driest month i.e. a > 10 - r/25 where 'a' stands for rainfall of the driest month and r stands for the me^n of annual rainfall in cm. The rainfall amount supports an ever green rain forest. It prevails up to an elevation of 1750 meters above mean sea level.

Cwb:- Warm temperate rainy climate

Its distinct dry month is in winter. The mean temperature of the coldest month is below 18°C and for more than four months above 10°C. Rainfall of the driest winter month is less than one tenth of the wettest summer month. The rainfall amount and its distribution varies considerably from one area to another such that the lowest is about 60 cm and the highest is about 200 cm. In areas of heavy rainfall forest are predominant while savanna grass with moderate rainfall. It prevails from an elevation of 1750 to 3200 meters above mean sea level.

11 Cfb:- Warm temperate rainy climate

With out distinct dry season and more soil moisture than Cwb climate. Rainfall of the driest winter month is more than one tenth of the wettest summer month and rainfall of the direst sunmer month is more than one third of the wettest winter month. The region has experienced annual rainfall between 100 - 280 cm. This climate is convenient for abundant forest cover.

Aws:- Tropical Aw & As climate

In this climatic regions the criteria of both summer dry as 'As' climate and winter dry as 'Aw' climate have met. It is groupeci as 'A' climate because the mean temperature of the coldest month is above 18°C and mean annual rainfall is greater than 2 (t + 7). The rainfall characteristics is bi-modal, which is two distinct rainfall maximums are separated by two dry seasons.

Cws:- Temperate Cw & Cs climate

It is grouped as C climate because the temperature of the coldest month is less than 18°C otherwise it has the same criteria as Aws.

H:- Cool highland climate

Due to high altitude the mean temperature of the warmest month is less than 10°C. The mean annual rainfall is between 80 - 200 cm. It is situated at an altitude equal or more than 3500 meters above mean sea level. It is confined on small isolated mountains.

1.5 Conclusion

The present investigation within the context of the Koeppen system has resulted the climatic map of Ethiopia (Fig. 1.1). The map shows pictorially the distribution of each climatic types It is helpful for those who need a basic understanding of the climitic realities of Ethiopia. The climatic types ranged from hot arid (Bwh) , to hot and cool steppe types (Bsh, Bsk) and from tropical savanna (Aw) to rain forest (Am) , and from warm temperate (Ctob, Cfb) to cool highland (H). The climate varied not only from arid

12 areas to areas of rather plentiful moisture but also from hot lowland to cool highland. The elevation of these lowland and highland varies from around 100 meters below sea level in the Dallol depression rising to 4620 meters (Ras Dashan) in the Semin mountain massif.

Koeppen's system is also quite useful to investigate the major impacts of climatic fluctuations and recurring droughts, using the classification in individual years for stations, with long series of records. For example, Mekele which is classed as steppe type climate (Bsk) with the average climatic records had a temperate ra_ny climate (Cwb) in 10 years out of 27, steppe type (Bsk) in 15 years out of 27 and a desert type (Bwk) in 2 years out of 27 years.

A similar classification have been done for a drought year, 1984, for’all stations in the country and mapped on Figure 1.2. When Figure 1.1 which is average climatic classification is compared with Figure 1.2 which is a drought year, the average cl:matic types have been replaced by drier climatic types. As it is observed in Figure 1.2, Tropical rain forest climate (Am) on Figure 1.1 is totally replaced by Aw climate, Similarly Cfb to Cwt, Aw to Bsh, Cwb to Bsk, Bsk to Bwk and so on. Thus the study reveals how often the stations have been in much drier climate than it usually is.

Reference

Trewartha, Glenn T., 1954. An introduction to climate. 3rd edition New Work.

Howard J .•critchfield, 1961. General climatology 2nd edition, New Jersey.

BernHard Haurwitz, and James M. Austin, 1944. Climatology McGRAW- HILL Book company. Inc. New York and London.

WMO. 1984. Guide to climatological practices. WMO - No. 100, WMO, Geneva, Switzerland.

Lowry, W., 1972. Compendium of lecture Notes in climatology for class IV Meteorological personnel.

13 Fig. 1.1 CLIMATIC ZONES OF ETHIOPIA Explanation on Legend Bwh- Hot Arid Climate Bsh- Hot Semi Arid Climate Bsk- Cool Dry Climate As- Tropical Climate (with dry summer) Aw- Tropical Climate (with distinct dry winter) Am- Tropical Monsoon Rainy Climate (with short dry season) Aws- Tropical Climate (Criteria of both w & s aremet) Cwb- Warm Temperate Rainy Climate (with dry winter) Cfb- Warm Temperate Rainy Climate (with out distinct dry season) Cws- Warm Temperate Climate (Criteria of both w & s are met) H- Cool Highland Climate

14 H16

-14

— 12

— 10

h-a

— 6

— 4

Fig 1.2 Climatic Classification of Ethiopia for 1984

Bwh Hot Arid Climate Bsh Hot Semi Arid Climate Bsk Cool Dry Climate As Tropical Climate with Dry Summer Aw Tropical Rainy Climate Cwb Warm Temperate Rainy Climate with Dry Winter H Cool Highland Climate

15 Chapter 2

Distribution of Dryness Ratio in Ethiopia

2.1 Introduction

The gradient of the dryness ratio from west Africa coast to the Sahelo-Saharan were examined by Hare. His work is very useful to investigate the nature of desertification and the spreading of deserts into formerly productive land. The objective of this study is to examine the distribution of the dryness ratio over Ethiopia to contribute more understanding on the climatic reality w;_th respect to potential evapotranspiration.

2.2 Data utilized

The data used in this study were from the publication of so3ar radiation in Ethiopia by Cesen in collaboration with the Ministry of Mines and Energy. The Annex contains tables of average daily radiation on horizontal surface in KJ/m2 and yearly totals in GJ/nr for 140 stations. These values were an estimate from the stations sunshine duration records using both modified Angstrom and Suchuepp. For this study modified Angstrom annual global solar radiation estimate is used.

2.3 Methodology

This study uses Budyko - Lettau dryness ratio index. " It is tne ratio of the annual net radiant energy arriving at the place to tie heat required to evaporate a years rainfall amount (Hare 1985) .

The expression is as follows

Qn/r.L

16 Where:-

Qn = stands for yearly total net radiation in cal/cm2

r = annual rainfall amount in mm. or cm.

L = Latent heat for vaporization of water.

Several researchers had discussed and proposed different empirical equations to estimate net radiation (Lim, 1983).

Their respective equations were as follows:

1. Penman: 1970

Qn = (I-,- r) QA (0.18 + 0.55 n/N) -6T4 (0.56 - 0.92Ved) (0.1 + 0.9 n/N)

2. Chang: 1970

Qn = (1 - r) QS - 6r4 (286.18 + 202.6 QS/QA - 45.24 ed - 10.2 QS/QA Ved)

3. Selino et al: 1971

Qn = 7.3 + 0.52 QS (for summer case only)

4. Davies: 1967

Qn = 0.617 QS - 24

Where:- Qn = net radiation

Qs = global solar radiation

QA = Solar radiation falling on horizontal surface at the top of the atmosphere

17 n = duration of sunshine

N = Maximum possible sunshine duration

6 = Stefan Bolt z man's constant

T = air temperature in °K t V • \ ed = Saturated vapour pressure at dew point •' ‘ • temperature in mb.

r = albedo of the surface.

In order to determine the applicability of these formulae, the actual net radiation measured were compared with values of monthly net radiation calculated from each of these formulae (table 2.1).

Table 2.1. Comparison of monthly net radiation (MJ/M2) measured at USM and monthly net radiation estimated by different formulae at Bayan Lepas station for 1980 (Lim, 1983) . Bayan Lepas is 4 Km from USM in the peninsular Malaysia (05° 18'N 100° 15'E)

Month Measured Davies Penman Chang Silirio

Jan 9.41 10 . 58 13 .13 15 .49 9 .91 Feb 11.47 10.71 13 .11 15 . 67 10 . 02 Mar 10.91 10.95 12 .42 15 .99 10 .22 Apr 10.71 10 .53 12 .54 15 .43 9.87 May 10 .18 9 .75 11.53 14 . 37 9 .21 Jun 8 .97 9.15 9.87 13 .56 8 .71 Jul 9.28 9.72 10.56 14 .3 3 9 .19 Aug 8 .44 8.5 9.17 12 .67 8 .15 Sep 8 .81 8.69 8 .92 12 . 93 8 .32 Oct 8 .19 8.8 9 .15 13 .08 8.41 Nov 9 .18 9.32 9 .73 13 .79 8 . 85 Dec 8 . 44 8.79 8.85 13 .06 8 .40

Th® -esult of the comparison in the above table shows t.hat Davies formula gives the closest estimate of the net radiation for

18 the period under comparison. Therefore it is appropriate to use Davies formula to estimate annual net radiation for the stations which had global solar radiation in Ethiopia.

2.4 Results and Discussion

In general net radiation represents the available energy for sensible heat transfer, evapotranspiration, soil heat flux and to the small extent photosynthesis. Net radiation is not only affected by the amount of solar radiation but also by the surface albedo and soil moisture. For example if the surface is dry evapotranspiration is less and more energy is available for sensible heating. On the other hand if the surface is smooth and white much of the solar energy will be reflected leaving very little energy for the soil heat and sensible heat.

According to Budyko the annual available net radiation is assumed to evaporate water as if there is water to evaporate which is equal in amount to the annual net radiation divided by the latent heat of vaporization, (i.e Qn/L). This value is similar to that of annual water need or potential evapotranspiration. The Index is obtained by dividing the annual water need (Qn/L) by mean annual water available as rainfall (Qn/L.r) (table 2.2).

19 Table 2.2. Mean Annual Radiational Index of Dryness.

Stations Lat Long. Elev QS QN QN/59 Rain PE /r °N °E GJ/M: Cal/cm PE (mm r (mm Irde 2 Mts. ) )

ABIY ADI 13.32 39.01 1870 7.824 106570 1806 793 2.3 ABOBO 7.48 34 .24 530 6 .375 85210 1444 1132 1.3 AD ABA 7.01 39.24 2485 6 .770 91033 1543 796 1.9 ADDIS ABABA 9.02 38.45 2408 6.742 90620 1536 1154 1.3 ADDIGRAT 14 .16 39.27 2457 7.993 109062 1849 581 3.2 ADI KEYIH 14 .50 39 .20 2490 7.998 109135 1850 484 3.8 ADI MGRI 14 .53 38.39 1022 8.053 109946 1863 573 3.3 ADI ZEMEN 12.07 37.52 2020 6.880 92655 1570 1065 1.5 ADOLA 5.55 39.05 2170 6 .775 91107 1544 1036 1.5 ADWA 14.10 38 .54 1980 7.987 108973 1847 736 ; .5 AGARO 7. 51 36.38 1560 6.458 86434 1465 1533 1 . 0 AKAKI 8.52 38 .47 2100 6.956 93775 1589 871 1 .8 AKORDAT 15.33 37.53 626 6.952 93716 1588 309 5.1 ALABA KOLITO 7.72 38 .06 1850 7.171 96944 1643 938 1.8 ALAMATA 12.31 39.41 2200 7.521 102104 1731 543 3.2 ALEMEKETEMA 10.05 39.18 1950 6 .734 90502 1534 1151 1.3 ALEMAYA 9.26 42.03 2125 7.216 97608 1654 838 2.0 AMBO 8.58 37.52 2080 6 .680 89706 1520 1087 1.4 ARBAMINCH 6.05 37.38 1290 7.076 95544 1619 783 2.1 ARJO 6.45 36.30 2565 6 .449 86301 1463 2103 0.7 ASELA 7.52 39.08 2450. 7.042 95043 1611 1303 1.2 ASENDABO 7.44 37.14 1870 6 .484 86817 1471 1193 1.2 ASMARA 15. 17 38.55 2325 7.957 108531 1840 537 3.4 ASOSA 10.04 34 .31 1750 6.644 89176 1511 1275 1 2 ATNAGO 8 .29 36.57 2000 6 .492 86935 1473 2212 0 . 7 AWASA 7.04 38.30 1750 6.965 93908 1592 944 1 . 7 AWASH 8 .59 40.09 916 6.979 94114 1595 615 2.6 AYKEL 12.31 37.03 2150 7.125 96266 1632 1180 1 . 4 BAHIRDAR 11.36 37 .24 1890 6.731 90458 1533 1486 1.0 BACO 9.07 37.05 1590 6.659 89397 1515 1193 1.3 BACO JINKA 5.52 36.38 1430 6.742 90620 1536 1342 1 . 1

20 Stations Lat Long. Elev QS QN QN/59 Rain PE/r °N °E GJ/M2 pal/cm PE (mm r (mm Inde Mts. ) ) * BAMBESI 9.45 34 .44 1450 6.585 88306 1497 1344 1.1 BARENTU 15.10 37.36 980 8.078 110315 1870 519 3.6 BAT I 11.13 40.03 1660 6.692 89883 1523 872 1.7 BEDELE 8 .27 36 .23 2090 6.430 86021 1458 1924 0.8 BEGI 9.21 34 .32 1722 6.551 87805 1488 1360 1.1 BEKOJI 7.32 39.15 2850 6.506 87141 1477 1012 1.5 BI LATE 6.39 37.58 1200 7.011 94586 1603 780 2.1

BONGA 7.13 36.17 1725 6 .444 86227 1461 1789 O CD E'JLKI 6.11 36.32 2600 6.702 90031 1526 1838 0.8 BURE 8 .17 35.06 1600 6.389 85417 1448 1282 1.1 BURJI 5 .24 37.56 1960 6.917 93200 1580 1015 1.6 BOTAJIRA 8 .07 38.27 2100 7.172 96959 1643 1020 1.6 CHAGNI 10.55 36.26 1720 6.596 88468 1499 1687 0.9 CHEFA 10.54 39.50 1600 6 .658 89382 1515 1042 1.5 CHENCHA 6 .15 37.37 2580 7.076 95544 1619 1481 1.1 DABAT 13.00 37.46 2685 7.242 97991 1661 928 1.8 DANGLA 11.17 36.55 2180 6.659 89397 1515 1460 1.0 DEBREBRIHAN 9.38 39.30 2820 7.018 94689 1605 890 1.8 DEBREMARKOS 10.21 37.43 2440 6.417 85829 1455 1348 1.1 DEBRETABOR 11.53 38 .02 2410 6.811 91637 1553 1747 0.9 DEBREZEIT 8.44 39.02 1900 7.200 97372 1650 878 1.9 DEGEHABUR 8.09 43.33 1000 7.004 94483 1601 313 5.1 DEMBI DOLO 8.30 34 .46 1850 6 .438 86139 1460 1175 1.2 DE3E 11.10 39.40 2540 6.621 88837 1506 1035 1.5 DI3 BAER 13 .14 37.56 2800 7.441 100925 1711 1616 1.1 DIDESA 9.00 36.06 1200 6 .436 86109 1459 1387 1.1 DILA 6 .25 38 .18 1670 7.016 94659 1604 1264 1.3 DIRE DAWA 9.36 41.52 1210 7.077 95559 1620 566 2.9 DIXIS 8 .08 39.35 2600 6 .720 90296 1530 929 1.6 DODOLA 6.58 39.11 2540 6 .770 91033 1543 843 1.8 FELEGE NEWAY 6.18 36.52 1360 6.736 90532 1534 1703 0.9 FICHE 9.48 38 .45 2800 6.713 90193 1529 1232 1.2 FILIKLIK 10.03 38 .15 1800 6.707 90104 1527 1125 1.4 FINCKA 9.32 37.23 2320 6.457 86419 1465 1141 1.3 GAMBELA 8 .15 34 .35 480 6.386 85372 1447 1131 1.3 GEWANE 10.05 40.38 625 7.205 97446 1652 373 4.4 GIDAMI 8.58 34.35 2040 5.970 79240 1343 1950 0.7 21 Stations Lat Long. Elev QS QN QN/59 Rain PE/r °N *E GJ/M2 £al/cm PE (mm r (mm Inde Mts. ) ) X

GIDOLE 5.37 37.29 2550 7.001 94438 1601 1113 1.4 GIMBI 9.05 35.47 1870 6.480 86758 1470 1950 0.8 GOBA 7.01 40.00 2700 6.399 85564 1450 912 1.{ GODE 6.06 43.05 320 7.368 99848 1692 300 5. ( GOHA TSION 10.02 38.14 2550 6.633 89014 1509 1581 1. ( GONDER 12.32 37.26 2270 7.062 95338 1616 1153 1.4 GORE 8.10 35 .33 2130 6.426 85962 1457 2240 0.7 GORGORA 12.15 37.18 1840 6.950 93687 1588 990 1.6 GRAWA 9.08 41.50 2250 6 .610 88674 1503 935 1.6 GUDER 8.57 37.47 2002 7.441 100925 1711 1049 1.6 HAGERE MARIAM 5.38 38.15 2000 6.983 94173 1596 847 1. 9 HAGERE SELAME 6.28 38.31 2840 7.016 94659 1604 1177 1.4 HAMERO 7.22 42.13 750 7.411 100482 1703 281 6 .1 HARER 9.12 42.07 1856 7.008 94542 1602 696 2.3 HOSAINA 71.15 37.50 2290 6.863 92404 1566 1139 1.4 HUMERA 14 .10 36.30 550 7.991 109032 1848 616 3.0 INDA SILASE 14 .06 38 .16 1913 7.765 105701 1792 962 1.9 ITANG 8.10 34 .15 550 6 .412 85756 1453 965 1.5 JIJIGA 9.20 42.43 1644 6.990 94276 1598 824 1.9 JIMMA 7.40 36.50 1577 6 .453 86360 1464 1503 1. 0 KEBRIDEHAR 6.40 44 .18 450 8 .032 109637 1858 400 4 . 6 KEREN 15.45 38 .26 1460 6 . 944 93598 1586 373 4 3 KOFFELE 7.04 38 .47 2680 6.992 94306 1598 1204 1 3 KOKA 8 . 25 39.10 1650 7.478 101470 1720 807 2 1 KOLA DIBA 12 . 20 37.14 2150 7.022 94748 1606 1011 1. 6 KOMBOLCHA 11.05 39.45 1903 6.654 89323 1514 1020 1.5 KONSO 5 .15 37.35 1460 6.893 92846 1574 805 2.0 KULUMSA 8 . 08 39.08 2600 6.723 90340 1531 857 1. 8 KURMUK 10.33 34 .23 600 6.657 89367 1515 860 1.8 KUVERA 7.15 38 .40 2010 6 .970 93981 1593 875 1.8 LANGANO ■ 7.35 38 .40 1600 7.213 97563 1654 628 2.6 MAYCHEW 12.46 39.32 2380 7.788 106040 1797 754 2.4 MEGA 4 .05 38 .20 2215 6.952 93716 1588 606 ; 2.6 MEKELE 13 .30 39.25 2212 7.079 95588 1620 586 2.8 MEKA WERER 9 .28 40.23 737 7.244 98020 1661 559 3.0 MEND I 9.47 35.05 1650 6.541 87657 1486 16.42 0.9 METEHARA 8 .52 39.59' 951 7.290 98699 1673 526 3.2 22 Stat ions Lat Long. Elev QS QN QN/59 Rain PE/r °N "E GJ/M2 Cal/cm PE (mm r (mm Inde Mts. ) ) X

METEMA 12.57 36.04 803 7.411 100482 1703 883 1.9 METU 8.19 35.35 1940 6.432 86050 1458 1837 0.8 MEREBE AGAYA 6 .20 37.50 1290 7.086 95691 1622 752 2.2 MIGCLA LOLA 8 .47 42.07 1428 7.266 98345 1667 730 2.3 MISIWA 15.37 39.27 10 7.438 100880 1710 201 8.5 MOJO 8 .37 39.09 1880 7 .415 100541 1704 866 2.0 MOTA 11.05 37.55 2400 6 .549 87775 1488 1561 1.0 MOYALE 3.32 39.03 1110 7.055 95234 1614 710 2.3 MUNESSA 7.35 38 .54 2550 7 .166 96871 1642 1295 1.3 NAKFA 16.40 38 .20 1676 7.850 106954 1813 229 7.9 NAZRATE 8.33 39.17 1622 7.485 101573 1722 891 1.9 NEGBLE 5.17 39.45 1444 6.702 90031 1526 793 1.9 NEJO 9.30 35.29 1800 6.259 83500 1415 1720 0.8 NEKEMTE 9.03 36.36 2005 6 .413 85770 1454 2147 0.7 CGELCHO 8.04 39.02 1800 7.224 97726 1656 661 2.5 POKWO 8 .15 34 .25 560 6 .382 85313 1446 1070 1.4 ROB I 7.52 39.40 1300 7 .123 96237 1631 760 2.1 SHERARO 14 .24 37.58 1500 7.885 107470 1822 750 2.4 SODO 6 .50 37.43 2020 6 .823 91814 1556 1339 1.2 TEKEZE BRIDGE 13.46 38 .15 850 7 .652 104035 1763 855 2.1 TEPI • 7.05 35.15 1200 6.379 85269 1445 1555 0.9 TESENEY 15.07 36.40 585 7.862 107131 1816 331 5.5 TICHO 7 .29 39.32 2800 6.520 87348 1480 1256 1.2 WELISO 8 . 33 37.59 1960 6.695 89927 1524 1276 1.2 WENDO 6.35 38 .25 1860 6.985 94202 1597 1538 1.0 WENDOGENET 7. 10 38.35 1880 7.284 98610 1671 1128 1.5 WENJI 8 .25 39.15 1540 7.488 101617 1722 775 2.2 WOLDIYA 11.49 39.36 1960 6.943 93583 1586 1248 1.3 WUSH WUSH 7. 16 36 .11 1950 6 .443 86213 1461 1775 0.8 YABELO 4 .53 38 . 06 1740 6 .894 92861 1574 663 2.4 YIRGAALEM 6.45 38.23 1835 7 . 041 95028 1611 1187 1.4 YIRGACHEFE 6 .14 38 .15 1925 7.019 94704 1605 1867 0.9 YUBDO 8 .57 35.27 1520 6 .513 87245 1479 1454 1.0 ZEGE 11.49 37.14 1820 6 .793 91372 1549 1519 1.0

7TWAY ft .no IB. 4 5 1640 7.46ft 101.123- 1717 ft14 2 . 1

23 Figure 2.1. shows the corresponding gradient of the dryness ratio over the country. The index has no units. Low values indicate v,et regions, high values indicate dry regions. The Radiational Incex less than one is the region of rain forest. A ratio of one is clcse to the limit between forest and grassland. Along index one the heat and moisture of the year are almost exactly balanced. A ratio of 2 (usually taken to be the outer limit of the arid zone) means that the available energy can evaporate two years average rain. Similarly a ratio of 3,4,5,6,7 mean that the available energy can evaporate 3,4,5,6,7 years average rain respectively Lowry, (1972) .

For example, in West Africa the following relations was applied approximately ( Hare, 1985).

Dryness Vegetation zone Remarks ratio value

> 10 True desert (sahara) vegetation confined to Oasis.

7-10 Sahelo - Sahara Semi - desert shrub much affected by pasturing.

2 - 7 Sahelian and Dry savannahs and Sahelo - Sudanian forests severely affecte-d by over -pasturing and cultivation.

1 - 2 Sudano - Guinean Moist savannahs and and Sudanian dry forests largely cleared.

Guinean For merely Tropical rain forest, now much used ty cultivators.

In a comparative review of the UN conference on desertificaticn Hare, (1985) found that the zone most at risk lies between dryness ratio of 2 and 7. At higher values (the ratio becomes infinite at zero annual rainfall), the biological productivity is already too low to support large human populations, which cluster around or

24 along the main Oasis. At values below 2 the remaining vegetation is vigorous enough to re-colonize damage land. Soil erosion may occur in these moister regions, but usually not to the point where productivity irreversibly lost.

The term arid zone have no exact limits, though the dryness index of 2 lies close to its humid edge in most areas, thus the term arid is used as a collective expression for all drier areas such as, Savannahs, dry forest and Semi-desert shrubs.

2.5 Conclusion

The distribution of Radiational Index of Dryness, which is the outcome of the expression of the mean annual demand of water (PE) to that of the mean annual water available (Rainfall) are given on figure 2.1. This map is very useful to assess the water resource potential of the country. It is also useful for planning water resources for various activities, such as agriculture, human consumption and for other industrial purposes.

Reference

Kennth Hare F., 1985. Climate variations, drought and desertification, WMO.No. 653.

Lowry P.W., 1972. Compendium of lecture notes in climatology for class IV Met.Per Sonel WMO.No.327.

Hu, H. C. and Lim, J.T., 1983. Solar and Net radiation in peninsular Malaysia. (Journal of Climatology. Vol.3., No. 3 Chichester. Newyork: John Willey and Sons.

25 Hum id c 1 i rraite Dry sub-humid RED SEA Dry Cl i r^ate

Arid Cliwate 14 D e s e r t SUDitt 2

12 GULF OF hDEH

— 10 schhlia

SUD»*

Fig.2.1 Annual Average Radiational Index of Dryness

26 Chapter 3

Climatic classification using moisture Index

3.1 Introduction

Classification of climates based on the availability of water which is measured as rainfall and water need as potential evapotranspiration (P.E) is very useful in the field of agriculture. Pant and Rwandusya, (1971) had classified the climate of East Africa according to Thornwaite1s, (1948), and obtained a reasonable climatic classification for both Kenya, Uganda and Tanzania. Since Ethiopia is a close bordering neighbor to these countries and more than 80% of its economy relay on agriculture similar climatic classification is very useful to meet the needs of agricultural planning and operation.

3.2 Data utilized

The water need as potential evapotranspiration was estimated * using the net solar radiation computed from the Global solar radiation which is complied in the publication of solar radiation by Cesen (1982). The average monthly available water measured as rainfall up to 1983 were taken from respective stations.

3.3 Methodology

Thornwaite1s method is the most appropriate for this study. It is based on the responses of plant growth to environmental conditions by considering that evaporation is reducing the water available for plants growth. To compute potential evapotranspiration (P.E) several researchers have developed various empirical equations Chang (1974); Davies (1967); Selirio et al (1971) and Penman (cited by Chang 1970).

Potential evapotranspiration computed using Davies and Penman's formulae were compared at different climatic regions (table 3.1 and Fig. 3.1). The values of dryness ratia computed

27 using both formulae are similar for dryness ratio of 1 to 2 5. Above 2.5 dryness ratio Penman's formula gives a higher estimate than Davies and the regions are characterized as arid climates. ?or this study Potential evapotranspiration (P.E) computed using Davi.es equation was used for the following reasons.

To keep the data set consistent with aridity Index of dryness ratio.

It is linear to compute potential evapotranspiration from net radiation values.

Since computer program has been developed to compute the moisture index it is simple to replace any relevant P.E to obtain a new result.

A dryness ratio of 1 and less lies in the regions of ra:.n- fed agricultural practices while above 2 is at risk without irrigation, therefore both formulae equally serve in rain- fed agricultural regions.

28 TABLE 3.1: A measure of aridity ratio (Annual P.E/Annual r) using Davie's and penman's formulae.

No. Station Name Davies Penman

1 ADDIS ABABA 1.33 1.33 2 AGRO 0.96 0.89 3 AKORDAT 5.19 6.62 4 ALEMAYA 1.96 1.84 5 ARBA MINCH 2.07 1.94 6 ASMARA 3.43 2.80 7 ASOSA 1.19 1.20 8 AWASA 1.69 1.68 9 AWASH 2.59 3.46 10 BACO 1.26 1.19 11 BACO JINKA 1.15 1.03 12 BAHIRDAR 1.03 1.03 13 BEKOJI 1.46 1.24 14 CHAGNI 0.89 0.81 15 DEBREMARKOS 1.08 1.02 16 DIRE DAWA 2.86 3.63 17 DIXIS 1.65 1.50 18 GAMBELA 1.28 1.37 19 GEWANE 4.10 5.88 20 GONDAR 1.40 1.48 21 GORGORA 1.60 1.43 22 GRAWA 1.61 1.25 23 HAMERO 5.88 7.52 24 HARERE 2.30 2.13 25 HUMER 3.00 3.26 26 JIJIGA 1.94 2.02 27 JIMMA 0.94 0.84 28 KEREN 4.25 4.95 29 KLUMSA 1.79 1.75 30 KOFFELE 1.33 1.23 31 KOMBOLCHA 1.48 1.55 32 LANGANO 2.63 2.47 33 MEKELE 3.10 2.94 34 MELKAWRER 3.02 3.81 35 METEHARA 3.18 3.97 36 MITSIWA 8’. 51 9.65 37 MOJO 1.97 2.00 38 NEGELE 1.93 2.05

29 a n n u a l (P.E / r ) TU

3.1 oprsn f rns rto n AL 1 TABLE in ratio dryness of Comparison 0 2 4 6 S 20 2 2 2 2 3 3 3 3 38 36 34 32 30 2S 26 24 22 0 2 IS 16 14 12 10 8 9 i 1 ais Pn an Penm + Davies □

1 tto Cd o |\ AL I IABLL |f\ os Code Station 13 i 15 i 17 19 i 21 I 23 5 27 25 “1 93 3335 3 3 31 29 37 Water budgeting procedure and computation of Moisture Index

Thornthwaite, (1948) devised a simple book-keeping procedure of water surplus and water deficit in which case rainfall as income and potential evapotranspiration as expenditure while moisture stored in the soil as reserve of being drawn as long as it lasts. The maximum amount of soil water holding capacity for the use of vegetation varies in different soils. But for this study 100 mm of rainfall is used as mean. When detailed observations of soil water holding capacity are available this estimate has to be replaced by actual observations for agricultural practices. Details of bookkeeping application are shown for 140 stations in Table 3.2.

Thornthwaite using the combination of water surplus and water deficiency defined an index of rainfall effectiveness with expression:-

Im = 100-, - 60d Pant and Rwandusya, (1971) n

Where Im = moisture index or rainfall effectiveness, s = Annual water surplus.0 d = Annual water deficiency n = Annual water need (P.E) i r * ' ■ . *

All the above values are expressed in millimeters, positive values of Im represent moist climates while negative values represent dry climate.

3.4 Result and Discussion

Classification of Climates

The following classification of climates based on moisture index is according to Thornthwaite (Pant and Rwandusya, 1971).

31 Moisture Index Im Climatic Type

100 and above A per humid 20 to 100 B Humid 0 to 20 c2 Moist sub-humid -20 to 0 c, Dry sub-humid -40 to -20 D semiarid -60 to -40 E - Arid

On the basis of the annual values of "S" and "d" obtained from the above mentioned bookkeeping procedure, the moisture Index is computed for all 140 stations. The value of this Index together with climatic type, aridity Index, humidity Index, climatic sufc - division and the length of growing period to which the station belongs is given in table 3.3. The main types of climates are also shown in fig 3.2.

Climatic Sub-divisions

It is also useful to know if a place is continuously wet cr dry throughout a year or whether it is wet in one season and dry in another season. For arriving at those sub-divisions of major climatic types, Thornthwaite make use of an aridity index in the case of moist climates and a humidity index in the case of dry climates, Pant and Rwandusya (1971).

These indices are defined as follows

Humidity Index Ih = 100 X annual water surplus (mm) annual water need (mm)

Aridity Index I„ = 100 X annual water deficit (mm) annual water need (mm)

Since in the tropics, summer and winter do not have as mucn significance as they have in higher latitude and since these are usually well defined rainy and dry seasons which are more relevant, the following modified sub-classification is proposed for tropics.

32 moist climates (A,B,C2) Aridity Index I, s - small water deficit 0 - 16.7 m - moderate water deficit 16.8 - 33.3 L - large water deficit > 33.4

Dry climates (C, D[ E) Humidity Index In s - small water surplus 0 - 1 0 m - moderate water surplus 10 - 20 L - large water surplus > 20

Distribution of water surplus and Deficiency

For agricultural planning as well as for general problem of water management, it is not only necessary to know the main types of climates and their sub-divisions as stated above, but also the variations from month to month in these parameters. Therefore to identify wet and dry months for East Africa ( Pant and Rwandusya 1971) have used the following expression.

Humid period (H) mean monthly rainfall (R) mean monthly potential evapotranspiration (P.E).

Inter mediate period (I) P.E > R > P_J3 2

Moderately dry period (MD) P.E > R > P_J3 2 4

Dry period (D) : PJ2 > R > P_J3 4 10

Very dry period (VD) : R < P.E 10

Length of growing period (LGP): A .E >0.5 P.E

33 A period composed of intermediate and humid months is called "Moist (M)" which is often a crop-growing season.

The above method of comparison defines more accurately the availability of water for plant growth than rainfall alone. Because, the same amount of rain may be insufficient in one place for plant growth whereas it may be ample in another place, depending on the magnitude of the evaporative demand of the atmosphere. In table 3.2 the ratio of actual evaporation to potential evaporation (A.E/P.E) is provided and the length of the growing period is computed by counting months with A.E/P.E razio >0.5 . Circular diagrams on Figures 3.4a, 3.4b and 3.4c illustrate how the growing period is done.

3.5 Conclusion The present study has resulted the climatic map Fig. 3.2 which shows different climatic groups based on the moisture index criteria. One of the main significant features of this map is that vast majority of the area about 83% is occupied by one of t:he relatively dry climates (C, D and E), with moisture index ranging from less than zero to negative sixty (< 0 to -60). As far as sub divisions of climates are concerned, most of these dry climatic regions are having small water surplus 'S' in the respective rainy season i.e the rain that occurs is just about sufficient to me^et the water demand (P.E) at most places in Eastern Shewa, all along the Rift Valley, Sidamo, Bale, Arsi, Harerge, Eastern Wello, c.nd Eastern Tgrai. The dry climates' (C, & D) of the north Western Sh€*wa Western Wello, Gonder and Western Tigrai are having moderate 'M' to large 'L' water surplus in the respective rainy season (Fig 3.3). As a result of high water run-off, soil erosion and water logging is likely depending on the soil type and land formation in these regions.

The moist climates (B and C2) are confined in western parts of the country ranging from 0 to 60 moisture Index. As far as the sub divisions of these moist climates are concerned large water deficit "L" in the respective dry seasons are in parts of Southern Gonder, most of Gojam and Wellega. Small water deficit 'S' are along the adjoining regions of central Illubabor, Kefa and GamoGofa, while the Northern and Southern parts along these regions are having moderate water deficit 'M'.(Fig 3.3)

34 rr Hun id |] Moist subhumid RED SEA Dry subhumid Semi Arid Arid SUDAN

GULF OF ADEN

SOMALIA

SUDAN

SOMALIA KEN*A ; .

rig 3.2 Classification of Climate Based on Moisture Index

35 - -- 11 r» - — : [c r ; ; = I Small water surplus

i.ur.r.:.; Moderate water surplus

Large water surplus

nz±) OlC.h Small water deficit

Moderate water defiict

Large water deficit"

IT..VXJ O'uiys-n f" j %-.A *

...... I nan ch/ Mritti.i p \

Fig.3.3 Distribution of water surplus in dry climatic regions and water deficit in moist climatic regions

36 Station.,. jihka......

7 40 36 5 lot...... long.. «. o. alt. 35 77. a rts Annual PET.. 1465, J An nual RR. . W . .

0• 10 • 20• 30 • 40 • 50 • scale i... i—i— i—i— i cm

Fig 3* 4a

37 S t a t i o n ...... lat.?3t.39... long.. ?*??* alt-?2.1.2-# 8 Annual PET. A8?1. . . An nual RR...... 1

0 10 20 30 40 50 cm scale

?u 3.40

38 Statior K O M b o lo h a tat.iirf. long.??? alt..1*??..”** Annual PET..1.514. Annual RR.....1?“

0 10 20 30 40 50 S C O j ® !•» • * )»> » f 1»H i_ln .1-A-l a 11 -A-1 ^

Pi« 3.4b Table 3.2: Computation of water budget. Station Name: Abiy Adi

'-■srameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 14 K 150 r ’i 172 172 155 124 114 153 162 145 142 180f r 3 0 22 9 40 95 289 249 62 10 2 12 79- A. E. 3 0 22 9 40 95 124 114 153 19 2 •12 593 W.D. 145 150 149 163 132 60 0 0 0 143 143 130 12 IE W.S. 0 0 0 0 0 0 65 135 0 0 0 0 20C S.C. 0 0 0 0 0 0 100 0 -91 -9 0 0 C S 0 0 0 0 0 0 100 100 9 0 0 0 20S AE/PE 0.02 0.00 0 .13 0.05 0.23 0.61 1.00 1.00 1.00 0.12 0.01 0.08 -29.7 (Im) V.D V.D D V.D D I H H H D V.D V.D 122 days

Station Name: Abobo

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL -.E. 137 125 131 141 113 107 108 88 113 125 123 133 1444 r 7 15 59 92 149 107 206 171 159 110 50 7 1132 A. E. 7 15 59 92 113 107 108 88 113 125 123 19 969 W.D. 130 110 72 49 0 0 0 0 0 0 0 114 475 W.S. 0 0 0 0 0 0 34 83 46 0 0 0 163 S.C. 0 0 0 0 36 0 98 0 0 -15 -73 -12 34 S 0 0 0 0 36 36 100 100 100 85 12 0 469 AE/PE 0.05 0.12 0.45 0.65 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.14 -8.45 (Im) V.D D MD I H HH H HH HD 244 days

Station Name: Adaba

Parameter JAN FEB MAR APR* MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 133 130 141 131 136 128 107 115 124 128 132 138 1543 r 26 58 64 63 42 62 168 162 85 39 17 10 796 A.E. 26 58 64 63 42 62 107 115 124 100 17 10 788 W.D. 107 72 77 68 94 66 0 0 0 28 115 128 755 W.S. 0 0 0 0 0 0 0 8 0 0 0 0 8 S.C. 0 0 0 0 0 0 61 3-9 -39 -61 0 0 0 S 0 0 0 0 0 0 61 100 61 0 0 0 222 AE/PE 0.20 0.45 0.45 0.48 0.31 0.48 1.00 1.00 1.00 0.78 0.13 0.07 -28.84 (Im) D MD MD MD MD MD HHH ID V.D 123 days

Station Name: Addis Ababa Parameter JAN FEB MAR APR MAY JDN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 137 128 145 its lie 113 95 103 116 145 144 143 1538 r 22 35 69 89 74 120 255 255 • 173 40 • 11 11 1154

A.E. 22 35 69 89 74 113 95 103 116 140 11 11 878 W.D. 115 93 76 44 62 0 0 0 0 5 133 132 660 W S. 0 0 0 0 0 0 67 152 57 0 0 0 276 S.C. 0 0 0 0 0 7 93 0 0 -100 0 0 0 S 0 0 0 0 0 7 100 100 100 0 0 0 307 AE/PE 0.16 0.27 0.48 0 .67 0.54 1.00 1.00 1.00 1.00 0.97 0.08 0.08 -7.80 (Im) D MD MD I IH H H H I V.D V.D 214 days

4 0 Table 3.2: Continued...computation of water budget

Station Name: Adigrat

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 142 135 166 170 188 167 145 144 159 161 136 137 1850 r 8 7 45 62 47 39 140 151 17 27 26 12 581 A . E. 8 7 45 62 47 39 140 144 24 27 26 12 581 W.D. 134 128 121 108 141 128 5 0 135 134 110 125 1269 W.S. 0 0 . 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 7 -7 0 0 0 0 S 0 0 0 0 0 0 0 7 0 0 0 0 7 AE/PE 0.06 0.05 0.27 0.36 0.25 0 .23 0.97 1.00 0.15 0. 17 0.19 0.09 -41.16 (Im) V.D V.D MD MD D I H DD D V.D 62 days

Staticr Name: Adi Keyih Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 140 134 166 170 189 168 152 144 158 160 135 136 1852 r 2 8 30 53 32 26 156 136 3 6 23 .9 484

A. E. 2 8 30 53 32 26 152 140 3 6 23 9 484 W.D. 138 126 136 117 157 142 0 4 155 154 112 127 1368 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 4 -4 0 0 0 0 0 S 0 0 0 0 0 0 4 0 0 0 0 0 4 AE/PE 0.01 0.06 0.18 0. 31 0.17 0.15 1.00 0.97 0.02 0.04 0.17 0.07 -44.32 (Im) V.D V.D D MD D D H I V.D V.D D V.D 62 days

St at Lon Name: Adi Ugri Paramerer JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.S. 142 139 168 173 190 170 152 136 153 165 139 137 1864 r 0 3 11 26 40 52 184 170 56 7 21 3 573 A.S. 0 3 11 26 40 52 152 136 122 7 21 3 573 W.D. 142 136 157 147 150 118 0 0 31 158 118 134 1291 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 32 34 -66 0 0 0 0 s 0 0 0 0 0 0 32 66 0 0 0 0 98 AE/PE 0.00 0.02 0.07 0.15 0.21 0.31 1.00 1.00 0.80 0.04 0.15 0.02 -41.56 (Im) V.D V.D V.D DD MD H H I V.D D V.D 92 days

Station Name: Addis Zemen

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 133 141 164 154 139 119 83 86 131 147 139 134 1570 r a 1 0 28 45 97 356 318 123 52 15 26 1065

A. E. 4 1 0 28 45 97 83 86 131 144 15 26 660 W.D. 129 140 164 126 94 22 0 0 0 3 124 1'08 910 W.S. 0 0 0 0 0 0 173 232 0 0 0 0 405 S.C. 0 0 0 0 •0 0 100 0 -8 -92 0 0 0 s 0 0 0 0 0 0 100 100 92 0 0 0 292 AE/PE 0.03 0.01 0.00 0.18 0.32 C 82 1.00 1.00 1.00 0.98 0.11 0.19 -8.98 (Im) V.D V.D V.D D MD XT H HH I D D 153 days

41 Table 3.2: Continued... computation of water budget

Station Name: Ado la

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 139 131 143 133 131 118 111 125 126 124 130 135 15-6 r 21 22 93 194 218 75 34 40 82 170 81 6 1036 A. E. 21 22 93 133 131 118 91 40 82 124 127 6 988 W.D. 118 109 50 0 0 0 20 85 44 0 3 129 5!) 8 W.S. 0 0 0 0 48 0 0 0 0 0 0 0 18 S.C. 0 0 0 61 39 -43 -57 0 0 46 -46 0 0 S 0 •o 0 61 100 57 0 0 0 46 0 0 2.4 AE/PE 0.15 0.1? 0.65 1.00 1.00 1. 00 0.82 0.32 0.65 1.00 0.98 0.04 -18.55 (Im) D D I H H H I MD I H I V.D 153/91 days

Station Name: Adwa Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 147 147 172 174 185 167 135 118 158 164 146 135 1818 r 1 3 13 28 29 65 216 219 97 86 6 0 763 A.E. 1 3 13 28 29 65 135 118 158 125 6 0 681 W.D. 146 144 159 146 156 102 0 0 0 39 140 135 1167 W.S. 0 0 0 0 0 0 0 82 0 0 0 . 0 82 S.C. 0 0 0 0 0 0 81 19 -61 -39 0 0 0 S 0 0 0 0 0 0 81 100 39 0 0 0 220 AE/PE 0.01 0.02 0.08 0.16 0.16 0.39 1.00 1.00 1.00 0.76 0.04 0.00 -33.45 (Im) V.D V.D V.D D D MD H H H I V r D V.D 123 deys

Station Name: Agaro

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 130 118 135 133 127 111 101 106 115 134 125 130 1<'65 r 43 33 93 80 209 202 195 247 170 171 75 19 If 37

A.E. 43 33 93 80 127 111 101 106 115 134 125 69 i:.37 W.D. 87 85 42 53 0 0 0 0 0 0 0 61 28 W.S. 0 0 0 0 0 73 94 141 55 37 0 0 ■i00 S.C. 0 0 0 0 82 18 0 0 0 0 -50 -50 0 s 0 0 0 0 82 100 100 100 100 100 50 0 ji 32 AE/PE 0.33 0.28 0.69 0.60 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.53 13.87 (Im) MD MD I IHHH HH H ■H I 3 06 days

Station Name: Akaki Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 136 129 150 141 142 120 107 114 122 146 143 ;40 1590 r 10 16 54 71 63 77 208 251 103 11 2 5 371 A.E. 10 16 54 71 63 77 107 114 122 92 2 5 733 W.D. 126 113 96 70 79 43 0 0 0 54 141 135 357 W.S. 0 0 0 0 0 0 1 137 0 0 0 0 138 S.C. 0 0 0 0 0 0 100 0 -19 -81 0 0 0 s 0 0 0 0 0 0 100 100 81 0 0 0 281 AE/PE 0.07 0.12 0.36 0.5 0 0.44 0.64 1.00 1.00 1.00 0.63 0.01 0 . 04 -23.66 (Im) V.D D MD I MD I H HH I V.D V.D 30/153 days

42 Table 3.2: Continued...computation of water budget

Station Name: Akordat

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 132 134 162 161 155 136 103 85 119 147 126 127 1587 r 0 0 '0 4 1 24 111 116 38 5 1 0 300 A . E. 0 0 ' 0 4 1 24 103 85 77 S 1 0 300 W.D. 132 134 162 157 154 112 0 0 42 142 125 127 1287 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 8 31 -39 0 0 0 0 S 0 0 0 0 0 0 8 39 0 0 0 0 47 AE/PE 0.00 0.00 0.00 0.02 0.01 0.18 1.00 1.00 0.65 0.03 0.01 0.00 -48.66 (Im) V.D V.D V.D V.D V.D ,D H H I V.D V.D V.D 92 days

Station Name: Alaba Kalito Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 139 136 160 150 146 125 117 121 117 150 144 139 1644 r 38 63 99 130 94 62 115 121 97 45 39 10 913 A . E. 38 63 99 130 94 62 115 121 97 45 39 ’10 913 W.D. 101 73 61 20 52 63 2 0 20 105 105 129 731 W.S . 0 0 0 0 ■ 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 AE/PE 0.27 0.46 0.S2 0.87 0.64 0.50 0.98 1.00 0.83 0.30 0.27 0.07 -26.68 (Im) MD MD I II MD I H I MD MD V.D 92/92 days

Station Name: Alamata

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 128 142 159 157 166 152 134 136 130 156 137 133 1730 r 60 68 78 84 44 0 34 90 23 17 16 29 543

A . E. 60 68 78 9-; 44 0 34 90 23 17 16 29 543 W.D. 68 74 81 73 122 152 100 46 107 139 121 104 1187 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 0 0 0 0 0 0 s 0 0 0 0 0 0 0 0 0 0 0 0 0 AE/PE 0 .47 0.48 0.49 0.54 0.27 0 .00 0.25 0.66 0.18 0 .11 0. 12 0.22 -41 .17 (Im) MD MD MD I MD V.D MD I D D DD 30/31 days

Station Name: Alem Ketema

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 128 137 130 134 150 122 103 102 114 138 145 133 1536 r 9 26 6 45 70 75 339 360 164 40 8 9 1151 A . E . 9 26 6 45 70 lb 103 102 114 138 10 9 707 W.D. 119 111 124 89 80 47 0 0 0 0 135 124 829 W .. . 0 0 0 0 C 0 136 258 50 0 0 0 444 S.C. 0 0 0 0 0 0 100 0 0 -98 -2 0 0 S 0 0 0 0 0 0 100 100 100 2 0 0 302 AE PE 0.07 0.19 0 .05 0.34 0.47 0.61 1 .00 1.00 1. 00 1.00 0.07 0.07 -3.48 (Im) V.D D V.D MD MD IH H H H V.D V.D 153 days

43 Table 3.2: Continued...computation of water budget

Station Name: Alemaya

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 146 132 148 141 139 127 131 133 131 142 143 141 1654 r 8 30 77 88 108 67 108 166 115 43 20 8 838 A.E. 8 30 77 88 108 67 108 133 131 60 20 8 838 W.D. 138 102 71 53 31 60 23 0 0 82 123 133 816 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 33 -16 -17 0 0 0 S 0 0 0 0 0 0 0 33 17 0 0 0 50 AE/PE 0.05 0.23 0.52 0.62 0.78 0.53 0.82 1.00 1.00 0 .42 0 .14 0.06 -29.60 (Im) V.D DI III I H H MD D V.D 214 c ays

Station Name: Ambo

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 135 128 143 139 132 111 96 105 114 141 140 138 1522 r 21 23 71 74 78 154 250 237 119 41 6 13 1387

A.E. 21 23 71 74 78 111 96 105 114 141 6 13 >3 53 W.D. 114 105 72 65 54 0 0 0 0 0 134 125 669 W.S. 0 0 0 0 0 0 97 132 5 0 0 0 234 S.C. 0 0 0 0 0 43 57 0 0 -100 0 0 0 S 0 0 0 0 0 43 100 100 100 0 0 0 343 AE/PE 0.16 0.18 0.50 0.53 0.59 1.00 1.00 1.00 1.00 1.00 0.04 0.09 -11.00 (Im) D D MD IIHH H H H V.D V.D 214 days

Station Name: Arba Minch

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANN JAL P.E. 146 139 146 141 141 120 110 119 130 142 141 145 1520 r 27 21 73 124 119 52 47 45 91 105 56 23 783 A.E. 27 21 73 124 119 52 47 45 91 105 56 23 783 W . D. 119 118 73 17 22 68 63 74 39 37 85 122 337 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. C 0 0 0 0 0 0 0 0 0 0 0 0 S 0 0 0 0 0 0 0 0 0 0 0 0 0 AE/PE 0.18 0.15 0.50 0.88 0.84 0.43 0.43 0.38 0.70 0.74 0.40 0.16 -31.00 Cm) D D I IMDMDMD I IMD• D 61/61 d.^ys

Station Name: Ar jo

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 136 129 138 143 123 103 96 93 113 133 127 128 1462 r 12 39 86 119 302 318 336 389 297 107 75 23 2. 03 A.E. 12 39 86 119 123 103 96 93 113 133 127 45 It 89 W.D. 124 90 52 24 0 0 0 0 0 0 0 83 373 W.S. 0 0 0 0 79 215 240 296 184 0 0 0 1014 S.C. 0 0 0 0 100 0 0 0 0 -26 -52 -22 0 S 0 0 0 0 100 100 100 100 100 74 22 0 596 AE/PE 0.09 0.30 0.62 0.83 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.35 54.05 Cm) V.D MD I I H H H H H H H MD 275 dc.ys

44 Table 3.2: Continued...computation of water budget

Station Name: Assela

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 143 138 146 141 139 132 113 121 118 144 141 138 1614 r 25 54 103 106 121 143 231 245 181 63 22 9 1303 A. E. 25 54 103 106 121 132 113 121 118 144 41 9 1087 W.D. 118 84 43 35 18 0 0 0 0 0 100 129 527 W.S. 0 0 0 0 •o 0 29 124 63 0 0 0 216 S.C. 0 0 0 0 0 11 89 0 0 -81 -19 0 0 S 0 0 0 0 0 11 100 100 100 19 0 0 330 AE/PE 0 .17 0.39 0.71 0.75 0.87 1.00 1.00 1.00 1.00 1.00 0.29 0.07 -6.21 (Im) D MD I II H HH H H MD V.D 245 days

Station Name: Asendabo Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 130 118 136 131 132 112 99 107 116 135 126 129 1471 r 21 39 90 75 153 197 216 195 116 52 27 12 1193

A. E. 21 39 90 75 132 112 99 107 116 135 44 12 982 W.D. 109 79 46 56 0 0 0 0 0 0 82 117 489 W.S. 0 0 0 0 0 6 117 88 0 0 0 0 211 S.C. 0 0 0 0 21 79 0 0 0 -83 -17 0 0 S 0 0 0 0 21 100 100 100 100 17 0 0 438 AE/PE 0.16 0.33 0.66 0.57 1.00 1 .00 1.00 1.00 1.00 1.00 0.35 0.09 -5.60 (Im) D MD I I HHHHH H MD V.D 24 5 days

Station Name: Asmera Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 138 118 165 170 184 171 158 151 158 159 134 135 1841 r 3 2 13 33 43 41 187 155 24 12 19 5 537 A. E. 3 2 13 33 43 41 158 151 57 12 19 5 537 W.D. 135 116 152 1 37 141 130 0 0 101 147 115 130 1304 W.S. 0 0 0 0 C 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 29 4 -33 0 0 0 0 S 0 0 0 0 0 0 29 33 0 0 0 0 62 AE/PE 0.02 0.02 0.08 0.19 0.23 0.24 1.00 1.00 0.36 0.08 0. 14 0.04 -42.50 dm) V.D V.D V.D DDDHH MD V.D D V.D 62 days

Station Name: Assosa

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 142 133 129 153 129 110 109 94 125 134 125 129 1512 r 1 6 24 62 119 .180 250 237 203 139 26 28 1275 A.3. 1 6 24 62 119 110 109 94 125 134 125 29 938 W.D. 141 127 105 91 10 0 0 0 0 0 0 100 574 W.S. 0 0 0 0 0 0 111 143 78 5 0 0 337 S.C. 0 0 0 0 0 70 30 0 0 0 -99 -1 0 S 0 0 0 0 0 ">0 100 100 100 100 1 0 471 AE/PE 0.01 0.05 0.19 0.43 0.92 1.00 1.00 1.00 1.00 1.00 1.00 G ,22 -0.49 (Im) V.D V.D D MD IHH HH HH D 214 days

45 Table 3.2: Continued... computation of water budget

Station Name: Atnago

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 136 129 143 139 125 104 96 96 113 135 133 127 1476 r 22 59 114 118 256 275 480 416 304 122 36 10 2212

A.E. 22 ■59 114 118 125 104 96 96 113 135 123 10 1115 W.D. 114 70 29 21 0 0 0 0 0 0 10 117 361 W.S. 0 0 0 0 31 171 384 320 191 0 0 0 1097 S.C. 0 0 0 0 100 0 0 0 0 -13 -87 0 0 S 0 0 0 0 100 100 100 100 100 87 0 0 587 AE/PE 0.16 0.46 0.80 0.85 1.00 1.00 1.00 1.00 1. 00 1.00 0.92 0.08 59.65 (Im) D MD I I HH H H H HI V.D 275 days

Station Name: Awassa

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 141 135 148 135 139 127 110 121 119 134 140 143 1592 r 27 42 60 87 127 91 128 133 128 76 32 13 944 A.E. 27 42 60 87 127 91 110 121 119 115 32 13 94-3 W.D. 114 93 88 48 12 36 0 0 0 19 108 130 648 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 18 12 9 -39 0 • 0 0 s 0 0 0 0 0 0 18 30 39 0 0 0 87 AE/PE 0.19 0.31 0.41 0.64 0.91 0.72 1. 00 1.00 1.00 0.86 0.23 0.09 -24.42 (Im) D MD MD I I IH HH ID V.D 214 days

Station Name: Awash

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 134 131 147 137 141 127 124 129 124 138 132 133 1597 r 21 47 56 68 35 33 112 143 55 21 18 6 615 A.E. 21 47 56 68 35 33 112 129 69 21 18 6 615 W.D. 113 84 91 69 106 94 12 0 55 117 114 127 98.2 W.S. C 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 14 -14 0 0 0 0 S 0 0 0 0 0 0 0 14 0 0 0 0 14 AE/PE 0.16 0.36 0.38 0.50 0.25 0.26 0.90 1.00 0.56 0.15 0.14 0.05 -36.89 (Im D MD MD MD D MD I HIDD V.D 92 day:

Station Name: Aykel

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAJ.

P.E. 132 142 165 157 143 132 109 93 135 148 138 138 1632 r 1 0 15 69 97 149 365 273 110 89 5 • 7 1180 A.E. 1 0 15 69 97 132 109 93 135 i48 21 7 827 W.D. 131 142 150 88 46 0 0 0 0 0 117 131 805 W.S. 0 0 0 0 0 0 173 180 0 0 0 0 351 S.C. 0 0 0 0 0 17 83 0 -25 -59 -16 0 0 S 0 0 0 0 0 17 100 100 75 16 0 0 308 AE/PE 0.01 0.00 0.09 0.44 0.68 1.00 1.00 1.00 1.00 1.00 0.15 0 .05 -7.97 (Im) V.D V.D V.D MD I HHHH H D V.D 184 day£;

I Tab_e 3.2: Continued...computation of water budget

Station Name: Bahir Dar

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 130 140 156 154 135 113 85 89 127 142 133 129 1533 r 4 2 7 24 86 179 454 403 202 95 26 40 1522 A.E. 4 2 7 24 86 113 85 89 127 142 79 40 798 W.D. 126 138 149 130 49 0 0 0 0 0 54 89 735 W.S. 0 0 0 0 0 0 335 314 75 0 0 0 724 S.C. 0 0 0 0 0 66 34 0 0 -47 -53 0 0 S 0 0 0 0 0 66 100 100 100 53 0 0 419 AE/PE 0.03 0.01 0.04 0.16 0 .64 1 .00 1.00 1.00 1.00 1.00 0.59 0.31 18.46 (Im) V.D V.D V.D D I HHHHHI MD 214 days

Station Name: Bako

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 132 128 141 145 131 116 97 106 114 139 136 133 1518 r 10 22 52 47 166 187 256 226 157 44 19 7 1193

A.E. 10 22 52 4 7 1'31 116 97 106 114 139 24 7 865 W.D. 122 106 89 98 0 0 0 0 0 0 112 126 653 W.S. 0 0 0 0 0 6 159 120 43 0 0 0 328 S.C. 0 0 0 0 35 65 0 0 0 -95 -5 0 0 S 0 0 0 0 3;5 100 100 100 100 5 0 0 440 AE/PE 0.08 0.17 0.37 0.32 1.00 1.00 1.00 1.00 1.00 1.00 0. 18 0.05 -4.20 (Im) V.D D MD MD H H H H HH D V.D 184 days

Station Name: Bako Jinka Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 140 139 132 142 123 118 110 103 119 134 136 141 1537 r 39 70 101 180 167 107 102 110 135 168 125 38 1342 A.E. 39 70 101 142 123 118 110 103 119 134 136 127 1322 W.D. 101 69 31 0 0 0 0 0 0 0 0 14 215 W.S. 0 0 0 0 0 0 0 0 0 20 0 0 20 S.C. 0 0 0 38 44 -11 -8 7 16 34 -11 -89 20 S 0 0 0 38 82 71 63 70 86 100 89 0 599 AE/PE 0 .28 0.50 0.77 1.00 1. 00 1.00 1.00 1 .00 1.00 1.00 1.00 0.90 -7.09 (Im) MD I IH HH H HH H ' H I 334 days

Staticu Name: Bambese

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 140 131 129 151 126 110 107 94 122 133 125 130 1498 r 3 3 14 46 2.73 256 229 269 232 103 13 3 1344 A.E. 3 3 14 46 126 110 107 94 122 133 83 3 844 W.D. 137 128 115 105 0 0 0 0 0 0 42 127 654 W.S. 0 0 0 0 0 93 122 175 110 0 0 0 500 S.C. 0 0 0 0 47 53 0 0 0 -30 -70 0 0 s 0 0 0 0 4 7 100 100 100 100 70 0 0 517 AE/PE 0.02 0.02 0 . 11 0.30 1 .00 1 .00 1.00 1.00 1.00 1.00 0.66 0.02 7.18 (Im) V.D V.D D MD HH H HH HI V.D 214 days

47 Table 3.2: Continued...computation of water budget

Station Name: Bati

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

P.E. 122 119 135 137 146 126 116 125 120 136 126 116 1524 r 67 62 67 56 57 10 173 248 54 60 3 15 872 A. E. 67 62 67 56 57 10 116 125 120 94 3 15 792 W.D. 55 57 68 81 89 116 0 0 0 42 123 101 732 W.S. 0 0 0 0 0 0 0 80 0 0 0 0 80 S.C. 0 0 0 0 •0 0 57 43 -66 -34 0 0 0 S 0 0 0 0 0 0 57 100 34 0 0 0 191 AE/PE 0.55 0.52 0.50 0.41 0.39 0.08 1.00 1.00 1.00 0.69 0.02 0.13 -23.57 (im) I I MD MD MD V.D H H H I V.D D 59/123 djys

Station Name: Bedelle

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 140 129 138 139 123 103 96 96 113 133 126 129 1465 r 12 8 70 112 241 287 403 315 292 123 58 3 1 *24 A. E. 12 8 70 112 123 103 96 96 113 133 126 25 1' 17 W.D. 128 121 68 27 0 0 0 0 0 0 0 104 •4 8 W.S. 0 0 0 0 18 184 307 219 179 0 0 0 '■07 S.C. 0 0 0 0 100 0 0 0 0 -10 -68 -22 0 S 0 0 0 0 100 100 100 100 100 90 22 0 <12 AE/PE 0.09 0.06 0.51 0.81 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.19 43.56 dm) V.D V.D I IH H H HH HH D 275 days

Station Name: Begi

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 140 131 130 148 124 109 106 94 121 133 123 131 1490 r 14 6 49 67 210 237 202 203 218 96 56 2 1360 A . E. 14 6 49 67 124 109 106 94 121 133 119 2 944 W.D. 126 125 81 81 0 0 0 0 0 0 4 129 546 W.S. 0 0 0 0 0 114 96 109 97 0 0 0 416 S.C. 0 0 0 fj 86 14 0 0 0 -37 -63 0 0 S 0 0 0 0 86 100 100 100 100 63 0 0 54 9 AE/PE 0.10 0.05 0.38 0.45 1.00 1.00 1.00 1.00 1.00 1.00 0.97 0.02 5.93 (Im) V.D MD MD HH H H HH I V.D 214 da/s

Station Name: Bekoj i

Parameter JAN FEB MARAPR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 143 128 i41 123 130 112 98 102 111 124 129 137 1478 r 32 47 81 87 97 106 200 180 93 60 19 10 1012 A . E. 32 47 81 87 97 106 98 102 111 124 37 10 932 W.D. 111 81 60 36 33 6 0 0 0 0 92 127 546 W.S. 0 0 0 0 0 0 2 78 0 0 0 0 00 S.C. 0 0 0 0 0 0 100 0 -18 -64 -18 0 0 S 0 0 0 0 0 0 100 100 82 18 0 0 300 AE/PE 0.22 0.37 0.57 0.7; 0.75 0.95 1.00 1.00 1.00 1.00 0.29 0.07 -16.75 (Im) D MD III I H H H H MD V.D 24 5 days

48 Table 3.2: Continued...computation of water budget

Station Name: Bilate

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 142 135 149 135 139 127 110 121 119 135 141 154 1607 r 26 28 70 103 99 88 109 57 74 74 32 20 780 A.E. 26 28 70 103 99 88 109 57 74 74 32 20 780 W.D. 116 107 79 32 40 39 1 64 45 61 109 134 827 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 0 0 0 0 0 0 s 0 0 0 0 0 0 0 0 0 0 0 0 0 AE 'PE 0.18 0.21 0 .47 0.76 0.71 0.69 0.99 0.47 0.62 0.55 0.23 0. 13 -30.88 (Im) D D MD I I I I MD I I D D 122/61 days

Station Name: Bonga

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 129 118 134 134 129 112 99 106 115 133 126 129 1464 r 39 93 130 188 243 196 226 226 204 149 52 43 1789

A.S. 39 93 130 134 129 112 99 106 115 133 126 69 1285 W.D. 90 25 4 0 0 0 0 0 0 0 0 60 179 W.S. 0 0 0 0 68 84 127 120 89 16 0 0 504 S.C. 0 0 0 54 46 0 0 0 0 0 -74 -26 0 s 0 0 0 54 100 100 100 100 100 100 26 0 600 AE/PE 0.30 0 .79 0.97 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.53 27.09 (Im) MD IIHHHH H HH H I 334 days

Station Name: Bulki

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 137 137 132 141 118 113 116 100 119 135 139 140 1527 r 42 46 200 251 211 125 141 178 187 206 136 115 1838 A.E. 42 46 132 141 118 113 116 100 119 135 139 140 1341 W.D. 95 91 0 0 0 0 0 0 0 0 0 0 186 W.S. 0 0 0 78 93 12 25 78 68 71 0 0 425 S.C. 0 0 68 32 0 0 O' 0 0 0 -3 -25 72 s 0 0 68 100 100 100 100 100 100 100 97 72 937 AE./PE 0.31 0.34 1.00 1 .00 1. 00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 20.52 (Im) MD MD HHHHHHHH H H 3 06 days

Station Name: Bure

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 136 129 135 136 115 106 103 88 114 129 123 133 1447 r 22 20 65 82 156 203 175 228 181 101 36 13 1282

A.E. 22 20 65 82 115 106 103 88 114 129 108 13 965 W.D. 114 109 70 54 0 0 0 0 0 0 15 120 482 W.S. 0 0 0 0 0 38 72 140 67 0 0 0 317 S.C. 0 0 0 0 41 59 0 0 0 -28 -72 0 0 S 0 0 0 0 41 100 100 100 100 72 0 0 513 AE/PE 0.16 0.16 0.48 0.60 1.00 1.00 1.00 1.00 1.00" 1.00 0.88 0.10 1.92 (Im) D D MD I H H HHHHI V.D 244 days

49 Table 3.2: Continued...computation of water budget

Station Name: Bur j i

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 151 143 140 142 122 127 115 112 119 131 137 142 1 fi 8 1 r 20 39 117 192 169 36 33 43 84 191 86 5 1015 A. E. 20 39 117 142 122 127 39 43 84 131 137 14 1015 W.D. 131 104 23 0 0 0 76 69 35 0 0 128 :>66 W.S. 0 0 0 0 0 0 0 0 0 0 0 ' 0 0 S.C. 0 0 0 50 47 -91 -6 0 0 60 -51 -9 0 s 0 0 0 50 97 6 0 0 0 60 9 0 222 AE/PE 0.13 0.27 0.84 1.00 1.00 1.00 0.34 0.38 0.71 1.00 1.00 0.10 -21.48 (Im) D MD IHH H MD MD IH H V.D 122/91 dc ys

Station Name: Butaj ira

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 138 136 160 150 146 126 118 122 116 150 143 138 1€ 43 r 35 45 109 85 124 92 168 162 114 56 19 11 1020 A. E. 35 45 109 85 124 92 118 122 116 144 19 11 1020 W.D. 103 91 51 65 22 34 0 0 0 6 124 127 623 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 50 40 -2 -88 0 0 0 S 0 0 0 0 0 0 50 90 88 0 0 0 228 AE/PE 0.25 0.33 0.68 0.57 0.85 0.73 1.00 1 .00 1.00 0.96 0.13 0.08 -22 .75 (Im) MD MD I II I H K H I D V.D 245 days

Station Name: Chagni

Parameter JAN FEB MAR A?k MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL $ P.E. 137 137 141 155 130 111 91 89 126 137 126 122 1502 r 4 9 17 28 156 277 350 356 292 161 22 15 1687

A. E. 4 9 17 28 130 111 91 89 126 137 122 15 £79 W . D. 133 128 124 127 0 0 0 0 0 0 4 107 623 W.S. 0 0 0 0 0 92 259 267 166 24 0 0 £08 S.C. C 0 0 0 26 74 0 0 0 0 -100 0 0 S 0 0 0 0 26 100 100 100 100 100 0 0 E 26 AE/PE 0.03 0.07 0.12 0.18 1.00 1.00 1.00 1.00 1.00 1.00 0.97 0.12 28.91 (Im) V.D V.D DDH HHHH HI D 214 dsys

Stat ion Name: Chef a

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNtAL

P.E. 122 119 134 13p 144 126 115 123 118 137 127 116 15 17 r 30 39 78 81 40 33 265 266 128 31 36 15 1C 42 A. E. 30 39 78 81 40 33 115 123 118 131 36 15 839 W.D. 92 80 56 55 104 93 0 0 0 6 91 101 678 W.S. 0 0 0 0 0 0 50 143 10 0 0 0 2 03 S.C. 0 0 0 0 0 0 100 0 0 -100 0 0 0 S 0 0 0 0 0 0 100 100 100 0 0 0 3 00 AE/PE 0.25 0.33 0.58 0.60 0.28 0.26 1.00 1.00 1.00 0.96 0.28 0.13 -13.43 (Im) D MD I I MD MD HH H I MD D 61/123 days

50 Table 3.2: Continued...computation of water budget

Station Name: Chencha

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 151 143 142 143 138 128 110 110 119 142 144 151 1621 r 40 114 151 249 156 108 106 136 139 189 52 41 1481 A.E 40 114 142 143 138 128 110 110 119 142 144 49 1379 W.D 111 29 0 0 0 0 0 0 0 0 0 102 242 W.S. 0 0 0 15 18 0 0 2 20 47 0 0 102 S.C. 0 0 9 91 0 -20 -4 26 0 0 -92 -8 2 S 0 0 9 100 100 80 76 100 100 100 8 0 673 AE/PE 0 .26 0.80 1.00 1. 00 1.00 1.00 1.00 1.00 1.00 1. 00 1.00 0.32 -2.67 (Im) MD I H HHHH H HH H MD 3 03 days

Station Name: Dabat Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 148 145 171 160 148 138 89 156 135 158 144 141 1733 r 0 11 20 17 63 19 318 326 100 31 18 5 928 A.E. 0 11 20 17 63 19 89 156 135 96 18 5 629 W.D. 148 134 151 143 85 119 0 0 0 62 126 136 1104 W.S. 0 0 0 0 0 0 129 170 0 0 0 0 299 S.C. 0 0 0 0 0 0 100 0 -35 -65 0 0 0 S 0 0 0 0 0 0 100 100 65 0 0 0 265 AE/?E 0.00 0.08 0.12 0. 11 0.43 0.14 1.00 1.00 1.00 0.61 0.13 0.04 -20.97 (Im) V.D V.D DD MD D H H HI D V.D 123 days

Star ion Name: Dangla

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E 136 139 150 155 132 112 87 87 130 137 127 125 1517 r 4 4 27 36 81 225 358 334 225 97 55 14 1460 A.E . 4 4 27 36 81 112 87 87 130 137 115 14 834 W.D . 132 135 123 119 51 0 0 0 0 0 12 111 683 W.S . 0 0. 0 0 0 13 271 247 95 0 0 0 626 S.C. 0 0 0 0 0 100 0 0 0 -40 -60 0 0 S 0 0 0 0 0 100 100 100 100 60 0 0 460 AE/PE 0.03 0.03 0 .18 0.23 0.61 1.00 1.00 1 . 00 1 .00 1 .00 0.91 0.11 14.25 (Im) V.D V.D DDI H H HH H I D 2 34 days

Station Name: Debre Berhan

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 134 135 143 134 148 123 108 123 128 14 5 146 134 1606 r 16 20 43 36 34 51 280 276 88 32 10 4 890 A.E. 16 20 43 36 34 51 108 123 128 92 10 4 665. W.D. 118 115 100 ‘98 114 77 0 0 0 53 136 130 941 W.S. 0 0 0 0 0 0 72 153 ' 0 0 0 0 225 S.C. 0 0 0 - 0 0 0 100 0 -40 -60 0 0 0 S 0 0 0 0 0 0 100 100 , 60 0 0 0 260 AE/PE 0 .12 0.15 0.30 0.27 0.23 0.40 1.00 1.00 1.00 0.63 0.07 0.03 -21.15 (Im) D D MD MD D MD H H H I V.D V.D 123 days

51 Table 3.2: Continued...computation of water budget

Station Name: Debre Markos

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 132 129 130 151 129 107 88 87 114 136 127 127 1157 r 17 20 50 64 90 156 309 305 218 78 26 15 l.;48 A. E. 17 20 50 64 90 107 88 87 114 136 68 ' 15 1156 W.D. 115 109 80 87 39 0 0 0 0 0 59 112 i 01 W.S. 0 0 0 0 • 0 0 170 218 104 0 0 0 -■92 S.C. 0 0 0 0 0 49 51 0 0 -58 -42 0 0 S 0 0 0 0 0 49 100 100 100 42 0 0 391 AE/PE 0.13 0.16 0.38 0.42 0.70 1.00 1.00 1.00 1.00 1.00 0.54 0.12 9.02 ■: m) D D MD MD I HH H H HI D 214 dtiys

Station Name: Debre! Tabor

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 132 140 159 151 139 118 85 86 125 151 137 132 1555 r 1 18 53 52 86 250 518 483 183 62 25 16 1747 A. E. 1 18 53 52 86 118 85 86 125 151 36 16 827 W.D. 131 122 106 99 53 0 0 0 0 0 101 116 728 W.S. 0 0 0 0 0 32 433 397 58 0 0 0 S20 S.C. 0 0 0 0 0 100 0 0 0 -89 -11 0 0 S , 0 0 0 0 0 100 100 100 100 11 0 0 4 11 AE/PE 0.01 0.13 0.33 0.34 0.62 1.00 1.00 1.00 1.00 1.00 0 .26 0.12 31. 07 dm) V.D D MD MD I H H H H H MD D 184 days

Station Name: Debre Zeit

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 135 135 159 151 147 127 119 122 128 150 142 136 1651 r 11 26 4 4 63 50 89 226 226 108 25 6 4 878 A. E. 11 26 44 63 50 89 119 122 128 105 6 4 767 W.D. 124 109 115 88 97 38 0 0 0 45 136 132 834 W.S. 0 0 0 0 0 0 7 104 0 0 0 0 111 S.C. 0 0 0 0 0 0 100 0 -20 -80 0 0 0 S 0 0 0 0 0 0 100 100 80 0 0 0 280 AE/PE 0.08 0.19 0.28 0.42 0 .34 0.70 1.00 1.00 1.00 0.70 0.04 0.03 -25.40 (I n) V.D D MD MD MD IH HH I V.D V.D 153 days

Station Name: Degehabur

Parameter JAN FEB MAR APR MAY JUN •JUL AUG SEP OCT NOV DEC ANNUAL P.E. 153 137 152 117 130 127 123 135 136 128 130 134 • 2 r 10 0 29 64 71 27 3 12 32 52 12 1 3 3

!a .e . 10 0 29 64 71 27 3 12 32 52 12 1 ; W.D. 14 3 137 123 53 59 100 120 123 104 76 118 133 121)9 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 0 0 0 0 0 0 s 0 0 0 0 0 0 0 0 0 0 0 0 0 AE/PE 0.07 0.00 0.19 0.55 0.55 0.21 0.02 0.09 0.24 0.41 0.09 0..01 -48 .28 (Im) V.D V.D D II D V.D V.D D MD V.D V.D 61 days Table 3.2: Continued...computation of water budget

Station Name: Dembi Dollo

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 137 130 131 139 118 108 106 88 118 130 124 133 1462 r 23 15 57 68 213 158 194 179 129 87 33 . 19 1175 A.E. 23 15 57 68 118 108 106 88 118 130 90 19 940 W.D. 114 115 74 71 0 0 0 0 0 0 34 114 522 W.S. 0 0 0 0 0 45 88 91 11 0 0 0 235 S.C. 0 0 0 0 95 5 0 0 0 -43 -57 0 0 s 0 0 0 0 95 100 100 100 100 57 0 0 552 AE/PE 0. 17 0.12 0.44 0.49 1.00 1.00 1.00 1.00 1.00 1.00 0.73 0.14 -5.35 (Im) D D MD MD H H H HHHID 214 days

Station Name: Dessie

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 120 118 134 137 144 125 114 121 117 136 125 115 1506 T* 7 34 155 106 52 29 189 368 37 47 11 0 1035 A.E. 7 34 134 127 52 29 114 121 117 67 11 0 813 W.D. 113 84 0 10 92 96 0 0 0 69 114 115 693 W.S. 0 0 0 0 0 0 0 222 0 0 0 0 222 S.C. 0 0 21 -21 0 0 75 25 -80 -20 0 0 0 s 0 0 21 0 0 0 75 100 20 0 0 0 216 AE/PE 0.06 0.29 1.00 0.93 0.36 0.23 1 .00 1.00 1.00 0.49 0.09 0.00 -12.87 (Im) V.D MD H 1 MD D H H H MD V.D V.D 61/92 days

Station Name: Didessa

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 138 134 134 146 120 103 94 89 113 133 125 132 1461 r 4 2 4 74 176 249 291 225 200 118 40 4 1387

A.E. 4 2 4 74 120 103 94 89 113 133 125 4 865 W.D. 134 132 130 72 0 0 0 0 0 0 0 128 596 W.S . 0 0 0 0 0 102 197 136 87 0 0 0 522 S.C. 0 0 0 0 56 44 0 0 0 -15 -85 0 0 .c 0 0 0 0 56 100 100 100 100 85 0 0 541 AE/PE 0.03 0.01 0.03 0.51 1.00 1.00 1 .00 1. 00 1. 00 1.00 1.00 0.03 11.25 (Im) V.D V.D V.D I H H HH HH H V.D 24 4 days

Station Name: Dilla Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 144 135' 146 143 140 126 109 116 126 138 142 139 1604 r 36 50 101 179 155 103 113 96 166 154 70 41 1264 A.E. 36 50 101 143 140 126 109 116 126 138 138 41 1264 W.D. 108 85 45 CC 0 0 0 0 0 4 98 340 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 36 15 -23 4 -20 40 16 -68 0 0 S 0 0 0 36 51 28 32 12 52 68 0 . 0 279 AE/PE 0.25 0.37 0.69 1.00 1 .00 1.00 1.00 1.00 1.00 1.00 0.97 0.29 -12.72 (Im) MD I H HHH H H H I MD 275 days Table 3.2: Continued...computation of water budget

Station Name: Dire Dawa

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 132 124 142 137 146 131 131 139 132 137 133 135 1619 r 17 36 58 59 39 23 93 137 62 16 16 10 566 A. E. 17 36 58 59 39 23 93 137 62 16 16 10 566 W.D. 115 88 84 78 107 108 38 2 70 121 117 125 1053 W.S. 0 0 1 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 ' 0 0 0 0 0 0 0 0 0 0 0 s 0 0 0 0 0 0 0 0 0 0 0 0 0 a e /pe 0.13 0.29 0.41 0.43 0.27 0J8 0.71 0.99 0.47 0.12 0.12 0.07 -39.02 (Im) D MD MD MD MD D II MD DD V.D 62 cays

Station Name: Dixis

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC • ANNUAL P.E. 137 126 138 134 134 126 106 117 115 133 131 134 1531 r 15 30 66 59 98 62 194 225 , 103 51 16 10 929 A. E. 15 30 66 59 98 62 106 117 115 133 22 10 833 W.D. 122 96 72 75 36 64 0 0 0 0 109 124 698 W.S. 0 0 0 0 0 0 0 96 0 0 0 0 96 S.C. 0 0 0 0 0 0 88 12 -12 -82 -6 0 0 S 0 0 0 0 •0 0 88 100 88 6 0 0 282 AE/PE 0.11 0.24 0.48 0.44 0.73 0.49 1.00 1.00 1.00 1.00 0.17 0.07 -21.08 (Im) DDMD MD I MD HHHHD V.D 31/123 days

Station Name: Dodola

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 134 131 141 131 136 128 106 115 124 128 132 138 1544 r 35 35 53 84 47 71 146 159 111 59 26 17 843

A . E. 35 35 53 H4 47 71 106 115 124 128 28 17 843 W.D. 99 96 88 47 89 57 0 0 0 0 104 121 701 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 40 44 -13 -69 -2 0 0 s 0 0 0 0 0 0 40 84 71 2 0 0 197 AE/PE 0.26 0.27 0.38 0.64 0.35 0.55 1.00 1.00 1.00 1.00 0.21 0.12 -27.24 (Im) MD MD MD I MD I HHH H D D 30/153 days

Station Name: Felege Neway

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC AIJNUAL

P.E. 139 137 132 139 118 113 116 104 119 135 138 145 1535 r 46 76 126 244 209 157 221 140 159 154 140 31 1703 A . E. 46 76 126 139 118 113 116 104 119 135 138 131 1361 W.D. 93 61 6 0 0 0 0 0 0 0 0 14 174 W.S. 0 0 0 5 91 44 105 36 40 19 2 0 342 S.C. 0 0 0 100 0 0 0 0 0 0 0 -100 0 S 0 0 0 100 100 100 100 100 100 100 100 -0 800 AE/PE 0.33 0.55 0 . 95 1.00 1.00 1.00 1.00 1.00 1 .00 1.00 1.00 0.90 15.48 (Im) MD I IH HHH H HH H I 334 days

54 Table 3.2: C ^ ^ ^ ^ ^ ^ ^ ^ ’omputation of water budget

Station N a m e P M R ^ ^ ^ ^ ^

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 130 1.28 135 134 148 121 100 102 114 138 145 135 1530 r 27 35 - 46 53 64 89 321 391 144 45 15 2 1232

A.E. 27 35 46 53 64 89 100 102 114 138 22 2 792 W.D. 103 93 89 81 84 32 0 0 0 0 123 133 738 W.S. 0 0 0 0 0 0 121 289 30 0 0 0 440 S.C. 0 0 0 0 0 0 100 0 0 -93 -7 0 0 S 0 0 0 0 0 0 100 100 100 7 0 0 307 AE/P3 0.21 0.27 0.34 0.40 0.43 0.74 1.00 1.00 1.00 1.00 0.15 0.01 -0.18 (Im) D MD MD MD MD IHH H H D V.D 153 days

Station Name:' Feleklik Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 129 127 135 134 148 122 100 102 114 138 145 134 1528 r 0 13 45 32 38 145 315 304 145 9 29 50 1125 A.E. 0 13 45 32 38 122 100 102 114 109 29 50 754 W.D. 129 114 90 102 110 0 0 0 0 29 116 84 774 W.S . 0 0 0 0 0 0 138 202 31 0 0 0 371 S.C. 0 0 0 0 0 23 77 0 0 -100 0 0 0 S 0 0 0 0 0 23 100 100 100 0 0 0 323 AE/PE 0.00 0.10 0. 33 0.24 0.26 1.00 1.00 1.00 1.00 0.79 0.20 0 .37 -6.11 (Im) V.D D MD D MD HH H H ID MD 153 days

Station Name: Fincha

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 134 128 137 150 126 105 87 89 114 136 131 129 1466 r 3 11 19 38 90 170 286 223 132 70 87 12 1141 A.E. 3 11 19 38 90 105 87 89 114 136 121 12 825 W.D. 131 117 118 112 36 0 0 0 0 0 10 117 641 W.S. 0 0 0 0 0 0 164 134 18 0 0 0 316 S.C. 0 0 0 0 0 65 35 0 0 -66 -34 0 0 S 0 0 0 0 0 65 100 100 100 34 0 0 399 AE/PE 0 .02 0.09 0 .14- 0.25 0.71 1.00 1.00 1.00 1 .00 1.00 0.92 0.09 -4.68 (Im) V.D V.D D MD I H H H H HI V.D 214 days

Star.ion Name: Gambella

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 137 127 131 139 115 106 107 88 114 127 124 133 1448 r 3 11 23 48 125 180 233 • 253 112 84 36 23 1131

A.E. 3 11 23 4 8 115 106 107 88 114 127 91 23 856 W.D. 134 116 108 91 0 0 0 0 0 0 33 110 592 W.S. 0 0 0 0 0 0 110 165 0 0 0 0 275 S.C. 0 0 0 0 10 74 26 0 -2 -43 -55 0 10 S 0 0 0 0 10 84 100 100 98 55 0 0 447 hE/PE 0.02 0.09 0.18 0.35 1.00 1 . 00 1.00 1 .00 1.00 1.00 0.73 0.17 -5.54 (Im) V.D V.D D MD H H H H H H I D 214 days

55 Table 3.2: Continued... computation of water budget

Station Name: Gewane

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC AN.'JUAL P.E. 127 132 136 144 14 9 132 134 136 137 151 144 1>0 1652 r 8 26 68 59 40 6 54 78 24 5 0 5 373 • A.E. 8 26 68 59 40 6 54 78 24 5 0 5 373 W.D. 119 106 68 85 109 126 80 58 113 146 144 125 .279 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 0 0 0 0 0 0 S 0 0 0 0 0 0 0 0 0 0 0 0 0 AE/PE 0.06 0.20 0.50 0.41 0.27 0.05 0.40 0.57 tf.18 0.03 0.00 0.04 -46.45 (Im) V.D D MD MD V.D MD ID V.D V.D V.D 31 rlays

Station Name: Gidmi

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 90 89 96 141 120 109 106 89 117 132 123 132 L344 r 61 7 51 91 201 267 212 128 67 220 76 8 1389 A.E. 61 7 51 91 120 109 106 89 117 132 123 61 .067 W.D. 29 82 45 50 0 0 0 0 0 0 0 71 277 W.S. 0 0 0 0 0 139 106 39 0 38 0 0 322 S.C. 0 0 0 0 81 19 0 0 -50 88 -47 -53 38 S 0 0 0 0 81 100 100 100 50 100 53 0 584 AE/PE 0.68 0 .08 0.53 0.65 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.46 11.59 Im) I V.D IIHHH H H H H MD 31/275 days

Station Name: Gidole

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 150 144 132 142 127 133 115 110 126 136 140 147 :602 r 47 51 155 140 182 98 10 47 193 93 89 8 1113 A.E. 47 ■51 132 142 127 133 51 47 126 136 113 8 1113 W.D. 103 93 0 0 0 0 64 63 0 0 27 •13 9 489 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 23 -2 55 -35 -41 0 67 -43 -24 0 0 S 0 0 23 21 76 41 0 0 67 24 0 0 252 AE/PE 0.31 0 .35 1.00 1.00 1.00 1.00 0.44 0.43 1.00 1.00 0.81 0.05 -18.31 (Im) MD MD H H H H MD MD H H I V.D 122/91 cays

Station Name: Gimbi Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 140 136 133 148 121 103 97 89 117 133 123 132 1472 r 10 6 37 79 213 336 341 372 364 154 32 6 1950 A.E. 10 6 37 79 121 103 97 89 117 133 123 15 930 W.D. 130 130 96 69 0 0 0 0 0 0 0 117 542 W.S. 0 0 0 0 0 225 244 283 247 21 0 0 1020 S.C. 0 0 0 0 92 8 0 0 0 0 -91 -9 0 S 0 0 0 0 92 100 100 100 100 100 9 0 601 AE/PE 0.07 0.04 0.28 0.53 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.11 47.20 (Im) V.D V.D MD I HHH HH H H D 244 days

56 Table 3.2: Continued... computation of water budget

Station Name: Goba

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 133 125 139 122 125 120 117 119 111 98 113 129 1451 r 22 39 59 141 119 63 90 73 123 112 65 6 912

A . E. 22 39 59 122 125 JZ.6 90 73 111 98 91 6 912 W.D. 111 86 80 0 0 44 27 46 0 0 22 123 539 W.S . 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 19 -6 -13 0 0 12 14 -26 0 0 S 0 0 0 19 13 0 0 0 12 26 0 0 70 AE/PE 0.17 0.31 0.42 1.00 1.00 0.63 0.77 0.61 1.00 1.00 0.81 0.05 -22.29 (Im) 1 D MD MD H HI I I H H I V.D 24 4 days

Station Name: Gode Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL r. E. 152 148 166 146 133 125 122 135 145 134 140 148 1694 r 0 5 19 91 69 1 0 0 7 59 46 3 300 A. E. 0 5 19 91 69 1 0 0 7 59 46 3 300 W.D. 152 143 147 55 64 124 122 135 138 75 94 145 1394 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 0 0 0 0 0 0 S 0 0 0 0 0 0 0 0 0 0 0 0 0 AE/PE 0.00 0 .03 0.11 0.62 0.52 0.01 0.00 0.00 0.05 0.44 0.33 0.02 -49.37 (Im) V.D V.D D I I V.D V.D V.D V.D MD MD V.D 61 days

Stat ion Name: Goha Tsiyon Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 129 126 135 136 137 117 100 101 114 138 142 135 1510 r 9 22 104 115 120 166 415 401 189 24 9 7 1581

A. E. 9 22 104 115 120 117 100 101 114 124 9 7 942 W.D. 120 104 31 21 17 0 0 0 0 14 133 128 568 W.S. 0 0 0 0 0 0 264 300 75 0 0 0 639 S.C. 0 0 0 0 0 49 51 0 0 -100 0 ' 0 0 S 0 0 0 0 0 49 100 100 100 0 0 0 349 AE/PE 0.07 0. 17 0.77 0.85 0.88 1 .00 1.00 1 .00 1.00 0.90 0.06 0.. 05 19.75 (Im) V.D DIIIHH HH I V.D V.D 24 5 days

Station Name: Gonder Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.Et 140 143 166 156 141 131 87 86 132 154 142 138 1616 r 5 6 19 41 85 157 326 303 119 53 25 14 1153 A. E. 5 6 19 41 85 131 87 86 132 140 25 14 771 W.D. 135 137 147 115 56 0 0 0 0 14 117 124 845 W.S. 0 0 0 0 0 0 165 217 0 0 0 0 382 S.C. 0 0 0 0 0 26 74 0 -13 -87 0 0 0 S 0 0 0 0 0 26 100 100 87 0 0 0 313 AE/PE 0.04 0.04 0.11 0.26 0.60 1. 00 1.00 1.00 1 .00 0.91 0.18 0.10 -7.74 (Im) V.D V.D D MD I H H H HID D 184 days

57 Table 3.2: Continued...computation of water budget

Station Name: Gore

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNI'AL P.E. 136 129 138 139 115 105 103 93 114 131 124 132 1**59 r 37 45 102 132 235 339 335 335 349 183 102 46 2. 40 A.E. 37 45 102 132 115 105 103 93 114 131 124 124 1. 25 W.D. 99 84 36 7 0 0 0 0 0 0 0 8 234 W.S. 0 0 0 0 20 234 232 242 235 52 0 0 1015 S.C. 0 0 0 0 100 0 0 0 0 0 -22 -78 0 S 0 0 0 0 100 100 100 100 100 100 78 0 578 AE/PE 0.27 0.35 0.74 0. 95 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.94 59.95 (Im) MD MD I T HH HHHHHI 306 days

Station Name: Gorgora

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 133 142 165 155 139 123 87 90 134 147 139 136 1590 r 1 2 2 25 68 187 294 251 123 27 8 2 990 A.E. 1 2 2 25 68 123 87 90 134 116 8 2 658 W.D. 132 140 163 130 71 0 0 0 0 31 131 134 932 W.S. 0 0 0 0 0 0 171 161 0 0 0 0 332 S.C. 0 0 0 0 0 64 36 0 -11 -89 0 0 0 S 0 0 0 0 0 64 100 100 89 0 0 0 353 AE/PE 0.01 0.01 0.01 0.16 0.49 1. 00 1.00 1.00 1.00 0.79 0.06 0.01 -14.29 (Im) V.D V.D V.D D MD H HHH I V.D V.D 153 cays

Station Name: Grawa Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 128 127 142 128 127 109 105 106 122 142 133 135 2504 r 14 31 79 122 154 64 103 168 117 52 26 5 935 A.E. 14 31 79 122 127 91 103 106 122 109 26 5 935 W.D. 114 96 63 6 0 18 2 0 0 33 107 130 569 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 27 -27 0 62 -5 -57 0 0 0 S 0 0 0 0 27 0 0 62 57 0 0 0 146 AE/PE 0.11 0.24 0.56 0.95 1.00 0.83 0.98 1.00 1.00 0.77 0.20 0.04 -22 .70 Im) D DI I ' H I IHHI D V.D 245 days

Station Name: Guder * Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 147 135 160 147 148 133 112 125 144 162 149 149 :711 r 15 34 71 57 100 150 221 216 110 37 19 11 .049

A.E. 15 34 71 57 100 133 112 125 144 111 19 11 932 W.D. 132 101 89 90 48 0 0 0 0 51 130 138 779 W.S. 0 0 0 0 0 0 26 91 0 0 0 0 117 S.C. 0 0 0 0 0 17 83 0 -26 -74 0 0 0 S 0 0 0 0 0 17 100 100 74 0 0 0 291 AE/PE 0.10 0.25 0.44 0.39 o VO GO 1.00 1.00 1.00 1.00 0.69 0.13 0.07 -20.48 (Im) D MD MD MD I H HH HID V.D 184 Jays

58 Table 3.2: Continued...computation of water budget

Station Name: Hagere Mariam

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 146 137 147 142 130 128 112 116 128 134 136 141 1597 r 13 27 75 161 182 49 43 47 55 136 45 14 847 A . E 13 27 75 142 130 120 43 47 55 134 47 14 847 . W.D. 133 110 72 0 0 8 69 69 73 0 89 127 750 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 19 52 -71 0 0 0 2 -2 0 0 S 0 0 0 19 71 0 0 0 0 2 0 0 92 AE/PE 0.09 0.20 0.51 1.00 1.00 0.94 0.38 0.41 0.43 1.00 0.35 0.10 -28.18 (Im) V.D D I H HI MD MD MD H MD V.D 122/31 days

Station Name: Hagere Selam

Parameter JAN FEB MAR APR MAY JUN ' JUL AUG SEP OCT NOV DEC ANNUAL P.E 142 135 , 146 143 140 123 109 120 127 138 143 138 1604 r 70 78 74 118 130 116 139 136 125 112 56 23 1177

A. E 70 78 74 118 130 116 109 120 127 138 74 23 1177 W.D 72 57 72 25 10 7 0 0 0 0 69 115 427 W.S 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 30 16 -2 -26 -18 0 0 S 0 0 0 0 0 0 30 46 44 18 0 0 138 AE/PE 0.49 0.58 0.51 0.83 0.93 0.94 1.00 1. 00 1.00 1. 00 0.52 0.17 -15.97 (Im) MD I I I I IH HH H I D 303 days

Station Name: Hamero Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 149 144 158 138 145 132 131 137 146 136 146 142 1704 r 6 1 18 78 93 10 1 2 25 39 7 1 281 A. E. 6 1 18 78 93 10 1 2 25 39 7 1 281 W.D. 143 143 140 60 52 122 130 135 121 97 139 <141 1423 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 0 0 0 0 0 0 s 0 0 0 0 • 0 0 0 0 0 0 0 0 0 AE/PE 0.04 0.01 0.11 0.57 0.64 0.08 0.01 0.01 0.17 0.29 0.05 0.01 -50 .11 (Im) V.D V.D D I I V.D V.D V.D D MD V.D V.D 61 days

Station Name: Harer

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 141 128 144 139 140 128 126 125 127 140 133 134 1605 r 19 26 63 86 93 61 90 111 82 51 8 6 696

A. E. 19 26 63 HP 93 61 90 111 82 51 8 6 696 W.D. 122 102 81 53 47 67 36 14 45 89 125 128 909 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 0 0 0 0 0 0 S 0 0 0 0 0 0 0 0 0 0 0 0 0 AE/PE 0 .13 0.20 0.44 0.62 0.66 0.48 0.71 0.89 0.65 0.36 0.06 0.04 -33.98 (Im) D D MD I I MD I II MD V.D V.D 61/92 days •

59 Table 3.2: Continued... computation of water budget

oi-atStation iuu nameName: ; Hosainanuaa.LI Id

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 140 130 151 138 146 119 99 108 117 138 144 138 1.568 r 24 32 93 .153 111 126 156 188 149 62 20- 25 1.139 A.E. 24 32 93 138 126 119 99 108 117 138 44 25 1 063 W.D. 116 98 58 0 20 0 0 0 0 0 100 113 505 W.S. 0 0 0 0 0 0 0 44 32 0 0 0 76 S.C. 0 0 0 15 -15 7 57 43 0 -76 -24 0 7 S 0 0 0 15 0 7 64 100 100 24 0 0 310 AE/PE 0.17 0.25 0.62 1.00 0.86 1.00 L. 00 1.00 1.00 1.00 0.31 0.18 -14.48 Im) D D IH I H HH H H MD D 245 ctays

Station Name: Humera

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 137 144 170 172 168 164 158 139 153 161 143 140 1849 r 0 0 0 9 29 93 189 197 86 10 3 0 616 A.E. 0 0 0 9 29 93 158 139 153 32 3 0 616 W.D. 137 144 170 163 139 71 0 0 0 129 140 140 1233 W.S. 0 0 0 0 0 0 0 0 0 0 0 • 0 0 S.C. 0 0 0 0 0 0 31 58 -67 -22 0 0 0 S 0 0 0 0 • 0 • 0 31 89 22 0 0 0 142 AE/PE 0.00 0.00 0.00 0.05 0.17 0.57 1.00 1.00 1.00 0.20 0.02 0.00 -40.01 (Im) V.D V.D V.D V.D D IH H H D V.D V.D 122 days

Station Name: Indaselase

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 147 140 173 174 173 159 127 110 146 163 146 136 1794 r 3 1 3 23 51 130 303 291 125 28 4 0 962

A.E. 3 1 3 23 51 130 127 110 146 107 4 0 705 W.D. 144 139 170 151 122 29 0 0 0 56 142 136 1089 W.S. 0 0 0 0 0 0 76 3/81 0 0 0 0 257 S.C. 0 0 0 0 0 0 100 0 -21 -79 0 0 0 S 0 0 0 0 0 0 100 100 79 0 0 0 279 AE/PE 0.02 0.01. 0.02 0.13 0.29 0.82 1.00 1.00 1.00 0.66 0.03 0.00 -22.10 (Im) V.D V.D V.D D MD I H H H I V.D V.D 153 days

Station Name: I tang

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 137 127 130 143 115 108 108 91 114 126 122 134 1455 r 1 7 12 51 144 94 197 191 100 98 69 1 965 A.E. 1 7 12 51 115 lC-8 108 91 114 126 122 6 961 W.D. 136 120 118 92 0 0 0 0 0 0 0 128 594 W.S. 0 0 0 0 0 0 4 100 0 0 0 0 104 S.C. 0 0 0 0 29 -14 89 0 -14 -28 -53 -5 4 S 0 0 0 0 29 15 100 100 86 58 5 0 393 AE/PE 0.01 0.06 0.09 0.36 1.00 1.00 1. 00 1.00 1.00 1.00 1.00 0.04 -17.35 (Im) V.D V.D V.D MD H HHHHH H V.D 214 days

60 Table 3.2: Continued... computation of water budget

Station Name: Koffele

Parameter JAN FEB MAR APR 'MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 14 3 136 147 143 140 119 111 125 126 133 137 139 1599 r 40 60 144 140 89 108 147 151 152 92 56 25 1204 A. E. 40 60 144 140 89 108 111 125 126 133 103 25 1204 W.D. 103 76 3 3 51 11 0 0 0 0 34 114 395 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 36 ?6 26 -41 -47 0 0 S 0 0 0 0 0 0 36 62 88 47 0 0 233 AE/PE 0.28 0.44 0.98 0.utj0.6-3 0.91 1.00 1.00 1.00 1 .00 0.75 0.13 -14.82 (Im) MD MD I III H HH HI D 275 days

Station Name: Koka

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 139 138 157 154 153 144 136 136 138 149 144 133 1721 r 17 25 52 49 36 63 220 190 102 27 14 12 807 A.E. 17 25 52 49 36 63 136 136 138 91 14 12 769 W.D. 122 113 105 105 117 81 0 0 0 58 130 121 952 W.S. 0 0 0 0 0 0 0 38 0 0 0 0 38 S.C. 0 0 0 0 0 0 84 16 -36 -64 0 0 0 S 0 0 0 0 0 0 84 100 64 0 0 0 248 AE/PE 0.12 0.18 0.33 0.32 0.24 0.44 1.00 1.00 1.00 0.61 0.10 0.09 -30.98 (Im) DD MD MD D MD H HHI V.D V.D 12? days

Station Name: Koladiba Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 137 143 166 156 141 128 87 87 133 150 141 i39 1608 r 2 2 12 36 59 202 263 245 99 60 27 3 1011 A.E. 3 2 12 36 59 128 87 87 133 126 27 3 703 W.D. 134 141 154 120 82 0 0 0 0 24 114 136 905 W.S. 0 0 0 0 0 0 150 158 0 0 0 0 308 S.C. 0 0 0 0 0 74 26 0 -34 -66 0 0 0 S 0 0 0 0 0 74 100 100 66 0 0 0 340 AE/PE 0.02 0.01 0.07 0.23 0.42 1.00 1.00 1.00 1.00 0.84 0.19 0.02 -14.61 (Im) V.D V.D V.D D MD HH HH I D V.D 153 days

Station Name: Kombolcha

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 121 119 134 136 144 126 115 123 118 136 127 115 1514 1 29 26 80 85 56 31 264 258 117 36 22 16 1020 A.E. 29 26 8 0 85 56 31 115 123 118 135 22 16 836 W.D. 92 93 54 51 88 95 0 0 0 1 105 99 678 W.S. 0 0 0 0 0 0 49 135 0 0 0 0 184 S.C. 0 0 0 0 0 0 100 0 -1 -99 0 0 0 S 0 0 0 0 0 0 100 100 99 0 0 0 299 AE/PE 0.24 0.22 0.60 0.63 0.39 0 .25 1.00 1.00 1.00 0.99 0.17 0*. 14 -14.72 (Im) D DII MD DH HHI DD 61/123 days

61 Table 3.2: Continued... computation of water budget

Station Name: Jij iga

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 143 125 143 134 143 125 126 124 128 139 133 135 L598 r 12 30 49 170 98 63 83 134 102 52 21 10 824 A.E. 12 30 49 134 134 63 83 124 112 52 21 10 824 W.D. 131 95 94 0 9 62 43 0 16 87 112 125 774 W.S. 0 0 0 0 0 0 0 0 ' 0 0 0 0 0 S.C. 0 0 0 36 -36 0 0 10 -10 0 0 0 0 S 0 0 0 36 0 0 0 10 0 0 0 0 46 AE/PE 0.08 0.24 0.34 1.00 0. 94 0.50 0.66 1.00 0.88 0.37 0.16 0.07 -29.06 Im) V.D D MD H I I IH I MD D V.D 183 days

Station Name: Jimma

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 129 118 135 133 129 112 99 106 115 133 126 130 1 465 r 31 56 94 139 163 214 219 213 180 91 57 46 1503 • A.E. 31 56 94 133 129 112 99 106 115 133 115 46 1169 W.D. 98 62 41 0 0 0 0 0 0 0 11 84 296 W.S. 0 0 0 0 0 42 120 107 65 0 0 0 334 S.C. 0 0 0 6 34 66 0 0 0 -42 -58 0 6 S 0 0 0 6 40 100 100 100 100 58 0 • 0 504 AE/PE 0.24 0.47 0.70 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.91 0.35 10.68 (Im) D MD I H . H HHH HH I MD 275 cays

Station Name: Kebri Dehar

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 165 148 172 161 145 147 141 159 168 144 148 161 1359 r 1 6 15 119 72 2 1 0 10 117 49 8 400

A.E. 1 6 15 119 72 2 1 0 10 117 49 8 400 W.D. 164 142 157 42 73 145 140 159 158 27 99 153 1159 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 0 0 0 0 0 0 s 0 0 0 0 0 0 0 0 0 0 0 0 0 AE/PE 0.01 0.04 0.09 0.74 0.50 0.01 0.01 0.00 0.06 0.81 0.33 0.05 -47.09 (Im) V.D V.D V.D I MD V.D V.D V.D V.D I MD V.D 30/31 days

Station Name: Keren Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NO.V DEC ANNUAL

P.E. 132 134 147 161 155 137 104 85 119 147 126 127 1574 r 0 0 2 8 23 46 110 127 50 4 3 0 573 A.E. 0 0 2 8 23 46 104 85 98 4 3 0 >73 W.D. 132 134 145 153 132 91 0 0 21 143 123 127 1201 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 6 42 -48 0 0 0 0 S 0 0 0 0 0 0 6 48 0 0 0 0 54 AE/PE 0.00 0.00 0.01 0.05 0.15 0.34 1.00 1.00 0.82 0.03 0.02 0.00 -45.78 Cm) V.D V.D V.D V.D D MD HHI V.D V.D V.D 92 day3

62 Table 3.2: Continued...computation of water budget

Station Name.- Korisci

Parameter JAN FfcB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL .• I P.E. 147 144 136 142 122 127 115 109 126 131 134 141 1574 r- 16 54 83 170 126 71 26 42 50 88 62 17 805

A.E. 16 54 83 142 122 103 26 42 50 88 62 17 805 W.D. 131 90 53 0 0 24 89 67 76 43 72 124 769 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 28 4 -32 0 0 0 0 0 0 0 S 0 0 0 28 32 0 0 0 0 0 0 0 60 AE/PE 0.11 0.38 0.61 1.00 1.00 0.81 0.23 0.39 0.40 0.67 0.46 0.12 -29.31 (Im) D MD I H H I D MD MD I MD D 122/31 days

Station Name: Kulumsa

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 128 128 133 128 137 132 111 122 107 134 136 136 1532 r 26 43 95 67 92 81 136 142 107 45 16 7 857 A.E. 26 43 95 67 92 81 111 122 107 90 16 7 857 W.D. 102 85 38 61 45 51 0 0 0 44 120 129 675 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 25 20 0 -45 0 0 0 S 0 0 0 0 0 0 25 45 45 0 0 0 115 AE/PE 0.20 0.34 0.71 0.52 0.67 0.61 1.00 1 .00 1.00 0.67 0 .12 0.05 -26 .44 (Im) D MD I I . I I H HHID V.D 245 days

Station Name: Kurmuk

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 139 132 130 153 134 111 110 94 125 136 132 128 1524 r 0 1 4 21 80 160 164 174 139 106 9 2 860

A.E. 0 1 4 21 80 111 110 94 125 136 79 2 763 W.D. 139 131 126 132 54 0 0 0 0 0 53 126 761 W.S. 0 0 0 0 0 0 .3 80 14 0 0 0 97 S.C. 0 0 0 0 0 49 51 0 0 -30 -70 0 0 S 0 0 0 0 0 49 100 100 100 70 0 0 419 AE/PE 0.00 0.01 0.03 0.14 0.60 1.00 1.00 1 .00 1.00 1.00 0.60 0.02 -23.60 (Im) V.D V.D V.D D I HH HH HI V.D 214 days

Station Name: Kuyera Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 140 134 150 134 138 126 110 123 120 134 142 143 1594 r 25 45 70 79 87 95 127 111 137 64 32 3 875 A.E . 25 45 70 79 87 95 110 123 120 86 32 3 875 W.D. 115 89 80 55 51 31 0 0 0 48 110 140 719 W.S. C 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 17 -12 17 -22 0 0 0 S 0 0 0 0 0 0 17 5 22 0 0 0 44 AE/PE 0. 18 0.34 0.47 0.59 0.63 0.75 1.00 1. 00 1.00 0.64 0.23 0.02 -27.06 (Im) D MD MD II IH HH I D V.D 214 days

63 Table 3.2: Continued...computation of water budget

Station Name: Langano

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANl.'UAL

P.E. 138 135 153 149 148 137 130 129 115 143 141 138 : 656 r 24 6 3 45 72 106 129 91 81 18 21 32 628 A.E. 24 6 3 45 72 106 129 91 81 18 21 32 628 W.D. 114 129 150 104 76 31 1 38 34 125 120 106 : 028 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 0 0 0 0 0 0 S 0 0 0 0 0 0 0 0 0 0 0 0 0 AE/PE 0.17 0.04 0.02 0.30 0.49 0.77 0.99 0.71 0.70 0.13 0.15 0.23 -37.25 Im) D V.D V.D MD MD I I I I DD D 122 c ays

Station Name: Maychew

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 135 142 166 162 173 156 141 137 145 161 142. 139 1799 r 7 23 43 79 49 26 171 192 70 36 26 32 754 A.E. 7 23 43 79 49 26 141 137 145 46 26 32 754 W.D. 128 119 123 83 124 130 0 0 0 115 116 107 1045 W.S. 0 0 0 0 0 0 0 0 0 0 0 ' 0 0 S.C. 0 0 0 0 0 0 30 55 -75 -10 0 0 0 S 0 0 0 0 . 0 0 30 85 10 0 0 0 125 AE/PE 0.05 0.16 0.26 0.49 0.28 0.17 1.00 1.00 1.00 0.29 0.18 0.23 -34.85 (Im) V.D D MD MD MD DH HH MD DD 92 cays

Station Name: Mekele

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 144 143 167 165 177 158 139 133 159 158 138 140 1821 r 3 11 24 41 24 27 216 203 28 2 5 2 586 A.E. 3 11 24 41 24 27 139 133 128 2 5 2 539 W.D. 141 132 143 124 153 131 0 0 31 156 133 138 1282 W.S. 0 0 0 0 0 0 0 47 0 0 0 0 47 S.C. 0 0 0 0 0 0 77 23 -100 0 0 0 0 S 0 0 0 0 0 0 77 100 0 0 0 0 177 AE/PE 0 . 02 0.08 0.14 0.25 0.14 0.17 1.00 1.00 0.81 0.01 0.04 0.01 -39.66 (Im) V.D V.D DDD D HH I V.D V.D V.D 92 days

Station Name: Melka Werer Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 130 129 149 145 146 140 132 133 137 149 138 135 1563 r 3 40 72 74 40 28 117 111 56 5 12 1 559 A.E. 3 40 72 74 40 28 117 111 56 5 12 1 559 W.D. 127 89 77 71 106 112 15 22 81 144 126 134 1104 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 0 0 0 0 0 0 S 0 0 0 0 0 0 0 0 0 0 0 0 0 AE/PE 0.02 0.31 0.48 0.51 0.27 0,20 0.89 0.83 0.41 0.03 0.09 0.01 -39.83 (Im) V.D MD MD I MD D I I MD V.D V.D V.D 30/62 days

64 Table 3.2: Continued...computation of water budget

Station Name: Mendi

Parameter JAN FEB MAR APR MAY JUN JUL AUG .SEP OCT NOV DEC ANNUAL P.E. 139 135 129 151 124 106 104 91 122 133 122 130 1486 r 3 4 20 61 170 289 291 310 334 121 36 3 1642 A.E. 3 4 20 61 124 106 104 91 122 133 122 5 895 W.D. 136 131 109 90 0 0 0 • 0 0 0 0 125 591 W.S. 0 0 0 0 0 129 187 219 212 0 0 0 747 S.C. 0 0 0 0 46 54 0 0 0 -12 -86 -2 0 S 0 0 0 0 46 100 100 100 100 88 2 0 536 AE/PE 0.02 0.03 0.16 0.40 1.00 1 .00 1.00 1.00 1.00 1.00 1 .00 0..04 26.41 (Im) V.D V.D D MD H H H HHH H V.D 214 days

Station Name: Metehara

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 134 131 152 145 149 140 133 139 137 143 135 136 1674 r 22 32 39 31 43 28 108 138 39 31 11 4 526 A.E. 22 32 39 31 43 28 108 138 39 31 11 4 526 W.D. 112 99 113 114 106 112 25 1 98 112 124 132 1148 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 0 0 0 0 0 0 0 s 0 0 0 0 0 0 0 0 0 0 0 0 0 AE/PE 0.16 0.24 0.26 0.21 0.29 0 .20 0.81 0.99 0.28 0.22 0.08 0.03 -41.15 (Im) D D MD D MD D I I MD D V.D V.D 62 days

Station Name: Metema

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 133 138 158 160 153 139 141 120 136 149 140 136 1703 r 1 0 0 2 67 162 208 213 181 45 4 0 883 A.E. 1 0 0 2 67 139 141 120 136 145 4 . 0 755 W.D. 132 138 158 158 86 0 0 0 0 4 136 136 948 W.S. 0 0 0 0 0 0 0 83 45 0 0 0 128 S.C. 0 0 0 0 0 23 67 33 0 -100 0 0 23 S 0 0 0 0 0 23 90 100 100 0 0 0 313 AE/PE 0.01 0.00 0.00 0.01 0.44 1.00 1.00 1.00 1 .00 0.97 0.03 0.00 -25.88 (Im) V.D V.D V.D V.D MD H H H H I V.D V.D 153 days

Station Name: Metu !<-' * ** 6 J ?. Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL

P.E. 137 130 138 139 118 104 102 93 114 131 123 131 1460 r 32 39 79 98 216 259 307 277 297 141 67 25 1837

A.E. 32 39 79 96 118 104 102 93 114 131 123 69 1102 W.D. 105 91 59 41 0 0 0 0 0 0 0 62 358 W.S. 0 0 0 0 0 153 205 184 183 10 0 0 735 S.C. 0 0 0 0 98 2 0 0 0 0 -56 -44 0 S 0 0 0 0 98 100 100 100 100 100 44 642 AE/PE 0.23 0.30 0.57 0.71 1.00 1.00 1.00 1.00 1. 00 1.00 1.00 0.53 35.63 (Im) L MD I •I H HH H HH HI 306 days

65 Table 3.2: Continued...computation'of water budget

Station Name: Ziway

Parameter JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL P.E. 142 138 157 154 152 143 136 136 122 149 145 143 1717 r 20 37 58 64 80 95 164 132 108 51 .3 2 814 A.E. 20 37 58 64 80 95 136 136 122 61 3 2 814 W.D. 122 101 99 90 72 48 0 0 0 88 142 141 903 W.S. 0 0 0 0 0 0 0 0 0 0 0 0 0 S.C. 0 0 0 0 0 0 28 -4 -14 -10 0 0 0 S 0 0 0 0 0 0 28 24 10 0 0 0 62 AE/PE 0.14 0.27 0.37 C . 42 0.53 0.66 1.00 1.00 1.00 0.41 0.02 0.01 -31.56 (Im) DMD MD MD I I HHH MD V.D V.D 153 days Table 3.3: Water budget, climatic classification and length of growing days.

R.F P.E W.S W.D Index Index Index LGP Station Name (mm) (mm) (mm) (mm) (Im) Type (la) (Ih) Sub-D

Abiy Adi 793 1808 200 1215 -29.26 D 11.1 M 122 days Abobo 1132 1444 163 475 -8.45 Cl 11.3 M 244 days Adaba 796 1543 8 755 -28.84 D 0.5 S 123 days Addis Ababa 1154 1538 276 660 -7.80 Cl 17.9 M 214 days Adigrat 581 1850 0 1269 -41.16 E 0.0 S 62 days Adi Keyih 484 1852 0 1368 -44.32 E 0.0 S 62 days Adi Ugri 573 1864 0 1291 -41.56 B 0.0 S 92 days Add_s Zemen 1065 1570 405 910 -8.98 Cl 25.8 L 153 days Ado^ a 1036 1546 48 558 -18.55 Cl 3.1 S 153/91 days Adwcj 763 1848 82 1167 - 33 ; 45 D 4.4 S 123 days Aga ro 1537 1465 400 328 13.87 C2 22 .4 M 306 days Akaki 871 1590 138 857 -23 .66 D 8.7 S 30/153 days Akordat 300 1587 0 1287 -48.66 E 0.0 s 92 days Alaba Kalito 913 1644 0 731 -26.68 D 0.0 s 92/92 days Alamata 54 3 1730 0 1187 -41.17 E 0.0 s 30/31 days Alem Ketema 1151 1536 444 829 -3.48 Cl 28 .9 L 153 days Alemava 838 1654 0 816 -29.60 D 0.0 * S 214 days Ambo 1087 1522 234 669 -11.00 Cl 15.4 M 214 days Arba Minch 783 1620 0 837 -31.00 D 0.0 S 61/61 days Ar jo 2103 1462 1014 373 54 .05 B 25.5 M 275 days Assela 1303 1614 216 527 -6 .21 Cl 13 .4 M 24 5 days Asendabo 1193 1471 211 489 -5.60 Cl 14 .3 M 24 5 days Astrera 537 1841 0 1304 -42.50 E 0.0 S 62 days • As sosa 1275 1512 337 574 -0.49 Cl 22.3 L 2jL'4 ’days Atnago 2212 1476 1097 361 59.65 B 24 .5 M 275 days Awassa 944 1592 0 648 -24 .42 D 0.0 S 214 days-- Awash 615 1597 0 982 -36.89 D 0.0 S 92 days Aykel 1180 1632 353 805 -7.97 Cl 21.6 L 184 days Bahir Dar 1522 1533 724 735 18 .46 C2 47.9 L 214 days Bako 1193 1518 328 653 -4 .20 Cl 21.6 L 184 days Bako Jinka 1342 1537 20 215 -7.09 Cl 1.3 S 334 days Bambese 1344 1498 500 654 7.18 C2 43.7 L 2 l f days Bati 872 1524 80 732 -23.57 D 5.2 S 5 9/123" days Bedelle 1924 1465 907 448 43.56 B 30.6 M 275 days Begi 1360 1490 416 546 5.93 C2 36 .6 L 214 days Bekoj i 1012 1478 80 54 6 -16 .75 Cl 5.4 S 24 5 days Biiate 780 1607 0 827 -30.88 D 0.0 s 122/61 days Bonga 1789 1464 504 179 27.09 B 12 .2 s 334 days Bulki 1838 1527 425 186 20.52 B 12 .2 s 306 days Bure 1282 1447 317 482 1.92 C2 33.3 L 244 days Bur j i 1015 1581 0 566 -21.48 D 0.0 s 122/91 days Butaj ira 1020 1643 0 623 -22 .75 D 0.0 s 24 5 days Chagni 1687 1502 808 623 28 . 91 B 41.5 L 214 days Chefa 1042 1517 203 678 -13 .43 Cl 13.4 M 61/123 days Chencha 1481 1621 102 242 -2.67 Cl 6.3 S 303 days Dabat - 928 1733 299 1104 -20.97 D 17.3 M 123 days Dangla 1460 1517 626 683 14 .25 C2 45.0 L 214 days Debre Berhan 890 1606 225 941 -21.15 D 14 .0 M 12 3 days Debre Markos 1348 1457 492 601 9.02 C2 41.2 L 214 days Debre Tabor 1747 1555 920 728 31.07 B 46.8 L 184 days Debre Zeit 878 1651 111 884 -25.40 D 6.7 S 153 days Degehabur 313 1602 0 1289 -48 .28 E 0.0 S 61 days De:nbi Dollo 1175 1462 235 522 -5.35 Cl 16.1 M 214 days Dessie 1035 1506 222 693 -12.87 Cl 14 .7 M 61/92 days Didessa 1387 1461 522 596 11.25 C2 40.8 L 244 days Dilla 1264 1604 0 340 -12 .72 Cl 0.0 S 275 days

75 Table 3.3 cont: Water budget, climatic classification and length of growing da/s

s = = sa B S = :s s B n = s = = = = ss a B 3 S = s = = ss c s s s s s s a s E s s s s a s c s s = ss a B S S = s = ss = ss = SE £ s s s s B a B a ts as* R.F P.E W.S W.D Index Index Index LGP Station Name (mm) (mm) (mm) (mm) (Im) Type (la) (Ih) Sub-D

Dire Dawa 566 1619 0 1053 -39.02 D 0.0 S 62 days Dixis 929 1531 96 698 -21.08 D 6.3 S 31/123 ■ ays Dodola 843 1544 0 701 -27.24 D 0.0 S 30/153 <.ays Felege Neway 1703 1535 342 174 15.48 C2 11.3 S 334 day; Fitche 1232 1530 440 738 -0.18 Cl 28 .8 L 153 days Feleklik 1125 1528 371 774 -6.11 Cl 24 .3 L 153 day! Fincha 1141 1466 316 641 -4 .68 Cl 21.6 L 214 day! Gambella 1131 1448 275 592 -5.54 Cl 19.0 M 214 day! Gewane 373 1652 0 1279 -46 .45 E 0.0 S 31 days Gidmi 1389 1344 322 277 11.59 C2 20.6 M 31/275 c ays Gidole 1113 1602 0 489 -18.31 Cl 0.0 S 122/91 cays Gimbi 1950 1472 1020 542 47.20 B 36.8 L 24 4 day.1 Gob a 912 1451 0 539 -22 .29 D 0.0 S 244 dayi Gode 300 1694 0 1394 -49.37 E 0.0 S 61 days Goha Tsiyon 1581 1510 639 568 19.75 C2 37.6 L 24 5 days Gonder 1153 1616 382 845 -.7.74 Cl 23 .6 L 184 dayi; Gore 2240 1459 1015 234 59.95 B 16.0 S 306 dayi Gorgora 990 1590 332 932 -14.29 Cl 20.9 L 153 dayj; Grawa 935 1504 0 569 -22.70 D 0.0 S 245 days Guder 1049 1711 117 779 -20.48 D 6.8 S 184 days Hagere Mariam 847 1597 0 750 -28.18 D 0.0 S 122/31 cays Hagere Selam 1177 1604 0 427 -15.97 Cl 0.0 S 303 days Hamero 281 1704 0 1423 -50.11 E 0.0 S 61 days Harer 696 1605 0 909 -33.98 D 0.0 S 61/92 days Hosaina 1139 1568 76 505 -14.48 Cl 4.8 s 245 days Humera 616 1849 0 1233 -40.01 E 0.0 s 122 days Indaselase 962 1794 257 1089 -22.10 D 14.3 M 153 days I tang 965 14b5 104 594 -17.35 Cl 7.1 S 214 days Jijiga 824 1598 0 774 -29.06 D 0.0 s 183 days Jimma 1503 1465 334 296 10.68 C2 20.2 M 275 days Kebri Dehar 400 1859 0 1459 -47.09 E 0.0 S 30/31 days Keren 373 1574 0 1201 -45.78 E 0.0 S 92 days Koffele 1204 1599 0 395 -14.82 Cl 0.0 S 275 days Koka 807 1721 38 952 -30.98 D 2.2 S 123 days Koladiba 1011 1608 308 905 -14 .61 Cl 19.2 M 153 days Kombolcha 1020 1514 184 678 -14.72 Cl 12 .2 M 61/123 days Konso 805 1574 0 769 -29.31 D 0.0 S 122/31 days Kulumsa 857 1532 0 675 -26.44 D 0.0 s 245 days Kurmuk 860 1524 97 761 -23.60 D 6.4 s 214 days Kuyera 875 1594 0 719 -27.06 D 0.0 s 214 days Langano 628 1656 0 1028 -37.25 D 0.0 S 122 days Maychew 754 1799 0 1045 -34.85 D 0.0 S 92 days Mekele 586 1821 47 1232 -39.66 D 2.6 s 92 days Melka Werer 559 1663 0 1104 -39.83 D 0.0 S 30/62 da/s Mendi 1642 1486 747 591 26.41 B 39.8 L 214 days Metehara 526 1674 0 1148 -41.15 E 0.0 S 62 days Metema 883 1703 128 948 -25.88 D 7.5 s 153 days Metu 1837 1460 735 358 35.63 B 24.5 M 306 days Mierab Abaya 752 1624 0 872 -32.22 D 0.0 S 214 days Migdaloloa 730 1667 0 937 -33.73 D 0.0 S 122/61 days Massawa 201 1712 0 1511 -52.96 E 0.0 s 0 days Mo j o 866 1705 100 939 -27.18 D 5.9 s 31/123 days Mot a 1561 1489 724 652 22.35 B 43.8 L 214 days Moyale 710 1616 0 906 -33.64 D 0.0 S 91/61 da/s Munesa 1295 1641 96 442 -10.31 Cl 5.9 S 303 days Nakfa 229 1739 0 1510 -52.10 E 0.0 S 0 days Nazreit 891 1725 56 890 -27.71 D 3.2 S 153 days

76 Table 3.3 cont: water budget, climatic classification and length of growing days.

s a s a s a S B = 3 = S 3 S S = S B C = :B 3 = = =3■ B S B B S E = s s = : R.F P.E W.S W.D Index Index Index LGP Station Name (mm) (mm) (mm) (mm) (Im) Typ3 (la) (Ih) Sub-D

Negelle 793 1525 45 777 -27.62 D 3.0 • S 91/61 days Nejo 1720 1416 852 548 36.95 B 38.7 L 214 days Nekemte 2147 1455 1147 455 60.07 B 31.3 M 275 days Ogelcho 661 1659 0 998 -36.09 D 0.0 S 31/122 days Pokow 1070 1447 182 559 -10.60 Cl 12.6 M 214 days Robie 760 1632 0 872 -32.06 D 0.0 S 31/123 days Sheraro 750 1823 111 1184 -32.88 D 6. 1 s 92 days Sodo 1339 1557 164 382 -4 .19 Cl 10.5 M 275 days Tekeze Bridge 855 1764 235 1144 -25.59 D 13.3 M 153 days Tepi 1555 1453 406 304 15.39 C2 20.9 M 306 days Teseney 331 1816 0 1485 -49.06 E 0.0 S 62 days Ticho 1256 1482 0 226 -9.15 Cl 0.0 S 303 days Weliso 1276 1526 447 697 1.89 C2 45.7 L 214 days Wendo 1538 1598 260 320 4 .26 C2 20.0 M 275 days Wendo Genet 1128 1674 0 546 -19.57 Cl 0.0 S 275 days Wonj i 775 1725 4 954 -32.95 D 0.2 s 123 days Woldiya 1248 1586 348 686 -4.01 Cl 21.9 L 61/123 days Wush Wush 1775 1464 459 148 25.29 B 10.1 S 334 days Yabelo 663 1575 0 912 -34 .74 D 0.0 S 92/31 days Yirga Alem 1187 1613 0 426 -15.85 Cl 0.0 S 24 5 days Yirga Chefe 1867 1607 529 269 22 .87 B 16.7 M 306 days Yubdo 1454 1479 57 8 603 14 .62 C2 40.8 L 214 days Zege 1519 1549 792 822 19.29 C2 53.1 L 18 3 days Ziway 814 1717 0 903 -31.56 D 0.0 S 153 days

P.E = Potential Evpotranspiration (mm,) ; r = Rainfall (mm,) ; S.C = Soil Charge Change (mm,) S. = Soil Charge (mm,) A.E = Actual Evapotranspiration (mm,) W.D = Water Deficit (mm,) W.S = Water Surplus (mm,) LGP = Length of growing days

77 Reference LOWRY P.W, 1972. Compendium of lecture notes in climatology for class IV Met.Per Sonel WMO.No.327.

Hu, H.C. and LIM, J.T, 1983. Solar and Net radiation in peninsular Malaysia. (Journal of Climatology. Vol.3., N o .3 Chichester.' Newyork: John Willey and Sons.

Trewartha, G.T, 1954. Introduction to climate, 3rd edition, Me Graw- HiLL Book Co. Pant, P.S.,and Rwandusya, 1971. -Climate of East AFRICA. Technical Memorandum No.18. E.A.Met.Dep. NAIROBI.