5 CDBM OUTPUTS UNDER CLIMATE CHANGE

SCENARIOS AND DIFFERENT IRRIGATION

MANAGEMENT SCENARIOS

RESULTS AND DISCUSSION

129

The basic CDBm data are the monthly averages, which have been calculated from

the daily values for many years, including total annual precipitation, and mean,

maximum, and minimum temperatures. Reference evapotranspiration has been

calculated using two different methods: Thornthwaite (1948) and Hargreaves

methods Hargreaves (1985). Climatic indices related to agricultural suitability can

also be calculated from CDBm data (for example: HUi, ARi, GS, MFi, PCi and AKi).

5.1 ANDALUSIA

5.1.1 CURRENT CLIMATE DATA Climatic observations and calculations of 62 climate stations (Table 5-1),

distributed throughout the eight provinces of Andalusia, have been used to get a

good picture of the local climate and the spatial variation. In each province, there

are a number of climatic stations and one climatic station has been selected to

represent the climate condition in each province, choosing the most

representative stations by considering which station has climatic parameter

values closest to the mean of all stations of each individual province (Table 5-1).

For example: in the case of precipitation, the spatial variation can be very large

within a province, and in many provinces the station with the highest annual

precipitation receives more than double the amount of rainfall of the lowest

reported value for the same province (Table 5-2).

Table 5-2 represents the lowest and the highest annual precipitation for each

province, and the precipitation for each station selected as representative for that

entire province. The value of the representative station is not always the exact

median, because selection was based on other parameters too.

The lowest annual minimum temperature has been reported as 3.9 oC, measured

in GR03, while the highest minimum temperature was recorded in CA02 (14.9 oC).

The highest reported value for the annual maximum temperature was recorded in

MA04 (26.0 oC) and the lowest annual maximum temperature in Al07 with 17.3

oC.

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Table 5-1. Climatic stations and their location within Andalusia (city and province). The

stations marked with an asterisk have been selected as the representative station for

their respective provinces.

Province Station code Location Natural region Almeria AL01 Bacares Almanzora-Alto AL02 Huércal Overa Almanzora-Bajo AL03 Laujar Mont. Andarax-Gabor AL04 Berja Campo-Dalias AL05 Almeria Campo-Níjar AL06 Lubrin Campo-Tabernas AL07* Vélez Rubio Los-Velez AL08 Canjayar Rio-Nacimento Cadiz CA01 Pantano Campiña CA02 Tarifa Campo-Gibraltar CA03 San Fernando Costa CA04* Medina Sidonia Janda-Aljibe CA05 Jerez B,A Rincón-Jerez CA06 Ubrique Sierra Cordoba CO01 Lucena Campiña-Alta CO02 Cordoba Campiña-Baja CO03* Hornachuelos Hornachuelos CO04 Pozobalnco Pedroches CO05 Pantano Puente Nuevo Sierra-Morena CO06 Pantano Izanajar Sierra-sur CO07 Posadas Vega Granada GR01 Pantano Bermejales Alhama GR02* Lanjarón Alpujarras GR03 Caniles Baza GR04 Motril Costa GR05 Exfiliana Guadix GR06 Huéscar Huescar GR07 Iznalloz Iznalloz GR08 Loja Esc. Loja GR09 Montefrío Montefrío GR10 Padul Valle-Lecrín GR11 Granada Vega Huelva HU01* Valverde Andevalo-Occidental HU02 Cabezas Rubias Andévalo-Oriental HU03 Escacena Condado-Campiña HU04 Bodegones Condado-literal Hu05 Huelva Costa HU06 Ayamonte Marismas HU07 Aracena Sierra-Morena Jaen JA01 Linares Campiña-Norte JA02* Torredonjimeno Campiña-Sur JA03 Pantano de Guadalmena Condado JA04 Ubeda La-Loma JA05 C. Santo Cristo Mágina JA06 Cazorla Sierra-Cazorla JA07 Pantano de Jandula Sierra-Morena JA08 Siles Sierra-Segura JA09 Jaen Sierra-Sur Malaga MA01 Alfarnate Antequera MA02 Vélez Málaga Axarquia MA03 Malaga Costa MA04* Tolox P.V Guadalhorce MA05 Gaucín Serranía-Ronda Sevilla SE01 Carmona Alcores SE02 Torrequemada Aljarafe SE03 Ecija Campiña SE04* Osuna Estepa SE05 Aznalcázar Marismas SE06 Pantano del Pintado Sierra-Morena SE07 Morón B. A Sierra-Sur SE08 Sevilla Aeropuerto Terrazas SE09 Sevilla Tablada Vega

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Table 5-2. Minimum, maximum and representative precipitation values in Andalusia

provinces.

Province P, minimum(mm) P, representative (mm) P, maximum (mm)

Almería *210 339 597

Cádiz 580 810 1066

Cordoba 575 626 680

Granada 232 508 654

Huelva 488 775 1022

Jaen 452 614 1155

Malaga 519 1014 *1171

Seville 514 616 750

Average 446 709 887

Table 5-3. Climate classification of Andalusian provinces (and the average for the whole

of Andalusia) according to De Martonne (1926).

Province Tm, oC P, mm Aridity index Climate type

Almería 14.9 335.1 14.6 Semi-arid

Cádiz 14.8 672.9 27.2 Semi-humid

Cordoba 14.4 555.0 22.7 Mediterranean

Granada 15.0 483.0 19.3 Semi-arid

Huelva 14.2 679.2 28.1 Humid

Jaen 15.3 615.1 24.3 Semi-humid

Malaga 13.2 742.0 32.0 Humid

Seville 17.8 604.7 21.7 Mediterranean

Average 14.7 585.9 23.7 Mediterranean

Although climate type (according to the De Martonne classification; Table 3-3

page 63) was classified as Mediterranean at the regional scale, it varied from

semi-arid to humid among provinces (Table 5-3).

5.1.2 CLIMATE CHANGE SCENARIOS The monthly climatic parameters of the eight representative climatic stations in

Andalusia have been presented graphically for different climate change scenarios:

the current situation, and projections for 2040, 2070, and 2100 (Figure 5-1). A

temporal variation has been observed for all the stations in the Andalusia region.

Over time, precipitation decreases in 2070 and 2100 scenarios, but this decrease

might be preceded by a small increase around 2040. On the other hand, the mean

temperature and potential evapotranspiration will increase in the projections for

2040, 2070, and 2100 (Figure 5-1).

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Figure 5-1. CDBm output for eight representative metrological stations in the Andalusia

region under different climate change scenarios. Tm: temperature mean in oC, P:

precipitation in mm, ET0: reference evapotranspiration in mm, ARi: aridity index

expressed as the number of months per year in which the reference evapotranspiration

exceeds the precipitation.

RESULTS AND DISCUSSION

133

Together, the decreasing precipitation and the increasing temperature and

evapotranspiration will result in longer and more severe aridity in the projected

scenarios, as can be seen from the growing yellow areas in Figure 5-1.

As illustrated in Figure 5-2, ET0 and ARi will increase under future climatic

scenarios (2040, 2070, and 2100) at all the representative climatic stations, while,

on the other hand, HUi will decrease. While these trends apply to all eight

stations, they are not all affected to the same extent, as can be seen in the

different ranking orders for the different parameters. In addition, climatic indexes

that are related to land degradation, such as PCi, MFi and Aki, have been

calculated by using CDBm.

Figure 5-2. Development of reference evapotranspiration (A, ET0; B, HUi; C, ARi; D, PCi;

E, MFi; and F, AKi) over time in the projections for 2040, 2070 and 2100 for the eight

representative climatic stations. Some lines may be hidden by others in some cases.

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134

PCi index values range from 8.3 (when precipitation does not vary largely among

different months) to 100 (when precipitation is concentrated in only one month).

PCi appears to be an appropriate statistical concept for comparing different

stations and different scenarios of climate change. As shown in Figure 5-2, PCi will

increase under future climatic scenarios (2040, 2070, and 2100) in comparison to

the current scenario, while, on the other hand, MFi and AKi values will decrease in

these climate scenarios. Therefore, even though the total quantity of precipitation

will decrease in the future, precipitation is thought to be more concentrated in

time.

In general, global climate change can accelerate the hydrological cycle. Warmer

air temperature favors evaporation. A warmer atmosphere can hold more water

vapor, so more water is available to fall back to soil when it rains or snows. As a

result, extreme precipitation events can become more frequent and intense,

which can lead to more severe flooding (Trenberth, 2011).

As is shown in the Appendix, climate station CA02 has the lowest values in ET0

where it reaches to 716, 767, 810, 900 mm under different climatic scenarios

(actual, 2040, 2070, 2100 respectively) on the other hand GR05 has the highest

values with 1348, 1434, 1483, 1594 under different climate scenarios respectively.

The ARi has the lowest values in JA08 with 4, 5, 6, and 6 under current, 2040, 2070

and 2100 climatic scenarios, respectively. Similarly, HUi varied between 0.3, 0.3,

0.2, and 0.2 in AL02 to 1.7, 1.5, 1.2, and 1.1 in JA06.

Annual climate indexes related to land degradation for the current climate (1961-

2000) and for projections for the future: 2040, 2070, and 2100, as is illustrated in

the Appendix. Those calculated indexes include Precipitation concentration index

(PCi); modified Fournier index (MFi); and Arkley index (AKi). GR03 has the lowest

values in PCi where it reaches to 9, 10, 9 and 10 mm under different climatic

scenarios (current, 2040, 2070, and 2100, respectively). On the other hand, SE05

has the highest values with 13, 14, 14 and 14 under the different climate

scenarios respectively. The lowest MFi values can be found in AL02 with 32, 26,

25, and 21 under the climatic scenarios current, 2040, 2070, 2100 respectively,

while the highest values are reported for MA05 with 149, 152, 131 and 123 under

the different climatic scenarios respectively. AKi varied between 50, 39, 42, 33 in

AL07 and the much higher values of 812, 733, 560, and 505 in JA06, again

correspondingly to the different climate scenarios.

RESULTS AND DISCUSSION

135

5.2 EL-FAYOUM

5.2.1 CURRENT AND FUTURE CLIMATE SCENARIO According to the IPCC-2007 report, the study area will likely be affected by

increasing air temperature and decreasing precipitation in a systematic manner.

The predicted scenario of climatic conditions of the study area, needed to study

this, was worked out using results from IPCC, 2007a. The annual precipitation is

expected to decrease from 11 (current) to 8 mm/year in 2080. To compare the

current climate with the projected climate in 2080, we chose temperature data

for June, as this is the hottest month (Figure 5-3). One extremely hot day can be

enough to reduce yield or even kill an entire crop. That is why geneticists and

plant breeders are working to produce new crop varieties that are better adapted

to the expected climatic changes. In addition, climatic change is projected to have

a significant impact on the amount of irrigation water entering El-Fayoum

province, which in this turn will affect soil degradation and agricultural

productivity.

Figure 5-3. Different temperature parameters in El-Fayoum Province for the month of

June under the current situation and the projected scenario (2080).

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Figure 5-4. Annual temperature parameters in El-Fayoum province under current

conditions and in the projection for 2080.

Figure 5-3 shows the predicted increase of minimum, mean, and maximum

temperature in 2080 compared with the climatic conditions in 2009. The

projection for the climatic parameters for June follows the same trend, but at

higher temperatures (Figure 5-4).

5.2.2 IRRIGATION MANAGEMENT SCENARIOS The scenarios for the development of irrigation conditions of the study area was

derived from historical data: the irrigation water data from 20 years (1989 - 2009)

and climatic data from 44 years (1962 - 2006). Many factors besides temperature

affect agricultural productivity, and these can be expected to change in the future;

irrigation management is one of them. To study the effect of changes on the

amount of irrigation water input, and climate change, four different scenarios

were studied:

� Scenario 1: The situation remains the same: The total cultivated area is

1566 km2 (ASRT, 2009) while the total amount of irrigation water reaching

the depression is 2.3 x 103 Hm

3. This is the equivalent of 1427 mm/year

(100% of current input).

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137

� Scenario 2: The irrigation input decreases by 25%; this hypothetical

scenario results in aridity due to water shortage.

� Scenario 3: The irrigation input decreases by 50%; this hypothetical

scenario results in more severe aridity due to water shortage.

Figure 5-5. CDBm output for four different climate and irrigation management scenarios

in El-Fayoum province. Tm: mean temperature, oC; P: precipitation (equivalent), mm;

ET0: reference evapotranspiration, mm; ARi: number of months in which the reference

evapotranspiration exceeds the precipitation.

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Under this scenario, 31.5% of the total irrigation water is needed to

mitigate the expected aridity.

� Scenario 4: This scenario represents the current climatic condition

(precipitation: 11 mm/year), but without any input of irrigation water

from the Nile. Under this scenario, the whole area is characterized by a

hyper-arid condition and true drought will severely affect agriculture.

The differences between the four different irrigation management scenarios in

the current situation and the projection for 2080 are shown in Figure 5-4.

The differences between the current values and the projections for 2080 for the

maximum and minimum temperature, and the annual climatic indexes are shown

in Table 5-4.

Through climate change, some parameters will increase: temperature,

evapotranspiration, and the aridity index, while the precipitation, the Humidity

index, and the Arkley index will decrease (Figure 5-6). This means that in the

period around the year 2080, the decrease in natural rainfall, combined with

higher temperatures and a possible reduction in input of irrigation water will

result in drought being the main problem for agricultural land use.

Table 5-4. Annual climate indexes related to the current climate (1962-2006) and the

projection for 2080, under different irrigation scenarios (S1, S2, S3, and S4). Calculated

by CDBm-El-Fayoum. Tmax: maximum temperature in oC; Tmin: minimum temperature,

in oC; ET0 (H): reference evapotranspiration according to Hargreaves (1985), in mm; Hui:

humidity index; ARi: Aridity index; GS: growing season, in months; AKi: Arkley index.

Climatic scenarios Tmax Tmin ET0 (H) HUi ARi GS AKi

Current climate

S1 29.9 14.6 1560 1.29 2 12 330.4

S2 29.9 14.6 1420 1.04 6 12 211.2

S3 29.9 14.6 1420 0.64 7 12 80.0

S4 29.9 14.6 1420 0.01 12 12 2.0

Projection for 2080

S1 33.5 18.2 1686 1.08 6 12 245.1

S2 33.5 18.2 1533 0.88 7 12 172.7

S3 33.5 18.2 1533 0.54 9 12 80.0

S4 33.5 18.2 1533 0.01 12 12 2.0

RESULTS AND DISCUSSION

139

The ranking of these four scenarios in terms of higher contamination risks

(according to the Arkley index, from lowest to highest risk) will be S1, S2, S3 and

S4. Data from Table 5-5 show that the average, maximum and minimum

temperature in the study area are 21.7 oC, 29.8

oC, 14.4

oC, respectively, and the

total annual precipitation is 8.5 mm. These data were analyzed by integrating the

obtained climatological data into the CDBm database. The land evaluation

approach was applied, based upon two hypothetical climate change scenarios: i)

Using climatic data observation over 44 years (1962–2006) and ii) Using data

based on projected changes in air temperature and precipitation for northern

Africa under the highest future emission trajectory for the 2080s (IPCC, 2007a).

Figure 5-6. Difference between current situation and 2080-projection for ET0), HUi, ARi

and AKi under four irrigation management scenarios (S1, S2, S3 and S4).

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Table 5-5. Summary of agro-meteorological data from El-Fayoum station, during the

1962 - 2006 period. Tm: mean temperature. Tmax: maximum temperature, oC; Tmin:

minimum temperature, oC; P: precipitation, mm; Pmax: daily maximum precipitation in

each month, mm; Pd: Days with precipitation. ET0(T): reference evapotranspiration, mm,

as calculated by Thornthwaite method. ET0(H): reference evapotranspiration as

calculated by Hargreaves method.

Months Tm Tmax Tmin P Pmax Pd ET0(T) ET0(H)

January 12.7 20.3 6.1 1.5 1.2 1 19.2 70.3

February 14.2 22.3 6.9 1.6 1.4 1 24.6 89.1

March 17.2 25.4 9.6 2.6 2 1 46.9 113.5

April 21.4 30.2 13.2 0.4 0.4 1 84.3 140.3

May 25.2 33.7 16.9 0.1 0.1 1 139.7 159.5

June 28.3 36.8 20 0 0 0 143.7 172

July 28.9 37.2 21.3 0 0 0 147.8 168.3

August 28.6 36.9 21.5 0 0 0 147.8 159.9

September 26.8 34.7 19.9 0 0 0 135 138.6

October 23.8 31.6 17.2 0.2 0.2 1 101.5 116.6

November 18.8 26.2 12.6 0.9 0.6 1 51.3 86.2

December 14 21.8 7.7 1.2 0.9 1 24.3 70.3

Annual 21.7 29.8 14.4 8.5 6.6 8 1066.1 1484.5

Table 5-6. Summary of agro-meteorological data from El-Fayoum station, during the more recent

period (1998-2009), converting the input of irrigation water to the equivalent in precipitation. Tm:

mean temperature. Tmax: maximum temperature, oC; Tmin: minimum temperature,

oC; Im: mean

irrigation input, mm; Imax: maximum irrigation input; mm P: precipitation, mm. ET0(T): reference

evapotranspiration, mm, as calculated by Thornthwaite method. ET0(H): reference

evapotranspiration, mm, as calculated by Hargreaves method. By converting irrigation input to

precipitation, the number of days with precipitation per month (Pd) equals the total number of

days per month.

Months Tm Tmax Tmin Im Imax ET0(T) ET0(H)

Jan 12.8 20.3 6.2 42.6 61.3 22.1 95.5

Feb 14.3 22.1 7.1 95.4 110.8 26.5 107.2

Mar 17.1 25.1 9.7 116.4 133.3 46.2 119.2

Apr 21.4 30.1 13.3 114.4 121.6 79.5 136.4

May 25.3 33.7 17.0 124.5 135.1 125.3 140.5

Jun 28.5 37.0 20.2 148.2 153.6 147.8 145.8

Jul 29.0 39.0 21.5 161.0 168.9 151.7 152.3

Aug 28.9 37.0 21.7 157.0 163.7 147.8 150.4

Sep 26.9 34.8 20.1 134.7 143.0 135.0 147.5

Oct 23.9 31.4 17.3 121.9 124.8 108.4 134.9

Nov 18.9 26.4 12.6 113.5 115.3 57.9 114.1

Dec 14.2 21.7 7.9 98.1 114.2 28.8 97.4

Annual 21.8 29.9 14.6 1427.7 1546.2 1077.1 1541.3

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Table 5-7. Index of climate type according to De Martonne (1926), El-Fayoum Province.

Climatic scenarios Tm, oC Water supply, mm Aridity index Climate type

S1 21.7 1427 45.0 Very humid

S2 21.7 1142 36.0 Very humid

S3 21.7 713 22.5 Mediterranean

S4 21.7 8.5 0.3 Arid

By converting the input of irrigation water to the equivalent in precipitation, it

was possible to calculate different parameters in CDBm for irrigated, as well as

non-irrigated, conditions, as shown in Table 5-5 and Table 5-6.

Taking into account these changes, Table 5-7 provides the future climatic

classification types, according to the classification of De Martonne (1926), of El-

Fayoum province under the different irrigation scenarios in comparison to rainfall

concentrations. The resulting climate classifications range from arid to very humid

depending on irrigation water supply: arid under 8.5 mm and zero irrigation input

and very humid if the irrigation input remains the same as currently, and is

considered as the precipitation equivalent of 1427 mm.