Sowing date determinants for Sahelian rainfed agriculture in the context of agricultural policies and water management

Land Use Policy 52 (2016) 316–328

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Land Use Policy journal homepage: www.elsevier.com/locate/landusepol

Sowing date determinants for Sahelian rainfed agriculture in the context of agricultural policies and water management Aline Bussmann a , Nadir Ahmed Elagib a,∗ , Manar Fayyad b , Lars Ribbe a a b

Institute for Technology and Resources Management in the Tropics and Subtropics (ITT), Cologne University of Applied Sciences, 50679 Cologne, Germany Water, Energy and Environment Center (WEEC), University of Jordan, Jordan

a r t i c l e

i n f o

Article history: Received 16 December 2014 Received in revised form 31 August 2015 Accepted 9 December 2015 Keywords: Sowing date Rainfall variability Rainfed agriculture Integrated water resources management (IWRM) Integrated coping strategies Agricultural policies Sorghum Sahel Sudan

a b s t r a c t Inappropriate sowing date constitutes a major reason for crop failure and low yields in the African Sahel region. Deriving from experience in Sudan, this study endeavors to: (1) identify the drivers of farmers’ choice of sowing date for rainfed agriculture, (2) suggest a best-suited guide for farmers in their decision making concerning sowing dates and (3) recommend integrated coping strategies that consider technical and socioeconomic dimensions and regional scales. In this study, sorghum is considered as a strategic crop for food security in the country. The result of data processing based on two climatic methods over the period 1971–2010 has determined the onset of rainfall between the last week of June and the first week of July. An early but safe sowing date in terms of less subsequent dry spells is 08 July. Accordingly, the probability for the establishment of the rainy season is high and the probability of occurrence of following dry spells is lowest. However, this date appears to be earlier than the sowing date commonly practiced by farmers which is usually in the end of July, but sometimes even in the beginning of August. The field survey analysis highlights several non-climatic factors that have significant influence on sorghum cultivation in general and sowing date definition specifically. These include limited agricultural extension service, weeds, basic machinery and low input of fertilizers, herbicides and pesticides. Weed presence and slow and long soil preparation procedures often cause farmers to delay sowing operations, consequently leading to yield reduction. Current coping strategies can serve as a base to advance long-term agricultural policies that guarantee sufficient institutional support and create an enabling environment for knowledge transfer and technical solutions. The results of this research constitute part of an integrated long-term adaptation strategy that has to be developed to improve agricultural activities under climate risk. © 2015 Elsevier Ltd. All rights reserved.

1. Introduction A main characteristic of rainfed agricultural systems is their vulnerability to climate variability. In rainfed agricultural areas, the amount of effective rainfall determines the agricultural production, and the seasonal rainfall variability leads to changing production (Bewket, 2009; Bannayan et al., 2011). In fact, the performance of a given rainy season for an optimal crop growth does not only depend on the overall total amount of rainfall, but also requires an adequate distribution of the rains during the year. The cause of crop failure is often intense rainfall events separated by long dry spells leading to an unequal intra-seasonal distribution (Camberlin and Diop, 2003; Bewket, 2009). The optimal sowing date may normally

∗ Corresponding author. E-mail addresses: [email protected], [email protected] (N.A. Elagib). http://dx.doi.org/10.1016/j.landusepol.2015.12.007 0264-8377/© 2015 Elsevier Ltd. All rights reserved.

occur within a ‘sowing window’ starting with the onset and closing when a sowing date would be too late to achieve a reasonable yield. While successful early sowing can produce a crop which may have a higher yield, later sowing reduces the risk of early crop failures. Farmers face a decision of whether or not to sow when sufficient rainfall accumulates to increase soil moisture content (Raes et al., 2004). One of the most extreme examples in the world where the aforementioned issues are inherently problematic is the African Sahel. In order to optimize rainfed crop production under increased rainfall variability, different studies in the semi-arid part of the Sahel focused on the definition of the growing season (Jolliffe and Sarria-Dodd, 1994; Camberlin and Diop, 2003; Odenkunle, 2004). ‘Growing season’ was defined by Odenkunle (2004) as the period of the year during which spatial and temporal rainfall distribution characteristics are suitable for crop germination, establishment, and full development. The existence of relationships between the

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317

Fig. 1. The focal problem of rainfed agriculture in Eastern Sudan and its causes.

start, end and length of growing season, and the number of wet days per growing season is critical for planning agricultural activities. In the West African Sahel, the detection of the onset date of the wet season is a crucial factor in deciding when to plant crops, as planting too early may lead to crop failure whereas significant delay may reduce the growing season and hence the crop yield (Dodd and Jolliffe, 2001). Marteau et al. (2009) found no observable systematic, spatially consistent advance or delay of the onset across the whole western and central Sahel. In a typical semi-arid Sahelian country (Niger) where pearl millet is grown, a field survey of on-farm sowing practices in addition to simulated and observed yield/biomass at the end of the season concluded with two findings (Marteau et al., 2011). First, ≈22% of total sowings failed due to dry spells. Second, sowing too early does not necessarily maximize the simulated yield because of the high risk of protracted dry spells following this early start. 2. Problem statement and objectives The importance of early stage of crop calendar to crop yield in the Sahel region of Sudan has been confirmed by Elagib (2013, 2014, 2015). In this regard, eastern Sudan is an illustrative case study to draw from the experience of the rainfed mechanized agricultural sector of El Gedaref1 State, which has a high potential to contribute to the national food stock and support foreign exchange earnings. Sorghum production dominates the agricultural economy but physio-geographic, social and institutional factors are causing severe limitations (see Fig. 1). Sorghum can tolerate dry spells at the end of the growing season well but depends highly on a constant and sufficient water supply at the beginning of the growing season (Bewket, 2009; Elagib, 2015). Sowing practices for sorghum differ widely among farmers in El Gedaref State. Some farmers have their own rain gauges for measurement in order to be independent from weather forecasts and limited data availability. Others use traditional techniques to define a date of sufficient soil moisture. For

1

One can also refer to Al Qadarif, Al-Gedarif or Gedarif.

example, they wait until cracks in the soil close due to the swelling process of clay vertisols in wet conditions (Respondent 2, Table 2, 2012). Monoculture, limited crop rotation and neglected fallow periods lead to a decline in soil moisture. Other consequences are increased run-off and topsoil erosion, eventually leading to land degradation. This has, in turn, further negative impacts on agricultural productivity (UNEP, 2007). Exact onset definition, and thus, sowing date determination is a crucial but not a single component of a complex problem leading to low agricultural productivity in this area. From the foregoing literature review, it can be emphasized that the farmers’ choice of an appropriate sowing date is one important adaptation and management strategy to climate change and variability for the sub-Saharan countries (Waha et al., 2013). Taking El Gedaref State in eastern Sudan as a case study, the goal of this study is threefold. The first one is to identify applicable determinants, which can provide farmers in the rainfed agriculture sector of the Sahel guidance for defining the sowing date of the yearly cropping calendar. The second goal is to suggest a safe sowing date for rainfed sorghum from rainfall data. These determinants can then be considered relevant for adjusting to current effects of climate variability and, moreover, can present one step towards successful adaptation strategies under future climatic change conditions. The third goal is to suggest coping strategies for variable rainfalls in an integrative approach on a regional scale in consideration of the scientific, socio-economic and technology elements, including the maximum use of rainfall and techniques that can minimize water loss. Most of these strategies interact with the sowing date. It is argued that this study is especially vital in view of the robust agreement across climate models which project a delayed and shorter rainy season of the semi-arid African Sahel (Biasutti and Sobel, 2009; Chen et al., 2013).

3. Physio-geographical characteristics of the study area El Gedaref State is located in eastern Sudan, bordered by Ethiopia to the east, Sennar State to the south, Gezira State and Khartoum to the west and Kassala State to the north (Fig. 2). The state extends

318

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Table 1 Selected methods for the determination of growing season onset.

Method applied Objective Data requirements Description

Example of case study

Method 1 (Ndomba, 2010)

Method 2 (Ati et al., 2002)

Percentage cumulative mean rainfall (Ilesanmi 1972); rainfall curves Define planting date that will coincide with onset of rainfall Daily rainfall amount; temperature Planting dates are obtained by using the onset of rain dates; rainfall curves

Rainfall–evapotranspiration relationship (Kowal and Knabe, 1972); dry spell factor (Salinger et al., 2000) Determination of onset date of growing season

Semi-arid to humind regions of Tanzania

Daily rainfall; temperature; calculation of ETo Onset date is defined as 10 days in which rainfall is equal to or greater than 25 mm, but where the subsequent 10-day rainfall total is ≥0.5 of the ETo . This definition is combined with a dry spell criterion of <7 days within the next month Semi-arid regions of Northern Nigeria

ETo is the reference evapotranspiration.

4. Methodology 4.1. Climatic methods for sowing date definition Different climate-based methods have been used in the semiarid region of Africa to determine indicators for the definition of the sowing date of sorghum. The results were then compared with traditional sowing dates in order to point out possible mismanagement in the cropping calendar. Additionally, information on several factors other than climatic ones received through interviews and field observations was used to provide a holistic view about the sowing date determinants. Primarily, two climate-based methods to define sowing dates are selected in this study and put in relation to the local conditions of soil, crop type and crop water requirements (see Table 1). The main criteria for choosing the methods are the application of available data and comparable climatic conditions. Furthermore, the chosen methods are recent complementary approaches which have been applied in case studies of other semiarid regions of Africa. These studies try to combine well-known existing approaches, e.g. percentage cumulative mean rainfall (Ilesanmi, 1972), with new ones, e.g. rainfall curves, in order to overcome limitations that have been discovered. The chosen methods were adjusted to local conditions or extended by further criteria or data if there seemed to be a significant difference between the case study areas.

Fig. 2. Location of El Gedaref State—Case Study Area.

between 12◦ 40 and 15◦ 45 N and 33◦ 34 and 37◦ 10 E over an area of 75,263 km2 . The rainfall characteristics in El Gedaref combined with clay-rich vertisols, which are suitable for sorghum, make the state the main rainfed crop producer in Sudan (Mohammed et al., 2010). Arable land in El Gedaref State includes 8 million acres, out of which 80% is cultivated. This area represents 17–20% of the cultivated area in Sudan and possesses 30–40% of the national sorghum production (Osman, 2012). Climatic conditions in El Gedaref vary from north to south with three distinct climatic and agro-ecological zones in terms of rainfall amount and agricultural characteristics: The northern part lies in an arid zone with rainfall amounts between 200 and 400 mm, the center of the state is a semi-arid zone with rainfall varying from 400 to 600 mm and the south of El Gedaref experiences a dry monsoon climate with 600–800 mm rainfall annually (Mohammed et al., 2010). The rainy season lasts from May to October, when the inter-tropical convergence zone (ITCZ) between the desert high-pressure zone and the southern moist zone reaches north. Temperature is high in summer and warm in winter. It is at its height in April (reaching 46 ◦ C) and at its minimum in January (reaching 15 ◦ C).

4.1.1. Rainfall method by Ndomba (2010) The method of cumulative percentage mean rainfall by Ilesanmi (1972) is commonly used to determine the onset and cessation of the growing season and is free of assumptions of rainfall threshold values. According to Ilesanmi (1972), onset and cessation of rainfall are determined by (i) computing seasonal dekadal rainfall values from the entire record, (ii) expressing it as a percentage of the total mean annual rainfall, and (iii) plotting the percentage cumulated seasonal dekadal rainfall values against the dekad numbers. The point of maximum positive curvature of the graph is then defined as the onset of rainfall, while the cessation of rainfall is at the point of maximum negative curvature, Maximum(xi−1 − xi+1 ) /2 − xi . The points of maximum positive and negative curvature can be estimated by calculating the distance between the point value (xi ) of a certain dekad and a straight line that connects the two neighboring points (xi − 1 ; xi + 1 ) of the chosen dekad. The biggest distance between the curve and the straight line means that a point of maximum curvature is reached. A problem related to this approach is that a few isolated showers at the beginning or end of the rainy season can lead to biased results. Therefore, Ndomba (2010) suggests adding rainfall curves and crop water requirement analysis as complementary approaches. Rainfall curves were developed for the rainy season using statistical and probabilistic parameters. Percentiles of 25, 50 and 75 as well as probability of occurrence of rainfall of each day in each

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Table 2 Survey method. Questions and interview partners Common questions for all interview partners What do you consider to be useful coping strategies (technologies or machineries)? Does any weather/climate forecast exist, and if yes, how does it reach farmers? What are the reasons for low productivity of sorghum cultivation? What are the parameters affecting sowing dates? Specific questions for the individual interview partnersa Ministry of Agriculture Respondent 1 (MoA)

Agriculture Research Cooperation (ARC)

Respondent 2

Large scale farmer in El Gedaref

Respondent 3

MS Inputs & Services Company

Respondent 4

ICS Company

Respondent 5

University of Gezira

Respondent 6

a

What is the main duty of the Ministry of Agriculture in El Gedaref? Are farms in El Gedaref predominantly private or do they belong to the government? Does the MoA focus more on rainfed or irrigation agriculture? What is the duty of the ARC? Can you characterize the structure of the agricultural sector in El Gedaref? What are the common sorghum varieties and their characteristics? How does the government support rainfed agriculture? What is the common machinery used in El Gedaref? Can you characterize the structure of the agricultural sector in El Gedaref? What are the current yield and price data of sorghum? What are the natural characteristics of El Gedaref? How would you describe the institutional framework of rainfed agriculture in El Gedaref? What are the common sowing and harvesting strategies? What is the impact of machinery on planting dates? What are the common land management practices? Can you give information about sorghum varieties? How can you describe the farmers’ organization?

The identities of respondents are not exhibited in accordance with the ethical stipulation of the study.

month of the rainy season were included in the analysis of models with variability in parameters. A percentile rank (R) is the percentage of scores that fall at or below a given score and is calculated by R=

P (N + 1) 100

(1)

where P is the desired percentile and N is the size of record. The probability of occurrence of rainfall event is calculated by P(E) =

n (E) n (S)

(2)

where n(E) is the number of events and n(S) is the sample size. In order to calculate the probability of occurrence of rainfall, the amount of precipitation required for a rainy day needs to be defined. A rainy day is commonly defined as a day with effective rainfall (Kowal and Knabe, 1972). Effective rainfall refers to the amount of rainfall that exceeds evapotranspiration. Therefore, a threshold of 5 mm is used to define a rainy day. On average 5 mm/day of rain needs to fall to overcome evapotranspiration and to add to soil moisture. 4.1.2. Rainfall–evapotranspiration method by Ati et al. (2002) Before the actual start of the season, rain is irregular and the amount of rainfall is insufficient to wet the soil to a depth that allows cultivation. Moreover, unreliable rainfall makes it too risky for farmers to start sowing (Kowal and Knabe, 1972). Ati et al. (2002) proposed reducing the problems of false starts and a growing season of insufficient length by combining Kowal’s method with the dry spell factor from Sivakumar’s method (Sivakumar, 1992). Such a factor is important because a dry spell of more than seven days within the first months after planting can lead to crop failure. Therefore, the sowing date has been calculated according to the suggested hybrid method. Sowing should take place when a 10-day period has rainfall greater than 25 mm, a subsequent 10day rainfall is greater than 50% of potential evapotranspiration and

no dry spell of seven days or more occurs within the next 30 days from the sowing date. For the purpose of calculation, the sowing date is taken as the sixth day from the subsequent 10-day period of concern. In the event of a dry spell, a new sowing date according to Kowal’s method should be determined after the dry spell. Results of these calculations were compared with an annual sowing date defined based on a threshold of 100 mm. Common practice under rainfed cultivation and heavy clay soils is to wait for an accumulation of 100 mm of rain before sowing (Mohammed et al., 2010). Initially, this threshold depends on the onset of rainfall. Since the onset is characterized by temporal and spatial differences, farmers have to find strategies that allow them to define the time of sufficient moisture availability for sowing sorghum on a yearly basis.

4.2. Meteorological data Rainfall data was the most important for sowing date calculations. Daily rainfall records for the period 1971–2010 are available from the meteorological station for El Gedaref city, run by the Sudan Meteorological Authority. No other meteorological station for El Gedaref State has continuous daily rainfall records. They offer only monthly rainfall data for different time periods. Besides, the reliability of such data cannot be guaranteed. The limited availability of rainfall data has impacts on the spatial application of the results of this research. Since methods dealing with sowing dates require daily rainfall data, all conclusions will specifically refer to the center of El Gedaref State. Variations in sowing dates in the south and north of the state cannot be ruled out. Available rainfall data show a north-south gradient in the direction of increasing rainfall. Hence, this study depends on this sole station. Monthly minimum, maximum and mean temperature records covering the period from 1971 to 2010 are used in this study to calculate the evapotranspiration values. Grass reference evapotranspiration ETo values can be estimated by using the Hargreaves

320

Percentage of total mean annual rainfall

A. Bussmann et al. / Land Use Policy 52 (2016) 316–328

120 100 80 60

Cessation

Onset

40 20 0 1

3

5

7

9

11

13

15

17

19

21

23

25

27

29

31

33

35

Dekads of a year Fig. 3. Plot of cumulative seasonal rainfall for El Gedaref City for the period1971–2010.

individual characteristics of information sources (Flick, 2009). The sample of interviewees represents the farmers and other information sources, such as policy makers and researchers. Having diverse information sources can be helpful to grasp different perceptions of the status quo but, of course, only serve as an explorative study (Flick, 2009). The sources of information included Agricultural Research Corporation (ARC), Farmer’s Union, Mechanized Farming Corperation (MFC), University of Khartoum, University of El Gedaref, Ministry of Agriculture and companies for machinery and seeds. All interviews were conducted in the capital (Khartoum State) and El Gedaref State while, due to logistic difficulties, only farms within a radius of 60 km around the city of El Gedaref could be considered. The survey also included visit to farmlands to observe land management practices and verify information collected through interviews and discussions. These visits were guided by responsible farmers and observations focused on varieties of sorghum, their individual planting dates and stages of growth of weeds, soil characteristics, methods of crop cultivation (mono and mixed cropping systems) and use of machinery. The visited farms included Umm Sharraba, Al-Gaboob (Wad Bazil) and Allayya. Primary data received from interviews, discussions and visits to farms were highly important since relevant secondary data about local land management practices, such as maps and statistics reports, are hardly available. Secondary data were obtained from published and unpublished materials of different institutional sources and companies. Specific data on growing and harvested

4.3. Field survey data

Probability of Occurence of Rainfall

In order to obtain primary data a field visit, which took place in October 2012, was included in the research. The field research helped to validate specific information, such as traditional sowing dates, and to assess the relevance of the topic among the local population. While the scientific relevance of the topic is indicated by the literature review, interviews with selected farmers, agricultural organizations, research institutions and policy bodies showed the perception of climate variability and its impacts on growing sorghum, land management practices and possible coping measures by the affected population. The purpose of the survey was to use qualitative interviews (see Table 2). Such interviews allow a focus on the interviewee’s point of view. However, since certain topics should be covered in the interview, semi-structured interviews including an interview guide are suggested to adapt to the

0.7

600

0.6

500

0.5

400

0.4 300 0.3 200

0.2

Cumulave Percenle

equation (Hargreaves and Samani, 1985). The method requires only measured temperature data. The FAO56 Penman–Monteith (FAO56-PM) equation (Allen et al., 1998) is another possibility to estimate ETo (mm/day) on a daily basis. Although FAO56-PM is considered to be the standard method for calculating ETo , it requires high data input that is often unavailable. For El Gedaref, values calculated from FAO56-PM are available from 1971 until 1996 from Elagib and Mansell (2000). In order to obtain ETo for the period 1996–2010, the Hargreaves equation is calibrated based on FAO56PM. The Hargreaves values were obtained by Elagib (2009).

100

0.1

0

Probability of Occurence

22-Nov

8-Nov

25-Oct

11-Oct

13-Sep

27-Sep

30-Aug

16-Aug

19-Jul

2-Aug

5-Jul

7-Jun

21-Jun

24-May

10-May

12-Apr

26-Apr

29-Mar

1-Mar

15-Mar

0

Cumulave 75th percenle

Fig. 4. Probability of occurrence of rainfall and cumulative 75th percentiles plotted against time (considering rainfall records from 1971 to 2010).

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Table 3 Details of sowing date records according to 100 mm threshold and Ati et al. (2002) method. Year

Sowing date (100 mm)

Sowing date (Kowal and Knabe, 1972)

1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990

13 Jul 01 Jul 14 Jul 14 Jun 04 Jul 28 Jun 17 Jun 28 Jun 08 Jun 21 Jun 06 Jul 30 Jun 13 Jul 18 Jul 29 Jun 30 Jun 20 Jun 29 Jun 24 Jun 20 Jul

14 Jul 27 Jun 20 Jul 02 Jul 17 Jun 26 Jun 15 Jun 02 Jul 14 Jun 27 Jun 07 Jul 07 Aug 22 Jul 10 Jul 18 Jun 06 Jul 21 Jul 05 Jul 30 Jun 13 Aug

Delayed, because of

Dry spell ≤0.5 ETo Dry spell

Dry spell Dry spell ≤0.5 ETo Dry spell

areas, cost, production, varieties and yield did not always meet the particular requirements of this study. Farmers and local institutions do not keep records or their records are neither systematic nor consistent. 5. Results and discussion 5.1. Results from the rainfall method by Ndomba (2010) For defining the onset of rainfall, cumulative seasonal rainfall for El Gedaref City is plot. Results show that the onset of rain for El Gedaref takes place within the 18th dekad of a year, which means between 28 June and 08 July (see Fig. 3). These results are in line with earlier findings for parts of western Sudan, where a waterbudget analysis showed “a distinct optimum planting period of June 20–July 10 with planting in early July as the most likely for best production” (Omer et al., 1988). The cessation of rainfall can be found within the 27th dekad, between 26 September and 06 October. Therefore, the rainy season lasts on average nine dekads. Fig. 4 shows rainfall curves of probability of occurrence and cumulative 75th percentiles useful for determining a sowing date period. The main requirements for an appropriate sowing date are sufficient soil moisture and a high probability of rain. The probability of rainfall occurrence is important to know since it is an indicator for avoiding dry spells. According to Fig. 3, the probability of occurrence of rainfall varies all season long. The probability starts to increase in April and reaches 0.28 in the middle of June. At the latter time, values for the 75th percentile start to rise while all values of the 25th and 50th percentiles stay at zero during the entire season. This means that there is no day for which rainfall events occurred in more than 50 percent of the examined years. The values for 75th percentile indicate that one day scored below certain values in 75% of the years and above the values in 25% of the years. A high value means that 25% of the wet days score above this high value and are valuable for the growing season. While April and May are still characterized by negligible values of the 75th percentile, the values increase steadily in June up to a maximum value of 9.5 mm. The average values of the 75th percentile jump up in the last dekad of June from 1.4 to 3.5 mm. The maximum average values are reached two dekads later by the middle of July. Similar to this development, the probability of rainfall occurrence starts to rise in June. The dates where it starts to increase sharply by 0.1–0.2 and can reach up to 0.4 are during the last week of June. By the time

Year

Sowing date (100 mm)

Sowing date (Kowal and Knabe, 1972)

Delayed, because of

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

11 Jul 12 Jul 26 Jun 04 Jul 02 Jul 20 May 03 Jul 21 Jul 13 Jun 29 Jun 08 Jul 25 Jun 28 Jun 22 Jun 04 Jul 21 Jun 05 Jul 24 Jun 03 Jul 02 Jul

28 Jul 10 Jul 02 Jul 10 Jul 30 Jun 18 Jun 02 Jul 24 Jul 02 Jul 23 Jul 09 Jul 19 Jul 28 Jun 26 Jun 02 Jul 29 Jun 07 Jul 30 Jun 05 Jul 20 Jul

Dry spell Dry spell Dry spell ≤0.5 ETo ≤0.5 ETo ≤0.5 ETo Dry spell Dry spell Dry spell

Dry spell

Dry spell

of higher rainfall probability, it is less likely for the rain to stop for long periods. From the first week of July on, the probability will not drop below 0.1 anymore. It rather fluctuates between 0.1 and 0.4. The probability of rainfall occurrence is highest between the end of July and the beginning of September, i.e. the time when the rainy season is established. Considering a total sorghum growth period of 130 days (Allen et al., 1998), the season for crop growth is very limited since the total rainfall amount per season ranges from 320 to 860 mm in the center of El Gedaref State. Reducing this rainfall amount by surface runoff and evaporation, a very limited amount of rain that is hardly sufficient for the crop falls in a short period. Therefore, the sowing date should be as close as possible to the onset of rains. The only consideration that should be a reason to delay sowing is a high probability of a subsequent dry period.

5.2. Results from the rainfall–evapotranspiration method by Ati et al. (2002) Table 3 compares the sowing dates based on the local tradition and Ati et al. (2002) method. Trying to eliminate false starts, the sowing date was delayed for 18 out of 40 years. Mostly due to dry spells after the definition of Kowal’s date, the sowing date had to be recalculated. In five years, the rainfall during the first 10 days of accumulation of 25 mm was not high enough to exceed 0.5 of reference evapotranspiration. For the other 13 years, dry spells of seven days or more caused a delayed sowing date. The average sowing date is the 08 July. Compared to the average sowing date determined based on a rainfall threshold of 100 mm (01 July), the sowing date criteria by Ati et al. (2002) causes a delay by one week. However, the 08 July as the recommended sowing date by this method is still earlier than farmers sow in reality. The most common sowing date farmers choose is usually in the end of July or sometimes even in the beginning of August. Despite the climatological drivers (e.g. a 100 mm threshold), field observation and farmer’s reports show that several non-climatic factors are leading to a common delay of the sowing date to mid or even end of July. Assuming that 08 July is the common sowing date for all the years, this date implicates a low probability of 0.175 that a dry spell of seven days occurs during the first months after sowing. Any earlier or later date is related to a higher probability (>0.2) of occurrence of dry spells.

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Table 4 Main parameters determining the sowing date and their relevance. Parameter

Effect

Possible impact

Relevance

Climate variability

• Inter- and intraseasonal variability of rainfall

• Dry spells cause delayed planting

+++

• Increasing temperatures

• Higher evaporation results in reduced soil moisture

• Water holding capacity

• Hard soil in dry conditions

• Infiltration rate

• Soil with low permeability in wet conditions

Soil characteristics

++

• Soil texture Crop’s genetics

Weeds and parasites

• Drought-resistant varieties (C4-Effect)

• Late and early maturing varieties

• Hybrid varieties

• Different requirements of soil moisture

• Striga (Striga hermonthica),

• Mainly Striga and different strategies to avoid this weed lead to delayed sowing dates

++

• Delayed sowing to be able to combine operations and save costs

++

• Earlier sowing possible if planter machines are available

+

• Limited research facilities available that cooperate and inform farmers

+

++

• Sudangrass (Sorghum × drummondii) • Headworm (Helicoverpa zea) Socio-economic factors

• Use of fertilizers and pesticides

• Cost of labor • Size of farm • Financial capacity Machinery

• Wide level disc

• Planter machine used for sowing Institutional environment

• Low investment in research facilities and (meteorological) institutions

5.3. Field survey results In general, climate factors, in particular rainfall, are the main aspects determining the sowing date. However, in this research field visits, interviews and personal observations lead to the assumption that there are several other variables, such as soil characteristics or weeds, influencing farmers’ decision on sowing dates. Even though each of these factors has different impacts that can vary from year to year and from one farm to another, a categorization of the main factors is necessary. Only by recognizing the complexity of interdependence among them, can decision making processes concerning sowing dates be understood and modified. The relevance of each factor, as stated in Table 4, should be understood as a suggestion based on how often farmers and experts were mentioning the respective factor during field visits. Farmers and agricultural experts have different perceptions concerning sowing date parameters. Therefore, the ranking of parameters is a subjective interpretation and requires further research to be confirmed. 5.3.1. Climate variability The main features of rainfall in El Gedaref are its seasonal characteristics and its variability from year to year. The deviation of mean annual temperature and rainfall is used to assess the interseasonal variability by describing the climatic departures from the

median (Fig. 5). Elagib and Elhag (2011) found that the percentage frequency of occurrence of above-normal annual temperature and rainfall for 1975–2008 in El Gedaref is 67.6 and 47.1%, respectively. The time series of both the mean annual temperature and annual rainfall indicate a continual warming from the 1980s onwards. Although year to year variability exists, the increase in mean annual temperature was more than 0.2 ◦ C per decade during 1941–2009 (Sulieman and Elagib, 2012). Seasonal rainfall in El Gedaref State is characterized by highly variable and few rainfall events in April or May, followed by a long dry spell of more than seven days, then a gradual advancement of the rainy season eventually reaching a peak, on average, in July. Usually farmers need to wait until the rainfall development in June in order to be able to define a sowing date. If rainfall is still erratic in June, they will postpone sowing to the middle or end of July. Once the rainy season is established, most rainfall is concentrated in the period from mid-July to midSeptember. The cessation of rains usually starts in September and ends in October. However, the daily rainfall data shows that there are years in which the last showers of the year occurred in the end of September. 5.3.2. Sorghum varieties Sorghum (Sorghum bicolour (L.) Moench) is an indigenous crop to Africa, and is one of the world’s leading cereal crops. It is the

300

1.0

200

0.5

100

0.0

0

2007

2009

2003

2005

2001

1997

1999

1995

1991

1993

1989

1987

1983

1985

-300 1981

-1.5 1977

-200

1979

-1.0

1975

-100

1973

-0.5

Rainfall (mm)

323

1.5

1971

Temperature (°C)

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Year Fig. 5. Deviation of annual temperature (grey) and rainfall (black) totals from the median value at El Gedaref meteorological station. Median temperature = 29.3 ◦ C; median rainfall = 609.2 mm.

main staple food for rural communities in Sudan, in particular in drought-prone areas. Sorghum belongs to the so-called C4-plants, which are characterized by improved photosynthesis activity at high temperature and dry conditions (Nsw Dpi, 2005). The crop is usually cultivated in dry areas on shallow and heavy clay soils (Plessis, 2008). Several varieties exist, such as early and late maturing, local and hybrid varieties. All of them interact with the sowing date in an individual way (Respondent 4, Table 2, 2012). In El Gedaref, around 30 different varieties of sorghum are available for farmers to choose from. It is necessary for the farmer to select the most suitable ones for their current conditions. The selection of the crop and varieties that are grown on rainfed farms is affected by a number of aspects: -

Timing and volume of water expected during the rainy season. High yield potential. Resistance or tolerance to prevalent diseases and weeds. Low requirement on chemical treatment and labor input. Good performance in previous years. Experience from crop choice of neighboring farms. Cost of seeds. Food and market value.

Sorghum varieties can be sub-divided according to maturation timing. Early maturing sorghum can either be planted early and be harvested before the end of the season or can be planted late and be harvested by the end of season. In the event of a short rainy season, early maturing varieties are important to choose. In contrast, late maturing varieties need to be planted with the first rains, early in the season. Under good climatic conditions, they give the highest yields. Growing period of different varieties can vary from 75 days to 110 days (Respondent 6, Table 2, 2012). The late maturing varieties are most risky if there is not enough rain altogether. The traditional cropping system is designed to be flexible enough to cope to a certain extent with inevitable crop failures. At the beginning of a cropping season, a late-maturing, high-yielding crop is planted. If this crop fails because of over-flooding, shortage of water or weeds and insect attack, it is replaced by an early-maturing and drought-, pest- and disease-tolerant variety, which is usually a lowyield variety. Otherwise, farmers can resow if they still have seeds available (Respondent 2, Table 2, 2012). Most farmers in El Gedaref use local varieties because they have been developed in the region over a long period, and are well adapted to the environment of soil and limited moisture availability (Respondent 1, Table 2, 2012). However, new national and international hybrid, high yielding varieties have been introduced in recent years (e.g. named Pac Sol, Alfa,

Hgeim Dora 1 and 2, Panar 606). Hybrid varieties have generally a higher yield potential but the seeds are expensive and their cultivation often requires the input of fertilizers. Mixing varieties on a farm is very common in order to distribute the risk of crop failure. Since each variety reacts to characteristics of rainfall seasons in different ways, the chance to have a successful harvest for at least one variety grown on parts of the farm is more attractive for farmers than to depend on the performance of one variety for the entire farm production. 5.3.3. Weeds and parasites Weeds and parasites can have significant implication on crop growth, yield and sowing dates. Most of them compete with the plant and lead to significant yield decline. In El Gedaref, the impact is serious because weed and pest control through crop rotation or application of herbicides and pesticides is very limited (Respondent 4, Table 2, 2012). There are several weeds and parasites in El Gedaref (Fig. 6a), such as: a) Sudangrass (Sorghum × drummondii): is a hybrid, a cross between sorghum and an African grass (Fig. 6a). Its local name is Hadar. Like sorghum, it is a fast-growing crop with an extensive root system that thrives in hot climate. It grows wild and competes with the sorghum crop for water and nutrient. b) A headworm (Helicoverpa zea): This feeds on sorghum and larvae in sorghum heads (Fig. 6b). Sorghum planted early is more likely to avoid major insect damage because parasites do not usually reach damaging population levels until after early plantings are mature. However, during field observation, worms were never stated as a factor influencing the sowing date c) A weed called Striga (Striga hermonthica): It affects sowing date and sorghum production in El Gedaref State (Fig. 6c). However, the only one seriously affecting the sowing date is Striga. Striga is the most destructive parasitic weed on sorghum in Sub-Saharan Africa. Striga seeds are stimulated by sorghum roots. As soon as they are sensed, Striga attaches to the sorghum and sucks nutrients and water to synthesize its own germination (Shank, 1996). Continuous droughts and land degradation have increased the infestation of Striga dramatically since there has not been any comprehensive control so far. Striga is more likely to exacerbate in poor farming cultivation where no crop rotation is practiced and where soils are heavily used and characterized by low fertility (Bebawi et al., 1985). It thrives in low nitrogen-fertility soils and under low rainfall ecologies (Shank, 1996). These conditions are often present in El Gedaref due to mono-cropping in a

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Table 5 Farm observations.

Farm size Crops Sorghum variety Sowing date determination

Yield Machinery

Chemical inputs Weeds a

Farm 1 Allayya

Farm 2 Al-Gaboob

Farm 3 Umm Sharraba

1000 feddan Sorghum, Sesame, Sunflower (distribution varies) Faterita type: Arfaa Gedamea Metal stick is pushed 30 cm deep in the soil to test texture Private rain gauge 300–400 kg/feddan Wide-level disc for land preparation and sowing, harvest is done manually and collecting byharvesters No Striga, sudangrass, headworms

1000 feddan Sorghum, Sesame (distribution varies)

13,000 feddana Sorghum, Sesame (distribution varies)

Faterita: Wad Bako Wait for cracks in vertisols to close

Afadreg (short) and Kura Kura Wait for cracks in vertisols to close between 10 July and 15 August for risk distribution 500–600 kg/feddan Wide-level disc for land preparation and sowing, harvest is done manually and collecting byharvesters 24D Pesticides Headworms, Striga infestation: The farmer tries to delay the sowing

300–400 kg/feddan Wide-level disc for land preparation and sowing, harvest is done manually and collecting byharvesters No Headworms, Striga infestation: The farmer tries to delay the sowing

1 feddan = 0.42 ha.

drought-prone area and limited application of fertilizers, pesticides and weed-killers. Several methods for Striga control are known: trap crops, 24D herbicides, early and constant weeding, intercropping with other crops, Striga-resistant varieties and delayed sowing (Respondent 4, Table 2, 2012). In general, each farmer has a different strategy to reduce Striga infestation. Problematically, most existing control measures require considerable labor and financial input. This puts a high burden on poor farmers who often have the highest infestation rates and are least capable of undertaking the laborious job of hand-pulling of Striga weeds. One strategy that is common among farmers in El Gedaref and is often stated to be successful because it is the least expensive is to delay sowing by two to three weeks (Respondent 1, Table 2, 2012). However, Striga infestation can spread through contaminated seeds, contaminated soil through plows, animal’s feet, eroding soil, passage through cattle grazing on infested areas and improper disposal of Striga plants. Movement of people and animals enhances re-infestation.

5.3.4. Soil While Northern El Gedaref is characterized by an undulating clay plain with some rocky hill group and an average slope of 0.5%, the El Gedaref clay plain—located in the south of the state—has a gentle, regular slope of 0.2%. El Gedaref is mostly covered by vertisols and partly by nitisols. Both of them are a common heavytextured soil type in the tropics, subtropics and warm temperate zones (Blokhuis, 1993). Vertisols play an important role in this environment because they are amongst the most productive soils. Due to their high water-holding capacity, vertisols are highly suited to dryland crop production in semi-arid environments with variable and erratic rainfall. Other than most soil types, vertisols allow crops to survive long dry periods and are potentially highly productive. However, they are strongly exposed to erosion, and farming systems need effective conservation techniques. As a consequence, the production potential is often unmet, especially for famers with limited resource (Virmani et al., 1982). Concerning the physical properties of vertisols, important aspects are texture, clay mineralogy and water availability. The soils found in El Gedaref state meet the basic properties of soils, reaching clay content as high as 75%. The clay mineral montmorillonite that absorbs great quantities of water and the high clay content cause high water-holding capacity of vertisols. In vertisols, available water for plant transpiration is held between field capacity and wilting point within the top 1.2 m of soil and can be exploited by shallow rooted crops such as sorghum (Virmani et al., 1982). The texture of vertisols poses a challenge to the ones cultivating it. The soil is extremely hard when dry. A much softer, very plastic and sticky soil texture can be found in the wet season. Only within a

certain range of moisture content are tillage and seedbed preparation possible. Depending again on the swelling and shrinking, the bulk density of vertisols varies extremely. In dry conditions, the bulk density is high while it is low in a swollen, wet stage. Highly important for any agricultural activity is the infiltration rate of vertisols. Initially, the soils have high infiltration rate due to the presence of cracks before the onset of the rainy season. Increased wetting of soil causes the cracks to be sealed and decreases the infiltration rate drastically. During the rainy season, values of infiltration rates range from 2.0 mm/h to 0.5 mm/day. The water balance of the soil, particularly the intake and runoff parameters, is determined by the infiltration rate and hydraulic conductivity. Poor drainage during the rainy season is an inherent physical constraint for crop production. Surface preparation of land is needed to drain or dispose excess water quickly (Virmani et al., 1982).

5.3.5. Socio-economic factors Farms in El Gedaref State are mostly private and have various sizes. Most farms which are larger than 1000 feddan (420 ha) are semi-mechanized, meaning that certain operations are done by machine, such as land preparation and sowing. Every farmer in El Gedaref is involved in local sorghum trading. Because the government does not undertake any price intervention, prices of sorghum strongly fluctuate (Respondent 1, Table 2, 2012). The uncertainty in the sorghum market prevents farmers from big investments. The price for sorghum has risen in recent years up to 150 SDG (33.5 US$) per 90 kg sack. Currently, the prices vary between 125 and 180 SDG (40.2 US$) per 90 kg sack. From 2011 to 2012, there was a 76% price increase because of low yield in 2010 and 2011 (Respondent 4, Table 2, 2012).

5.3.6. Machinery Use of farm machinery is related to local agricultural practices that in turn depend on socio-economic conditions. The traditional sowing method in the semi-mechanized areas of eastern Sudan is the use of a four-wheel drive tractor of about 65 hp with a widelevel disc harrow equipped with a seeder box. Disc cultivation starts after the first rains of the season that add to soil moisture and result in a closure of deep cracks in the clay soil. At this moment, the soil starts to be soft enough for preparations. A wide-level disc used for seeding results in a relatively low rate of seeds that succeed to germinate. Another problem related to wide-level discs is that, after many subsequent years of usage, the unploughed soil (around 15 cm deep) will get compacted. This hardpan prevents water infiltration and root growth.

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Fig. 6. Weeds and parasites affecting sorghum in El Gedaref State (Photos: Bussman).

Modern planter machines are much more expensive than widelevel discs but could cut down time for seeding operation, increase crop establishment and reduce seed rates. Planter machines could increase crop establishment by 20–30% just by locating seeds precisely in the soil and, thus, avoid seeds erosion from the surface by wind or birds (Respondent 3, Table 2, 2012). Such machines would allow planting at a stage when soil moisture is still low 25–50 mm. Planters put the seeds at an exact depth in the ground, and by having a good contact to the soil, seeds need a lower level of humidity to germinate. The expensive investment in planter machines can help farmers to make use of additional 50–75 mm of rain, and, therefore, to extend the growing season and make the sowing less affected by erratic establishment of the rainy season (Respondent 6, Table 2, 2012). The sowing date could take place two to three weeks earlier than the usual date determined by rainfall (Respondent 5, Table 2, 2012).

6. From coping measures to adaptation Given the exchangeable use of the terms ‘coping’ and ‘adapting’ to climate variability and climate change in current scientific literature (e.g. Thomas et al., 2007; Mengistu, 2011), this research refers to the term defined by Thomas et al. (2007), who differentiate coping and adaptation measures according to the range of response, meaning rapid responses to climate variability are considered to be ‘coping measures’ while long term responses are considered to be ‘adaptation measures’. Subsequently, farming practices are defined as ‘coping’ measures. However, all kinds of economic and political structures affecting farming practices can certainly adapt to changing environments and, in turn, help to increase the adaptive capacity of farmers. Trying to answer the question of how farmers can increase their productivity and optimize sorghum yields, the field observations

Fig. 7. Importance of rainfed agriculture within a regional IWRM strategy.

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and interviews showed clearly that several other factors beside the sowing date need to be considered (see Tables 4 and 5). However, most of them interact with the sowing date. A new research field in eastern Sudan is the enhancement of water availability for agriculture through higher rainfall capture (crop residues, tied ridges, etc.), rainwater harvesting and supplemental irrigation. It is known that the volume of rainfall lost through surface runoff during high intensity rainfall is large. Runoff harvesting into underground reservoirs in addition to use of channels, small dams and road embankments to store water are already common water saving strategies in other arid regions (Yuen et al., 2001; Ouessar et al., 2004). First pilot studies have been developed (Tabor, 1995; Niemeijer, 1998; Elramlawi et al., 2009; Elfaki et al., 2013), but local farmers are often critical towards water harvesting. Although water harvesting for domestic use is a traditional method that has been implemented for centuries, hardly any farmer utilizes it for irrigation. It is considered too expensive to be implemented for farms of ≥ 1000 feddan (420 ha) (Respondent 2, Table 2, 2012). The same argument applies for supplementary irrigation. For large-scale farming with relatively low farm inputs, the installation of such a system is highly cost intensive and requires know-how and long-term operation and maintenance. Soil surface formation—known as in-situ water harvesting techniques—has high potential to result in higher yields by improving soil moisture stored within the root zone. However, sowing on contour ridges or tied ridges depends on the machinery used on the farms. The utilization of wide-level discs and the relatively large size of farms form obstacles to the implementation of soil surface formation for water conservation (Elramlawi et al., 2009 Respondent 5, Table 2, 2012). It is a big challenge to succeed in combining technical efficiency, low-cost inputs and good management. Introducing advanced technological equipment in agriculture to reduce the vulnerability of farmers can have negative side-effects, such as soil degradation, increasing salinity or pollution. For most farmers, in particular small-scale farmers, sorghum cultivation is associated with risk management. Therefore, ideas need to be developed to reduce the risk and make use of the high potential to increase productivity (Respondent 5, Table 2, 2012). Early warning systems for agricultural droughts can be a helpful method to reduce farmers’ risks. At the moment, it seems most likely that shifts of sowing date and new varieties will be adopted in the long term (Respondent 4, Table 2, 2012). Water uptake and conservation can be enhanced by selecting water-stress tolerant crops and varieties. However, it is most likely that sorghum will remain the crop of choice in eastern Sudan (Respondent 3, Table 2, 2012). Other crop management factors, such as weed and disease control and soil fertility improvement are equally important (Teklu, 2012; Respondent 2, Table 2, 2012). Looking at the institutional framework, the current agricultural policy does not favor rural rainfed agriculture. Moreover, the water sector in Sudan is very fragmented. Several ministries and institutions are involved and are mostly concerned about their individual interests. As a consequence, Sudan at a regional level lacks a clear water resources strategy, including guidelines on how to conserve water supplies, adopt ways to optimize water use efficiency, increase water storage, check on-ground water, improve river basin management and enhance awareness of threats to water resources. The concept of Integrated Water Resources Management (IWRM) is still of minor importance in any water-related sectors of Sudan, especially rainfed agriculture. From an IWRM perspective (Fig. 7), increasing productivity in rainfed agriculture depends on and affects aspects that start at the farm level and reaches far beyond. At first, the institutional level needs to understand that rainfed agriculture is a very vulnerable system. Therefore, in order to make the best use of available resources, water demand management should be a main approach at the farm level. Fur-

thermore, agricultural land management and water management within an IWRM framework mean to allow active participation of the agricultural sector in resource management. To inform and raise awareness is, therefore, a first step for future strategic planning and sustainable land management. Such an approach is needed for local communities to adopt new strategies. Ultimately, farmers need to implement new strategies rather than research and management. However, any further research on sustainable agriculture under climate risk should consider the indigenous knowledge of farmers. On a regional scale, rainwater management in rainfed agriculture also aims at reducing the need for irrigation extension and, thereby, decreasing the pressure on scarce blue water resources. However, to achieve positive effects from such an integrated approach of managing green and blue water resources, the policy and institutional framework has to recognize its potential in enabling participatory farm development in rainfed (Fig. 7). Among other activities, transfer of information based on knowledge of previous rainfall season patterns between an agrometeorological advisory body, research workers and farmers can improve the decision making on sowing and help to optimize water use for food production (Ati et al., 2002). In general, the application of any method requires information transfer to the farmers which in turn depends on the institutional framework and research capacities. If the institutional environment does not favor and support rainfed agriculture, farmer’s capability to cope with current and adapt to future climate trends would be limited. So far, this has been the case, but changes are possible due to political and economic reasons. Since the separation of South Sudan in 2011 and the associated loss of oil resources, the Sudanese government has been looking for new sources of income. Because of the country’s large land resources, the agriculture sector has high economic potential. However, not only irrigated but also rainfed agriculture needs to receive increasing recognition by the Sudanese government. In particular, agricultural extension services need to be strengthened and to switch from a disabling to an enabling environment. Otherwise, the decreasing productivity will lead at first to an expansion of agricultural activities, then to increasing land degradation and finally to a conflict over resources, all of which lead to food insecurity and migration from rural sides to urban centers Fig. 1. 7. Conclusions The chosen climatic methods clearly indicate a sowing date in the first half of July. However, experience shows that this date is earlier than most farmers usually sow. A delay of sowing dates commonly takes place because farmers do not have reliable tools to define the onset of the season and generally act risk-averse. They are highly vulnerable to crop failure owing to non-climatic factors that are considered affecting the germination of crops. Due to such reasons, the onset of rains and soil moisture levels are sometimes ignored and the growing seasons is not being optimally used and, thus, yield is not maximized. Different actions can be recommended which could help farmers to solely consider seasonal and shortterm weather forecasts when deciding the sowing date. Thus, the main recommendations for improvement in sorghum yields are: • Introduction of new hybrid varieties (water-stress tolerant, Striga-resistant). • Using herbicides and wide-level disc for weed control, especially Striga. • Techniques for water conservation, such as rainwater harvesting. • Sowing by modern planter machinery. • Execution of crop rotation. • Erosion protection using shelter belts and wind breaks.

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• Monitoring of climate and early warning system for droughts. A stronger agricultural extension service, including know-how transfer related to varieties, application of fertilizers and pesticides, as well as an easy access to loans and credits for investments on the farm level are important conditions for the adaptation of any farming practice that can help to optimize sowing dates under climate variability Based on the outcomes of this study, the next step would be to develop further hypotheses. The following hypotheses can help to build a framework for future research that would complement the results of this study: 1. Lack of institutional support, research and information transfer leads to an increased need for risk management by farmers. 2. Risk-averse farmer’s decision-making causes delayed sowing dates and, therefore, decreases yields. 3. High input of fertilizer, hybrid varieties and planter machinery can optimize sowing dates. 4. Integrated strategies, including socioeconomic as well as technical components, are needed for coping with climate risk and for related agricultural decision making. Acknowledgements The scholarship provided by the German Academic Exchange Service (Deutscher Akademischer Austausch Dienst (DAAD)) to the principal author is acknowledged. Many thanks should also go to Alexander von Humboldt Foundation for funding the research stay at the ITT through Georg Forster Fellowship for Experienced Researchers that was provided to the second author. We would like to thank all interviewees who responded to the field survey and gratefully acknowledge the great assistance that was received by many during the field visit in Sudan. Special thanks go to Muhammad Khalifa for his generous support, which facilitated gathering all necessary information. References Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop evapotranspiration -guide-lines for computing crop water requirements. In: FAO Irrigation and Drainage Paper 56. Food and Agriculture Organization of the United Nations, Rome, Italy, pp. 300. Ati, O.F., Stigter, C.J., Oladipo, E.O., 2002. A comparison of methods to determine the onset of the growing season in northern Nigeria. Int. J. Climataol. 22, 731–742. Bannayan, M., Lakzian, A., Gorbanzadeh, N., Roshani, A., 2011. Variability of growing season indices in northeast of Iran. Theor. Appl. Climatol. 105, 485–494. Bebawi, F.F., El Hag, G.A., Khogali, M.M., 1985. The production of dura (Sorghum vulgare) in Sudan and the parasite buda (Striga hermonthica). In: Natural Resources and Rural Development in Arid Lands: Case Studies from Sudan. Khartoum, Sudan, pp. 1–15. Bewket, W., 2009. Rainfall variability and crop production in Ethiopia case study in the Amhara region. Proceedings of the 16th International Conference of Ethiopian Studies. Trondheim, Norway, 823–836. Biasutti, M., Sobel, A.H., 2009. Delayed Sahel rainfall and global seasonal cycle in a warmer climate. Geophys. Res. Lett. 36, http://dx.doi.org/10.1029/ 2009gl041303, L23707. Blokhuis, W.A., 1993. Vertisols in the Central Clay Plain of the Sudan. PhD. Thesis. Wageningen Agricultural University, Netherlands. Camberlin, P., Diop, M., 2003. Application of daily rainfall principal component analysis to the assessment of the rainy season characteristics in Senegal. Clim. Res. 23, 159–169. Chen, H., Guo, J., Zhang, Z., Xu, C.Y., 2013. Prediction of temperature and precipitation in Sudan and South Sudan by using LARS-WG in future. Theor. Appl. Climatol. 113 (3–4), 363–375. Dodd, D.E.S., Jolliffe, E.T., 2001. Early detection of the start of the wet season in semiarid tropical climates of western Africa. Int. J. Climatol. 21, 1251–1262. Elagib, N.A., 2009. Assessment of drought across central sudan using UNEP dryness ratio. Hydrol. Res. 40, 194–481. Elagib, N.A., 2013. Meteorological drought and crop yield in Sub-Saharan Suda. Int. J. Water Resour. Arid Environ. 3, 164–171, ISSN 2079-7079, www.icwraepsipw.org/.

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