Reference evapotranspiration is a key parameter in hydrological and meteorological studies and used to determine the actual water use rate for various crops. The objectives of this study were to explore trend in the grass-reference evapotranspiration (ETo) through years 1961–2011 and to identify trend in the aridity index as an indicator of change in climate in Togo. ETo was calculated using the FAO-56 Penman–Monteith method, and trends analyses were performed with non-parametric statistics proposed by Mann–Kendall and the Sen slope estimator. Results showed that annual ETo varied from 1,440 to 1,690 mm at Lomé, from 1,761 to 1,905 mm at Tabligbo, and from 1,839 to 1,990 mm at Sokode. The Mann–Kendall test revealed significant increase in annual ETo at Tabligbo (Z = 2.89) and Sokode (Z = 2.29). Annual ETo is much more stable at Lomé, with non-significant decrease. In Togo, according to the three study sites, the 1961–2011 period annual aridity index varied from 0.26 to 0.99 at Lomé, 0.38 to 0.98 at Tabligbo, and 0.45 to 1.08 at Sokode. The Mann–Kendall test revealed a declining trend in the ratio of precipitation/ETo which adversely implies an increasing severity of the aridity index at all the sites, prejudicial to rainfed agriculture practiced by about 90% of Togolese crop growers.

INTRODUCTION

Increasing interest has been shown in the study of change in climate parameters and its effects on the hydrological cycle and water supply. Research has been conducted to detect climate changes, trends, and variability in various parts of the world considering some climate parameters such as air temperature, rainfall depth, reference evapotranspiration, and pan evapotranspiration (Schwartz & Randall 2003; Garbrecht et al. 2004; Hegerl et al. 2007; Fu et al. 2009; Saghravani et al. 2009; Hakan et al. 2010). Climate change is expected to intensify the hydrological cycle and to alter one of its important components, evapotranspiration (Huntington 2006). A linear warming trend over the last 50 years has been recorded at a rate of 0.13 °C per decade (IPCC 2007a). In particular, all of Africa is highly likely to experience warming during this century, with the warming expected to exceed the global average (IPCC 2007b). Therefore, analyzing how climate change affects reference evapotranspiration is critical for understanding the impact of climate change on the hydrological cycle. To evaluate evapotranspiration in the context of climate change, Zheng et al. (2009) characterized the cause of the decreased pan evaporation during 1957–2001 in the Hai River Basin, and found that the declining wind speed is the climate variable that impacted ETo. Goyal (2004) studied the sensitivity of evapotranspiration in terms of change in temperature, solar radiation, wind speed, and vapor pressure for a 32 year (1971–2002) period from the arid zone of Rajasthan, India, and the results showed that the calculated ETo was most sensitive (14.8%) to temperature. Porter et al. (2012) reported grass-reference evapotranspiration (ETo) and alfalfa reference evapotranspiration (ETr) sensitivity to measurement errors in wind speed and air temperature followed by incoming shortwave (solar) radiation. Bandyopadhyay et al. (2009) also studied reference evapotranspiration trends in India and reported decreases in ETo all over India. On the other hand, several researchers also reported increases in ETo trends. Yu et al. (2002) observed increasing trends in reference evapotranspiration at Kao-Hsiung, south Taiwan, using 48 years of data. Hess (1998) reported an increasing trend in reference evapotranspiration in the northeast arid zone of Nigeria, due to the increases in wind speed. Myneni et al. (1997) and Milly & Dunne (2001) reported that the accelerated reference evapotranspiration over North America is assumed to be due to a rise in temperature over the past century. Dinpashoh et al. (2011) reported more pronounced temporally increasing trends in ET than the decreasing trends over Iran, with the wind speed found to be the most dominant variable influencing ETo in all months except the winter months. Other studies reported changes in pan evaporation, which is related to reference evapotranspiration through appropriate and locally developed pan coefficients. Liu et al. (2004) found that the decrease in solar radiance was most likely the driving force of the trend in pan evaporation from 1955 to 2000 in China. In the southern and eastern parts of the Hai River Basin, the annual reference evapotranspiration was dominated by the decreasing trends, and the reference evapotranspiration was more sensitive in decreasing gradient to relativity humidity, temperature, shortwave radiation, and wind speed (Zhao et al. 2014).

Precipitation is one other key component in the hydrologic cycle that affects numerous locations of the world. Reduction in seasonal precipitation is becoming recurrent, and many countries are concerned by the concept of climate change. Climate change has resulted in extreme drought conditions in some parts of the world and flooding in other parts (van de Giesien et al. 2010), and according to a modeling study, anthropogenic climate change may soon yield increases in the frequency and severity of droughts and the expansion of deserts (Manabe et al. 2004). In particular, environmental changes in Africa have been mostly directly related to rainfall (Zheng et al. 1997). Many studies revealed a drastic decrease in precipitation in Africa (Hubert et al. 1989; Mahé & Olivry 1995; Bricquet et al. 1997; Servat et al. 1999; Balme-Debionne 2004; Van Vyve 2006). Nicholson & Grist (2001) identified several changes in the general atmospheric circulation that accompanied a shift to drier conditions in the West African Sahel. This atmospheric circulation is believed to generate and maintain wave disturbances that modulate the rainfall field. Rotstayn & Lohmann (2002) showed that a prominent feature is the drying of the Sahel in North Africa, and suggested that the indirect effects of anthropogenic sulfate may have contributed to the Sahelian drying trend. A few studies in Togo revealed a rainfall deficit since 1970 (Klassou 1996; Badameli 1996, 1998; Adewi 2002; Adewi et al. 2010). The decreasing trend in precipitation against the unbalanced evapotranspiration reduces water availability that can be expressed in terms of aridity.

Aridity is usually expressed as a function of rainfall and temperature. The long-term difference (or ratio) between ETo and precipitation (P) has been considered a measure of aridity used in several climate classification schemes (Köppen 1936; Thornthwaite 1948; Prentice 1990). UNESCO (1979) applied an aridity/humidity classification system based on the average annual precipitation divided by the average annual potential evapotranspiration (PET). Aridity results from the presence of dry, descending air. Therefore, aridity is mostly found in regions with anticyclonic conditions, such as the subtropical area where Togo is located. Climatological aridity is a critical environmental factor that helps to determine the character and sustainability of natural vegetation, rainfed agriculture, and terrestrial ecosystems. The aridity index is qualified by the index of drought by Rind et al. (1990).

To achieve water conservation and sustainability, climate interactions with various aspects of the water cycle should be a research priority. However, despite the broad studies in several countries and regions on the trends in reference evapotranspiration and precipitation, very little information is available on the temporal trend analysis of ETo over Togo. Therefore, the present study is undertaken with three objectives, which are as follows: (1) to detect the monotonic linear trends in the monthly and annual ETo time series using the Mann–Kendall non-parametric test; (2) to estimate the slopes of trend lines of ETo times series using the Theil–Sen's estimator method; and (3) to estimate the trend in the aridity index in Togo.

MATERIALS AND METHODS

The study was conducted in Togo, where three weather stations at Lomé (6 °9′56″ N, 1 °15′16.24″E, elevation 22 m), Tabligbo (6 °34′59″ N, 1 °30′00″ E, elevation: 76 m), and Sokode (8 °58′59″ N, 1 °07′59″ E, elevation: 417 m) were selected for reliability and the long-term dataset without missing data covering the period 1961 to 2011. A record of monthly average climatic parameters including air maximum and minimum temperature, minimum and maximum relative humidity, wind speed, solar radiation, and precipitation were used to estimate monthly evapotranspiration.

Reference evapotranspiration estimation model

Daily grass-reference evapotranspiration (ETo) was computed using the standardized ASCE form of the Penman–Monteith (ASCE-EWRI PM) equation (ASCE-EWRI 2005). The Penman–Monteith reference evapotranspiration equation with fixed stomatal resistance values for grass surface is: 
formula
1
where ETo is the reference evapotranspiration (mm/day), Δ is the slope of saturation vapor pressure versus air temperature curve (kPa °C−1), Rn is net radiation at the crop surface (MJ m−2 d−1), G is soil heat flux density at the soil surface (MJ m−2 d−1), T is mean daily air temperature at 1.5–2.5 m height (°C), u2 is mean daily wind speed at 2 m height (m s−1), es is the saturation vapor pressure (kPa), ea is the actual vapor pressure (kPa), es – ea is the saturation vapor pressure deficit (kPa), γ is the psychrometric constant (kPa °C−1), Cn is 900 °C mm s3 Mg−1 d−1 for grass and 1,600 °C mm s3 Mg−1 d−1 for alfalfa, Cd is 0.34 s m−1 for grass and 0.38 s m−1 for alfalfa, λ is the latent heat of vaporization, 2.45 (MJ kg−1). All parameters necessary for computing ETo were computed according to the procedure developed in FAO-56 by Allen et al. (1998).

Aridity index

The aridity index was defined by UNESCO (1979) as the ratio of the average annual precipitation divided by the average annual PET. Monthly and annual aridity indexes during the 1961–2011 period were calculated using the estimated ETo and the precipitation data.

Temporal trend analysis

For the analysis of the temporal trend in ETo and the aridity index, the Mann–Kendall test (Mann 1945; Kendall 1975; Caloiero et al. 2011; Li et al. 2013), a non-parametric method for trend analysis, was used. It should be noted that the Mann–Kendall test statistic is non-dimensional, and it does not offer any quantification of the scale of the trend in the units of the time series under study, but is rather a measure of the correlation of a variable with time and, as such, simply offers information as to the direction and a measure of the significance of observed trends. The Mann–Kendall test statistic S is given as follows: 
formula
2
where xi is the data value at time i, xj is the data value at time tj, n is the length of the dataset and sign( ) is the sign function which can be computed as: 
formula
3
For n >10, the test statistic Z approximately follows a standard normal distribution: 
formula
4
in which Var(S) is the variance of statistic S.

A positive value of Z indicates that there is an increasing trend, and a negative value indicates a decreasing trend. The null hypothesis, H0, that there is no trend in the records, is either accepted or rejected depending on whether the computed Z statistics are less than or more than the critical value of Z statistics obtained from the normal distribution table at the 5% significance level. If |Z| > Z(1−α/2), the null hypothesis of no autocorrelation and trend in dataset is rejected, in which Z(1−α/2) is corresponding to the normal distribution with α being the significance level.

If the data have a trend, the magnitude of the trend can be denoted by trend slope ß (Theil 1950; Sen 1968) 
formula
5
where xi and xj are data values at time ti and tj (i > j), respectively.

Linear regression

Linear regression analysis was applied for analyzing trends in the time series. The main statistical parameter drawn from regression analysis is the slope that indicates the mean temporal change in the variable under study. Positive values of the slope show increasing trends, while negative values of the slope indicate decreasing trends. The total change during the period under observation was obtained by multiplying the slope by the number of years (Tabari & Marofi 2011).

RESULTS AND DISCUSSION

Trends in annual reference evapotranspiration

Dynamics in reference evapotranspiration are of great interest for water resources planning, irrigation management and agricultural production, mainly under rainfed conditions similar to more than 90% of crop production systems in Togo. Annual reference evapotranspiration varied from 1,440 to 1,690 mm at Lomé, from 1,761 to 1,905 mm at Tabligbo, and from 1,839 to 1,990 mm at Sokode (Figure 1). At Lomé, Tabligbo, and Sokode, the maximum annual ETo was obtained in 1984, 2011 and 2007 respectively, and the minimum ETo was registered during 1991, 1980, and 1994 at the same stations respectively. The wettest years during the study period were 2010, 1969, and 1963 at Lomé, Tabligbo, and Sokode respectively, and the driest years were 2000, 1992, and 1961 at the same locations respectively. The statistical analysis revealed that there was a significant increase in ETo at Sokode (Z = 2.29 at α = 0.05) and a highly significant ETo increase at Tabligbo (Z = 2.89 at α = 0.01). Reference evapotranspiration was more stable at Lomé; however, it showed an increasing tendency from 1982 to 1984 and from 1991 to 1998. From 1986 to 1991 and from 1998 to 2001, ETo showed a decreasing tendency at Lomé. Overall, the Z statistic of the annual ETo trend at Lomé was (−0.34), and was not significant with a decreasing trend. Climate parameters, mostly air temperature and ambient air relative humidity, are the driving forces of crop evapotranspiration through the vapor pressure deficit. Linear regressions between annual ETo and the climate variable showed the parameters which influenced the trend of annual ETo during the 1961–2011 period. Figure 2 showed that at Lomé, ETo was more correlated with the air thermal amplitude (Tmax − Tmin) (R2 = 0.91) followed by Tmax (R2 = 0.64), RHmin (R2 = 0.51), (RH max − RHmin) (R2 = 0.43), annual mean RH (R2 = 0.35), and wind speed (R2=0.21). ETo has the least correlation with RHmax, Tmin, and annual Tmean at Lomé (Figure 2). At Tabligbo, ETo had a higher correlation with thermal amplitude Tmax – Tmin (R2 = 0.74) and Tmean (R2 = 0.50) than with Tmax, Rhmax, and RHmin (Figure 3). Therefore, the trend in mean annual ETo at Tabligbo was more influenced by thermal amplitude than other climate variables. At Sokode, ETo had greater correlation with Tmax (R2 = 0.68), Tmin (R2 = 0.26), and the thermal amplitude (R2 = 0.32) than wind speed and relative humidity (Figure 4). Overall, ambient air temperature amplitude was the main climate variable that was correlated with ETo, followed by RH in the coastal areas, Lomé and Tabligbo, while maximum temperature influenced ETo the most at Sokode, which is about 340 km inland. In fact, temperature is an important climate variable that directs the trend in ETo in Togo. The variation in the maximum and minimum temperature in any area affects the vapor pressure of the atmosphere, which ultimately influences the ETo (Ullah et al. 2001). Liang et al. (2012) found an increasing trend of reference evapotranspiration during 1951–2001 for the West Songnen Plain of China under the combined effects of a decreasing relative humidity and increasing air temperature. Similar to the results of this study, the increasing trend in reference evapotranspiration over North America was assumed to be due to a rise in temperature over the past century (Myneni et al. 1997; Milly & Dunne 2001). In the coastal area, there is more variation in the air temperature and relative humidity. Inland, relative humidity is less variable and the temperature is subjected to more variability. From the linear regression analysis, there were increases of 0.99 mm and 0.93 mm in ETo per year at Tabligbo and Sokode, respectively, which represented an increase of 50.6 mm and 47.5 mm over 51 years at Tabligbo and Sokode respectively, while at Lomé the ETo increase over the same period was only 0.5 mm, but with a more increasing and decreasing trend within the 51 year period. The results are confirmed by the Mann–Kendall test and the Sen slope results. Our results are in contrast to the results of Zhang et al. (2011), who reported that RH is the primary driver of ETr in high altitude areas in the Aksu River Basin in Xinjiang Province, northwest China. Gao et al. (2007) found that the actual evapotranspiration had an increasing trend in the western and the northern parts of northeast China, and there was a decreasing trend in most of the eastern part of China, and that the change in precipitation played a key role in the change of estimated actual evapotranspiration. The increasing trend in ETo has been reported in other parts of the world. Tabari et al. (2012) found that both seasonal and monthly reference evapotranspiration in most regions of Iran showed increasing trends. In arid regions of southern Russia, PET showed increasing trends (Golubev et al. 2001) and in Australia, a real reference evapotranspiration would most likely increase over most regions (Whetton 2001). Terink et al. (2013) projected an increase in annual ETo in Northern Africa and the Middle East for the periods of 2010–2030 and 2040–2050. However, several other studies showed, in contrast, decreasing trends in ETo. Jhajharia et al. (2014) reported both seasonal and annual ETo decreased in northeast India. Bandyopadhyay et al. (2009) also studied reference evapotranspiration trends in India and reported decreases in ETo all over India. Yin et al. (2010) showed that variation in ETo in Northeast China was mainly due to a decreasing wind speed rather than an increasing air temperature and decreasing relative humidity. Tabari et al. (2012) showed that in the arid and semi-arid regions of Iran, the increasing trend of reference evapotranspiration was most likely due to a significant increase in minimum air temperature similar to the results of this study, while a decreasing trend of reference evapotranspiration was mainly caused by a significant decrease in wind speed. Temperature and relative humidity are the attributes of the trends in the reference evapotranspiration in Togo. These two climatic parameters manifest through the vapor pressure deficit, which is the driving force of the evaporative demand of ambient air and ultimately influences evapotranspiration as reported by Irmak et al. (2006) and other sensitivity analyses of the reference evapotranspiration to the change in climatic parameters (Wright 1982; Piper 1989; Monteith & Unsworth 1990,). The increased greenhouse effect induces global warming. Thus, global warming is expected to induce an increase in temperature and an increase in water vapor deficit which in turn will cause an increase in evapotranspiration, declines in soil moisture that may offset modest increases in continental precipitation and lead to greater aridity in water limited systems (Zavaleta et al. 2003; Abtew & Assefa 2013). Evapotranspiration, being the major component of the hydrological cycle, will affect crop water requirements and water resources planning and management. In addition, the weather stations' landscapes changed with time due to urbanization at Lomé, Tabligbo, and Sokode, and there is a need to relocate the weather stations for more accurate and representative data collection at all three meteorological stations. Koopmans et al. (2014) showed that urbanization caused an increase in air temperature of 0.22 ± 0.06 °C from 1900 to 2000 at the De Bilt (The Netherlands) weather station. Sertel et al. (2011) indicated that urbanization increased the average temperature in Turkey according to the results of a simulation with the Weather Research and Forecasting (WRF) regional climate model. Changing climate can help to sustain and even increase agricultural productivity and livelihoods by adopting appropriate practices and strategies. However, the confrontation of reference evapotranspiration presented in this study to the precipitation will give more direction to the adoption of best management practices. Identifying changes in ETo can also help in future planning of agriculture-water and recreation projects and identify lower and higher ETo zones for proper planning and management of agricultural projects over Togo and its surrounding agro-ecological zones.
Figure 1

Trends in ETo at Lomé, Tabligbo, and Sokode during the 1961–2011 period.

Figure 1

Trends in ETo at Lomé, Tabligbo, and Sokode during the 1961–2011 period.

Figure 2

Correlation between annual reference evapotranspiration and annual mean climate variables at Lomé during the 1961–2011 period.

Figure 2

Correlation between annual reference evapotranspiration and annual mean climate variables at Lomé during the 1961–2011 period.

Figure 3

Correlation between annual reference evapotranspiration and annual mean climate variables at Tabligbo during the 1961–2011 period.

Figure 3

Correlation between annual reference evapotranspiration and annual mean climate variables at Tabligbo during the 1961–2011 period.

Figure 4

Correlation between annual reference evapotranspiration and annual mean climate variables at Sokoke during the 1961–2011 period.

Figure 4

Correlation between annual reference evapotranspiration and annual mean climate variables at Sokoke during the 1961–2011 period.

Trends in monthly reference evapotranspiration

Long-term average monthly ETo is presented in Figure 5. The maximum monthly mean ETo for the three sites were registered during March and were 144, 177, and 190 mm at Lomé, Tabligbo, and Sokode respectively. Minimum monthly mean ETo were 114 mm at Lomé, 137 mm at Tabligbo, and 136 mm at Sokode and were obtained during July at Lomé and Taligbo and August at Sokode. At Lomé, monthly average ETo had an increasing trend for January, May, June, July, October, November, and December (Table 1). February, March, April, August, and September had a decreasing trend in ETo. Overall, the trend in monthly ETo was not significant, whatever the month considered at Lomé (Figure 6). At Tabligbo, except for March, all of the months registered an increasing trend in ETo during the 1961–2001 period; however, the trend was significant in January and October (p < 0.05) (Table 1), highly significant in July and November (p < 0.01), and very highly significant in December, with Z statistics equal to 3.85 (p < 0.0001) (Figure 6). At Sokode, only January registered a decreasing trend in long-term monthly mean ETo (Table 1). Significant increases in monthly ETo were noted for March, May, June, July, and the increase in September is highly significant (Z = 3.02) (Figure 6). Monthly mean ETo Z-statistics showed seasonal patterns in the trends of monthly ETo that correspond to seasonal precipitation patterns at Lomé, Tabligbo, and Sokode. The change in daily and monthly meteorological variables in different locations might have a different effect on daily and monthly reference evapotranspiration (Djaman et al. 2015). Jhajharia et al. (2012) reported significant positive trends in ETo only for April through June, with seasonal pattern that did not correspond to either precipitation or streamflow in the Rio Puerco Basin. A significant positive trend magnitude was found for the months of September, October, and November, with Theil–Sen's slope equal to 1.08, 1.15, and 1.30 mm/year in the Soenath River Basin, Chhattisgarh (India) during the 1960–2008 period (Chakraborty et al. 2013). Kosa & Pongput (2007) reported that temporal distributions of mean monthly reference evapotranspiration were affected by the meteorological variables, especially temperature and net radiation, because the temporal distribution pattern of mean monthly reference evapotranspiration was similar to the temporal distribution pattern of temperature and net radiation.
Table 1

Monthly Sen's slopes estimated by Mann–Kendall test

Months Lomé Tabligbo Sokode 
January 0.042 0.149 −0.058 
February −0.039 0.057 0.006 
March −0.146 −0.121 0.127 
April −0.009 0.008 0.125 
May 0.031 0.034 0.119 
June 0.018 0.070 0.136 
July 0.030 0.230 0.126 
August −0.060 0.060 0.085 
September −0.029 0.028 0.129 
October 0.029 0.079 0.076 
November 0.035 0.113 0.103 
December 0.040 0.202 0.073 
Months Lomé Tabligbo Sokode 
January 0.042 0.149 −0.058 
February −0.039 0.057 0.006 
March −0.146 −0.121 0.127 
April −0.009 0.008 0.125 
May 0.031 0.034 0.119 
June 0.018 0.070 0.136 
July 0.030 0.230 0.126 
August −0.060 0.060 0.085 
September −0.029 0.028 0.129 
October 0.029 0.079 0.076 
November 0.035 0.113 0.103 
December 0.040 0.202 0.073 
Figure 5

Long-term average monthly ETo at Lomé, Tabligbo, and Sokode during the 1961–2011 period.

Figure 5

Long-term average monthly ETo at Lomé, Tabligbo, and Sokode during the 1961–2011 period.

Figure 6

Monthly trend of ETo at Lomé, Tabligbo, and Sokode over 51 years (1961–2011).

Figure 6

Monthly trend of ETo at Lomé, Tabligbo, and Sokode over 51 years (1961–2011).

Trends in aridity index

In Togo, the increase in annual evapotranspiration is associated with decreasing trends in annual precipitation. Under rainfed and irrigated agriculture, the difference between precipitation and ETo, or the ratio of precipitation over ETo named the aridity index, is very important in water resources planning, complementating of irrigation management, and conservation agriculture. In Togo, according to the three sites in this study, the annual aridity index varied from 0.26 to 0.99 at Lomé, 0.38 to 0.98 at Tabligbo, and from 0.45 to 1.08 at Sokode (Figure 7). The 1961–2011 period mean aridity indexes were 0.55 at Lomé, 0.63 at Tabligbo, and 0.70 at Sokode. Therefore, Lomé and Tabligbo are in the dry sub-humid zone and Sokode is in the wet humid zone according to the classification of UNESCO. Increased aridity is a robust proximate cause of desertification, both indirectly through greater rainfall variability and directly through prolonged droughts (Costa & Soares 2012; Hrnjak et al. 2013). Years or months when the aridity index is greater that unity are broadly classified as wet since precipitation met evaporative demand. Similarly, years or months with an aridity index less than unity are broadly classified as dry. The Mann–Kendall test revealed a declining trend in the ratio of precipitation/ETo, which adversely implies an increase in the severity of the aridity index at all the sites. However, the trend was significant at Tabligbo and Sokode at a 95% confidence interval while it is not significant at Lomé, although it had a deceasing trend at that site similar to the others. The monthly aridity index varied from 0.07 to 1.9 at Lomé, 0.06 to 1.15 at Tabligbo, and from 0.02 to 1.9 at Sokode (Figure 8). The aridity index showed two patterns at Lomé and Tabligbo corresponding to the two cropping seasons in south Togo, while at Sokode it presented the pattern of the long crop growing season in the central region of Togo (Figure 9). The Mann–Kendall test revealed different trends in the monthly aridity index depending on the month and location. A significant increase in aridity severity was observed in December at Lomé and a significant reduction in the severity of the aridity index was noted in August and October at Lomé. Similar to the results of this study, Some'e et al. (2013) reported a mean annual P/ETo that varied from 0.06 to 1.0 in Iran. During the 1951–2010 period, the aridity index over Italy varied from 0.22 to 3.08 with a national territory average of 0.9 (Salvati et al. 2013). For production seasonality, the monthly aridity index should be a better indicator of the onset and establishment of the crop growing season, and the choice of appropriate crop species within rainfed agriculture systems. The increasing trend in the aridity index is an expression of the lack of moisture or water for crop production. Some studies in Togo revealed a rainfall deficit since 1970 (Klassou 1996; Badameli 1996, 1998; Adewi 2002; Adewi et al. 2010). Adewi et al. (2009) found that there is a relation between the rainfall disturbance and water stress at the critical period of maize growth and development in the country. Precipitation will be able to cover crop evapotranspiration demands when the aridity index is equal to or greater than 1. Crop actual evapotranspiration is estimated by the product (kc*ETo) (Allen et al. 1998; Djaman & Irmak 2013), with crop coefficient kc that varies with crop growth, crop development, watering regimes, and the environment (Djaman & Irmak 2013). Thus, the long-term monthly average aridity index could be used for setting the planting period under rainfed production. With regard to the monthly aridity index, the period November–March is considered dry throughout the country, and the month of August is considered dry only in the maritime region. With regard to the aridity index, in the maritime region of Togo where Lomé and Tabligbo are located, late March–early April is well indicated for the planting period during the first growing season and early September is the appropriate time of planting during the second growing season. Late April is indicated for the beginning of the crop growing season in the central region of Togo where Sokode is located. From May to October, the aridity index was close to or greater than unity except in August at Lomé and Tabligbo. This explicitly expresses more abundant rainfall, such as to counterbalance or exceed what is required by PET. The onset of the cropping season, using the aridity index, coincided with the results of Adewi et al. (2010), who delimited the beginning and the end of the crop growing season across Togo based on historical climatic data of the 1950–2000 period. Sogbedji (1999) found that the decrease in seasonal rainfall amount represents a serious threat to maize growth during the second growing season. In Togo, where crop production is essentially rainfed, water management requires more attention to better planting date choice and the crop species with regard to water availability and crop evapotranspiration, as proposed by Adewi et al. (2010). The increasing trend toward aridity in recent times has been reported by Dregne & Chou (1992), Nicholson (2003), Hanafi & Jauffret (2008), and Gaughan & Waylen (2012). Amégadjé (2007) reported an aridity index of less than 0.75 with diminishing precipitation and the number of rainy days in the savannah region of Togo. Over the past 60 years, Togo has experienced three major droughts, in 1942–1943, 1976–1977, and 1982–1983, leading to severe famines. Predictions for 2025 by the SCENGEN model showed that the declining trend in rainfall is set to continue and the country is expected to be 10–30% drier than the previous 50 years (CNI 2001). Rainfall amount and temporal distribution is primordial to crop production. Whenever the aridity index is high, uniform distribution of rainfall may meet crop evapotranspiration and reduce water loss through excessive runoff and deep percolation.

The results of this study may constitute some useful information required by different actors in development, and confirm the ongoing strategies for the sustainability of crop production in Togo. With irrigated agriculture less than 2% of the country's total cultivated land, crop production in Togo is heavily dependent on natural rainfall. Thus, the amount and temporal distribution of rainfall and other climatic factors during the growing season are critical to crop productivity. Rainfall variability and associated droughts have been major causes of food shortage and famine in Togo. Droughts are characterized by a progressive increase in temperature, a decline in rainfall events, a reduction in the number of rainy days, and a shift in the ratio of rainfall to PET. Simulations made led to an overall increase in temperatures ranging from 1.5 to 5.3 °C between the latitudes of Togo (Mikemina 2013,). Togo's mean annual temperature has increased by 1.1 °C since 1960, an average rate of 0.24 °C per decade (UNDP 2011). With changes in climate parameters, mostly an increasing trend in air temperature combined with an increasing trend in reference evapotranspiration, several actions have been taken by agricultural and water resources actors to contrast the effects of climate change on Togo's agriculture. Effective adaptation strategies were designed and promoted to cope with the potential impacts of climate change, among which are: integrated water management, production of improved seeds, conserving and restoring soil quality (amendments, water and soil conservation, conserving soil fertility), improving the agro-meteorological information system, and enhancing crop calendars, plant protection, improving agricultural practices, developing breeding species that are more resistant to climate conditions, and management of mangroves (UNDP 2011). As climate conditions change, crop growers are increasingly receptive to new agricultural technologies offered by extension services. The use of drought-resistant seeds is becoming more common, which minimizes the risk of crop failure due to prolonged drought. The PNIASA program initiated by the government of Togo is consistent with the National Poverty Reduction Strategy, and has a balanced focus of investment in support of improved agricultural production, improving the institutional framework, and physical infrastructure for higher productivity in the agricultural sector. Several other actions are being taken by the government of Togo, such as rehabilitation of water reservoirs, rehabilitation of irrigation schemes, and agricultural land development of 666 hectares at Mission-Tove and 89 hectares at Agome Glozou, and implementing the national environmental policy and disaster management policy. Despite the adoption of strategic options, there is a need to continue implementing them and more participative decision-making is necessary for the durability of the innovation. Moreover, policy-makers should be involved at every step from the introduction to the adoption process. In addition, more research should be done on all of the strategic options to strengthen the system.
Figure 7

Trends in aridity index at Lomé, Tabligbo, and Sokode during the 1961–2011 period.

Figure 7

Trends in aridity index at Lomé, Tabligbo, and Sokode during the 1961–2011 period.

Figure 8

Comparison of the 1961–2011 period average monthly aridity index at Lomé, Tabligbo, and Sokode.

Figure 8

Comparison of the 1961–2011 period average monthly aridity index at Lomé, Tabligbo, and Sokode.

Figure 9

Monthly average precipitation and trend in annual precipitation at Lomé, Tabligbo, and Sokode during the 1961–2011 period.

Figure 9

Monthly average precipitation and trend in annual precipitation at Lomé, Tabligbo, and Sokode during the 1961–2011 period.

CONCLUSIONS

The objective of this study was to analyze the trend in the grass-reference evapotranspiration (ETo) calculated by FAO-56 Penman–Monteith method using historical data from three weather stations through the years 1961–2011 and to identify trend in the aridity index as an indicator of change in climate in Togo. Results showed that annual reference evapotranspiration varied from 1,440 to 1,690 mm at Lomé, from 1,761 to 1,905 mm at Tabligbo, and from 1,839 to 1,990 mm at Sokode. The Mann–Kendall test revealed a significant increase in annual ETo at Tabligbo and Sokode. Annual ETo was more stable in Lomé, with a non-significant decrease. In Togo, according to the three sites under study, the annual aridity index varied from 0.26 to 0.99 at Lomé, 0.38 to 0.98 at Tabligbo, and from 0.45 to 1.08 at Sokode. The 1961–2011 period mean aridity indexes were 0.55 at Lomé, 0.63 at Tabligbo, and 0.70 at Sokode. The Mann–Kendall test revealed a declining trend in the ratio of precipitation/ETo, which adversely implies an increase in the severity of the aridity at all the sites in this study. Information regarding trends in the aridity index as a result of climate change is necessary for policy-makers and water resources managers within the context of water resources management, hydrology, agriculture, and the environment. These results may constitute some useful information required by different levels of actors in development, particularly in reducing the vulnerability of rainfed crop growers in Togo. The findings of this research suggest the need to consider ETo changes in planning for agricultural and water resources projects in the dynamics of climate change. Most of the rural poor households in Togo rely for their livelihood and food security on highly climate sensitive rainfed subsistence or small-scale farming, pastoral herding and direct harvesting of natural services of ecosystems such as forests and wetlands (CNI 2001). Therefore, adaptation efforts to climate change should target conservative water resources management technologies, crop breeding for more drought and heat tolerant varieties to increase crop productivity under adverse weather, and promote and support surface runoff water harvesting and the development of small-scale irrigation in upland and lowland areas.

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