Gezira of agric. 14(2): 113-120(2016)

SHORT NOTE

Factors affecting Pan Evaporation

in the hyper arid region of the Sudan and the quality of the data of National Institute of Desert Studies meteorological station

Habiballa A. Mohamed

National Institute of Desert Studies, University of Gezira,Wad Medani, Sudan

Evaporation is an important climate element for agricultural production, particularly in the hyper arid and arid regions where irrigation water becomes the most limiting factor in terms of availability and cost (Mohamed, 2015).The magnitude of evaporation depends on other climate elements like air temperature, relative humidity, wind speed and solar radiation (Liu et al., 2011; Mohamed and Mohamed, 2011).The water needs of crops, on the other hand, depends on evapotranspiration and on the crop factor, where evapotranspiration includes both evaporation and transpiration (Brouwer and Heibloem,1986).

Determination of the exact crop water requirement depends on the correct measurements and estimation of evapotranspiration. Precise estimation of evapotranspiration is vital in agriculture and hydrology (ElAlafandi and Abdrabbo, 2015). There are numerous methods for the estimation of evapotranspiration including energy budget, aerodynamic and numerical methods in addition to various methods of measurements including atmometers, lysimeters, Class (A) Pan and Piche tube. One of the simplest and reliable methods of measurements is the use of Class (A) pan. Because of the importance of these measurements, the National Institute of Desert Studies (NIDS)established in 2008 a meteorological station within its experimental farm, (17.92^° N, 31.17^◦ E).The station measures air and soil temperatures; wet and dry bulb temperatures; wind speed and direction, rainfall, Piche evaporation and Class Pan evaporation.

Habiballa A. Mohamed

This study investigates the effects of air temperature, relative humidity and wind speed and their combinations on Class A pan evaporation and develops prediction equations of evaporation using the data sets for March 2008 to December, 2010. The study also investigates the quality of NIDS meteorological station data for the full years 2009 to 2011 through comparison with the nearest meteorological stations. Table 1. shows the mean of the daily elements for each of the complete years 2009 to 2011.

Table 1. Climate elements of NIDS for 2009 to 2011.

Piche evap. (mm/da)

Class (A)

pan evap.

(mm/day)

Relative humidity

(%)

Wind speed (km/day)

Mean temp.(° C)

Year

20.1

21.0

20.4

20.5

16.6

16.9

16.7

27.6

34.9

44.5

35.6

201.7

199.3

189.3

196.7

27.5

27.6

.662

227.

2009

2010

2011

Mean

It is observed that the means for Pan and Piche evaporation for the three years were almost similar and also the means of wind speed and air temperature. There was a clear and successive increase in the percentage relative humidity through the years. The increase in the percentage relative humidity could be attributed to the existence of the lake of Marowe dam. Such increase may have a negative impact on the productivity and quality of dry dates which is produced mainly in northern Sudan. In fact, farmers have reported a decline in productivity, but this remains to be investigated.

When compared to either of Karima, (18.56^◦ N, 31.58^◦ E) and Dongola, (19.17^◦ N, 30.48^◦ E) data normals of 1961/1990, 1971/2000 and 1981/2010, (Table 2) show that mean air temperature was higher in Karima, while that of Dongola was comparable to the air temperature of NIDS which lied at almost an equidistance from both Karima and Dongola. Mean air temperature increased progressively with time in either of Karima and Dongola due to global warming.

Pan Evaporation in the arid region of the Sudan

Wind speed was lower in NIDS compared to both Dongola and Karima. Piche evaporation was higher in both Karima and Dongola compared to NIDS, and this might be due to the higher wind speeds in both stations, and also to the higher air temperature in Karima, and the higher relative humidity in NIDS.

Table 2. Climate normals for Karima and Dongola for various periods.

Piche evaporation (mm/day)

Relative humidiy (%)

Wind speed (km/day)

Mean temp.(°c)

Period

20.3

20.7

20.0

18.9

20.7

18.9

23.0

22.0

25.0

24.0

Karima

371.5

368.0

499.2

Dongola

380.2

390.4

345.6

29.0

29.2

29.5

27.3

27.6

1961/1990

1971/2000

1981/2010

1961/1990

1971/2000

1981/2010

na: not available

These differences justify the establishment of NIDS meteorological station which was supposed to serve NIDS experimental purposes and also to avail data for other needs.

Figure1 shows the regression of Class (A) pan evaporation on mean daily air temperature. Evaporation increased with increase in air temperature throughout the period, with high correlation, (R=0.86), high significance, (P<0.001) and a standard error of 2.1. Because of its great effects on the magnitude of evaporation, particularly in the arid regions, air temperature was used in some studies as a single factor to predict pan evaporation (Manoj and Mrugen , 2013).

Habiballa A. Mohamed

Figure 1. Pan evaporation vs. mean temperature.

Figure 2 shows the regression of Class (A) Pan evaporation on wind speed, (WS). The effect is also highly significant (P<0.001), with an (R) of 0.65 and a SE of 3.1. Pan evaporation increased as wind speed increased.

.. Figure 2. Pan evaporation vs. wind speed

Figure 3 shows the effect of relative humidity on Class (A) pan evaporation. There was a highly significant, (P< 0.001), negative correlation, (R = 0.75) where evaporation decreased with the increase in relative humidity percentage. When the pan evaporation was correlated to both mean air temperature (T), and percentage relative humidity (RH%), the correlation was even higher, with an R of 0.91 and a SE of as low as 1.7 so that Class (A) pan evaporation (PE) can be estimated from the equation:

PE=7.9+0.48T-0.15RH…………..( 1 )

Pan Evaporation in the arid region of the Sudan

Figure 3. Pan evaporation vs. Relative humidity.

On the other hand, the three elements together showed a higher effect on pan evaporation, with an (R) of 0.93, P of <0.001 and a SE of 1.5. The equation connecting the three elements is:

PE=3.2+0.42T-0.13RH+0.02WS …( 2 )

The latter equation has a better predictability if the data on wind speed were also available. However, the former equation is equally sufficient if there are no wind speed data.

Figure 4 shows the regression of Class A pan evaporation on Piche evaporation throughout the period. The correlation coefficient is 0.97 and the significance is P< 0.001.

Habiballa A. Mohamed

Figure 4. Pan evaporation vs. Piche evaporation.

Accordingly, an equation for the prediction of Class (A) pan Evaporation from that of the Piche( Pi) data can be written as follows:

0.62…………..( 3 )- PE=0.84 Pi.E

This equation can be used in the hyper arid region in areas where no Pan evaporation data are available. Piche evaporation data while can easily be obtained, they are of lesser quality because the Piche atmometer usually overestimates evaporation by varying degrees depending on climatic zone under consideration. In the Sudan, the difference between the Class (A) pan reading and that of the Piche becomes larger as latitude increases northward.

It is concluded from this study that, NIDS meteorological station data generally lies with an acceptable magnitude and although not too far from those of Karima and Dongola, they are still different, which justify the importance of the station. It is also clear that pan evaporation is affected positively by the mean temperature and wind speed and negatively by the relative humidity, and that it can be estimated from regression equations.

It is recommended to strengthen the station by addition of equipments for measurements of pressure, solar radiation (incident, reflected and net) and sunshine duration and to replace the old instruments.

Habiballa A. Mohamed

REFERENCES

Brouwer, C and M.Heibloem. 1986. Irrigation water

management: Irrigation water needs. A Training Manual. FAO. Rome, Italy.

ELAfandi, G. and M. Abdrabbo. 2015. Evaluation of

Reference evapotranspiration equations under

current climate conditions of Egypt.Turkish Journal

of Agriculture,Food Science and Technology

3(10):819-825.

Liu Xiaomang, Zheng Hongxing, Zhang Minghwa

and Liu Changming. 2011. Identification of

dominant climate factor for pan evaporation trend in

the Tibetan Plateau. Jounal of Geographical

Sciences 21(4):594-608.

Mohamed, H. A. 2015. Correlating annual Piche

evaporation over Sudan and South Sudan to

latitudes, longitudes and altitudes. Ethiopian Journal

of Environmental Studies and Management 8(3):301-

307. doi:http://dx.doi.org/10.4314/ejesmv8i3.7

Mohamed, H. A. and A. A. Mohamed. 2011.

Estimation of evaporation in the hyper arid region of

northern Sudan using different methods. Gezira

Journal of Agricultural Science 9(1):21-31.

Manoj,G.J and D.B. Mrugen. 2013. Modelling pan

evaporation using mean air temperature and mean pan

evaporation relationship in middle south Saurashtra Region. International Journal of Water Resources and Environmental Engineering 5(11):622-629.

مجلة الجزيرة للعلوم الزراعية المجلد14، العدد(2)2016م

العوامل المؤثرة على خزان البخر في الاقليم فوق القاحل بالسودان وجودة معلومات محطة الارصاد التابعة للمعهد القومي لدراسات الصحراء

حبيب الله عبد الحفيظ محمد

المعهد القومي لدراسات الصحراء، جامعة الجزيرة، ود مدنى، السودان

الخلاصة

تم تحليل معلومات الأرصاد الخاصة بمحطة المعهد القومي لدراسات الصحراء للفترة 2009والى 2011 و ذلك لدراسة اثر درجة حرارة الهواء و الرطوبة النسبية و سرعة الرياح على معدل البخر من خزان البخر الأمريكي Class A Pan)) لما للبخر من أهمية في تحديد الاحتياجات المائية للمحاصيل. كما هدفت الدراسة للتأكد من جودة المعلومات و ذلك من خلال مقارنتها مع متوسطات طويلة المدىNormals)) لمعلومات المحطات القريبة و هي محطات دنقلا وكريمة. أوضحت نتائج الدراسة الارتباط الوثيق بين البخر من جهة و درجة الحرارة و الرطوبة النسبية و سرعة الرياح من الجهة الأخرى و أوضحت مدى إمكانية تقدير البخر من هذه العوامل باستخدام المعادلات المختلفة. كذلك أوضحت نتائج الدراسة و مقارنة مع متوسطات معلومات المحطات القريبة المـــــوجـــــودة فـــــي دنـــــقـــــــلا

وكريمة أن المعلومات الإرصادية تقع في إطار المدى المتوقع في مثل هذا المناخ مع وجود الاختلافات الخاصة بالمحطة مما يبرر أهميتها العلمية و العملية للمعهد و لكل المؤسسات العلمية الأخرى.