Department of Agricultural Engineering

Due to the lack of standard Agro-climatic Weather Stations (AWS) in Saudi Arabia, simple conversion formulas were derived to find the average daily ETo value per month for 29 weather
stations. The Hargreaves (HRG) formula was used instead of the Penman-Monteith formula due to the ease of calculation of HRG formula, as it almost require only temperature. For each station, two formulas were derived considering both standard and non-standard AWS. Results show very good statistical representation of the formulas, with average root mean squared deviations of 0.73 and 0.57 and the mean percent errors of 1.22%, and 1.12% while considering the standard and non-standard AWS, respectively. Results also confirm the importance of temperature correction when using data from non-standard AWS, especially for the stations in the Middle to Midwest region (e.g. Arriadh,
AlQassim, and Almadina); where the errors of using non-standard AWS data may be up to +24% of the correct ETo value, which results in a massive waste of water.

Friction head loss equations and friction correction factors were evaluated and compared to field observations collected from thirty center‐pivots with laterals made of PVCs. The friction head loss equations include Darcy‐Weisbach (D‐W), Hazen‐Williams (H‐W), and Scobey, in addition to a proposed equation valid for smooth and rough pipe types and for all turbulent flow types. The proposed equation was developed by combing the equations of D‐W and H‐W, along with the multiple non‐linear regression technique. The friction correction factors were computed using the typical Christiansen, modified Christiansen, Anwar, and Alazba formulae. The evaluation has been based on statistical error techniques with observed values as a reference. With the combination of modified Christiansen, Anwar, and Alazba formulae, the results revealed that the magnitudes of friction head loss calculated using D‐W equation, H‐W equation, and proposed equation were in agreement with field observations. The root mean square deviation (RMSD) values were found to be ranging from 1.6 to 1.7 m. As expected and when the typical Christiansen friction correction factor was used with the D‐W equation, with the H‐W equation, and with the proposed equation, the results showed poor agreement between observed and computed friction head loss values. This was clearly reflected by the high RMSD values that were ranging from 5.4 to 5.8 m. On the other hand, there was agreement between observed friction head loss values and those calculated using Scobey equation, invalid for PVC pipe type, when combined with the typical Christiansen formula. This interesting finding led to improved results of Scobey equation through a developed Cs coefficient suitably valid for PVC pipe type via analytically mathematical derivation. And accordingly, the RMSD value dropped from about 8.6 to 1.6 m.

Problem statement: Reference agro-climatic Weather Stations (WS) are rarely found in newly reclaimed areas. The usage of weather data from non-reference WS may lead to inaccurate estimations of Evapo Transpiration (ET), especially if the non-reference stations are distant from the reclaimed location. Approach: Weather data from four WS located at Riyadh were used to calculate ET by using Penman Monteith (PM) and Hargreaves equations. PM equation was applied with both alfalfa and grass reference crops. Calculations were done with and without temperature correction for non-reference weather stations. All calculations were compared with measured lysimeter data and corrections in Hargreaves formula were suggested. Results: (1): Weather data from non-reference WS can be used safely to calculate ET only when temperature corrections are applied. (2) Hargreaves formula underestimates ET at all locations in the study area. By applying the simple linear correction to the data, highly acceptable results are obtainned. (3) The ET ratio between alfalfa and grass in Riyadh is 1.25. Conclusion: The study concluded that temperature correction for non-reference WS is essential to ensure acceptable ET calculations. Usage of Hargreaves formula is recommended with the corrections suggested in the study due to its simplicity.

Water management in Saudi Arabia is facing major challenges due to the limited water resources and increasing uncertainties caused by climate change. This paper presents an analysis of the daily, monthly and annual mean, maximum and total rainfall records of the Saudi meteorological data for nineteen cities covering the all thirteen districts for more than three decades (1980 to 2010). An increased annual total and maximum rainfall was observed for 6 cities with the decreased trends in both parameters for the same number of cities. For the reaming seven cities, however, an increased annual maximum rainfall trend was seen in opposite to the decreased annual total rainfall. This opposite rainfall trend is also seen for the 12 months of the year for the same city which signifies the variability of changing climate pattern not only in different districts but also during the year. The increased rain intensities due to climate change results in flooding of short in urban centers which are designed based on dry climates. Finally, the recommendations are made for the rooftop rainwater harvesting and management to cope with the increasing short-duration floods and to provide an additional source of drinking water. Co-operations among official efforts, local NGOs and public are suggested for better results of water supply management due to rainwater harvesting in Saudi Arabia in a changing climate associated with increased rainfall intensities.