Decision support systems Deficit irrigation Model MIRRIG Model SADREG Northeast Syria This study explores the use of drip and surface irrigation decision support systems to select among furrow, border and drip irrigation systems for cotton, considering water saving and economic priorities. Data refers to farm field observations in Northeast of Syria. Simulation of drip irrigation was performed with MIRRIG model for various alternatives: double and single row per lateral, emitter spacing of 0.5 and 0.7 m, six alternative pipe layouts and five self-compensating and non-compensating emitters. Furrow and border irrigation alternatives were designed and ranked with the SADREG model, considering lasered and nonlasered land levelling, field lengths of 50e200 m and various inflow discharges. A multicriteria analysis approach was used to analyse and compare the alternatives based upon economic and water saving criteria. Results for surface irrigation indicate a slight advantagefor long non-lasered graded furrows; non-lasered alternatives were selected due to economic considerations. For drip irrigation, the best ranking is for systems having lower costs, mainly with double rows per lateral and larger emitter spacing. Comparing surface and drip irrigation systems, despite low cost, drip alternatives may lead to 28e35% water saving relative to improved graded furrows, and increase water productivity from 0.43 kg m À3 to 0.61 kg m À3 , surface irrigation provides higher farm returns. Drip irrigation is selected only when high priority is assigned to water saving. Deficit irrigation does not change this pattern of results. Apparently, adopting drip irrigation requires appropriate economic incentives to farmers, changes in the structure of production costs and increased value of production. b i o s y s t e m s e n g i n e e r i n g 1 2 2 ( 2 0 1 4 ) 7 4 e9 0 http://dx.

Improving surface irrigation systems for cotton in Ras-El-Ain district, Northeast Syria, needs finding alternative solutions that provide for both water saving and farm economic benefits in a context of small and family farms. Multicriteria analysis was used to evaluate and rank a set of furrow and border irrigation alternatives, with and without precise land leveling, that were created with the decision support system SADREG. This approach allowed to consider various criteria, mainly water saving and farm economics. Results show that both graded furrow and border alternatives are acceptable, with a slight advantage for graded furrows. Alternatives without land leveling have shown to be more appropriate when focusing farm economic results, while alternatives including land leveling were selected when priorities were assigned to water saving. These results relate with higher costs of alternatives that consider land leveling. Equipment for appropriate control of inflow rates was considered for all cases. The improved alternatives may lead to savings of 20-28% of irrigation water and increasing the irrigation water productivity from present 0.31 to 0.44 kg m −3. When the same alternatives were ranked for a 20% deficit irrigation their rankings changed, with reduced ranks of alternatives requiring land leveling. This is due to the fact that yields and yield values are reduced with deficit irrigation, thus making it less favorable to select alternatives that imply higher costs. The study shows that adopting more advanced but more costly irrigation technologies aimed at water saving requires appropriate economic incentives, training of farmers and an institutional framework able to support the sustainable use of water in irrigation.

The computation of the grass reference evapotranspiration with the FAO56 Penman-Monteith equation (PM-ET o ) requires data on maximum and minimum air temperatures (T max , T min ), actual vapour pressure (e a ), shortwave solar radiation (R s ), and wind speed at 2 m height (u 2 ). Nonetheless, related datasets are often not available, are incomplete, or have uncertain quality. To overcome these limitations, several alternatives were considered in FAO56, while many other procedures were tested and proposed in very numerous papers. The present study reviews the computational procedures relative to predicting the missing variables from temperature, i.e., the PM temperature approach (PMT), and estimating ET o with the Hargreaves-Samani (HS) equation. For the PMT approach, procedures refer to predicting: (a) the dew point temperature (T dew ) from the minimum or the mean air temperature; (b) shortwave solar radiation (R s ) from the air temperature difference (TD = T max -T min ) combined with a calibrated radiation adjustment coefficient (k Rs ); and (c) wind speed (u 2 ) using a default value or a regional or local average. The adequateness of computing T dew from air temperature was reassessed and the preference for using an average u 2 has been defined. To ease the estimation of R s, for the PMT approach and the coefficient of the HS equation, multiple linear regression equations for predicting k Rs were developed using local averages of the temperature difference (TD), relative humidity (RH) and wind speed as independent variables. All variables were obtained from the Mediterranean set of CLIMWAT climatic data. Two types of k Rs equations were developed: climate-focused equations specific to four climate types -humid, sub-humid, semi-arid, and hyper-arid and arid -, and a global one, applicable to any type of climate. The usability of the k Rs equations for the PMT and HS methods was assessed with independent data sets from Bolivia, Inner Mongolia, Iran, Portugal and Spain, covering a variety of climates, from hyper-arid to humid. With this purpose, ET o estimated with PMT and HS (ET o PMT and ET o HS ) were compared with PM-ET o computed with full data sets to evaluate the usability of the k Rs equations. Adopting the climate-focused k Rs equations with ET o PMT , the RMSE averaged 0.59, 0.64, 0.65 and 0.72 mm d −1 for humid, sub-humid, semi-arid, and arid and hyper-arid climates, respectively, while the RMSE values relative to ET o HS when using the respective climate-focused k Rs equations averaged 0.58, 0.60, 0.60 and 0.69 mm d −1 for the same climates. These results are similar to those obtained with the k Rs global equation. The accuracy of the PMT approach when using the k Rs equations was also evaluated when one, two, or all three T dew , R s and u 2 variables are missing and the resulting goodness-of-fit indicators demonstrated the advantage of the combined use of observed and estimated weather variables. The usability of the k Rs equations for an efficient parameterization of both the PMT approach and ...