Calibration of Hargreaves–Samani equation for estimating reference evapotranspiration in semiarid and arid regions

The Penman–Monteith (FAO-56 PM) equation is suggested as the standard method for estimating evapotranspiration (ET₀) by the International Irrigation and Drainage Committee and Food and Agriculture Organization (FAO). On the other hand, the Hargreaves–Samani (HS) equation is an alternative method compared with the FAO-56 PM equation. In the present study, the original coefficient C of the HS equation is calibrated based on the FAO-56 PM equation for estimating the reference ET₀ from 15 meteorological stations in central Iran (about 170,000 km²) under semiarid and arid conditions. After calibration, the new values for C are ranged from 0.0018 to 0.0037. The mean bias error (MBE), the root mean square error (RMSE), and the ratio of average estimations of ET₀ (R) values for all stations are ranged from 0.12 to 5.38, ?5.35 to 1.15 mm d^?1 and 0.64 to 1.28 for the HS equation and from 0.12 to 2.48, ?2.2 to 0.60 mm d^?1, and 1.00 to 1.05 for the calibrated Hargreaves–Samani equation (CHS), respectively. Results indicate that the average RMSE and MBE values are decreased by 40% and 66%, respectively. Relationships for calibrating the C coefficient on the basis of annual average of daily temperature range (ΔT) and wind speed (V) are proposed, calibrated, and validated. Hence, the CHS equation can be used for ET₀ estimates with acceptable accuracy instead of the FAO-56 PM method.     

Crop sequences and fertilization affect soil vital enzyme activities

This experiment was conducted in split plots based on randomized complete block design with three replications. Three crop sequences: (R1): chickpea, sunflower, wheat, and canola; (R2): green manure, chickpea, green manure, wheat, green manure, and canola; (R3): canola, wheat, and canola were used as main plots. Sub plots consisted of six methods of fertilization: (N1): farmyard manure; (N2): compost; (N3): chemical fertilizers; (N4): farmyard manure + compost; (N5): farmyard manure + compost + chemical fertilizers; and (N6): control. Results showed that the enzyme activities were higher in the N4 treatment. The highest amount of acid phosphatase, protease, dehydrogenase activity, and grain yield was observed in R2 sequence. The highest urease activity (58.6 µg g^?1 h^?1) was obtained in R2N4 treatment. In R2N4 treatment using in-farm inputs, a non chemical fertilizer system can be carried out to improve soil biological activity.     

Effects of inoculation with stress-adapted arbuscular mycorrhizal fungus Glomus deserticola on growth of Solanum melogena L. and Sorghum sudanese Staph. seedlings under salinity and heavy metal stress conditions

The beneficial effects of a Glomus deserticola strain isolated from the rhizosphere of grasses (belonging to Poaceae family) growing along the industrial waste from a distillery were investigated under stress conditions. The study was conducted to assess the efficacy of the arbuscular mycorrhizal (AM) fungal ecotype in salinity and heavy metal (HM) tolerance of eggplant (Solanum melongena L.) in soils amended with various stress levels of NaCl, zinc and cadmium. Mycorrhizal (M) seedlings produced a significantly (p < 0.05) greater growth response and were more tolerant to salt and HM stresses than nonmycorrhizal (NM) seedlings in all treatments. The HM contents in the plant tissues were significantly higher in M than NM eggplants. Furthermore, when the efficacy was compared with other AM isolates in HM-polluted soils with Sudan grass (Sorghum sudanese Staph.) as a test plant, the AM ecotype responded best to these soils, as evident from the significantly greater growth response and its aggressiveness in colonizing roots in all soil types tested. These results suggest that this G. deserticola ecotype can be used as an effective tool to alleviate the adverse effects of excessive salinity and HM toxicity on plant growth. Finally, the isolate may have potential in the bioremediation of polluted soils.     

HYDRUS simulations of the effects of dual-drip subsurface irrigation and a physical barrier on water movement and solute transport in soils

Subsurface drip irrigation systems, compared to other irrigation systems, enhance the delivery of water and nutrients directly into the root zone. However, in light-textured soils, certain quantities of water may percolate below the root zone due to the subsurface position of drip lines and/or poor management of irrigation systems. The main objective of this paper is to evaluate three technologies to enhance a spatial distribution of water and solutes in the root zone and to limit downward leaching. The three technologies include (a) a physical barrier, (b) a dual-drip system with concurrent irrigation, and (c) a dual-drip system with sequential irrigation. To achieve this objective, we performed computer simulations using the HYDRUS (2D/3D) software for both bare and vegetated soils. The results indicate that the physical barrier is more efficient than dual-drip systems in enhancing the water distribution in the root zone while preventing downward leaching. On the other hand, the dual-drip system improves water distribution in sandy soils. Additionally, the dual-drip system with sequential irrigation, followed by the dual-drip system with concurrent irrigation, is the most efficient in limiting downward leaching of solutes.     

Efficiency of some molecular markers linked to rhizomania resistance gene (Rz 1 ) for marker assisted selection in sugar beet

Sugar beet (Beta vulgaris L.) is one of the two major products supplying sugar (sucroses) in the world. Rhizomania is one of the most destructive diseases of sugar beet world-wide. Holly is the major source of resistance to rhizomania. The objectives of this study were to identify the dominant homozygous genotypes resistant to rhizomania using ZN1 molecular marker, to field evaluate S₁ progenies of plants already proved to be containing the marker and also to determine the relationship of this and other SCAR (sequence characterized amplified region) markers with SNP1 (single nucleotide polymorphism) marker associated with the Rz ₁ gene. Molecular analysis was carried out on 27 O-type populations (consisting of 13 susceptible and 6 resistant genotypes). Field evaluation and scoring of the phenotypic traits including greenness, growth, uniformity and disease score of 12 O-type populations were carried out on a rhizomania-infested field. The percent agreement of coupling marker ZN1 and repulsion marker ZN8 with disease score was 0.91 and 0.93, respectively. Although all O-types had the Rz ₁ resistance gene but the phenotypic differences were observed due to the effect of different genetic backgrounds and modifier genes. Overall, the results showed that the selected markers can be used for marker-assisted selection (MAS) to reduce the time and cost of breeding programs and increase the efficiency of selection.     

Comparative analysis of 31 reference evapotranspiration methods under humid conditions

Evaluation of simple reference evapotranspiration (ET_o) methods has received considerable attention in developing countries where the weather data needed to estimate ET_o by the Penman–Monteith FAO 56 (PMF-56) model are often incomplete and/or not available. In this study, eight pan evaporation-based, seven temperature-based, four radiation-based and ten mass transfer-based methods were evaluated against the PMF-56 model in the humid climate of Iran, and the best and worst methods were selected from each group. In addition, two radiation-based methods for estimating ET_o were derived using air temperature and solar radiation data based on the PMF-56 model as a reference. Among pan evaporation-based and temperature-based methods, the Snyder and Blaney–Criddle methods yielded the best ET_o estimates. The ET_o values obtained from the radiation-based equations developed here were better than those estimated by existing radiation-based methods. The Romanenko equation was the best model in estimating ET_o among the mass transfer-based methods. Cross-comparison of the 31 tested methods showed that the five best methods as compared with the PMF-56 model were: the two radiation-based equations developed here, the temperature-based Blaney–Criddle and Hargreves-M4 equations and the Snyder pan evaporation-based equation.     

Simulation of drainage water quality with DRAINMOD

The design and management of drainage systems should consider impacts on drainage water quality and receiving streams, as well as on agricultural productivity. Two simulation models that are being developed to predict these impacts are briefly described. DRAINMOD-N uses hydrologic predictions by DRAINMOD, including daily soil water fluxes, in numerical solutions to the advective-dispersive-reactive (ADR) equation to describe movement and fate of NO₃-N in shallow water table soils. DRAINMOD- CREAMS links DRAINMOD hydrology with submodels in CREAMS to predict effects of drainage treatment and controlled drainage losses of sediment and agricultural chemicals via surface runoff. The models were applied to analyze effects of drainage intensity on a Portsmouth sandy loam in eastern North Carolina. Depending on surface depressional storage, agricultural production objectives could be satisfied with drain spacings of 40 m or less. Predicted effects of drainage design and management on NO₃-N losses were substantial. Increasing drain spacing from 20 m to 40 m reduced predicted NO₃-N losses by over 45% for both good and poor surface drainage. Controlled drainage further decreases NO₃-N losses. For example, predicted average annual NO₃-N losses for a 30 m spacing were reduced 50% by controlled drainage. Splitting the application of nitrogen fertilizer, so that 100 kg/ha is applied at planting and 50 kg/ha is applied 37 days later, reduced average predicted NO₃-N losses but by only 5 to 6%. This practice was more effective in years when heavy rainfall occurred directly after planting. In contrast to effects on NO₃-N losses, reducing drainage intensity by increasing drain spacing or use of controlled drainage increased predicted losses of sediment and phosphorus (P). These losses were small for relatively flat conditions (0.2% slope), but may be large for even moderate slopes. For example, predicted sediment losses for a 2% slope exceeded 8000 kg/ha for a poorly drained condition (drain spacing of 100 m), but were reduced to 2100 kg/ha for a 20 m spacing. Agricultural production and water quality goals are sometimes in conflict. Our results indicate that simulation modeling can be used to examine the benefits of alternative designs and management strategies, from both production and environmental points-of-view. The utility of this methodology places additional emphasis on the need for field experiments to test the validity of the models over a range of soil, site and climatological conditions.     

Applicability of support vector machines and adaptive neurofuzzy inference system for modeling potato crop evapotranspiration

Estimation of crop evapotranspiration (ET_C) for certain crops such as potato is very important for irrigation planning, irrigation scheduling and irrigation systems management. The primary focus of this study was to investigate the accuracy of the adaptive neurofuzzy inference system (ANFIS) and support vector machines (SVM) for potato ET_C estimation when lysimeter measurements or the complete weather data for applying the FAO method are not available. The estimates of the ANFIS and SVM models were compared with the empirical equations of Blaney–Criddle, Makkink, Turc, Priestley–Taylor, Hargreaves and Ritchie. The performances of the different SVM and ANFIS models were evaluated by comparing the corresponding values of root mean square error (RMSE), mean absolute error (MAE) and correlation coefficient (r). The drawn conclusions confirmed that the SVM and ANFIS models could provide more accurate ET_C estimates than the empirical equations. Overall, the minimum RMSE (0.042 mm/day) and MAE (0.031 mm/day) values and the maximum r value (0.98) were obtained using the SVM model with mean air temperature, relative humidity, solar radiation, sunshine hours and wind speed as inputs.     

Evaluation of surface irrigation system performance using System Dynamics (SD) approach

Various methods and criteria have been proposed and utilized for the evaluation of irrigation systems performance, which can be used for comparison of design conditions and irrigation systems performance. Surface irrigation systems should be paid more attention among all other irrigation systems due to their operation simplicity and high losses. In the present study, while describing main relationships of irrigation evaluation criteria of application efficiency, water requirement efficiency, Deep Percolation Ratio and Tail Water Ratio, a method based on SD will be introduced. Modeling of this approach has been done using VENSIM-DSS software. Model has been tested in a case study that included the modeling of a furrow in four irrigation status: current situation, full irrigation, deficit irrigation and finally deficit irrigation with optimized irrigation cutoff time and inflow into furrow. The results reveal the high capabilities of SD approach in modeling water resources and irrigation systems. Its user friendly and ability in transferring data to the data bank can introduce this approach and software as an applicable decision support system.     

Effects of tree species diversity on leaf litter decomposition process in semi-arid Mediterranean oak forests

European Journal of Forest Research - Many studies have been conducted on the effects of changes in plant diversity and species composition on ecosystem functioning and plant productivity due to...