In this paper soil conventional tillage (CT) in two adiacent on-farm sites, hilly and plain fields, was carried out in comparison with direct-seeding + fertilizing at very low water content. The quality and quantity of work were evaluated through machine performance, fossil-fuel energy requirements and carbon dioxide emissions from agricultural machinery. The fields were previously sampled and mapped to investigate spatial variability of soil properties, to find soil quality indicators and to asses soil workability. The results revealed good traction performance during CT operations (slip values were lower than 15%). During plowing, time efficiency of the wheeled tractor was 40% lower with respect to the tracked tractor. Global energy employed was of the same magnitude for the tracked and wheeled tractor (220 kWh ha^-1) while was significantly lower (52 kWh ha^-1) for direct-seeding+fertilizing. The degree of crushing of the soil caused by CT required further energy employed (98 kWh ha^-1) to seedbed preparation. Fossil-fuel energy requirements from agricultural machinery were significantly lower during direct-seeding+fertilizing (0.52 GJ ha^-1) with respect to the conventional soil tillage (2.30 GJ ha^-1). Wheat yield of direct seeded field and the total cost of the crop cycle (€/ha) were 9% and 16% lower respectively than the values recorded on fields under conventional tillage.

According to aquatic life limits (CCME, 2011), the quality of Douro River water was found acceptable. Except for DO, where a significant number of samples presented levels below 5.0 mg l^-1, Cr(VI) (mean±sd = 3.09±1.54; median = 2.82 ppb) and Se (10.9±10.1; 7.74 ppb) all the other parameters measured fell well within acceptable limits. Occasional high levels were found for most trace elements, reflecting sporadic and local inputs. Important spatial differences in trace element levels were also found. Except for Be, Al and Mn, most metals tended to increase in the downstream direction. Some trace elements related with agriculture practices (Zn, Cu and Ni) were higher in samples collected on sampling sites located at the middle part of the studied area and were highly correlated, reflecting an eventual common source. Important seasonal differences in trace element levels were also observed, e.g., October samples were generally characterized by higher Ni, Cu, Zn and Pb levels.

In the present study, a monthly time series model was developed for pan evaporation (E_pan) in Jorhat (Assam), northeast India. We assume that the E_pan series can be decomposed into deterministic and stochastic components, and a turning point test was used to identify the presence of a trend component in the series. A trend-free E_pan time series was further obtained by eliminating the trend component from the original E_pan time series, and later used in identifying the periodic component using Fourier series analysis. Results show that the first three harmonics explained the total variance by 88,2 %. Before modelling the stochastic dependent component, the periodic component was removed from the time series. In the stochastic dependent component modelling, the moving average (MA) model of order 2 was found suitable on the basis of minimum value of the Bayesian information criterion (BIC). The independent stochastic component was modelled using the normal distribution function. Overall, a very good agreement is observed between generated and historical records, with the Nash-Sutcliffe coefficient being equal to 0,98.