Phosphorus (P) loss from agricultural fields through surface runoff may contribute to the eutrophication of surface waters. The objective of this study was to evaluate surface runoff and P transport from different cropping systems during 2007-2009. The treatments consisted of a control (wheat/fallow) and three double cropping systems: wheat/corn (Zea mays L.), wheat/cotton (Gossypium hirsutum L.), and wheat/soybean [Glycine max (L.) Merr.]. Wheat/ fallow was not fertilized and had no crop planted during the summer crop growing season. The four treatments were randomly assigned to 12 plots of 5 9 2 m on a silt clay soil. Surface runoff from natural rainfall was sampled for P analysis during the 3 years. Double cropping systems, when compared with wheat/ fallow, reduced runoff volume and losses of total dissolved P (TDP), particular P (PP), and total P (TP). Wheat/soybean was the most beneficial system reducing the 3-years mean runoff volume by 58%, TDP loss by 81%, PP loss by 89%, and TP loss by 85%, compared with wheat/fallow. The 3-years flowweighted mean (FWM) concentrations of TDP, PP, and TP followed the order wheat/fallow [ wheat/ cotton [ wheat/corn [ wheat/soybean. The least temporal variations of the P concentrations and losses were observed from wheat/soybean. Therefore, selecting wheat/soybean as the main double cropping system appears to be a practical method for controlling runoff and associated P loss from farmland under similar weather and soil conditions.

The accurate simulation or prediction of storm runoff is one of the most important bases of water resource management and environmental quality assessment of water and soil. The soil conservation service-curve number (SCS-CN) method cannot effectively determine the effect of antecedent precipitation storage and depletion on runoff, which limits the accuracy of the method's runoff prediction. Thus, potential initial abstraction and decay constant were developed in this study to improve the SCS-CN method. Potential initial abstraction determined the maximum rainfall storage before runoff and the threshold of daily effective rainfall, and the decay constant was used to describe the dynamic depletion of antecedent daily effective rainfall induced by evapotranspiration and seepage. The improved SCS-CN method was evaluated withthe runoff data observed in four cropping systems and three drainage areas, and it proved that the improved SCS-CN method predicted runoff more accurately than the original SCS-CN method. The inproved SCS-CN method increased both NSE and R 2 values by more than 20 % for the four cropping systems, and increased R 2 values by 11.9, 13.9 and 9.6 % for the plot, field, and catchment, respectively, compared with the original SCS-CN method. The decay constant did not vary with cropping systems and drainage areas.

Reducing nitrogen (N) loss from agricultural soils as surface runoff is essential to prevent surface water contamination. The objective of 3-year study, 2007–09, was to evaluate surface runoff and N loss from different cropping systems. There were four treatments, including one single-crop cropping system with winter wheat (Triticum aestivum L.) followed by summer fallow (wheat/fallow), and three double-cropping systems: winter wheat/corn (Zea mays L.), wheat/cotton (Gossypium hirsutum L.), and wheat/soybean (Glycine max L. Merrill). The wheat/fallow received no fertiliser in the summer fallow period. The four cropping systems were randomly assigned to 12 plots of 5 m by 2 m on a silty clay soil. Lower runoff was found in the three double-cropping systems than the wheat/fallow, with the lowest runoff from the wheat/soybean. The three double-cropping systems also substantially reduced losses of ammonium-N (NH4+-N), nitrate-N (NO3–-N), dissolved N (DN), and total N (TN) compared with the wheat/fallow. Among the three double-cropping systems, the highest losses of NO3–-N, DN, and TN were from the wheat/cotton, and the lowest losses were from the wheat/soybean. However, the wheat/soybean increased NO3–-N and DN concentrations compared with wheat/fallow. The losses in peak events accounted for >64% for NH4+-N, 58% for NO3–-N, and 41% for DN of the total losses occurring during the 3-year experimental period, suggesting that peak N-loss events should be focussed on for the control of N loss as surface runoff from agricultural fields.

Drainage water reuse has the potential to supplement irrigation, reduce drainage, and alleviate the area source pollution caused by agricultural drainage. This study aimed to evaluate the effects of influencing factors of drainage water reuse on supplementary irrigation and drainage reduction rates. To evaluate the effects, a water balance model was constructed to describe the irrigation water requirement and drainage water storage of a pond. The irrigation water requirement was calculated using the Penman-Monteith equation and the crop coefficient method while considering field leakage and effective rainfall; the drainage water volume was calculated using the improved Soil Conservation Service (SCS) model. The model was applied to the rice planting area in the Zhanghe Reservoir Irrigation District. Simulation results show that the supplementary irrigation and drainage reduction rates are primarily affected by the ratio of irrigation to drainage areas (RID), the pond volume ratio (PV), and the initial storage ratio (PSi); interactions among the three parameters are also observed. The RID, PV, and PSi contribute approximately 4:3:1 to the average variations in the supplementary irrigation rate. The supplementary irrigation rate increases with the values of PV and PSi but decreases with the increases of RID. For the drainage reduction rate variation, the average contribution percentages of PV and RID are 70% and 10%, respectively. Increasing PV and RID or reducing PSi enhances the drainage reduction rate. Adjusting the combination of parameters PV and RID can simultaneously maximize the supplementary irrigation and drainage reduction rates. Keywords: Drainage reduction, Drainage water reuse, Pond, Supplementary irrigation, Water balance model.