Transport of phosphorus (P) through surface runoff from agriculture is suspected to contribute to the eutrophication of surface waters in South Florida and elsewhere. There is minimal quantitative information on the concentrations and loads of various P forms in surface runoff water on a field‐scale. The objective of this study was to evaluate the annual loads of various P forms in runoff water from citrus and vegetable crop production systems in sandy soil regions in Florida and their relations to soil P status, fertilizer P input, and environmental conditions. Eleven field sites (four on vegetable farms and seven in citrus groves) were selected for this monitoring study over a 2‐yr period. The concentrations of total P (TP) in the runoff water samples varied widely from 0.01 to 22.74 mg L−1, with approximately half of the samples having the TP over 1 mg L−1 Eighty‐three percent of the samples had orthophosphate (PO4–P) higher than 0.02 mg L−1 The mean proportion of total dissolved P (TDP) in the TP was higher than that of the total particulate P (TPP). The TDP constituted the major proportion of P in runoff water from most of the sites. The PO4–P accounted for approximately 64% of the TDP. The annual median concentrations of various P forms in the runoff water varied spatially and temporally and were correlated with total and labile P in the soils (water‐P, Olsen‐P, Mehlich 1‐P, and Mehlich 3‐P) as well as fertilizer P rate. The vegetable farms had higher concentrations of P in the runoff water than citrus groves due to their more severe soil erosion and higher fertilizer P input, which resulted in higher soil P accumulation and availability. The annual loads of TP, TDP, and PO4–P varied among the field sites and between the 2 yr. The TP loads were significantly correlated with soil labile P estimated by the four extraction procedures, but the Olsen‐P was best related to runoff P. Runoff P concentrations and the annual discharge rate accounted for 55 to 64% of the variance in the annual P loads. These results indicate that P transport through surface runoff from agriculture is affected by soil P status and water management, and merits attention in the development of best management practices.

Climate variation and land use changes have been widely recognized as two major factors that impact hydrological processes. However, it is difficult to distinguish their contributions to changes in streamflow. Quantifying their contributions to alteration of streamflow is especially important for the sustainable management of water resources. In this study, the changes in streamflow for the period of 1960–2008 at two stations (Dongwan and Luhun) were analyzed in the Yihe watershed in China based on hydrological data series and climate parameters. Using a non-parametric Mann–Kendall (MK) and Pettitt’s test, as well as Budyko analysis, we first examined the trends of hydroclimatic variables and the breakpoint of annual streamflow over the past 50 years. Subsequently, we evaluated the contributions of annual precipitation (P), potential evapotranspiration (PET), and land use condition (represented by w), respectively, to streamflow variation. We observed a decreasing trend for P, as well as increasing trends for PET and w. Annual streamflow showed a significant downward trend with an abrupt change occurring in 1985 during the period of 1960–2008. Accordingly, we divided the studied period into two sub-periods: period I (1960–1985) and period II (1986–2008). The sensitivity of the streamflow to the different environmental factors concerned in this study differed. Streamflow was more sensitive to P than to PET and w. The decrease in P was the greatest contributor to the decline in streamflow, which accounted for 50.01% for Dongwan and 55.36% for Luhun, followed by PET, which accounted for 24.25% for Dongwan and 24.45% for Luhun, and land use change was responsible for 25.25% for Dongwan and 20.19% for Luhun. Although land use change plays a smaller role in streamflow reduction, land use optimization and adjustment still have great significance for future water resource management, since climate variation is difficult to control; however, the pattern optimization of land use can be achieved subjectively.

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