BACKGROUND Key climatic factors influencing the transport of pesticides to drains and to depth were identified. Climatic characteristics such as the timing of rainfall in relation to pesticide application may be more critical than average annual temperature and rainfall. The fate of three pesticides was simulated in nine contrasting soil types for two seasons, five application dates and six syn...

Characterization of the error associated with satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving spaceborne passive and active microwave measurements for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. The authors focus here on the relative error structure of Tropical Rai...

Climate change models predict that future precipitation patterns will entail lower-frequency but larger rainfall events, increasing the duration of dry soil conditions. Resulting shifts in microbial C cycling activity could affect soil C storage. Further, microbial response to rainfall events may be constrained by the physiological or nutrient limitation stress of extended drought periods; thus...

This study evaluated the accuracy of several models for estimating daily solar radiation (Q) across Australia. Data from 39 sites were taken from MetAccess. The sites were grouped into four climatic zones. Coefficients of nine models, including two newly developed formulae, were fitted for the 39 sites. Correlation coefficients (R2) between estimated Q and measured Q and root mean squared error...

Error characterization is vital for the advancement of precipitation algorithms, the evaluation of numerical model outputs, and their integration in various hydro-meteorological applications. The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) has been a benchmark for successive Global Precipitation Measurement (GPM) based products. This has given way to...

The effect of hygroscopic seeding on warm rain clouds was examined using a hybrid cloud microphysical model combining a Lagrangian Cloud Condensation Nuclei (CCN) activation model, a semi-Lagrangian droplet growth model, and an Eulerian spatial model for advection and sedimentation of droplets. This hybrid cloud microphysical model accurately estimated the effects of CCN on cloud microstructure...

Rainfall forecasting is an important research topic in disaster prevention and reduction. The characteristic of rainfall involves a rather complex systematic dynamics under the influence of different meteorological factors, including linear and nonlinear pattern. Recently, many approaches to improve forecasting accuracy have been introduced. Artificial neural network (ANN), which performs a non...

This study explores the decomposition of predictive uncertainty in hydrological modeling into its contributing sources. This is pursued by developing data-based probability models describing uncertainties in rainfall and runoff data, and incorporating them into the Bayesian Total Error Analysis methodology (BATEA). A case study based on the Yzeron catchment (France) and the conceptual rainfall-...