successful modeling of hydro-environmental processes widely relies on quantity and quality of accessible data and noisy data might effect on the functioning of the modeling. on the other hand in training phase of any artificial intelligence (ai) based model, each training data set is usually a limited sample of possible patterns of the process and hence, might not show the behavior of whole pop...

there is different methods for simulating river flow. some of thesemethods such as the process based hydrological models need multiple input data and high expertise about the hydrologic process. but some of the methods such as the regression based and artificial inteligens modelsare applicable even in data scarce conditions. this capability can improve efficiency of the hydrologic modeling in u...

Pesticide runoff research relies heavily on rainfall simulation experiments. Most are conducted at a constant intensity, i.e., at a fixed rainfall rate; however, large differences in natural rainfall intensity is common. To assess implications we quantified runoff of two herbicides, fluometuron and pendimethalin, and applied preemergence after planting cotton on Tifton loamy sand. Rainfall at c...

This study uses a stochastic ensemble-based representation of satellite rainfall error to predict the propagation in flood simulation of three quasi-global-scale satellite rainfall products across a range of basin scales. The study is conducted on the Tar-Pamlico River basin in the southeastern United States based on 2 years of data (2004 and 2006). The NWSMultisensor Precipitation Estimator (M...

A biased coinflip Ansatz provides a stochastic regional scale land surface climate model of minimum complexity, which represents physical and stochastic properties of an ideal rainfall–runoff chain. The solution yields the empirically derived Schreiber formula as an Arrhenius-type equation of state W = exp(-D). It is associated with two thresholds and combines river runoff Ro, precipitation P a...

It is widely recognised that the Murray-Darling Basin (MDB) in south-eastern Australia has been in the grip of a serious drought for many years. Over the period 1997−2006, mean annual rainfall has been approximately 16 percent lower than the long-term (1895−2006) average across the MDB. Runoff has been 39 percent lower over the same period. The continuing drought in the MDB has brought the need...

Continuous hydrologic models account for the soil moisture balance in the catchment over a long-term period. Different hydrologic physical processes such as: interception, surface depression storage, infiltration, soil storage, percolation, and groundwater storage should be considered in continuous hydrologic modeling. In this paper, the Hydrologic Modeling System (HMS) model was used for conti...

In the Atlantic Coastal Plain region of southern Georgia (USA), cotton (Gossypium hirsutum L.) acreage increased threefold in the past decade. To more effectively protect water quality in the region, best management practices are needed that reduce pesticide runoff from fields in cotton production. This study compared runoff of two herbicides, fluometuron [N,N-dimethyl-N'-[3-(trifluoromethyl)-p...

As a result of quick progression in computer and information technologies, computer modeling has become a vital tool in watershed research and management practices. Stanford Watershed Model (SWM) is an integrated physically based Watershed model that can be used to simulate water flow stream/canal network and overland runoff, interflow and evaporation by considering the interaction between surf...