Rainfall-runoff modeling

Srinivasula S, Jain A (2006) A comparative analysis of training methods for artificial neural network rainfall-runoff models. Appl Soft Comput 6 295-306... 

Cheng CT, Ou CP, Chau KW (2002) Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall-runoff model calibration. J Hydrol 268 72-86... 

Burger CM, Kolditz O, Fowler HJ, Blenkinsop S (2007) Future climate scenarios and rainfall-runoff modelling in the Upper Gallego catchment (Spain). Environ Pollut 148 842-854... 

Yapo PO, Gupta HV, Sorooshian S (1996) Automatic calibration of conceptual rainfall-runoff models sensitivity to calibration data. J Hydrol 181(1—4) 23—48... 

Jain, A. Prasad Indurthy, S. K. V. (2003) Comparative Analysis of Event-based Rainfall-runoff Modeling Techniques-Deterministic, Statistical, and Artificial Neural Networks, Journal of Hydrologic Engineering, 8, p. 93-98. 

Unit hydrographs or other rainfall runoff models... 

The automated pesticide runoff model consists of a set of FORTRAN programs which calculate the amount of pesticide runoff from input of river basin data, rainfall data, pesticide characteristics, and application data. Table I shows the input requirements for the SWRRB model. Table II shows the output data from the SWRBB model. 

Kendall C. and McDonnell J. J. (1993) Effect of intrastonn heterogeneities of rainfall, soil water and groundwater on runoff modelling. In Tracers in Hydrology, Int. Assoc. Hydrol. Sci. Publ. 215, July 11-23, 1993 (eds. N. E. Peters et al.) Yokohama, Japan, pp. 41-49. 

Stahl RG, Liehr JG, Davis EM. 1984. Characterization of organic compounds in simulated rainfall runoffs from model coal piles. Arch Environ Contam Toxicol 13 179-190. 

Zhou, J.L., Rowland, S.J., Mantoura, R.F.C., and Lane, M.C.G. (1997). Desorption of tefluthrin insecticide from soil in simulated rainfall runoff systems - Kinetic studies and modelling. Water Res., 31(1), 75-84. 

Table VII shows a sensitivity analysis on the SWRRB model. It can be seen that the intensity of the rainfall is one of the most important parameters affecting runoff.

The weight of soil carried in the surface runoff has been estimated by relating the sediment load to the rate of energy dissipation at the land surface by the rainfall and flowing water. The resistance of the soil to eroding forces has also been considered (4), and a method has been developed to estimate the net effect of erosion on radioaerosol transport. The volume of the liquid phase is estimated on a continuous basis by the Stanford watershed model, through consideration of a water budget. This feature has been retained in the HTM-1. 

The soil and air concentrations of p,p -DDT were used in a soil-air exchange model developed by Harner et al. [103] to estimate p,p -DDT emissions to air from soils under steady-state conditions. The volatilization flux of p,p -DDT from soil to air was larger than fluxes in runoff over the same time period. For example 15.7 kg of DDT was volatilized during the period March-June, if it was assumed that an area of 300 km2 of land was formerly treated with DDT the steady-state model results were used and calculated monthly, with adjustment for mean monthly temperature. Re-deposition in rainfall was about 15 g ofp,p -DDT to the watershed, based on concentrations in precipitation measured at the field station during May-August 2000. The extent of re-deposition of gas-phase DDT compounds on plants and soils was not known. 

Because there are no direct applications of PBO to water, the exposure of aquatic organisms to PBO is limited to spray drift at the time of application to adjacent lands and runoff associated with rainfall. Regarding drift the EPA uses a default assumption of 5 a- drift, which is defined as 5% of the actual application rate applied to the entire surface of the water body (pond) on a per acre basis. The compound applied is assumed to be instantaneously at equilibrium within the water column (Urban and Cook, 1%6). In modelling aquatic exposure, the amount of chemical in runoff is also added to the water body (pond) based on historical rainfall data, the properties of the chemical, and other factors. 

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