Waterborne Environmental, Inc.
897-B Harrison Street, S.E.
Leesburg, VA 20175
Phone: (703) 777-0005
Fax: (703) 777-0767
Phone: (703) 777-0005
Fax: (703) 777-0767
email: wei@waterborne-env.com
Homepage: http://www.waterborne-env.com/modeling/index.html
Purpose:
Rice production presents a unique problem with respect to agrochemical runoff because of the high seasonal rainfall,
water management, and proximity of cropland to surface water bodies.
Existing pesticide transport models are not configured to simulate the flooding conditions,
overflow, and controlled releases of water that are typical under rice production.
RICEWQ was developed to simulate water and chemical mass balance associated with these unique governing processes.
Processes Simulated:
RICEWQ simulates pesticide transport from rice paddies based on water and pesticide mass balance. Water mass balance
takes into account precipitation, evaporation, seepage, overflow, irrigation, and drainage.
Pesticide mass balance can accommodate dilution, advection, volatilization, partitioning between water/sediment,
decay in water and sediment, burial in sediment, and resuspension from sediment.
The water quality algorithms first originated from the
SWRRBWQ Lake Water Quality Model (LAKEWQ)
developed by Jeff Arnold and Nancy Sammons, USDA-ARS, Temple, TX. Agronomic and hydrologic routines have been added
to represent rice culture. Water quality algorithms have been modified for error checking and to allow first-order
degradation. Nutrient algorithms from SWRRBWQ have not been included. To the extent possible and convenient,
variable names and coding have remained unaltered from LAKEWQ. RICEWQ uses a daily time step.
Input Parameters:
Pesticide properties include the number of pesticide applications, dates of application, rate of application,
washoff coefficient, water/sediment partition coefficient, degradation rate in water, degradation rate in sediment,
mixing velocity (diffusion), and rate of volatilization.
Other key input include beginning and ending date of simulation, surface area of paddy,
initial depth of water in paddy, depth of paddy outlet, seepage rate of paddy, depth to initiate and terminate
irrigation, date that paddy is drained, crop emergence and maturation dates, drift factor.
Sediment properties include initial suspended sediment concentration, settling velocity, resuspension
velocity, porosity of bed sediment, and bulk density of bed sediment.
Weather input include daily precipitation and daily or monthly pan evaporation.
Output Parameters:
Hydrologic output file contains daily time series of precipitation, evaporation, seepage, irrigation, depth in paddy,
and outflow from paddy. Pesticide output file contains daily time series accounting of pesticide mass: applied,
outflow, degradation in water, volatilization, settled, resuspended, diffused between water and sediment, degraded
in sediment, and lost from active sediment layer due to burial.
Current Version No.: 1.2
Critical Assessment:
Strengths of Model: RICEWQ simulates the flooding conditions and water management typical for rice production. The model is extremely easy to use and was intentionally designed to not be overly sophisticated with algorithms for which input and validation data are seldom available.
Weaknesses of Model:
Degradation is represented by lumped 1st-order kinetics. Distinct biological and chemical transformation processes are not included as a standard option, but have been included for one case study. Degradation products are currently not simulated.
Source of abstract: American Crop Protection Association (ACPA) model database (04/1998)
Other key input include beginning and ending date of simulation, surface area of paddy, initial depth of water in paddy, depth of paddy outlet, seepage rate of paddy, depth to initiate and terminate irrigation, date that paddy is drained, crop emergence and maturation dates, drift factor.
Sediment properties include initial suspended sediment concentration, settling velocity, resuspension velocity, porosity of bed sediment, and bulk density of bed sediment.
Weather input include daily precipitation and daily or monthly pan evaporation.