Previous studies reported photolysis half-lives of 10-20 days in soil surface under continuous UV radiation . Under field conditions however, there won’t be continuous exposure to sunlight, and photolytic degradation will probably be much slower than reported values, especially in winter months. Another factor that potentially affected the observed degradation rates was pesticide exposure histories at the study sites. According to data from the California Department of Pesticide Regulation , the Hospital Creek watershed had a higher use of chlorpyrifos than the other study sites and chlorpyrifos use in this watershed consistently increased between 2007 to 2010 . Although the SJRNWR site is downstream, at the confluence of Hospital Creek and Ingram Creek, it is less susceptible to chlorpyrifos exposure because the compound is deposited to sediments upstream. When soils are repeatedly exposed to chlorpyrifos, some microorganisms may gain an enhanced capability to degrade the compound, a phenomenon called enhanced biodegradation . For example, Singh et al. observed rapid degradation of both chlorpyrifos and the transformation product TCP in an Australian soil collected from a site where chlorpyrifos had been used continuously for more than 14 years. It has also been reported in some other studies, however,hydroponic dutch buckets that chlorpyrifos was resistant to enhanced biodegradation . Additional research is needed to assess the differences in microbial communities among the study sites and their link to the pesticide exposure history. The functionality of the study sites as riparian buffers was assessed using the California Rapid Assessment Method for Wetlands . Results of the CRAM analysis indicate that these riparian areas range from very low functionality , to high functionality.
The finding of higher chlorpyrifos degradation capacity of sites with low functionality may be related to the fact that healthy wetlands often contain large areas of anaerobic sediments that may not be conducive to microbial communities that rapidly degrade chlorpyrifos. As a result, strategies intended to increase wetland functionality alone may not be conducive to pesticide degradation. The hydrolysis of the P-O linkage of organophosphate insecticides is catalyzed by phosphotriesterase , a zinc metalloenzyme capable of hydrolyzing organophosphate compounds including agricultural pesticides and chemical warfare agents . This enzyme reportedly has been responsible for the biodegradation of organophosphate insecticides in previous studies. Phosphomonoesterase and phosphodiesterase enzymes were involved in chlorpyrifos mineralization making phosphorus available for uptake by microorganisms . To investigate the relationship between different types of phosphoesterase enzymes and observed chlorpyrifos degradation rates, enzyme activities were measured and compared to the biodegradation rates. A positive correlation between PTE enzyme activities and chlorpyrifos degradation rates was observed, however, the relationship differed for each site . These results suggest that the PTE enzyme assay may be useful as a tool for assessing temporal variations at individual sites after PTE enzyme activities are calibrated to the site-specific degradation rates. No correlation was observed between chlorpyrifos degradation rates and phosphomonoesterase and phosphodiesterase activities .The engineering module simulates the hydrology and water quality for the landscape of a river basin. A river basin has tributary lands, rivers, and reservoirs. To capture the spatial variations within a river basin, the WARMF model divides the basin into a hydrologic network of land catchments, stream segments, and lake layers.
Physical dimensions of the hydrologic components are prescribed by digital elevation map data, which can be downloaded from the website of US Geological Survey . By selecting a specific land catchment, stream segment, or reservoir on the basin map, dialog boxes for physical, chemical, and biological characteristics of a location can be displayed with the description of variable names and their units. Values for model coefficients can be modified by the user during model calibration. The model allows the user to include atmospheric deposition from precipitation and dry dust, point source discharges and fertilizers applied to farm lands. Hydrology, non-point load and water quality are simulated in all sections of the waterway. Simulated parameters include flow, water depth, and an array of water quality parameters including pH, temperature, dissolved oxygen, ammonia, nitrate, phosphate, suspended sediments, fecal coliforms, major cations and anions, and pesticides. The time step of simulations is typically one day. The model’s database contains default input data and data to evaluate simulation results. The model also uses input including digital elevation maps, land use, fertilizer application, air quality, meteorology, and point source discharges. A variety of model outputs are automatically saved for graphical, tabular or GIS displays. The sub-models embedded in WARMF are adapted from many well established algorithms, such as sediment erosion and pollutant transport algorithms in ANSWERS , and pollutant accumulation and wash off algorithms in SWMM .To simulate the dynamics of a river basin, WARMF uses a number of time series data sets in modeling. Meteorology, air quality, precipitation quality, point source discharge, and reservoir flow release data are used to drive the model. Hydrology and water quality data are used to check model results. The data module allows users to review the input data sets and make changes. The time series data sets are stored in ASCII text files, one file per monitoring station . Each row of a data file contains a date and a series of numerical values for monitored parameters in separate columns. As a part of continuous planning process, new data may be collected after the planning is completed.
When there is a need to extend the time period of old data sets to include the new data, the data module allows users to enter new data as they become available. The knowledge module can include reservoir operation rules, water quality standards, rate coefficients, and other items. The reservoir operation rules are replaced by an input file that contains the specified flow releases from various outlets. Water quality standards are included in the water quality criteria for various designated uses. The knowledge module can be used to store files used to process input data for a site-specific application, spreadsheets used to calculate the cost of best management practices, references, applicable laws, and relevant case studies.Consensus and TMDL modules are road maps that provide guidance for stakeholders during the decision-making process. Through the TMDL Module, calculations are made for a series of control points throughout the river basin. A road map is provided for the step-by-step procedure. An iterative set of simulations is performed to calculate various combinations of point and non-point loads that the water body can accept and meet the water quality criteria of the designated uses. The water quality criteria can be specified for multiple parameters and based on percent compliance. The consensus module is an application tool embedded in WARMF. The purpose of the module is to guide stakeholders to a general agreement on a watershed management plan. It relies on the engineering models to furnish technical information for stakeholders to make decisions.The San Joaquin River Model Interface is a WARMF version developed to simulate the San Joaquin River and its watershed . The section of the San Joaquin River within the watershed was divided into 93 river segments. The irrigated lands were divided into 17 land catchments. The model simulates natural storm water runoff, irrigation return flow, groundwater table of land catchments, and groundwater lateral flow from land catchments to the receiving river segments. There are gauge stations that provide measured inflows as inputs to the model. For example, there are three gauges for the three major east-side tributaries . For the agricultural lands, the model inputs includes daily diversions, locations of diversions, and areas upon which the irrigation water was applied. Based on the locations of diversions, the model uses the water quality of the source water when applying that water for irrigation.The model simulates the hydrological processes of snow pack accumulation, snow melt, canopy interception, through fall, evaporation and transpiration, infiltration, percolation, groundwater lateral flow, and surface runoff. These processes are simulated based on water balance and physics of flow . Precipitation and irrigation water can percolate into the soil. Within the soil, water increases the moisture level in each soil layer. After the field capacity is exceeded, water percolates down to the water table,bato bucket where it flows laterally out of the land catchment according to Darcy’s Law. Water on the soil or within the soil is subject to evapotranspiration, which is calculated based on temperature, humidity, and season. The amount of water entering and leaving each soil layer is tracked by the model. If the amount of water entering the soil layer is greater than the amount leaving the soil layer, the water table rises. If the water table reaches the surface, the soil is saturated and overland flow occurs, which is calculated by Manning’s equation . Rivers accept the subsurface and overland flow from linked catchments. They also receive point source discharges and flow from upstream river segments. Diversion flows are removed from river segments. The remaining water in the river is routed downstream using the kinematic wave algorithm. The channel geometry, Manning’s roughness coefficient, and bed slope are used to calculate depth, velocity, and flow. The velocity is a measure of the travel time down the river, which in turn affects the water quality simulation.The fundamental principle which guides the model’s simulation of water quality is heat and mass balance. Heat is transferred to the soil via precipitation and irrigation. Heat exchange occurs between catchments and the atmosphere based on the thermal conductivity of the soil. Temperature is then calculated by heat balance throughout the model. There are various ways by which chemical constituents can enter the model domain.
They can enter the land surface via irrigation water, land application, atmospheric deposition or point source discharge. Chemical species move with water by percolation between soil layers, groundwater lateral flow to rivers, and surface runoff. Each soil layer is modeled as a completely mixed reactor, as is the land surface within each land use . Competitive cation exchange between the major cations are simulated on the available soil exchange sites. Anions and optional metals partition between dissolved and adsorbed phases in the soil based on an adsorption isotherm. Nutrient cycling between soil and vegetation is simulated for each land use. The model simulates the soil erosion of sand, clay, and silts from the land surface, and sedimentation and resuspension of particles in streams. A dynamic equilibrium is maintained between dissolved and adsorbed phases of each ion. The dissolved oxygen concentration is tracked during the simulations, and anoxic reactions take place as DO is depleted. When overland flow takes place, sediment is eroded from the catchment surface according to the modified universal soil loss equation. Adsorbed ions are carried on soil particles to the river. Each river segment is modeled as a completely mixed reactor. Sediment can settle into the river bed and is scoured from the river bed when velocity is high enough. Chemical reactions take place in the canopy, soil surface, soil layers, and surface waters. Reaction rates are based on first-order decay with reaction-specific rates. .The model requires six categories of input data: geometric dimensions of land catchments and river segments and their elevations, soil characteristics of the watersheds, model coefficients, land uses, meteorological conditions, and operating conditions. The first 4 categories of data are time invariant variables, which remain constant during the model simulation. Their input values are set only once during model setup. The model coefficients include reaction rates and their temperature correction factors. The model allows for land use changes, which can occur once every few years. In that case, the model uses a “warm start” procedure to run the simulation in sequence. In this procedure, the model uses a set of land use data to perform a simulation for a period of a few years. It saves the results at the end of the simulation and uses them as the initial condition to start the simulation for the next few years with the new land use data. The last two categories of data vary with time. These are sometimes referred to as “driving variables” . The meteorology affects the annual and seasonal variations of hydrology and water quality . The operating conditions include human activities such as fertilizer applications, reservoir releases, diversions, irrigation and waste discharges, which can be modified by management alternatives to improve water quality.