A COMPARISON OF GEOSTATISTICAL METHODOLOGIES USED TO ESTIMATE SNOW WATER EQUIVALENT1

ABSTRACT: The need to monitor and forecast water resources accurately, particularly in the western United States, is becoming increasingly critical as the demand for water continues to escalate. Consequently, the National Weather Service (NWS) has developed a geostatistical model that is used to obtain areal estimates of snow water equivalent (the thtal water content in all phases of the snowpack), a major source of water in the West. The areal snow water equivalent estimates are used to update the hydrologic simulation models maintained by the NWS and designed to produce extended streamflow forecasts for river systems throughout the United States. An alternative geostatistical technique has been proposed to estimate snow water equivalent. In this research, we describe the two methodologies and compare the accuracy of the estimates produced by each technique. We illustrate their application and compare their estimation accuracy using snow data collected in the North Fork Clearwater River basin in Idaho.     

USING UNCENSORED TRACE-LEVEL MEASUREMENTS TO DETECT TRENDS IN GROUND WATER CONTAMINATION1

ABSTRACT: Environmental decision making involving trace-levels of contaminants can be complicated by censoring, the practice of reporting concentrations either as less than the limit of detection (LOD) or as not detected (ND) when a test result is less than the LOD. Censoring can result in data series that are difficult to meaningfully summarize, graph, and analyze through traditional statistical methods. In spite of the relatively large measurement errors associated with test results below the LOD, simple and meaningful analyses can be carried out that provide valuable information not available if data are censored. For example, an indication of increasing levels of contamination at the fringe of a plume can act as an early warning signal to trigger further study, an increased sampling frequency, or a higher level of remediation at the source. This paper involves the application of nonparametric trend analyses to uncensored trace-level groundwater monitoring data collected between March 1991 and August 1994 on dissolved arsenic and chromium for seven wells at an industrial site in New York.     

DRAINAGE GENERATION AND WATER USE IN THE EVERGLADES AGRICULTURAL AREA BASIN1

ABSTRACT: The Everglades Agricultural Area (EAA) covers 2,850 km² in area and is characterized by high water table and organic soil. The area is actively irrigated and drained as a function of weather conditions and crop status. Anthropogenic activities in the basin have resulted in nutrient-enriched drainage water that is discharged to Lake Okeechobee and the Everglades ecosystem. Water quantity and quality issues of the basin have become of increasing interest at local, state, and federal levels, so legislative and regulatory measures have been taken to improve water quality in discharges from the basin. In this study, simulation of hydrologic conditions and soil moisture were conducted using 100 years of daily synthetic rainfall data. From the simulations, the statistical distribution of half-month drainage discharge and supplemental water use in the basin was developed. The mean annual drainage/runoff was 49 cm, the mean supplemental water was 30 cm, and the mean annual a real rainfall was 122 cm. On the average, drainage exceeded supplemental water use in the months of June to September while from December to March drainage and supplemental water use were equivalent. Supplemental water use exceeded drainage in the months of October, November, April, and May. High drainage occurred in June and September; smallest drainage was in February. On the average, the highest supplemental water use occurred in May and November. The 10-year return period of annual drainage during wet and dry cycles were 60 cm and 38 cm per year, respectively. The semi-monthly drainage coefficient of variation (cv) is above 100 percent for the period from the second half of October to end of April. The cv is lower than 100 percent for the remaining season (wet season). The purpose of this paper is to present the magnitude, temporal, and frequency distribution of drainage runoff generation and supplemental water use in the EAA basin. Information on statistics of drainage will contribute to the optimization of the design and operation of drainage water treatment systems.     

STATISTICAL LOW FLOW ESTIMATION USING GIS ANALYSIS IN HUMID MONTANE REGIONS IN PUERTO RICO1

ABSTRACT: Statistical analysis of watershed parameters derived using a Geographical Information system (GIS) was done to develop equations for estimating the 7d–10yr, 30d–10yr, and 7d–2yr low flow for watersheds in humid montane regions of Puerto Rico. Digital elevation models and land use, geology, soils, and stream network coverages were used to evaluate 21 geomorphic, 10 stream channel, 9 relief, 7 geology, 4 climate, and 2 soil parameters for each watershed. To assess which parameters should be used for further investigation, a correlation analysis was used to determine the independence and collinearity among these parameters and their relationship with low flows. Multiple regression analyses using the selected parameters were then performed to develop the statistical models of low flows. The final models were selected in the basis of the Mallow Cp statistic, the adjusted R², the Press statistic, the degree of collinearity, and an analysis of the residuals. In the final models, drainage density, the ratio of length of tributaries to the length of the main channel, the percent of drainage area with northeast aspect, and the average weighted slope of the drainage were the most significant parameters. The final models had adjusted standard errors of 58.7 percent, 59.2 percent, and 48.6 percent for the 7d–10yr, 30d–10yr, and 7d–2yr low flows respectively. For comparison, the best model based on watershed parameters that can be easily measured without a GIS had an adjusted standard error of 82.8 percent.     

SENSITWITY OF IRRIGATION DEMAND IN A HUMID-TEMPERATE REGION TO HYPOTHETICAL CLIMATIC CHANGE1

ABSTRACT: An irrigation model based on a modified Thornthwaite water balance was used to simulate the effects of various hypothetical climatic changes on annual irrigation demand in a humidtemperate climate. The climatic-change scenarios consisted of combinations of changes in temperature, precipitation, and stomatal resistance of plants to transpiration. The objectives were to (1) examine the effects of long-term changes in these components of climatic change on annual irrigation demand, and (2) identify which of these factors would cause the largest changes in annual irrigation demand. Hypothetical climatic changes that only included increases in temperature and changes in precipitation resulted in increased annual irrigation demand, even with a 20 percent increase in precipitation. The model results showed that, for the ranges of changes in temperature and precipitation used in this study, changes in irrigation demand were more sensitive to changes in temperature than to changes in precipitation. Model results also indicated that increased stomatal resistance to transpiration counteracted the effects of increases in temperature and decreases in precipitation on irrigation demand. Changes in irrigation demand were even more sensitive to changes in stomatal resistance than to changes in temperature. A large amount of uncertainty is associated with predictions of future climatic conditions; however, uncertainty associated with natural climatic variability may be larger and may mask the effects of climatic change on irrigation demand.     

AN OBJECTWE TEST FOR HYDROLOGIC SCALE1

ABSTRACT: Improving the reliability of parametric hydrologic models (sometimes called cenceptual rainfall-runoff models) in the continuous simulation of runoff from ungaged catchments has been frustrated by difficulties in estimating model parameters from catchment characteristics. An underlying problem is that these models use parameters to represent catchments as a whole, whereas data on catchment characteristics are collected at multiple field locations and are difficult to transform into one measure of collective impact. Subdividing the catchment and calibrating a stochastic parametric model to estimate distributions for the parameters that covered the range of observed streamflow values was found to improve the simulations. This paper presents an optimization of the amount of subdivision to use in simulation with a version of the Stanford Watershed Model using available climatological data. The calibration process assumes that catchment heterogeneity introduces errors that can be reduced by calibrating parameters as spatial distributions rather than single values. Calibrations for three diverse small gaged catchments located in California and in Virginia found the optimal number of subdivisions to range from 4 to 25 and the optimal scale to range from 0.3 to 2.1 mi².     

OPTIMIZING THE PROBABILITIES OF WATER YIELD FOR THE RIDAURA AQUIFER (SPAIN)1

ABSTRACT: Aquifer pumping represents, in many geographical locations, an alternative and/or a complementary source of water to surface water supplies. Several Catalonian coastal towns in the northeastern corner of Spain are in this situation. Also, since pumped water is used to supply drinking water, the main purpose in managing these water resources is to supply, no matter the cost, the amount needed at every moment. In other words, the managers of these aquifers attempt to optimize firm water yield. If we think of these aquifers as underground reservoirs with fixed storage capacity, most of the techniques which are applied to surface reservoirs can be implemented. In this paper we use a Stochastic Dynamic Programming model to optimize the yield from the aquifer of the Ridaura River. The objective function in this model was chosen with the aim of maximizing the reliability of the target yields in each of four seasons.     

SIMULATION OF SEDIMENT AND PLANT NUTRIENT LOSSES BY THE CREAMS WATER QUALITY MODEL1

ABSTRACT: CREAMS was applied to a field-sized watershed planted to cotton in the Limestone Valley region of northern Alabama. The field was cultivated for three years with conventional tillage (CvT) followed by three years of conservation tillage (CsT). CREAMS is composed of three components: hydrology, erosion, and chemistry. Surface runoff and losses of sediment, N and P were simulated and results were compared with the observed data from the watershed. Curve numbers recommended in the CREAMS user's guide were not adequate for the watershed conditions. The hydrology submodel improved runoff simulation from CvT and CsT when field-data based curve numbers were used. The erosion submodel demonstrated that CsT reduced sediment loss more than CvT, even though CsT had higher runoff than CvT. The nutrient submodel based on the simulated runoff and sediment underpredicted N loss for both CvT and CsT. This submodel, however, accurately predicted P loss for CvT, but underpredicted for CsT (50 percent lower than the observed). The results of CREAMS simulation generally matched the observed order of magnitude for higher runoff, lower sediment, and higher N and P losses from CsT than from CvT.     

WATERSHED CONFIGURATION AND GEOGRAPHIC INFORMATION SYSTEM PARAMETERIZATION FOR SPUR MODEL HYDROLOGIC SIMULATIONS1

ABSTRACT: A grid cell geographic information system (GIS) is used to parameterize SPUR, a quasi-physically based surface runoff model in which a watershed is configured as a set of stream segments and contributing areas. GIS analysis techniques produce various watershed configurations by progressive simplification of a stream network delineated from digital elevation models (DEM). We used three watershed configurations: ≥ 2nd, ≥ 4th, and ≥ 13th Shreve order networks, where the watershed contains 28, 15, and 1 channel segments with 66, 37, and 3 contributing areas, respectively. Watershed configuration controls simulated daily and monthly sums of runoff volumes. For the climatic and topographic setting in southeastern Arizona the ≥ 4th order configuration of the stream network and contributing areas produces results that are typically as good as the ≥ 2nd order network. However both are consistently better than the ≥ 13th order configuration. Due to the degree of parameterization in SPUR, model simulations cannot be significantly improved by increasing watershed configuration beyond the ≥ 4th order network. However, a range of Soil Conservation Service curve numbers derived from rainfall/runoff data can affect model simulations. Higher curve numbers yield better results for the ≥ 2nd order network while lower curve numbers yield better results for the ≥ 4th order network.     

WATER RESOURCES MODELING AND OPTIMIZATION BASED ON CONSERVATION AND FLOODING POOLS1

ABSTRACT: A new and practical concept in water resources modeling and optimization is introduced. Instead of unrealistically assuming a multipurpose reservoir to be composed of a single lumped pool of water, it is treated as two different pools namely conservation and flood pools. Based on this treatment, the optimization problem is stated using the concepts of Lagrange multipliers and parameter optimization. The optimization problem consists of the material balance equation, the constraints on control and state variables and the objective function.