Christopher J. Martinez

Bio: Christopher J. Martinez is an academic researcher from University of Florida. The author has contributed to research in topics: Climate change & Forecast skill. The author has an hindex of 21, co-authored 66 publications receiving 1338 citations. Previous affiliations of Christopher J. Martinez include Florida State University.

Estimating Reference Evapotranspiration with Minimum Data in Florida

Abstract: Reference evapotranspiration estimation methods that require minimal data are necessary when climatic data sets are incomplete, inaccurate, or unavailable. This study was conducted to evaluate temp...

A Review of Turfgrass Fertilizer Management Practices: Implications for Urban Water Quality

Abstract: Urban watersheds include extensive turfgrass plantings that are associated with anthropocentric attitudes toward landscapes. Native and constructiondisturbed urban soils often cannot supply adequate amounts of nitrogen (N) and phosphorus (P) for the growth and beauty of landscape plants. Hence, fertilization of landscape plants is practiced. Mismanaged fertilization and irrigation practices represent a potential source of nutrients that may contribute to water quality impairment. This review focuses on turfgrass fertilization practices and their impacts on urban water quality. Research results show that fertilization during active growth periods enhances turfgrass nutrient uptake efficiencies. The major concern regarding the fertilization of turfgrass and landscape plants in urban watersheds, therefore, is selecting the proper combination of fertilizer rate, timing, and placement that maximizes nutrient utilization efficiency and reduces the risk for nutrient loss to water bodies. Encouraging individuals to adopt best management practices (BMPs) is a priority for watershed managers. Research has found that educational programs are an important part of changing fertilization habits and that education needs to be thorough and comprehensive, which is beyond the scope of many seminars and fact sheets currently in use.

The Environmental Protection Agency

Abstract: The Environmental Protection Agency (EPA) provides access to information on a variety of topics related to the environment and strives to inform citizens of health risks. The EPA also has an extensive library network that consists of 26 libraries throughout the United States, which provide access to a plethora of information to EPA employees, scientists, and researchers. The EPA implemented a reorganization project to digitize their materials so they would be more accessible to a wider range of users, but this plan was drastically accelerated when the EPA was threatened with a budget cut. It chose to close and reduce the hours and services of some of their libraries. As a result, the agency was accused of denying users the “right to know” by making information unavailable, not providing an adequate strategic plan, and discarding vital materials. This case study explores the background of the digitization project, the practices implemented, and the critiques of the project.

Hydrologic and Water Quality Models: Performance Measures and Evaluation Criteria

Abstract: Performance measures (PMs) and corresponding performance evaluation criteria (PEC) are important aspects of calibrating and validating hydrologic and water quality models and should be updated with advances in modeling science. We synthesized PMs and PEC from a previous special collection, performed a meta-analysis of performance data reported in recent peer-reviewed literature for three widely published watershed-scale models (SWAT, HSPF, WARMF), and one field-scale model (ADAPT), and provided guidelines for model performance evaluation. Based on the synthesis, meta-analysis, and personal modeling experiences, we recommend coefficient of determination (R2; in conjunction with gradient and intercept of the corresponding regression line), Nash Sutcliffe efficiency (NSE), index of agreement (d), root mean square error (RMSE; alongside the ratio of RMSE and standard deviation of measured data, RSR), percent bias (PBIAS), and several graphical PMs to evaluate model performance. We recommend that model performance can be judged satisfactory for flow simulations if monthly R2 0.70 and d 0.75 for field-scale models, and daily, monthly, or annual R2 0.60, NSE 0.50, and PBIAS ≤ ±15% for watershed-scale models. Model performance at the watershed scale can be evaluated as satisfactory if monthly R2 0.40 and NSE 0.45 and daily, monthly, or annual PBIAS ≤ ±20% for sediment; monthly R20.40 and NSE 0.35 and daily, monthly, or annual PBIAS ≤ ±30% for phosphorus (P); and monthly R2 0.30 and NSE 0.35 and daily, monthly, or annual PBIAS ≤ ±30% for nitrogen (N). For RSR, we recommend that previously published PEC be used as detailed in this article. We also recommend that these PEC be used primarily for the four models for which there were adequate data, and used only with caution for other models. These PEC can be adjusted within acceptable bounds based on additional considerations, such as quality and quantity of available measured data, spatial and temporal scales, and project scope and magnitude, and updated based on the framework presented herein. This initial meta-analysis sets the stage for more comprehensive meta-analysis to revise PEC as new PMs and more data become available.