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This article presents a summary of the information discussed on fertilizer management, irrigation scheduling, and drip system maintenance and troubleshooting. A list of additional references is also included. This document is HS917, one of a series of the Horticultural Sciences Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Publication date: March 2003. HS917/HS172: Drip Irrigation: The BMP Era?An Integrated Approach to Water and Fertilizer Management for Vegetables Grown with Plasticulture (ufl.edu)

This document is Fact Sheet ABE 326, one of a series of the Department of Agricultural and Biological Engineering, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. First published: August 2002. ABE326/TR015: Using Tensiometers for Vegetable Irrigation Scheduling in Miami-Dade County (ufl.edu)

Improving irrigation efficiency can contribute greatly to reducing production costs of vegetables, making the industry more competitive and sustainable. This publication is intended to help growers to conserve water through the use of soil moisture sensors. Written by Rafael Muñoz-Carpena, Michael D. Dukes, and Bernard Cardenas, and published by the UF/IFAS Department of Agricultural and Biological Engineering, revised August 2024.

Abstract Hydrologic resilience modeling is used in public watershed management to assess watershed ability to supply life-supporting ecoservices under extreme climatic and environmental conditions. Literature surveys criticize resilience models for failing to capture watershed dynamics and undergo adequate testing. Both shortcomings compromise their ability to provide management options reliably protecting water security under real-world conditions. We formulate an empirical protocol to establish real-world correspondence. The protocol applies empirical nonlinear dynamics to reconstruct hydrologic dynamics from watershed records, and analyze the response of reconstructed dynamics to extreme regional climatic conditions. We devise an AI-based early-warning system to forecast (out-of-sample) reconstructed hydrologic resilience dynamics. Application to the La Tejería (Spain) experimental watershed finds it to be a low dimensional nonlinear deterministic dynamic system responding to internal stressors by irregularly oscillating along a watershed attractor. Reconstructed and forecasted hydrologic resilience behavior faithfully captures monthly wet-cold/dry-warm weather patterns characterizing the Mediterranean region.

Grapefruit are well-adapted to arid and warm climatic conditions, but well-irrigated trees usually produce better-quality fruits. Because water is a major component of the fruits, there is a strong relationship between drought stress and fruits quality traits such as fruits size, external fruits color, and juice quality. The object of this study was to develop a computer model to predict postharvest external grapefruit color as a function of drought stress. During model development, drought stress was quantified using a concise water balance model based on crop evapotranspiration, precipitation, and irrigation. Data collected from Murcia, Spain, during the 2007 and 2008 growing seasons were used for model development, and the model was optimized by comparing model predictions and observations for each growing season. The root mean square error and Nash and Sutcliffe coefficient of efficiency (NSE) were used to evaluate model performance. Then, the model was evaluated with independent data collected from Florida during the 2005–06 growing season. A second-order polynomial relationship was found between external fruits color and drought stress, with less drought stress resulting in better external fruits color. Model optimization revealed good model performance for predicting external fruits color in Murcia, with NSE values of 0.975 and 0.979 for the 2007 and 2008 growing seasons, respectively. Model evaluation with the data from Florida showed that model predictions were reliable, with a NSE value of 0.984. A robust model to predict external grapefruit color as affected by drought stress was developed during the present study and could be potentially applied to supply information for suitable irrigation management of various grapefruit cultivars grown under different climatic conditions. Model performance could be confirmed by future research with data collection during further multiple seasons for different cultivars and a range of climatic conditions.

Abstract Past experimental work found that rill erosion occurs mainly during rill formation in response to feedback between rill-flow hydraulics and rill-bed roughness, and that this feedback mechanism shapes rill beds into a succession of step-pool units that self-regulates sediment transport capacity of established rills. The search for clear regularities in the spatial distribution of step-pool units has been stymied by experimental rill-bed profiles exhibiting irregular fluctuating patterns of qualitative behavior. We hypothesized that the succession of step-pool units is governed by nonlinear-deterministic dynamics, which would explain observed irregular fluctuations. We tested this hypothesis with nonlinear time series analysis to reverse-engineer (reconstruct) state-space dynamics from fifteen experimental rill-bed profiles analyzed in previous work. Our results support this hypothesis for rill-bed profiles generated both in a controlled lab (flume) setting and in an in-situ hillside setting. The results provide experimental evidence that rill morphology is shaped endogenously by internal nonlinear hydrologic and soil processes rather than stochastically forced; and set a benchmark guiding specification and testing of new theoretical framings of rill-bed roughness in soil-erosion modeling. Finally, we applied echo state neural network machine learning to simulate reconstructed rill-bed dynamics so that morphological development could be forecasted out-of-sample.

Study Region: Lake Okeechobee and its drainage basins, the Northern Lake Okeechobee (NLO) watershed, have faced climate variability and changes. The frequencies and magnitudes of extreme weather events are projected to increase in the future, and the impact of climate change on hydrological changes in upstream watersheds would significantly affect the water quality of downstream waterbodies. A holistic, system-wide modeling approach is necessary for a watershed–lake system. Study Focus: This study evaluated the impacts of climate change on the water quantity and quality of the NLO watershed–Lake Okeechobee system using a spatially integrated modeling framework combining watershed loading and receiving waterbody models together. Future climate projections and water level operation scenarios were incorporated into the modeling to investigate how the watershed–lake system may react to projected climate changes and how management practices can mitigate the impacts. New Hydrological Insights for the Region: The modeling results highlight that the water quality of the lake would be closely associated with the internal hydrodynamic process driven by wind and water level operation practices as well as external nutrient loads from the upstream drainage areas. Such findings indicate that the lake and watershed management requires implementation plans and practices to be uniquely customized to efficiently improve the lake’s water quality in the future depending on the types of issues: high nutrient loads, concentrations, and algal blooms.

Agent-based models (ABMs) simulate the behavior of complex systems from bottom to top so that macro-scale patterns emerge from randomized micro-scale interactions among autonomous agents and their environment. However, our ability to construct complex ABMs currently exceeds our capacity to evaluate their emergent dynamics, contributing to an explainability problem in convincing policymakers that in silico experimentation with ABMs can be trusted to correspond to the real world they are charged with regulating. While there is no universally agreed-upon approach for analyzing or benchmarking ABM dynamics, past work has emphasized statistical and probabilistic analyses. Consistent with a key feature of ABMs—the macro-level order emerges from micro-level randomness—we propose a deterministic analytical framework built from nonlinear time series methods to reveal an emergent low-dimensional dynamical structure concealed in complex ABM output. In particular, embedding ABM dynamics (time series) in a nonlinear state space enables diagnosis of a low-dimensional structure, inference of causal interaction regimes among macro-level variables, extraction of a phenomenological meta-model consisting of a system of ordinary differential equations, and benchmarking of ABMs against real-world systems, to establish credibility in the eyes of policymakers and stakeholders. We demonstrate the deterministic approach with a canonical model for virus outbreaks.

Although Richards’ equation (RE) generally provides a good description of infiltration and water redistribution in soils, its numerical solutions can be computationally intensive or suffer from numerical instability and require extensive soil data. Simplified physically based approaches are often used in many practical settings after validation against RE used as a benchmark. The purpose of this research was to develop and test an approximated physical model for simulating transient point-source infiltration and redistribution in a quasi three-dimensional flow domain. An existing three-dimensional Green–Ampt model that simulates only the infiltration phase is extended based on the one-dimensional modified Green–Ampt with redistribution (MGAR) method to calculate the three-dimensional soil water redistribution phase between point-source events. Comparison with the HYDRUS-2D numerical solution of RE showed the proposed model (3DMGAR) to provide satisfactory results for a broad range of soils. The ability of 3DMGAR to accurately and robustly simulate infiltration and redistribution for point-source water application time series is particularly important for cases with difficult Richards solutions, such as in sandy soils, to improve water application efficiency and decrease chemical leaching in many settings like crop fertigation, waste water disposal, and mitigation of climate-induced coastal salinization.

Unsaturated zone properties and processes are central to understanding the interacting effects of land-use change, contamination, and hydroclimate on our ability to grow food, sustain clean water supplies, and minimize loss of life and property. Advances in unsaturated zone science are being achieved through collaborations across traditional boundaries where information from biological, physical, and chemical disciplines is combined for new insights. The Unsaturated Zone Interest Group (UZIG) is an organization that exists principally to promote multidisciplinary collaborations and the sharing of ideas, expertise, and technical assets. Here we summarize key findings from 14 papers, several of which originated from a meeting convened by UZIG in 2017 at the University of Florida in Gainesville titled “Land-Use Change, Climate Change, and Hydrologic Extremes: Unsaturated Zone Responses and Feedbacks.” This special section of contains multidisciplinary research in three general categories relevant to measuring and understanding unsaturated zone responses to changing land uses and climate: (i) unsaturated zone properties and processes; (ii) soil–plant–atmosphere interactions; and (iii) novel field sampling devices. A strong cross-cutting theme in these papers is the value of continuous monitoring data and ways of utilizing them to discover novel hydrologic, biologic, and pedologic information. As climatic and land-use conditions change and demands for resources and stresses on ecosystems continue to intensify, it is vital to improve our fundamental understanding of the processes at work in the unsaturated zone. Toward that goal, we discuss the need for improved ground-based unsaturated zone monitoring networks.

The design and analysis of surface water pollution control practices such as vegetative filter strips and riparian buffers typically focus on surface runoff, with limited attention given to subsurface flow and transport. Field evidence suggests a prevalence of macropore flow (MF) in the riparian vadose zone (RVZ) due to abundant biological activity (e.g., fauna and roots) and steep hydraulic gradients created by the adjacent stream and the presence of a seasonally shallow water table (SWT). Because rapid leaching and subsurface transport of contaminants can be significant with MF, their prevalence in riparian buffers can negate the intended benefits of this widely adopted surface runoff pollution control practice. While theories exist for modeling preferential flow processes, experimental and modeling techniques are still lacking to characterize in situ RVZ macropore network morphologies at the soil profile and landscape scales. Importantly, the presence of a seasonal SWT can increase MF and transport processes neglected in current analyses. Additional research is needed to evaluate holistic modeling frameworks that can represent MF from measurable parameters at the riparian field scale. In this work, we review various MF theories and concepts suitable to RVZ conditions and identify current limitations and knowledge gaps. We emphasize the use of dual-permeability approaches as a compromise between model complexity and parameter identifiability. We also identify the need for well-controlled experimental studies using the latest monitoring technology and validation studies at the laboratory and field scales. Only then can decision-support tools realistically predict the influence of preferential flow processes on the performance of riparian buffers as a surface water quality control practice.

Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to improve our understanding of the role, magnitude, and spatial distribution of the key environmental and socioeconomic factors driving vegetation change in a southern African savanna. This research was conducted across the Kwando, Okavango and Zambezi catchments of southern Africa (Angola, Namibia, Botswana and Zambia) and explored vegetation cover change across the region from 2001-2010. A novel coupled analysis was applied to model the dynamic biophysical factors then to determine the discrete / social drivers of spatial heterogeneity on vegetation. Previous research applied Dynamic Factor Analysis (DFA), a multivariate times series dimension reduction technique, to ten years of monthly remotely sensed vegetation data (MODIS-derived normalized difference vegetation index, NDVI), and a suite of time-series (monthly) environmental covariates: precipitation, mean, minimum and maximum air temperature, soil moisture, relative humidity, fire and potential evapotranspiration. This initial research was performed at a regional scale to develop meso-scale models explaining mean regional NDVI patterns. The regional DFA predictions were compared to the fine-scale MODIS time series using Kendall's Tau and Sen's Slope to identify pixels where the DFA model we had developed, under or over predicted NDVI. Once identified, a Random Forest (RF) analysis using a series of static social and physical variables was applied to explain these remaining areas of under- and over- prediction to fully explore the drivers of heterogeneity in this savanna system. The RF analysis revealed the importance of protected areas, elevation, soil type, locations of higher population, roads, and settlements, in explaining fine scale differences in vegetation biomass. While the previously applied DFA generated a model of environmental variables driving NDVI, the RF work developed here highlighted human influences dominating that signal. The combined DFRFA model approach explains almost 90% of the variance in NDVI across this landscape from 2001-2010. Our methodology presents a unique coupling of dynamic and static factor analyses, yielding novel insights into savanna heterogeneity, and providing a tool of great potential for researchers and managers alike.

Deconstructing the drivers of large-scale vegetation change is critical to predicting and managing projected climate and land use changes that will affect regional vegetation cover in degraded or threated ecosystems. We investigate the shared dynamics of spatially variable vegetation across three large watersheds in the southern Africa savanna. Dynamic Factor Analysis (DFA), a multivariate time-series dimension reduction technique, was used to identify the most important physical drivers of regional vegetation change. We first evaluated the Advanced Very High Resolution Radiometer (AVHRR)- vs. the Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Difference Vegetation Index (NDVI) datasets across their overlapping period (2001–2010). NDVI follows a general pattern of cyclic seasonal variation, with distinct spatio-temporal patterns across physio-geographic regions. Both NDVI products produced similar DFA models, although MODIS was simulated better. Soil moisture and precipitation controlled NDVI for mean annual precipitation (MAP) < 750 mm, and above this, evaporation and mean temperature dominated. A second DFA with the full AVHRR (1982–2010) data found that for MAP < 750 mm, soil moisture and actual evapotranspiration control NDVI dynamics, followed by mean and maximum temperatures. Above 950 mm, actual evapotranspiration and precipitation dominate. The quantification of the combined spatio-temporal environmental drivers of NDVI expands our ability to understand landscape level changes in vegetation evaluated through remote sensing and improves the basis for the management of vulnerable regions, like the southern Africa savannas.

Man-made activities can induce climate change and global sea-level rise, posing threats to the survival and growth of coastal vegetation in Florida. This 3-page fact sheet explains how to ensure plant survival and facilitate the growth of coastal vegetation threatened by sea-level rise and the resulting oxygen deficiencies and saline stresses. Written by Guodong Liu, Yuncong Li, Kimberly Moore, Kim Gabel, Lei Wu, and Rafael Muñoz-Carpena, and published by the Horticultural Sciences Department, April 2016. HS1280/HS1280: How to Chemigate Salinity-Stressed Plants with Hydrogen Peroxide to Increase Survival and Growth Rates (ufl.edu)

Increasing numbers of pollutants have been observed in natural water systems. As awareness of agricultural sources of water pollution has grown, Best Management Practices (BMPs) have been specifically designed to address agricultural water pollutants and protect water quality. This 4-page fact sheet introduces one of the BMPs, Vegetative Filter Strips (VFSs), which efficiently control nonpoint pollution such as sediments, nutrients, and pesticides. The publication covers primary functions, key design factors, and maintenance of VFSs. Written by Lei Wu, Rafael Muñoz-Carpena, and Yuncong Li, and published by the UF Department of Soil and Water Science, October 2015. SL432/SS646: Vegetative Filter Strips—A Best Management Practice for Controlling Nonpoint Source Pollution (ufl.edu)

BACKGROUND: Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving vegetation change in southern African savanna, and how they vary across physiographic gradients. METHODOLOGY/PRINCIPAL FINDINGS: We applied Dynamic Factor Analysis (DFA), a multivariate times series dimension reduction technique to ten years of monthly remote sensing data (MODIS-derived normalized difference vegetation index, NDVI) and a suite of environmental covariates: precipitation, mean and maximum temperature, soil moisture, relative humidity, fire and potential evapotranspiration. Monthly NDVI was described by cyclic seasonal variation with distinct spatiotemporal patterns in different physiographic regions. Results support existing work emphasizing the importance of precipitation, soil moisture and fire on NDVI, but also reveal overlooked effects of temperature and evapotranspiration, particularly in regions with higher mean annual precipitation. Critically, spatial distributions of the weights of environmental covariates point to a transition in the importance of precipitation and soil moisture (strongest in grass-dominated regions with precipitation950 mm). CONCLUSIONS/SIGNIFICANCE: We quantified the combined spatiotemporal effects of an available suite of environmental drivers on NDVI across a large and diverse savanna region. The analysis supports known drivers of savanna vegetation but also uncovers important roles of temperature and evapotranspiration. Results highlight the utility of applying the DFA approach to remote sensing products for regional analyses of landscape change in the context of global environmental change. With the dramatic increase in global change research, this methodology augurs well for further development and application of spatially explicit time series modeling to studies at the intersection of ecology and remote sensing.

A tensiometer is a simple and relatively inexpensive tool that can be used to schedule irrigation in Miami-Dade County vegetable crops. Tensiometers continuously measure soil water potential or tension. If the tension in the soil is high, plants have to use more energy to extract soil water. If tension in the soil is low, then plants have lower energy requirements to extract soil water. This revised 6-page fact sheet was written by Kati W. Migliaccio, Teresa Olczyk, Yuncong Li, Rafael Muñoz-Carpena, and Tina Dispenza, and published by the UF Department of Agricultural and Biological Engineering, December 2012. ABE326/TR015: Using Tensiometers for Vegetable Irrigation Scheduling in Miami-Dade County (ufl.edu)

El manejo actual del recurso hídrico en la cuenca del Tempisque es insostenible y se predice que empeorará dadas las proyecciones de aumento de temperatura y condiciones de sequia en el futuro cercano. Describimos aquí los planes para realizar un análisis cuantitativo del suministro y la demanda del recurso hídrico en esta cuenca y explorar, a partir de datos empíricos y de la integración de información de distintos usuarios, cómo el cambio climático podría afectar los servicios ecosistémicos en términos de disponibilidad de agua, uso del suelo y biodiversidad. De esta manera, el proyecto intenta modelar esta información para investigar cuáles acciones deben acometerse para ayudar a mantener o mejorar el suministro de agua y los servicios ecosistémicos en el futuro.

BackgroundThe Gulf coastal ecosystems in Florida are foci of the highest species richness of imperiled shoreline dependent birds in the USA. However environmental processes that affect their macroecological patterns, like occupancy and abundance, are not well unraveled. In Florida the Snowy Plover (Charadrius alexandrinus nivosus) is resident along northern and western white sandy estuarine/ocean beaches and is considered a state-threatened species.Methodology/principal findingsHere we show that favorable nesting areas along the Florida Gulf coastline are located in regions impacted relatively more frequently by tropical cyclones. The odds of Snowy Plover nesting in these areas during the spring following a tropical cyclone impact are seven times higher compared to the odds during the spring following a season without a cyclone. The only intensity of a tropical cyclone does not appear to be a significant factor affecting breeding populations.Conclusions/significanceNevertheless a future climate scenario featuring fewer, but more extreme cyclones could result in a decrease in the breeding Snowy Plover population and its breeding range. This is because the spatio-temporal frequency of cyclone events was found to significantly affect nest abundance. Due to the similar geographic range and habitat suitability, and no decrease in nest abundance of other shorebirds in Florida after the cyclone season, our results suggest a common bioclimatic feedback between shorebird abundance and tropical cyclones in breeding areas which are affected by cyclones.

Revised! ABE368, a 6-page fact sheet by Kati W. Migliaccio, Jonathan H. Crane, Edward Evans, Bruce Schaffer, Yuncong Li, and Rafael Muñoz-Carpena, presents results of fruit grower responses from a survey designed to assess changing views of agricultural producers in Miami-Dade county from 2006 to 2009 regarding water quantity and quality management practices — methods, demographics, water quality and quantity opinions concerning lifestyle, agriculture, and best management practices (BMPs). Includes references. Published by the UF Department of Agricultural and Biological Engineering, November 2009.

HS-1059, a 6-page fact sheet by David Studstill, Eric Simonne, Teresa Olczyk, Rafael-Munoz Carpena, presents the results of a study of flow rates on calcareous soils using dyes to observe the movement of water in the beds under various flow rates and emitter spacings. Published by the UF Horticultural Sciences Department, March 2006. HS1059/HS313: Water Movement in Mulched Beds in Rocky Soils of Miami-Dade County (ufl.edu)

ABE-368, a 5-page fact sheet by Kati W. Migliaccio, Jonathan H. Crane, Edward Evans, Bruce Schaffer, Yuncong Li, and Rafael Muñoz-Carpena, presents the results of a survey designed to assess changing views of tropical fruit producers in Miami-Dade County regarding water quantity and quality management practices. Published by the UF Department of Agricultural and Biological Engineering, July 2006.

ABE-369, a 5-page fact sheet by Kati W. Migliaccio, Edward Evans, Jonathan H. Crane, Bruce Schaffer, Yuncong Li, and Rafael Muñoz -Carpena, presents the results of a survey designed to assess changing views of ornamental plant producers in Miami-Dade County regarding water quantity and quality management practices. Published by the UF Department of Agricultural and Biological Engineering, July 2006.

Chemigation is a process by which an irrigation system is used for transport and delivery of an agrochemical, generally fertilizers or pesticides, to a crop. Often times, the irrigation system used in chemigation is drip irrigation. The purpose of this report is to provide some helpful tips for papaya growers interested in chemigation. This document is ABE 360, one of a series of the Department of Agricultural and Biological Engineering, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, Universtiy of Florida. First printing: August 2005.

Improving irrigation efficiency can contribute greatly to reducing production costs of vegetables, making the industry more competitive and sustainable. Through proper irrigation, average vegetable yields can be maintained (or increased) while minimizing environmental impacts caused by excess applied water and subsequent agrichemical leaching. Recent technological advances have made soil water sensors available for efficient and automatic operation of irrigation systems. Automatic soil water sensor-based irrigation seeks to maintain a desired soil water range in the root zone that is optimal for plant growth. This document is AE354, one of a series of the Department of Agricultural and Biological Engineering, UF/IFAS Extension. Original publication date June 2005. AE354/AE354: Automatic Irrigation Based on Soil Moisture for Vegetable Crops (ufl.edu)

This fact sheet reports on the part of a survey that addressed growers sources of notification and information on water management and conservation in Miami-Dade County. This document is ABE349, one of a series of the Agricultural and Biological Engineering Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Published February 2005.

In the context of water management for irrigation, measuring and monitoring soil water status is an essential component of best management practices (BMPs) to improve the sustainability of agriculture. This document is Bulletin 343, one of a series from the Department of Agricultrural and Biological Engineering, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. First publihsed: July 2004. This document replaces in part CIR 532. BUL343/AE266: Field Devices For Monitoring Soil Water Content (ufl.edu)

This fact sheet reports water conservation trends from golf course managers based on an extensive survey carried out in Miami-Dade County. This document is Fact Sheet ABE348, one of a series of the Agricultural and Biolgoical Engineering Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Published January 2004. https://edis.ifas.ufl.edu/ae259

This fact sheet reports water conservation trends for ornamental nursery producers based on an extensive survey carried out in Miami-Dade County. This document is Fact Sheet ABE347, one of a series of Agricultural and Biolgoical Engineering Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Published December 2003. https://edis.ifas.ufl.edu/ae260

This fact sheet reports water conservation trends for tropical fruit producers based on an extensive survey carried out in Miami-Dade County. This document is Fact Sheet ABE345, one of a series of the Agricultural and Biological Engineering Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Published December 2003. https://edis.ifas.ufl.edu/ae257

This fact sheet reports water conservation trends for vegetable producers based on an extensive survey carried out in Miami-Dade County. This document is Fact Sheet ABE346, one of a series of Agricultural and Biological Engineering Department, Florida Cooperative Exension Service, Institute of Food and Agricultural Sciences, University of Florida. Published December 2003. https://edis.ifas.ufl.edu/ae258

This document is ABE 333, one of a series of the Agricultural and Biological Engineering Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Original publication date: October 2002. ABE 333/AE230: Alternatives of Low Cost Soil Moisture Monitoring Devices for Vegetable Production in South Miami-Dade County (ufl.edu)