Statistics for Spatial Data.

treatment, and promote mental health and well-being resources, appropriate new technology, and financial services, including microfinance

Sustainable Development Goals

In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Forecasting, Structural Time Series Models and the Kalman Filter

Find loads of the research methods in the social sciences book catalogues in this site as the choice of you visiting this page. You can also join to the website book library that will show you numerous books from any types. Literature, science, politics, and many more catalogues are presented to offer you the best book to find. The book that really makes you feels satisfied. Or that's the book that will save you from your job deadline.

Research methods in the social sciences

The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the USDA Agricultural Research Service (ARS). SWAT has gained international acceptance as a robust interdisciplinary watershed modeling tool as evidenced by international SWAT conferences, hundreds of SWAT-related papers presented at numerous other scientific meetings, and dozens of articles published in peer-reviewed journals. The model has also been adopted as part of the U.S. Environmental Protection Agency (USEPA) Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) software package and is being used by many U.S. federal and state agencies, including the USDA within the Conservation Effects Assessment Project (CEAP). At present, over 250 peer-reviewed published articles have been identified that report SWAT applications, reviews of SWAT components, or other research that includes SWAT. Many of these peer-reviewed articles are summarized here according to relevant application categories such as streamflow calibration and related hydrologic analyses, climate change impacts on hydrology, pollutant load assessments, comparisons with other models, and sensitivity analyses and calibration techniques. Strengths and weaknesses of the model are presented, and recommended research needs for SWAT are also provided.

/pdf/the-soil-and-water-assessment-tool-historical-development-4e4d97tdfq.pdf

The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions

The water quality of a waterbody is determined by internal hydrodynamic processes as well as external loadings. Understanding the interaction between the external loading and internal process of a waterbody is essential for efficient water management and water quality improvement. Studies and efforts have focused on water and nutrient loading from drainage watersheds, but the contribution of the waterbody's internal process to water quality is often ignored and not well documented. This study investigated how the water quality of Lake Okeechobee is controlled by external and internal factors using statistical and numerical modeling approaches. Water quantity and quality observed at the outlets of the Lake Okeechobee drainage basins and 19 monitoring sites located within the lake were statistically analyzed using multilinear regression. A three-dimensional numerical model, namely Environmental Fluid Dynamics Code (EFDC), was calibrated to the observations to mathematically represent the lake's internal hydrodynamic process. The multilinear regression found that the water quality was the most sensitive to air temperature, the total phosphorus (TP) concentration of inflow entering the lake from the Kissimmee River basins, and the amount of outflow discharged from the lake among external factors. However, the regression models and their explanatory power were substantially varied by the monitoring stations. The model parameter sensitivity analysis of the calibrated EFDC model showed that model parameters related to the lake's internal algal processes including algal growth, predation, and basal metabolism rates had greater impacts on algal biomass than other model parameters controlling nutrient-related processes such as nutrient half-saturation and hydrolysis rates. The EFDC input data sensitivity analysis found that wind (speed) is the major driving force for the internal hydrodynamic processes; its impact on algal biomass was greater than those of the external loadings. In addition, the algal biomass was found to have an inverse relationship with wind-induced horizontal currents. The results demonstrate the dynamic contribution of the internal and external drivers to the water quality of Lake Okeechobee, suggesting the need to consider both internal hydrodynamic and external loading processes for efficient water quality improvement of the lake.

Quantifying the contribution of external loadings and internal hydrodynamic processes to the water quality of Lake Okeechobee.

This study was conducted to evaluate the accuracy of a simple model, based on the “drained to equilibrium” concept, for predicting soil water dynamics in the presence of a fluctuating, shallow, transient water table. This concept assumes that soil water is primarily due to capillary rise from the water table. Water table depth varied between 1.8 and 2.3 m (with a mean of 2.0 m) during this study. The model was evaluated under four field conditions: (i) deep soil created by trenching, with tree roots, (ii) deep soil created by trenching, without tree roots, (iii) shallow soil with tree roots, and (iv) shallow soil without tree roots. Collocated water table and soil water content data at the 10-, 20-, 40-, and 60-cm depths were collected in a lychee ( Litchi chinensis Sonn.) orchard in Homestead, FL. Hydrostatic conditions were identified and van Genuchten parameters were determined using the filtered data set and the van Genuchten equation; accuracy of the predictions was assessed with the Nash–Sutcliffe coefficient of efficiency ( C eff ). The greatest variability in soil water content was measured at the 10-cm depth, while at other depths the soil water content was more consistent. In general, for the highly permeable soils and predominantly dry conditions tested, the drained-to-equilibrium model evaluated in this study proved to be a simple one-dimensional physical expression that predicted soil water content well (median C eff = 0.85) based on a shallow water table level. This information can be used to improve irrigation scheduling and flood management in shallow groundwater systems.

Predicting Soil Water Content Using the “Drained to Equilibrium” Concept

Parameter Variability and Drought Models: A Study Using the Agricultural Reference Index for Drought (ARID)

The coupled regional simulation model, and the transport and reaction simulation engine were recently adapted to simulate ecology, specifically Typha domingensis (Cattail) dynamics in the Everglades. While Cattail is a native Everglades species, it has become invasive over the years due to an altered habitat over the last few decades, taking over historically Cladium jamaicense (Sawgrass) areas. Two models of different levels of algorithmic complexity were developed in previous studies, and are used here to determine the impact of various management decisions on the average Cattail density within Water Conservation Area 2A in the Everglades. A Global Uncertainty and Sensitivity Analysis was conducted to test the importance of these management scenarios, as well as the effectiveness of using zonal statistics. Management scenarios included high, medium and low initial water depths, soil phosphorus concentrations, initial Cattail and Sawgrass densities, as well as annually alternating water depths and soil phosphorus concentrations, and a steadily decreasing soil phosphorus concentration. Analysis suggests that zonal statistics are good indicators of regional trends, and that high soil phosphorus concentration is a pre-requisite for expansive Cattail growth. It is a complex task to manage Cattail expansion in this region, requiring the close management and monitoring of water depth and soil phosphorus concentration, and possibly other factors not considered in the model complexities. However, this modeling framework with user-definable complexities and management scenarios, can be considered a useful tool in analyzing many more alternatives, which could be used to aid management decisions in the future.

Accounting for the Impact of Management Scenarios on Typha Domingensis (Cattail) in an Everglades Wetland

Design of vegetative filter strips for trapping sediment and sediment-borne chemicals can be done on a stormevent basis using VFSMOD. This approach requires confidence in a number of input parameters such as soil infiltration characteristics, surface topography, vegetative composition and roughness, and incoming sediment load and particle size distribution. We have developed a simple program, UH, to estimate runoff hydrographs and sediment transport from a source area based on the NRCS Unit Hydrograph Method and the Modified Universal Soil Loss Equation (MUSLE). VFSMOD uses this information from the source area to predict the amount of sediment trapped in the filter strip. UH and VFSMOD have been integrated into one system using a graphical user interface program, VFSMOD-W. The integrated system allows the user to develop input data sets and perform complex modeling analyses such as sensitivity and uncertainty analyses.

VFSMOD-W a graphical Windows system for the evaluation and design of vegetative filter strips for sediment trapping 1

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Rafael Muñoz-Carpena

Author Tools

Chat about Author