Owens Valley Vegetation Condition Report

Introduction

This repository contains the code and data for the Owens Valley Vegetation Condition Report, which is part of the Inyo-LA Technical Group's annual monitoring program. The report follows the guidelines described in the Green Book Box I.C.1.a.ii for monitoring vegetation response to groundwater pumping. The goal is to identify and evaluate groundwater-dependent vegetation parcels that exhibit significant deviations from baseline conditions.

Objectives

The primary objectives of this report are:

1. To provide a summary of the annual monitoring program.
2. To flag groundwater-dependent vegetation parcels in wellfield areas with significant deviations from the 1984-87 vegetation baseline.
3. To identify parcels that have been below baseline for five consecutive years.
4. To corroborate significant trends using NDVI time series data.

Data and Methods

Baseline Data

From September 1984 to November 1987, LADWP inventoried and mapped vegetation on LA-owned lands in Owens Valley into 2,126 polygons of similar vegetation type, covering 223,168 acres. The monitoring program focuses on a subset of these groundwater-dependent parcels that are affected by groundwater pumping.

Monitoring Sample Size

Parcels were selected based on several criteria, including the presence of permanent monitoring sites, proximity to pumping wells, and availability of past and current land use data. Over the years, the number of sampled parcels has varied due to staffing availability, with a total of 192 parcels sampled at least once after the baseline period.

Statistical Methods

Welch's t-test for unequal variance is used to evaluate deviations in total perennial cover and perennial grass cover from baseline conditions. For parcels with low baseline sample sizes, a one-sample t-test is performed. The statistical methods described in Green Book Box I.C.1.a.ii are implemented using a transparent and reproducible data pipeline written in R.

Data Aggregation

Perennial species cover is analyzed because annual species are not dependent on groundwater. Perennial cover is aggregated into grass, herb, and shrub categories. The proportion of shrub, herb, and grass cover as fractions of total perennial cover is calculated to analyze changes over time.

Results

The results section includes a comparison of control and wellfield parcel groups, rarefied to those parcels sampled every year since 1992. Linear trends for total cover, perennial herbaceous cover, and shrub cover are reported. Detailed maps showing parcel-level changes in perennial cover and grass cover are provided for each wellfield.

Discussion

The methods outlined in this report automatically flag wellfield parcels that have been statistically below baseline for the past five consecutive years in terms of total perennial cover or perennial grass cover. The measurability of the effect has been determined according to Green Book Section I.C.1.a. Steps to determine the causation of the measurable change are outlined in Green Book Section I.C.1.b. Detailed information on each flagged parcel is available for further investigation.

Repository Structure

• code/: Contains R scripts for data processing and analysis.
• data/: Contains raw and processed data files (to be added).
• docs/: Documentation files.
• figures/: Contains figures and maps used in the report.
• images/: Contains image files for the report.
• output/: Contains generated reports and summary tables.
• .gitignore: Lists files and directories to be ignored by git.
• LICENSE: License for the project.
• README.md: This file.
• _targets.R: Configuration file for the targets pipeline.
• _quarto.yml: Configuration file for Quarto.
• index.qmd: Quarto markdown file for the main report.

Getting Started

Prerequisites

Ensure you have the following software installed:

• R
• RStudio
• Required R packages (listed in the setup chunk of the R scripts)

Installation

1. Clone the repository:

   git clone https://github.com/inyo-gov/vegetation-condition.git
   cd vegetation-condition

2. Install required R packages:

   install.packages(c("targets", "tidyverse", "rmarkdown", "DT", "htmlwidgets", "sf", "tmap", "tmaptools", "ggpmisc", "ggpubr", "gt", "glue", "ggdist", "here", "ggstatsplot", "janitor", "withr", "rprojroot"))

Building the Targets Pipeline

Before running the report, you need to build the targets pipeline. This will ensure that all necessary data processing steps are completed.

1. Open the R project in RStudio.
2. Load the targets package and build the pipeline:

   library(targets)
   tar_make()

Running the Analysis

1. Once the targets pipeline is built, open the main analysis script (e.g., index.qmd) and execute the code chunks to generate the report.

Viewing the Report

The final report will be generated as an HTML file in the output/ directory. Open this file in a web browser to view the results.

Contributing

Contributions to improve the report and code are welcome. Please submit issues or pull requests on the GitHub repository.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

We acknowledge the efforts of the Inyo County Water Department and the Los Angeles Department of Water and Power in data collection and monitoring. Special thanks to all contributors and reviewers of this report.

For more information, visit Inyo County Water Department.