Drought in Arizona

Proposal

Data visualization

Author

Graph Gurus - Akranth, Hari, Nikitha, Swetha

Packages Setup

Installed Packages

### GETTING THE LIBRARIES
if (!require(pacman))
  install.packages(pacman)

pacman::p_load(tidyverse,
               formattable,
               dlookr,
               readxl,
               writexl)

Did You Know?

Did you know that Arizona has been in a drought for 27 years? with the land thirsting for water and our water supplies running low this isn’t the first time. Twice before, in the 1900s and 1950s, we faced similar tough times. The drought we’re in now started in the late 1990s and hasn’t stopped.

Introduction

This enduring drought in Arizona presents more than a climatic challenge; it disrupts the balance of life, affecting everything from our environment to the economy. It’s evolving drought conditions, not only impact the state’s immediate well-being but also have far-reaching implications for its future.

Our desire to explore and interpret the data on Arizona’s drought conditions is a combination of curiosity and the recognition that water scarcity is an issue that resonates deeply with the state’s residents. By delving into this database, will allow us to gain valuable insights into the dynamic nature of Arizona’s drought experiences. Additionally, during our recent interactions with a group of individuals actively raising awareness about the dire drought situation in Arizona and the adverse effects of water wastage, we were inspired to investigate this interesting topic. This exploration would not only provide us with valuable data for our visualization but also offer a profound understanding of the challenges faced by the state. Our aim is to create easy-to-understand visuals that show what’s happening and get people thinking about solutions. We’ll look closely at how different areas are dealing with water shortages to figure out where to focus our efforts to help.

Why this dataset

We chose the Arizona’s Drought Conditions dataset sourced from the Arizona Drought Monitoring Technical Committee, because it offers real-time, up-to-date information right up to the present. This allows us to analyze ongoing drought patterns and make immediate, informed decisions for water conservation and resource management in Arizona.

The Dataset

#Importing the dataset using read_excel
data <- read_excel("./Shiny App/data/drought_data.xlsx")

The Arizona Drought Conditions Dataset is a comprehensive collection of data that provides crucial insights into short-term and long-term drought conditions in various counties within the state of Arizona. from the year 2000 to the present. This dataset is used to monitor and report drought conditions, serving as a valuable resource for researchers, policymakers, and the general public. The data is sourced from the Arizona Drought Monitoring Technical Committee, which convenes weekly to advise the U.S. Drought Monitor authors on the current drought conditions in Arizona. This information influences the official record of drought for Federal drought relief claims.

This dataset allows users to explore drought conditions for the entire state of Arizona or for specific counties, and it covers a time span of over two decades. It is updated on a monthly basis, providing a valuable resource for monitoring and understanding drought patterns in the region.

#Properties of the dataset 
data |>
  diagnose() |>
  formattable()

variables	types	unique_count	unique_rate
Date	POSIXct	1189	6.666667e-02
County	character	17	9.531819e-04
State	character	1	5.606953e-05
None	numeric	1319	7.395571e-02
D0	numeric	2688	1.507149e-01
D1	numeric	3036	1.702271e-01
D2	numeric	2590	1.452201e-01
D3	numeric	1463	8.202972e-02
D4	numeric	429	2.405383e-02

Description of the Dataset

The data-set contains 17,386 rows and 9 columns, showing Arizona’s drought numbers by county since 2000 to present:

Date : This column represents the date for which the drought conditions are recorded. It is in the format “MM-DD-YYYY” and serves as the temporal dimension for the dataset.
County : This column specifies the name of the county within Arizona for which the drought conditions are being reported. Each row represents a different county.
State : This column specifies the state, which is “AZ” for Arizona. It is a constant value for all rows, indicating the state where the data is collected.

Drought Level Definitions
None - No dry or drought conditions.
D0 - Abnormally dry conditions are characterized by short-term dryness that may slow planting, growth of crops or pastures.
D1 - Moderate drought conditions may cause the development of water shortages and fire activity to increase.
D2 - Severe drought conditions may lead to large surface water levels dropping and crop/pasture losses.
D3 - Extreme drought conditions may lead to widespread water shortages and major crop/pasture losses.
D4 - Exceptional drought conditions are characterized by shortages of water in reservoirs, streams, and wells as well as high wildfire counts and exceptional and widespread crop/pasture losses.

Research Question

How have drought conditions evolved across different counties in Arizona from 2000 to the present, and what are the implications for water resource management and policy-making?

Goal

The goal of our project is to develop an Interactive Drought Dashboard that presents a detailed view of Arizona’s drought conditions from 2000 to the present. This interactive tool allows users to examine drought trends over time and analyze the data for specific time frames or particular counties, providing a dynamic and user-focused experience.

Analysis

We plan to build an interactive dashboard with several key components, designed to offer both a broad overview and detailed examination of drought trends across the state’s counties. Here’s how we will approach the analysis:

Geographic Visualization :

Shows a map of Arizona that displays the counties present in Arizona. When we want to visualize a particular county, we can do so by clicking that county on the map. This filters that county’s data for the entire dashboard.

Time Series Analysis :

A time series plot shows the evolution of drought levels (D0, D1, D2, D3, D4, None) over time. Each of these drought levels are stacked above each other for easier comparison.
This also allows users to filter data by county, severity level, or a combination of these factors.

Statistical Insights:

We plan on making a stacked bar plot, showing the average drought levels of each category through the years and a pie chart showing the spread of drought levels.
This will provide summary statistics and trends in drought severity for different counties and time periods.

Interactivity:

We will incorporate user-friendly interactive features, such as dropdown menus, sliders, and checkboxes, for selecting and filtering data.
We will also implement tool tips and hover effects on the map for detailed information when the user interacts with data points.

Risk assessment analysis

Choropleth Maps:

These maps are represent various levels of drought severity with different colors across the geographical layout of Arizona. They provide a quick and clear way to see which counties are most at risk and how the severity of drought conditions varies across the state.

Stacked Area Charts:

They show the cumulative impact of different drought severity levels over time. It can illustrate how much of the state is affected by each category of drought and how these proportions change from year to year.

Implementation Plan:

Our high level implementation plan includes:

1. Data Collection and Preparation:

Obtain the drought dataset for Arizona, which includes county, time, and drought severity levels (D0, D1, D2, D3, D4, None) and another dataset for plotting the map of Arizona.
Clean and preprocess the data to ensure consistency, handle missing values, and format it for visualization.

2. Choose Tools and Libraries:

Select R programming and relevant libraries for creating interactive visualizations, such as Shiny for building the web application, Leaflet for mapping, and ggplot2 for time series plots.

3. Design the User Interface (UI):

Plan the layout and design of the dashboard. Consider a user-friendly and responsive design that allows users to easily navigate and interact with the data.

4. Geographic Visualization:

Use Leaflet to create a map that represents the different counties in Arizona to let the users choose from them.

5. Time Series Analysis:

Use ggplot2 to generate time series plots for drought severity over time.
Add interactive features to allow users to filter and explore data based on counties, severity levels, or date ranges.

6. Statistical Insights:

Make the pie chart and stacked barplot using ggplot2, and compute summary statistics, trends, and forecasts based on the dataset.
Present these insights in a user-friendly and easily understandable format.

7. Integrate with Shiny:

Create a Shiny web application that combines the geographic map, time series plots, pie chart, stacked bar chart and statistical insights.

Weekly plan of action

Week	Weekly Tasks	Person in charge
Week 5	Work on the Peer review feedback and submit final proposal	Everyone
Week 6	Understanding the basics , exploring shiny app	Everyone
	Assign induvidial tasks
Week 7	Data Exploration, Data Cleaning, Data preprocesing	Everyone
	create plots: 1. pie chart that shows the average percentage of each drought level from 2000 to present. 2. The bar chart that shows the average percentage of each drought level by year from 2000 to present. 3. The time-series that shows weekly drought levels in square miles for the state. 4. Geographical map	TBD
Week 8	Explore shiny and ways to integrate our visualizations and shiny
Week 9	start creating an interactive dashboard	TBD
	start working on the report	TBD
Week 10	final peer review and presentations	Everone

Repo Organization

The following are the folders involved in the Project repository.

‘data/’: Used for storing our input data file.
‘images/’: Used for storing image files used in the project.
‘presentation_files/’: Folder for having presentation related files.
‘_extra/’: Used to brainstorm our analysis which won’t impact our project workflow.
‘_freeze/’: This folder is used to store the generated files during the build process. These files represent the frozen state of the website at a specific point in time.
‘_site/’: Folder used to store the generated static website files after the site generator processes the quarto document.
‘.github/’: Folder for storing github templates and workflow.

--- title: "Drought in Arizona" subtitle: "Proposal" author: - name: " Graph Gurus - Akranth, Hari, Nikitha, Swetha" format: html: code-tools: true code-overflow: wrap code-line-numbers: true embed-resources: true editor: visual code-annotations: hover categories: - Data visualization execute: warning: false --- ### Packages Setup ```{r load packages, message=FALSE, output=FALSE} #| label: load-pkgs #| message: false #| warning: false #| output: false #| code-fold: true #| code-summary: "Installed Packages" ### GETTING THE LIBRARIES if (!require(pacman)) install.packages(pacman) pacman::p_load(tidyverse, formattable, dlookr, readxl, writexl) ``` ## Did You Know? Did you know that Arizona has been in a drought for 27 years? with the land thirsting for water and our water supplies running low this isn't the first time. Twice before, in the 1900s and 1950s, we faced similar tough times. The drought we're in now started in the late 1990s and hasn't stopped. ## Introduction This enduring drought in Arizona presents more than a climatic challenge; it disrupts the balance of life, affecting everything from our environment to the economy. It's evolving drought conditions, not only impact the state's immediate well-being but also have far-reaching implications for its future. Our desire to explore and interpret the data on Arizona's drought conditions is a combination of curiosity and the recognition that water scarcity is an issue that resonates deeply with the state's residents. By delving into this database, will allow us to gain valuable insights into the dynamic nature of Arizona's drought experiences. Additionally, during our recent interactions with a group of individuals actively raising awareness about the dire drought situation in Arizona and the adverse effects of water wastage, we were inspired to investigate this interesting topic. This exploration would not only provide us with valuable data for our visualization but also offer a profound understanding of the challenges faced by the state. Our aim is to create easy-to-understand visuals that show what's happening and get people thinking about solutions. We'll look closely at how different areas are dealing with water shortages to figure out where to focus our efforts to help. ## Why this dataset We chose the Arizona's Drought Conditions dataset sourced from the Arizona Drought Monitoring Technical Committee, because it offers real-time, up-to-date information right up to the present. This allows us to analyze ongoing drought patterns and make immediate, informed decisions for water conservation and resource management in Arizona. ## The Dataset ```{r dataset, message=FALSE} #Importing the dataset using read_excel data <- read_excel("./Shiny App/data/drought_data.xlsx") ``` The Arizona Drought Conditions Dataset is a comprehensive collection of data that provides crucial insights into short-term and long-term drought conditions in various counties within the state of Arizona. from the year 2000 to the present. This dataset is used to monitor and report drought conditions, serving as a valuable resource for researchers, policymakers, and the general public. The data is sourced from the Arizona Drought Monitoring Technical Committee, which convenes weekly to advise the U.S. Drought Monitor authors on the current drought conditions in Arizona. This information influences the official record of drought for Federal drought relief claims.\ \ This dataset allows users to explore drought conditions for the entire state of Arizona or for specific counties, and it covers a time span of over two decades. It is updated on a monthly basis, providing a valuable resource for monitoring and understanding drought patterns in the region. ```{r} #Properties of the dataset data |> diagnose() |> formattable() ``` ### Description of the Dataset The data-set contains 17,386 rows and 9 columns, showing Arizona's drought numbers by county since 2000 to present: - Date : This column represents the date for which the drought conditions are recorded. It is in the format "MM-DD-YYYY" and serves as the temporal dimension for the dataset. - County : This column specifies the name of the county within Arizona for which the drought conditions are being reported. Each row represents a different county. - State : This column specifies the state, which is "AZ" for Arizona. It is a constant value for all rows, indicating the state where the data is collected.\ \ **Drought Level Definitions** - None - No dry or drought conditions. - D0 - Abnormally dry conditions are characterized by short-term dryness that may slow planting, growth of crops or pastures. - D1 - Moderate drought conditions may cause the development of water shortages and fire activity to increase. - D2 - Severe drought conditions may lead to large surface water levels dropping and crop/pasture losses. - D3 - Extreme drought conditions may lead to widespread water shortages and major crop/pasture losses. - D4 - Exceptional drought conditions are characterized by shortages of water in reservoirs, streams, and wells as well as high wildfire counts and exceptional and widespread crop/pasture losses. ## Research Question How have drought conditions evolved across different counties in Arizona from 2000 to the present, and what are the implications for water resource management and policy-making? ## Goal The goal of our project is to develop an Interactive Drought Dashboard that presents a detailed view of Arizona's drought conditions from 2000 to the present. This interactive tool allows users to examine drought trends over time and analyze the data for specific time frames or particular counties, providing a dynamic and user-focused experience. ## Analysis We plan to build an interactive dashboard with several key components, designed to offer both a broad overview and detailed examination of drought trends across the state's counties. Here's how we will approach the analysis: 1. **Geographic Visualization :** - Shows a map of Arizona that displays the counties present in Arizona. When we want to visualize a particular county, we can do so by clicking that county on the map. This filters that county's data for the entire dashboard. 2. **Time Series Analysis :** - A time series plot shows the evolution of drought levels (D0, D1, D2, D3, D4, None) over time. Each of these drought levels are stacked above each other for easier comparison. - This also allows users to filter data by county, severity level, or a combination of these factors. 3. **Statistical Insights:** - We plan on making a stacked bar plot, showing the average drought levels of each category through the years and a pie chart showing the spread of drought levels. - This will provide summary statistics and trends in drought severity for different counties and time periods. 4. **Interactivity:** - We will incorporate user-friendly interactive features, such as dropdown menus, sliders, and checkboxes, for selecting and filtering data. - We will also implement tool tips and hover effects on the map for detailed information when the user interacts with data points. ### Risk assessment analysis 5. **Choropleth Maps**: - These maps are represent various levels of drought severity with different colors across the geographical layout of Arizona. They provide a quick and clear way to see which counties are most at risk and how the severity of drought conditions varies across the state. 6. **Stacked Area Charts**: - They show the cumulative impact of different drought severity levels over time. It can illustrate how much of the state is affected by each category of drought and how these proportions change from year to year. ## Implementation Plan: Our high level implementation plan includes: **1. Data Collection and Preparation:** - Obtain the drought dataset for Arizona, which includes county, time, and drought severity levels (D0, D1, D2, D3, D4, None) and another dataset for plotting the map of Arizona. - Clean and preprocess the data to ensure consistency, handle missing values, and format it for visualization. **2. Choose Tools and Libraries:** - Select R programming and relevant libraries for creating interactive visualizations, such as Shiny for building the web application, Leaflet for mapping, and ggplot2 for time series plots. **3. Design the User Interface (UI):** - Plan the layout and design of the dashboard. Consider a user-friendly and responsive design that allows users to easily navigate and interact with the data. **4. Geographic Visualization:** - Use Leaflet to create a map that represents the different counties in Arizona to let the users choose from them. **5. Time Series Analysis:** - Use ggplot2 to generate time series plots for drought severity over time. - Add interactive features to allow users to filter and explore data based on counties, severity levels, or date ranges. **6. Statistical Insights:** - Make the pie chart and stacked barplot using ggplot2, and compute summary statistics, trends, and forecasts based on the dataset. - Present these insights in a user-friendly and easily understandable format. **7. Integrate with Shiny:** - Create a Shiny web application that combines the geographic map, time series plots, pie chart, stacked bar chart and statistical insights. ## Weekly plan of action +----------+---------------------------------------------------------------------------------------------------------+------------------+ | Week | Weekly Tasks | Person in charge | +==========+=========================================================================================================+==================+ | Week 5 | Work on the Peer review feedback and submit final proposal | Everyone | +----------+---------------------------------------------------------------------------------------------------------+------------------+ | Week 6 | Understanding the basics , exploring shiny app | Everyone | +----------+---------------------------------------------------------------------------------------------------------+------------------+ | | Assign induvidial tasks | | +----------+---------------------------------------------------------------------------------------------------------+------------------+ | Week 7 | Data Exploration, Data Cleaning, Data preprocesing | Everyone | +----------+---------------------------------------------------------------------------------------------------------+------------------+ | | create plots:\ | TBD | | | 1. pie chart that shows the average percentage of each drought level from 2000 to present. | | | | | | | | 2\. The bar chart that shows the average percentage of each drought level by year from 2000 to present. | | | | | | | | 3\. The time-series that shows weekly drought levels in square miles for the state. | | | | | | | | 4\. Geographical map | | +----------+---------------------------------------------------------------------------------------------------------+------------------+ | Week 8 | Explore shiny and ways to integrate our visualizations and shiny | | +----------+---------------------------------------------------------------------------------------------------------+------------------+ | Week 9 | start creating an interactive dashboard | TBD | +----------+---------------------------------------------------------------------------------------------------------+------------------+ | | start working on the report | TBD | +----------+---------------------------------------------------------------------------------------------------------+------------------+ | Week 10 | final peer review and presentations | Everone | +----------+---------------------------------------------------------------------------------------------------------+------------------+ ## Repo Organization The following are the folders involved in the Project repository. - **'data/':** Used for storing our input data file. - **'images/':** Used for storing image files used in the project. - **'presentation_files/':** Folder for having presentation related files. - **'\_extra/':** Used to brainstorm our analysis which won't impact our project workflow. - **'\_freeze/':** This folder is used to store the generated files during the build process. These files represent the frozen state of the website at a specific point in time. - **'\_site/':** Folder used to store the generated static website files after the site generator processes the quarto document. - **'.github/':** Folder for storing github templates and workflow.