Merge pull request #453 from nbiswasuw/eis-casi-sid

[do not merge] Casi data story
NASA-IMPACT · Oct 14, 2024 · 59ed45e · 59ed45e
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diff --git a/stories/CASI_AFRC.csv b/stories/CASI_AFRC.csv
diff --git a/stories/CASI_AMES.csv b/stories/CASI_AMES.csv
diff --git a/stories/CASI_GISS.csv b/stories/CASI_GISS.csv
diff --git a/stories/CASI_GRC.csv b/stories/CASI_GRC.csv
diff --git a/stories/CASI_GSFC.csv b/stories/CASI_GSFC.csv
diff --git a/stories/CASI_JPL.csv b/stories/CASI_JPL.csv
diff --git a/stories/CASI_JSC.csv b/stories/CASI_JSC.csv
diff --git a/stories/CASI_KSC.csv b/stories/CASI_KSC.csv
diff --git a/stories/CASI_LARC.csv b/stories/CASI_LARC.csv
diff --git a/stories/CASI_MAF.csv b/stories/CASI_MAF.csv
diff --git a/stories/CASI_MSFC.csv b/stories/CASI_MSFC.csv
diff --git a/stories/CASI_NASACenters.png b/stories/CASI_NASACenters.png
diff --git a/stories/CASI_SSC.csv b/stories/CASI_SSC.csv
diff --git a/stories/CASI_WFF.csv b/stories/CASI_WFF.csv
diff --git a/stories/CASI_WSTF.csv b/stories/CASI_WSTF.csv
diff --git a/stories/CASI_header.avif b/stories/CASI_header.avif
diff --git a/stories/casi-story-1.mdx b/stories/casi-story-1.mdx
@@ -1,43 +1,130 @@
 ---
-id: 'eis-global-reservoir-storage'
-name: The Status of Global Reservoir Storage at a Watershed Scale
-description: 'NASA measurements and models shed light on present and future coastal risks'
+id: "eis-reservoir"
+name: The Value of Data in Monitoring The Health of Crops
+description: "The Status of Global Reservoir Storage at a Watershed Scale using satellite information"
 featured: true
 media:
-  src: ::file ./coastal-flooding-and-slr-cover.jpg
-  alt: Flooding in York, UK - February 2020.
+  src: ::file ./sat-data-agriculture--discovery-cover.jpg
+  alt: A reservoir across a river
   author:
-    name: Don Lodge
-    url: https://unsplash.com/photos/P8PuYidUYMw
-pubDate: 2024-07-15
+    name: Meta AI
+    url: 
+pubDate: 2024
 taxonomy:
   - name: Topics
     values:
-      - Water Resources
-      - Agriculture
-      - Drought
+      - Reservoir
 ---
+
+<Block>
+  <Prose>
+    ## The Value of Data
+
+    Providing insights into agricultural production, crop conditions, and food supply are among some of the most impactful information provided by Earth observing satellites. Information derived from the data retrieved can affect the price we pay at grocery stores, effect policy implementation from regional to global scales, and food security around the world. Not only can satellite data tell us about current and near-future food and commodity crop conditions, but researchers are also studying the long-term trends in climate change and its effects on our food supply in support of agricultural resilience.
+
+    As demonstrated by recent global crises including the COVID-19 pandemic and the ongoing Russian war in Ukraine, the globally interconnected nature of the agri-food system has been thrust into the spotlight. These extreme disruptions to the global food supply underscore the importance of global agriculture monitoring, both of major producing countries and those who are major importers and therefore most vulnerable to food insecurity. A key example of international coordination in support of better food information is the G20 GEOGLAM Crop Monitor spearheaded by NASA scientists in response to a request from the G20 Agricultural Market Information System (AMIS). The Crop Monitor provides a public good of open, timely, science-driven information on crop conditions in support of market transparency. The GEOGLAM Crop Monitor Initiative is supported by the [global agriculture community](https://cropmonitor.org/index.php/about/amis-partners-cm/) and national space agencies - including the NASA Harvest Consortium and US-based institutions, The Japan Aerospace Exploration Agency, (JAXA) deleteand JASMINdelete, the European Space Agency (ESA) and several European institutions, ministries of agriculture across the globe and many more. It reflects an international, multi-source, consensus assessment of crop growing conditions, status, and agro-climatic (the relationship between crops and the climate) factors likely to impact global production. The focus areas are the major producing and trading countries for the four primary crops monitored by AMIS (wheat, maize, rice, and soybean),  as well as the countries most at risk to food insecurity and their primary staple crops.
+    </Prose>
+
+</Block>
+
 <Block>
-  <Prose>  
-  **Authors**: Nishan Biswas, Sujay Kumar, Kim Locke
-  **Disclaimer**: This Discovery presents work in progress and not peer-reviewed results!
+  <Prose>
+  ## Why We Monitor Agricultural Production
+
+Any extreme event such as conflict, severe weather, or environmental abnormalities pose threats to agricultural production and may shock the system which is why it is so critical to have the accessible, transparent, timely, and global information afforded by satellite data. For example, based on community consensus and available satellite data we understand that at the end of June 2022, conditions are generally favorable for maize, rice and soybean production, while mixed for wheat. We also know that in the northern hemisphere, there are areas of concern for wheat in North America, Europe, and Central Asia. In the southern hemisphere, sowing in Argentina has begun under mixed conditions. While maize harvest continues in the southern hemisphere, crop growth continues in the northern hemisphere. Furthermore, rice conditions are generally favorable except southern China and Indonesia. Satellite data helps us monitor these global crop conditions on a regular basis, especially in times and places where ground access is dangerous or limited.
 
   </Prose>
+  <Figure>
+    <Image
+      src={new URL('./crops-around-world.jpg', import.meta.url).href}
+      alt='Map showing where crops are grown around the world, and the current crop conditions as of June 2022'
+    />
+    <Caption attrAuthor='GEOGLAM Crop Monitor' attrUrl='https://cropmonitor.org/'>
+      GEOGLAM Crop Monitor for AMIS and Early Warning synthesis map showing where crops are grown around the world, and the current crop conditions as of June 2022.
+    </Caption>
+  </Figure>
+</Block>
+
+<Block>
+  <Prose>
+    ## What We Monitor
+
+    Basin-wide reservoir storage status for the year of 2023. In the snapshot, water storage in the Western USA can be seen either much below the normal or below the normal. Whereas, in the Amazon, Congo, Nile are showing much above the normal storage of reservoirs.
+    </Prose>
+
 </Block>
 
 <Block>
   <Prose>
-    ## Introduction
     **Storage status of reservoirs in 2023**
-
+
+    Basin-wide reservoir storage status for the year of 2023. In the snapshot, water storage in the Western USA can be seen either much below the normal or below the normal. Whereas, in the Amazon, Congo, Nile are showing much above the normal storage of reservoirs.
+
   </Prose>
+  <Figure>
+    <Image
+      src={new URL('./chart-crop-health.jpg', import.meta.url).href}
+      alt='Chart for Normalized Difference Vegetation Index (NDVI): A measure of crop health'
+    />
+    <Caption>
+      The AGMET Indicators use satellite data to measure key indicators of crop health, including NDVI and NDVI anomalies. Source on [Cropmonitor](https://cropmonitor.org/tools/agmet/).
+    </Caption>
+  </Figure>
 </Block>
 
 <Block>
+  <Figure>
+    <Image
+      src={new URL('./chart-soil-moisture.jpg', import.meta.url).href}
+      alt='Chart for Surface soil moisture: A measure of water stored in the ground and available to crops.'
+    />
+    <Caption>
+      Soil moisture can be measured using satellite data and directly affects crop growth. Source on [Cropmonitor](https://cropmonitor.org/tools/agmet/).
+    </Caption>
+  </Figure>
   <Prose>
-  **Editor**: Nishan Biswas, Sujay Kumar, Kim Locke 
-  **Developers**:
-  **Science and Content Contributors**: 
-  **Acknowledgements**: 
+    **2. Surface soil moisture: A measure of water stored in the ground and available to crops.**
+
+    Like NDVI, surface soil moisture is a key component for crop production that can be measured using satellite data (such as NASA's Soil Moisture Active Passive (SMAP) instrument). The amount of moisture in the soil will depend on meteorological conditions that can be measured with the help of satellite data (precipitation, temperature, etc.) as well as sun exposure, wind, runoff/drainage, and soil type. If there is less water in the soil, it will be more difficult for crop roots to take up that water, resulting in a crop that is under greater stress. If the stress continues, the crop will wilt and eventually die. However, if the soil is above field capacity and the pores are oversaturated with water, then oxygen levels are restricted, and it can be detrimental for the crop. This is why soil moisture is a key indicator of what may ultimately be a successful or failed crop.
+
   </Prose>
-</Block>
+</Block>
+
+<Block>
+  <Prose>
+    ## Examples
+
+    The Southern Plains are a major wheat producing region in the U.S. and are monitored closely from planting to harvest given the importance of this major commodity crop. The AGMET Indicator graphic for the 2022 Southern Plains winter wheat season (below) shows below-average cumulative precipitation, NDVI, and soil moisture, consistent with drought conditions trending throughout the Southern Plains. U.S. winter wheat is typically harvested over the summer months but due to the drought conditions affecting the region, there is concern over the potential yields. With the help of satellite data, we understand several months ahead of the harvest that we might expect lower than average production as a result of the environmental indicators measured. With this knowledge comes the ability to respond and prepare appropriately while simultaneously providing market transparency.
+
+    <Image
+      src={new URL('./chart-southern-plains.png', import.meta.url).href}
+      alt='Chart matrix for Southern Plains of USA'
+    />
+
+    Not only does satellite data help us understand the current season's productivity, but they also provide a rich historical record of agricultural measurements that enable researchers to compare outcomes to previous seasons and evaluate broader trends such as the impacts of climate change.
+
+    <Image
+      src={new URL('./charts-sousse.png', import.meta.url).href}
+      alt='Chart matrix Sousse (Northern center, Tunisia)'
+    />
+
+    Significant parts of Northern Africa and the Middle East are experiencing drought conditions including countries such as Morocco, Tunisia (see below), Syria and Iraq that are significantly impacting crop production. Earth observations are key to identifying and quantifying these impacts early and in providing support for future agricultural planning and mitigation actions when needed.
+
+    Likewise in Southern Brazil crops did not receive the expected amount of precipitation, which negatively impacted yields of the spring planted crop. Looking at the information provided by satellite data, the drought conditions are striking and serve as a preemptive sign that governments and markets should prepare for less commodity crops coming out of this region of Brazil. This not only impacts Brazil and the global market, but also the countries that rely on the region for their food/feed imports. Earth observations can give an early indication of threats to food security should supplies end up being less than needed. Another benefit of remotely sensed satellite data is these types of evaluations can be done anywhere in the world throughout the season.
+
+    <Image
+      src={new URL('./chart-southern-plains.png', import.meta.url).href}
+      alt='Chart matrix for Southern Plains of USA'
+    />
+
+    As data access and technology have made significant advances in recent decades, it comes as no surprise that the amount of available data can often be overwhelming and difficult to decipher. Tools such as the [GEOGLAM-Harvest AGMET Indicators](https://cropmonitor.org/tools/agmet/) play a key role for quick and digestible information processing and supporting key agricultural decisions. To increase food market stability and reduce price volatility, it is critical that market analysts, farmers, and other agricultural stakeholders have a thorough understanding of the amount of food coming to market - whether that be in line with the average amount seen in previous years or more/less. Just as with any other consumer good, supply and demand are the key drivers of agri-food (relating to the commercial production of food by farming) markets and commodity prices. Satellite data can fill a critical gap in agricultural monitoring, enabling us to not only understand current crop conditions but prepare for potential outcomes in a given growing season. The benefits include wider-reaching impacts on market stability, earlier reaction time for humanitarian response, and bolstering food security.
+
+  </Prose>
+</Block>
+<Block>
+<Prose>
+*** References ***  
+Biswas, N.K., F. Hossain, M. Bonnema, H. Lee, F. Chishtie (2021). Towards a global Reservoir Assessment Tool for predicting hydrologic impacts and operating patterns of existing and planned reservoirs. Environmental Modelling & Software, 140, 105043. https://doi.org/10.1016/j.envsoft.2021.105043 
+Donchyts, G., Winsemius, H., Baart, F. et al. (2022). High-resolution surface water dynamics in Earth’s small and medium-sized reservoirs. Sci Rep 12, 13776. https://doi.org/10.1038/s41598-022-17074-6
+</Prose>
+</Block>
diff --git a/stories/casi-story-2.mdx b/stories/casi-story-2.mdx
@@ -1,15 +1,15 @@
 ---
-id: 'eis-casi-story-2'
-name: CASI Story 2
-description: 'NASA measurements and models shed light on present and future coastal risks'
+id: 'eis-casi-story'
+name: CASI Story
+description: 'NASA measurements and models shed light on present and future in soil moisture condition'
 featured: true
 media:
-  src: ::file ./coastal-flooding-and-slr-cover.jpg
-  alt: Flooding in York, UK - February 2020.
+  src: ::file ./CASI_header.avif
+  alt: Drought typical photo.
   author:
-    name: Don Lodge
-    url: https://unsplash.com/photos/P8PuYidUYMw
-pubDate: 2024-07-15
+    name: Bernd Dittrich
+    url: https://unsplash.com/photos/a-close-up-of-a-cracked-surface-of-dirt-HtTIiBMUY9M
+pubDate: 2024-10-15
 taxonomy:
   - name: Topics
     values:
@@ -18,14 +18,103 @@ taxonomy:
       - Drought
 ---
 <Block>
-  <Prose>  
-  **Authors**: Nishan Biswas, Sujay Kumar, Kim Locke
-  **Editor**: 
-  **Developers**:
-  **Science and Content Contributors**: 
-  **Acknowledgements**:
+  <Prose>
+  ## Introduction
+  <mark>🚧 This Discovery presents work in progress and not peer-reviewed results! 🚧</mark>
 
-  **Disclaimer**: This Discovery presents work in progress and not peer-reviewed results!
+  National Aeronautics and Space Administration (NASA) Centers are currently experiencing heavy downpours, heatwaves and coastal flooding, and these are expected to increase in the coming decades due to climate variability and change. The United States Global Change Research Program (USGCRP) 2009 Climate Impacts Report concluded that “human-induced climate change is happening now, the impacts are already apparent, and greater impacts are projected, particularly if [greenhouse] gas emissions continue unabated.”
 
+  The EIS team integrates the Noah-MP land surface model within [NASA’s LIS framework](https://lis.gsfc.nasa.gov/) and Earth observations by assimilating soil moisture from the Climate Change Initiative Program released by European Space Agency  ([ESA CCI](https://esa-soilmoisture-cci.org/)), leaf area index from Moderate Resolution Imaging Spectroradiometer ([MODIS](https://lpdaac.usgs.gov/products/mcd15a2hv006/)), and terrestrial water storage anomalies from Gravity Recovery and Climate Experiment and the follow-on satellites ([GRACE/GRACE-FO](https://earth.gsfc.nasa.gov/geo/data/grace-mascons)). Using this data assimilation approach, the team provides a daily global water cycle reanalysis product for 2003-2021 at a 10 km spatial resolution. This allows us to better quantify surface variables and groundwater, human management influence, and hydrological extremes. These resulting reanalysis datasets are publicly available and interactable via this NASA VEDA platform, including key water, energy, and carbon fluxes such as terrestrial water storage (TWS) and gross primary production (GPP). For more information, please visit the corresponding [VEDA dataset page](https://www.earthdata.nasa.gov/dashboard/data-catalog?taxonomy=%7B%22Topics%22%3A%22eis%22%7D).
+
+  Join the discussion and provide comments on this Discovery at https://github.com/orgs/Earth-Information-System/discussions.
+
+  Authors: Nishan Kumar Biswas, Sujay V. Kumar, Kim Locke
+
+  </Prose>
+</Block>
+
+<ScrollytellingBlock>
+  <Chapter
+    center={[-100,80]}
+    zoom={2}
+    datasetId='eis_casi_monthly'
+    layerId='median-soil-moisture'
+    datetime='2099-12-01'
+  >
+    ## Significant increase in soil moisture 
+    Big jump in soil moisture percentile in the arctic zone during the year of 2099 compared to the historical period.
+  </Chapter>
+  <Chapter
+    center={[-55,-10]}
+    zoom={3.8}
+    datasetId='eis_casi_monthly'
+    layerId='median-soil-moisture'
+    datetime='2099-12-01'
+  >
+    ## Drop in soil moisture percentile in Amazon 
+    A hotspot in Amazon where soil moisture will drop significantly during the projected period of 2099 
+  </Chapter>
+  <Chapter
+    center={[77.63,24.27]}
+    zoom={2}
+    datasetId='eis_casi_monthly'
+    layerId='median-soil-moisture'
+    datetime='2099-12-01'
+  >
+    ## Showing increasing pattern in China
+    Meanwhile, data from our model simulations shown here indicate increasing soil moisture gradually over the Central China region 
+  </Chapter>
+  <Chapter
+    center={[105.5001,40.7899]}
+    zoom={3.8}
+    datasetId='eis_casi_monthly'
+    layerId='median-soil-moisture'
+    datetime='2099-12-01'
+  >
+    ## Northern Africa is showing decline
+    Northern Africa shows a significant drop in soil moisture due the the drop in soil drying and more drought phenomena in the upcoming years.
+  </Chapter>
+</ScrollytellingBlock>
+
+<Block type="full">
+  <Figure>
+    <Map
+      datasetId='eis_casi_monthly'
+      layerId='minimum-soil-moisture'
+      dateTime='2015-01-01'
+      compareDateTime='2015-01-01'
+	  layerId='maximum-soil-moisture'
+
+    />
+    <Caption>
+      Figure 1. The spreading of soil moisture percentile between the minimum and maximum among the different ensembles.
+    </Caption>
+  </Figure>
+  <Prose>
+    ### Using satellite data to study soil moisture dynamics
+	The soil moisture percentile was caluclated from 25 different ensembles and an example of spreading of soil moisture is shown in the snapshot to understand the difference betweent he different percentiles.
+
   </Prose>
-</Block>
+</Block>
+
+<Block type="wide">
+  <Figure>
+    <Image
+      src={new URL('./CASI_NASA_Centers.png', import.meta.url).href}
+      alt='Soil Moisture dynamics around NASA Centers'
+    />
+    <Caption>
+      Comparison of soil moisture percentile calculated around the NASA centers with a five-year window. Here the number of months when soil moisture percentile crossed 50% are plotted along the y axis for the locations aroudn all the NASA centers.
+    </Caption> 
+  </Figure>
+</Block>
+
+
+
+<Block>
+  <Prose>
+  ## References
+
+</Prose>
+</Block>
+