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Kim's Notes
Famiglietti, J. S., & Rodell, M. (2013). Water in the Balance. Science, 340(6138), 1300–1301. https://doi.org/10.1126/science.1236460
- How granular can GRACE data get currently?
AghaKouchak, A., Farahmand, A., Melton, F. S., Teixeira, J., Anderson, M. C., Wardlow, B. D., & Hain, C. R. (2015). Remote sensing of drought: Progress, challenges and opportunities. Reviews of Geophysics, 53(2), 452–480. https://doi.org/10.1002/2014RG000456
- To what degree can uncertainty from GRACE be quantified? Does it vary by region, time period, etc.?
- GRACE is still new--it's crucial that GRACE be combined with other data sources and models for the most useful information.
Rodell, M., Chen, J., Kato, H., Famiglietti, J. S., Nigro, J., & Wilson, C. R. (2007). Estimating groundwater storage changes in the Mississippi River basin (USA) using GRACE. Hydrogeology Journal, 15(1), 159–166. https://doi.org/10.1007/s10040-006-0103-7
- Do we need to use statistical processes to smooth the data?
- Some important points about error and uncertainty with GRACE
Kim "How severe is overallocation in the CRB currently?"
ChatGPT
The overallocation of the Colorado River is a significant and pressing issue that poses serious challenges to the long-term sustainability of water resources in the region. Here are some key factors that highlight the severity of the overallocation problem:
Legal Agreements and Water Rights: The Colorado River Compact of 1922, which allocated water rights among the seven basin states, was based on hydrological data from a period of relatively high river flows. As a result, the allocations exceeded the river's long-term average supply. Additionally, subsequent agreements and court decisions further allocated water, resulting in more water being allocated on paper than is reliably available.
Increasing Demand: Population growth, agricultural needs, and industrial development have significantly increased water demand in the Colorado River Basin. The basin's population has steadily grown, putting additional strain on limited water resources. Moreover, agricultural activities, particularly in arid regions, require substantial amounts of water, further exacerbating the demand-supply gap.
Drought Conditions: The Colorado River Basin has been experiencing prolonged and severe drought conditions over the past two decades. Reduced snowpack, decreased precipitation, and higher temperatures have contributed to reduced river flows. These drought conditions have led to decreased water availability, challenging the ability to meet the existing water allocations.
Declining Water Levels in Reservoirs: The overallocation issue is evident in the declining water levels of major reservoirs in the basin, such as Lake Mead and Lake Powell. These reservoirs, which are critical for water storage and supply, have experienced significant declines in their storage capacity due to prolonged drought and increased demand. Low water levels in these reservoirs not only indicate the strain on the system but also trigger water shortage declarations and mandatory water use restrictions.
Environmental Concerns: Overallocation of the Colorado River has detrimental effects on the basin's ecosystems and wildlife. Reduced flows and altered water levels can disrupt habitats, impact native species, and lead to the degradation of riparian areas. Maintaining adequate flows is crucial for preserving the ecological balance and biodiversity of the region.
To address the seriousness of the overallocation problem, stakeholders in the basin are actively working on various water management strategies. These include conservation measures, water recycling and reuse, enhanced water efficiency, and exploring additional water sources. Collaborative efforts among the basin states, Native American tribes, and other stakeholders aim to find sustainable solutions to ensure the equitable and responsible use of Colorado River water resources.
The slides from the reproducible research workshop have some helpful content. In particular, I thought the sections about data storage were useful. (link: https://docs.google.com/presentation/d/1L0yEDWwzMWiQl49VYKaFo5hTv6qhdXurstVIF5UDntw/edit#slide=id.g7e36063d48_0_58). We could actually potentially store a dataset (maybe a tabular dataset from the output of our pipeline) in addition to our pipeline, for just the CRB. This could be really useful.
Questions with GRACE data:
- What's the difference between Mascon solution data and spherical harmonic solution?
Both of these methods are used to estimate gravity field estimates. Satellites like GRACE measure the Earth's gravitational field, which is determined by density of Earth at a given point. The satellites can detect changes in the Earth's gravitational field, which can then be used to measure density/mass. Since we know a lot about Earth's other processes such as land mass and their time scales, the satellites can provide us information about gravity anomalies on the Earth which can then be used to say something about mass anomalies. See this link for a helpful explanation: https://podaac.jpl.nasa.gov/gravity#:~:text=Gravity%20is%20the%20field%20around,glacial%20melt%2C%20droughts%20or%20geodesy.
Mascon's and spherical harmonic solution:
Both of these are processes for producing estimates. "Mass Concentration blocks (mascons) are another form of gravity field basis function. The “mascon” make the implementing of geophysical constraints much easier and is a much more rigorous approach comparing with the standard spherical harmonic approach of empirical post-processing filtering27,28."
you use a spherical harmonic series to model the non-perfect spherical parts of the Earth, ie, a mountain range can't be expressed in a functional form.
When should we apply the scale factor? What does uncertainty mean?
From the 2006 paper (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2005GL025305): [4] Suppose the goal is to use GRACE mass variations to assess a regional water storage model. The GRACE results would be interpreted as estimates of total water storage variability. The errors in those estimates fall into two categories: (i) those due to errors in the monthly GRACE gravity field solutions; (ii) those due to changes in the true monthly mass averages caused by things other than continental water storage. Measurement and processing errors contribute to (i). Contributions to (ii) could include gravity signals caused, for example, by unmodeled mass variations in the Earth's interior.
This is an interesting and important point about benchmarking GRACE data to "groundtruth" from the same paper:
[8] It is difficult, at present, to use ground truth to validate GRACE mass estimates. It is not clear there is any place where monthly variations of vertically integrated mass, averaged over the area of a GRACE footprint (probably at least 106 km2 given the present GRACE accuracy levels), are monitored well enough. Fortunately, the physics that relates the GRACE observables (orbital motion) to the end products (mass anomalies) is well known, following from Newton's law of gravity and the second law of motion. This reduces the need for validation, and makes it feasible to construct error estimates using only the GRACE fields. Our method is an extension of that described by Wahr et al. [2004].
How should we think about aggregating over a region？ Do we still need to average over different processing centers for Mascon data?