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Groundwater and drought

Groundwater and drought

Post by Andy Baker, Professor researching groundwater, caves, past climate, organic carbon and more at the University of New South Wales, in Australia.

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Drought is in the news here in New South Wales, Australia. But how are rainfall, drought and groundwater related?

First, we need to understand what drought is. Is it a water shortage? Or a lack of rainfall? Or something else? In the USA, the National Climatic Data Center define drought as the ‘absence of water’. They identify four types of drought: 1) meteorological drought (a lack of rainfall), 2) hydrological drought (a loss of surface water or groundwater supply), 3) agricultural drought (a water shortage leading to crop failure), and 4) socioeconomic drought (where demand for water exceeds availability).

Here in Australia, the Bureau of Meteorology defines drought as ‘a prolonged, abnormally dry period when the amount of available water is insufficient to meet our normal use’.  They add that ‘drought is not simply low rainfall; if it was, much of inland Australia would be in almost perpetual drought’. Much of inland Australia depends on surface and groundwater for their economy. If those regions experienced a groundwater drought, it would therefore be bad news.

Let’s look at New South Wales again. It covers both coastal regions, such as Sydney (where I am writing this), as well as a vast interior (where most of my research is based). The Bureau of Meteorology produces meteorological drought maps based on rainfall amounts over recent months. The current map shows large areas of New South Wales are experiencing rainfall totals that are in the lowest 10 percentile (‘serious’), lowest 5 percentile (‘severe’) and the lowest on record.

How does this deficiency in rainfall affect groundwater? And is there a groundwater drought? Long-term measurement of groundwater levels in boreholes (also called wells, depending on your country) can tell you whether water levels are rising or falling. Wells integrate groundwater recharge that comes from both surface water (e.g. rivers that lose water through their base) and from rainfall (also called diffuse recharge).

Real-time data of water levels from telemetered boreholes can provide timely information on groundwater drought (for example, here for NSW). Satellite products such as GRACE, which can infer groundwater levels from small changes in gravity over time, can provide large scale spatial coverage. Modelling products can calculate water balance from meteorological, soil and land use data.

The current Bureau of Meteorology map shows that deep soil moisture is very much below average across New South Wales. If we assume that deep soil moisture levels are only determined by rainfall recharge, then from this we would expect no rainfall recharge of groundwater to be occurring over large parts of New South Wales. From one location, Wellington, close to the middle of the drought region, we have the measured evidence from inside a cave that shows that rainfall recharge hasn’t occurred for 18 months (and counting).

Since 2011, forty loggers have been measuring the water percolating through the unsaturated zone of the limestone at a depth of 25 m at Wellington Caves. This winter, I did the latest download of the data. Or rather, the lack of data, as only four drip water sources were still active. Conditions in the cave are the driest since we started collecting data in 2011.

Drip rates have been on the decline since the winter of 2016. But note the decline temporarily slowed in 2017, starting in early April. That is the response to the last time there was rainfall recharge there – owing to almost 70 mm of rain falling over three days in late March 2017. Eighteen months ago.

In the inland of New South Wales, it is clear that in dryland farming regions, the lack of rainfall has now led to an agricultural drought. In contrast, latest available data from our groundwater monitoring networks shows that there is currently no decline in groundwater levels in the major irrigation districts, which is where river recharge occurs. But for our dryland farmers, and ecosystems that rely on rainfall recharge, the karst drip data show that the groundwater drought has hit. Australia is often called a country of drought and flooding rains. Flooding rains are what we need next so that we also have some river recharge to replenish our groundwater resource.

 

Wellington, NSW. July 2018. This is the UNSW Research Station, normally stocked and cropped, but not this year.

How deep does groundwater go? Mining (dark) data from the depths

How deep does groundwater go? Mining (dark) data from the depths

Post by Kevin Befus, Assistant Professor at the College of Engineering and Applied Science at the University of Wyoming, in the United States.

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3D geologic data can be hard to come by, and can be even more difficult to combine into a continuous dataset. The cross-sections shown here are directly from 3D groundwater models that I compiled [Befus et al., 2017], primarily from USGS groundwater models, for the U.S. East Coast. I kept each of the regional domains (different color swaths on the map) separate, since I ran into the issue of “border discontinuities” between different models where naming conventions and hydrostratigraphic structure didn’t match up. Kh is the horizontal hydraulic conductivity.

We’ve all been asked (or do the asking), “where does your water come from?” This is a fundamental question for establishing a series of additional questions that can ultimately help define strategies for valuing and protecting a particular water resource.

For groundwater, we could phrase this question differently, and I often do when talking to well owners: How deep is your well? If I get an answer to this, then I can dive into additional questions that can help define more about the local groundwater resource: How deep is the well screen? How long is the screen? Do you know what the water level in the well is? Has it changed over some given time? Seasonally?

These are all useful questions, and they serve to begin establishing the hydraulic conditions of a particular aquifer. I ask these whenever I can.

To do this at a larger scale, we can turn to various governmental agencies that regulate groundwater resources and/or water well drilling and often collect and store groundwater data (e.g., www.waterqualitydata.us/, http://nlog.nl/en/data, http://gin.gw-info.net/service/api_ngwds:gin2/en/gin.html, or http://www.bgs.ac.uk/research/groundwater/datainfo/NWRA.html). There is a wealth of information out there internationally on wells when they were drilled and where the driller first hit water. These driller logs can provide a snapshot in time of the water table elevation and can be extremely useful for tracking hydrologic variability [Perrone and Jasechko, 2017], extracting hydraulic parameters [Bayless et al., 2017],  and for testing model results [Fan et al., 2013]. Unfortunately for us earthy nerds, some governments have restricted access to well installation data for either certain types of wells (i.e., municipal) or for all wells, usually for privacy or safety concerns.

Back to the original question. How deep is groundwater? I keep this question broad. We can usually answer this question for particular areas where we have access to the right data, but for large parts of the globe, and potentially underneath you right now, we cannot answer this question. The “right data” for a hydrogeologist is some form of information on geologic/stratigraphic layer (or lack of layering) that can be tied to the rock properties. For a surficial, unconfined aquifer, this can be relatively easy, but when we start stacking several geologic units on top of each other or start actually using the groundwater, this question of how deep groundwater is becomes tricky. We could qualify this question by asking how deep “usable” groundwater is, which, of course, depends on our definition of usable water for a specific purpose. Or, we can point (or integrate) through the Earth’s crust, core, and right back to its crust and calculate the huge value of how much water is “in the ground” (and minerals)[Bodnar et al., 2013]. And I haven’t even brought up porosity yet! Or specific storage!

A example of a great public 3D interactive web viewer (https://wateratlas.net/) that integrates groundwater data, geological information, and well construction details produced by the Centre for Coal Seam Gas at the University of Queensland (https://ccsg.centre.uq.edu.au/), which is supported by the University of Queensland and industry partners. For more information on this water atlas, please contact Dr. Sue Vink (s.vink@smi.uq.edu.au) or Alexandra Wolhuter (a.wolhuter@uq.edu.au).

Don’t worry. I won’t go there. I want to harass/encourage the hydro[geo]logic community to get serious about sharing their hydrogeologic data. This does mean metadata (do I hear a collective groan?), but metadata and data management plans are increasingly required to secure funding. CUAHSI’s Hydroshare site (www.hydroshare.org) provides a platform uploading hydro models, and the U.S. Geological Survey has developed a slick web system for exploring hydrogeologic models. But, I’d like to take this further, or at least get a service like that going for anyone who wants to share their models. There is a wealth of crustal structure data out there, and groundwater models are unique in often containing some representation of three-dimensional geology/hydrostratigraphy along with Earth properties. There are some great deterministic, published datasets and models of global hydrogeology [De Graaf et al., 2015; Huscroft et al., 2018], but we can do better. Wouldn’t it be great to have a centralized database to extract an ensemble of hydrogeologic structure used in previous regional or local studies? How about be able to draw a model boundary on a web interface and extract 3D structure for your next model? And compare cross-sections between models in the same area? Want to start fitting your puzzle pieces into the international hydrogeologic puzzle? The question now becomes, how do we do it? A “DigitalCrust” has been proposed [Fan et al., 2015], but is not yet in reach.

Join the movement of a “Digital Earth” [Gore, 1998]!

Here are some examples, initiatives, and free 3D [hydro]geology resources to get you started:

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Kevin Befus leads the groundwater hydrology group in the Civil and Architectural Engineering Department at the University of Wyoming. With his research group, he studies how groundwater systems respond to hydrologic conditions over glacial timescales and in mountainous and coastal environments.  You can follow along with Kevin’s research through any of the links below:

Personal WebpageTwitter Research Group Page | UW Faculty Page

 

 

 

 

 

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References

Bayless, E. R., L. D. Arihood, H. W. Reeves, B. J. S. Sperl, S. L. Qi, V. E. Stipe, and A. R. Bunch (2017), Maps and Grids of Hydrogeologic Information Created from Standardized Water-Well Driller’s Records of the Glaciated United States, U.S. Geol. Surv. Sci. Investig. Report2, 20155105, 34, doi:10.3133/sir20155105.

Befus, K. M., K. D. Kroeger, C. G. Smith, and P. W. Swarzenski (2017), The Magnitude and Origin of Groundwater Discharge to Eastern U.S. and Gulf of Mexico Coastal Waters, Geophys. Res. Lett., 44(20), 10,396-10,406, doi:10.1002/2017GL075238.

Bodnar, R. J., T. Azbej, S. P. Becker, C. Cannatelli, A. Fall, and M. J. Severs (2013), Whole Earth geohydrologic cycle, from the clouds to the core: The distribution of water in the dynamic Earth system, Geol. Soc. Am. Spec. Pap., 500, 431–461, doi:10.1130/2013.2500(13).

Fan, Y., H. Li, and G. Miguez-Macho (2013), Global patterns of groundwater table depth, Science, 339(6122), 940–943, doi:10.1126/science.1229881.

Fan, Y. et al. (2015), DigitalCrust – a 4D data system of material properties for transforming research on crustal fluid flow, Geofluids, 15(1–2), 372–379, doi:10.1111/gfl.12114.

Gore, A. (1998), The Digital Earth: Understanding our planet in the 21st Century, Aust. Surv., 43(2), 89–91, doi:10.1080/00050326.1998.10441850.

De Graaf, I. E. M., E. H. Sutanudjaja, L. P. H. Van Beek, and M. F. P. Bierkens (2015), A high-resolution global-scale groundwater model, Hydrol. Earth Syst. Sci., 19(2), 823–837, doi:10.5194/hess-19-823-2015.

Huscroft, J., T. Gleeson, J. Hartmann, and J. Börker (2018), Compiling and Mapping Global Permeability of the Unconsolidated and Consolidated Earth: GLobal HYdrogeology MaPS 2.0 (GLHYMPS 2.0), Geophys. Res. Lett., 45(4), 1897–1904, doi:10.1002/2017GL075860.

Perrone, D., and S. Jasechko (2017), Dry groundwater wells in the western United States, Environ. Res. Lett., 12(10), 104002, doi:10.1088/1748-9326/aa8ac0.

 

Data drought or data flood?

Data drought or data flood?

Post by Anne Van Loon, Lecturer in Physical Geography (Water sciences) at the University of Birmingham, in the United Kingdom.

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The basis for (almost) all scientific work, at least in the earth and environmental sciences, is DATA. We all need data to search for the answers to our questions. There are a number of options to get hold of data; we can measure stuff ourselves in the field or in the lab, generate model data, process data measured by satellites, or use data that other people collected. The last option has the advantage that you can cover much larger temporal and spatial scales than if you do all the measurements yourself, but it is not necessarily much easier or quicker. In this blog I do a quick and dirty tour of large-scale data collection initiatives in hydrology and introduce a new initiative focusing on groundwater drought.

“Hydrometeorological data…” (source: https://cloudtweaks.com/)

The classical way for hydrologists to use other people’s data (also called “secondary data”) is to use national-scale government-funded hydrometeorological databases such as the National River Flow Archive (NRFA, https://nrfa.ceh.ac.uk/) and National Groundwater Level Archive (NGLA, http://www.bgs.ac.uk/research/groundwater/datainfo/levels/ngla.html) in the UK and the US Geological Survey Water Data in the USA (https://water.usgs.gov/data/). This seems a good and reliable source for data, but there are worries, for example that the number of gauges worldwide is decreasing due to various reasons (Mishra & Coulibaly, 2009; https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2007RG000243; Hannah et al., 2011; https://onlinelibrary.wiley.com/doi/full/10.1002/hyp.7794) and that paper or microfilm archives are at risk (https://public.wmo.int/en/our-mandate/what-we-do/observations/data-rescue-and-archives). These national data are collated in global databases like the Global Runoff Data Centre (GRCD, http://www.bafg.de/GRDC/EN/Home/homepage_node.html) and the Global Groundwater Network (GGN, https://ggmn.un-igrac.org/), hosted by the International Groundwater Resources Assessment Centre (IGRAC). The problem there is that it is very dependent on the national hydrometeorological institutes to provide data, the records are not always up to date and quality checked, and important meta-data are not always available.

That is the reason that many researchers spend a lot of time combining and expanding these datasets. A few recent examples (NB: not at all an exhaustive list):

These are very helpful, but also quite time consuming for a single person (usually an early-career scientist) or a small group of people to compile and the dataset easily becomes outdated.

On the other side of the spectrum is crowd-sourced or citizen science data. This is already quite common in meteorology, both for weather observations (Weather Observations Website, WOW, http://wow.metoffice.gov.uk/), historic weather data (for example Weather Rescue, https://www.zooniverse.org/projects/edh/weather-rescue/) and climate model data (weather@home, https://www.climateprediction.net/, by Massey et al., 2014 https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/qj.2455 ), but citizen science is starting to get used in hydrology as well. Some examples are (again not exhaustive):

Example of crowd-sourcing hydrological data via an App (source: http://www.crowdhydrology.com/)

Most of these are using citizens as passive data collectors with the scientists doing the analysis and interpretation. The nice thing is that it creates lots of data, but the downside is a lot of local knowledge is underused. There are, however, also initiatives that try to make use of this local knowledge, either from citizens themselves, from the experts in government agencies, or from local scientists who know much more about the local hydrological situation. Some of these are funded projects, such as:

Some of these are not funded, like the UNESCO NE-FRIEND Low flow and Drought group that produced an analysis of the 2015 streamflow drought in Europe after a community effort to collect streamflow data and drought characteristics from partners in countries around Europe (Laaha et al., 2017, https://www.hydrol-earth-syst-sci.net/21/3001/2017/hess-21-3001-2017.html). Or are only partly funded, for example by a COST action that only provides travel funding, as in the case of the FloodFreq initiative in which researchers collected a dataset of long streamflow records for Europe to study floods (Mediero et al. 2015, https://www.sciencedirect.com/science/article/pii/S0022169415004291) or the European Flood Database that could have been developed with support of an ERC Advanced Grant (Hall et al., 2015, https://www.proc-iahs.net/370/89/2015/piahs-370-89-2015.html).

The databases developed in funded projects are great because there is (researcher) time to develop something new. But it is also hard to maintain the database when the project funding stops and a permanent host then needs to be found. Unfunded projects can benefit from the enthusiasm and commitment of their collaborators, but have to rely on people spending time to provide data and be involved in the analysis and interpretation. These work best if they are rooted in active scientific communities or networks. I already mentioned the NE-FRIEND Low flow and Drought group (http://ne-friend.bafg.de/servlet/is/7402/), which developed into a nice group of scientific FRIENDs, but also organisations like the International Association of Hydrological Sciences (IAHS, https://iahs.info/) and the International Association of Hydrogeologists (IAH, https://iah.org/) play an important role (see Bonnell et al. 2006 – HELPing FRIENDs in PUBs; https://onlinelibrary.wiley.com/doi/full/10.1002/hyp.6196 ). IAHS for example drives the Panta Rhei decade on Change in Hydrology and Society (https://iahs.info/Commissions–W-Groups/Working-Groups/Panta-Rhei.do), which has a number of very active working groups that are driving data sharing initiatives. Another very successful example is HEPEX (https://hepex.irstea.fr/), which is a true bottom-up network with “friendly people who are full of energy” (https://hepex.irstea.fr/hepex-highlights-egu-2018/). These international networks can provide the framework for data sharing initiatives.

The value of international scientific networks for data sharing (source: https://hepex.irstea.fr/)

It also helps if there is one (funded) person driving the data collection and if there is a clear aim or research question that everyone involved is interested in. Also, a clear procedure and format for the data helps. With that in mind, portals have been developed specifically for data sharing in hydrology, for example:

– SWITCH-ON that focusses on open data and virtual laboratories where people can do collective experiments (http://www.water-switch-on.eu/project_pages/index.html).

– Hydroshare, which is a collaborative website where people can upload hydrological data and models (https://www.hydroshare.org/)

The most inclusive are the initiatives (either funded or unfunded) that manage to incorporate local knowledge, so those that do not only collect data, but also work with the data providers for the interpretation of the data. This synthesis aspect is the main strength of these initiatives and a lot can be learned by bringing data and knowledges together, even if no new data is created.

In a NEW initiative we are hoping to combine some of the advantages of the above-mentioned data collection efforts. The Groundwater Drought Initiative (GDI, http://www.bgs.ac.uk/research/groundwater/waterResources/groundwaterDroughtInitiative/home.html) is a three-year initiative starting in April 2018 that aims to develop and support a network of European researchers and stakeholders with an interest in regional- to continental-scale groundwater droughts. Through the GDI network we will collect groundwater level data and groundwater drought impact information for Europe. This is needed because most of the data collection initiatives mentioned above are focussed on floods, not on drought, and most collate data on streamflow, not on groundwater. Since around 65% of the Europe’s drinking water supply is obtained from groundwater and drought is (and will increasingly be) a threat to water security in Europe, it is essential to get a good understanding of groundwater drought and its impacts. Since groundwater drought is typically large-scale and transboundary, data on a pan-European scale is needed to increase this understanding.

The GDI initiative is embedded in the NE-FRIEND Low flow and Drought group and has obtained a bit of funding from the UK Research Council for workshops and some researcher time, but we hope to arouse the interest and the enthusiasm of even more scientists and government employees of various nationalities and regions to be involved in the initiative and to contribute with data, meta-data, local knowledge and interpretation of data. In return the GDI will provide tools to visualise and analyse groundwater droughts, a regional- to continental-scale context of the groundwater drought information, insights into the impacts of major groundwater droughts, access to a network of international groundwater drought researchers and managers, and the opportunity to participate in joint scientific publications. The long-term sustainability of the initiative will hopefully be developed through the network that we will establish and through the link with formal organisations like the European Drought Centre (EDC, http://europeandroughtcentre.com/) and IGRAC (https://www.un-igrac.org/ ), where the groundwater drought data will be stored after the end of the funded project.

If you are interested, please get in touch:

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Anne Van Loon is a catchment hydrologist and hydrogeologist working on drought. She studies the relationship between climate, landscape/ geology, and hydrological extremes and its variation around the world. She is especially interested in the influence of storage in groundwater, human activities, and cold conditions (snow and glaciers) on the development of drought.

Bio taken from Anne’s University of Birmingham page.

Hydraulic fracturing close to groundwater wells

Hydraulic fracturing close to groundwater wells

Post by Scott Jasechko, Assistant Professor of Water Resources with the Bren School of Environmental Science & Management, at the University of California, Santa Barbara, and by Debra Perrone, non-resident Fellow at Water in the West and an Assistant Professor, also at the University of California, Santa Barbara, in the United States.

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In December, 2016, the Environmental Protection Agency finalized a report [Ref. 1] on hydraulic fracturing and drinking water resources that, among other conclusions, states:

(a) Quote from [Ref. 1]: “scientific evidence that hydraulic fracturing activities can impact drinking water resources under some circumstances”

(b) Quote from [Ref. 1]: “When hydraulically fractured oil and gas production wells are located near or within drinking water resources, there is a greater potential for activities in the hydraulic fracturing water cycle to impact those resources.”

Tens-of-millions of Americans rely on groundwater stored in aquifers for drinking water. Because it is possible that hydraulic fracturing activities can impact water resources (i.e., quote (a) above), and because groundwaters located close to hydraulic fracturing activities are more likely to be impacted than those farther away should a contamination event occur (i.e., quote (b) above), it is important to assess how many domestic groundwater wells are located close to hydraulically fractured wells.

In a recent study [Ref. 2], we assessed how close domestic groundwater wells are to hydraulically fractured wells, and to oil and gas wells (some hydraulically fractured, some not). Due to consistencies limitations in both oil and gas and groundwater well datasets, we limited our analysis to groundwater wells constructed between 2000-2014, hydraulically fractured wells likely stimulated during the year 2014, and oil and gas wells producing in 2014.

Our study has two main findings.

First, we found that most (>50 %) recorded domestic groundwater wells constructed between 2000 and 2014 exist within 2 km of at least one hydraulically fractured well in 11 US counties (Fig. 1). Further, about half of all recorded hydraulically fractured wells that were stimulated during 2014 are located within 2-3 km of at least one domestic groundwater well. We suggest these regions where groundwater wells are frequently located near hydraulically fractured wells might be suitable areas to focus limited resources for further water quality monitoring.

Figure 1. The percentage of domestic groundwater wells that were constructed between 2000 and 2014 that have a recorded location that lies within a 2 km radius of the recorded location of at least one hydraulically fractured well that was stimulated during the year 2014.

Second, we assessed the proximity of oil and gas wells being produced in 2014 – some hydraulically fractured but others not – and groundwater wells. We found that many domestic groundwater wells are located nearby (<1-2 km) at least one oil and gas well, and, that actively-producing oil and gas wells are frequently located nearby at least one domestic groundwater well (Figure 2). Many of the potential contamination mechanisms associated with the construction, stimulation and use of hydraulically fractured wells are also associated with conventional oil and gas wells, including potential for spills on the land surface and well integrity failures [Ref. 3]. Therefore, assessing potential water quality impacts resulting from activities associated with oil and gas production derived from both hydraulically fractured wells and from conventional oil and gas wells is important.

Figure 2. The upper panel shows the distance between recorded oil and gas wells producing in 2014, and recorded domestic groundwater wells constructed between 2000 and 2014. The lower panel shows the distance between recorded domestic groundwater wells constructed between 2000 and 2014 and the nearest recorded oil and gas wells producing in 2014 (see Ref. [2] and references therein for data sources).

We conclude that (i) publicly-available groundwater well construction data are critical for managing groundwater resources and completing water quality risk assessments (see Ref. 4 for data quality information), and emphasize that not all states currently provide access to digitized groundwater well construction records (e.g., Figure 2), (ii) hotspots exist where activities related to oil and gas production occur nearby domestic groundwater wells, and these regions may be targeted for further groundwater quality monitoring, and (iii) assessing how frequently activities in the hydraulic fracturing water cycle impact groundwater quality may be vital to securing high quality water pumped from many domestic water wells where oil and gas production is common.

Figure 3. Hydraulically fractured well situated close to an irrigation system in California’s San Joaquin Valley.

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References:

[Ref. 1] U.S EPA. Hydraulic Fracturing for Oil and Gas: Impacts from the Hydraulic Fracturing Water Cycle on Drinking Water Resources in the United States (Final Report). U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-16/236F, 2016. Accessed from https://www.epa.gov/hfstudy November 15, 2017.

[Ref. 2] Jasechko S., Perrone D. (2017). Hydraulic fracturing near domestic groundwater wells. Proceedings of the National Academy of Sciences.

[Ref. 3] Vengosh A., Jackson R. B., Warner N., Darrah T. H., Kondash A. (2014). A critical review of the risks to water resources from unconventional shale gas development and hydraulic fracturing in the United States. Environmental Science & Technology 48, 8334-8348.

[Ref. 4] Perrone D., Jasechko S. (2017). Dry groundwater wells in the western United States. Environmental Research Letters 12, 104002.

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Scott Jasechko’s research focuses on fresh water resources, and uses large datasets to understand how rain and snow transform into river water and groundwater resources.

Find out more about Scott’s research at : http://www.isohydro.ca.

 

 

 

Debra Perrone  is interested in the multifaceted interrelationship between water, energy, and food resources. Her research explores how the interactions among these resources affect decisions and tradeoffs involved in water resource management.

Find out more about Debra’s research at: http://debraperrone.weebly.com/.

Good groundwater management makes for good neighbors

Good groundwater management makes for good neighbors

Post by Samuel Zipper, postdoctoral fellow at both McGill University and the University of Victoria, in Canada. You can follow Sam on Twitter at @ZipperSam.

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Dedicated Water Underground readers know that this blog is not just about water science, but also some of the more cultural impacts of groundwater. Keeping in that tradition, today’s post begins with a joke*:

Knock, knock!

Who’s there?

Your neighbor

Your neighbor who?

Your neighbor’s groundwater, here to provide water for your plants!

Figure 1. Typical reaction to joke written by the author.

Ahem.

Perhaps this joke needs a little explanation. As we’ve covered before, groundwater is important not just as a supply of water for humans, rivers, and lakes, but also because it can increase the water available to plants, making ecosystems more drought resistant and productive. However, we also know that groundwater moves from place to place beneath the surface. This means that human actions which affect groundwater in one location, like increasing the amount of paved surface, might have an unexpected impact on ecosystems in nearby areas which depend on that groundwater.

Imagine, for example, two neighboring farmers. Farmer A decides retire and sells his land to a developer to put in a new, concrete-rich shopping center. Farmer B continues farming her land next door. How will the changes next door affect the groundwater beneath Farmer B’s land, and will this help or hurt crop production on her farm?

In a new study, my colleagues and I explored these questions using a series of computer simulations. We converted different percentages of a watershed from corn to concrete to see what would happen. Our results showed that the response of crops to urbanization depended on where the land use change occurred.

Figure 2. Conceptual diagram showing how urbanization might impact crop yield elsewhere in a watershed. From Zipper et al. (2017).

In upland areas where the water table was deep, replacing crops with concrete caused a reduction in groundwater recharge, lowering the water table everywhere in the watershed – not just beneath the places where urbanization occurred. This meant that places where the ecosystems used to be reliant on groundwater could no longer tap into this resources, making them more vulnerable to drought. However, places where the water table used to be too shallow saw boosts in productivity, as the lower water table was closer to the optimum water table depth.

In contrast, urbanization happening in lowland areas had a much more localized effect, with changes to the water table and yield occurring primarily only in the location where land use changed, because the changes in groundwater recharge were accounted for by increased inflows from the stream into the groundwater system.

So, what does this mean for the neighboring farmers we met earlier?

For Farmer A, it means the neighborly thing to do is work with the developers to minimize the effects of the land use change on groundwater recharge. This can include green infrastructure practices such as rain gardens or permeable pavement to try and mimic predevelopment groundwater recharge.

For Farmer B, the impacts depend on the groundwater depth beneath her farm. If the groundwater beneath her farm is shallow enough that her crops tap into that water supply, she should expect changes in the productivity of her crops, especially during dry periods, and plan accordingly.

*Joke written by scientist, rather than actual comedian.

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For More Information:

Zipper SC, ME Soylu, CJ Kucharik, SP Loheide II. Indirect groundwater-mediated effects of urbanization on agroecosystem productivity: Introducing MODFLOW-AgroIBIS (MAGI), a complete critical zone model. Ecological Modelling, 359: 201-219. DOI: 10.1016/j.ecolmodel.2017.06.002

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Sam Zipper is an ecohydrologist. His main research focuses broadly on interactions between vegetation and the water cycle, with a particular interest in unintended or indirect impacts of land use change on ecosystems resulting from altered surface and subsurface hydrological flowpaths. You can find out more about Sam by going to his webpage at: samzipper.weebly.com.

Crop kites

Crop kites

Post by WaterUnderground contributor Mikhail Smilovic. Mikhail is a PhD  candidate in the Department of Civil Engineering at McGill University, in Quebec.

Crops use water for photosynthesis, absorbing nutrients, and transpiration, or the plant-equivalent of sweating. A crop may experience water-stress if the soil surrounding the roots is not adequately wet, and this stress will affect the crop differently depending on the crop’s stage of growth. Irrigation is the watering of plants to ultimately avoid such water-stress.

Non-irrigated crops are more vulnerable to intervals of dry and hot weather, and the increasing unpredictability of a changing climate will further complicate other crop management tools, such as choosing different cultivars (the particular variety of crop, some which may deal with certain stresses in an improved way) or changing planting dates.

Irrigated crops do not experience water stress (they may in fact experience water stress under a non-perfect irrigation system, but forgive this for now), but the water is necessarily derived from somewhere else. This somewhere else may also experience water withdrawals from municipalities, industry, and other agriculture. The source of water may be underground, or water from a river, lake, or spring, but a connection between both underground and surface waters shares with us that water removed from a system somewhere will have a response somewhere. This somewhere may very well be an ecosystem. Irrigation may also be costly related to the abstraction, transportation, and on-farm distribution.

Between non-irrigated and irrigated is a curious place where we can increase the resiliency of our agricultural systems to periods of drought and heat with limited irrigation, while allowing crops to experience well-timed water stress. Agricultural productivity or yield is determined as the amount of crop produced per area of land, say 3 tons/hectare for wheat. When water is a limiting factor, we would be sensible to also consider water productivity, that is the ratio of crop yield and water use, or, the amount of crop produced per drop of water. The practices of limited irrigation, also known as supplemental or deficit irrigation, makes an effort to increase this water productivity.

This space in-between non-irrigated and irrigated, however, has been often poorly explored or simplified. Crop kites is a novel tool to determine and quantify the potential agricultural and water productivity associated with different irrigation practices. This is important for regions interested in shifting investments into or away from irrigation, as well as for researchers interested in evaluating limited irrigation practices as initiatives to establish food and water security, both currently and with changing climates.

A first thought might be, if a crop uses three quarters of the water than it would under ideal conditions, does the crop produce three quarters as much as the crop under ideal conditions? In fact, the answer depends very much on when this water is used.

Let us take the example of winter wheat in northern Africa. Winter wheat can be broadly characterized into five different growth stages. We can illustrate water use throughout the season with the following figure:

Water use is represented by the bottom blue colour, and the associated deficit is represented with the upper orange colour – the top line of the shape is the amount of water the crop would use under ideal conditions on the associated day. This example shows a 0, 10, 20, 30, and 40% deficit occurring in stages 1 to 5 respectively, representing a 78% water use across the entire growing season as compared to ideal conditions. Understanding both the amount of water used and when the water was used, we are able to determine the associated yield, for this example, we reach 68% of potential yield.

Now, what if we were to simulate the yield using all reasonable water uses and all reasonable distributions of the timing of this water use? The resulting shape is our crop kite, with each point associated with a water use distributed throughout the growing season in a particular way:

 

This shape illustrates the incredible range of yields associated with each water use; for example, 80% of potential water use relates to between ~20 and 90% of potential crop yield.

Water distributed through canals are often delivered according to a schedule, and not necessarily related to growth-stage sensitivities or actual weather. From the crop kite we can derive estimates on how the crop yield will be affected by adopting certain irrigation schedules. We elaborate on this with three examples: S1) water use is distributed to optimize yield, S2) the deficit is distributed evenly across all growth stages, S3) water is used preferentially for the earlier growth stages. The resulting crop-water production functions are illustrated in the following figure:

 

Although the first schedule optimizing for crop yield may be in line with the motivations of the irrigating farmer, it is often an unreasonable assumption for farmers delivered water according to predetermined schedules, but may be appropriate for farmers irrigating with a privately owned well. Evaluating the potential of supplemental irrigation necessitates estimating the ability of farmers to manage both the amount and timing of irrigation applications. Otherwise, non-reasonable assumptions may be used to evaluate and over promise estimates for agricultural production, with the fault not in the practice of limited irrigation, but in the criteria used to evaluate the system.

Crop kites demonstrate the wide range of water use-crop yield relationships, and can be used to evaluate the potential of limited irrigation to shift both food and water security.

 

Mikhail Smilovic is a PhD candidate at McGill University and the University of Victoria . Mikhail’s work investigates the interplay between foot security, water resources, and energy, and evaluating and integrating initiatives that increase agricultural production while reducing demands on water resources.

A new data portal for permeability!

A new data portal for permeability!

Permeability data is tucked many dusty corners of the web and in even dustier reports, books and thesis. The purpose of the Crustal Permeability Data Portal is to ‘unearth’ (pun intended!) permeability data by providing links to online, peer-reviewed permeability data that is open to anyone around the world.

This data portal colldata portalates links to other data sources rather than hosting data and is a community-based effort that grew out of a compilation of papers on Crustal Permeability (Geofluids special edition and forthcoming Wiley book).

A related community-based effort is the Digital Crust which a 4D data system of spatially-located data. The Crustal Permeability Data Portal is different from the Digital Crust since it will not host data and data does not have to be spatially located.

Why should I contribute data?

  • data availability is crucial to the core scientific principle of reproducibility
  • sharing is easy and feels good
  • some journals (e.g. Nature) and most scientific funding agencies (NSF, NSERC, NERC etc.) encourage or require data management and sharing

What are the data requirements?

  • Peer-reviewed, that is published in a peer-reviewed journal, book or report
  • Permeability or other related fluid flow and transport parameters such as porosity, storage etc.
  • Hosted on a publicly available on an online data repository such as figshare or institutional webpages such as the USGS

It’s simple: All you need to do is upload your data and fill out this form.

Communicating research results through comics: is the permeability of crystalline rock in the shallow crust related to depth, lithology, or tectonic setting?

Communicating research results through comics: is the permeability of crystalline rock in the shallow crust related to depth, lithology, or tectonic setting?

Mark Ranjram, a Masters student in my research group, wrote a paper on crystalline permeability that is coming out in a special edition of Geofluids on ‘Crustal Permeability’ early in 2015 (other cool papers in early view here). Here is Mark’s awesome response when I asked him if he wanted to write a plain language summary:

PlainLanguagePermeabilityComic_1Column