remote sensing of water quality in the valle de bravo
TRANSCRIPT
TECHNICAL GUIDANCE NOTE: REMOTE SENSING October 2020 | Issue No. 3
Remote Sensing of Water Quality in the Valle de Bravo Reservoir, MexicoThe Valle de Bravo reservoir, or Lake Avandaro, is a
constructed lake located in the Mexican tropical
highlands approximately 150 kilometers
southwest of Mexico City. With a surface
area of 18.55 square kilometers and a
storage capacity of 391 cubic hectometers
(Merino-Ibarra et al. 2008), it is the largest
reservoir of the Cutzamala system, a
system of seven interconnected reservoirs
that provide part of the water supply for
the more than 20 million inhabitants of
the Mexico City metropolitan area and
other surrounding cities. In addition to its
use for water supply and hydroelectric power
generation, the Valle the Bravo reservoir has become
a popular weekend getaway for affluent families from
the capital, with recreation activities such as boating and sailing. ©Aleix Serrat Capdevila/World Bank
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WATER GLOBAL PRACTICE | REMOTE SENSING OF WATER QUALITY IN THE VALLE DE BRAVO RESERVOIR, MEXICO 2
Because of its importance as the single-largest surface source of water for the political and economic center of Mexico, the reservoir has been intensely studied and is the best instrumented lake in Mexico. Like many other tropical reservoirs with human activity rapidly increasing in its watershed, the Valle de Bravo reservoir has suffered from an ongoing process of eutrophication, mainly due to high inflows of nutrients from anthropogenic sources, resulting in frequent algal and cyanobacterial blooms. High concentrations of cyanobacteria negatively affect the potability of water, as well as the health of the aquatic fauna (zooplankton and fish). Nutrient loadings of nitrogen and phosphorus were found to have increased two- and threefold within a single decade (Ramírez-Zierold 2010). Such water-quality issues interfere with the designated uses of the reservoir and complicate the allocation of water resources. In addition, the eutrophication is imposing
significant pressures and increasing costs to the Los Berros potable water treatment plant, responsible for treating the water supply that is then transported to the Toluca and Mexico City metropolitan areas. However, the ability to design, implement, and evaluate adequate management actions depends on an accurate knowledge of the spatial patterns and temporal dynamics of water-quality properties in the reservoir.
In addition to the water supply relevance of Valle de Bravo, the water quality of this reservoir is also important to the regional communities for its many uses including agriculture, sanitation, and recreation. Although the reservoir is considered the best instrumented lake in Mexico (map 1 and figure 1), existing in situ measurements provide a limited picture for monitoring and understanding the complex water-quality dynamics in the lake.
MAP 1. Location of Water-Quality Monitoring Stations in the Valle de Bravo Reservoir
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Source: Data provided by the Comisión Nacional del Agua (CONAGUA).Note: Chlorophyll data was not available for stations 4 and 9. The size of the squares corresponds to the number of Chlorophyll measurements in situ data.
WATER GLOBAL PRACTICE | REMOTE SENSING OF WATER QUALITY IN THE VALLE DE BRAVO RESERVOIR, MEXICO 3
FIGURE 1. Time Series Data for Chlorophyll
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Remote Sensing of Water Quality
This case study assessed ongoing initiatives to address surface water pollution issues in Mexico, working in partnership with the Comisión Nacional del Agua (CONAGUA), the national agency responsible for the administration of water resources and its management. Particular focus was placed on a pilot case study application of remote sensing techniques to detection of water-quality issues in the Valle de Bravo reservoir. This assessment will contribute to a better understanding of options for water-quality remote sensing capabilities and needs and assist CONAGUA in identifying appropriate remote sensing tools and devising an application strategy to provide information needed to support decision making regarding the targeting and monitoring of nutrient pollution prevention and mitigation measures.
In situ data collection is able to provide point estimations of the quality of water conditions in time and space. However, obtaining spatial and temporal variations of quality indicators in large water bodies through in situ measurements is practically and costly challenging (Ritchie, Zimba, and Everitt 2003). Briefly listed are important limitations associated with conventional methods:
• In situ sampling of water-quality parameters are labor intensive, time consuming, and costly.
• Investigation of the spatial and temporal variations and water-quality trends using manual sampling in large water bodies is impractical.
• Monitoring entire water bodies with in situ methods may be impractical due to weather conditions, personnel availability and logistical issues such as access to equipment such as boats, vehicles, and sampling equipment.
• Accuracy and precision of collected in situ data can be affected by environmental variability and both field-sampling and laboratory errors.
To overcome these limitations and complement in situ water-quality monitoring efforts, remote sensing can be a useful tool. For decades, remote sensing has evolved toward providing strong capabilities to monitor and evaluate the quality of inland waters (table 1). Several scientific studies have led to obtaining robust correlations between water column reflectance and physical and biogeochemical constituents, such as chlorophyll concentration (phytoplankton), dissolved organic matter and suspended sediments in different water bodies (Chipman, Olmanson, and Gitelson 2009; El-Din et al. 2013; Giardino et al. 2014; Ritchie, Zimba, and Everitt 2003; Wang et al. 2006). However, due to atmospheric correction errors and local water complexity in near-coastal and inland water bodies, remote sensing must be combined with traditional sampling methods and field surveying to obtain adequate precision. In other words, to obtain better insight, integrated use of remote sensing, in situ measurements, and water-quality modeling may lead to an increased knowledge of the quality of water systems.
Kallio (2000) highlights four advantages of applying remote sensing in compliance with other water-quality monitoring programs:
• Gives a synoptic view of the entire water body for more effective monitoring of the spatial and temporal variation
• Makes possible a synchronized view of the water quality in a group of lakes over a vast region
• Provides a comprehensive historical record of water quality in an area and represents trends over time
• Prioritizes sampling locations and field surveying times
Satellite remote sensing–derived estimates are spatially continuous and repeated at regular intervals; hence, they can be used to increase data availability and complement in situ point measurements for an improved and integrative monitoring approach. Recent advances in remote sensing technology and analysis have allowed estimation of key water-quality constituents from space, including total
WATER GLOBAL PRACTICE | REMOTE SENSING OF WATER QUALITY IN THE VALLE DE BRAVO RESERVOIR, MEXICO 4
TABLE 1. Suite of Satellite Sensors Used in the Valle de Bravo Water-Quality Change Analysis
SATELLITE (INSTRUMENT)
AGENCYTEMPORAL COVERAGE
REVISIT FREQUENCY (1/DAY)
RESOLUTION (M) NOTES
Landsat–8 (OLI) USGS/NASA 2013–present ~1/16 30 pan ~15 m
Sentinel–2A (MSI) ESA 2015–present ~1/10 10
Sentinel–2B (MSI) ESA 2017–present ~1/10 10 2A+2B ~ 5 days
Envisat (MERIS) ESA 2002–2012 -3 300
Sentinel–3A (OLCI) ESA 2016–present ~2 300 3A+3B -1day
EOS Aqua/Terra (MODIS)
NASA Aqua: 2002–present Terra: 2000–present
1~2 250~500 3hr offset
SNPP-JPSS (VIIRS) NOAA/NASA 2015–present ~1 -375
Himawari–8 (AHI) JAXA 2015–present ~60 (10mins) ~1000 geostationary
Source: World Bank study.
nitrogen, total phosphorus, chlorophyll-a concentration, colored dissolved organic matter (dissolved organic carbon or total organic carbon), harmful algal blooms (for example, cyanobacterial toxins, microcystin concentrations or red-tides or karenia brevis blooms), total suspended sediment (or turbidity), and temperature. Combination of multiple sensors and different types of estimation methods can improve the retrieval accuracy of different water-quality parameters. Optically active constituents of water that interact with light and change the energy spectrum of reflected solar radiation due to absorption or scattering. This optical signal from water bodies can be measured using satellite remote sensing (Ritchie, Zimba, and Everitt 2003). Major water-quality parameters, such as those previously mentioned, constitute most of the important indicators of pollution in surface waters. In addition, other water-quality parameters, such as acidity, chemicals, and pathogens, which do not change the spectral properties of reflected light and have no directly detectable signals, may be inferable from those detectable water-quality parameters with which strong correlations can be found.
Valle de Bravo: Monitoring Algal Blooms
Continued eutrophication of the Valle de Bravo reservoir will increasingly impair the numerous ecosystem services it provides. In this work, we demonstrate a path for the development of water-quality monitoring using publicly available remote sensing data from satellites Sentinel-2A and Landsat 8. Estimates of chlorophyll and turbidity
were obtained from atmospherically corrected remote sensing surface reflectance and are regionally tuned using in situ data available from CONAGUA. Chlorophyll and turbidity were used as proxies for biological productivity (nutrient supply and photosynthetic activity) and concentration of suspended particulates, which are some of the key indicators of water quality. This enables the generation of calibrated maps and time series data to provide improved insight into the spatial and temporal water-quality dynamics.
Figure 2 shows the comparison between in situ measurements of chlorophyll and remote sensing measurements derived from reflectance data from Sentinel-2A and Landsat 8 satellites. Higher reflectance values measured by satellites are indicative of lower light absorption, lower photosynthetic activity, and thus lower chlorophyll values, and vice versa. Good agreement can be observed when comparing chlorophyll data at three target dates labeled “A”, “B” and “C” (for February 2016, July 2016, and February 2017). Also, a favorable comparison between in situ data and remote sensing-derived values is obtained for chlorophyll and turbidity measured at the in situ station locations.
The satellite spatial coverage of the Valle de Bravo reservoir is shown in figure 3. Figure 4 shows the correlation between in situ measurements and satellite-derived values that is used to calibrate the remote sensing algorithms that can then be used to produce estimates of chlorophyll (panel a) and turbidity (panel b) concentrations throughout the reservoir.
WATER GLOBAL PRACTICE | REMOTE SENSING OF WATER QUALITY IN THE VALLE DE BRAVO RESERVOIR, MEXICO 5
FIGURE 2. Remote Sensing and In Situ Measurements of Chlorophyll across the Valle de Bravo Reservoir
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Note: The figure shows chlorophyll estimates using Sentinel-2A and Landsat 8 data in pixels corresponding to the in situ stations. The upper right plot shows chlorophyll concentrations from in situ measurements, and the points A, B and C are reference dates in both plots, spanning a year, for comparison purposes. The three in situ measurements miss the complex seasonal dynamics, which are captured by numerous remote sensing estimates. A: target date of February 2016; B: target date of July 2016; C: target date of February 2017.
What Controls Water Quality in Valle de Bravo?
Values of concentration of chlorophyll and turbidity at high spatial resolution (10 to 30 meters) were derived from Sentinel-2A and Landsat 8–calibrated algorithms. These values were used to generate the spatial maps shown in map 2, which show plumes of chlorophyll (panel a) and turbidity (panel b) in the northern part of Valle de Bravo, more pronounced toward the northwest area of the reservoir. This pattern of pollution can result from hydrological discharges of pollutants (for example, nutrients and/or sediments), which are entrained into the interior of the reservoir through the lakes circulation process.
These discharges are likely associated with nonpoint sources of pollution that are typical of land use practices in the watershed that contribute to the reservoir (for example, agricultural irrigation and fertilizer applications).
In addition to the snapshots depicted in these maps, the remote sensing data can be used to produce a high-spatial-resolution time series of pollution in the lake, as depicted in figure 5. This allows exploration of temporal trends of water-quality pollution in spatial areas of the lake that may be of interest, particularly in managing pollution sources and their discharges to the reservoir. In figure 5, the lake area is divided into four quadrants labeled “1”, “2”, “3” and “4” in the inset. A median pixel value is calculated for each
WATER GLOBAL PRACTICE | REMOTE SENSING OF WATER QUALITY IN THE VALLE DE BRAVO RESERVOIR, MEXICO 6
FIGURE 3. Spatial Coverage of the Valle de Bravo Reservoir by the Sentinel-2A and Landsat 8 Satellite Tiles
Sentinel-2A/2B tileT14QLG
Landsat 8 tilePath = 27/Row = 47
Source: Google.
FIGURE 4. Correlations between In Situ and Remote Sensing Measurements of Chlorophyll and Turbidity
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WATER GLOBAL PRACTICE | REMOTE SENSING OF WATER QUALITY IN THE VALLE DE BRAVO RESERVOIR, MEXICO 7
MAP 2. High-Resolution Maps of Chlorophyll and Turbidity for the Valle de Bravo Reservoir
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quadrant and plotted as a function of time for all available satellite retrievals. The solid lines represent a 30-day moving average over the data for each of the quadrants separately.
Some key findings from the introduction of remote sensing water-quality data in the Valle de Bravo reservoir can be summarized as follows:
• In Valle de Bravo, the seasonal precipitation and the annual lake turnover appear to be key hydrologic drivers for the nutrient input and frequent algal blooms with typically a lower level of biological productivity in the fall and winter seasons.
• Time series analysis of the retrieved chlorophyll and turbidity in Valle de Bravo shows frequent recurrence of algal blooms and mesotrophic to eutrophic water quality either localized to near-shore areas or along central stretches of the reservoir.
• Time series analysis of the retrieved chlorophyll and turbidity in Valle de Bravo shows frequent recurrence of algal blooms, during which chlorophyll concentrations can reach 60 to 100 milligrams per cubic meter, with baseline concentrations of less than 10 milligrams per cubic meter
• The remote sensing data show a modulation of the algal bloom intensity that may be related to the significant freshwater input (or reduced photosynthetic active radiation [PAR]) during the rainiest month (July). If this is the case, the variation in biological productivity may increase further as a result of hydrometeorologic variability or regional climate change.
• The frequent algal blooms appear highly cyclical, often with a maximum in the spring and late summer. Biological productivity is generally lowest in winter (December through January) and midsummer.
• The algal blooms appear to be highly cyclical, coinciding with the increased PAR and nutrient-input as a result of precipitation, often with a maximum in the late spring and late summer—a reduction in biological productivity is also occasionally observed in June to early July, possibly due to a temporary drop in PAR during weeks with highest precipitation rates. Biological productivity is generally lowest during the turnover of the reservoir (December through January).
WATER GLOBAL PRACTICE | REMOTE SENSING OF WATER QUALITY IN THE VALLE DE BRAVO RESERVOIR, MEXICO 8
FIGURE 5. High-Resolution Time Series of Chlorophyll and Turbidity for Spatial Sections (Quadrants) in the Valle de Bravo Reservoir
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Operational Monitoring of Water Quality
Remote sensing applications are powerful, low-cost, and easily accessible techniques when combined with in situ and meteorological observations. This can result in comprehensive water-quality monitoring and management supported by operational systems, which provide automated data ingestion, atmospheric correction, and regional calibration.
Satellite data are made public and exchanged by cooperative agreements between the source government agencies in
Europe, the United States, Canada, Japan, Korea, and others. Agency data are free. Creating operational information flow is low cost—although some development is needed for calibration and validation of atmospheric correction, regional tuning, and operational processing toward system reliability.
Remote sensing enables quantitative insight into spatial and temporal dynamics of biogeochemical processes in lakes and estuaries and near coastal and ocean zones; it is a scalable technique across bodies of water, regions, and applications.
WATER GLOBAL PRACTICE | REMOTE SENSING OF WATER QUALITY IN THE VALLE DE BRAVO RESERVOIR, MEXICO 9
For Valle de Bravo, an online automated remote sensing data and visualization system has been developed to serve as a repository of imagery and processing of water-quality data for the reservoir, as shown in Figure 6. This system downloads and integrates the latest satellite imagery in real time and thus provides access to the latest data, updating the water-quality database to the latest overpass for the Landsat 8 and Sentinel-2 satellites. There are now two satellites in the Sentinel constellation
(2A and 2B), and in 2021 Sentinel-2C is expected to be operational.
The product maps of chlorophyll (Map 3, panel a) and turbidity (panel b) are displayed for each selected image by clicking on the “open” icon in the online visor. Users can also see the list of available images and download the *.nc (hierarchical data format, or HDF) files, which contain all the water-quality product numerical information.
FIGURE 6. Automated Remote Sensing Data and Visualization System Developed for Valle de Bravo for Landsat and Sentinel Imagery
Source: Current site maintenance and ongoing image visualization courtesy of Gybe (www.gybe.eco). Note: Figure displays Sentinel imagery.
MAP 3. Chlorophyll and Turbidity Product Maps Visualized in the Online Automated Water-Quality Monitoring System Developed for Valle de Bravo
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WATER GLOBAL PRACTICE | REMOTE SENSING OF WATER QUALITY IN THE VALLE DE BRAVO RESERVOIR, MEXICO 10
These systems are publicly accessible through the following links:
• Sentinel-2: http://oceancolor.coas.oregonstate.edu / vdb/sen/rgb.html
• Landsat 8: http://oceancolor.coas.oregonstate.edu /vdb/lan/rgb.html
Benefits
With the increasing presence of remote sensing for water-quality monitoring applications in terms of areal coverage, accuracy, and free or public data availability, there is an opportunity to operationalize the use of satellite data to complement existing ground-based measurements and information for potentially impaired surface water bodies.
In the case of large reservoirs such as Valle de Bravo, high spatial and temporal resolution of water-quality key parameters, such as chlorophyll and turbidity, as explored in this work, can be helpful in identifying the combination of conditions—that is, rainfall, freshwater inflows into the lake, and seasonality in lake turnover—that can lead to harmful algal blooms. This improved knowledge can help enhance mitigation strategies put in place by CONAGUA, such as releasing water from another reservoir (Villa Victoria) to reduce negative impacts to the Los Berros water treatment plant, which gets clogged when algal blooms are present in Valle de Bravo.
In this way, operationalizing water-quality monitoring through remote sensing can lead to substantial economic savings and contribute to the sustainability of water treatment infrastructure. Similar benefits from the operational use of remote sensing can be achieved as well in terms of near-term and future investments in water-quality improvements in the Cutzamala system (for example, design of new infrastructure or retrofits to existing systems).
Challenges
The remote sensing setup used in this case study consisted of primarily computational equipment and training of human resources. Moving forward, an operational water-quality monitoring system that incorporates satellite observations would require investments in computational or information technology (IT) and human resources.
On the computational or IT side, appropriate server and data communication infrastructure is needed to acquire,
store, process, and visualize water-quality data obtained from satellite measurements.
On the human resources side, this could be training CONAGUA staff on the processes of data acquisition from the satellite streams (for example, Sentinel and Landsat); calibration of algorithm parameters to translate satellite reflectance data into water-quality values; integration with ground-based data sources; and interpretation, analysis, and mapping techniques through geographic information system (GIS) platforms already in use by CONAGUA.
Overall, the satellite platform described in this case study provides an excellent basis for development and delivery of calibrated water-quality data products for CONAGUA. Together with ground-truth calibration with field observations, the enhanced water-quality data system showcased through this work provides significant new insight critical for monitoring this important reservoir. This system can be operationalized and extended to other important surface water bodies across Mexico that present similar water-quality challenges.
Recommendations for Adoption and Implementation
Successful management of lakes, reservoir, rivers, and streams depends on improved monitoring techniques for water quality. The high-resolution satellites (such as Sentinel 2 and Landsat 8) explored in this work have proved useful in extracting complex water-quality dynamics from remote sensing reflectance data. The Valle de Bravo case study highlights the ability to generate new insight about the water-quality dynamics from remote sensing and the benefits of incorporating it to the existing streams of in situ measurements in the reservoir. Research efforts continue to develop advanced algorithms and methods for improved data retrieval and new remote sensing instruments toward operational implementation by water agencies like CONAGUA.
Remote sensing and GIS techniques in conjunction with traditional in situ sampling are the most effective, cost-effective, and reliable tools for monitoring water-quality parameters in various surface water bodies (lakes, rivers and coasts). The techniques developed in this work regarding Valle de Bravo can be extended to other reservoirs managed by CONAGUA because the footprint of satellites such as Sentinel and Landsat is able to cover larger areas at increasing spatial and temporal resolution.
WATER GLOBAL PRACTICE | REMOTE SENSING OF WATER QUALITY IN THE VALLE DE BRAVO RESERVOIR, MEXICO 11
Monitoring and assessing water-quality issues through remotely sensed data can result in effective management of water resources, though few managerial decisions currently rely on this. Instead, most operational methods focus on in situ periodic (boat-based) or continuous (ship-based or buoy-based) measurements, which are often very scarce. The remote sensing technology has advanced a lot in past years, and all the satellite imagery used in this study is completely free and available to the public. With just a few in situ measurements, periodic remote sensing data can be processed and calibrated over large spatial areas. Therefore, it is important to understand that a modest investment in remote sensing will represent a large multiplier on the value of in situ measurements, usually much costlier and more limited in time and space.
References
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Ramírez-Zierold, J. 2010. “Dinamica Biogeoquímica de N y P de un Embalse Tropical Eutro-fizado (Valle de Bravo, Estado de Mexico).” Doctoral thesis, Universidad Nacional Autónoma de Mexico.
Ritchie, J. C., P. V. Zimba, and J. H. Everitt. 2003. “Remote Sensing Techniques to Assess Water Quality.” Photogrammetric Engineering and Remote Sensing 69: 695–704.
Wang, F., L. Han, H. T. Kung, and R. van Arsdale. 2006. “Applications of Landsat-5 TM Imagery in Assessing and Mapping Water Quality in Reelfoot Lake, Tennessee.” International Journal of Remote Sensing 27: 5269–83.
Acknowledgments
This knowledge note is part of a broader initiative to support the government of Mexico in developing a road map for improving the water quality of the Valle de Bravo reservoir as part of the World Bank’s Remote Sensing Initiative for Water Resources Management and in support of the Water Security and Resilience Project in Mexico.
This work was coordinated by the Sub-Direccion de Calidad del Agua de CONAGUA, led by Dr. Enrique Mejia Maravilla with Dr. Claudia Navas, as well as Ramiro Gutierrez, from OCAVM. The Gerencia de Cooperacion Internacional, led by Sean Casares, with Griselda Medina Laguna, smoothly coordinated this collaborative effort between CONAGUA and the World Bank.
The World Bank team in Mexico was led by Diego Rodriguez (senior water resources management specialist), and the remote sensing component was coordinated by Aleix Serrat-Capdevila (senior water resources management specialist) within the Global Remote Sensing Initiative for Water Resources Management, with technical contributions from Ivan Lalovic (remote sensing and water quality specialist), Fernando Miralles-Wilhelm (remote sensing and water quality specialist), and Stefanie Herrmann (remote sensing specialist). The project was implemented under the guidance of Gerardo Corrochano (country director), Maria Angelica Sotomayor (practice manager), and Rita Cestti (practice manager) of the World Bank.
This publication has been funded by the Global Water Security and Sanitation Partnership. The views expressed in this publication are the authors’ alone.
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