Water resource managment and Remote Sensing, a prospective issue that requires considerable attention
Background:
Water Remote sensing is a means of monitoring the water color and temperature, which provides information on the presence and loads of optically active substances in the water and that has hundreds of practical applications in the arena water resource management.
For an example, Surface runoff from agricultural land can carry nutrients (i.e., nitrogen and phosphorus from fertilization of crops) into that water bodies that might cause algal blooms and have the potential to degrade the water quality (i.e., fish kills). Satellite remote sensing derived indicators such as chlorophyll, can monitor that algal bloom thus monitoring water quality in a spatio-temporal fashion.
Incessant pressure on water resource caused by population growth and climate variability is obvious and there is a little quantitative information available to capture the spatial and temporal variability in water quality and quantity and therefore hard to derive efficient and effective water resource management policy.
Water Resource Management and Remote Sensing Applications:
Satellite Remote Sensing (RS) or Earth Observation (EO) can be crucial in understanding the spatio-temporal dynamics of water quantity and quality, which can be used to simulate water resources management scenarios under different water quantity/quality demand and derive effective policy recommendations, accordingly. Besides, EO also can competently assist different phases of water resource management projects’ life-cycle. In this context, Some of the widely used RS techniques are itemed bellow:
Surface Water Quantity: In context of water resource management, one of the key argument is the lack of the ground data, which plays an important role in evaluating the status of water resource and taking useful measures to respond the threat of water scarcity. In this regard, EO can offers standardized and long-term observations to address such challenges.
The EO capability of multi-temporal imaging and satellite imagery based indices (i.e., Normalized Difference Water Index (NDWI)), can efficiently identify, map and calculate the total surface area of the water bodies in different seasons (i.e., dry, wet) and by integrating satellite altimetry measurements we can quantify and monitor the water storage change over time.
The Aral Sea was once the world’s fourth-largest lake, but as can be seen in the four satellite images, has decreased in size over the last forty years; Images: USGS, EROS Data Center
Ground water Quantity: For planning and management of our water resource, we need to know, globally how much fresh water we have. Gravity Recovery and Climate Experiment (GRACE), an EO mission made possible to have an idea of how much ground water we have and how much we are extracting every day that was almost impossible to quantify few years back.
GRACE continuously measuring the changes in earth’s mass hence gravity that are mainly due to water moving on and under the surface. The negative change in gravity is the indication of losing mass, which means falling water table and by monitoring the changes over time we can estimate the rate of diminishing water table, which has strong water policy implication.
Water resource managment and Remote Sensing: GRACE satellite data showing California’s groundwater depletion in recent years. Image: NASA JPL
Surface Water Quality: Regarding water quality, there are several indicators, which are commonly used to describe and assess the water quality. Such as, water temperature, nutrients presence and abundance, total suspended solid, turbidity, presence of humic substances etc. EO can efficiently communicate with almost all kind of mentioned indicators very efficiently. For an instance, one of the most popular remote sensing based water quality parameters is chlorophyll-a, which can explain the nutrients presence and abundance in the water. Besides, Total Suspended Matter (TSM) concentrations as well as attenuation coefficient (Kd) can be used to measure the water turbidity and Colored Dissolved Organic Matter (CDOM) can play the proxy role to assess the presence of humic substances in the water.
Multi-temporal analysis of these remote sensing based parameters can provide more deeper understanding of our water quality dynamics or variability over time (i.e., seasonal or long-term). Besides, remote sensing based water quality indicators in combination with land use and other spatial information, we can successfully not only detect the eutrophication sources but also can understand the mechanisms, which are most likely caused by high rate of unmanaged urbanization and intensification of agricultural use of lands surrounding the water bodies which put pressures on the water bodies’ ecosystem.
Water resource managment and Remote Sensing: These images show true-color imagery and water quality (i.e., water clarity) data for Green Bay, Wisconsin during the summer of 2001. (Images courtesy Jonathan Chipman, Center for Limnology and Environmental Remote Sensing Center, University of Wisconsin)
Ground Water Quality: Besides the surface water quality assessment, we also can study ground water quality assessment using remote sensing technologies. For an example, we know groundwater discharge (GD) is a potential source of nutrients and algal bloom, which is an indicator of nutrient release in the water bodies. Now, If we know about the seasonal variability of ground water discharge and if the seasonal algal blooming variability correlates with the GD variability that can be an indicator of groundwater quality.
Water Project Management: EO-based information can be of important in view of implementing, coordinating, and monitoring large-scale water related projects and long term strategic planning (i.e. definition of priority interventions or understanding risks and vulnerabilities etc.). Different EO aided development projects has demonstrated the potentials of EO in water related project management.
For an example conducting projects on cross-boundary or trans-boundary water management issues are always difficult and complex in manner, regarding data collection and harmonization of available datasets where the particular advantage of EO is, EO service Information is globally consistent in nature that can facilitate the comparison capability of spatial facts and figures. Besides, EO based global water quality monitoring can identify where the water quality is deteriorating and requires local monitoring and water management program to tackle local challenges.
Last but not the least, EO also cal play a crucial role in project evaluation or impact assessment. Using EO information service we can very easily measure, either a water quality improvement project has met the goal or not by just analyzing satellite image in no time.
Conclusion:
The possibility of EO can potentially optimize the ground measurements and in such sense EO is simply awesome and can play a crucial role in water resource management but there are several changelings that we need to attain to successfully couple water specialist with EO. It’s obvious that EO information services are not widely used in the water resource management and one of the main reason of freely available EO data been underutilized due to the lack of staff capacity for processing and accessing EO data.
On the other hand the EO professionals’ density in land RS is remarkably higher than Water RS and to make water RS trendy, we should promote Water RS among the EO professionals. Besides, the number of studies/research on water RS or with water RS, are also not that significant, which should be enhanced by funding water RS related projects.
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This post is to address, Earth Observation Information Services as an assisting mechanism to operatively connect Earth Observation Industry, International Financial Institutions and Development Agencies.
International Financial Institutions (IFI) and Development Agencies (DA):
International financial institutions (IFI) (e.g., World Bank (WB)) are providing financial supports and professional advises for development activities and thus ensuring the processes to accelerate development in developing countries in a self-sustained manner. Besides, Development Agencies/Programs (e.g., UN family) are financed through voluntary contributions, also contributing to the comprehensive development of the developing countries.
IFIs and DAs organise and manage their development activities according to sectors (i.e., guided by economic activities) or Themes (i.e., guided by organizational goals/objectives) (e.g., agriculture, debt management) and we, EO professionals, believe Earth Observation (EO) data and information services can play a major role by supporting the management of development activities across sectors and by contextualizing local learning from global experience. IN this context, the particular advantages of EO are EO Information is globally consistent in nature and the availability of historical EO information that can be compared to the current status.
Earth Observation Industry (EOI):
Earth Observation Industry is a combination of commercial/non-commercial Earth Observation data providers (EODP) (e.g., European Space Agency (ESA)) that are dealing with reception, archiving and distribution of Earth Observation (EO) data and Value Adding Earth Observation Companies (VAEOC) that are turning EO data into information and providing EO Information Services.
EO is such an awesome technology that can deal with almost all kind of development activities very efficiently. For an instance, to plan and manage our water resource, we need to know, globally how much fresh water we have. Gravity Recovery and Climate Experiment (GRACE), an EO mission made possible to have an idea of how much ground water we have and how much we are extracting every day that was almost impossible to quantify few years back and that’s something remarkable.
Bridging EOI, IFIs and Das:
EOI is not a new entity anymore then again it’s a very new arena; to some it’s “a computer fantasy that can’t be a real tool for serious work”. The Non-EO people, who have considered EO as a possibility, appreciated it very much and from their exemplary experiences, some others are coming forward.
We, being an EO Professionals and as a stakeholder of EOI, are working across disciplines to ensure effective use of EO data by assisting non-EO people to use EO data efficiently. These have always been a vibrant experience and we love to do it again and again until we all in the same page.
Here, it’s worth to mention that EO data providers (i.e., ESA) have been working last couple of years to encourage EO data use among IFIs and supporting Value Adding EO Companies to assist IFIs with Earth Observation Information Services in their development activities. Besides, the commercial EO data providers like Planet Labs are also coming forward to assist humanitarian efforts.
Conclusion
Now, we have EO data providers, EO service providers and EO aware IFIs but still the assimilation process among EOI, IFIs and DAs is not evident and why is that? The noticeable reason can be: 1) the relatively small number of EO professional in IFIs and DAs, limiting the growth of EO usages. 2) EO data can be considered as Big Data as they comes in different formats and they are huge in size that requires special infrastructure and that is discouraging, in some extent. 3) Lack of necessary EO skilled professionals in the job market, which is the pre-requisite for successful EO integration in IFIs and DAs. Last but not the least 4) Lack of EO awareness, globally.
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