Water Data And Analysis


Water is important to both the natural and built environment. Analyzing Water usage and quality helps to deepen understanding of the systems being measured and guide management functions. Water quality can be defined as the chemical, physical and biological features of water and is usually related to its suitability for a particular use. Water quality analysis is mainly necessary for monitoring purposes for example; to check if the water meets the quality standards and is suitable for the specific use. The poor condition of water bodies is not only an indicator of environmental degradation, but also a threat to the ecosystem. In the industrial sector, improper water quality can cause significant risks and economic losses. Therefore, water quality is extremely important in both an ecological and economic point of view.

The world's water resources are in the air, seas, land, rivers, lakes and oceans because of the cycle of water. To understand how to make the most of the available water supply, you must first understand where and how water is currently used. Analyzing consumption data can provide valuable information about how most people use water, as well as help with evacuation permits, community development, or drought response. Moreover, latest data analysis tools can be used to monitor the information on floods and droughts, access real-time data, and identify potential hazards.

Hydro/ Flood modeling

Climate change is increasing the risks associated with flooding. The magnitude and frequency of floods are being affected by climate change. It clearly shows that changes in quantity and frequency will continue as concentrations of greenhouse gasses (GHGs) in the atmosphere continue to increase (IPCC, 2012). Floods are the most common natural disaster and the third most damaging natural disaster in the world after hurricanes and earthquakes (Wilby and Keenan, 2012). Flooding is a major concern in Myanmar and actually elsewhere in the world. Floods in Myanmar occur mainly during the monsoon season (June to October), causing people to lose their crops and housing. Hence, the research community has been putting a great deal of effort into finding models and methodologies for understanding immersion at various spatial scales.

Flood modeling is an important first step in understanding and managing floods at all spatial scales, from large river watersheds to highly developed cities, individual properties and infrastructure. Flood modeling typically involves developing useful algorithms to describe floods in terms of flood depth and extent, and flow velocity. Flood mitigation assessments, land use planning management, infrastructure design, and even flood insurance classification are directly affected by the accuracy of the flood modeling, and some progress has been observed to improve flood analysis and monitoring situations.

Introduction to Spatial Analysis

Spatial analysis is the process of extracting new information about a set of geographical features for routine examination, assessment, evaluation, analysis or modeling of data in geographic areas based on pre-computed standards and criteria. The history of spatial analysis is closely related to the development of cartography and geography in the 18th and 19th centuries. Spatial analysis is now used to process modeling, evaluate ability, estimate and predict, examine and interpret model results to aid interpretation and understanding. In the Environmental field, spatial analysis can help predict future climate change events such as flooding and drought.

Environmental Remote Sensing

The growing concern about environmental impacts on humans has led to the development of new monitoring and analytical tools to address and monitor the types, magnitudes, and rates of environmental change. The availability of remote sensing data from a variety of sensors on different platforms and the ability to obtain different spatiotemporal, radiative, and spectral resolutions make remote sensing the best data source for future research.

Remote sensing can be used in various fields and water remote sensing is important for agricultural economies like Myanmar's. Water remote sensing is a method of monitoring water color and temperature, providing information on the presence and percentage of optically active substances in water, and has hundreds of practical applications in the management of stadium water resources. One of the major challenges in water resource management is the lack of ground data which plays an important role in assessing the condition of water resources and taking useful actions to respond to the threat of water scarcity. Apart from the evaluation of surface water quality, it is also possible to study the water quality evaluation of groundwater using remote sensing technology.

Field Measurement

Water quality is very important to biodiversity and life on Earth and is one of the most important health indicators in ecosystems. Water pollution can cause major problems for humans in terms of drinking water, fishing and aquaculture. On-site measurements should represent as closely as possible the physical and chemical characteristics of the surrounding surface water or groundwater system such as dissolved oxygen, turbidity, pH, biomarkers, nitrate chemistry, and water temperature at the time of sampling.

Water level is one of the most commonly measured parameters and accurate level data is essential for many applications. Measuring water levels in streams and rivers helps engineers obtain data for designing structures such as bridges and dams. In addition, ecologists can use baseline data to study their impact on aquatic habitats and the environment. Water level measurement is also important in some industries, where stormwater runoff may contain hazardous chemicals. Monitoring the water level is especially important in lakes and reservoirs which serve as sources of drinking and irrigation water for many communities, and measuring the water level along the coast helps predict natural processes in the environment and determine human impacts on an ecosystem.


Written by Hnin Wut Yee San, an intern at The Water Agency.

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