Remote Sensing in Water Quality and Water Resources Management

Abstract
The quality of water ascertains the ‘integrity’ of water for specific purposes. Tests and quality of examination of water can provide sufficient information about the waterway health. If tests are conducted over a span of time period, the water quality changes can be realized. There are several testing parameters like pH value, temperature, salinity, turbidity, phosphates and nitrates, which can help assess the water quality. Also, aquatic macro-invertebrates can give a proper water quality indication. Surface water contaminated can pose a high risk to the entire human population and it remains a challenging task to investigate and resolve the problem for public health authority. Intensification of agricultural activities, change in climatic conditions, coastal area quick urban development, and resultant freshwater source declining have contributed considerably to the surface water contamination risk and the augmentation of waterborne disease incidences. The quality of surface water monitoring needs frequent problem detection to reduce any negative effect on public health. The epidemiology study applies geospatial and remote sensing technologies to distinguish the temporal and spatial environmental variability determinants to assess the epidemiology of certain diseases. By providing an integrated and systematic approach to risky water management for the public health and safety, a proper epidemiology method can be used and proved to be an efficient device to evaluate the quality of surface water and any related health risks. SWRMS- Spatial water resource monitoring system provides important and beneficial information to support water management. Requisite innovative features involve the explicit water redistribution description and use of river water and groundwater systems, to achieve more spatial details like key irrigated area features and wetlands, to improve hydrometer observation accuracy and assimilating the observations. A review of research and operational applications reveals that satellite view can enhance spatial detail and accuracy in estimating hydrological model. Every operating system uses land cover classification, dynamic forcing, and a parameterization priory of vegetation dynamics, which is partially or completely based on remote sensing, while satellite observations are utilized in varying stages for data assimilation and model evaluation. The satellite observation, utility by data assimilation varies as a dominant hydrological function. This review paper identifies the spatial and temporal precipitation products, including the application of a higher remote sensing product range, along with operational challenges while research satellite mission continuity with data services, finding computationally-efficient data assimilation techniques. The entire observations critically relies on the detailed information availability and understanding the remotely-sensed spatial and temporal scaling.