Application Remote Sensing in Hydrology - Lecture Note - Lecture Material
Application Remote Sensing in Hydrology

Hydrology

Hydrology is the study of water on the Earth's surface, whether flowing above ground, frozen in ice or snow, or retained by soil. Hydrology is inherently related to many other applications of remote sensing, particularly forestry, agriculture and land cover, since water is a vital component in each of these disciplines. Most hydrological processes are dynamic, not only between years, but also within and between seasons, and therefore require frequent observations. Remote sensing offers a synoptic view of the spatial distribution and dynamics of hydrological phenomena, often unattainable by traditional ground surveys. Radar has brought a new dimension to hydrological studies with its active sensing capabilities, allowing the time window of image acquisition to include inclement weather conditions or seasonal or diurnal darkness.


Examples of hydrological applications include:
  • wetlands mapping and monitoring,
  • soil moisture estimation,
  • snow pack monitoring / delineation of extent,
  • measuring snow thickness,
  • determining snow-water equivalent,
  • river and lake ice monitoring,
  • flood mapping and monitoring,
  • glacier dynamics monitoring (surges, ablation)
  • river /delta change detection
  • drainage basin mapping and watershed modelling
  • irrigation canal leakage detection
  • irrigation scheduling
Did you know?

Catastrophic flooding can happen almost anywhere. In Iceland, huge floods that carry boulders the size of houses occur relatively frequently. These floods are called jökulhlaups, roughly meaning "glacial flood". Iceland is situated upon the mid-Atlantic rift, an area of frequent volcanic activity. The island itself is a product of this activity, and continues to grow in size with each volcanic event. Covering much of the island, and some of the volcanic craters, is an 8300 km2 ice cap. During sub-glacial eruptions, glacial ice is melted, and temporarily dammed by either the crater or the ice itself. Eventually the pressure of the water is released in a catastrophic flood. A flood in 1996 discharged a 3km3 volume of water, lasting 2 ½ days. The glaciers and landscape are abruptly and extensively modified by this strong force, which erodes channels, moves and deposits huge blocks of ice and rock, and deposits kilometre scale alluvial fans.

Scientists can use radar imagery to create topographic models of the glaciers and extensive outwash plains to use as baseline maps for multitemporal change detection and mapping studies. Radar is preferred because persistently cloudy conditions limit the use of optical data. With new monitoring methods, including the analysis of glacial dynamics related to volcanic activity, scientists are better able to predict the timing of these extreme jökulhlaups.

 

Flood Delineation & Mapping

Background
A natural phenomenon in the hydrological cycle is flooding. Flooding is necessary to replenish soil fertility by periodically adding nutrients and fine grained sediment; however, it can also cause loss of life, temporary destruction of animal habitat and permanent damage to urban and rural infrastructure. Inland floods can result from disruption to natural or man-made dams, catastrophic melting of ice and snow (jökulhlaups in Iceland), rain, river ice jams and / or excessive runoff in the spring.

Why remote sensing?
Remote sensing techniques are used to measure and monitor the areal extent of the flooded areas , to efficiently target rescue efforts and to provide quantifiable estimates of the amount of land and infrastructure affected. Incorporating remotely sensed data into a GIS allows for quick calculations and assessments of water levels, damage, and areas facing potential flood danger. Users of this type of data include flood forecast agencies, hydropower companies, conservation authorities, city planning and emergency response departments, and insurance companies (for flood compensation). The identification and mapping of floodplains, abandoned river channels, and meanders are important for planning and transportation routing.

Data requirements
Many of these users of remotely sensed data need the information during a crisis and therefore require "near-real time turnaround". Turnaround time is less demanding for those involved in hydrologic modelling, calibration/validation studies, damage assessment and the planning of flood mitigation. Flooding conditions are relatively short term and generally occur during inclement weather, so optical sensors, although typically having high information content for this purpose, can not penetrate through the cloud cover to view the flooded region below. For these reasons, active SAR sensors are particularly valuable for flood monitoring. RADARSAT in particular offers a high turnaround interval, from when the data is acquired by the sensor, to when the image is delivered to the user on the ground. The land / water interface is quite easily discriminated with SAR data, allowing the flood extent to be delineated and mapped. The SAR data is most useful when integrated with a pre-flood image, to highlight the flood-affected areas, and then presented in a GIS with cadastral and road network information.

Canada vs. International
Requirements for this application are similar the world over. Flooding can affect many areas of the world, whether coastal or inland, and many of the conditions for imaging are the same. Radar provides excellent water/land discrimination and is reliable for imaging despite most atmospheric limitations.

Case study (example):
RADARSAT MAPS THE MANITOBA SEA:
THE FLOODS OF 1997
In 1997, the worst Canadian flood of the 20th century inundated prairie fields and towns in the states of Minnesota, North Dakota, and the Canadian province of Manitoba. By May 5th, 25,000 residents of Manitoba had been evacuated from their homes, with 10,000 more on alert. The watershed of the Red River, flowing north from the United States into Canada, received unusually high winter snowfalls and heavy precipitation in April. These factors, combined with the northward flow into colder ground areas and very flat terrain beyond the immediate floodplain, caused record flooding conditions, with tremendous damage to homes and property, in addition to wildlife and livestock casualties. For weeks emergency response teams, area residents, and the media monitored the extent of the flood, with some input from remote sensing techniques. It is impossible to imagine the scale of flooding from a ground perspective, and even video and photographs from aircraft are unable to show the full extent. Spectacular satellite images however, have shown the river expand from a 200 m wide ribbon, to a body of water measuring more than 40 km across. Towns protected by sand-bag dikes, were dry islands in the midst of what was described as the "Red Sea". Many other towns weren't as fortunate, and home and business owners were financially devastated by their losses.

Insurance agents faced their own flood of claims for property, businesses, and crops ruined or damaged by the Red River flood. To quickly assess who is eligible for compensation, the insurance companies can rely on remotely sensed data to delineate the flood extent, and GIS databases to immediately identify whose land was directly affected. City and town planners could also use the images to study potential locations for future dike reinforcement and construction, as well as residential planning.

NOAA image of the Manitoba Flood

Both NOAA-AVHRR and RADARSAT images captured the scale and extent of the flood. The AVHRR sensors onboard the NOAA satellites provided small-scale views of the entire flood area from Lakes Manitoba and Winnipeg south to the North Dakota - South Dakota border. Some of the best images are those taken at night in the thermal infrared wavelengths, where the cooler land appears dark and the warmer water (A) appears white. Manmade dikes, such as the Brunkild Dike (B), were quickly built to prevent the flow of water into southern Winnipeg. Dikes are apparent on the image as very regular straight boundaries between the land and floodwater. Although the city of Winnipeg (C) is not clearly defined, the Winnipeg floodway (D) immediately to the east, paralleling the Red River at the northeast end of the flood waters, is visible since it is full of water. The floodway was designed to divert excess water flow from the Red River outside of the city limits. In this case, the volume of water was simply too great for the floodway to carry it all, and much of the flow backed up and spread across the prairie.

RADARSAT image of the Manitoba Flood

RADARSAT provided some excellent views of the flood, because of its ability to image in darkness or cloudy weather conditions, and its sensitivity to the land/water differences. In this image, the flood water (A) completely surrounds the town of Morris (B), visible as a bright patch within the dark flood water. The flooded areas appear dark on radar imagery because very little of the incident microwave energy directed toward the smooth water surface returns back to the sensor. The town however, has many angular (corner) reflectors primarily in the form of buildings, which cause the incident energy to "bounce" back to the sensor.

Transportation routes can still be observed. A railroad, on its raised bed, can be seen amidst the water just above (C), trending southwest - northeast. Farmland relatively unaffected by the flood (D) is quite variable in its backscatter response. This is due to differences in each field's soil moisture and surface roughness.

Did you know?

It is worth your while to pay attention to the polarization characteristics of the radar imagery that you are collecting. If your target is to map flooded versus dry land, then HH (horizontal transmit, horizontal receive) is a much better choice than (say) VV (vertical transmit, vertical receive) polarization. The HH imagery will produce a noticeably stronger contrast between these two types of surfaces, allowing greater accuracy in the mapped result.

 

Soil Moisture

Background
Soil moisture is an important measure in determining crop yield potential in Canada and in drought-affected parts of the world (Africa) and for watershed modelling. The moisture content generally refers to the water contained in the upper 1-2m of soil, which can potentially evaporate into the atmosphere. Early detection of dry conditions which could lead to crop damage, or are indicative of potential drought, is important for amelioration efforts and forecasting potential crop yields, which in turn can serve to warn farmers, prepare humanitarian aid to affected areas, or give international commodities traders a competitive advantage. Soil moisture conditions may also serve as a warning for subsequent flooding if the soil has become too saturated to hold any further runoff or precipitation. Soil moisture content is an important parameter in watershed modelling that ultimately provides information on hydroelectric and irrigation capacity. In areas of active deforestation, soil moisture estimates help predict amounts of run-off, evaporation rates, and soil erosion.

Why remote sensing? Remote sensing offers a means of measuring soil moisture across a wide area instead of at discrete point locations that are inherent with ground measurements. RADAR is effective for obtaining qualitative imagery and quantitative measurements, because radar backscatter response is affected by soil moisture, in addition to topography, surface roughness and amount and type of vegetative cover. Keeping the latter elements static, multitemporal radar images can show the change in soil moisture over time. The radar is actually sensitive to the soil's dielectric constant, a property that changes in response to the amount of water in the soil.

Users of soil moisture information from remotely sensed data include agricultural marketing and administrative boards, commodity brokers, large scale farming managers, conservation authorities, and hydroelectric power producers.

Data requirements
Obviously, a sensor must be sensitive to moisture conditions, and radar satisfies this requirement better than optical sensors. Frequent and regular (repeated) imaging is required during the growing season to follow the change in moisture conditions, and a quick turnaround is required for a farmer to respond to unsuitable conditions (excessive moisture or dryness) in a timely manner. Using high resolution images, a farmer can target irrigation efforts more accurately. Regional coverage allows an overview of soil and growing conditions of interest to agricultural agencies and authorities.

Canada vs. International
Data requirements to address this application are similar around the world, except that higher resolution data may be necessary in areas such as Europe and Southeast Asia, where field and land parcel sizes are substantially smaller than in North America.

Case Study (example)
Rainfall distribution , Melfort, Saskatchewan, Canada

As with most Canadian prairie provinces, the topography of Saskatchewan is quite flat. The region is dominated by black and brown chernozemic soil characterized by a thick dark organic horizon, ideal for growing cereal crops such as wheat. More recently, canola has been introduced as an alternative to cereal crops.

Shown here is a radar image acquired July 7, 1992 by the European Space Agency (ESA) ERS-1 satellite. This synoptic image of an area near Melfort, Saskatchewan details the effects of a localized precipitation event on the microwave backscatter recorded by the sensor.

Shown here is a radar image acquired July 7, 1992 by the European Space Agency (ESA) ERS-1 satellite. This synoptic image of an area near Melfort, Saskatchewan details the effects of a localized precipitation event on the microwave backscatter recorded by the sensor. Areas where precipitation has recently occurred can be seen as a bright tone (bottom half) and those areas unaffected by the event generally appear darker (upper half). This is a result of the complex dielectric constant which is a measure of the electrical properties of surface materials. The dielectric property of a material influences its ability to absorb microwave energy, and therefore critically affects the scattering of microwave energy.

The magnitude of the radar backscatter is proportional to the dielectric constant of the surface. For dry, naturally occurring materials, this is in the range of 3 - 8 , and may reach values as high as 80 for wet surfaces. Therefore the amount of moisture in the surface material directly affects the amount of backscattering. For example, the lower the dielectric constant, the more incident energy is absorbed, the darker the object will be on the image.

Did you know?

Another part of the electromagnetic spectrum that has been used for soil moisture measurement is the gamma ray wavelength range. Recording the natural emission of gamma rays from the earth, aircraft carrying gamma ray spectrometers are used to detect the attenuation or alteration by soil moisture, of the intensity of the emanation. The gamma ray wavelength is extremely short - about 10-12 metres in length (!) and the intensity of this natural radiation at the earth's surface is very weak. As a result satellite altitudes are not practical for this form of remote sensing. Even the aircraft used for this purpose must fly as close to the ground as possible.

Source: http://www.ccrs.nrcan.gc.ca/