Lecture 4: Monitoring water resources Flashcards
Define the following:
- Monitoring
- Historic Analysis
- Forecasting
- Prediction
- Projections
- Monitoring: assessing current conditions
- Historic analysis: reconstructing or examining the past to
understand resources or risks - Forecasting: making an estimate of what will happen in the
future (exact or deterministic) - Prediction: making an estimate of what might happen in the
future (inexact or probabilistic) - Projections: making an estimate of a plausible future (inexact)
What are different approaches to monitoring water resources?
- in-situ observations
- Remote sensing from satellite and aircraft
- UAVs and other autonomous vehicles
- Paleo-data
- Modelling and prediction
What do we mean by models?
- Remote sensing often uses a retrieval model
to convert/invert the electromagnetic signal
into a hydrologic state/flux - Land Surface and hydrological
Models are used to monitor, forecast
and understand
-Weather and Climate
Models are used to forecast
and project
-Reanalysis and regional climate models
are used to reconstruct global and
regional atmospheric/land variables
-Diagnostic Tools used to
understand specific
processes
What is the uncertainty and error associated with models?
Hydrology and monitoring water resources is inherently uncertain:
-Random processes (e.g. weather); complex process interactions; difficult
to measure properties and states in detail; lack of data
Systematic error or bias
-errors that are consistently high or low over time – e.g. precipitation gauge
has a 10% low bias because of undercatch
Random error
-Errors that are unpredictable in space or time, e.g. hour to hour variations
in water levels
Error propagation
-Errors in a measured value propagate into quantities derived from it, e.g.
model predictions of soil moisture depend on the errors in the precipitation
data used to drive the model
Model errors
- simplified of erroneous representation of the physical processes
- Incorrect or uncertain parameter values
- Errors in forcing data (e.g. precipitation)
What are in-situ measurements?
- precipitation
- snow
- meterology
- evapotranspiration
- streamflow
- soil moisture
- groundwater
how do you measure precipiitation?
Rain gages are most commonly used for the measurement of precipitation,
both in terms of rain fall and snow
There are two main types of rain gages which are used to measure precipitation. These are:
- Non recording rain gages – just provides the daily total
2. Recording rain gages – gives the total but also the distribution within the day 1. Float type rain gages 2. Tipping bucket type rain gages 3. Weighing type rain gages
Also many other types: Optical gauges, capacitance gauges, acoustical,
disdrometers
- there are many types of gauges, which vary in their catch efficiency. Shielded gauges, like the one above, tend to perform better than unsheilded gauges. the liquid water equivalent of snowfall is especially hard to measure
describe snow measurement
Often using standard precipitation gauges • But also sophisticated snow measurement sites
what are the sources of errors in precipitation gages?
Undercatch – due to obstructions, orifice size, orientation, height, wind
shielding
Snowfall undercatch
Splash
Evaporation
Low precipitation
Recording errors
Observing time errors
Changes in gauge location
The last three also apply to measurements of other hydrological
processes
Precipitation measurement errors: undercatch, phase and orographic effects
1) Systematic undercatch of precipitation caused
by wind effects. Correction Factors ~ 1.0 -2.0
2) Undercatch correction dependent on precipitation
phase
3) Underestimation due to orographic effects
describe: estimating precipitation over a catchment
• A problem often faced with monitoring and
assessing water resources is to come up with an
areal average over the region of interest
(catchment, basin) or a gridded field of precipitation
(e.g. to drive a hydrological model)
• This generally requires interpolation of gauge data
between gauges
• Many types interpolation methods: simple
averaging, inverse distance weighting to optimal
interpolation. In general:
• Pinterp = SUM (Pi wi) / SUM (wi)
• NOTE – if the gauge network is dense enough then
all interpolation methods work equally well. If the
network is sparse, none of them work well. How
dense is dense enough?
How do you estimate the weights?
Some examples: • Based on distance -Develop a function based on the distance decay of the correlation in precipitation -This represents how close precipitation values at two different locations are expected to be
• Based on elevation -Precipitation can be strongly affected by elevation (hypsometric method) - Develop a relationship between precipitation and elevation - This relationship can be complex and changeable
what is the station density in the USA; Arctic?
Station density in the US looks very dense, but at the scale of a small catchment it
can be very sparse
Station density in the Arctic is very sparse and leads to large uncertainties in a
region that is experiencing some of the largest changes globally
UK precipitation gauge and Radar networks some of the densest in the world
What are radar measurements of precipitation?
A weather radar is a type of radar used to locate precipitation, calculate
its motion, estimate its type (rain, snow, hail, etc.), and forecast its
future position and intensity. Weather radars are mostly Doppler radars,
capable of detecting the motion of rain droplets in addition to intensity
of the precipitation. Both types of data can be analyzed to determine
the structure of storms and their potential to cause severe weather.
Often radar is merged with gauge data to provide a spatially continuous data product
that is consistent with gauge observations
Global precipitation- a decline in number of gauges leads to increasig uncertainty in global trends and basin averages
Figure. Uncertainties in global land precipitation from several datasets. The lower panel shows decline in the number of contributing gauges since the 1980s
explain gauge density versus uncertainty in spatial precipitation
• The error in areal average precipitation can be estimated (see Dingman) • For different global precipitation datasets, which use different sets of gauges and therefore densities, the error is different and this also depends on the location. • Main errors are from sampling errors (how representative the gauges are of the larger area) • And measurement errors (undercatch, interpolation, orographic) • Simple estimate of error: • E(%) = 40 e-0.05d • d is the gauge density (the number of gauges per 106 square kilometers)
How do you monitor precipiation?
- Direct methods:
a. Pan evaporation – direct measurement, but only free
water evaporation;
b. Weighing lysimeter – direct measurement, but difficult to set up and maintain - Calculation methods – using meteorological data
a. temperature- based
b. radiation based
c. combination methods
How do you estimate actual evaportranspiration (ET)?
- PET methods (Empirical methods with PET/P ratios;
Monthly water balance models; Soil moisture functions;
Complementary methods)
• ET = function(PET, other variables) +
assumptions/empiricism - Water balance approaches (land area budgets; lysimeter
and pan; soil moisture balance; atmospheric water balance;)
• ET = residual of the water balance given available data
for other components; e.g. E = P – R - dS/dt - Turbulent Excahnge/Energy balance approaches (P-M;
Bowen ratio; Eddy correlation; scintillometer)
• ET = derived from measured moisture and energy
fluxes - Water quality approaches (dissolved solids, isotopes)
• ET = derived from concentration of solids or isotopic fractions
equipment:
- scintillometer
- eddy correlation
Estimating actual ET
The Budyko Approach
- look at diagram
Streamflow gauges around the world with readily available data
…
Focus on africa: real-time hydrological monitoring is sparse
in terms of
GRDC streamflow records Real-time precipitation gauges Fluxnet (ET) Soil moisture only from research sites AMMA Network CARBOAFRICA network
How do we estimate water resources in an ungauged basin?
• Some of the places with the most need to understand and predict
water resources are the places with the least capacity to monitor
• This prevents analysis of past water resources variability, and floods
and drought, and thus risk assessment
• Real-time monitoring of water resources and hydrological hazards is
not feasible
• How do we estimate water resources in an ungauged basin?
Local data does exist but not easily useable
- many pentad records on paper
- often not real time
- perhaps the best case scenario in africa
What is involved in remote sensing and modelling
Remote sensing • Vegetation stress • Precipitation • Surface Water Storage • Evapotranspiration • Soil Moisture •Groundwater • Snow Modeling • Global • Regional • National
what is crowd sourcing
The power of the people
Define remote sensing
Remote sensing is the acquisition of information about an object or
phenomenon without making physical contact with the object and thus in contrast
to on-site observation
What are passive sensors
Passive sensors gather radiation that is emitted or reflected by the object or
surrounding areas. Reflected sunlight is the most common source of radiation
measured by passive sensors. Examples of passive remote sensors include film
photography, infrared, charge-coupled devices, and radiometers.
what are active sensors
Active sensors emit energy in order to scan objects and areas whereupon a
sensor then detects and measures the radiation that is reflected or backscattered
from the target. RADAR and LiDAR are examples of active remote sensing where
the time delay between emission and return is measured, establishing the
location, speed and direction of an object.
What are earth satelites?
Earth observation satellites are satellites specifically
designed for Earth observation from orbit, for uses
such as environmental monitoring, weather
monitoring and forecasting, map making etc.
What types of sensors are there for water resources?
Altimetry
• measures laser pulse return time
• changes in water levels (e.g. reservoirs, lakes, rivers)
Radar/scatterometers (active, MW & VI/NIR frequencies)
• measures returned/backscattered signal
• precipitation, soil moisture (MW)
• land surface temperature, evapotranspiration (VI/NIR)
Ranging
• measures satellite location due to gravity change
• changes in total water
storage
Sounder (MW)
• measures the atmospheric vertical profile
• Humidity, temperature, precipitation
Multispectral Radiometers/imagers (passive, MW & VI/NIR frequencies)
• Measure various atmospheric/surface properties in discrete spectral bands
• Soil moisture, snow, humidity, surface energy fluxes (ET), land imaging
Hyperspectral Spectrometers (passive) • Measure various atmospheric/surface properties in contiguous bands • Land surface properties, vegetation, agriculture
What different european space agency (ESA) satelittles are there ?
Meterological programme
- Weather monitoring and forecasting
Copernicus programme
- applications and earth monitoring
Earth observation envelope programme
- earth science
Give a few examples of the current NASA earth observation satellites
SMAP- soil moisture
AIRS- atmopsheric humidity and temp
GRACE- total water storage change
Jason 2- lake and river levels
How do satellites measure precipitation?
• Satellites can provide a more complete picture of
rain/snow from space, allowing us to look at
individual storms, rainfall totals, and changes over
seasons and years
• They are especially important in many developing
regions where in-situ data is sparse.
• The Tropical Rainfall Measuring Mission (TRMM)
has provided rainfall data since 1998 in the tropics
and mid latitudes
• The recently launched Global Precipitation
Measurement (GPM) Mission is extending
observations of rain and snow up to the high
latitudes (> 50o latitude N/S).
examples
TRIMM
GPM core
What are the methods for satellite precipitation?
Most precipitation satellites use a combination of TRMM Satellite
sensors to measure various aspects of precipitation
and merge these together to provide a final estimate
For TRMM this includes:
• Visible and Infrared Scanner (VIRS). Infrared
energy shows the temperature of the clouds
which is related to their altitude. VIRS sense the
top of the clouds only
• TRMM Microwave Imager (TMI). Measure water
vapor, cloud water and rainfall intensity within
clouds
• Precipitation Radar (PR). Shows the 3-D structure
of the clouds or a storm, indicating where the
rainfall is most intense, but only available as a
narrow swath.
• Lighting Imaging Sensor (LIS). An optical camera that
can see where lighting is occurring, which is very
useful for identifying heavy convective rainfall
What was the global precipitation mission?
• Core satellite launched February 27th, 2014 • Next-generation observations of rain and snow worldwide every three hours •GPM Microwave Imager (GMI) captures precipitation intensities and horizontal patterns • Dual-frequency Precipitation Radar (DPR) provides insights into the three dimensional structure of precipitating particles.
Applications: •Extends the capabilities of the TRMM sensors to detect falling snow, measure light rain, •And quantitative estimates of microphysical properties of precipitation • Drought monitoring globally, plus floods and water availability
What are satellite precipitation products?
Multiple products available in real-time that combine various sensor products in
different ways, including from TRMM and GPM
•TMPA, PERSIANN, CMORPH, CHIRPS, GSMAP, GPM IMERG, …
Satellite soil moisture- methods
• Microwave Radars (active): Backscattering coefficient s0 a measure of the reflectivity of
the Earth surface (e.g. C-Band of the Advanced SCATterometer (ASCAT) aboard the
EUMETSAT MetOp satellite)
• Microwave Radiometers (passive): Brightness temperature TB = e × Ts where e is the
emissivity and Ts is the surface temperature (e.g. ESA’s Soil Moisture Ocean Salinity
(SMOS) microwave radiometer; AMSR-E Advanced Microwave Scanning Radiometer
aboard EOS)
• Passive and active methods are interrelated through Kirchhoff’s law: e = 1 – r where r is
the reflectivity. Example: increase in soil moisture content
Backscatter ↑
Emissivity ↓
example:
SMOS passive radiometer
What are the disadvantages of microwave soil moisture sensors?
• Disadvantages of microwave Soil Moisture
Sensors: only see the top cm of soil; cannot
penetrate dense vegetation at high
frequencies; generally low resolution (10s km);
radio frequency interference
What what the soil moisture active passive (SMAP) mission?
• SMAP launched in Jan 2015
• Global mapping of soil moisture at a 10-km
spatial resolution with a 2-3 day revisit time
under both clear and cloudy sky conditions
• Improved resolution relative to AMSR-E (25km)
and SMOS (50km)
• Combines L-band radar (high resolution 1-3km,
lower accuracy) and an L-band radiometer (low
resolution 40km higher accuracy)
• Retrievals for a wider range of vegetation
conditions and for top 5cm
• Plus root zone estimates by merging SMAP
observations with model estimates via
assimilation system
How do you measure surface water levels?
e.g. USDA global reservoir and lake monitor
- based on laser altimetry data
- limited to large lake and reservoirs
- repeat 10 days for a single location
What was the surface water ocean topography (SWOT) mission?
• Launch date 2020
• Water surface elevation for inland waters
including lakes, reservoirs, rivers, and wetlands
• Follow on from Topex/Poseidon, Jason-1 and -2,
ENVISAT RA
• Ka-band synthetic aperture radar (SAR)
interferometer with two antennas
• Spatial resolution of 10s meters - capability to
resolve rivers with widths greater than 50-100-m
and water bodies with areas greater than 250-m2
• Maximum 10-day temporal resolution
Applications: • Surface water (i.e., areal extent, storage, and discharge) globally • Lake storage, water surface profiles, depth and discharge of rivers • Assimilation into hydrological models • Water resources management • Energy, agriculture, transport,
How do you measure ET from remote sensing?
Various methods for retrieving ET – energy balance, mass transfer, combination and
index methods.
• Methods are generally based on the fact that when a surface evaporates, it loses
energy and cools
• The satellite senses infrared heat radiation from the Earth, thus enabling to
distinguish between cool (more evaporation) and warn (less evaporation) surfaces
Satellite evaporative stress indices based on LST
blackboard
Satellite surface/ subsurface water: GRACE
well done
The Gravity Recovery and Climate Experiment
(GRACE) is a pair of NASA satellites that has
flown in low-Earth orbit since 2002. The
satellites use a precise microwave ranging
system to measure the distance between
themselves due to gravitational acceleration.
Onboard GPS instruments determine the exact
position of the satellites over the Earth.
Resolution is ~500km, monthly – very coarse!
GRACE measures changes in Earth's gravity field, which are directly related to changes in surface mass. The surface mass signal largely reflects total water storage (TWS); over the ocean TWS is interpreted as ocean bottom pressure and on land it is the the sum of groundwater, soil moisture, surface water, snow and ice.
Application of GRACE to drought monitoring?
- GPS and GRACE are
complementary in terms of
resolution, timeliness and coverage - Assimilation of GRACE into
model for drought
monitoring
What are the errors in satellite data?
• Sensor measurement errors
- Geometric distortions
- Rotation of the earth, curvature, relief/shadowing,
- Sensor stability
- Antenna movement, altitude, velocity
- Sampling errors
- Instantaneous image, footprint resolution, repeat time
- Retrieval algorithm
- Errors in the physical representation
• Algorithm calibration
• Continuity errors
• Long-time series require stitching together of data from
individual satellites that may fly for only a few years
what are the example of errors in satellite precipitation?
Component analysis of errors
in satellite-based precipitation
estimates
The total systematic error (bias) (difference from in-situ) = Hit bias (satellite predicted rain when it did rain, but predicted too much or too little - Missed P (satellite predicted no rain when it did rain) \+ False P (satellite predicted predicted rain when it did not rain) Tian et al (2009)
Satellite precipitation- dependency of errors on elevation
diagram on blackboard
satellite precipitation- what are the errors from discontinuties
Time at which there is a detectable shift between a satellite product and a satellitegauge-corrected
product
How do you quantify the water busget from satelittles?
satellite sources:
ds/dt from GRACE
ET from CERES/MODIS/ AIRS
P from GPM
Q from TOPEX/ POSEIDON/ JASON
Independent RS-based estimates of the
water budget do not provide closure
How do you reduce uncertainties (ε = 0)
and close the water budget?
…
What are hydrological modelling?
Hydrologic models are simplified, conceptual representations of the land part of
the hydrologic cycle. They are primarily used for hydrologic prediction
(monitoring and forecasting) and for understanding hydrologic processes.
What are the two major types of hydrological models?
• Stochastic Hydrological Models. These models are black box systems, based
on data and using mathematical and statistical concepts to link a certain input
(for instance rainfall) to the model output (for instance runoff). Commonly
used techniques are regression, transfer functions, neural networks and
system identification.
• Process-Based or Physically-Based Hydrological Models. These represent
the physical processes observed in the real world. Typically, such models
contain representations of surface runoff, subsurface flow,
evapotranspiration, and channel flow, but they can be far more complicated.
These models are also known as deterministic hydrology models but can be
run in a stochastic framework
How are hydrological models used to understand the hydrological cycle and water resources?
a. Estimating available water in ungauged regions
b. Hazard risk assessment
c. Hazard forecasts (floods and droughts)
d. Quantifying sustainability (e.g. safe yield)
e. Understanding and attributing processes and changes
f. Land use change impacts
g. Climate change impacts
What is the scale representation in hydrological models?
Computational unit is a
catchment.
Stochastic/physical
Computational unit is a
sub-catchment.
Stochastic/physical
Computational unit is a grid
cell. Physically based
What is in a physically-based model?
Each component is modeled using a set of equations that represent the physical hydrological process
Inputs: precipitation,
temperature (humidity,
windspeed, surface
radiation, pressure, …)
Outpus: R, Q, ET, SM,
GW, …
How different are predictors from different models?
- Averaged evapotranspiration over the Amazon basin for 1989-
2008 period from a set of models using the same precipitation - Implies that which model you choose has a large influence on your results
What are operational hydrological modelling systems?
Models are run in real-time (perhaps a few
hours behind) to monitor water resources,
forecast floods and droughts, provide early
warning, …
UK 1km Grid-2-Grid Hydrological Model
What are the new technologies for monitoring water resources
Several new technologies have emerged in the last few years that could
transform how we monitor hydrology and water resources
• UAVs
• Low cost environmental sensors
• Sensor networks
• Crowd sourcing
What are the unmanned Aerial Vehicles (UAVs)
UAVs can carry portable cameras and sensors that replicate the spectral bands on satellite sensors (e.g. Sentinel 2)
Uses in water resources monitoring a. Estimating ET b. Estimating crop water use c. Irrigation needs d. Vegetation information (phenology, health and stress) e. Surface temperature
How do you overcome the lack of in-situ gauges?
Low Cost Environmental Sensors communicating
over the Mobile Phone Network
What are automatic weather stations vs low cost sensors?
£20,000 (high accuracy, reliable)
vs
£300 (low accuracy, reliable enough?)
Sensor networks- NetAtmo example?
Recent reports from NetAtmo home weather stations showing a global sample of rainfall reports as categorized from light to extreme rainfall, and (bottom right) reports for southern England showing the much higher density of reports in western Europe.
Crowd-sourcing- Met office example
…
