This document discusses using unmanned aerial vehicles (UAVs) for hydrological monitoring. It provides details on UAV applications such as precision agriculture, environmental monitoring, and stream flow monitoring. Methods are described for detecting water stress with UAV thermal imagery and predicting root zone soil moisture. Guidelines are also presented on UAV rules and regulations, velocity measurement techniques, and testing tracers for stream flow monitoring with UAVs.
Use of Unmanned Aerial Systems for Hydrological MonitoringSalvatore Manfreda
Invited presentation given during the EGU General Assembly at the session entitled "Advances in river monitoring and modelling: data-scarce environments, real-time approaches, Inter-comparison of innovative and classical frameworks, uncertainties, Harmonisation of methods and good practices"
DEM-based Methods for Flood Risk Mapping at Large ScaleSalvatore Manfreda
Oral presentation given during the meeting "Valutazione e Gestione del Rischio Alluvioni – Governance del territorio e contributo del mondo scientifico" of the project "Mettiamoci in Riga"
Introduction -Remote means – far away ; Sensing means – believing or observing or acquiring some information.
Remote sensing means acquiring information of things from a distance with sensors. (without touching the things)
Sensors are like simple cameras except that they not only use visible light but also other bands of the electromagnetic spectrum such as infrared, microwaves and ultraviolet regions.
Distance of Remote Sensing, Definition of remote sensing - Remote Sensing is:
“The art and science of obtaining information about an object without being in direct contact with the object” (Jensen 2000).
India’s National Remote Sensing Agency (NRSA) defined as : “Remote sensing is the technique of deriving information about objects on the surface of the earth without physically coming into contact with them.”
Remote Sensing Process, - (A) Energy Source or Illumination.
(B) Radiation and the Atmosphere.
(C) Interaction with the Target.
(D) Recording of Energy by the Sensor.
(E) Transmission, Reception, & Processing.
(F) Interpretation and Analysis.
(G) Application.
Remote sensing platforms , History of Remote Sensing, Applications of remote sensing - In Agriculture, In Geology, Applications of National Priority.
Optical and Microwave Remote Sensing for Crop Monitoring in MexicoCIMMYT
Remote sensing –Beyond images
Mexico 14-15 December 2013
The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)
Workshop on Operationalizing the Regional Collaborative Platform to Address ‘Water Consumption, Water Productivity and Drought Management’ in Agriculture, 27 - 29 October 2015, Cairo, Egypt
Use of Unmanned Aerial Systems for Hydrological MonitoringSalvatore Manfreda
Invited presentation given during the EGU General Assembly at the session entitled "Advances in river monitoring and modelling: data-scarce environments, real-time approaches, Inter-comparison of innovative and classical frameworks, uncertainties, Harmonisation of methods and good practices"
DEM-based Methods for Flood Risk Mapping at Large ScaleSalvatore Manfreda
Oral presentation given during the meeting "Valutazione e Gestione del Rischio Alluvioni – Governance del territorio e contributo del mondo scientifico" of the project "Mettiamoci in Riga"
Introduction -Remote means – far away ; Sensing means – believing or observing or acquiring some information.
Remote sensing means acquiring information of things from a distance with sensors. (without touching the things)
Sensors are like simple cameras except that they not only use visible light but also other bands of the electromagnetic spectrum such as infrared, microwaves and ultraviolet regions.
Distance of Remote Sensing, Definition of remote sensing - Remote Sensing is:
“The art and science of obtaining information about an object without being in direct contact with the object” (Jensen 2000).
India’s National Remote Sensing Agency (NRSA) defined as : “Remote sensing is the technique of deriving information about objects on the surface of the earth without physically coming into contact with them.”
Remote Sensing Process, - (A) Energy Source or Illumination.
(B) Radiation and the Atmosphere.
(C) Interaction with the Target.
(D) Recording of Energy by the Sensor.
(E) Transmission, Reception, & Processing.
(F) Interpretation and Analysis.
(G) Application.
Remote sensing platforms , History of Remote Sensing, Applications of remote sensing - In Agriculture, In Geology, Applications of National Priority.
Optical and Microwave Remote Sensing for Crop Monitoring in MexicoCIMMYT
Remote sensing –Beyond images
Mexico 14-15 December 2013
The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)
Workshop on Operationalizing the Regional Collaborative Platform to Address ‘Water Consumption, Water Productivity and Drought Management’ in Agriculture, 27 - 29 October 2015, Cairo, Egypt
Runoff is one of the most significant hydrological variables used in most of the water resources applications. Physiographically the area is characterized by undulating topography with plains and valleys. The Soil Conservation Service Curve Numbers also known as hydrologic soil group method were used in this study. This method is adaptable and suitable approach for quick runoff estimation and is approximately easy to use with minimum data and it gives good result. From the study yearly rainfall and runoff were estimated easily. The study area covers an area of 466.02 km2, having maximum length of 36.5 km. The maximum and minimum elevation of the basin is 569 m and 341 m above MSL, respectively.
Streamflow simulation using radar-based precipitation applied to the Illinois...Alireza Safari
This paper describes the application of a spatially distributed hydrological model WetSpa (Water and Energy Transfer between Soil, Plants and Atmosphere) using radar-based rainfall data provide by the United States Hydrology Laboratory of NOAA's National Weather Service for a distributed model intercomparison project. The model is applied to the
river basin above Tahlequah hydrometry station with 30-m spatial resolution and one hour time--step for a total simulation period of 6 years. Rainfall inputs are derived from radar. The distributed model parameters are based on an extensive database of watershed characteristics available for the region, including digital maps of DEM, soil type, and land use. The model is calibrated and validated on part of the river flow records. The simulated hydrograph shows a good correspondence with observation (Nash efficiency coeffiecient >80%, indicating that the model is able to simulate the relevant hydrologic processes in the basin accurately.
ESTIMATION OF NRCS CURVE NUMBER FROM WATERSHED MORPHOMETRIC PARAMETERS: A CAS...IAEME Publication
The NRCS-CN equation for flood predictions relies on the value of the Curve Number and the amount of rainfall event to determine the corresponding runoff. Usually, the curve number value (CN value) is extracted from the tables that follow United State land features classification which might not be applicable to the land features in Saudi Arabia. This research paper doesn’t use NRCS-CN table values form of the US for estimating the curve number value, rather, the CN values have been estimated from the data of rainfall and runoff events of some gauged watersheds in the western region of Saudi Arabia (Yiba watershed and its sub-basins).
SWaRMA_IRBM_Module2_#5, Role of hydrometeorological monitoring for IRBM in Ne...ICIMOD
This presentation is the part of 12-day (28 January–8 February 2019) training workshop on “Multi-scale Integrated River Basin Management (IRBM) from the Hindu Kush Himalayan Perspective” organized by the Strengthening Water Resources Management in Afghanistan (SWaRMA) Initiative of the International Centre for Integrated Mountain Development (ICIMOD), and targeted at participants from Afghanistan.
Watershed management: Role of Geospatial Technologyamritpaldigra30
Watershed management is the study of the relevant characteristics of a watershed which is done to enhance watershed functions that affect the plant, animal and human or other living communities within the watershed boundary.
This PPT dscribes the Role of Geospatial Technology in Watershed Management
- Morphometric analysis of the Watershed is considered to be the most satisfactory method because it enables in
understanding of the relationship of various aspects within a drainage basin. In the present study two mini watersheds in Raichur city
have been considered Mini-watershed 1 with an area of 519.32 km2 with highest order stream of 6 it flows through north of city and it
joins the streams of Krishna, Mini –Watershed 2 with an area of 360.97 km2 with highest order stream of 5 it flows through south of
city and joins Tungabhadra streams. The values of Stream frequency is 1.07 and 1.03, Form factor 0.35and 0.53, Shape factor 2.84 and
1.90, Elongation Ratio 0.67 and 0.82, Circularity Ratio 0.27 and 0.42, Drainage density 1.26 and 1.30, Length of overland flow 0.40 and
0.38 for Mini-watershed 1 and Mini-watershed 2 respectively
In recent years, numerous studies have shown a growing concern about the effects of climate change on the hydrological cycle and hydrological extremes. In particular, statistical analyses on either long hydrological series or modelled data show conflicting trends in different areas of Europe. In addition, the absence of continuous observations and the significant alterations experienced by some watersheds makes difficult to quantify the effects of climate change. These critical issues are particularly felt in Southern Italy where hydrometric monitoring is often discontinuous, updated flow rating curves rarely exist, and territories underwent significant anthropogenic transformations. The present work aims to update flood time-series in Southern Italy, using direct and indirect measurements, over the period 1920-2021. The numerous missing data were reconstructed by means of specially defined flood rating curve or by using daily flow rates to derive equivalent flood flows through the empirical function by Fuller. The obtained series were, then, analysed using the nonparametric Mann-Kendall test in order to detect possible trends. The results of the present study provide preliminary indications of flood trends over the last 50 years in Southern Italy by integrating an information gap regarding this phenomenon and its dynamics.
TECNICHE DI RICOSTRUZIONE SPAZIALE DELLE SERIE DI PIOGGIA ESTREMA IN ITALIA M...Salvatore Manfreda
Nel presente lavoro sono state identificate le dinamiche delle precipitazioni estreme sub-giornaliere nell'Italia meridionale nel periodo 1970-2020 attraverso un database dei massimi annuali delle precipitazioni orarie (1, 3, 6, 12 e 24 ore).
Le attività di Ricerca sull’Impiego di Droni in AgricolturaSalvatore Manfreda
L’impiego di tecnologie avanzate, IOT ed i servizi innovativi guideranno la trasformazione digitale di numerosi settori a diversa vocazione primo tra tutti
l’Agricoltura. Questi i temi al centro del workshop organizzato dall’Associazione Italiana Droni insieme a Confindustria Servizi Innovativi e Tecnologici che avrà come obiettivo l’analisi del contributo delle tecnologie e dei servizi digitali come abilitatori di nuovi modelli di business, orientati all’utilizzo dei dati, alla collaborazione tra attori della filiera, all’attenzione e centralità del cliente finale.
Ref: https://rebrand.ly/UAS
Sistema di gestione e monitoraggio delle risorse idriche in BasilicataSalvatore Manfreda
Presentazione tenuta durante il convegno "Gestione, rischio e riabilitazione delle opere di sbarramento: il ruolo degli enti e delle istituzioni e lo stato della ricerca", Potenza, 27 Marzo 2019.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
1. SC53| Early Career Scientists (ECS)| www.egu.eu/ecs
Use of UAV for Hydrological Monitoring
Wed, 26 Apr, 15:30–17:00 / Room -2.85
Salvatore Manfreda
University of Basilicata, Italy
salvatore.manfreda@unibas.it
http://www2.unibas.it/manfreda/
NhET & ESSI ECS
5. The Rules
Source: BI Intelligene – 2015 and ENAC 2017
USA ITALY
• The drafted rules are relatively restrictive — they allow only for commercial flights by licensed operators within visual range of the
aircraft (i.e., no remotely operated flights) and severely restrict where the flights can be conducted.
• The operator of the aircraft must be licensed as a drone pilot
by the FAA, and the credential must be renewed every two
years. The licensing process is not yet in place and is part of
what needs to be detailed for the rules to go into effect
• The UAV may not weigh more than 55 pounds (25 kilograms)
• The pilot must keep the UAV within visual line of sight at all
times during flight
• The UAV may not fly any faster than 100 miles per hour (161
kilometers per hour)
• Maximum altitude is only 500 feet (152 meters)
• Other government agencies will need to study the privacy
implications of the flights and propose a framework for
industry self-regulation
<25 kg
>25<150
UAV
60 kilometers per hour
150 meters altitude
and 500 meters
distance
• UAVs cannot be flown above any people not involved in the flight or near restricted airport or flight areas (this effectively rules out
UAV flights over urban or even sparsely populated areas)
• The flights must occur in daylight
• Professional use “Section 333” – exemptions
possible under authorization
60 months < 40 y
24 months < 50 y
12 months < 65 y
6 months > 65
Enac
APR SAPR - (remotely piloted aircraft systems)
On line section
6. TOP APPLICATIONS
Precision agriculture: management of crops to guarantee efficiency of
inputs like water and fertilizer and maximize productivity, quality, and
yield. It also involves the minimization of pests, unwanted flooding, and
disease.
Energy, mining, and utilities: resources management and research
requires monitoring over large territories, often in inaccessible areas.
Real estate, construction, and land development: need managing and
mapping large portion of land or collections of buildings.
Environmental monitoring: ecological state of ecosystems, plant stress,
water pollution, soil contamination, water contamination, monitoring
of water systems (rivers, lakes, dams etc.).
7. An example
in Agriculture
• Pathogen/pest/weed detection
• Crop modeling/yield estimation
• Nutrient management
• Crop water use/irrigation
8. Engines
MK3638
Li-Po Battery
8Amp 30C
Camera mount
servo-stabilized
carbon-fiber
UAVEurope ®
Example: multi-copter 6
engines equipped with a
thermal camera
Thermal camera
GOBI384 Xenics®!
Ubiquiwifi ,
on line wi-fi
data streaming
Propellers
(APC 12x3,8 inc)Frame
(carbon fiber Air-
Sci UAVEurope®)
Electronic
systems:
Mikrokopter®
20. Thermal indexes… an attempt to normalize the environment (Idso et al., 1980; Jones, 1999)
CWSI = T canopy – Twet / Tdry – Twet
IG = T dry – Tcanopy / Tcanopy – Twet
I3= T canopy – Twet / Tdry – Tcanopy
And the leaf energy balance:
𝑇" − 𝑇$ =
𝑟() 𝑟$* + 𝑟, 𝛾𝑅/0 − 𝑝𝑐3 𝑟() 𝐷
𝑝𝑐3 𝛾 𝑟$* + 𝑟, + 𝑠𝑟()
6
𝑟, =
−𝑝𝑐3 𝑟() 𝑠 𝑇" − 𝑇$ + 𝐷
𝛾 𝑇" − 𝑇$ 𝑝𝑐3 − 𝑟() 𝑅/0 − 𝑟$*
6
How to detect the
drought from an UAV?
21. How to detect the
drought from an UAV?
http://bestdroneforthejob.com/
22. Predicting root zone soil moisture
with near-surface moisture data in
semiarid environments
23. Manfreda et al. (AWR - 2007)
Relationship existing between
surface and root-zone soil
moisture
24. Soil Moisture Analytical
Relationship (SMAR)
The schematization proposed assumes the soil composed of two layers,
the first one at the surface of a few centimeters and the second one
below with a depth that may be assumed coincident with the rooting
depth of vegetation (of the order of 60–150 cm).
The challenge is to define a soil water balance equation where the
infiltration term is not expressed as a function of rainfall, but of the soil
moisture content in the surface soil layer.
This may allow the derivation of a function of the soil moisture in one
layer as a function of the other one.
Manfreda et al. (HESS - 2014)
s1(t)
s2(t)
First layer
Second layer
Zr2
Zr1
25. Soil water balance
Defining x=(s-sw)/(1-sw) as the “effective” relative soil saturation and
w0=(1-sw)nZr the soil water storage, the soil water balance can be
described by the following expression:
where:
s [–] represents the relative saturation of the soil,
sw [–] is the relative saturation at the wilting point,
n [–] is the soil porosity,
Zr [L] is the soil depth,
V2 [LT-1] is the soil water loss coefficient accounting for both
evapotranspiration and percolation losses,
x2 [–] is the “effective” relative soil saturation of the second soil layer.
1 − !! n!!!!
d!!(!)
d!
= !!!!!y t − !!!! !
Infiltration Losses
(1)
26. Water flux exchange between
the surface and the lower layer
The water flux from the top layer can be considered significant only
when the soil moisture exceeds field capacity (Laio, WRR 2006).
Assuming that
where n1 [-] is the soil porosity of the first layer;
Zr1 [L] is the depth of the first layer;
s1 (θ1/n1) [-] is the relative saturation of the first layer;
s1(t)
s2(t)
First layer
Second layer
(2)
Zr2
Zr1
sc1 [-] is the value of relative
saturation at field capacity.
27. Soil Moisture Analytical Relationship
(SMAR) beetween surface and root
zone soil moisture
Expanding Eq. 8 and assuming Dt = (tj - ti), one may derive the
following expression for the soil moisture in the second layer based on
the time series of surface soil moisture:
Assuming an initial condition for the relative saturation s2(t) equal to
zero, one may derive an analytical solution to this linear differential
equation that is
(7)
(9)
!! !! = !! + (!! !!!! − !!)!!!! !!!!!!!
+ 1 − !! !!! !! !! − !!!!
For practical applications, one may need the discrete form as well:
(8)
28. Sensitivity of SMAR’s
parameters
The derived root zone soil moisture (SRZ) is plotted changing the soil water
loss coefficient (A), the depth of the second soil layer (B), and the soil
textures (C).
Manfreda et al. (HESS - 2014)
29. Use with satellite data:
coupling the SMAR with EnKF
(Baldwin et al., J. Hydr., 2016)
Ridler et al (2014) showed how a satellite correction bias could be
calculated within the EnKF to correct the discrepancy between satellite
and in situ near-surface measurements.
Integrating a simple hydrologic model with an EnKF algorithm can
provide RZSM estimates as accurately as those made by complex
process models (Bolten et al, 2010; Crow et al, 2012).
Since the SMAR model’s four parameters (surface field capacity, root
zone wilting level, diffusivity coefficient and water loss coefficients) are
related theoretically to soil properties that are available globally, it
would be possible to effectively run SMAR across space after
uncovering relationships between soil physical variables and SMAR
model parameters (Reichle et al, 2001).
30. Schematic of the bias estimation
procedure for SMAR-EnKF
(Baldwin et al., J. Hydr., 2016)
31. SMAR-EnKF optimization
and prediction
Root mean square errors ranging from 0.014 - 0.049 [cm3 cm-3].
Semi-arid Highlands
Temperate Forests
Temperate Forests
North American Deserts
Great PlainsTropical Wet Forests
Forested Mountains Northern Forests
(Baldwin et al., J. Hydr., 2016)
34. • The evaluation of river water discharge is traditionally
performed according to the rule ISO 748/1997, using the
velocity-area method which represents an efficient and
reliable tool. Operatively, computations require to divide
the section areas into several verticals and a further
subdivision of each vertical into discrete points, in order
to evaluate the mean velocity of the flow along each
vertical.
• The number of verticals and the distribution inside the
cross section must been chosen case by case based on
section width, riverbed geometry and flow regimes
characteristics, while the measurement points are fixed
according to the measurement methodology used, that
is, by wading or bridge.
Traditional Methods for water
discharge measures 1/2
35. The main objective is to obtain a correct evaluation of the
mean velocity for each vertical and section which is related to
a reliable reconstruction of flow field obtained through velocity
point measurements in several marks of hydraulic sections
generally distributed from bottom up to the free surface flow.
Once evaluated the mean velocity for each vertical, the water
discharge can be calculated by the way of the mean-section
method or mid section method.
Traditional Methods for water
discharge measures 1/2
i + 1
i
( ) ( )( )
( ) ( )[ ]
2.0
,1max
1
<
+
-+
iviv
iviv
36. Mean-Section method
In the first one, the partial discharge is computed by
multiplying the average value of mean velocities of two
adjacent verticals times the area included in the respective
verticals. The equation of the partial discharge between
two verticals 1 and 2, with depth d1 and d2, mean velocities
v1 and v2 and the horizontal distance between the two
verticals b, is the following:
b
2
dd
2
vv
q 2121
×÷
ø
ö
ç
è
æ +
×÷
ø
ö
ç
è
æ +
=
This is repeated for each segment and the total
discharge is obtained by adding the partial discharge
from each segment.
(10)
37. di+1di
bi
åå =
++
=
×÷
ø
ö
ç
è
æ +
×÷
ø
ö
ç
è
æ +
==
N
i
i
iiii
N
i
i b
ddvv
QQ
1
11
1 22
Mean-section method
2
1++
= å ii
ii
bb
dvQ
Mid section method
DISCHARGE
COMPUTATION
di
b
(11)
(12)
38. Entropy Model
Entropy distribution of flow velocity is:
( ) ú
û
ù
ê
ë
é
-
-
-+=
0max
0max
11ln
xx
xxM
e
M
u
u
M
1
1e
e
u
u
M
M
max
-
-
==f
where M is the entropy parameter that could be derived by the relation
between the mean and the maximum velocities observed in the cross
section:
÷
ø
ö
ç
è
æ
-
-
-
=
hD
y
hD
y
1expx
D
y
=x
dimensionless variable x, depending on the reference system adopted:
in the case of natural and artificial free surface
flows:
(13)
(14)
(15)
(16)
39. According to the approach of Moramarco and Singh (2010), the mean velocity
can be evaluated using the classical Manning’s formula:
fh SR
n
u 3/21
=
( ) ú
û
ù
ê
ë
é
÷
ø
ö
ç
è
æ
-+= *
D
y
k
α
y
y
k
uyu 1lnln
1
0
While the maximum velocity of the cross-section, umax, can be derived
through the velocity distribution proposed by Yang et al. (2004)
ú
û
ù
ê
ë
é
+
=÷÷
ø
ö
çç
è
æ
-
-
=F
D
y-D
ln
y
y-D
y
y
ln
k
1
g/R
n
1
M
1
1
)M(
max
max
max
0
max
6/1
h
M
M
e
e
y0 is the distance at which the velocity is hypothetically equal to zero; α is the dip-correction
factor, depending only on the ratio between the relative distance of the maximum velocity location
from the river bed, ymax, and the water depth, D, along the y axis, where umax is sampled
Entropy Model
(17)
(18)
(19)
45. Testing different
tracers
Distance (m) Vmicro (m/s)
0.4 0.086
0.5 0.080
0.6 0.084
Wood Chips
polystyrene polyurethane
micro current meter
Q=18 l/s; h=0.27 m
Q=31 l/s; h=0.15 m
46. Velocity validation
Test 3 – PE + Alu
Test 3 – wood chips
EGU2017-15792 | Posters | NH6.3/AS4.43/GI2.10/HS11.31/SM5.8/SSS12.21
Testing different tracers for stream flow monitoring with UAS
Silvano Fortunato Dal Sasso, Salvatore Manfreda, Alonso Pizarro, and Leonardo Mita
Fri, 28 Apr, 17:30–19:00, Hall X3, X3.250
47. Comparison with
different tracers
Test Tracers
Vs (m/s)
% difference implementation issues
current meter radar Vmed (m/s)
1
wood chips
0.09
- 0.09 1% tracer clearly visible
coal 0.09 4% poor tracer's contrast
2
PE
0.46 0.38
0.50 8%
tracer visible - formation of
agglomerates
coal 0.52 12% poor tracer's contrast
3
PE + Al
0.37 0.32
0.37 0% tracer clearly visible
wood chips 0.36 4%
tracer with low dimension
and contrast
coal 0.34 9% poor tracer's contrast
PE + Al Wood chips Coal
52. Papers related to this research line…
Baldwin, D., S. Manfreda, K. Keller, and E.A.H. Smithwick, Predicting root zone soil moisture with
soil properties and satellite near-surface moisture data at locations across the United States,
Journal of Hydrology, (under review) 2016.
Faridani, F., A. Farid, H. Ansari, and S. Manfreda, Estimation of the root-zone soil moisture using
passive microwave remote sensing and SMAR model, Journal of Irrigation and Drainage
Engineering, 04016070, 1-9, 2016.
Faridani, F., A. Farid, H. Ansari, S. Manfreda, A modified version of the SMAR model for estimating
root-zone soil moisture from time series of surface soil moisture, Water SA (under review), 2016
Manfreda, S., L. Brocca, T. Moramarco, F. Melone, and J. Sheffield, A physically based approach for
the estimation of root-zone soil moisture from surface measurements, Hydrology and Earth System
Sciences, 18, 1199-1212, 2014.
Manfreda, S., M. Fiorentino, C. Samela, M. R. Margiotta, L. Brocca, T. Moramarco, A physically
based approach for the estimation of root-zone soil moisture from surface measurements:
application on the AMMA database, Hydrology Days, pp. 47-56, 2013.
Manfreda, S., T. Lacava, B. Onorati, N. Pergola, M. Di Leo, M. R. Margiotta, and V. Tramutoli, On
the use of AMSU-based products for the description of soil water content at basin scale, Hydrology
and Earth System Sciences, 15, 2839-2852, 2011.
53. Summer School of Hydrology
Applied Course on UASs for
Environmental Monitoring
MATERA - Italy