Water and Energy Management in India: Artificial Neural Networks and Multi-Criteria Decision Making Approaches

292 Pages·2021·7.985 MB·English

by  Mrinmoy Majumder, Ganesh D. Kale

Mrinmoy Majumder
Ganesh D. Kale Editors
Water and
Energy
Management
in India
Artificial Neural Networks and
Multi-Criteria Decision Making
Approaches
Water and Energy Management in India
·
Mrinmoy Majumder Ganesh D. Kale
Editors
Water and Energy
Management in India
Artificial Neural Networks and Multi-Criteria
Decision Making Approaches
Editors
MrinmoyMajumder GaneshD.Kale
Hydro-InformaticsEngineering(under DepartmentofCivilEngineering
DepartmentofCivilEngineering) SardarVallabhbhaiNationalInstitute
NationalInstituteofTechnologyAgartala ofTechnology
Jirania,Agartala,India Surat,Gujarat,India
ISBN978-3-030-66682-8 ISBN978-3-030-66683-5 (eBook)
https://doi.org/10.1007/978-3-030-66683-5
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Preface
Theuncontrolledextractionandtheunevendistributionofthewaterresourcesworld-
widehaveresultedinscarcityofwaterandnowinmanyplacesoftheEarthmany
peopledonothaveregularsupplyofdrinkingwater.
Theburgeoningpopulationaddedwiththeadvancementoftechnologyhasalso
imbibedhighdemandforenergyresources.GAIAhasfiniteamountoffossilfuels.
Ifthedemandgetincreasedcomparedtotheavailablefossil-basedenergyresources,
then deficit will occur and if the current rate of consumption continues then also
scarcitywilltakeplaceandsoonmostoftheregionwillbeunderenergystress.
Nowbothwaterandenergyresourcesareunderstressandthesolutionliesintheir
interdependencies.Optimalmanagementofwaterinenergysystemsandviceversa
canreducethestressonboththeresources.
ManagementofWaterandEnergyInterdependencies
inWorld
Globally,billionsofcitizenslackaccesstothecleandrinkingwaterandcleanliness
and more than 3/4th of the wastewater is released untreated. Energy is a critical
partofthesolution.AccordingtoastudybyInternationalEnergyAgency(IEA),it
wasfoundthatattainingcomprehensiveaccesstocleanwaterandsanitation(SDG6)
wouldincreaselessthan1%toglobalenergydemandintheSustainableDevelopment
Scenarioby2030.Inruralareas,nearly66%ofthosewholackaccesstoelectricity
alsolackaccesstothecleandrinkingwater.Therefore,optimizationofwatersupply
andsanitationmeasurescanminimizethedemandforelectricity(IEA2020).
The physical, economic and environmental viability of future projects of elec-
tricity generation will need to consider the impact of water availability. Increased
water stress has material as well as economic impact on the cooling technolo-
gies deployed across China’s coal-fired power fleet. Moreover, in the same study
conducted by IEA, it was found that hydropower in the Africa will emphasize the
v
vi Preface
significance of policy measures on management of the water available to enhance
theresilienceofhydropower(IEA2020).
The reduced freshwater reserves can lead to a larger dependence on energy-
intensive sources of water supply like desalination, which is evident in case of
the Middle East where share of total final energy consumption for desalination is
predictedtoincreasefrom5%todaytoalmost15%by2040(Moniz2014).
The operation of some power plants and other energy production activities has
become constrained when an acute drought affected more than 30% of the United
States in 2012 due to the lack of adequate supply of water. Hurricane Sandy is
another example, when because of no power, vital water infrastructures failed to
function(Moniz2014).
‘Thewater-energynexus—theconceptreferstotherelationshipbetweenthewater
usedforenergyproductionincludingbothelectricityandsourcesoffuelsuchasoil
andnaturalgas,andtheenergyconsumedtoextract,purify,deliver,heat/cool,treat
anddisposeofwater(andwastewater)sometimesreferredtoastheenergyintensity
(EI)’(Spangetal.2014).Allformsofenergyproductionrequiresomeinputofwater
makingtherelationshipcomplicatedandanywaterinfrastructurerequiresenergyto
operate.
In India also the need to inculcate the concept of the water-energy nexus has
becomesignificantasthescarcityofwaterandenergyisintenseinthissubcontinent
duetothesizeofthepopulationandtheircapacitytousemoderntechnology.
ManagementofWaterandEnergyInterdependencies
inIndia
The unruly extraction of water and energy resources is one of the major reasons
why India is facing acute shortage of these resources. For example, overdrafting
of groundwater for irrigation in the state of Punjab has made 79% of the ground-
water wells ‘overexploited’ and ‘critical’ with extraction exceeding the supply as
perastudyconductedbyCentralGroundWaterBoardintheyearof2010(CGWB
2010).Punjabisalsocontendingwiththesignificancesofuncontrolledapplication
of chemical fertilizers and pesticides, water for irrigation and power subsidies, in
theformofdryingupofaquifers,degradedsoilquality,pollutedgroundwaterand
rivers.Cohesiveevaluationsassociatedwithanexusapproachcanbecomeimportant
toolsofnaturalresourcemanagementandpolicyframeworksrequiringtheneedto
understandtheseresourcesandtheiruse.
‘In India, groundwater irrigation has witnessed a recognizable increase since
1970sandwatertablesarediminishingrapidlyinmanypartsofthecountry’.Today,
over half of India’s geographical area has high to extremely high water stress.
‘However, tweaking the existing preference for rice and wheat using policy has
remainedelusive’.Asaresult,continuouspowersupplywasprovidedtothefarmers
resulting in the trip of the northern and eastern grids in 2012 and 2014 (Ganguly
Preface vii
et al. 2018). The state electricity boards require heavy subsidies to stay afloat and
thepoliticalwilltosubvertthemassiveagriculturepowersubsidyisgrowingonly
slowly.
Energy Policy of Indian Government has also given stress on the use of high-
efficiencyelectricaldevicesinagriculture,whichwillensurereductionofstresson
availableenergycontentoftheregion(Prajapati2018).
Inthisaspect,thepresentmonographwasinitiatedtoprovideaplatformtothe
researchers who are working in the field of water and energy nexus in India for
sustenanceofmankindandtheirlivelihoodinthefaceofclimatechangeandother
‘man-made’naturaldisasters.
Thesoftcomputationanddifferentdatasciencetechniquesareinevitablyusedto
solvethevariousproblemsofthenexusinbetweenwaterandenergyandtoselectthe
bestsolutionavailableortoevaluateanovelsystemwhichmayoptimizethenexus.
Thesolutionsdepictedinthismonographhaveutilizedvarioussoftcomputationand
datasciencetechniqueslikeArtificialIntelligence(AI),InternetofThings-basedReal
Time Modules, Multi-criteria Decision-Making (MCDM)-aided decision support
systems,andalsovariousoptimizationtechniqueswhichfollownatureareutilized
tofindthebestsolutionavailable.
Thatiswhy,Chapter“AReviewofMultipleCriteriaDecision-MakingMethods
inReferencetoWaterResourcesandClimateScienceApplications”introducedthe
differentMCDMtechniques,whicharenowusedtosolvevariouswaterresourcesand
climate-change-relatedproblemsinreal-timeorreal-lifescenario.Chapter“Develop-
mentofSpatialCognitiveModelforEstimationofUngaugedRunoffforMesoscale
Rivers” depicts the development of a new model, which can predict runoff for
ungauged catchment. This investigation applied the analytical hierarchy process
(AHP),whichisapopularMCDMtechniquetodevelopthemodel.
Chapter “Indicator Based Impact Analysis of Urbanization with Respect
to Evapo-Transpiration” proposed an indicator, which can represent the vulner-
ability of an urban city due to rapid urbanization with the help of poten-
tial evapotranspiration-based indicator. Here, also, the MCDM techniques are
used to develop the indicator and to automate the approximation process an
AI-based technique was utilized. This indicator can be applied universally for
any city of the world for evaluation of the impact of urbanization on local
climate.
In Chapter “Trend Analyses in Groundwater Levels of the Bikaner District,
Rajasthan”,thetrendingroundwaterlevelswasanalysedforanimportantregionof
the state of Rajasthan. In this aspect, many trend evaluation metrics were utilized,
andaspecifictrendwaspossibletobeproposedfortheselectedblocks.
Virtual Water can be defined as the water used as a raw material to produce an
iteminanindustry.ThisconceptwasproposedbyJohnAnthonyAllanintheyearof
1993(Allan1993).Itisanimportantindicatorwhereitmeasuresthelevelofimpact
on the available water due to the industry for which the Virtual Water Availability
isbeingconducted.Chapter“ClimateChangeImpactonVirtualWaterAvailability:
A Categorized Polynomial Neural Network Approach” tries to analyse the impact
of climate change on the Virtual Water Availability of the watershed. Instead of
viii Preface
specificindustries,thestudytriestoevaluatetheVWAofawatershed,whichhave
the cumulative impact of all the industries on the available water in the context of
impactsofclimaticabnormalities.
InChapter“DevelopmentofANNModelforSimulationoftheRunoffasAffected
byClimaticFactorsontheJamunaRiver,Assam,India”,ArtificialNeuralNetwork
(ANN)isusedforestimationofrunoffinthefaceofclimatechange.Thesmartuseof
thetechniqueforapproximationofrunoffforthewatershedofariverintheAssam
State of North East India depicts that the adaptiveness of the AI can be used for
water resource management with optimal accuracy. Chapter “Modelling of Refer-
ence Evapotranspiration for Semi-arid Climates Using Artificial Neural Network”
appliedANNforestimationofreferenceevapotranspiration(RET)ofariverunder
semi-arid climate and situated in the state of Telangana in southern part of India.
ThisinvestigationusedANNtooptimizeanexistingempiricalmodelavailablefor
predictionofRET.
Chapter“VerifyingStormWaterDrainageSystemCapacityforVadodaraAirport”
depicts the application of Storm Water Management Model for the evaluation of
preparednessofthepresentdrainagesystemfora1-and2-yearreturnperiodfloods
of a soon to be international airport in the city of Vadodara located in the state of
GujratinthewesternpartofIndia.
InChapter“OptimalTrade-OffBetweentheEnergy—EconomyofaHydropower
Plant for Better Management of the Renewable Energy Resources”, the optimal
trade-off between the energy production and financial liability of a hydropower
plant located in state of Tripura of North East India was identified with the help
of novel MCDM techniques and polynomial neural network-based mathematical
frameworks,which willbelater onembedded inreal-timemonitoringsystemsfor
monitoringtheperformanceaswellasfinancialliabilityofthepowerplant.Chapter
“Impact Analysis of Water, Energy, and Climatic Variables on Performance
ofSurfaceWaterTreatmentPlants”utilizesthesametechniquesbutappliedanovel
modified MCDM rule for evaluation of performance with respect to water, energy
andclimaticparametersofSurfaceWaterTreatmentPlant(SWTP).Chapter“Power
Allocation in an Educational Institute in India: A Fuzzy-GMDH Approach” uses
MCDMtechniquestoanalysetheenergyallocationmethodsofaneducationalinsti-
tute.Thisstudyalsousesamodifiedanalyticalhierarchyprocesswherefuzzyratings
wereappliedtofindthepairwisecomparisonratioofthealternatives.Thesamestudy
alsousedthepolynomialneuralnetworkforoptimizationoftheallocationprocess.
The last two chapters deal with system failure. Chapter “Application of New
Convergent Point Decision Making Method in Estimation of Vulnerability Index
forHydroPowerReservoirs”aimstoanalysetheperformanceofhydropowerreser-
voirfailureandsafetyfactorwithnewMCDMtechniqueswhereasChapter“Recog-
nitionofFatigueFailureinWaveEnergyConverterUsingStatisticalControlChart,
Multi-criteriaDecisionMakingToolsandPolynomialNeuralNetworkModel”tries
toevaluatethefatiguefailureofwaveenergyconvertersystems.Thisstudyalsoused
MCDMandPNNfortheirperformanceanalysis.
All these 13 chapters provide a solution to the problems faced in the water
and energy-based systems like watershed, reservoirs, SWTPs and wave energy
Preface ix
converters. Although none of the study encases the nexus between the two most
usednaturalresources(waterandenergy),thedataandinformationcollectedfrom
the studies can be easily used to create such interdependencies in a more optimal
andfeasiblemannersuchthatmaximumutilizationunderminimumliabilitycanbe
achieved.
Jirania,India Dr.MrinmoyMajumder
Surat,India Asst.Professor
Dr.GaneshD.Kale
Asst.Professor
References
Allan,J.A.,(1993).“FortunatelyThereareSubstitutesforWater,otherwiseourHydro-Political
FuturesWouldbeImpossible.”InPrioritiesforWaterResourcesAllocationandManagement
(pp.13–26).London:OverseasDevelopmentAdministration.
CGWB (Central Groundwater Board) (2010). State profile. Groundwater scenario for Punjab.
Availableathttp://cgwb.gov.in/gw_profiles/St_Punjab.htm.
Ganguly, A. R., Bhatia, U., Flynn, S. E., (2018). Critical infrastructures resilience: Policy and
engineeringprinciplesRoutledge.ISBN9781498758635.
IEA (International Energy Agency) (2020). Introduction to the water-energy nexus, IEA, Paris,
Retrievedfromhttps://www.iea.org/articles/introduction-to-the-water-energy-nexus.
Moniz,(2014).EnsuringtheResiliencyofOurFutureWaterandEnergySystems,Energy.gov,USA,
Retrieved from https://www.energy.gov/articles/ensuring-resiliency-our-future-water-and-ene
rgy-systems.
Prajapati,P.,(2018).Water-food-energynexusinIndia,India,Retrievedfromhttps://www.teriin.
org/article/water-food-energy-nexus-india.
Spang,E.S.,Moomaw,W.R.,Gallagher,K.S.,Kirshen,P.H.,Marks,D.H.2014,“Thewater
consumption of energy production: an international comparison.” Environmental Research
Letters,9(10),105002.
Acknowledgements
The editors would like to acknowledge the help of all the people involved in this
project and, more specifically, to the authors and reviewers that took part in the
reviewprocess.Withouttheirsupport,thisbookwouldnothavebecomeareality.
First,theeditorswouldliketothankeachoneoftheauthorsfortheircontributions.
Our sincere gratitude goes to the chapter’s authors who contributed their time and
expertisetothisbook.
Second, the editors wish to acknowledge the valuable contributions of the
reviewers regarding the improvement of quality, coherence and content presenta-
tion of chapters. Most of the authors also served as referees; we highly appreciate
theirdoubletask.
We will also like to thank our Director Prof. H. K. Sharma and Prof. S. R.
Gandhi,respectively,forprovidingthesupportandencouragementwerequiredfor
the completion of the book in the era of Covid 19 and during an extremely busy
academicschedule.
Wewouldalsoliketoacknowledgetheassistancewereceivedfromourpublishers
during the preparation of the book; from proof to press their cooperation was
exemplaryandunparallel.
In addition, we would also like to recognize with gratitude to the numerous
publishers,governmentagenciesandauthorswhohaveallowedourchapterauthors
tousetheirworksforbettermentoftheirsynthesis.
Althoughwehavetakenutmostcareand,withsincerity,havetriedtomakethis
pieceerrorfreestillfewdiscrepanciesmaycreepin.Wewillbehighlyindebtedto
ourreadersiftheykindlypointoutthosesuchthatinthenexteditionwecanmake
thebookreallyerrorfree.
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