GBP-NIHE MONITORING AND ASSESSMENT OF ENVIRONMENTAL PARAMETERS Editors Vasudha Agnihotri Sumit Rai Ashutosh Tiwari Sandipan Mukherjee Kireet Kumar Ranjan Joshi
Monitoring and Assessment of Environmental Parameters Edited by Vasudha Agnihotri, Sumit Rai, Ashutosh Tiwari, Sandipan Mukherjee, Kireet Kumar, Ranjan Joshi
ISBN: 978-93-5396-711-6 Published by G.B. Pant National Institute of Himalayan Environment Kosi-Katarmal, Almora, 263643, Uttarakhand, India www.gbpihed.gov.in / www.gbpihed.in/ Citation: Monitoring and Assessment of Environmental Parameters (2020) Eds. V. Agnihotri, S. Rai,A. Tiwari, S. Mukherjee, K. Kumar, R. Joshi, GBPNIHE,Almora. © GBPNIHE 2020 This book contains information obtained from authentic sources. Some chapters contain excerpted materials from Ph.D. theses also. All the sources used for writing the chapters by the authors are tried to be indicated. Reasonable e orts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the consequences of their use. No part of this document is to be published, copied or used otherwise without proper reference. Acknowledgement: Director of GBPNIHE, Kosi-Katarmal, Almora, Uttarakhand is acknowledged for providing technical and logistic support.
Foreword “The environment is where we all meet; where we all have a mutual interest; it is the one thing all of us share.” -Lady Bird Johnson Environmental constituents are essential for the existence of all the living beings on earth. These include water, air, soil, biodiversity, etc. which need to be monitored for better understanding and proper management by the respective authorities. Now, the world is facing increasing environmental concerns associated with water, air, and soil pollution as well as climate change,largely caused by various anthropogenic activities. Therefore, accurate assessment of the state of these constituents of the environment is essential to support actions towards improvement.In the recent years, considerable progress has taken place in the eld of environmental monitoring.This has resulted in development of more accurate, fast, convenient, and cost-e ective techniques using various technologies. The institute, for over last three decades, is engaged with the monitoring of di erent parameters in physical, biological, and social domains. Among others, water, soil, and air remained major focus. With the experience gained over the years, institute now imparting training to variousstakeholders, particularly the budding researchers, on various aspects of environmental monitoring. This book is the result of Green Skill Building Program “Monitoring of Environmental Factors and their interpretation” organized by Centre for Land and Water Resource Management (CLWRM), in the institute during 26th February to 14th March 2019. The chapters of this book containdetailed information on monitoring and assessment strategies in the eld of various environmental factors and mainly covering the hydrometeorological measurements, quantication and qualityassessment of water, basics of soil monitoring, plantsas indicators, assessment tools including RS-GIS, statistical tools,etc. I hope that the contents of this book will help the researchers, and academician, in better understanding the basics of various environmental parameters. They will be better equipped with the approaches of assessment and monitoring of these parameters. The team of editors deserve appreciation for putting their hard e orts to make this document owing and information rich. March 2020 R. S. Rawal. PhD Director GBP-NIHE iii
About the Book As most of the natural habitats are presently facing consistently increasing anthropogenic pressures alongside environmental changes on these habitats and their environmental constituents including water, air, soil, biodiversity, etc. Every habitat possesses its unique set of inter-relational physical, biological and social characteristics. Periodic monitoring and analytical assessment of the environmental constituents and their respective parameters lead to appropriate decision-making and specic interventions thereupon. This concept was turned into demonstrative actions by way of conducting a training “Monitoring of Environmental Factors and Their Interpretation” under Green Skill Building Programme during 26th February to 14th March 2019 by the Centre for Land and Water Resources Management (CLWRM) of G.B. Pant National Institute of Himalayan Environment at its Headquarters, Kosi-Katarmal,Almora, Uttarakhand. Moving forward, the demonstrative actions or trainings under this Green Skill Building Programme have been translated in form of this present book entitled “Monitoring and Assessment of Environmental Parameters” for providing the fundamental understanding on environmental monitoring and assessment strategies. The book helps in igniting the further insights in certain key monitoring and assessment elds, namely Hydrometeorology, Precipitation, Streamow, Water, Indicator Bacteria, Geospatial assessment tools, Soil functions and inter-relationship with water, etc. through some proven monitoring and assessment techniques. Thus, the present book is compilation of the key fundamental training sessions summarized in form of total 13 Chapters, and the approach used in development of each chapter is based on well-established scientic research and proven demonstrative interventions. The chapters of this book are restricted to monitoring and assessment of natural environmental parameters such as water, air, soil and plant signs and symptoms. The present book opens with Chapter 1 drawing attention on basic objectives and types of monitoring and assessment of environmental parameters, aiming at specic environmental problems. Emphasizing the Watershed Diagram, this also highlights the Environmental Management Laws in India. Chapter 2 brings the Hydrometeorological Data and Instruments into attention, using several tools and techniques viz., Barometer, Sunshine recorder, Digital sunshine recorder, Open pan evaporimeter, Lysimeter, weather satellites, etc. utilized in an Automatic Weather Station (AWS). Chapter 3 highlights another crucial environmental parameter Precipitation stating its basic theory, forms, characterization, measurement, recording, monitoring and analysis by means of various proven theories and methods. Chapter 4 is added herein on Streamow measurements by way erecting specic hydraulic structures to understand the hydrological cycles through various recorders, gauge and other proven methods and measurement techniques. Chapter 5 brings forth basic introduction about Groundwater on the background of Global Hydrological Cycle, studying its Flow and Distribution patterns along with Yield, Retention and Rejuvenation v
Techniques. Chapter 6 stresses on the need of Instrumentation while in-situ monitoring of water resources. Highlighting the Conceptual Framework, the chapter leads to continuous Real-Time (RT) Monitoring of diverse water resources towards suggesting some key water management solutions. It also provides basic understanding on advancements in Modern Monitoring Systems with a brief on a few monitoring tools and devices under best water conservation practices. Chapter 7 highlights Water Quality Assessment by way of monitoring 15 water quality variables/ core parameters through tested Sampling Techniques and then using some proven Treatment Procedures. Stressing on microbiological quality of drinking water, Chapter 8 lays emphasis on the role of Indicator Bacteria and draws attention on microbial contamination, indicating water-borne bacterial diseases and its causal organisms/ bacteria. Citing some Case Studies, it further suggests some water monitoring-cum-assessment methods and techniques for bacteriological analysis of water samples. Chapter 9 draws the underlying basic concepts and principles of Geo-Spatial Techniques using the Remote Sensing and Geological Information System (RS-GIS) to interpret the geographical as well as geological characteristics, data and other monitoring parameters on Spatial (springshed, watershed, sub-watershed, river basin) and Temporal (daily, sub-daily, weekly, monthly, annually) scales. For processing and rening the satellite digital data with geo-tags and referencing, signicance of some basic products like image, toposheets, digital database, etc. is also elaborated alongside classications, mosaicking multiple toposheets, datasets design, analytical techniques and virtual visualization towards pre-informed decision-making and action-oriented implementation with adoption of treatment, mitigation and adaptation measures. Chapter 10 guides the readers about Meteorology, particularly on instrumentation and methodology aspects of observational study. Introducing the basic structure of atmosphere, this informs the readers about the Schematics of Energy Participation while describing the Earth's Energy Budget and apprising further Standards, Denitions, Measurement techniques and instrumentations utilized in a weather observation facility for monitoring and assessing the parameters of air, wind, rainfall, etc. in the atmosphere. Chapter 11 covers fundamental concepts of the soil, integrating principles developed in cognate disciplines viz., biology, chemistry, mineralogy, physics, etc. for the cataloging, modelling and quantifying the soil diversity in the capacity as a physical supporter, plant nutrient medium, and moisture capacitor. Unravelling the hidden treasures present in the soil from the viewpoints of “Pedology”, i.e. as occurring in natural environment, on the one hand, and “Edaphology”, i.e. in relation to plant production, on the other hand, this apprises the readers of its formation, horizon, properties, textures, structures, organic matter along with their inter- relational e ects and impacts, particularly with water, which play crucial roles in providing food, fuel, feed and bre needs of the burgeoning populations alongside regulating the quality, decomposing organic waste, recycling nutrients, ltering pollutants, etc. Chapter 12 draws the attention of the readers on the soil nutrient deciencies, as reecting in crops and plants and thus a ecting the living organisms/ species and stresses on the importance of plant nutrition management. For obtaining maximum yield potential by way of understanding the macro- and micro- nutrients, their functions and further signicance in crops/ plants, this also describes the ways to identify the deciency and toxicity in crops/plants through visual symptoms as well as diagnosis. Assessing the nutritional status through soil health card, this lays emphasis on Micronutrient Deciency Maps available vi
with the State Agriculture Department for better informed decision-making on nutrient management and application. This will help Agro-Consultants, Agro-Producers, Rural youth, Small-scale Farmers, towards improved agro-farming, livelihood generation, food security and environment protection. Chapter 13 brings forth three important multivariate techniques, both exploratory and inferential in nature, for monitoring, assessing and analyzing the various datasets of environmental parameters, including cluster analysis, multiple regression analysis and factor analysis, supported with a respective Case Study and detailed analysis thereupon. This helps in determining strong insights into the datasets, discovering the legitimate patterns, visualizing further datasets, formulating the hypotheses and drawing applicable inferences. Overall, the book provides the basic underlying theory on each method or process and refers to other more detailed comprehensive textbooks when needed. The intended target readership is for junior and senior undergraduates majoring in Environmental Sciences and for graduate students who wish to have a comprehensive introduction about monitoring and assessment of the crucial environmental parameters. The focus of this book is on methods and strategies for environmental monitoring with lucid emphasis on eld methods. Laboratory methods are also presented in each chapter as needed to complement eld methodology or to illustrate a principle or an application. The book underlines the basic principle of the “Sustainable Coexistence” with all other Environmental Components, which has emerged over recent years as one among prominent priorities in the wake of increasing environmental and climate changes alongside challenges. The book also resonates the message underneath that to ensure “Sustainable Coexistence” in the earth's environment, timely monitoring and legitimate assessment of the environmental parameters lead towards e ective decision-making and long-term sustainability. The authors and contributors of the book hope that this will be useful for researchers, academicians, rural youths, small-scale farmers, agro-consultants, technicians, ecopreneurs, data scientists, quality managers, planners among others. We also wish that with the increasing years, increasing number of stakeholders and contributors will extend its gains and benets to larger sections of the society and environment all around us with the message “Sustainable Coexistence”! Authors and Contributors vii
AUTHORS Soham Adla Kritsnam Technologies Private Limited Kanpur, Uttar Pradesh. Vasudha Agnihotri, Ph.D. Centre for Land and Water Resource Management G.B. Pant National Institute of Himalayan Environment, Kosi - Katarmal, Almora, Uttarakhand. [email protected] Deepak Arya Kritsnam Technologies Private Limited Kanpur, Uttar Pradesh. Vaibhav E. Gosavi, M.Tech. Centre for Land and Water Resource Management G.B. Pant National Institute of Himalayan Environment, Kosi-Katarmal, Almora, Uttarakhand. [email protected] Paromita Ghosh, Ph.D. Centre for Socio-Economic Development G.B. Pant National Institute of Himalayan Environment, Kosi - Katarmal, Almora, Uttarakhand. paroghosh@redi mail.com K Sri Harsha, B.Tech. Kritsnam Technologies Private Limited Kanpur, Uttar Pradesh. [email protected] Kireet Kumar, M.Tech. Centre for Land and Water Resource Management G.B. Pant National Institute of Himalayan Environment, Kosi-Katarmal, Almora, Uttarakhand. [email protected] Sandipan Mukherjee, Ph.D. Centre for Land and Water Resource Management G.B. Pant National Institute of Himalayan Environment, Kosi-Katarmal, Almora, Uttarakhand. [email protected] Raman Nautiyal Division of Forestry Statistics, ICFRE, Dehradun, Uttarakhand. [email protected] Anita Pandey, Ph.D. Department of Biotechnology, Graphic Era (Deemed to be University), Bell Road, Clement Town, Dehradun 248002, Uttarakhand. [email protected] ix
H J Shiva Prasad, Ph.D. Department of Civil Engineering, G.B. Pant University of agriculture and Technology, Pantnagar, Uttarakhand. [email protected] Jyothi Prasad, Ph.D. Department of Civil Engineering G.B. Pant University of agriculture and Technology, Pantnagar, Uttarakhand. [email protected] Santosh Murlidhar Pingale, Ph.D. Hydrological Investigations Division, National Institute of Hydrology, Roorkee, Uttarakhand. [email protected] Sumit Rai, Ph.D. Centre for Environment Assessment and Climate Change G.B. Pant National Institute of Himalayan Environment, Kosi-Katarmal,Almora, Uttarakhand. [email protected] Anagani Prudhvi Sagar Kritsnam Technologies Private Limited, Kanpur, Uttar Pradesh. Soukhin Tarafdar, Ph.D. G.B. Pant National Institute of Himalayan Environment, Garhwal Regional Centre, Uttarakhand. [email protected] Ashutosh Tiwari, M.Tech. Centre for Land and Water Resource Management G.B. Pant National Institute of Himalayan Environment, Kosi- Katarmal,Almora, Uttarakhand. [email protected] Shivam Tripathi Department of Civil Engineering, Indian Institute of Technology Kanpur, Uttar Pradesh. Shivam Sharma Kritsnam Technologies Private Limited Kanpur, Uttar Pradesh. Shivi Saxena Kritsnam Technologies Private Limited Kanpur, Uttar Pradesh. x
REVIEWERS Kambale Janardan Bhima, Ph.D. Assistant Professor College of Agriculture, Bheemarayanagudi Shahapur, Dist: Yadgir- 585287, Karnataka, India Girish Chandra, Ph.D. Scientist-C Division of Forestry Statistics, Indian Council of Forestry Research and Education (An autonomous body under Ministry of Environment, Forest, and Climate Change, GoI), PO- New Forest, Dehradun-248006, Uttarakhand, India Dibakar Mahanta. Ph.D. Senior Scientist, ICAR-VPKAS, Hawalbag, Almora- 263601, Uttarakhand, India Vijay Singh Meena, Ph.D. Scientist -Crop Production Division, ICAR- VPKAS Hawalbag, Almora- 263601, Uttarakhand, India Debashis Mandal, Ph.D. Senior Scientist, HRD & SS div, ICAR-IISWC, 218, Kaulagarh Road, Dehradun- 248195, Uttarakhand, India Santosh Murlidhar Pingale, Ph.D. Scientist-C Hydrological Investigations Division, National Institute of Hydrology (NIH) Roorkee, Ministry of Jal Shakti, Department of Water Resources, River Development & Ganga Rejuvenation, Govt. of India, Jal Vigyan Bhawan, Roorkee - 247667, Uttarakhand, India Jyoti Patil, Ph.D. Scientist-D, National Institute of Hydrology (NIH) Roorkee, Ministry of Jal Shakti, Department of Water Resources, River Development & Ganga Rejuvenation, Govt. of India, Jal Vigyan Bhawan, Roorkee - 247667, Uttarakhand, India xi
D.S. Rawat, Ph.D. Scientist G (Retired Scientist) G. B. Pant National Institute of Environment Development (An autonomous body under Ministry of Environment, Forest, and Climate Change, GoI) Kosi-Katarmal, Almora-263643, Uttarakhand, India Indra S. Sen, Ph.D. Assistant Professor Department of Earth Sciences Western lab Extension, O ce 201 Indian Institute of Technology Kanpur, Kanpur - 208016, Uttar Pradesh, India Shivesh Sharma, Ph.D. Department of Biotechnology MNNIT Prayagraj - 211004, Uttar Pradesh, India P. C. Chandra, Ph.D. Former Regional Director, MER, Central Ground Water Board Ministry of Water Resources Lucknow Uttar Pradesh, India xii
Contents Page No. Foreword iii About the book v Authors ix Reviewers xi Figures xv Tables xviii Chapters Chapter1 Environmental Monitoring and Assessment 1-10 Chapter 2 Kireet Kumar and Vasudha A gnihotri Chapter 3 Chapter 4 Hydrometeorological data and instruments 11-29 Chapter 5 H J Shiva Prasad Chapter 6 Precipitation: Theory, Measurement and Analysis 30-50 Chapter 7 Vaibhav E. Gosavi Chapter 8 Chapter 9 Stream ow measurements 51-65 Jyothi Prasad Chapter 10 An introduction to groundwater 66-78 Chapter 11 Soukhin Tarafdar Chapter 12 Chapter 13 Instrumentation for in-situ monitoring of water resources 79-97 Shivam Sharma, Shivi Saxena, Soham A dla, Deepak A rya, K Sri Harsha, and Shivam Tripathi Water quality assessment 98-119 Vasudha A gnihotri Indicator bacteria in water monitoring 120-128 A nita Pandey Basics of Geospatial Techniques for Interpretation of Hydro- 129-145 Environmental Variables A shutosh Tiwari and Santosh Murlidhar Pingale Meteorology: Guide to instrumentation and methods of 146-159 observations Sandipan Mukherjee Fundamental Concepts of Soil 160-176 Sumit Rai Soil Nutrient Deciencies as reected in crops/plants 177-189 Paromita Ghosh Multivariate techniques for data analysis for 190-200 environmentalmonitoring Raman Nautiyal xiii
Figures Page No. Figure 1.1 : Staircase system showing the importance of science-based observation and data collection 2 Figure 1.2 : Major Environmental problems which needs to be monitored 3 Figure 1.3 : Types of environmental monitoring 3 Figure 1.4 : Global mean temperature depiction generated through simple monitoring 4 Figure 1.5 : Scale of observation and measurements for environmental monitoring 5 Figure 1.6 : (a) Direct and (b) indirect mode of environmental monitoring 6 Figure 1.7 : Watershed diagram 7 Figure 1.8 : Biotic and abiotic factors in the ecosystem 8 Figure 2.1 : Meteorological station 13 Figure 2.2 : A utomatic Weather Station (AW S) 13 Figure 2.3 : Stevenson Screen 16 Figure 2.4 : Temperature Measurement (Dry, Wet, Max, Min) 18 Figure 2.5 : Cup Counter A nemometer 19 Figure 2.6 : Wind Vane 20 Figure 2.7 : Sunshine Recorder 21 Figure 2.8 : Digital Solar Radiation Recorder 22 Figure 2.9 : Open Pan Evaporimeter 23 Figure 2.10 : Schematic diagram of Field Lysimeter 24 Figure 2.11 : Typical Weather Satellite 25 Figure 3.1 : (a) Normal dates of onset of Monsoon and (b) Normal dates of withdrawl of Mosoon 33 Figure 3.2 : South-west Monsoonn rainfall (in cm) over the India and neighbourhood 34 Figure 3.3 : Non-recording Rain gauge (Symons' Gauge) (a) Dimensions 36 and (b) Pictorial view of Rain guage with measuring ask 37 Figure 3.4 : (a) Exterior part (b) Interior part and (c) Recorder of tipping bucket type rain gauge 38 Figure 3.5 : Weighing-Bucket type Rain gauge 39 Figure 3.6 : Natural-Syphon type/oat-type rain gauge (a) Internal specication and details and (b) Pictorial view 39 Figure 3.7 : Recording from a Natural Syphon-type gauge 40 Figure 3.8 : Radar measurement of rainfall 41 Figure 3.9 : Measurement of snow depth on snow board 42 Figure 3.10 : Measurement of snowfall using snow tube 46 Figure 3.11 : Double mass curve 46 Figure 3.12 : Mass curve of rainfall 47 Figure 3.13 : Hyetograph of a storm 48 Figure 3.14 : Thiessen polygon method 49 Figure 3.15 : Isohyets of a storm 52 Figure 4.1 : Cross section of a river with gauge datum and water stage 52 Figure 4.2 : Sta gauge 53 Figure 4.3 : Float type recorder 54 Figure 4.4 : Bubbler gauge 54 Figure 4.5 : A contact type ultrasonic sensor 55 Figure 4.6 : Typical velocity prole 56 Figure 4.7 : Velocity distribution in channel cross section 56 Figure 4.8 : Measurement of ow velocity using oats xv
Figure 4.9 : Propeller-type current meter 57 Figure 4.10 : Cup-type current meter 57 Figure 4.11 : Procedure for a current meter measurement 58 Figure 4.12 : Concentration Prole of Sudden Injection method 60 Figure 4.13 : Concentration Prole of Constant Rate Injection method 61 Figure 4.14 : Flow over a Sharp-Crested Rectangular and V-Notch weirs 62 Figure 4.15 : Typical weir and ume 63 Figure 5.1 : Global hydrological Cycle: Total global uxes in thousands of km3/year 68 Figure 5.2 : Cross section showing di erent water uxes and vertical distribution of 69 unsaturated and saturated zone with sub-zones are depicted. 70 Figure 5.3 : Cross section showing unconned conned and perched aquifer 71 systems in soft rock geological medium. Figure 5.4 : Typical stream hydrograph showing proportions of Quick ow 71 and Baseow during a rainfall event. 72 Figure 5.5 : River hydrograph of two rivers showing clear di erence of hydrograph dominated by 73 74 quick ow(black line) whereas the hydrograph (blue line) showing a more stable ow regime. 75 Figure 5.6 : Pictorial depiction of porosity. Figure 5.7 : Di erent types of porosity in relation to rock texture 76 Figure 5.8 : The specic yield of unconned aquifer is signicantly higher compared to 82 the storage coe cient of a conned aquifer Figure 5.9 : Illustration of Darcy's experimental setup of ow through cylinder lled with sand 85 89 Figure 5.10 : Illustration of some of the common forms of springs in western Himalaya Figure 6.1 : Conceptual framework representing how continuous real-time monitoring of 90 diverse water resources can lead to sustainable water management solutions 91 Figure 6.2 : A Conceptual Diagram of the Instrument and the Cloud 93 Figure 6.3 : Examples of ultrasonic water-level sensor deployed in rivers and lakes - 94 (a) sensor with solar panels attached to it, and (b) sensor operating on a D size primary battery 99 Figure 6.4 : Examples of radar water-level sensor deployed on Ganga River in Rudraprayag - 100 (a) sensor operating on a D size primary battery, and 101 (b) sensor with solar panels attached to it 109 Figure 6.5 : Examples of ultrasonic pipe ow meters 110 Figure 6.6 : Example of oating buoy based continuous water quality monitoring instrument 110 111 Figure 6.7 : Example of soil moisture monitoring instrument deployed in kanpur farms 112 114 Figure 7.1 : Monitoring cycle 114 Figure 7.2 : Water residence time in inland freshwater bodies 125 Figure 7.3 : Water Sampling (a) grab; (b) In-situ measurements Figure 7.4 : Parameters monitored under the national programme for monitoring water quality Figure 7.5 : pH ranges for di erent types of water resources Figure 7.6 : pH electrode Figure 7.7 : Water quality parameters a ected due to temperature Figure 7.8 : (a) and (b) Multi-ion analyzers Figure 7.9 : (a) Flow diagram of turbidity meter; (b) Sechhi disk Figure 7.10 : Deposits on pipelines and taps due to hard water Figure 8.1 : A &B. The Jageshwar temple complex and the river Jataganga- a site that experiences a variety of anthropogenic activities; C&D. Enumeration techniques- MPN and MFT, respectively; E. E. coli colonies showing typical metallic sheen. xvi
Figure 9.1 : Electromagnetic waves 130 Figure 9.2 : Electromagnetic spectrum 131 Figure 9.3 : Components of remote sensing 133 Figure 9.4 : Interaction of EMR with Earth's Surface and A tmosphere 133 Figure 9.5 : Satellite imageries and its classication 139 Figure.9.6 : Raster V s. Vector 140 Figure.9.7 : Map projections 141 Figure 9.8 : Geo-referencing of the Toposheet 142 Figure.9.9 : Joining (Mosaicking) multiple toposheet 142 Figure.9.10 : Watershed delineation over SOI Toposheet 143 Figure.9.11 : Spatial analysis techniques & creation of a GIS database 144 Figure 10.1 : Temperature based vertical structure of atmosphere. 147 The vertical structure is linear up to 40 km and logarithmic above 40 km. 148 Figure 10.2 : The vertical structure of troposphere indicating di erent layers. 149 Figure 10.3 : Schematics of energy partition 151 Figure 10.4 : Schematics of radiative forcing of individual GHGs 153 Figure 10.5 : Left panel shows ordinary dry and wet bulb thermometers. 154 Right panel shows a Stevenson Screen that protects these thermometers from radiation. Figure 10.6 : Left panel shows electronic sensor for air temperature measurement. 155 Right panel shows a radiation screen within which the thermometer sensor is inserted. 156 Figure 10.7 : Left panel shows a combined cup anemometer with a wind vane. 157 Right panel shows a combined wind speed and direction sensor (Make is R.M. Young Company, USA ). Figure 10.8 : Left panel shows a 3-D sonic anemometer design from Campbell Sci, 162 165 USA . Right panel shows a 3-D anemometer design from Gill Instruments, UK. 167 Figure 10.9 : Left panel shows a tradition al rain gauge where as the right panel shows the electronic 168 181 structure of the same. 182 Figure 11.1 : Volume composition of a desirable surface soil 183 Figure 11.2 : Soil prole horizons. 183 Figure 11.3 : The USDA textural triangle 184 Figure 11.4 : Types of soil structure. 185 Figure 12.1 : Relationship between crop yield and nutrient concentration 185 Photo plate 12.1 : Deciency symptoms of nitrogen 186 Photo plate 12.2 : Deciency symptoms of phosphorus 193 Photo plate 12.3 : Deciency symptoms of potassium 200 Photo plate 12.4 : Deciency symptoms of magnesium Photo plate 12.5 : Deciency symptoms of (a): sulphur and (b) boron Photo plate 12.6 : Deciency symptoms of (a): iron and (b) zinc Photo plate 12.7 : Deciency symptoms of calcium Figure13.1 : Tree Diagram for 8 cases single Linkage Squared Euclidean distances. Figure 13.2 : Three-dimensional plot of factors expressing the dataset in three dimensions xvii
Tables Page No. Table 3.1 : Types of rainfall and corresponding rainfall intensity 31 Table 5.1 : Distribution of waterin Earth Reservoirs 67 Table 5.2 : Typical values of porosity of geological material. 73 Table 6.1 : Comparison of sensortechnologies forcontinuous monitoring of waterquantity 88 Table 6.2 : Comparison of sensortechnologies forcontinuous monitoring of waterquality 92 Table 7.1 : Sampling frequency fordi erent types of waterbodies 102 Table 7.2 : Recommended preservative treatment and maximum permissible storage time 103 forwaterquality variables 105 Table 7.3 : Classication of surface waterbased on usage Table 7.4 : Waterquality parameters and drinking waterstandards 106 Table 7.5 : Methods used forthe measurement of majorwaterquality parameters 117 Table 8.1 : Main water-borne bacterial diseases 122 Table 9.1 : Visible light spectrum 131 Table 9.2 : Infrared spectrum 132 Table 9.3 : Microwave remote sensing bands 134 Table 9.4 : Indigenous remote sensing products and theirtechnical specications 142 Table 9.5 : Projection parameters 168 Table 11.1 : Types of soil structure. 173 Table 11.2 : Soil drainage classes 179 Table 12.1 : Typical ranges of macronutrients concentrations in mature leaf tissues 179 Table 12.2 : Typical ranges of micronutrients concentrations in mature leaf tissues 180 Table 12.3 : Nutrient deciency symptoms 187 Table 12.4 : Nutrient A ntagonisms 192 Table 13.1 : Observed dummy value of pollutants 193 Table 13.2 : Distance Matrix afterrunning the algorithm 194 Table 13.3 : Representation of clusters with theirrespective membership 196 Table 13.4 : Performance of coe cients and S.E. in multivariate regression 196 Table 13.5 : Performance of coe cients and SE in Post multivariate regression 197 Table 13.6 : Factorloadings in FactorA nalysis with 3 factors 198 Table 13.7 : Output using Varimax noramalized rotation 199 Table 13.8 : The eigenvalues and % total variance explained by the factors xviii
1 ENVIRONMENTAL MONITORING Kireet Kumar and Vasudha Agnihotri Abstract Environmental monitoring is importantfor systemic generation of data for understanding the health of our environment. It generally involves systematic monitoring of environmental factors such as water, soil, air, plants, along with processes like hydrological, and meteorological processes. The representation of these monitoring results through statistical data analysis and remote sensing-geographic information system (RS- GIS) tools are becoming common now days. The government regulations are also becoming strict for maintaining the quality of environment so that we can live properly. The chapter is providing the brief introduction about the importance of environmental monitoringas a base for the upcoming chapters. Keywords: Environment, monitoring, law Introduction Number of natural cycles control the environmental processes occurring in the earth's atmosphere such as nitrogen cycle, water cycles etc. Their relationship with the geological processes, water resources, atmosphere and living organisms have been studied by the environmental scientists. A person who is not aware of the earth's processes can think that the atmosphere is separate than the earth surface but a person having the knowledge of these processes can understand the interrelativity of these processes. Environmental monitoring is the observation and study of the environment through which we can generate the information of the environmental processes. Figure 1.1 is showing the importance of observation and data collection for understanding any system. Kireet Kumar Centre for Land and Water Resource Management G.B. Pant National Institute of Himalayan Environment, Kosi-Katarmal, Almora, India. [email protected] Vasudha Agnihotri, Ph.D. Centre for Land and Water Resource Management G.B.Pant National Institute of Himalayan Environment, Kosi - Katarmal, Almora [email protected] Monitoring and A ssessment of Environmental Parameters Eds. V. A gnihotri, S. Rai, A . Tiwari, S. Mukherjee, K. Kumar, R. Joshi, GBPNIHE, A lmora, Uttarakhand, India ©GBPNIHE 2020 1
Environmental Monitoring Figure 1.1 : Staircase system showing the importance of science-based observation and data collection (Roots, 1997) Environmental monitoring can be dened as the systematic sampling of air, water, soil, and biota to observe and study the environment, as well as to derive knowledge from this process (Artiola et al., 2004; Wiersma, 2004). There are two main reasons due to which environmental monitoring is important. One is to establish baseline information which can show the current situation of ecosystem components and second is to detect changes in the environmental characteristics overtime (Hicks and Brydges 1994). Environmental monitoring is very broad and requires a multi-disciplinary scientic approach. Environmental scientists require skills in basic sciences such as chemistry, physics, biology, mathematics, statistics, and computer science. There fore, all science-based disciplines are involved in this Endeavour. The major objectives of environnemental monitoring are (Mitchell, 2002): 1. To establish environmental “baselines, trends, and cumulative e ects” 2. To test environmental modeling processes 3. To educate the public about environmental conditions 4. To inform policy design and decision-making 5. To ensure compliance with environmental regulations 6. To assess the e ects of anthropogenic inuences 7. To conduct an inventory of natural resources Various problems caused by human through anthropogenic activities has also increased the importance of continuous monitoring of environmental parameters, mainly for the factors which are causing problems (Figure 1.2). 2
Environmental Monitoring Global climate Air Biodiversity Habitat destruction change pollution depletion Habitat degradation Stratospheric Extinction ozone depletion Major Soil Outdoor and environmental related Overgrazing indoor pollutants and other Farmland loss and Acid deposition problems problems degradation Overshing Sediment load Water Waste Soil erosion Nutrient overload pollution production Soil salinization Toxic chemicals Soil water logging Microbial Water shortages contamination Groundwater depletion Oxygen deletion Pesticides Solid waste Oil spills Hazardous waste Excess heat Figure 1.2 : Major Environmental problems which needs to be monitored TYPES OF ECOLOGICALMONITORING Ecological monitoring programs fall into four broad categories (Brydges, 2004) as shown in Figure 1.3. Environmental monitoring Simple Survey Surrogate or Integrated monitoring monitoring Proxy monitoring monitoring Figure 1.3 : Types of environmental monitoring Simple monitoring Under this method, the values of a single variable at one geographical point over time are recorded. Global mean temperature variation measurement (Figure 1.4) and carbon di oxide measurements are the examples of the application of simple monitoring. Data from around the world are used to calculate the average global air temperature which is one of the keystone measurements in the global warming/climate change issue. 3
Environmental Monitoring Figure 1.4 : Global mean temperature depiction generated through simple monitoring Survey Monitoring In the cases where historical monitoring records are not available, monitoring is done using this method where a survey of current conditions over a geographical area is conducted. If the area under study is a ected by any environmental problem, then the monitoring through survey needs to be compared with the controlled conditions (i.e., nearby una ected areas). Surrogate or Proxy monitoring In the absence of actual measurements of the desired variable, surrogate or proxy monitoring of environmental parameters can also be conducted. In this approach, data are obtained frominformation “stored” in the environment that relates to the desired variable.This method is popular in monitoring of wastewater treatment along with the water, air and soil pollution (Edzwald et al., 1985; Pifer and Fairey, 2014), river bedload ux monitoring (Gray et al., 2010) etc. Integrated monitoring The simple, survey and surrogate monitoring can provide substantial information about the changing environment, still understanding the reason of these changes are also important. This can be achieved through integrated monitoring. This type of monitoring is based on four objectives: 1. To establishment of cause-and-e ect relationships 2. To derive scientically defensible pollution control or resource management programs 3. To measure the environmental response to the control measures 4. To provide early warnings of new problems 4
Environmental Monitoring The integrated monitoring sites includes long term (i.e., indenite) multidisciplinary monitoring, such as meteorology, precipitation chemistry, runo chemistry, and monitoring of biological factors etc. Scale of Observation At which scale, the environmental monitoring should be done is also very important for analysing spatial-temporal variation of environmental parameters (Figure 1.5). The advancement in technologies have made the measurement ranging from micro to global Atomic < 1 nm atoms, subatomic Ultra-micro – virus, molecules >1nm Bacteria >1µm Macro – animal, plant, fungi >1mm Field – agricultural eld, waste site >1 m Intermediate – watershed, river, lake >1 km Meso-continent, country, state >100 km Global >10000 km Instantaneous < 1 second Hourl >60 minutes Daily >24 hours Seasonal >4 Months Annual >1 year Generation-Lifetime 20 -100 years Geologic >10000 years Figure 1.5 : Scale of observation and measurements for environmental monitoring 5
Environmental Monitoring level very easy. So, on the one hand we can use subatomic particles as probe to measure atomic and molecular properties of solid, liquids and gases through which minute quantities of the substances can be measured which are present in the environment. On the other hand,space-based satellite sensors can scan and map the entire earth surface many times in a day. Data collection is important in environmental monitoring. It can either be direct or indirect. In the direct mode, monitoring is performed by the person by direct measurement of the parameter eg., temperature measurement at several locations along the length of a river or at di erent times of the year including baseline measurement and then monitoring the parameter systematically to determine changes (Figure 1.6 (a)), measurement of nitrate levels/ ammonia levels/ chloride levels as an indication of nutrient overload etc., while in case of indirect mode related parameters are the measure which can indirectly tell us about the conditions of environmental parameters eg., dissolved oxygen (DO), Biological oxygen demand (BOD), presence or absence of indicator species. Dissolved oxygen shows the suitability of water for drinking and aquatic life, BOD tells about the presence of microbes in water. The DO is used by aerobic bacteria to break down the organic matter in a specic volume of water. The greater the organic matter (sewage, agricultural run-o , fertilizer, etc.) the higher the BOD. If DO equals or exceeds the BOD, the system is considered healthy and if DO level is less than BOD, it is possible that there is not enough oxygen to sustain larger organisms like sh.The process of accumulating large amount of organic matter is called eutrophication. Through indicator species such as bees, buttery, we can analyze the status richness of biodiversity in any area (Figure 1.6 (b)). (a) (b) Figure 1.6 : (a) Direct and (b) indirect mode of environmental monitoring 6
Environmental Monitoring After the collection of datasets, their statistical analysis is also important. It helps environmental scientists to interpolate and extrapolate information by observing a few sample observations to an entire environment or population Some of the details on statistical data interpretation will be discussed in Chapter 13 of this book. Monitoring of the environmental parameters in water shed area, must be carried out in the form of ecosystem (Box 1.1) for understanding the factor a ecting ecological processes (Figure 1.7). Abiotic, biotic, climatic and edaphic factors are controlling di erent environmental parameters. Abiotic factors include non-living features of an ecosystem (i.e. the physical and chemical conditions) that a ect the community such as temperature, light intensity, air speed, water current, humidity, pH, dissolved oxygen, salinity, nitrate, phosphate and other plant nutrients. Biotic factors are the living features of an ecosystem that a ect the other members of the community such as plants for food and shelter, predators, prey, parasites and pathogens, decomposers, competitors, and pollinators (Figure 1.8). Figure 1.7 : Watershed diagram (Source: http://watersheddiscipleship.org/page/what-watershed) 7
Environmental Monitoring Box 1.1 Ecosystem:“A functioning natural unit with interacting biotic and abiotic components in a system whose boundaries are determined by the cycles and ux of energy, materials and organisms”It is valid to describe di erent ecosystems with di erent, overlapping sets of boundaries in the same geographic area (e.g. forest ecosystems, watershed ecosystems and wetland ecosystems). Watershed: “An area of land that drains water, sediment and dissolved materials to a common receiving body or outlet. The term is not restricted to surface water runo and includes interactions with subsurface water” Figure 1.8 : Biotic and abiotic factors in the ecosystem (Source: http://oydmiddle.typepad.com/howard/2012/08/) The climatic factors are elements of the climate (weather) that inuence the life and distribution of the organisms that live in an environment such as temperature, rainfall, humidity, wind, light intensity (including seasonal variations), day length etc. The edaphic factors are the physical, chemical, and biological characteristics of the soil that inuence the community such as soil type, soil pH, available (soil) water, air and mineral content, humus, soil texture and structure etc. Environmental Management Laws in India The need for protection and conservation of environment and sustainable use of natural resources is reected in the constitutional framework of India and in the international commitments of India. The Constitution under Part IVA (Art 51A-Fundamental Duties) casts a duty on every citizen of India to protect and improve the natural environment including forests, lakes, rivers, and wildlife, and to have compassion for living creatures. Further, the Constitution of India under Part IV (Art 48A-Directive Principles of State Policies) stipulates that the State shall endeavour to protect and improve the environment and to safeguard the forests and wildlife of the country. The true thrust for putting in force a well-developed framework came only after the UN Conference on the Human Environment (Stockholm, 1972). After the Stockholm Conference, the National Council for Environmental Policy and Planning was set up in 1972 within the Department of Science and Technology to establish a regulatory body to 8
Environmental Monitoring look after the environment-related issues. This Council later evolved into a full-edged Ministry of Environment and Forests (MoEF). MoEF (currently Ministry of Environment, Forest and Climate Change (MoEFCC)) was established in 1985, which today is the apex administrative body in the country for regulating and ensuring environmental protection and lays down the legal and regulatory framework for the same. Since the 1970s, several environment legislations have been put in place. The MoEFCC and the pollution control boards (\"CPCB\", ie, Central Pollution Control Board and \"SPCBs\", ie, State Pollution Control Boards) together form the regulatory and administrative core of the sector.Central Pollution Control Board (CPCB), established under Water (Prevention & Control of Pollution) Act 1974 passed by Indian Parliament, is responsible for environmentalquality monitoring in India. Some of the important legislations for environment protection are National Green Tribunal Act, 2010; Air (Prevention and Control of Pollution) Act, 1981; Water (Prevention and Control of Pollution) Act, 1974; Environment Protection Act, 1986; Hazardous Waste Management Regulations; Wildlife Protection Act, 1972; Forest Conservation Act, 1980; The Biological Diversity Act, 2002 etc(Vibhav 2016) and there are new regulations coming with the technologies and changing lifestyle of the people. Purpose of the Textbook This textbook is composed of chapters that cover monitoring and assessment of environmental parameters including meteorological processes and instrumentation, surface and ground water quantity and quality assessment, edaphic factors such as soil, and its relation with plants, statistical interpretation remote sensing and GIS information and other related areas. The approach used in the development of each chapter is scientic and objective. It presents the facts based on well-established and accepted scientic principles, and also gives the reader basic underlying theory on each method or process and refers the reader to other more detailed comprehensive textbooks when needed. The intended target audience is for junior and senior undergraduates majoring in Environmental Sciences and for graduate students who wish to have a comprehensive introductioninto monitoring and characterizing the environment.The focus of this textbook is on methods and strategiesfor environmental monitoring with emphasis on eld based methods. Laboratory methods are also presented ineach chapter as needed to complement eld methodology or to illustrate a principle or an application.The chapters of this book are restricted to monitoring of natural environment parameters such as water, air, soil and plant symptoms. References Artiola JF, Pepper IL, Brusseau M (Eds.) (2004). Environnemental Monitoring and Characterization. Burlington, MA: ElsevierAcademic Press. Brydges T (2004). Basic Concepts and Applications of Environmental Monitoring.in Environmental monitoring. Wiersma G BEd., © CRC Press, 83-110. EdzwaldJames K, Becker William C, WattierKevin L (1985). Surrogate Parameters for Monitoring Organic Matter and THM Precursors. Journal AWWA Research and 9
Environmental Monitoring Technology, 77 (4), 122-132. Gray JR, Laronne JB, Marr JDG (2010). Bedload-surrogate monitoring technologies: U.S. Geological Survey Scientic Investigations Report 2010–5091, 37 http://pubs.usgs.gov/sir /2010/5091 Hicks BB and Brydges TG (1994). A strategy for integrated monitoring. Environ. Manage. 18(I), 1–12. Mitchell B (2002). Resource and Environmental Management (2nd ed.). Harlow: Pearson Pifer Ashley D, Fairey Julian L (2014). Suitability of Organic Matter Surrogates to Predict Trihalomethane Formation in Drinking Water Sources. Environmental Engineering Science, 31 (3), 117-126. Roots EF (1997). Inclusion of di erent knowledge systems in research. In: Terra Borealis. Traditional and Western Scientic Environmental Knowledge. Workshop Proceedings, Northwest River, Labrador 10 & 11 Sept. 1997. No. 1. Manseau M. (ed), Institute for Environmental Monitoring and Research, P.O. Box 1859, Station B Happy Valley–Goose Bay Labrador, Newfoundland,AOP E10. Terra Borealis, 1,42–49, 1998. Bruns D A and Wiersma G B (2004). Conceptual basis of environmental monitoring systems: A geospatial perspective, in Environmental Monitoring, Wiersma GB (Ed.)© CRC Press. 1-36. VibhawNawneet, 2016. Environmental Law–An Introduction. Lexis Nexis; First edition. 10
2 HYDROMETEOROLOGICAL DATA AND INSTRUMENTS H J Shiva Prasad Abstract Various hydrometeorological parameters to be observed, types of data used in hydrological analysis and the related instruments are briey explained in this chapter. The detailed information on the hydro-meteorological variables and available methods to retrieve them. In addition, it also provides information on how to primary validate and correct the elaborated collected data. This chapter has been prepared based on detailed review of the scholarly articles, technical reports, project reports, BIS codes and other practice manuals. Key Words: Hydro meteorological measurements, Meteorological data Introduction Hydrology forms an integral part of water resources development. Hydrological estimates are based on hydrometeorological data. Hence proper collection and processing of data becomes prerequisite to any hydrological analysis on which the resources development strategies are based. This chapter covers various types of data used in hydrological analysis. The chapter also covers measurement of various climatological data, analysis and typical possible measurement errors, corrections. Some of the hydrological instruments to measure precipitation like Rain gauge, Snow gauge etc including their data analysis, presentation is already dealt in precipitation chapter. H J Shiva Prasad, Ph.D. Department of Civil Engineering, G B Pant University of agriculture and Technology, Pantnagar [email protected] Monitoring and A ssessment of Environmental Parameters Eds. V. A gnihotri, S. Rai, A . Tiwari, S. Mukherjee, K. Kumar, R. Joshi, GBPNIHE, A lmora, Uttarakhand, India ©GBPNIHE 2020 11
Hydrometeorological Data and Instruments Hydro-Meteorological Data Various hydrometeorological data can be classied into three major categories as Space-oriented data Space-oriented data comprise all the information related to physical characteristics of catchments, rivers, lakes, and reservoirs. They also include the characteristics of observational stations and data series and various attributes associated with them. Time oriented data Time-oriented data comprise all the hydro-meteorological, quality and quantity data for which observations are periodically made in time at various observational stations. Time- oriented data can be equidistant, cyclic, or non-equidistant in nature according to whether the observations are made at intervals which are equal, unequal but at dened intervals, or at unequal intervals. Most surface water data are equidistant and cyclic. Relation oriented data Relation-oriented data comprise information about the relationships established between two or more variables. Stage-discharge data and the calibration ratings of various instruments can also be considered under this category of relation-oriented data. Abrief description of each type is presented in following section: Space Oriented Data Space oriented data comprise the following Ÿ Catchment data: physical and morphological characteristics Ÿ River data: cross-sections, prole, bed characteristics Ÿ Lake/reservoir data: elevation-area Time-oriented data Time oriented data may be classied as (i) meteorological data (Figure 2.1 and 2.2), (ii) hydrological data and (iii) water quality data. The details are given in following sections. Meteorological data The following meteorological and climatic variables are of importance. (i) Precipitation Ÿ Rainfall Ÿ Snowfall 12
Hydrometeorological Data and Instruments (ii) Evaporation (iii) Temperature Ÿ Minimum temperature Ÿ Maximum temperature Ÿ Dry bulb temperature Ÿ Wet bulb temperature Figure 2.1 : Meteorological station Figure 2.2 : A utomatic Weather Station (AW S) 13
Hydrometeorological Data and Instruments (iv) Atmospheric pressure (v) Atmospheric humidity (vi) Wind speed and direction (vii) Sunshine (viii) Derived meteorological variables such as relative humidity, dew point, lake evaporation and evapotranspiration etc. Hydrological data Records of time series of level (stage) and ow in surface water bodies constitute the bulk of hydrological data. Water Quality data The following water quality data are of importance (i) Organic matter (ii) Dissolved oxygen (iii) Major and minor ions (iv) Toxic metals and organic compounds (v) Nutrients (vi) Biological properties Relation oriented data Any kind of relationship between two or more variables is classied as relation-oriented data. The relationship can be of any mathematical form, which is the result of regression or a calibration exercise. The variables themselves may form a time series but it is their relationship rather than their occurrence in time, which is the principal focus of the data and their storage and management. Relation-oriented data include the following: (i) Flow data - Stage discharge data - Stage discharge rating parameters (ii) Sediment data - Discharge sediment concentration/load data - Discharge concentration/load rating parameters 14
Hydrometeorological Data and Instruments Sediment may be divided into two types of material: (i) Bed material forming the bed or transported as bed and as suspended load and (ii) Wash load material, only transported as suspended load The information about sediment size and the sediment concentration for the transported load, bed load and suspended load should form the part of sediment data bases. Climatic Data Measurement and Related Errors Measurement and typical measurement errors of following climatological/ meteorological parameters are explained. i. Temperature ii. Humidity iii. Wind speed iv. Atmospheric pressure v. Sunshine duration vi. Evaporation Temperature (a) Measurement Temperature is periodically observed (once or twice daily) using a set of four thermometers, located in a Stevenson screen(Figure 2.3), which from its construction and installation provides a standard condition of ventilation and shade. The screen should face towards north. The four thermometers are: Ÿ Dry bulb thermometer - measuring ambient air temperature Ÿ Wet bulb thermometer - which provides a basis for calculating relative humidity Ÿ Maximum thermometer - to indicate the highest temperature reached since the last setting Ÿ Minimum thermometer - to indicate the lowest temperature reached since the last setting Graduations are etched on the glass stem of the thermometer. In the case of the dry bulb, wet bulb and maximum thermometers, observations are of the position of the end of the mercury column but in the case of the minimum thermometer, the reading is taken of the position of the end of the dumb-bell shaped index farthest from the bulb. Each thermometer has a calibration card, which shows the di erence between the true temperature and the 15
Hydrometeorological Data and Instruments temperature registered by the thermometer. Corrections for a given temperature are applied to each observation. When the maximum and minimum thermometers have been read, they are reset using a standard procedure. Figure.2.3 : Stevenson Screen Temperature is also measured continuously using a thermograph in which changes in temperature are recorded using a bi-metallic strip. The temperature is registered on a chart on a clock-driven revolving drum and the measurement (chart) period may be either one day or one week. The observer extracts temperatures at a selected interval from the chart. The manually observed reading on the dry bulb thermometer is measured and recorded at the beginning and end of the chart period and if these di er from the chart value, a correction is applied to the chart readings at the selected interval (IS:5901 – 1970 / 2008). (b) Measurement errors Ÿ Observer error in reading the thermometer, often error of 1°C (di cult to detect) but sometimes 50C or 10°C. Such errors are made common in thermometers with faint graduation etchings. Ÿ Observer error in registering the thermometer reading 16
Hydrometeorological Data and Instruments Ÿ Observer reading meniscus level in minimum thermometer rather than index Ÿ Thermometer fault - breaks in the mercury thread of the dry, wet or maximum thermometer Ÿ Thermometer fault - failure of constriction of the maximum thermometer Ÿ Thermometer fault - break in the spirit column of minimum thermometer or spirit lodged at the top or bubble in the bulb Ÿ Thermograph out of calibration and no correction made. Ÿ Thermometer faults will result in individual or persistent systematic errors in temperature. (c) Error detection Many of the above faults would have been identied by the eld supervisor or at data entry but others may be identied by setting up appropriate maximum minimum and warning limits for the station in question. These may be altered seasonally. For example, summer maximum temperature can be expected not to exceed 50°C while winter maximum temperature should not exceed 33°C. Other checks may include: Ÿ Dry bulb temperature should be greater than or (rarely) equal to the wet bulb temperature. Ÿ Maximum temperature should be greater than minimum temperature. Ÿ Maximum temperature measured using the maximum thermometer should be greater than or equal to the maximum temperature recorded by the dry bulb during the interval, including the time of maximum observation. The value of the maximum will be set to the observed maximum on the dry bulb if this is greater. Ÿ Minimum temperature should be less than or equal to the minimum temperature recorded by the minimum thermometer during the interval, including the time of observation of the minimum thermometer. The value of the minimum will be set to the observed minimum on the dry bulb if this is lower. Ÿ Thermograph readings at time of putting on the taking o should agree with the manually observed readings. Humidity (a) Measurement Wet and dry bulb thermometers (Figure 2.4) used for temperature assessment also used for calculating various measures of humidity. The wet bulb is covered with a clean muslin sleeve, tied round and bulb by a cotton wick which is then led to a water container, by which the wick and muslin are kept constantly moist. 17
Hydrometeorological Data and Instruments The observer calculates the relative humidity from the dry bulb and wet bulb temperatures using a set of tables. Relative humidity may also be measured continuously by means of hygrograph in which the sensor is human/horsehair whose length varies with relative humidity. The humidity is registered on a chart on a clock-driven revolving drum and the measurement (chart) period may be either one day or one week. The observer extracts humidity at a selected interval from the chart. A manually computed reading from dry and wet bulb thermometers is recorded at the beginning and end of the chart period and if these di er from the chart value, a correction is applied to the chart readings at the selected interval. Fig.2.4 : Temperature Measurement (Dry, Wet, Max, Min) (b) Typical measurement errors Measurement errors using dry and wet bulb thermometers in the assessment of humidity are the same as those for temperature. In addition, an error will occur if the muslin and wick of the wet bulb are not adequately saturated. Similarly, there will be an error if the muslin becomes dirty or covered by grease. These defects will tend to give too high a reading of wet bulb temperature and consequently too high a reading of relative humidity. Errors in the hygrograph may also result from poor calibration or the failure to correct for manually observed values at the beginning and end of the chart period. (c) Error detection Errors may be detected by setting up upper and lower warning limits appropriate to the station and season. The maximum is set at 100%. Graphic inspection of the daily series can be used to identify any anomalous values. 18
Hydrometeorological Data and Instruments The observer calculated values of relative humidity might be compared with those calculated by the computer. However, in view of the fact that the calculation can be done very simply in the o ce there seems little point in continuing the eld calculation except in those cases where it is used to calibrate the hygrograph. Accompanying eld notes should be inspected for observations by the supervisor of errors in the thermometers or of a dry or dirty muslin. Hygrograph records can be inspected for departures of starting and nishing values measured by manual methods. Wind speed and direction (a) Measurement Wind speed is measured using an anemometer, usually a cup counter anemometer (Figure 2.5). The rate of rotation of the anemometer is translated by a gear arrangement to read accumulated wind total (km) on a counter. By observing the counter reading at the beginning and end of a period, the wind run over the period can be determined and the average speed over the interval can be determined by dividing by the time interval. Standard Indian practice is to measure the wind speed over a three-minute period as representing an e ectively instantaneous wind speed at the time of observation. Daily wind run or wind speed is calculated from counter readings on successive days at the principal observation times (IS:5912 – 1970). Wind direction is commonly measured but is not used in the calculation of evapotranspiration and is therefore only ofmarginal use in hydrology. It is observed using a wind vane(Figure 2.6) and reported as 16 points ofthe compass either as a numerical gure or an alpha character (IS:5799 – 1970/2007). (b) Typical measurement errors Errors in wind speed might arise as the result of observer errors of the counter total, or arithmetic errors in the calculation of wind run or average wind speed. Instrumental errors might arise from poor maintenance or damage to the spindle, which might thus result in reduced revolutions for given wind speed. Figure.2.5 : Cup Counter A nemometer 19
Hydrometeorological Data and Instruments (c) Error detection Because of extreme variability in wind speed in space and time, it is di cult to set up convincing rules to detect suspect values. Nevertheless, simple checks are as follows: Ÿ Wind speeds should be zero where the direction is reported as '0' (calm). Ÿ Wind speeds cannot exceed 5 km/h when the wind speed is reported as variable. Ÿ Wind speeds more than 200km per hour should be considered suspect and will result in a warning ag. Atmospheric pressure (a) Measurement Atmospheric pressure is usually measured using a mercury barometer where the weight of the mercury column represents the atmospheric pressure. Commonly the Kew pattern barometer is used in India. It is read using a Vernier scale. Corrections are made for index error and for temperature (reducing to a standard temperature of 0oC using a set of tables. It is also reduced to mean sea level pressure. A barograph is also used for the continuous measurement of pressure. It consists of an aneroid sensor, which expands, and contracts with changes in pressure. These are registered on a clock-driven drum chart. Values of pressure may be extracted at hourly or other intervals from the chart and it is calibrated and set up to correspond with the reading of more accurate mercury barometer (IS:5945 – 1970). Figure.2.6 : Wind Vane 20
Hydrometeorological Data and Instruments (b) Typical measurement errors Observer errors may result from incorrect observation, incorrect registration or in the application of corrections for temperature or reduction to sea level. Observation problems can result from the use of the Vernier scale. Instrumental errors result from the entry of air into the space above the mercury and mechanical defects in the Vernier head. (c) Error detection Primary validation is mainly through the setting up of upper and lower warning and maximum and minimum limits. Values outside the maximum and minimum limits are rejected; values outside the warning limits are agged. Sunshine (a) Measurement The only instrument in common use in India for sunshine measurement is the Campbell Stokes sunshine recorder (Figure 2.7). This consists of a glass sphere mounted on a section of a spherical bowl. The sphere focuses the sun's rays on a card graduated in hours, held in the grooves of the bowl, which burns the card linearly through the day when the sun is shining. The card is changed daily after sunset. Hence the sunshine recorder uses the movement of the sun instead of a clock to form the time basis of the record. Di erent grooves in the bowl must be used in winter summer and the equinoxes, taking di erent card types. The total length of the bum in each hour gives an Figure.2.7 : Sunshine Recorder hourly sunshine duration (IS:7243 – 1974/2007). (b) Typical measurement errors The instrument is very simple in principle and the use of the sun rather than a clock as a time base avoids timing errors. Potential errors may arise from the use of the wrong chart which may result in the burn reaching the edge of the chart, beyond which it is not registered. Possible errors may result from extraction of information from the chart by the observer. 21
Hydrometeorological Data and Instruments (c) Error detection Error detection checks may include Ÿ Values of hourly sunshine greater than 1.0 or less than 0.0 may not be permitted. Ÿ Sunshine records before 0500 and after 1900 are rejected and hence daily totals greater than 14.0 hours are rejected. Daily warning limits may be set seasonally within SWDES based on the maximum possible sunshine for the location and time of year. Digital Solar Radiation Recorder (Pyranometer) It is an instrument for measuring solar radiation received from a whole hemisphere (Figure 2.8). It is suitable for measuring global sun plus sky radiation. The Pyranometer Sensor measures global solar radiation (sun plus sky) for a spectral response graph. This instrument is used extensively in meteorological studies, passive solar system analysis, irrigation scheduling, hydrologic studies and many other environmental studies Pan evaporation (a) Measurement Figure2.8 : Digital Solar Radiation Recorder The standard measurement in India is made using the Class A pan evaporimeter (Figure 2.9). It is a circular pan 1.22 m in diameter and 0.255 m deep. It rests on a white painted wooden stand. The pan is covered by a wire mesh to avoid loss of water due to birds and animals. The inner base of the pan is painted white. A stilling well is situated in the pan within which there is a pointer gauge. Measurement must take account not only of evaporation losses but also gains due to rainfall; the rain gauge nearby is used to assess the depth of rain falling in the pan. (IS:5973 – 1998) On days without rain at daily (or twice-daily) reading, water is poured into the pan using a graduated brass cylinder to bring the level up precisely to the top of the pointer gauge. The volume of water added is recorded and represents a depth of evaporation. On days with rain since the last observation the rainfall may exceed evaporation and water must be removed from the pan to bring it to the hook level. The adjacent rain gauge is used to assess the rainfall inow. 22
Hydrometeorological Data and Instruments Figure 2.9 : Open Pan Evaporimeter On days with forecast heavy rainfall, a measured amount of water may be removed from the pan in advance of the rainfall occurrence (to avoid pan overow). (b) Typical measurement errors Ÿ Observer errors - the observer over - or underlls the pan - such values will be compensated for the following day Ÿ Leakage: this is the most serious problem and it occurs usually at the joint between the base and side wall. Small leaks are often di cult to detect in the eld but may have a signicant systematic e ect on measured evaporation totals. Ÿ Animals may gain access to the pan, especially if the wire mesh is damaged Ÿ Algae and dirt in the water will reduce the measured rate of evaporation Ÿ Errors arise in periods of high rainfall when the depth caught by the rain gauge is di erent in depth from the depth caught in the pan as a result of splash or wind eddies round the gauges. (c) Error detection Warning and maximum limits may again be allocated to screen spurious values arising from observer error, leakage, animal interference or dirty water. Where leakage has been identied and is recorded in the eld record book, the records for a period preceding the discovery should be inspected and agged as suspect. 23
Hydrometeorological Data and Instruments The occurrence of heavy rain reduces the accuracy of measurement but may also reduce the rate of evaporation. Excessively high or excessively low values during days with heavy rain with reference to the rainfall time series will be agged as suspect and should be amended on further validation. Lysimeter It is a device to measure the quantity or rate of downward water movement through a block of soil usually undisturbed, or to collect such percolated water for analysis as to quality (Figure 2.10). Lysimeters account for change in water storagei.e. measure actual evapotranspiration. Figure 2.10 : Schematic diagram of Field Lysimeter Weather Satellites Weather satellite is a type of satellite that is primarily used to monitor the weather and climate of the Earth (Figure 2.11). These meteorological satellites, however, see more than clouds and cloud systems. City lights, res, e ects of pollution, auroras, sand and dust storms, snow cover, ice mapping, boundaries of ocean currents, energy ows, etc., are other types of environmental information collected using weather satellites. Visible-light images from weather satellites during local daylight hours are easy to interpret even by the average person; clouds, cloud systems such as fronts and tropical storms, lakes, forests, mountains, snow ice, res, and pollution such as smoke, smog, dust and haze are readily apparent. Even wind can be determined by cloud patterns, alignments, and movement from successive photoseg TRMM-NASASatellite etc. 24
Hydrometeorological Data and Instruments Figure 2.11 : Typical Weather Satellite Validation of Climatic Data (Goel N K, 2003, S Prasad H J, 2017) Validation is mainly concerned with spatial comparisons between neighbouring stations to identify anomalies in recording at the station. Methods of validation include the following (i) Multiple station validation Ÿ Comparison plots of stations Ÿ Residual series Ÿ Regression analysis Ÿ Double mass curve Ÿ Test of spatial homogeneity (nearest neighbour analysis) (ii) Single series tests of homogeneity Ÿ Trend analysis (time series plot) Ÿ Residual mass curves Ÿ Student's 't' test of di erence of means Multiple stations validation Comparison plots The simplest and often the most helpful means of identifying anomalies between stations is in the plotting of comparative time series. This should generally be carried out rst before other tests. For climate variables the series will usually be displayed as line graphs of a variable at two or more stations where measurements have been taken at the same time 25
Hydrometeorological Data and Instruments interval, such as 0830 dry bulb temperature, atmospheric pressure, or daily pan evaporation. In examining current data, the plot should include the time series of at least the previous month to ensure that there are no discontinuities between one batch of data received from the station and the next - a possible indication that the wrong data have been allocated to that station. For climatic variables, which have strong spatial correlation, such as temperature, the series will generally run along closely parallel, with the mean separation representing some location factor such as altitude. Abrupt or progressive straying from this pattern will be evident from the comparative plot, which would not necessarily have been perceived at primary validation from the inspection of the single station. An example might be the use of a faulty thermometer, in which there might be an abrupt change in the plot in relation to other stations. An evaporation pan a ected by leakage may show a progressive shift as the leak develops. This would permit the data processor to delimit the period over which suspect values should be corrected. Comparison of series may also permit the acceptance of values which were suspected in primary validation because they fell outside the warning range. Where two or more stations display the same behaviour there is strong evidence to suggest that the values are correct. An example might be the occurrence of an anomalous atmospheric pressure in the vicinity of a tropical cyclone. Comparison plots provide a simple means of identifying anomalies but not of correcting them. This may be done through regression analysis, spatial homogeneity testing (nearest neighbour analysis) or double mass analysis. Residual series An alternative method of displaying comparative time series is to plot the di erences. This procedure is often applied to river ows along a channel to detect anomalies in the water balance, but it may equally be applied to climate variable to detect anomalies and to ag suspect values or sequences. The equation is simply: Yi = X1,i – X2,i Where i is the time stamp, X is the time series of river ow and Y is the anomaly providing residuals. Regression analysis Regression analysis is a very commonly used statistical method. In the case of climatic variables where individual or short sequences of anomalous values are present in a spatially conservative series, a simple linear relationship with a 26
Hydrometeorological Data and Instruments neighbouring station may well provide a su cient basis for interpolation. In a plot of the relationship, the suspect values will generally show up as outliers but, in contrast to the comparison plots, the graphical relationship provides no indication of the time sequencing of the suspect values and whether the outliers were scattered or contained in one block. The relationship should be derived for a period within the same season as the suspect values. (The relationship may change between seasons). The suspect values previously identied should be removed before deriving the relationship, which may then be applied to compute corrected values to replace the suspect ones. Double mass curves Double mass curve analysis, cumulative plots of variable under consideration at one station and surrounding stations may also be used to show trends or in homogeneities between climate stations but it is usually used with longer, aggregated series. However, in the case of a leaking evaporation pan, described above, the display of a mass curve of daily values for a period commencing some time before leakage commenced, the anomaly will show up as a curvature in the mass curve plot. This procedure may only be used to correct or replace suspect values where there has been a systematic but constant shift in the variable at the station in question, i.e., where the plot shows two straight lines separated by a break of slope. In this case the correction factor is the ratio of the slope of the adjusted mass curve to the slope of the unadjusted mass curve. Where there has been progressive departure from previous behavior, the slope is not constant as in the case of the leaking evaporation pan, and the method should not be used. Spatial homogeneity (nearest neighbor analysis) This procedure is most used for rainfall but can be used for other variables also. Its advantage for rainfall in comparison to climate is that there are generally more rainfall stations in the vicinity of the target station than there are climate stations. The advantage for some climate variables is that there is less spatial variability and the area over which comparison is permitted may be increased. Although there is strong spatial correlation, there may be systematic di erence due to, for example, altitude for temperature. In these cases normalized rather than actual values should be used. The following methods are generally used for checking spatial homogeneity Ÿ Normal ratio method Ÿ Distance power method 27
Hydrometeorological Data and Instruments Single series tests of homogeneity Single series testing for homogeneity will normally only be used with long data sets. Series may be inspected graphically for evidence of trend and this may often be a starting point. However, statistical hypothesis testing can be more discriminative in distinguishing between expected variation in a random series and real trend or more abrupt changes in the characteristics of the series with time. Trend analysis (time series plot) A series can be considered homogeneous if there is no signicant linear or curvilinear trend in the time series of the climatic element. The presence of trend in the time series can be examined by graphical display and/or by using simple statistical tests. The data are plotted on a linear or semi-logarithmic scale with the climatic variable on the Y-axis and time on the X-axis. The presence or absence of trend may be seen by examination of the time series plot. Mathematically one may t a linear regression and test the regression coe cients for statistical signicance (Subramanya K, 2017). Trend generally does not become evident for several years and so the tests must be carried out on long data series, often aggregated into annual series. Trend may result from a wide variety of factors including: Ÿ change of instrumentation Ÿ change of observation practice or observer Ÿ local shift in the site of the station Ÿ growth of vegetation or nearby new buildings a ecting exposure of the station Ÿ e ects of new irrigation in the vicinity of the station (a ecting humidity, temperature, and pan evaporation) Ÿ e ects of the urban heat island with growing urbanization Ÿ global climatic change The presence of trend does not necessarily mean that part of the data are faulty but that the environmental conditions have changed. Unless there is reason to believe that the trend is due to instrumentation or observation practices or observer, the data should not generally be altered but the existence of trend noted in the station record. Residual mass curve A residual mass curve represents accumulative departures from the mean. It is a very e ective visual method of detecting climatic variability or other inhomogeneities. The residual mass curve can be interpreted as follows: Ÿ an upward curve indicates an above average sequence Ÿ a horizontal curve indicates an about average sequence Ÿ a downward curve indicates a below average sequence 28
Hydrometeorological Data and Instruments Student's t test of stability of the mean The series may be tested for stability of variance and mean. Considering only the simpler case where the variance has not changed, the test for stability of the mean requires computing and then comparing the means of two or three sub-sets of the time series. The details of such tests are available in standard textbooks of statistics (Reddy, 2011). Conclusion Due to the increased water scarcity throughout the world, a lot of attention is given to monitor the available water resources. In these studies, hydrometeorology plays an important role. The chapter is designed to help the researchers and other eld worker, who want to understand the basic concept of hydrometeorology and the related instrumentations. References List of BIS standards on meteorological instruments IS:5948 – 1970 Thermometer screen IS:5681 – 1983 Meteorological thermometers IS:5799 – 1970 Wind vane IS:5912 – 1970Anemometer IS:5973 – 1998 Open Pan Evaporimeter IS:7243 – 1974 Sunshine recorder IS:5901 – 1970 Thermograph IS:5945 – 1970 Barograph Goel NK (2003). Hydrological data collection, processing and analysis lecture notes, IIT Roorkee,Hydrology Project, training manual draft, 1999 Shiva Prasad H J (2018). Lecture notes of PG students. Reddy PJaya Rami (2011).Atextbook of Hydrology. Laxmi Publications Subramanya, K (2013). Engineering Hydrology. Tate McGraw Hill Publishing Company Limited, New Delhi. Wiesner C J (1970). Hydrometeorology, Chapman and Hall, London, 232 29
3 PRECIPITATION (THEORY, MEASUREMENT AND ANALYSIS): A BEGINNER LEVEL LEARNING Vaibhav E. Gosavi Abstract Precipitation plays a very signicant role in the hydrological cycle of the earth and is a primary source of fresh water on earth. It is rst and foremost input to any water resource development and planning projects. Considering the immense value of precipitation and its importance and relevance to researchers in hydrological sciences, environmental science and climatology or those who are concerned with water resources and ood management system, this chapter gives the overview of introduction, measurement and basic analysis of precipitation. Keeping in view the arena of participants of Green Skill Development Programme (GSDP) and their di erent educational background, author kept the chapter very brief and simple; and therefore, includes only basic introductory theory, measurement and simple arithmetic's of precipitation so that the participants will be familiarize with important aspects of rainfall, and, in particular, with the collection and analysis of rainfall data. Keywords: Precipitation, Rainfall, Measurement,Analysis Theory of Precipitation Introduction Precipitation is a primary source of fresh water on earth. It is one among the basic inputs required for many hydrological studies through its amount, intensity and spatio- temporal distribution over the land mass. Basically 'precipitation' is referred to all forms of water (expressed in the terms of depth) that reach the earth from the atmosphere. The forms of precipitation are rainfall, snowfall, hail, frost and dew. The signicant amounts of contribution come from rainfall (in plain region) and snowfall (higher mountainous region); whereas, other forms are least in contribution attributing to their rare/occasional occurrence in the form of extreme events. Rainfall is biggest contributor of river stream Vaibhav E. Gosavi, M.Tech. Centre for Land and Water Resource Management G. B. Pant National Institute of Himalayan Environment, Kosi-Katarmal, Almora [email protected] Monitoring and A ssessment of Environmental Parameters Eds. V. A gnihotri, S. Rai, A . Tiwari, S. Mukherjee, K. Kumar, R. Joshi, GBPNIHE, A lmora, Uttarakhand, India ©GBPNIHE 2020 30
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