eChapters

Introduction

The issue of environmental protection has become increasingly important in recent years, and one of the most effective ways to address this problem is through the use of recycled products. Recycling helps to conserve natural resources, reduce waste, prevent pollution, and combat climate change making it a critical part of any sustainable development strategy. In this chapter, we can explore how recycled products can help protect the environment and the many benefits that come with their use.

Introduction
Environmental science plays a critical role in understanding and addressing the complex interactions between human activities and the natural world. This chapter explores the intersection of environmental science and agriculture, emphasizing the importance of ecological balance for sustainable development. As agriculture continues to be a major driver of environmental change, understanding its impacts on ecosystems, biodiversity, and climate is crucial for developing strategies that promote sustainability.
The chapter begins by examining the environmental impacts of agriculture, including land degradation, deforestation, and pollution. It then explores agroecology and biodiversity, highlighting the importance of maintaining diverse ecosystems to support sustainable agricultural practices. Sustainable resource management is discussed as a key approach to conserving natural resources and minimizing the environmental footprint of agriculture.
Climate-smart agriculture, a modern concept that integrates environmental sustainability with agricultural productivity, is introduced as a solution to mitigate the effects of climate change while ensuring food security. The chapter also covers environmental regulations and policies, which are essential for guiding sustainable agricultural practices and protecting the environment.
As the chapter progresses, it delves into the importance of environmental science in food security, the impact of environmental factors on global warming, and various modern concepts in environmental science, including sustainable food systems, circular economy, and ecosystem-based approaches. The chapter concludes with a discussion on combating food security and global warming challenges through sustainable practices and policies.
Environmental science plays a crucial role in agriculture by studying the interactions between agricultural practices and the natural environment. This chapter explores various aspects of environmental science in agriculture, including the environmental impacts of agriculture, agroecology and biodiversity, sustainable resource management, climate-smart agriculture, and environmental regulations and policies. Agriculture and the environment are inherently interconnected, as agricultural practices have both direct and indirect impacts on the natural environment. Environmental science in agriculture aims to understand these impacts and develop sustainable practices that minimize negative environmental

Bhuva is a small village in north-west Gujarat – India.  My mother was born there. The loving people of Bhuva called me ‘Bhano’ (Sister’s Son / Nephew) and it was my favourite place to go as a child. I have my fondest memories of Bhuva, but could not visit for several decades, until when I was once at the Junagadh Campus of Gujarat Agricultural University, to inaugurate the International Conference on New Developments in Agriculture. Bhuva was not too far and I decided to go there. Soon as I reached, a familiar face, now aged with time, recognized me from a distance and with tears rolling from his old eyes (and mine) he hugged me, calling out “MaroBhano, MaroBhano” (My sister’s son, my sister’s son)! Now in his eighties, it was overwhelming to meet Nanji Ata, who I always remembered being wise, educated and cheerful. He was a relatively progressive farmer with about 6 to 7 acres of land, a few cows and a buffalo. Though water was scarce and saline, he managed to make a good living and was considered a well to do man.

7.1 Summary

Climate change is a complex global phenomenon that poses significant challenges for agriculture including uncertainty about future weather patterns, soil conditions, and other environmental factors. Farmers are facing the difficult task of interpreting and responding to these changes in order to maintain their livelihoods and ensure food security for growing populations. In this context, mental modelling has emerged as a useful approach for understanding how farmers interpret and respond to climate change. Mental models are cognitive representations of how individuals understand and make decisions about complex systems, and can be used to identify key drivers of behaviour and decision-making.

The present study has explored the social, ecological, and economic factors that influence farmers’ mental models on perception of climate change, level of uncertainty and trend of agricultural change in the selected study area. It argues that farmers’ mental models are shaped by a range of factors, including their own experiences and observations, social networks and interactions, access to information and resources, and broader economic and political contexts. The present study has also highlighted the role of uncertainty in shaping farmers’ mental models and decision-making. Uncertainty about the future impacts of climate change can create significant challenges for farmers, as they must make decisions based on incomplete information and uncertain predictions.

Flooding and soil erosion are closely connected because concentrated runoff detaches, transports, and deposits soil material throughout a watershed and river system. Raindrop impact initiates splash erosion, while surface flow produces sheet, rill, and eventually gully erosion. Sediment generated from fields and channels reduces reservoir capacity, raises riverbeds, obstructs drainage, and lowers channel conveyance, thereby increasing flood risk. This chapter explains erosion mechanisms, classifications, influencing factors, gully development, sediment yield, sediment-delivery ratio, suspended and bed loads, and sediment-transport models. It also examines soil-loss estimation and agronomic or structural conservation measures that can reduce erosion, control sediment movement, and improve watershed-level flood management

5.1 INTRODUCTION

A GIS database without single error is reliable for decision making. There are various possible sources of errors in GIS. If an error is not removed during scanning, the final output will also have that error. Besides whatever the work has been carried on wrongly scanned map it will add to errors because the source map itself's erroneous. This is like garbage in garbage out proverb. If wrong data is taken for analysis it will only result in wrong output. Hence it is important to remove error at every stage of GIS work. It is important to locate the sources of errors so that due care may be taken while handling a project.

5.2 ORIGINAL SOURCES OF ERRORS

All the equipments which give attributed data and spatial data will give errors. Before going to field or before collecting data all the related instruments should be calibrated properly. Also the instrument should not cross the permissible error. Besides these while using data from diversified sources errors pertaining to those instruments are mixed to give a different result. When very good accuracy is desired data should be collected from high end equipments. Even if one adds the data from a comparbly less accurate instrument to the data of many accurate instrument is then the result obtained finally will not reliable enough. Global Positioning System (GPS) is available with mm accuracy to meters accuracy. Also surveying with suitable map projection and datum is important; otherwise the result will be wrong. Survey instruments posses some inaccuracy and when a person is using it he should have the accuracy over the instrumental like rain gauge, water level recorders which give attributed data which should be checked for instrumental inaccuracies and method of data collection before using it. Likewise satellite and aerial sensors miss some data and some error are inherent. Such errors should be removed before moving ahead. Errors are resulted due to map reduction, enlargement, data editing and computation method adopted. At the same mapping instruments also possess inaccuracies. When after certain interval a person is going for survey, the registered object may have been changed. Many new features might have come up. Hence the established control points are changed and if the wrongly placed control points are taken for survey then the result itself will be wrong. If proper resolution is not available in the instruments, then the instruments may not capture the minute details which are required.

Introduction

The GIS database is a model of real world. It goes without saying that there is an inherent discrepancy between GIS database and the real world it represents. This is so because all models are fraught with cognitive issues and remain as approximations. To realize the objectives of a GIS, geographical data collected, entered and processed are to be sufficiently error free and reliable.

Errors can be statistical errors like mistakes, wrong inputs or faulty field surveys or system errors like excessive tolerances or high RMS error. The spatial database has further problems in the sense that the real world phenomena are not always intrinsically discrete. For instance where is the bank of a shallow river? Where is the boundary between two soil types? These are but a few questions revealing the fuzzy nature of geographic data. Many soil scientists, geographers have noticed that carefully drawn boundaries or iso-lines on maps in general give misrepresentations of change that are often gradual, vague or fuzzy. Traditional cartography as a medium of spatial data handling had a solution to such problems. But now when digital data are handled, they need to be stored with certain precision. Moreover, the spatial variation of natural phenomena is not just a local noise function or inaccuracy that can be removed by collecting more data or by increasing the precision measurement but is often a fundamental aspect of nature that occurs at all scales. (Goodchild, 1980; Mark and Aronson, 1984). This means residual unmapped variation is a remarkable problem in geographical information processing. It is therefore a prerequisite to fully understand how errors arise or propagated in GIS and what might be the effects of errors on output.

Agricultural meteorology, a discipline that has traditionally focused on understanding the relationships between weather and climate, and agricultural productivity, is at a critical juncture. The increasing vulnerability of agricultural systems to climate change, coupled with the need for sustainable and resilient agricultural practices, necessitates a fundamental transformation of agricultural meteorology. To support the development and implementation of climate resilient agriculture (CRA) practices, agricultural meteorology must be reoriented as a super speciality discipline. This requires a comprehensive overhaul of the discipline, including its curriculum, research focus, and practice. The reorientation of agricultural meteorology as a super speciality discipline is essential to provide the necessary expertise and knowledge to support CRA practices. This includes developing and applying cutting-edge technologies, such as precision agriculture, remote sensing, and machine learning, to support agricultural decision-making. However, the current state of agricultural meteorology is not equipped to meet the demands of CRA. The discipline faces several challenges, including a lack of interdisciplinary approaches, inadequate emphasis on practical skills, and limited focus on climate change and sustainability (Fig. 8.1). To address these challenges, essential reforms are necessary to reorient agricultural meteorology as a super speciality discipline. This chapter will discuss the essential reforms required to transform agricultural meteorology, including reforms in curriculum, research, practice, and policy. By implementing these

The credibility of academic publishing hinges significantly on the integrity of journal rating systems. These systems, designed to evaluate and rank academic journals based on various metrics, play a pivotal role in shaping research priorities, funding allocations, and academic career trajectories. However, despite their importance, many journal rating systems are criticized for lacking transparency and ethical rigor (Fig. 10.1).
This chapter explores these shortcomings, focusing on potential biases embedded in current systems and proposing solutions to enhance their transparency and fairness.
10.1. Role of Journal Rating Systems in Academic Publishing
Journal rating systems serve as gatekeepers in the academic publishing ecosystem. They influence where researchers choose to publish their work, how institutions evaluate scholarly output, and how funding agencies allocate resources. Metrics such as impact factor, h-index, and SCImago Journal Rank (SJR) are commonly used to rank journals. These metrics, while useful, often reduce the multifaceted nature of scholarly impact into single numerical values, potentially oversimplifying and distorting the evaluation process. The reliance on these metrics creates a feedback loop wherein highly ranked journals attract more submissions, increasing their citation counts and reinforcing their dominance. This system can marginalize smaller or niche journals that publish

Abstract

The paper presents an approach of selecting suitable areas for artificial groundwater recharge structures through remote sensing and integrated terrain analysis by statistical method. The study area “Ayyar basin” is an aquifer system of gneisses and charnockite litho-units in Tiruchirappalli district, Tamil Nadu. The area has witnessed a steady decline in groundwater table. Hence, the scope for artificial groundwater recharge was studied in this area with the help of Tamil Nadu State Council for Science and Technology (TNSCS&T).

Introduction 
The preceding chapters have laid a robust foundation, introducing the concept of agricultural systems, delving into the architecture and types of crop models, and meticulously detailing the essential data requirements for their operation. We have established that crop models are powerful tools for simulating the complex interactions within the soil-plant-atmosphere continuum, driven by a rich tapestry of environmental and management inputs. Among these inputs, weather stands out as arguably the most dynamic and influential factor, wielding profound control over every aspect of crop life, from the precise timing of germination to the final quantity and quality of the harvest. Chapter 5 shifts our focus to the direct and indirect consequences of this critical environmental driver: the evaluation of crop responses to weather. This chapter is dedicated to understanding, quantifying, and interpreting how variations in meteorological conditions—such as temperature, solar radiation, precipitation, humidity, and wind—directly influence the physiological processes, developmental progression, biomass accumulation, and ultimate yield of cultivated crops. It‘s about moving from simply providing weather data to actually assessing its impact on the plant‘s performance. The ability to accurately evaluate these responses is paramount for several interconnected reasons: Firstly, from a fundamental scientific perspective, it deepens our understanding of plant ecophysiology. By analyzing how crops react to specific weather patterns, we gain invaluable insights into the underlying biological mechanisms that govern growth and development under diverse environmental pressures. This knowledge is crucial for advancing agricultural science itself. Secondly, for agricultural management and decision-making, this evaluation is directly actionable. Understanding optimal weather conditions for specific growth stages, or predicting the impact of adverse events, enables farmers

ABSTRACT

The present study reports shoreline changes at Gopalpur along east coast of India for 30 years during 1973-2003. In order to understand the trend of sediment transport, shoreline changes at the vicinity areas viz. Rushikulya and Bahuda estuaries are also discussed. Geomorphological investigation is also carried out to understand the processes acting on this system. One Landsat image (1973) and two IRS 1C/1D images (1993 and 2003) were used for the study. The data were subjected to digital analysis using ERDAS Imagine and management of information layers using ARC/INFO GIS software. The results of the study show that the changes occurred differently in three distinct spatial features namely, i) sand spit ii) beach and, (iii) channel zone. Changes documented in these imageries reveal that the lengths of NE spit and SW spit are increased and decreased respectively in thirty years. Areas of NE and SW spits are also showing the similar pattern. Beach is almost stabilised and a slight decrease of 0.28 km in length is observed. However, area has been increased in the southern beach. Towards north, the beach area is also increased over a period of thirty years. The change of width of the beach is not found to be significant. The mouth near channel zone is reduced to 70 meter from 135 meter during the period of study.

The change of state of water from solid and liquid to the vapour and its diffusion into the atmosphere is referred as Evaporation. In the meteorology, evaporation is defined as the maximum possible loss of moisture from a wet, horizontal, flat surface exposed to weather which exist in the vicinity of plants.

FACTORS AFFECTING EVAPORATION

1. Those affecting water supply at the evaporating surface. i.e., soil and plants including soil storage capacity, rainfall and irrigation and

2. Those affecting energy supply to the evaporating surface like solar radiation.

This chapter is fundamental to agricultural water management, as it explains how water moves from the land surface and plants back into the atmosphere, directly influencing irrigation needs and drought impacts. Water is the lifeblood of agriculture, and its efficient management is paramount for sustainable food production. Understanding how water is lost from the soil and plants to the atmosphere is central to optimizing irrigation and assessing crop water needs. This chapter delves into the concepts of evaporation, transpiration, their combined effect as evapotranspiration, and how these relate to overall crop water use (Fig.5.1).

Definition: Evaporation is the physical process by which liquid water is converted into water vapor and transferred from the land surface (e.g., bare soil, water bodies, or wet plant surfaces) into the atmosphere. It is purely a physical process driven by solar energy and the vapor pressure gradient between the surface and the air.

In cropped soils, evaporation refers to evaporation of water from the soil and transpiration refers to evaporation of water from plant canopies (Fig.6.1). Evaporation and transpiration play very significant role in mass and energy transfer. The latent heat of vaporization is defined as amount of heat required to evaporate 1 gm of water at a temperature of 100°C; i.e. the boiling point of water is 540 cal/gm. The amount of heat required for evaporation of water at ordinary temperature of about say 30°C is 610 cal/gm.
Fig. 6.1: Process of evapotranspiration
The evapotranspiration from crop depends upon several factors as indicated below:
• The evapotranspiration increases with increase in air temperature.
• The evapotranspiration increases with increase in wind speed up to a certain limit.
• The evapotranspiration decreases with increase in relative humidity
• The evapotranspiration increases with increase in Saturation Vapor Pressure Deficit (SVPD). SVPD = es – ea

Evapotranspiration is the combination of two separate processes named evaporation and transpiration. Evaporation accounts for the movement of water to the air from sources such as the waterbodies and soil. Transpiration accounts for the movement of water within a plant and the subsequent loss of water as vapour through stomata in its leaves. So evapotranspiration is a bio-physical process.

Evaporation

The change of state of water from liquid to the vapour and its diffusion into the atmosphere is referred to as evaporation. During evaporation, water molecules absorb energy which gives them the motion required to escape from the surface of liquid and become a gas. Since a certain amount of energy is consumed in the process of evaporation, the remaining liquid is cooled by an equivalent amount. Thus, the process of evaporation is always accompanied by a cooling effect.

As evaporation proceeds, the surrounding air becomes gradually saturated with water vapour and the process will slow down and might stop if the wet air is not transferred to the atmosphere. The replacement of the saturated air with drier air depends greatly on wind speed. Hence, solar radiation, air temperature, air humidity and wind speed are meteorological parameters to be considered when assessing the evaporation process.

In agrometeorology, evaporation is defined as the maximum possible loss of moisture from a wet, horizontal, flat surface exposed to weather parameters, which exist in the vicinity of plants. Evaporation is an essential part of the water cycle. It is the primary pathway through which water moves from the liquid state back into the water cycle as atmospheric water vapour. The oceans, seas, lakes and rivers provide nearly 90 per cent of the moisture in the atmosphere via evaporation, with the remaining 10 per cent being contributed by plant transpiration. A very small amount of water vapour enters the atmosphere through sublimation, the process by which water changes from a solid (ice or snow) state to a gaseous one, bypassing the liquid phase.