Agricultural Impacts of Climate Change [Volume 1]

Rohitashw Kumar, Vijay P Singh, Deepak Jhajharia, Rasoul Mirabbasi

• Publisher: CRC Press
• Year: 2019
• Print ISBN: 9780367345235
• eBook ISBN: 9781000701227
• Edition: 1
• Topic: Biological Sciences
• Subtopic: Botany
• Index: Biological Sciences

Conservation agriculture is a sustainable production model that not only optimizes crop yields, but also reaps economic and environmental benefits as well. The adoption of successful conservation agriculture methods has resulted in energy savings, higher organic matter content and biotic activity in soil, increased crop-water availability and thus resilience to drought, improved recharge of aquifers, less erosion, and reduced impacts from the weather associated with climate change in general.

Agricultural Impacts of Climate Change examines several important aspects of crop production, such as climate change, soil management, farm machinery, and different methods for sustainable conservation agriculture. It presents spatial distribution of a daily, monthly and annual precipitation concentration indices, Diffuse Reflectance Fourier Transform Infrared Spectroscopy for analyzing the organic matter in soil, and adaptation strategies for climate-related plant disease scenarios. It also discusses solar energy-based greenhouse modeling, precision farming using remote sensing and GIS, and various types of machinery used for conservation agriculture.

Features:

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• Examines the effects of climate change on agriculture and the related strategies for mitigation through practical, real-world examples

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• Explores innovative on-farm technology options to increase system efficiency resulting in improved water usage

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• Presents examples of precision farming using climate-resilient technologies

1	Spatial Distribution of a Daily, Monthly and Annual Precipitation Concentration Index

Farshad Ahmadi

Shahid Chamran University of Ahvaz

Mohammad Nazeri

University of Birjand

Rasoul Mirabbasi

Shahrekord University

Keivan Khalili

Urmia University

Deepak Jhajharia

College of Agricultural Engineering & Post Harvest Technology, CAU

CONTENTS

1.1Introduction

1.2Methodology

1.2.1CI

1.2.2PCI

1.3Results and Discussion

1.3.1Results of Lake Urmia Basin PCI

1.3.2A Study on CI of Precipitation Distribution in Lake Urmia

1.4Conclusion

References

1.1INTRODUCTION

Climate changes are one of the most important environmental challenges at present. Our understanding of the human impacts on the environment, particularly those associated with the warming due to the increasing greenhouse gases, shows that several parameters are most likely changing. According to scientific reports, the average surface temperature of Earth has increased about 6°C during the 20th century. It is expected that the amount of evaporation will have an ascending trend. Therefore the atmosphere will be able to move greater amounts of water vapor and hence the amount of precipitation will be affected (Tabari 2011). Insufficient precipitation and its severe fluctuations on daily, seasonal, and annual scale are amongst the inherent climatic characteristics of Iran. The precipitation patterns have changed under the influence of global warming and led to the occurrence of extreme weather events such as floods, drought, rain, storm, etc. For instance a significant reduction in the number of rainy days has been confirmed in many parts of the world, including China (Zhang et al. 2008, Ren et al. 2000, Gong and Ho 2002, Zhai et al. 2005). One of the most important aspects of climate change that requires closer examination is to review the temporal distribution of precipitation and its historical changes. With regard to the effect of precipitation on water resources like groundwater, surface water, and snow reserves, it seems necessary to use indices for the expression of changes. Some of these indicators include Standardized Precipitation Index (SPI), Precipitation Concentration Index (PCI), and Density Index (DI).

Concentration Index (CI) is actually an index to examine the statistical characteristics of daily precipitation. PCI index is a part of the famous Fournier index used for the analysis of natural resources such as soil erosion (Luis et al. 2011). The results of PCI calculations could be hydraulic management programs, water and environmental resources as a warning instrument to be prepared against flood or erosion (Adegun et al. 2012). This concept could also be used in irrigation planning and designing new systems. An unbalanced distribution of precipitation could reduce the agricultural crops yield through the reduction of moisture in soil and increase the irrigation periods. Besides, an unbalanced distribution of precipitation means drought. Precipitation less than the regional average may cause drought of varying intensity since soil moisture will reduce, and vegetation will be destroyed.

This will eventually lead to increased protection precautions in the basin in order to maintain water structures. Martin-Vide (2004) calculated the CI for daily precipitation in Spain and divided the results into two regions with highest dispersion and regular dispersion of precipitation. Zhang et al. (2009) calculated the CI for serial precipitation for Pearl River basin. Alijani et al. (2008) examined Iran’s rainfall intensity in 90 synoptic stations and indicated that the rainfall dispersion has been erratic in Iran. The stations located in the Caspian Sea, the Zagros Mountains, and the North West of Iran had the most significant amount of rainfall. Li et al. (2011) calculated the CI values for Kaidu River basin. Luis et al. (2011) studied the annual and seasonal average amounts and wet and dry periods of PCI in the vicinity of Spain for two (1976–2005 and 1964–1975) time spans. The analysis of the two sub periods revealed that significant rainfall changes occurred in Spain from 1946 to 2005. Adegun et al. (2012) evaluated the PCI index on two annual and seasonal scales during 1974–2011 in two areas in Nigeria. The results of PCI analysis in this area showed that 87% and 71% of studied years were located in the first and second area, respectively, within an average concentration domain. Valli et al. (2013) used the PCI index to show rainfall pattern in Andhra Pradesh State during 1981–2010 on two annual and seasonal scales. The results indicate that there is an irregular distribution of rainfall (with values ranging from 16 to 35) in this area. Khalili et al. (2016) studied the dispersion of monthly and annually rainfall of synoptic stations in Iran for the last 50 years in a 25-year period. Scientists believe that the changes in concentrations of the greenhouse gases resulting from fossil fuel consumption lead to drastic changes in some components of the hydrological cycle, such as precipitation in different parts of the world. In the following sections of this chapter, the fundamentals of PCI and CI indices theory will be explained. Then the Lake Urmia basin will be introduced and the aforesaid indices will be used to study the distribution and concentration of rainfall in the basin of Lake Urmia. The results are presented and discussed here and the overall results are presented in the final section.

1.2METHODOLOGY

In this section, two indices of PCI and CI are completely described. Necessary examples are also given for further explanation of the calculation method.

1.2.1CI

The method of calculating CI is based on the principle that the overall ratio of rainy days to total rainfall could be adjusted by a negative exponential distribution (Brooks and Carruthers 1953, Martin‐Vide 2004). According to the geographic features and time span, the chance of low daily precipitation is probably higher than the large amounts of precipitation. So the initial lowest precipitation class will reduce the ultimate absolute frequency (Martin-Vide 2004). To study the effect of different doses of daily precipitation and the ratio of high amounts of precipitation to total precipitation, cumulative precipitation percent (Y) and cumulative daily percent (X) were studied during Y events. According to the studies by Olascoaga (1950), daily precipitation data in the range of 1 mm/day were firstly classified to examine the CI. The number of days with rainfall was specified in each category and their cumulative values were also calculated. Finally, the cumulative percentage of rainy days and the relationship between precipitation and rainy days were established. According to the steps outlined, an exponential curve of the cumulative percentage of rainy days (X) in contrast to the percentage of cumulative rainfall (Y) was obtained. Martin-Vide (2004) recommended Y = (a × X)exp(b × X) for this curve in which a, b are the regression coefficients. Gini CI 2S/10,000 will be applied as an index to measuring the concentration in which S is equal to the area enclosed by the first quarter bisector and polygon line or Lorenz curve. In fact, the precipitation concent...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• Preface
• Editors
• Contributors
• Chapter 1 Spatial Distribution of a Daily, Monthly and Annual Precipitation Concentration Index
• Chapter 2 Use of Mid-Infrared Diffuse Reflectance to Assess the Effects of Soil Management on Soil Quality in Tropical Hill Slope Agro Eco-Systems
• Chapter 3 Climate Change and Production of Horticultural Crops
• Chapter 4 Climate Change on Disease Scenario in Crops and Management Strategies
• Chapter 5 Solar Thermal Modeling of Microclimatic Parameters of Agricultural Greenhouse
• Chapter 6 Development of Agriculture under Climate and Environmental Changes in the Brazilian Semiarid
• Chapter 7 Role of PGPR in Sustainable Agriculture under Changing Scenario of Climate Change
• Chapter 8 Status and Prospect of Precision Farming in India
• Chapter 9 Low-Cost On-Farm Indigenous and Innovative Technologies of Rainwater Harvesting
• Chapter 10 Impact of Climate Change on Food Safety
• Chapter 11 Microbial Assisted Soil Reclamation for Sustainable Agriculture in Climate Change
• Chapter 12 Production of Temperate Fruits in Jammu & Kashmir under Climate Change Scenario
• Chapter 13 Impact of Climate Change on Quality Seed Production of Important Temperate Vegetable Crops
• Chapter 14 Climate Change, its Impact and Mitigation Strategies with Reference to Vegetable Crops
• Chapter 15 Remote Sensing and GIS: A Tool of Precision Agriculture
• Chapter 16 Farm Machinery for Conservation Agriculture
• Index