Space-time variation and regionalization of seasonal and monthly summer monsoon rainfall of the sub-Himalayan region and Gangetic plains of India

The present study analyses space-time variation of the seasonal and monthly monsoon rainfall of the sub-Himalayan region and Gangetic plains of India by using rainfall data of 90 well-distributed stations for a period of 114 yr (1871 to 1984). Principal components (PCs) and varimaxrotated principal components (RPCs) are computed from the interstation similarity matrix. The 4 leading PCs explaining 52 to 61 of the variance respectively for seasonal and monthly rainfall are found to be statistically significant. When rotated by the varimax method these 4 PCs provide 4 distinct areas of homogeneous rainfall variability for both time scales. The most coherent region is located along the central longitude of the study area, with another coherent region over the extreme western parts. The area east of 81° E is divided into 2 coherent zones roughly along the 22° N parallel. It is noted that the regions thus identified will be useful in understanding climate variability and in weather prediction research

Supply Response of Indian Farmers - Pre and Post Reforms

Supply response to price changes is likely to increase with the increasing liberalization of the agricultural sector. Past studies revealed weak supply response for Indian agriculture. There are no recent reliable estimates to see if the response has improved after the economic reforms introduced in early 90s in India. This study estimates supply response for major crops during pre and post reform periods using Nerlovian adjustment cum adaptive expectation model. Estimation is based on dynamic panel data approach with pooled cross section - time series data across states for India. The standard procedure is to use area as an indicator of supply due to the reason that area decision is totally under the control of farmers. Moreover using supply conceals some variations in area and yield if they move in the opposite directions. In this paper, it is hypothesized that acreage response underestimates supply response and farmers respond to price incentives partly through intensive application of other inputs given the same area, which is reflected in yield. Acreage and yield response functions were estimated and the supply response estimates were derived from these two responses. The significant feature of the specification used in the study is both main and substitutable crops are jointly estimated by a single equation by introducing varying slope coefficients to capture different responses. As expected, foodgrains reveal less response than non-foodgrains. The study found no significant difference in supply elasticities between pre and post reform periods for majority of crops. It raises questions such as whether the constraints are properly identified by the policies or if the impact of reform is yet to be felt in order to make a prominent impact on response parameters. In this study, infrastructural variables other than irrigation could not be introduced due to lack of information for a long time series. Results confirmed that farmers respond to price incentives equally by more intensive application of non-land inputs. Further analysis of the reasons for little impact of reforms on the responses is awaited.dynamic panel model, supply elasticity, acreage and yield response.

Quantification of yield gaps in rain-fed rice, wheat, cotton and mustard in India

Rainfed farming / Crop yield / Simulation / Rice / Wheat / Cotton / Mustard / India

Changes in the pattern of distribution of southwest monsoon rainfall over India associated with sunspots

Despite the systematic nature of the monsoon rains over India, large year-to-year variations in the pattern of distribution of rainfall during the season occur. The yearly pattern of rainfall distribution during the monsoon season (May 31–October 2) for each of the years 1901–51 for a network of 105 stations over India is characterized by a set of six distribution parameters. A brief description of the spatial distribution of the different patterns is given to indicate the nature of the component patterns. Polynomial trend analyses of the time series of the distribution parameters indicate oscillatory features. Power spectrum analyses reveal certain significant periods corresponding to the sunspot cycle or some higher harmonics with regional preferences. The variation of distribution parameters in the different parts of the country with the different sunspot epochs is demonstrated. Studies of the distribution of surface pressure anomalies, frequency of storms and depressions, and the frequency of “breaks in monsoon” associated with the contrasting sunspot epochs suggest that the monsoon circulation features as well as the characteristics of the rainfall distribution have a periodicity nearing the sunspot cycle

Environmental Challenge due to Climate Change in Bihar, Developing State of India

As detailed in the Vulnerability Atlas of India, 27 districts in Bihar are fully affected by high-speed winds of 47 m/s intensity due to climatic change. The area of districts—Banka, Jahanabad, Arwal, and Nalanda is nearly 90 percent affected. Other districts of South Bihar except Nawada are partly affected by high-speed winds of 44 m/s. In all 86 percent of the total area of Bihar is prone to high-speed winds of 47 m/s intensity and only 14 percent of the area prone to high-speed winds of lesser intensity. The five major district, in all 21.1 % of Bihar fall under seismic zone-V. The Himalayan tectonic plate near the Bihar-Nepal Border is having six subsurface fault lines penetrating through its Gangetic planes in four directions, Bihar is vulnerable to the worst kind of disaster caused by earthquake. Available evidence shows that there is high probability of increase in the frequency and intensity of climate related natural hazards due to climate change and hence increase in potential threat due to climate change related natural disasters in India, and Bihar is no exception to this. It is highly vulnerable to hydro-meteorological natural disasters, with North Bihar in general being highly flood-prone, and South Bihar being highly drought prone due to the recent climatic change. Keywords: Climatic change, Natural Disaster, Earthquake, Flood, Drought, Cyclone

Mapping of Salt Affected and Waterlogged Areas using Geospatial Technique

Integration of remote sensing and geographical information system (GIS) technique for the delineation of salt affected and waterlogged areas has become an innovation in the field of ground water research. The main objective of the present investigation is to identify and map the surface extent of salt affected and waterlogged areas during pre-monsoon and post-monsoon season using multi-temporal satellite images and its relationship with soil, rainfall, seasonal groundwater fluctuation and canal command areas. For this purpose, Satellite images from IRS P6, LlSS-III sensor, on a scale of 1:50,000 have been used for delineation of thematic layers such as salt affected and waterlogged areas. The area covered under post monsoon waterlogging (seasonal) comprised of as 114.79 sq km area which is 3.60% of the study area whereas post monsoon waterlogging (permanent) comprised of 89.37 sq km area, which is 2.80% of the study area. The map depicting salt affected soils in the area indicates calcareous fine loamy, coarse-loamy, fine loamy and very fine soil comprising 2799.43 sq km, 9.26 sq km 363.73 sq km and 2.80 sq km area respectively. The monthly TRMM 3B43 rainfall data for the period of 1998-2009 covering the month of June to September shows rainfall varies from less than 965 mm to 1165 mm in the entire state. Depth to groundwater level recorded at select locations by Central Ground Water Board (CGWB), Government of India, for the period 2004-2005 during pre and post monsoon period indicated that a large portion of the area is under groundwater induced waterlogging conditions where groundwater occurs at a depth of 0-3 m below ground surface. The soil and rainfall map clearly specifies that salinity are pre dominant in areas with shallow groundwater levels and high rainfall. Canal command areas comprised the highest waterlogging and salt affected areas in their vicinity as a result of seepage and over irrigation

Near Real-Time Biophysical Rice (Oryza sativa L.) Yield Estimation to Support Crop Insurance Implementation in India

Immediate yield loss information is required to trigger crop insurance payouts, which are important to secure agricultural income stability for millions of smallholder farmers. Techniques for monitoring crop growth in real-time and at 5 km spatial resolution may also aid in designing price interventions or storage strategies for domestic production. In India, the current government-backed PMFBY (Pradhan Mantri Fasal Bima Yojana) insurance scheme is seeking such technologies to enable cost-efficient insurance premiums for Indian farmers. In this study, we used the Decision Support System for Agrotechnology Transfer (DSSAT) to estimate yield and yield anomalies at 5 km spatial resolution for Kharif rice (Oryza sativa L.) over India between 2001 and 2017. We calibrated the model using publicly available data: namely, gridded weather data, nutrient applications, sowing dates, crop mask, irrigation information, and genetic coefficients of staple varieties. The model performance over the model calibration years (2001–2015) was exceptionally good, with 13 of 15 years achieving more than 0.7 correlation coefficient (r), and more than half of the years with above 0.75 correlation with observed yields. Around 52% (67%) of the districts obtained a relative Root Mean Square Error (rRMSE) of less than 20% (25%) after calibration in the major rice-growing districts (>25% area under cultivation). An out-of-sample validation of the calibrated model in Kharif seasons 2016 and 2017 resulted in differences between state-wise observed and simulated yield anomalies from –16% to 20%. Overall, the good ability of the model in the simulations of rice yield indicates that the model is applicable in selected states of India, and its outputs are useful as a yield loss assessment index for the crop insurance scheme PMFBY

Technology -- Climate Interactions in the Green Revolution in India

This paper present a model of the Green Revolution in India, in which the development and diffusion of HYVs, the expansion of irrigation and the expansion of multiple-cropping are treated as endogenous responses to more basic investments in agricultural technology and infrastructure, as well as to climate and edaphic endowments. We incorporate explicit climate-technology interactions in the model, in order to identify climate effects on the diffusion of HYVs, irrigation and multiple- cropping, and on Net Revenue to agriculture. We find that climate affects technology development and diffusion, and that technology development and diffusion affect the impacts of climate on agricultural productivity in India.Green Revolution, India, HYV, Rice, Wheat, Climate, Agricultural Research

Online tools for assessing the climatology and predictability of rainfall and temperature in the Indo-Gangetic plains based on observed datasets and seasonal forecast models

Rainfall in the Northern India-Nepal-Bangladesh region is crucial for farmers, water managers and others in the region. Most precipitation falls predominantly during the south Asian summer monsoon season. The phase of El Niño-Southern Oscillation (ENSO) affects the monsoon as well as winter rainfall in some of the region, but the spring predictability barrier and weakness of ENSO-monsoon relationships lead to relatively low-to-moderate seasonal forecast skill in the region during summer. This report documents a set of tools developed to facilitate the analysis of the mean climate and the predictability of seasonal climate in the region and presents preliminary results for the summer monsoon season. These tools advance the tailoring of historical and forecast climate information for agriculture and increase the accessibility of the information via online map rooms to benefit stakeholders throughout the region

CCAFS Site Portfolio: Core Sites in the CCAFS Regions: East Africa, West Africa and South Asia

The CGIAR Research Program Climate Change, Agriculture, Food Security (CCAFS) is a 10-year research initiative launched by CGIAR and the Earth System Science Partnership (ESSP). CCAFS seeks to overcome the threats to agriculture and food security in a changing climate, exploring new ways of helping vulnerable rural communities adjust to global changes in climate. CCAFS brings together the world’s best researchers in agricultural science, development research, climate science, and Earth System science to identify and address the most important interactions, synergies and trade- offs between climate change, agriculture and food security. CCAFS also involves farmers, policy makers, donors, non-governmental organizations and other stakeholders to integrate their knowledge and needs into the tools and approaches that are being developed. The overall goal of CCAFS is to overcome the additional threats posed by a changing climate to achieving food security, enhancing livelihoods and improving environmental management. In 2010/2011, CCAFS initially focused on three regions: East Africa (EA), West Africa (WA) and South Asia (SA). Two additional target regions (Southeast Asia and Latin America) were added in late 2012. This report outlines the site selection process of current and future sites and provides a brief overview of the initially selected CCAFS sites