Water use pattern and related agrometeorological indices of rabi & kharif sunflower (Helianthus annuus L.) at Deccan plateau

The agrometeorological data pertinent to estimation of water use and related agrometeorological indices of KBSH - II (1988 to 1991) and MORDEN varieties of sunflower (1992 and 1993) cultivated both in rabi and kharif seasons, were used to understand the comparative water use pattern and agrometeorological indices for getting an idea about the crop condition at Bangalore. The study revealed that mean weekly water use was higher in almost all the years during the kharif season than during the rabi season except in 1990 and the consumptive water use increased with development of the vegetative cover of the crop reaching a peak value in the vegetative growth stage. The ARI (agroclimatic rainfall index) and cumulative YMI (yield moisture index) were always higher during the kharif season than correspondingly those during the rabi season and showed yearly and seasonal variability in different growth stages which was due to the moisture stress condition of the soil as well as prevailing weather conditions of the atmosphere. In case of AI (aridity index), high values were observed at early and late crop growth stages during the kharif season which showed that the crop experienced less aridity between vegetative to seed formation stage. The water use efficiency (WUE) of the crop also revealed wide variation due to variety and season.

Remote Sensing Mapping of Peat-Fire-Burnt Areas: Identification among Other Wildfires

Peat fires differ from other wildfires in their duration, carbon losses, emissions of greenhouse gases and highly hazardous products of combustion and other environmental impacts. Moreover, it is difficult to identify peat fires using ground-based methods and to distinguish peat fires from forest fires and other wildfires by remote sensing. Using the example of catastrophic fires in July–August 2010 in the Moscow region (the center of European Russia), in the present study, we consider the results of peat-fire detection using Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) hotspots, peat maps, and analysis of land cover pre- and post-fire according to Landsat-5 TM data. A comparison of specific (for detecting fires) and non-specific vegetation indices showed the difference index ΔNDMI (pre- and post-fire normalized difference moisture Index) to be the most effective for detecting burns in peatlands according to Landsat-5 TM data. In combination with classification (both unsupervised and supervised), this index offered 95% accuracy (by ground verification) in identifying burnt areas in peatlands. At the same time, most peatland fires were not detected by Terra/Aqua MODIS data. A comparison of peatland and other wildfires showed the clearest differences between them in terms of duration and the maximum value of the fire radiation power index. The present results may help in identifying peat (underground) fires and their burnt areas, as well as accounting for carbon losses and greenhouse gas emissions.

Soil Moisture Assessment Using Soil Moisture Index (SMI) Method at the Bangelan Coffee Plantation, Malang Regency, East Java

Water is one of the limiting factors in the growth of coffee plants. If plants experience a lack of water, it can inhibit plant growth and, at a critical level, can lead to drought stress and plant damages. The available soil water to plants can be estimated from the level of soil moisture index. The monitoring of soil moisture status can be used in improving the management of coffee plantations. Soil Moisture Index (SMI) is a method that can be used to estimate the level of soil moisture using remote sensing technology using NDVI and LST values. The purpose of this study was to analyze the status and distribution of soil moisture at the coffee plantation; analyze the relationship between vegetation index and soil moisture; and analyzed the relationship between soil moisture status using the SMI method and soil moisture measured in coffee plantations. Results showed that the soil moisture index obtained from Landsat 8 OLI/TIRS image processing had an average value of 0.60. The average soil moisture index at the study site is 1.05. Soil moisture index from the Landsat 8 OLI/TIRS image has a significant positive effect on soil moisture at the study site (y = 7.4996x – 3.4789; R2 = 0.7146**). It is suggested that the SMI method can be used to estimate soil moisture in the coffee plantation.

Projected Moisture Index (MI) for Tropical Sri Lanka

Atmospheric moisture loading can cause a great impact on the performance and integrity of building exteriors in a tropical climate. Buildings can be highly impacted due to the changing climate conditions over the world. Therefore, it is important to incorporate the projected changes of moisture loads in structural designs under changing climates. The moisture index (MI) is widely used in many countries as a climate-based indicator to guide the building designs for their durability performance. However, this was hardly considered in structural designs in Sri Lanka, even though the country is one of the most affected countries under climate change. Therefore, this study investigates future climate change impacts on the environmental moisture in terms of MI, which can be used in climate zoning, investigating indoor air quality, understanding thermal comfort and energy consumption, etc. The moisture index was found as a function of the drying index (DI) and wetting index (WI) to the whole country for its four rainfall seasons. The temporal and spatial distributions were plotted as MI maps and showcased under two categories; including historical MI maps (1990–2004) and future projected MI maps (2021–2040, 2041–2070, and 2071–2100). Future projected MI maps were constructed using bias-corrected climatic data for two RCP climatic scenarios (RCP4.5 and RCP8.5). Results showed that the temporal and spatial variations of MIs are justifiable to the country’s rainfall patterns and seasons. However, notable increases of MIs can be observed for future projected MIs in two seasons, and thus a careful investigation of their impacts should be assessed in terms of the construction of buildings and various agricultural activities. Therefore, the outcome of this research can be essentially used in policy implementation in adapting to the ongoing climate changes in Sri Lanka.

Requirement of heat unit and agrometeorological indices in selected wheat growing zones

Wheat growing ET -stations (viz., Jorhat, Varanasi, New Delhi, Ludhiana, Raipur, Jabalpur, Akola, Bellary, Banswara and Jodhpur) situated in arid to per humid climatic zones were selected. Heat unit and three agromeleorological indices, viz., ARI (agroclimatic rainfall index), YMI (yield moisture index) and AI (aridity index) were computed at various growth stages of wheat crop using latest available five years data for each of the stations. The study revealed that the crop degree days requirement varied from 1580 (at Jorhat) to 2350 (at Akola) with the maximum requirement at tillering and milk stages. All the stations (except Jorhat) recorded ARI values less than 25%, while for the stations in peninsular and western India, the values were even below 10%. Low cumulative YMI values were obtained in peninsular and western India, while high values were observed over eastern India. The wheat crop did not experience any aridity during tillering to flowering stages for all the stations (except Bellary and Banswara). High values of At were observed at early and late crop growth stages. Negative correlation was obtained between AI and ARI with the highest value (-0.89) observed at New Delhi. Depending upon this study, the wheat growing areas were divided into five zones.

Droughts and aridity in northeast Brazil

ABSTRACT. Results of a study of droughts and aridity in northeast Brazil are presented in this paper. The study is based on the analysis of yearly water balances at fifteen stations in the region. Incidence of droughts of varying intensities at the stations is discussed. Climatic shifts at the stations are evaluated on the basis of the moisture index values. The use of the cumulative deviation technique in drought studies is briefly mentioned.

Detection of Groundwater in Iraq-Wasit Governorate Using Remote Sensing and GIS

The groundwater in Iraq has been studied for the need for it due to the shortage of surface water levels.The vegetation cover index, the soil moisture index, and the surface water index were used to detect the presence of groundwater in Wasit Governorate, Iraq. Those indicators that appear on the ground cover and indicate the presence of groundwater in the study area were compared with the coordinates of wells underground water. The results were identical with information obtained from the Ministry of Water Resources.

Long-term trends in agricultural droughts over Netherlands and Germany: how extreme was the year 2018?

Droughts can have important impacts on environment and economy like in the year 2018 in parts of Europe. Droughts can be analyzed in terms of meteorological drought, agricultural drought, hydrological drought and social-economic drought. In this paper, we focus on meteorological and agricultural drought and analyzed drought trends for the period 1965–2019 and assessed how extreme the drought year 2018 was in Germany and the Netherlands. The analysis was made on the basis of the following drought indices: standardized precipitation index (SPI), standardized soil moisture index (SSI), potential precipitation deficit (PPD) and ET deficit. SPI and SSI were computed at two time scales, the period April-September and a 12-months period. In order to analyze drought trends and the ranking of the year 2018, HYDRUS 1-D simulations were carried out for 31 sites with long-term meteorological observations and soil moisture, potential evapotranspiration (ET) and actual ET were determined for five soil types (clay, silt, loam, sandy loam and loamy sand). The results show that the year 2018 was severely dry, which was especially related to the highest potential ET in the time series 1965–2019, for most of the sites. For around half of the 31 sites the year 2018 had the lowest SSI, and largest PPD and ET-deficit in the 1965–2019 time series, followed by 1976 and 2003. The trend analysis reveals that meteorological drought (SPI) hardly shows significant trends over 1965–2019 over the studied domain, but agricultural droughts (SSI) are increasing, at several sites significantly, and at even more sites PPD and ET deficit show significant trends. The increasing droughts over Germany and Netherlands are mainly driven by increasing potential ET and increasing vegetation water demand.