Simulation of leaf blast infection in tropical rice agro-ecology under climate change scenario

Assessing disease risk has become an important component in the development of climate change adaptation strategies. Here, the infection ability of leaf blast (Magnaporthe oryzae) was modeled based on the epidemiological parameters of minimum (T _min), optimum (T _opt), and maximum (T _max) temperatures for sporulation and lesion development. An infection ability response curve was used to assess the impact of rising temperature on the disease. The simulated spatial pattern of the infection ability index (IAI) corresponded with observed leaf blast occurrence in Indo-Gangetic plains (IGP). The IAI for leaf blast is projected to increase during the winter season (December–March) in 2020 (2010–2039) and 2050 (2040–2069) climate scenarios due to temperature rise, particularly in lower latitudes. However, during monsoon season (July–October), the IAI is projected to remain unchanged or even reduce across the IGP. The results show that the response curve may be successfully used to assess the impact of climate change on leaf blast in rice. The model could be further extended with a crop model to assess yield loss.     

Image quality characterization of fine resolution RISAT-1 data using impulse response function

This study presents the results obtained from image quality assessment of Radar Imaging SATellite (RISAT-1). Image quality parameters such as spatial resolution, peak to sidelobe ratio (PSLR) and integrated sidelobe ratio (ISLR) are calculated by the analysis of impulse response function (IRF) of the point target. The study is carried out to assess temporal stability and consistency of image quality parameters obtained from analysis of IRF of 44 point targets. The results obtained from this study show that the mean values of the range and azimuth resolution are 2.048 ± 0.081 m and 3.383 ± 0.097 m for RH and 1.981 ± 0.081 m and 3.348 ± 0.076 m for RV, respectively. PSLR/ISLR values for RH channel are obtained as ?26.492 dB/?26.823 dB for azimuth and ?19.209 dB/?19.921 dB for the range. For RV channel, PSLR/ISLR values are ?26.300 dB/?27.572 dB for azimuth and ?19.146 dB/?19.827 dB for range.     

Trends in major and minor meteorological variables and their influence on reference evapotranspiration for mid Himalayan region at east Sikkim,India

Estimation of evapotranspiration(ET) for mountain ecosystem is of absolute importance since it serves as an important component in balancing the hydrologic cycle.The present study evaluates the performance of original and location specific calibrated Hargreaves equation(HARG) with the estimates of Food and Agricultural Organization(FAO)Penman Monteith(PM) method for higher altitudes in East Sikkim,India.The results show that the uncalibrated HARG model underestimates ET_0 by 0.35 mm day~(-1) whereas the results are significantly improved by regional calibration of the model.In addition,this paper also presents the variability in the trajectory associated with the climatic variables with the changing climate in the study site.Nonparametric Mann-Kendall(MK) test was used to investigate and understand the mean monthly trendof eight climatic parameters including reference evapotranspiration(ET_0) for the period of 1985-2009.Trend of ET_0 was estimated for the calculations done by FAO PM equation.The outcomes of the trend analysis show significant increasing(p ≤ 0.05) trend represented by higher Z-values,through MK test,for net radiation(Rn),maximum temperature(Tmax) and minimum temperature(Tmin),especially in the first months of the year.Whereas,significant(0.01 ≥ p ≤0.05) decreasing trend in vapor pressure deficit(VPD)and precipitation(P) is observed throughout the year.Declining trend in sunshine duration,VPD and ET_0 is found in spring(March- May) and monsoon(June –November) season.The result displays significant(0.01≤ p ≤ 0.05) decreasing ET_0 trend between(June- December) except in July,exhibiting the positive relation with VPD followed by sunshine duration at the station.Overall,the study emphasizes the importance of trend analysis of ET_0 and other climaticvariables for efficient planning and managing the agricultural practices,in identifying the changes in the meteorological parameters and to accurately assess the hydrologic water balance of the hilly regions.     

Assessment of urban heat island effect for different land use–land cover from micrometeorological measurements and remote sensing data for megacity Delhi

Urban heat island intensities (UHI) have been assessed based on in situ measurements and satellite-derived observations for the megacity Delhi during a selected period in March 2010. A network of micrometeorological observational stations was set up across the city. Site selection for stations was based on dominant land use–land cover (LULC) classification. Observed UHI intensities could be classified into high, medium and low categories which overall correlated well with the LULC categories viz. dense built-up, medium dense built-up and green/open areas, respectively. Dense urban areas and highly commercial areas were observed to have highest UHI with maximum hourly magnitude peaking up to 10.7 °C and average daily maximum UHI reaching 8.3 °C. UHI obtained in the study was also compared with satellite-derived land surface temperatures (LST). UHI based on in situ ambient temperatures and satellite-derived land surface temperatures show reasonable comparison during nighttime in terms of UHI magnitude and hotspots. However, the relation was found to be poor during daytime. Further, MODIS-derived LSTs showed overestimation during daytime and underestimation during nighttime when compared with in situ skin temperature measurements. Impact of LULC was also reflected in the difference between ambient temperature and skin temperature at the observation stations as built-up canopies reported largest gradient between air and skin temperature. Also, a comparison of intra-city spatial temperature variations based UHI vis-à-vis a reference rural site temperature-based UHI indicated that UHI can be computed with respect to the station measuring lowest temperature within the urban area in the absence of a reference station in the rural area close to the study area. Comparison with maximum and average UHI of other cities of the world revealed that UHI in Delhi is comparable to other major cities of the world such as London, Tokyo and Beijing and calls for mitigation action plans.