The best and commonly used ground-based sensor to monitor crop growth, ASD FieldSpecPro Spectroradiometer (Analytical Spectral Devices, Boulder, CO, USA) is a passive sensor, which can be used under adequate light condition. However, now-a-days active sensors such as GreenSeeker? (GS) handheld crop response (Trimble Agriculture division, USA) are used for monitoring crop growth and are flexible in terms of timeliness and illumination conditions besides being cheaper than the ASD. Before its wide use, the suitability and accuracy of GS should be assessed by comparing the NDVI measured by this instrument with that by ASD, under diverse wheat growing conditions of India. Keeping this in view, the present experiment was undertaken with the following objectives: (1) to find out the temporal variation of NDVI measured both by ASD and GS treatments, (2) to find out relationship between the NDVI measured through ASD and GS and, (3) to evaluate the suitability of GS for NDVI measurements. It was observed that the numerical value of NDVI as measured by GS was always significantly (P < 0.05) lower than that measured by ASD for all the experiments under study. The NDVI-ASD and NDVI-GS were significantly positively correlated (P < 0.01) with the correlation coefficients being +0.94, +0.88 and +0.87 for irrigation and nitrogen experiment, irrigation and cultivars experiment, and tillage, residue and nitrogen experiments, respectively. Further, the regression equation developed between the NDVI-ASD and NDVI-GS: [NDVI-GS = 1.070 × (NDVI-ASD ? 0.292] can be successfully used to compute the NDVI of ASD from that computed by GS. 相似文献
Reservoir sedimentation is the gradual accumulation of incoming sediments from upstream catchment leading to the reduction in useful storage capacity of the reservoir. Quantifying the reservoir sedimentation rate is essential for better water resources management. Conventional techniques such as hydrographic survey have limitations including time-consuming, cumbersome and costly. On the contrary, the availability of high resolution (both spatial and temporal) in public domain overcomes all these constraints. This study assessed Jayakwadi reservoir sedimentation using Landsat 8 OLI satellite data combined with ancillary data. Multi-date remotely sensed data were used to produce the water spread area of the reservoir, which was applied to compute the sedimentation rate. The revised live storage capacity of the reservoir between maximum and minimum levels observed under the period of analysis (2015–2017) was assessed utilizing the trapezoidal formula. The revised live storage capacity is assessed as 1942.258 against the designed capacity of 2170.935 Mm3 at full reservoir level. The total loss of reservoir capacity due to the sediment deposition during the period of 41 years (1975–2017) was estimated as 228.677 Mm3 (10.53%) which provided the average sedimentation rate of 5.58 Mm3 year1. As this technique also provides the capacity of the reservoir at the different elevation on the date of the satellite pass, the revised elevation–capacity curve was also developed. The sedimentation analysis usually provides the volume of sediment deposited and rate of the deposition. However, the interest of the reservoir authorities and water resources planner’s lies in sub-watershed-wise sediment yield, and the critical sub-watersheds upstream reservoir requires conservation, etc. Therefore, in the present study, Soil and Water Assessment Tool (SWAT) was used for the estimation of sediment yield of the reservoir. The average annual sediment yield obtained from the SWAT model using 36 years of data (1979–2014) was 13.144 Mm3 year?1 with the density of the soil (loamy and clay) of 1.44 ton m?3. The findings revealed that the rate of sedimentation obtained from the remote sensing-based methods is in agreement with the results of the hydrographic survey. 相似文献
This study presents the chemical composition (carbonaceous and nitrogenous components) of aerosols (PM2.5 and PM10) along with stable isotopic composition (δ13C and δ15N) collected during winter and the summer months of 2015–16 to explore the possible sources of aerosols in megacity Delhi, India. The mean concentrations (mean?±?standard deviation at 1σ) of PM2.5 and PM10 were 223?±?69 µg m?3 and 328?±?65 µg m?3, respectively during winter season whereas the mean concentrations of PM2.5 and PM10 were 147?±?22 µg m?3 and 236?±?61 µg m?3, respectively during summer season. The mean value of δ13C (range: ??26.4 to ??23.4‰) and δ15N (range: 3.3 to 14.4‰) of PM2.5 were ??25.3?±?0.5‰ and 8.9?±?2.1‰, respectively during winter season whereas the mean value of δ13C (range: ??26.7 to ??25.3‰) and δ15N (range: 2.8 to 11.5‰) of PM2.5 were ??26.1?±?0.4‰ and 6.4?±?2.5‰, respectively during the summer season. Comparison of stable C and N isotopic fingerprints of major identical sources suggested that major portion of PM2.5 and PM10 at Delhi were mainly from fossil fuel combustion (FFC), biomass burning (BB) (C-3 and C-4 type vegitation), secondary aerosols (SAs) and road dust (SD). The correlation analysis of δ13C with other C (OC, TC, OC/EC and OC/WSOC) components and δ15N with other N components (TN, NH4+ and NO3?) are also support the source identification of isotopic signatures.
Theoretical and Applied Climatology - Sudden stratospheric warmings (SSWs) are associated with rapid rise in temperature in a short period of time in the polar vortex and reversal of the zonal... 相似文献
Theoretical and Applied Climatology - The present study examines the effects of convective available potential energy (CAPE), temperature and humidity on the spatiotemporal variation of... 相似文献
Theoretical and Applied Climatology - Spatial variability in catchment processes is crucial for hydrologic and water resources planning and management. The spatial density of ground-based rain... 相似文献
Theoretical and Applied Climatology - This paper presents a composite approach for drought characterization and monitoring using in situ and remote sensing-based drought indicators. The study was... 相似文献
In this study we present the seasonal chemical characteristics and potential sources of PM10 at an urban location of Delhi, India during 2010?2019. The concentrations of carbonaceous aerosols [organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC) and water insoluble organic carbon (WIOC)] and elements (Al, Fe, Ti, Cu, Zn, Mn, Pb, Cr, F, Cl, Br, P, S, K, As, Na, Mg, Ca, B, Ni, Mo, V, Sr, Zr and Rb) in PM10 were estimated to explore their possible sources. The annual average concentration (2010–2019) of PM10 was computed as 227?±?97 µg m?3 with a range of 34?734 µg m?3. The total carbonaceous aerosols in PM10 was accounted for 22.5% of PM10 mass concentration, whereas elements contribution to PM10 was estimated to be 17% of PM10. The statistical analysis of OC vs. EC and OC vs. WSOC of PM10 reveals their common sources (biomass burning and/or fossil fuel combustion) during all the seasons. Enrichment factors (EFs) of the elements and the relationship of Al with other crustal metals (Fe, Ca, Mg and Ti) of PM10 indicates the abundance of mineral dust over Delhi. Principal component analysis (PCA) extracted the five major sources [industrial emission (IE), biomass burning?+?fossil fuel combustion (BB?+?FFC), soil dust, vehicular emissions (VE) and sodium and magnesium salts (SMS)] of PM10 in Delhi, India. Back trajectory and cluster analysis of airmass parcel indicate that the pollutants approaching to Delhi are mainly from Pakistan, IGP region, Arabian Sea and Bay of Bengal.
The seasonal variation of particulate matter and its relationship with meteorological parameters were measured at five different residential sites in Delhi. Sampling was carried out for one year including all three seasons (summer, monsoon, and winter). The yearly average concentration of particulate matter (PM2.5) was 135.16 ± 41.34 µg/m3. The highest average values were observed in winter (208.44 ± 43.67 µg/m3) and the lowest during monsoon season (80.29 ± 39.47 µg/m3). The annual average concentration of PM2.5 was found to be the highest at the Mukherjee Nagar site (242.16 µg/m3 ) during the winter and lowest at (Jawaharlal Nehru University) JNU (35.65 µg/m3) during the monsoon season. The strongest correlation between PM mass and a meteorological parameter was a strong negative correlation with temperature (R2=0.55). All other parameters were weakly correlated (R2<0.2) with PM mass.
The occurrence of uranium in groundwater is of particular interest due to its toxicological and radiological properties. It has been considered as a relevant contaminant for drinking water even at a low concentration. Uranium is a ubiquitously occurring radionuclide in the environment. Four hundred and fifty-six (456) groundwater samples from different locations of five districts of South Bihar (SB) were collected and concentrations of uranium (U) were analyzed using a light-emitting diode (LED) fluorimetric technique. Uranium concentrations in groundwater samples varied from 0.1 µg l?1 to 238.2 µg l?1 with an average value of 12.3 µg l?1 in five districts of Bihar in the mid-eastern Gangetic plain. This study used hot spot spatial statistics to identify the distribution of elevated uranium concentration in groundwater. The hypothesis whether spatial distribution of high value and low value of U is more likely spatially clustered due to random process near a uranium hotspot in groundwater was tested based on z score and Getis-Ord Gi* statistics. The method implemented in this study, can be utilized in the field of risk assessment and decision making to locate potential areas of contamination. 相似文献
