Yield Forecasting of Spring Maize Using Remote Sensing and Crop Modeling in Faisalabad-Punjab Pakistan

Real time, accurate and reliable estimation of maize yield is valuable to policy makers in decision making. The current study was planned for yield estimation of spring maize using remote sensing and crop modeling. In crop modeling, the CERES-Maize model was calibrated and evaluated with the field experiment data and after calibration and evaluation, this model was used to forecast maize yield. A Field survey of 64 farm was also conducted in Faisalabad to collect data on initial field conditions and crop management data. These data were used to forecast maize yield using crop model at farmers’ field. While in remote sensing, peak season Landsat 8 images were classified for landcover classification using machine learning algorithm. After classification, time series normalized difference vegetation index (NDVI) and land surface temperature (LST) of the surveyed 64 farms were calculated. Principle component analysis were run to correlate the indicators with maize yield. The selected LSTs and NDVIs were used to develop yield forecasting equations using least absolute shrinkage and selection operator (LASSO) regression. Calibrated and evaluated results of CERES-Maize showed the mean absolute % error (MAPE) of 0.35–6.71% for all recorded variables. In remote sensing all machine learning algorithms showed the accuracy greater the 90%, however support vector machine (SVM-radial basis) showed the higher accuracy of 97%, that was used for classification of maize area. The accuracy of area estimated through SVM-radial basis was 91%, when validated with crop reporting service. Yield forecasting results of crop model were precise with RMSE of 255 kg ha^?1, while remote sensing showed the RMSE of 397 kg ha^?1. Overall strength of relationship between estimated and actual grain yields were good with R² of 0.94 in both techniques. For regional yield forecasting remote sensing could be used due greater advantages of less input dataset and if focus is to assess specific stress, and interaction of plant genetics to soil and environmental conditions than crop model is very useful tool.     

Wind-driven estuarine turbidity maxima in Mandovi Estuary,central west coast of India

Systematic studies on the suspended particulate matter (SPM) measured on a seasonal cycle in the Mandovi Estuary, Goa indicate that the average concentrations of SPM at the regular station are ∼20mg/l, 5mg/l, 19mg/l and 5mg/l for June–September, October–January, February–April and May, respectively. SPM exhibits low-to-moderate correlation with rainfall indicating that SPM is also influenced by other processes. Transect stations reveal that the SPM at sea-end stations of the estuary are at least two orders of magnitude greater than those at the river-end during the monsoon. Estuarine turbidity maximum (ETM) of nearly similar magnitude occurs at the same location in two periods, interrupted by a period with very low SPM concentrations. The ETM occurring in June–September is associated with low salinities; its formation is attributed to the interactions between strong southwesterly winds (5.1–5.6ms⁻¹) and wind-induced waves and tidal currents and, dominant easterly river flow at the mouth of the estuary. The ETM occurring in February–April is associated with high salinity and is conspicuous. The strong NW and SW winds (3.2–3.7ms⁻¹) and wind-driven waves and currents seem to have acted effectively at the mouth of the estuary in developing turbidity maximum. The impact of sea breeze appears nearly same as that of trade winds and cannot be underestimated in sediment resuspension and deposition     

Spatial dimension of impact,relief, and rescue of the 2014 flood in Kashmir Valley

Flood relief and rescue form an important basis of disaster management, and the assessment of flood damage is a critical component of flood risk management. In its recent history, Kashmir Valley witnessed the floods in 2014, 2015, 2017, 2019, 2020, and 2021, but the worst flood in the living memory of the people was witnessed in the year 2014, which created widespread loss in economic and societal aspects. The present study discusses the spatial dimension of impact, relief, and rescue of the flood of 2014 in the Kashmir Valley. It analyses the distribution of relief and politics of relief and rescue and highlights the role of the communitarianism and the heroics of the community members in dealing with floods. The study provides the data of relief distribution under different government schemes and reveals that the relief was not distributed equally in various districts of the valley. The study relies on primary and secondary sources of data. Ethnographic approach was used for acquiring primary data because it provides the complex narratives of disasters and the political and social rupture experienced during the disasters. The data have been analysed with the help of Geographic Information System.

     

Variation of paleo-productivity and terrigenous input in the Eastern Arabian Sea during the past 100 ka

A 4.1 m long sediment core from the Eastern Arabian Sea (EAS) is studied using multiple geochemical proxies to understand the variation of productivity and terrigenous matter supply during the past 100 ka. The temporal variation in element concentration and fluxes of CaCO₃, organic carbon (C_org) and Barium excess (Ba_exc), together, in general indicate a higher productivity during the cold climate and highest during the Last Glacial Maximum (LGM) in particular. This cold climate-increased productivity coupling may be attributed to the shoaling of nutricline due to enhanced convective mixing resulting from the intensified winter monsoon. Increased linear sedimentation rates and fluxes of Al, Fe, Mg, Ti, Cr, Cu, Zn, and V during the cold period also suggest increased input of terrigenous matter supporting intensified winter winds. However, the presence of large abundance of structurally unsupported elemental content (e.g.: Mg-86%, Fe-82% and Al-53%) indicate increased input of terrigenous material which was probably enhanced due to intense winter monsoon.     

Characterization of regional hydrological drought using improved precipitation records under multi-auxiliary information

Theoretical and Applied Climatology - Drought is a complex natural hazard that has been recurrently occurred in many regions across the globe. Therefore, precise drought characterization and its...