Evapotranspiration is resilient in the face of land cover and climate change in a humid temperate catchment

In temperate humid catchments, evapotranspiration returns more than half of the annual precipitation to the atmosphere, thereby determining the balance available to recharge groundwaters and support stream flow and lake levels. Changes in evapotranspiration rates and, therefore, catchment hydrology could be driven by changes in land use or climate. Here, we examine the catchment water balance over the past 50 years for a catchment in southwest Michigan covered by cropland, grassland, forest, and wetlands. Over the study period, about 27% of the catchment has been abandoned from row‐crop agriculture to perennial vegetation and about 20% of the catchment has reverted to deciduous forest, and the climate has warmed by 1.14 °C. Despite these changes in land use, the precipitation and stream discharge, and by inference catchment‐scale evapotranspiration, have been stable over the study period. The remarkably stable rates of evapotranspirative water loss from the catchment across a period of significant land cover change suggest that rainfed annual crops and perennial vegetation do not differ greatly in evapotranspiration rates, and this is supported by measurements of evapotranspiration from various vegetation types based on soil water monitoring in the same catchment. Compensating changes in the other meteorological drivers of evaporative water demand besides air temperature—wind speed, atmospheric humidity, and net radiation—are also possible but cannot be evaluated due to insufficient local data across the 50‐year period. Regardless of the explanation, this study shows that the water balance of this landscape has been resilient in the face of both land cover and climate change over the past 50 years.     

Two dimensional electromagnetic shock structures in dense electron-positron-ion magnetoplasmas

Linear and nonlinear analysis of low frequency magnetoacoustic waves propagating at an angle θ with the ambient magnetic field are investigated in dense electron-positron-ion (e-p-i) plasmas using the quantum magnetohydrodynamic (QMHD) model. In this regard, a quantum Kadomtsev-Petviashvili-Burgers (KPB) equation is derived in the small amplitude limit. The stability of KPB equation is also presented. The variation of the nonlinear fast and slow magnetoacoustic shock waves with the positron concentration, kinematic viscosity, obliqueness parameter θ, and the magnetic field, are also investigated. It is observed that the aforementioned plasma parameters significantly modify the propagation characteristics of two dimensional nonlinear magnetoacoustic shock waves in dissipative quantum magnetoplasmas. The relevance of the present investigation with regard to dense astrophysical environments is also pointed out.     

Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space–time heterogeneity of rainfall observations make space–time estimation of precipitation a challenging task. In this paper we propose a Box–Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space–time monthly precipitation in the monsoon periods during 1974–2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by [11] is used for Bayesian non-stationary multivariate space–time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method.     

Effect of Shale Distribution on Hydrocarbon Sands Integrated with Anisotropic Rock Physics for AVA Modelling: A Case Study

Shales can be distributed in sand through four different ways; laminated, structural, dispersed and any combination of these aforementioned styles. A careful analysis of well log data is required for the determination of shale distribution in sand affecting its reservoir quality. The objective of this study is to characterize the effect of shale distribution on reservoir quality of sands using well log data. The correlation of well data in terms of lithology has revealed four sand and three shale layers in Lower Goru Formation acting as a major reservoir in the study area. Our results indicate that the laminated type of shale distribution prevails at the Basal sand level, which does not affect its reservoir quality greatly. The remaining layers of variable vertical extent show a variety of shale distribution models affecting their reservoir quality adversely. We also present anisotropic rock physics modelling for AVA analysis at Basal sand level.     

Validation of Chlorophyll-a Algorithms in the Coastal Waters of Bay of Bengal Initial Validation Results from OCM-2

In this paper we report chlorophyll measurements made during an ocean colour validation cruise in April 2011 of the research vessel, Sagar Paschimi in the coastal waters of Northern Bay of Bengal. The chlorophyll-a concentration in these waters range from 0.2 to 4.0 mg/m³. Chlorophyll-a concentration from OCM-2 was estimated using the global ocean colour algorithms namely, OC2, OC3, OC4 and Chl-a algorithms respectively. OCM data was processed using the global SeaWiFS Data Analysis System (SeaDAS) in which all the above mentioned algorithms are embedded for estimating the chlorophyll-a concentration. A comparative study was made between and in-situ and satellite derived chlorophyll-a concentration. Although the matchups between in-situ and satellite data from OCM-2 were sparse, it indicates that direct application of the standard SeaWiFS algorithm-the OC4-V4 algorithm—in the coastal waters of the Bay of Bengal will underestimate chlorophyll-a by up to 30%. The results show a good correlation with an R value of 0.61 using OC2 algorithm. However, all the other global algorithms over estimate the chlorophyll-a concentration even in low chlorophyll concentration range. The comparison between in-situ and all the existing chlorophyll algorithms shows the efficiency of these algorithms for quantification of chlorophyll in coastal waters and hence the need to develop regional algorithms and fluorescence based algorithms for better quantification.     

Analysis and farmers’ perception of climate change in the Kashmir Valley,India

Theoretical and Applied Climatology - Analysis of climatic variables is important for the detection and attribution of climate change trends and has received considerable attention from researchers...     

Indirect Effects of Salinity and Temperature on Kuwait’s Shrimp Stocks

Discharge of the Shatt Al-Arab is believed to be a dominating component of the northern Arabian Gulf’s ecology and largely responsible for productivity of Kuwait’s fisheries. With major construction of dams on the Tigris and Euphrates Rivers in Turkey, river discharge has been substantially reduced, and flooding essentially eliminated. We attempted to relate river flow and shrimp landings indirectly by correlating 19 years of salinity and temperature data from Kuwait’s waters with corresponding annual shrimp landings. For green tiger prawns (Penaeus semisulcatus), the combination of October salinities and January temperatures provided the best correlation (r = 0.67) with landings in the following shrimping season. For the combined landings of jinga and kiddi shrimps (Metapenaeus affinis and Parapenaeopsis stylifera, respectively), December salinity during season and May temperature prior to season resulted in the best correlation (r = 0.87). Landings of these two species also correlated well with spring and summer temperatures. Under normal conditions, late winter or early spring temperatures prior to fishing season influence recruitment of the green tiger prawn, whereas December salinities during harvest season influence the abundance of jinga–kiddi shrimps. With further reductions in the Shatt Al-Arab discharge and the elimination of flood events, Kuwait’s shrimp landings will most likely decrease over time.