14 research outputs found
Endometrial polypoid adenomyomatosis in a bitch with ovarian granulosa cell tumour and pyrometra.
Uterine malignant mixed Mullerian tumor (metaplastic carcinoma) in the cat: Clinicopathologic features and proliferation indices.
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Impact of climate change on European winter and summer flood losses
Climate change is expected to alter European floods and associated economic losses in various ways. Here we investigate the impact of precipitation change on European average winter and summer financial losses due to flooding under a 1.5 °C warming scenario (reflecting a projected climate in the year 2115 according to RCP2.6)and for a counterfactual current-climate scenario where the climate has evolved without anthropogenic influence (reflecting a climate corresponding to pre-industrial conditions). Climate scenarios were generated with the Community Atmospheric Model (CAM)version 5. For each scenario, we derive a set of weights that when applied to the current climate's precipitation results in a climatology that approximates that of the scenario. We apply the weights to annual losses from a well-calibrated (to the current climate)flood loss model that spans 50,000 years and re-compute the average annual loss to assess the impact of precipitation changes induced by anthropogenic climate change. The method relies on a large stochastic set of physically based flood model simulations and allows quick assessment of potential loss changes due to change in precipitation based on two statistics, namely total precipitation, and total precipitation of very wet days (defined here as the total precipitation of days above the 95th percentile of daily precipitation). We compute the statistics with the raw CAM precipitation and bias-corrected precipitation. Our results show that for both raw and bias-corrected statistics i)average flood loss in Europe generally tend to increase in winter and decrease in summer for the future scenario, and consistent with that change we also show that ii)average flood losses have increased (decreased)for winter (summer)from pre-industrial conditions to the current day. The magnitude of the change varies among scenarios and statistics chosen
Geomorphic Signatures on Brutsaert Base Flow Recession Analysis: case study of 27 Swiss catchments
Recession flow analysis are crucial in many areas of water resource management and useful to forecast base flow in gauged rivers. Moving from a classical recession curve analysis method, a large set of recession curves has been analyzed from Swiss streamflow data of 27 watersheds. For these catchments, digital elevation models have been precisely analyzed and a method aimed at the geomorphic origins of recession curves has been applied to the Swiss dataset. The method links river network morphology, epitomized by time-varying distribution of contributing channel sites, with the classic parametrization of recession events. This is done by assimilating two scaling exponents, and bG, with |dQ/dt|Q where Q is at-a-station gauged flow rate and N(l) G(l)bG where l is the downstream distance from the channel heads receding in time at constant speed c, N(l) is the number of draining channel reaches located at distance l from their heads, and G(l) is the total drainage network length at a distance greater or equal to l. We find that the method provides good results in catchments where drainage density can be regarded as spatially constant. We propose several corrections to the method accounting for arbitrary local drainage densities affecting the local drainage inflow per unit channel length. In particular, we relax the assumption of uniform constant speed c. Such corrections properly vanish when the local drainage density become spatially constant. Overall, definite geomorphic signatures are recognizable for recession curves. In general, we suggest that this conceptual model might be useful to estimate the low flow regime of natural ungauged basins by predicting its features solely from information remotely acquired and objectively manipulated through DEM data