Effect of spatial distribution of daily rainfall on interior catchment response of a distributed hydrological model

International audienceWe investigate the effect of spatial variability of daily rainfall on soil moisture, groundwater level and discharge using a physically-based, fully-distributed hydrological model. This model is currently in use with the district water board and is considered to represent reality. We focus on the effect of rainfall spatial variability on day-to-day variability of the interior catchment response, as well as on its effect on the general hydrological behaviour of the catchment. The study is performed in a flat rural catchment (135 km2) in the Netherlands, where the climate is semi-humid (average precipitation 800 mm/year, evapotranspiration 550 mm/year) and rainfall is predominantly stratiform (i.e. large scale). Both range-corrected radar data (resolution 2.5×2.5 km2) as well as data from a dense network of 30 raingauges are used, observed for the period March?October 2004. Eight different rainfall scenarios, either spatially distributed or spatially uniform, are used as input for the hydrological model. The main conclusions from this study are: (i) using a single raingauge as rainfall input carries a great risk for the prediction of discharge, groundwater level and soil moisture, especially if the raingauge is situated outside the catchment; (ii) taking into account the spatial variability of rainfall instead of using areal average rainfall as input for the model is needed to get insight into the day-to-day spatial variability of discharge, groundwater level and soil moisture content; (iii) to get insight into the general behaviour of the hydrological system it is sufficient to use correct predictions of areal average rainfall over the catchment

The relationship between time series models for water table depth and physical information

The relationship between parameters of autoregressive moving average exogenous variable (ARMAX) models and physical information that can be derived from databases such as digital topographical maps, digital elevation maps and soil profile descriptionswas investigated at 51 sites with open sandy soils in the Pleistocene part of the Netherlands, The ARMAX parameters appeared to be weakly related with physical information. Water-table depth predicted with ARMAX models which were guessed using physical information have large systematic errors but relatively small random errors. It is concluded that the relationships between time series model paremters and physical information can be improved with respect to the modelling as well as the quality of the data used

Understanding the heterogeneity of high-grade CIN lesions: Chromosomal and epigenetic analysis

Snijders, P.J.F. [Promotor]Meijer, C.J.L.M. [Promotor]Steenbergen, R.D.M. [Copromotor

Особливості правової моделі ханафітського мазгабу

Статья Исмагилова С.В. «Особенности правовой модели ханафитского мазхаба» исследует возникновение и развитие ханафитского мазхаба – правовой школы имама Абу Ханифы. В работе автор исследует источники фикха, феномен возникновения мазхабов и особенности правовой модели ханафитского мазхаба. В статье подчеркивается, что мазхаб ханафитов явился результатом научно-правовой деятельносты не только самого Абу Ханифы, но также и его учеников. Ключевые слова: ханафитский мазхаб, мусульманское право, иджтихад.The article by Ismagilov S.V. "Features of the jural model of the Hanafi school of thought" investigates the origin and development of the Hanafi school of thought - the juridical school of Imam Abu Hanifa. In this paper, the author analyses the sources of fiqh, the phenomenon of emergence of schools of thought and peculiarities of the juridical model of the Hanafi school of thought. The paper stresses that Madh'hab Hanafi is a product of scientific and jural activities not only of Abu Hanifa, but his disciples also. Key-words: juridical school of Abu Hanifa, Moslem jury, idgtikhad

Прогнозирование временного сопротивления разрыву малоуглеродистой низколегированной арматурной стали на основе системы частных регрессионных моделей

Предложен способ декомпозиции многофакторной регрессионной модели прогнозирования механических свойств арматурного проката. Обоснована система частных регрессионных моделей прогнозирования временного сопротивления разрыву арматурного проката. Показано, что полученные результаты хорошо согласуются с экспериментальными данными

Гоголевские традиции в творчестве М. Булгакова

Model studies suggest that semiarid ecosystems with patterned vegetation can respond in a nonlinear way to climate change. This means that gradual changes can result in a rapid transition to a desertified state. Previous model studies focused on the response of patterned semiarid ecosystems to changes in mean annual rainfall. The intensity of rain events, however, is projected to change as well in the coming decades. In this paper, we study the effect of changes in rainfall intensity on the functioning of patterned semiarid ecosystems with a spatially explicit model that captures rainwater partitioning and runoff-runon processes with simple event-based process descriptions. Analytical and numerical analyses of the model revealed that rainfall intensity is a key parameter in explaining patterning of vegetation in semiarid ecosystems as low mean rainfall intensities do not allow for vegetation patterning to occur. Surprisingly, we found that, for a constant annual rainfall rate, both an increase and a decrease in mean rainfall intensity can trigger desertification. An increase negatively affects productivity as a greater fraction of the rainwater is lost as runoff. This can result in a shift to a bare desert state only if the mean rainfall intensity exceeds the infiltration capacity of bare soil. On the other hand, a decrease in mean rainfall intensity leads to an increased fraction of rainwater infiltrating in bare soils, remaining unavailable to plants. Our findings suggest that considering rainfall intensity as a variable may help in assessing the proximity to regime shifts in patterned semiarid ecosystems and that monitoring losses of resource through runoff and bare soil infiltration could be used to determine ecosystem resilience. Key Points Rainfall intensity controls patterning and the resilience of arid ecosystems Both an increase and decrease in rainfall intensity can trigger desertification In line with observations, three types of rain events were identified in our mode