Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere最新文献

Daily satellite precipitation estimates have become available for the first time by the Global Precipitation Climatology Project. The experimental version of the GPCP-1DD product, recently launched and available from NASA, provides the research community with 1 degree daily precipitation fields exclusively computed from satellite measurements. These comprise IR estimates from geostationary satellites and SSM/I data in the tropics as well as TOVS data from polar orbiting satellites at higher latitudes. The purpose of the present study is to verify the TOVS based GPCP-1DD rain rates over Central Europe with the surface precipitation measured with the dense rain gauge network operated during The Mesoscale Alpine Programme (MAP). 3 100 high quality daily rain gauge measurements during June/July 1997 have been objectively analyzed on the grid of the GPCP-1DD products. Verification results are given here in terms of difference fields (mean error=−0.59 mm/day), correlation coefficients (mean monthly value =0.57) as well as accuracy scores (probability of detection=0.6, false alarm ratio=0.2) and skill scores (true skill statistics=0.36). These scores are slightly inferior than those known from NWP model verifications.

The objective of this study is the assessment of a catchment water quality model towards its suitability for simulation of solute transport and nitrogen budgets and application in river basin management. The conceptual semi-distributed water budget and water quality model NPSM (Non Point Source Model) was applied in the meso-scale Brugga catchment (39,9 km²) in southwest Germany. Spatial distribution was achieved by classifying sub-areas based on the concept of hydrological chemical response units (CHRUs).

Parameter values for the runoff and nitrogen simulation were estimated from catchment properties, previous experimental and modelling studies, regional field studies and literature. Optimization of the parameter values, calibration of the model and validation of the simulation was achieved using the runoff curve, concentrations of nitrate and natural tracers. Sensitivity analysis revealed that only a few parameters were important for the simulation of runoff and the dynamics of the nitrogen fluxes. The simulated nitrate concentrations were strongly controlled by the nitrogen input, the water movements and the nitrogen reactions in the different sub-areas. Due to the lack of data, the parameterization of the nitrogen contents and reactions in the soil remained uncertain.

As a result of this study NPSM proved to be applicable in a meso-scale catchment performing satisfactory results for the simulation of stream flow. However the short time dynamics of the measured nitrate could not be fitted by the nitrogen simulation. An improvement of the short time performance can only be achieved using a more detailed soil and agricultural data basis. To evaluate the suitability of the model as a tool for river basin management, simulations for longer time periods and with additional nutrients have to be performed.

Land use changes over a 30 year period (1961–1990) have been incorporated into a continuous simulation rainfall runoff model to investigate the effect of these changes on flood frequency in the Thames catchment to its tidal limit at Kingston. The base map of land use in the Thames catchment uses a 50m grid of 25 land use classes for 1990. For use in the rainfall runoff model these classes have been combined into six land use types. Statistics of percentage change for four land use categories, cultivated land, permanent grassland, woodland and urban areas, are available back to 1945, calculated every five years. These statistics are at a county level and were related to the six land use types used in the rainfall runoff model to assess the flood frequency changes in the Thames catchment in relation to land use. Broad scale changes in land use over the last 120 years in the Thames catchment were also determined from a variety of sources.

Recently, dramatic flooding occurred in several regions of the world. To investigate the causes of the flooding and the influence of land use, soil characteristics and antecedent catchment moisture conditions, the distributed catchment model LISFLOOD has been developed. LISFLOOD simulates runoff in large river basins. Two transnational European river basins are used to test and validate the model: the Meuse catchment (France, Belgium, Germany and The Netherlands) and the Oder basin (The Czech Republic, Poland and Germany). In the Meuse and Oder catchment, land use change information over the past 200 years is processed at the moment. The LISFLOOD simulation model is used to simulate the effects of these land use changes on floods. Some influences of land use and vegetation on the water balance are clear, such as the changing vegetation cover (leaf area index) which will influence evapotranspiration. However, not so much is known about the influences of vegetation on soil properties, which influencesinfiltration, soil water redistribution, throughflow and groundwater recharge.

Caribbean rainfall is affected by climate variability of Pacific and Atlantic origin, e.g. the El Nino-Southern Oscillation (ENSO) phenomenon, and variability in the North Atlantic High sea level pressure (SLP) center, respectively. During the lifetime of an ENSO cycle, the basin experiences dry and wet extremes. In the case of a warm event, the dry extreme precedes the mature ENSO phase, and can be explained in terms of a direct response to the atmospheric anomaly generated by the warm sea surface temperatures (SST) in the eastern equatorial Pacific. The wet extreme follows the mature phase, and is consistent with the lagged warming effect of ENSO on tropical North Atlantic SSTs. The wintertime state of the North Atlantic High is hypothesized to affect Caribbean rainfall through its effect on tropical SST. A strong North Atlantic High SLP center during the early months of the calendar year strengthens the trade winds, hence cooling SSTs in the tropical latitudes of the North Atlantic. The effect lingers on most noticeably until the start of the Caribbean rainy season, in May–June, when cool SSTs are associated with deficient rainfall in the basin.

One of the objectives of EU-project ALPCLIM is the generation of a gridded data-set of monthly instrumental precipitation data. The area of investigation covers the Alps and wide regions of the surroundings from 4° to 18°E and 43° to 49° N. Grid distance is 1 deg longitude and 1 deg latitude. The project is not finished yet, more than 140 single series have been collected by now and are in the state of homogeneity testing and adjusting. The average linear distance of the stations is 75 km. Furthermore first results can be shown, dealing with the main purpose of the generation of the instrumental data-set within ALPCLIM—to use the instrumental data (both temperature and precipitation) to create a longer temperature proxi-data-set based on stable isotope ice core data from high elevation sites in the Monte Rosa and Mont Blanc region. The ice core temperature proxis are supposed to be at least 500 years long. The precipitation series will be used to analyse the problem that ice-cores in principle carry information only for precipitation days, not for all days. Analyses on daily temperature and precipitation data of 50 years series have shown already a way to construct “precipitation-mass weighted mean temperatures” for the longer series based on monthly values. The degree of correlation of those “precipitation-mass-weighted” temperatures with real temperatures will decide on the possibility to use stable isotope proxis from high level sites as temperature information. In addition to the described use within ALPCLIM, also projects like MAP may profit from the outcome of the ALPCLIM precipitation data-set. It will provide the MAP community with carefully homogenised monthly precipitation series to see the situation of MAP-results in a long-term context.

With the increasing scarcity of water and the need for real water saving measures, a clear understanding of the productivity of water is essential. For a basin in western Turkey, simulation modeling was performed at three different scales (field, irrigation scheme, and basin level) to obtain all terms of the water balance. These water balances were used to calculate the Productivity of Water (PW) at the three levels. Four PW indices were considered: PW_irrigated (yield / irrigation), PW_inflow (yield / net inflow), PW_depleted (yield / depletion), and PW_process (yield / process depletion), all expressed in kg yield per m³ water. Two cotton fields were considered at the field scale and it was found that the more upstream field performed better than the field at the tail-end since runoff from the upstream field was used by downstream users and was not considered as a loss. At the irrigation scheme level PW_irrigated was higher than at the individual cotton field level, since non-irrigated crops were also included. Other PW values were lower as crops more sensitive to drought were also found in the irrigated areas. Basin scale PWs were lower than those at the irrigation scheme, as large areas of the basin were covered with less productive land types. This study demonstrates that the PW indices provide quantitative measures of water dynamics. Models provide a useful methodology for extending field observation for the estimation of the indicators.

The short-term variation of discharge and solute concentration of the runoff of small catchments generally reflects the interplay of a variety of different processes. This makes the investigation of anthropogenic impacts on the catchment's runoff often rather difficult. On the other hand, short-term dynamics at the output boundary provide information about the system. This information can be used, in principle at least, to assess its long-term behaviour more precisely. In this paper examples of time series of sulphate and nitrate in the runoff of two small forested catchments are presented. To minimise the danger of over-parametrisation, the objective was to find a very simple empirical model to map a substantial portion of the observed variance (daily values). Here artificial neural networks were applied. They yield an efficiency of more than 0.7 for the solutes investigated, based on discharge depth and air temperature as input variables only. As a next step, the invariance of these relationships was investigated. In the case of sulphate, a significant trend is observed. However, it differs considerably for different subregions of the regression plane. Thus the neural network approach reveals a much more detailed insight into temporal shifts of the dynamics than an overall trend analysis.