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1.
ABSTRACT

Assessment of forecast precipitation is required before it can be used as input to hydrological models. Using radar observations in southeastern Australia, forecast rainfall from the Australian Community Climate Earth-System Simulator (ACCESS) was evaluated for 2010 and 2011. Radar rain intensities were first calibrated to gauge rainfall data from four research rainfall stations at hourly time steps. It is shown that the Australian ACCESS model (ACCESS-A) overestimated rainfall in low precipitation areas and underestimated elevated accumulations in high rainfall areas. The forecast errors were found to be dependent on the rainfall magnitude. Since the cumulative rainfall observations varied across the area and through the year, the relative error (RE) in the forecasts varied considerably with space and time, such that there was no consistent bias across the study area. Moreover, further analysis indicated that both location and magnitude errors were the main sources of forecast uncertainties on hourly accumulations, while magnitude was the dominant error on the daily time scale. Consequently, the precipitation output from ACCESS-A may not be useful for direct application in hydrological modelling, and pre-processing approaches such as bias correction or exceedance probability correction will likely be necessary for application of the numerical weather prediction (NWP) outputs.
EDITOR M.C. Acreman ASSOCIATE EDITOR A. Viglione  相似文献   

2.
Land surface processes and their initialisation are of crucial importance for Numerical Weather Prediction (NWP). Current land data assimilation systems used to initialise NWP models include snow depth analysis, soil moisture analysis, soil temperature and snow temperature analysis. This paper gives a review of different approaches used in NWP to initialise land surface variables. It discusses the observation availability and quality, and it addresses the combined use of conventional observations and satellite data. Based on results from the European Centre for Medium-Range Weather Forecasts (ECMWF), results from different soil moisture and snow depth data assimilation schemes are shown. Both surface fields and low-level atmospheric variables are highly sensitive to the soil moisture and snow initialisation methods. Recent developments of ECMWF in soil moisture and snow data assimilation improved surface and atmospheric forecast performance.  相似文献   

3.
ABSTRACT

“Panta Rhei – Everything Flows” is the science plan for the International Association of Hydrological Sciences scientific decade 2013–2023. It is founded on the need for improved understanding of the mutual, two-way interactions occurring at the interface of hydrology and society, and their role in influencing future hydrologic system change. It calls for strategic research effort focused on the delivery of coupled, socio-hydrologic models. In this paper we explore and synthesize opportunities and challenges that socio-hydrology presents for data-driven modelling. We highlight the potential for a new era of collaboration between data-driven and more physically-based modellers that should improve our ability to model and manage socio-hydrologic systems. Crucially, we approach data-driven, conceptual and physical modelling paradigms as being complementary rather than competing, positioning them along a continuum of modelling approaches that reflects the relative extent to which hypotheses and/or data are available to inform the model development process.
EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR not assigned  相似文献   

4.
ABSTRACT

“Panta Rhei – Everything Flows” is the science plan for the International Association of Hydrological Sciences scientific decade 2013–2023. It is founded on the need for improved understanding of the mutual, two-way interactions occurring at the interface of hydrology and society, and their role in influencing future hydrologic system change. It calls for strategic research effort focused on the delivery of coupled, socio-hydrologic models. In this paper we explore and synthesize opportunities and challenges that socio-hydrology presents for data-driven modelling. We highlight the potential for a new era of collaboration between data-driven and more physically-based modellers that should improve our ability to model and manage socio-hydrologic systems. Crucially, we approach data-driven, conceptual and physical modelling paradigms as being complementary rather than competing, positioning them along a continuum of modelling approaches that reflects the relative extent to which hypotheses and/or data are available to inform the model development process.
EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR not assigned  相似文献   

5.
The Canadian Land Surface Scheme (CLASS) was modified to correct an underestimation of the winter albedo in evergreen needleleaf forests. Default values for the visible and near‐infrared albedo of a canopy with intercepted snow, αVIS,cs and αNIR,cs, respectively, were too small, and the fraction of the canopy covered with snow, fsnow, increased too slowly with interception, producing a damped albedo response. A new model for fsnow is based on zI*, the effective depth of newly intercepted snow required to increase the canopy albedo to its maximum, which corresponds in the model with fsnow = 1. Snow unloading rates were extracted from visual assessments of photographs and modelled based on relationships with meteorological variables, replacing the time‐based method employed in CLASS. These parameterizations were tested in CLASS version 3.6 at boreal black spruce and jack pine forests in Saskatchewan, Canada, a subalpine Norway spruce and silver fir forest at Alptal, Switzerland, and a boreal maritime forest at Hitsujigaoka, Japan. Model configurations were assessed based on the index of agreement, d, relating simulated and observed daily albedo. The new model employs αVIS,cs = 0.27, αNIR,cs = 0.38 and zI* = 3 cm. The best single‐variable snow unloading algorithm, determined by the average cross‐site d, was based on wind speed. Two model configurations employing ensemble averages of the unloading rate as a function of total incoming radiation and wind speed, and air temperature and wind speed, respectively, produced larger minimum cross‐site d values but a smaller average. The default configuration of CLASS 3.6 produced a cross‐site average d from October to April of 0.58. The best model employing a single parameter (wind speed at the canopy top) for modelling the unloading rate produced an average d of 0.86, while the two‐parameter ensemble‐average unloading models produced a minimum d of 0.81 and an average d of 0.84. © 2015 Her Majesty the Queen in Right of Canada. Hydrological Processes published by John Wiley & Sons, Ltd.  相似文献   

6.
ABSTRACT

The old principle of parsimonious modelling of natural processes has regained its importance in the last few years. The inevitability of uncertainty and risk, and the value of stochastic modelling in dealing with them, are also again appreciated, after a period of growing hopes for radical reduction of uncertainty. Yet, in stochastic modelling of natural processes several families of models are used that are often non-parsimonious, unnatural or artificial, theoretically unjustified and, eventually, unnecessary. Here we develop a general methodology for more theoretically justified stochastic processes, which evolve in continuous time and stem from maximum entropy production considerations. The discrete-time properties thereof are theoretically derived from the continuous-time ones and a general simulation methodology in discrete time is built, which explicitly handles the effects of discretization and truncation. Some additional modelling issues are discussed with a focus on model identification and fitting, which are often made using inappropriate methods.

EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR S. Grimaldi  相似文献   

7.
ABSTRACT

Terrain variables are the main factors affecting the spatial distribution of snow cover. This paper aims to find a relationship between snow-cover area (SCA) and topographic variables (elevation, slope and aspect), using MODIS Terra data (MOD09A1) in parts of the Chenab basin, western Himalayas. The inter-annual variability of SCA% for each month has been analysed for the years 2000 to 2011. The analysis reveals that mean annual SCA value was maximum (37.89%) in 2005 and minimum (32.07%) in 2001. The slope classes with maximum and minimum SCA% are 5°–10° and 30°–35°, respectively. Among the 16 aspect classes, the ESE-facing slope evinces maximum SCA%. During the snow accumulation period, the expanse at 3600–4300 m elevation, and in the depletion period, 4300–5000 m elevation are found to have maximum rate of change in SCA% per 100 m rise in elevation, i.e. 3.37% and 3.67%, respectively.
EDITOR Z.W. Kundzewicz; ASSOCIATE EDITOR not assigned  相似文献   

8.
In this study, we evaluate uncertainties propagated through different climate data sets in seasonal and annual hydrological simulations over 10 subarctic watersheds of northern Manitoba, Canada, using the variable infiltration capacity (VIC) model. Further, we perform a comprehensive sensitivity and uncertainty analysis of the VIC model using a robust and state-of-the-art approach. The VIC model simulations utilize the recently developed variogram analysis of response surfaces (VARS) technique that requires in this application more than 6,000 model simulations for a 30-year (1981–2010) study period. The method seeks parameter sensitivity, identifies influential parameters, and showcases streamflow sensitivity to parameter uncertainty at seasonal and annual timescales. Results suggest that the Ensemble VIC simulations match observed streamflow closest, whereas global reanalysis products yield high flows (0.5–3.0 mm day−1) against observations and an overestimation (10–60%) in seasonal and annual water balance terms. VIC parameters exhibit seasonal importance in VARS, and the choice of input data and performance metrics substantially affect sensitivity analysis. Uncertainty propagation due to input forcing selection in each water balance term (i.e., total runoff, soil moisture, and evapotranspiration) is examined separately to show both time and space dimensionality in available forcing data at seasonal and annual timescales. Reliable input forcing, the most influential model parameters, and the uncertainty envelope in streamflow prediction are presented for the VIC model. These results, along with some specific recommendations, are expected to assist the broader VIC modelling community and other users of VARS and land surface schemes, to enhance their modelling applications.  相似文献   

9.
ABSTRACT

This study presents an adaptation of the double-ring infiltrometer (DRI) device, which allows several infiltration experiments to be conducted at the same location. Hence, it becomes possible to use the DRI method to investigate infiltration behaviour under different initial soil moisture conditions. The main feature is the splitting of the inner ring into two parts. While the lower part remains in the soil throughout the investigation period, the upper part is attached to the lower one just before the infiltration experiment. This method was applied to eight test sites in an Alpine catchment, covering different land-use/cover types. The results demonstrated the applicability of the adapted system and showed correlations between total water infiltration and initial soil moisture conditions on pastures, independent of the underlying soil type. In contrast, no correlation was found at forest sites or wetlands. Thus, the study emphasizes the importance of paying special attention to the impact of initial soil moisture conditions on the infiltration—and consequently the runoff behaviour—at managed areas. Given the differences in the total infiltrated water of between 30 and 1306 mm, consideration of the interplay between initial soil moisture conditions, land-use/cover type, and soil properties in rainfall–runoff models is a prerequisite to predict runoff production accurately.
EDITOR Z.W. Kundzewicz; ASSOCIATE EDITOR not assigned  相似文献   

10.
ABSTRACT

This study presents a systematic illustration quantifying how misleading the calibration results of a groundwater simulation model can be when recharge rates are considered as the model parameters to be estimated by inverse modelling. Three approaches to recharge estimation are compared: autocalibration (Model 1), the empirical return coefficient method (Model 2), and distributed hydrological modelling using the Soil and Water Assessment Tool, SWAT (Model 3). The methodology was applied in the Dehloran Plain, western Iran, using the MODFLOW modular flow simulator and the PEST method for autocalibration. The results indicate that, although Model 1 performed the best in simulating water levels at observation wells in the calibration stage, it did not perform satisfactorily in real future scenarios. Model 3, with SWAT-based recharge rates, performed better than the other models in the validation stage. By not evaluating the model performance solely on calibration results, we demonstrate the relative significance of using more accurate recharge estimates when calibrating groundwater simulation models.
EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR M. Besbes  相似文献   

11.
12.
Probable maximum flood (PMF) event estimation has challenged the scientific community for many years. Although the concept of the PMF is often applied, there is no consensus on the methods that should be applied to estimate it. In PMF estimation, the spatio-temporal representation of the probable maximum precipitation (PMP) as well as the choice of modelling approach is often not theoretically founded. Moreover, it is not clear how these choices influence PMF estimation itself. In this study, combinations of three different spatio-temporal PMP representations and three different modelling approaches are applied to determine the PMF of a mesoscale basin keeping the antecedent catchment conditions and the total precipitation amount constant. The nine resulting PMF estimations are used to evaluate each combination of methods. The results show that basic methods allow for a rough estimation of the PMF. In cases where a physically plausible and reliable estimation is required, sophisticated PMP and PMF estimation approaches are recommended.
EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR A. Viglione  相似文献   

13.
The Natural Resource Conservation Service – Curve Number (NRCS-CN) methodology is a widely used tool for estimating surface runoff, which is of prime importance in hydrological engineering, agricultural planning and management, environmental impact assessment, flood forecasting, and others fields. This article reviews the methodology and associated hydrological models used for runoff estimation along with their advantages and limitations. Furthermore, discussion focuses on the potential applications of Remote Sensing (RS) and Geographical Information System (GIS) techniques for estimating hydrological variables, such as rainfall, soil moisture and CN required for the NRCS-CN methodology, as well as future research and opportunities for improved runoff estimation at the macro scale.
EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR A. Efstratiadis  相似文献   

14.
ABSTRACT

In snow-dominated basins, collection of snow data while capturing its spatio-temporal variability is difficult; therefore, integrating assimilation products could be a viable alternative for improving streamflow simulation. This study evaluates the accuracy of daily snow water equivalent (SWE) provided by the SNOw Data Assimilation System (SNODAS) of the National Weather Service at a 1-km2 resolution for two basins in eastern Canada, where SWE is a critical variable intensifying spring runoff. A geostatistical interpolation method was used to distribute snow observations. SNODAS SWE products were bias-corrected by matching their cumulative distribution function to that of the interpolated snow. The corrected SWE was then used in hydrological modelling for streamflow simulation. The results indicate that the bias-correction method significantly improved the accuracy of the SNODAS products. Moreover, the corrected SWE improved the simulation performance of the peak values. Although the uncertainty of SNODAS estimates is high for eastern Canadian basins, they are still of great value for regions with few snow stations.  相似文献   

15.
In this study we quantify the spatial variability of seasonal water balances within the Omo-Ghibe River Basin in Ethiopia using methods proposed within the Prediction in Ungauged Basins initiative. Our analysis consists of: (1) application of the rainfall–runoff model HBV-Light to several sub-catchments for which runoff data are available, and (2) estimation of water balances in the remaining ungauged catchments through application of the model with regionalized parameters. The analyses of the resulting water balance outcomes reveal that the seasonal water balance across the Omo-Ghibe Basin is driven by precipitation regimes that change with latitude, from being strongly “seasonal” in the north to “precipitation spread throughout the year, but with a definite wetter season” in the south. The basin is divided into two distinct regions based on patterns of seasonal water balance and, in particular, seasonal patterns of soil moisture storage.
EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR A. Efstratiadis  相似文献   

16.
ABSTRACT

The Integrated Water Flow Model (IWFM), developed by the California Department of Water Resources, is an integrated hydrological model that simulates key flow processes including groundwater flows, streamflow, stream–aquifer interactions, rainfall–runoff and infiltration. It also simulates the agricultural water demand as a function of soil, crop and climatic characteristics, as well as irrigation practices, and allows the user to meet these demands through pumping and stream diversions. This study investigates the modelling performance of the groundwater module of IWFM using several hypothetical test problems that cover a wide range of settings and boundary conditions, by comparing the simulation results with analytical solutions, field and laboratory observations, or with results from MODFLOW outputs. The comparisons demonstrate that IWFM is capable of simulating various hydrological processes reliably.
EDITOR M.C. Acreman; ASSOCIATE EDITOR A. Efstratiadis  相似文献   

17.
Quantifying the relative contributions of different factors to runoff change is helpful for basin management, especially in the context of climate change and anthropogenic activities. The effect of snow change on runoff is seldom evaluated. We attribute the runoff change in the Heihe Upstream Basin (HUB), an alpine basin in China, using two approaches: a snowmelt-based water balance model and the Budyko framework. Results from these approaches show good consistency. Precipitation accounts for 58% of the increasing runoff. The contribution of land-cover change seems unremarkable for the HUB as a whole, where land-cover change has a major effect on runoff in each sub-basin, but its positive effect on increasing runoff in sub-basins 1 and 3 is offset by the negative effect in sub-basin 2. Snow change plays an essential role in each sub-basin, with a contribution rate of around 30%. The impact of potential evapotranspiration is almost negligible.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR S. Huang  相似文献   

18.
To facilitate precise and cost-effective watershed management, a simple yet spatially and temporally distributed hydrological model (DHM-WM) was developed. The DHM-WM is based on the Mishra-Singh version of the curve number method, with several modifications: The spatial distribution of soil moisture was considered in moisture updating; the travel time of surface runoff was calculated on a grid cell basis for routing; a simple tile flow module was included as an option. The DHM-WM was tested on a tile-drained agricultural watershed in Indiana, USA. The model with the tile flow module performed well in the study area, providing a balanced water budget and reasonable flow partitioning. The daily coefficient of determination and Nash-Sutcliffe coefficient were 0.58 and 0.56, for the calibration period, and 0.63 and 0.62 for the validation period. The DHM-WM also provides detailed information about the source areas of flow components, the travel time and pathways of surface runoff.
EDITOR A. Castellarin; ASSOCIATE EDITOR F.-J. Chang  相似文献   

19.
ABSTRACT

In this study, a hybrid factorial stepwise-cluster analysis (HFSA) method is developed for modelling hydrological processes. The HFSA method employs a cluster tree to represent the complex nonlinear relationship between inputs (predictors) and outputs (predictands) in hydrological processes. A real case of streamflow simulation for the Kaidu River basin is applied to demonstrate the efficiency of the HFSA method. After training a total of 24?108 calibration samples, the cluster tree for daily streamflow is generated based on a stepwise-cluster analysis (SCA) approach and is then used to reproduce the daily streamflows for calibration (1995–2005) and validation (2008–2010) periods. The Nash-Sutcliffe coefficients for calibration and validation are 0.68 and 0.65, respectively, and the deviations of volume are 1.68% and 4.11%, respectively. Results show that: (i) the HFSA method can formulate a SCA-based hydrological modelling system for streamflow simulation with a satisfactory fitting; (ii) the variability and peak value of streamflow in the Kaidu River basin can be effectively captured by the SCA-based hydrological modelling system; (iii) results from 26 factorial experiments indicate that not only are minimum temperature and precipitation key drivers of system performance, but also the interaction between precipitation and minimum temperature significantly impacts on the streamflow. The findings are useful in indicating that the streamflow of the study basin is a mixture of snowmelt and rainfall water.
EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR G. Thirel  相似文献   

20.
This study aimed to quantify possible climate change impacts on runoff for the Rheraya catchment (225 km2) located in the High Atlas Mountains of Morocco, south of Marrakech city. Two monthly water balance models, including a snow module, were considered to reproduce the monthly surface runoff for the period 1989?2009. Additionally, an ensemble of five regional climate models from the Med-CORDEX initiative was considered to evaluate future changes in precipitation and temperature, according to the two emissions scenarios RCP4.5 and RCP8.5. The future projections for the period 2049?2065 under the two scenarios indicate higher temperatures (+1.4°C to +2.6°C) and a decrease in total precipitation (?22% to ?31%). The hydrological projections under these climate scenarios indicate a significant decrease in surface runoff (?19% to ?63%, depending on the scenario and hydrological model) mainly caused by a significant decline in snow amounts, related to reduced precipitation and increased temperature. Changes in potential evapotranspiration were not considered here, since its estimation over long periods remains a challenge in such data-sparse mountainous catchments. Further work is required to compare the results obtained with different downscaling methods and different hydrological model structures, to better reproduce the hydro-climatic behaviour of the catchment.
EDITOR M.C. Acreman

ASSOCIATE EDITOR R. Hirsch  相似文献   

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