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1.
《Advances in water resources》2005,28(1):15-32
The current practice for assessing spatial predictions from distributed hydrological models is simplistic, with visual inspection and occasional point observations generally used for model assessment. With the increasing availability of spatial observations from remote sensing and intensive field studies, the current methods for assessing the spatial component of model predictions need to advance. This paper emphasises the role that spatial field comparisons can play in model assessment. A review of the current methods used in hydrology, and other disciplines where spatial field comparisons are widely used, reveals some promising methods for quantitatively comparing spatial fields. These promising approaches––segmentation, importance maps, fuzzy comparison and multiscale comparison––are for local comparison of spatial fields. They address some of the weaknesses with the current approaches to spatial field comparison used in hydrological modelling and, in doing so, emulate some aspects of human visual comparison. The potential of these approaches for assessing spatial predictions and understanding model performance is illustrated with a simple example. 相似文献
2.
Recognizing spatial distribution patterns of grassland insects: neural network approaches 总被引：2，自引：1，他引：1
WenJun Zhang XiaoQing Zhong GuangHua Liu 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(2):207-216
The main objective of this study was to fit and recognize spatial distribution patterns of grassland insects using various
neural networks, and to analyze the feasibility of neural networks for detecting spatial distribution patterns of grassland
insects. BP neural network, Learning vector quantization (LVQ) neural network, linear neural network and Fisher’s linear discriminant
analysis were used to fit and recognize spatial distribution patterns at different ecological scales. Various comparisons
and analysis were conducted. The results showed that BP, LVQ and linear neural networks were better algorithms for recognizing
spatial distribution patterns of grassland insects. BP neural network was the best algorithm to fit spatial distribution patterns.
BP network may be used to recognize the spatial details of distribution patterns, and the recognition performance of BP network
became better as the increase of the number of hidden layers and neurons. Performance of linear neural network for pattern
recognition was similar to linear discrimination method. Linear neural network would yield better performance in finding the
general trends of distribution patterns. Recognition performance of LVQ network was just between BP network and linear network.
It was found that recognition performance of neural networks depended upon not only the ecological scale but also the criterion
for classification. Under the uniform criterion, recognition efficiency of linear methods tended to be weak as ecological
scale became to be coarser. A joint use of neural networks was suggested in order to achieve both overall and detailed understanding
on spatial distribution patterns. 相似文献
3.
Improvement of Global Hydrological Models Using GRACE Data 总被引：2，自引：0，他引：2
Andreas Güntner 《Surveys in Geophysics》2008,29(4-5):375-397
After about 6 years of GRACE (Gravity Recovery and Climate Experiment) satellite mission operation, an unprecedented global data set on the spatio-temporal variations of the Earth’s water storage is available. The data allow for a better understanding of the water cycle at the global scale and for large river basins. This review summarizes the experiences that have been made when comparing GRACE data with simulation results of global hydrological models and it points out the prerequisites and perspectives for model improvements by combination with GRACE data. When evaluated qualitatively at the global scale, water storage variations on the continents from GRACE agreed reasonably well with model predictions in terms of their general seasonal dynamics and continental-scale spatial patterns. Differences in amplitudes and phases of water storage dynamics revealed in more detailed analyses were mainly attributed to deficiencies in the meteorological model forcing data, to missing water storage compartments in the model, but also to limitations and errors of the GRACE data. Studies that transformed previously identified model deficiencies into adequate modifications of the model structure or parameters are still rare. Prerequisites for a comprehensive improvement of large-scale hydrological models are in particular the consistency of GRACE observation and model variables in terms of filtering, reliable error estimates, and a full assessment of the water balance. Using improvements in GRACE processing techniques, complementary observation data, multi-model evaluations and advanced methods of multi-objective calibration and data assimilation, considerable progress in large-scale hydrological modelling by integration of GRACE data can be expected. 相似文献
4.
ABSTRACTHigh-resolution data on the spatial pattern of water use are a prerequisite for appropriate and sustainable water management. Based on one well-validated hydrological model, the Distributed Time Variant Gains Model (DTVGM), this paper obtains reliable high-resolution spatial patterns of irrigation, industrial and domestic water use in continental China. During the validation periods, ranges of correlation coefficient (R) and Nash-Sutcliffe efficiency (NSE) coefficient are 0.67–0.96 and 0.51–0.84, respectively, between the observed and simulated streamflow of six hydrological stations, indicating model applicability to simulate the distribution of water use. The simulated water use quantities have relative errors (RE) less than 5% compared with the observed. In addition, the changes in streamflow discharge were also correctly simulated by our model, such as the Zhangjiafen station in the Hai River basin with a dramatic decrease in streamflow, and the Makou station in the Pearl River basin with no significant changes. These changes are combined results of basin available water resources and water use. The obtained high-resolution spatial pattern of water use could decrease uncertainty of hydrological simulation and guide water management efficiently.
Editor M.C. Acreman; Associate editor X. Fang 相似文献
5.
《中国科学:地球科学(英文版)》2021,(5)
Over the past decades, a number of water sciences and management programs have been developed to better understand and manage the water cycles at multiple temporal and spatial scales for various purposes, such as ecohydrology,global hydrology, sociohydrology, supply management, demand management, and integrated water resources management(IWRM). At the same time, rapid advancements have also been taking place in tracing, mapping, remote sensing, machine learning, and modelling technologies in hydrological research. Despite those programs and advancements, a water crisis is intensifying globally. The missing link is effective interactions between the hydrological research and water resource management to support implementation of the UN Sustainable Development Goals(SDGs) at multiple spatial scales. Since the watershed is the natural unit for water resources management, watershed science offers the potential to bridge this missing link.This study first reviews the advances in hydrological research and water resources management, and then discusses issues and challenges facing the global water community. Subsequently, it describes the core components of watershed science:(1)hydrological analysis;(2) water-operation policies;(3) governance;(4) management and feedback. The framework takes into account water availability, water uses, and water quality; explicitly focuses on the storage, fluxes, and quality of the hydrological cycle; defines appropriate local water resource thresholds through incorporating the planetary boundary framework; and identifies specific actionable measures for water resources management. It provides a complementary approach to the existing water management programs in addressing the current global water crisis and achieving the UN SDGs. 相似文献
6.
Distributed hydrological models can make predictions with much finer spatial resolution than the supporting field data. They will, however, usually not have a predictive capability at model grid scale due to limitations of data availability and uncertainty of model conceptualizations. In previous publications, we have introduced the Representative Elementary Scale (RES) concept as the theoretically minimum scale at which a model with a given conceptualization has a potential for obtaining a predictive accuracy corresponding to a given acceptable accuracy. The new RES concept has similarities to the 25‐year‐old Representative Elementary Area concept, but it differs in the sense that while Representative Elementary Area addresses similarity between subcatchments by sampling within the catchment, RES focuses on effects of data or conceptualization uncertainty by Monte Carlo simulations followed by a scale analysis. In the present paper, we extend and generalize the RES concept to a framework for assessing the minimum scale of potential predictability of a distributed model applicable also for analyses of different model structures and data availabilities. We present three examples with RES analyses and discuss our findings in relation to Beven's alternative blueprint and environmental modeling philosophy from 2002. While Beven here addresses model structural and parameter uncertainties, he does not provide a thorough methodology for assessing to which extent model predictions for variables that are not measured possess opportunities to have meaningful predictive accuracies, or whether this is impossible due to limitations in data and models. This shortcoming is addressed by the RES framework through its analysis of the relationship between aggregation scale of model results and prediction uncertainties and for considering how alternative model structures and alternative data availability affects the results. We suggest that RES analysis should be applied in all modeling studies that aim to use simulation results at spatial scales smaller than the support scale of the calibration data. 相似文献
7.
8.
Balzs M. Fekete John J. Gibson Pradeep Aggarwal Charles J. Vrsmarty 《Journal of Hydrology》2006,330(3-4):444-456
Isotope tracers are widely used to study hydrological processes in small catchments, but their use in continental-scale hydrological modeling has been limited. This paper describes the development of an isotope-enabled global water balance and transport model (iWBM/WTM) capable of simulating key hydrological processes and associated isotopic responses at the large scale. Simulations and comparisons of isotopic signals in precipitation and river discharge from available datasets, particularly the IAEA GNIP global precipitation climatology and the USGS river isotope dataset spanning the contiguous United States, as well as selected predictions of isotopic response in yet unmonitored areas illustrate the potential for isotopes to be applied as a diagnostic tool in water cycle model development. Various realistic and synthetic forcings of the global hydrologic and isotopic signals are discussed. The test runs demonstrate that the primary control on isotope composition of river discharge is the isotope composition of precipitation, with land surface characteristics and precipitation-amount having less impact. Despite limited availability of river isotope data at present, the application of realistic climatic and isotopic inputs in the model also provides a better understanding of the global distribution of isotopic variations in evapotranspiration and runoff, and reveals a plausible approach for constraining the partitioning of surface and subsurface runoff and the size and variability of the effective groundwater pool at the macro-scale. 相似文献
9.
湖泊是地球表层水体的重要组成部分,在区域社会经济发展和生物多样性保护等方面发挥着不可替代的作用.气候变化和高强度的水资源开发利用等,导致湖泊物理、化学特性在时空格局上发生显著的变化,引起一系列的社会、环境、气候等响应.湖泊水文学研究湖泊水文要素及其时空变化特征、平衡关系与变化规律,在水文过程演变与归因解析、湖泊洪旱发生机理与调控、湖泊资源评估与可持续利用等方面,解决了众多理论和实践问题,为区域发展提供了强大支撑.本文评述了近50年来我国湖泊水文学的发展与研究进展,重点阐述湖泊水量平衡与水量变化、湖泊水动力与水文过程调蓄、湖泊极端水文事件成因、湖泊水文遥感反演等方面的研究进展,展望了湖泊水文学的未来发展趋势. 相似文献
10.
The emergence of regional and global satellite‐based rainfall products with high spatial and temporal resolution has opened up new large‐scale hydrological applications in data‐sparse or ungauged catchments. Particularly, distributed hydrological models can benefit from the good spatial coverage and distributed nature of satellite‐based rainfall estimates (SRFE). In this study, five SRFEs with temporal resolution of 24 h and spatial resolution between 8 and 27 km have been evaluated through their predictive capability in a distributed hydrological model of the Senegal River basin in West Africa. The main advantage of this evaluation methodology is the integration of the rainfall model input in time and space when evaluated at the sub‐catchment scale. An initial data analysis revealed significant biases in the SRFE products and large variations in rainfall amounts between SRFEs, although the spatial patterns were similar. The results showed that the Climate Prediction Center/Famine Early Warning System (CPC‐FEWS) and cold cloud duration (CCD) products, which are partly based on rain gauge data and produced specifically for the African continent, performed better in the modelling context than the global SRFEs, Climate Prediction Center MORPHing technique (CMORPH), Tropical Rainfall Measuring Mission (TRMM) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). The best performing SRFE, CPC‐FEWS, produced good results with values of R2NS between 0·84 and 0·87 after bias correction and model recalibration. This was comparable to model simulations based on traditional rain gauge data. The study highlights the need for input specific calibration of hydrological models, since major differences were observed in model performances even when all SRFEs were scaled to the same mean rainfall amounts. This is mainly attributed to differences in temporal dynamics between products. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
11.
Streamflow variability in space and time critically affects anthropic water uses and ecosystem services. Unfortunately, spatiotemporal patterns of flow regimes are often unknown, as discharge measurements are usually recorded at a limited number of hydrometric stations unevenly distributed along river networks. Advances in understanding the physical processes that control the spatial patterns of river flows are therefore necessary to predict water availability at ungauged locations or to extrapolate pointwise streamflow observations. This work explores the use of the spatial correlation of river flows as a metric to quantify the similarity between hydrological responses of two catchments. Following a stochastic framework, 340,000 cross‐correlations between pairs of daily streamflows time series are predicted at a seasonal timescale across the contiguous United States using 413 catchments of the MOPEX dataset. Model predictions of streamflow correlation obtained in absence of run‐off information are successfully used to identify catchment outlets sharing similar discharge dynamics and flow regimes across a broad range of geomorphoclimatic conditions, without relying on calibration. The selection of reference streamgauges based on predicted streamflow correlation generally outperforms the selection based on spatial proximity, especially as the density of available gauged sections decreases. Interestingly, correlated outlets share a broad spectrum of hydrological signatures (mean discharge, flow variability, and recession properties), suggesting that catchments forced by analogous frequency and intensity of effective rainfall events might exhibit common geomorphoecological traits leading to similar hydrological responses. The proposed framework provides a physical basis to assist the regionalization of flow dynamics and to interpret the spatial variability of flow regimes along stream networks. 相似文献
12.
Long‐term observations are critical in hydrology to understand the dynamics of biological and physicochemical processes involved in and affected by the flux of water. Long‐term observations have been employed to provide basic understanding of the water cycle (e.g., infiltration, evaporation, run‐off generation, and groundwater–surface water interactions), but they are lacking in hydrologically relevant regions such as the Andes Mountains, including alpine watersheds. Although the call for long‐term data acquisition in Latin America has been made, the establishment of long‐term data collection centres remains logistically challenging. This ever‐growing scientific gap hinders our understanding of differences and similarities in hydrological processes of tropical and temperate regions. Furthermore, technological advances such as in situ optical sensors for water quantity and quality remain cost‐prohibitive for both short and long deployment at most existing research sites in Latin America, restricting researchers pursuing research funding or developing meaningful, intersite comparisons and syntheses. Here, we emphasize the importance of and need for rapid assessments (i.e., field campaigns conducted over a few days) for improved hypothesis development and mechanistic understanding of hydrological dynamics in Latin America. We report on rapid assessments conducted in the high‐elevation mountains (>3,000 m) of Colombia. Our results highlight rapidly changing dynamics in nutrient retention potential and dissolved CO2 (pCO2), as well as highly variable spatial distribution of water quality parameters (N, C, P, Cl) in areas with varying land use. We present an initial examination of the effects of land‐use change on stream nutrient dynamics in one of the most biodiverse and threatened ecosystems on Earth. We conclude that rapid assessments not only are necessary but also represent a cost‐effective way to develop clear, testable hypotheses to advance a hydrologic research agenda in Latin America and work towards long‐term hydrological knowledge and information for use by other scientists. 相似文献
13.
《水文科学杂志》2013,58(6):857-880
Abstract Drainage basins in many parts of the world are ungauged or poorly gauged, and in some cases existing measurement networks are declining. The problem is compounded by the impacts of human-induced changes to the land surface and climate, occurring at the local, regional and global scales. Predictions of ungauged or poorly gauged basins under these conditions are highly uncertain. The IAHS Decade on Predictions in Ungauged Basins, or PUB, is a new initiative launched by the International Association of Hydrological Sciences (IAHS), aimed at formulating and implementing appropriate science programmes to engage and energize the scientific community, in a coordinated manner, towards achieving major advances in the capacity to make predictions in ungauged basins. The PUB scientific programme focuses on the estimation of predictive uncertainty, and its subsequent reduction, as its central theme. A general hydrological prediction system contains three components: (a) a model that describes the key processes of interest, (b) a set of parameters that represent those landscape properties that govern critical processes, and (c) appropriate meteorological inputs (where needed) that drive the basin response. Each of these three components of the prediction system, is either not known at all, or at best known imperfectly, due to the inherent multi-scale space—time heterogeneity of the hydrological system, especially in ungauged basins. PUB will therefore include a set of targeted scientific programmes that attempt to make inferences about climatic inputs, parameters and model structures from available but inadequate data and process knowledge, at the basin of interest and/or from other similar basins, with robust measures of the uncertainties involved, and their impacts on predictive uncertainty. Through generation of improved understanding, and methods for the efficient quantification of the underlying multi-scale heterogeneity of the basin and its response, PUB will inexorably lead to new, innovative methods for hydrological predictions in ungauged basins in different parts of the world, combined with significant reductions of predictive uncertainty. In this way, PUB will demonstrate the value of data, as well as provide the information needed to make predictions in ungauged basins, and assist in capacity building in the use of new technologies. This paper presents a summary of the science and implementation plan of PUB, with a call to the hydrological community to participate actively in the realization of these goals. 相似文献
14.
15.
Bartel H. J. Van Nieuwenhuyse Michael Antoine Guido Wyseure Gerard Govers 《水文研究》2011,25(24):3760-3773
The degree of hydrological connectivity is mainly determined by the spatial organisation of heterogeneity. A meaningful and aggregate abstraction of spatial patterns is one of the promising means to gain fundamental insights into this complex interaction and can, moreover, be used as a tool to acquire a profound understanding of the major controls of catchment hydrology. In order to disclose such controls, pattern‐process relationships and the explanatory power of landscape metrics were tested by simulating the runoff of differently patterned virtual basins, generated by neutral landscape models and fractal networks and solved by a surface hydrological model composed of kinematic wave routing and Green‐Ampt infiltration. A total of 23 landscape metrics quantified the spatial patterns and were subsequently related to the functional connectivity, assessed as the proportion of internal runoff generation constituting the hydrological response at the outlet. Landscape metrics allowed the identification of dominant features of heterogeneity that explained the observed connectivity, and to disclose changes in control with class abundance. Therefore, landscape metrics are a useful tool for basin comparison and classification in terms of the dominant processes and the corresponding model structure requirements. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
16.
Petra Döll Hervé Douville Andreas Güntner Hannes Müller Schmied Yoshihide Wada 《Surveys in Geophysics》2016,37(2):195-221
Quantification of spatially and temporally resolved water flows and water storage variations for all land areas of the globe is required to assess water resources, water scarcity and flood hazards, and to understand the Earth system. This quantification is done with the help of global hydrological models (GHMs). What are the challenges and prospects in the development and application of GHMs? Seven important challenges are presented. (1) Data scarcity makes quantification of human water use difficult even though significant progress has been achieved in the last decade. (2) Uncertainty of meteorological input data strongly affects model outputs. (3) The reaction of vegetation to changing climate and CO2 concentrations is uncertain and not taken into account in most GHMs that serve to estimate climate change impacts. (4) Reasons for discrepant responses of GHMs to changing climate have yet to be identified. (5) More accurate estimates of monthly time series of water availability and use are needed to provide good indicators of water scarcity. (6) Integration of gradient-based groundwater modelling into GHMs is necessary for a better simulation of groundwater–surface water interactions and capillary rise. (7) Detection and attribution of human interference with freshwater systems by using GHMs are constrained by data of insufficient quality but also GHM uncertainty itself. Regarding prospects for progress, we propose to decrease the uncertainty of GHM output by making better use of in situ and remotely sensed observations of output variables such as river discharge or total water storage variations by multi-criteria validation, calibration or data assimilation. Finally, we present an initiative that works towards the vision of hyperresolution global hydrological modelling where GHM outputs would be provided at a 1-km resolution with reasonable accuracy. 相似文献
17.
Assessment of the impact of pools on the water isotopic signature of a boreal patterned peatland 
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下载免费PDF全文 Recent studies have shown that boreal peatlands exhibit considerable chemical variability but without clear spatial pattern. This chemical heterogeneity illustrates the complex hydrological behaviour of peatlands, particularly patterned fen. Isotopic, chemical and physical tracers were used to describe the hydrological behaviour of a small boreal headwater catchment (13 ha) during the snow‐free period with a special emphasis on the downstream patterned fen. Results showed that shallow pools were mixed every day during the summer, particularly during nights or discharge periods. Despite large water storage capacities in pools, which should induce large buffer effect, hydrological behaviour of patterned fen is more similar to a piston flow process. This is probably because of the division of the fen into successive small cascading streamflow reservoirs. The consequences were a rapid change of the chemical signature throughout the fen, particularly upstream. A spatial pattern was observed downstream in early summer. The isotopic signature passed from an upstream depleted and homogeneous signature to a progressively enriched downstream signature. However, this pattern was not identified during the wetter period (late summer), probably because the discharge, which dominated the water budget, decreased the surface water residence time and flushed a large proportion of stored surface water. We developed for this patterned fen a conceptual model of the surface flow to explain these particular mixing effects and the implications on the dynamics of the chemical signature. To further our understanding of similar boreal headwater catchments, future work should include the development of a multiple mixed‐reservoir model. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
18.
Qiuan Zhu Hong Jiang Xiaohua Wei Changhui Peng Xiuqing Fang Shirong Liu Guomo Zhou Shuquan Yu Weiming Ju 《水文研究》2010,24(4):429-445
The Integrated Biosphere Simulator is used to evaluate the spatial and temporal patterns of the crucial hydrological variables [run‐off and actual evapotranspiration (AET)] of the water balance across China for the period 1951–2006 including a precipitation analysis. Results suggest three major findings. First, simulated run‐off captured 85% of the spatial variability and 80% of the temporal variability for 85 hydrological gauges across China. The mean relative errors were within 20% for 66% of the studied stations and within 30% for 86% of the stations. The Nash–Sutcliffe coefficients indicated that the quantity pattern of run‐off was also captured acceptably except for some watersheds in southwestern and northwestern China. The possible reasons for underestimation of run‐off in the Tibetan plateau include underestimation of precipitation and uncertainties in other meteorological data due to complex topography, and simplified representations of the soil depth attribute and snow processes in the model. Second, simulated AET matched reasonably with estimated values calculated as the residual of precipitation and run‐off for watersheds controlled by the hydrological gauges. Finally, trend analysis based on the Mann–Kendall method indicated that significant increasing and decreasing patterns in precipitation appeared in the northwest part of China and the Yellow River region, respectively. Significant increasing and decreasing trends in AET were detected in the Southwest region and the Yangtze River region, respectively. In addition, the Southwest region, northern China (including the Heilongjiang, Liaohe, and Haihe Basins), and the Yellow River Basin showed significant decreasing trends in run‐off, and the Zhemin hydrological region showed a significant increasing trend. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
19.
In this study, uncertainty in model input data (precipitation) and parameters is propagated through a physically based, spatially distributed hydrological model based on the MIKE SHE code. Precipitation uncertainty is accounted for using an ensemble of daily rainfall fields that incorporate four different sources of uncertainty, whereas parameter uncertainty is considered using Latin hypercube sampling. Model predictive uncertainty is assessed for multiple simulated hydrological variables (discharge, groundwater head, evapotranspiration, and soil moisture). Utilizing an extensive set of observational data, effective observational uncertainties for each hydrological variable are assessed. Considering not only model predictive uncertainty but also effective observational uncertainty leads to a notable increase in the number of instances, for which model simulation and observations are in good agreement (e.g., 47% vs. 91% for discharge and 0% vs. 98% for soil moisture). Effective observational uncertainty is in several cases larger than model predictive uncertainty. We conclude that the use of precipitation uncertainty with a realistic spatio‐temporal correlation structure, analyses of multiple variables with different spatial support, and the consideration of observational uncertainty are crucial for adequately evaluating the performance of physically based, spatially distributed hydrological models. 相似文献
20.
The increased availability of global datasets and technologies such as global hydrologic models and the Gravity Recovery and Climate Experiment (GRACE) satellites have resulted in a growing number of global‐scale assessments of water availability using simple indices of water stress. Developed initially for surface water, such indices are increasingly used to evaluate global groundwater resources. We compare indices of groundwater development stress for three major agricultural areas of the United States to information available from regional water budgets developed from detailed groundwater modeling. These comparisons illustrate the potential value of regional‐scale analyses to supplement global hydrological models and GRACE analyses of groundwater depletion. Regional‐scale analyses allow assessments of water stress that better account for scale effects, the dynamics of groundwater flow systems, the complexities of irrigated agricultural systems, and the laws, regulations, engineering, and socioeconomic factors that govern groundwater use. Strategic use of regional‐scale models with global‐scale analyses would greatly enhance knowledge of the global groundwater depletion problem. 相似文献