Publications
196 results found
Mao F, Clark J, Karpouzoglou T, et al., 2016, A conceptual framework for assessing socio-hydrological resilience under change
<jats:p>Abstract. Despite growing interest in resilience, there is still significant scope for increasing its conceptual clarity and practical relevance in socio-hydrological contexts. Specifically, questions of how socio-hydrological systems respond to and cope with perturbations and how these connect to resilience remain unanswered. In this paper, we propose a novel conceptual framework for understanding and assessing resilience in coupled socio-hydrological systems. Taking a systems perspective, we argue resilience is a set of systematic properties with three dimensions: absorptive, adaptive and transformative, and contend that socio-hydrological systems can be viewed as various forms of human-water couplings, reflecting different aspects of these interactions. We propose a framework consisting of two parts. The first part addresses the identity of socio-hydrological resilience, answering questions such as ‘resilience of what in relation to what’. We identify three framings of resilience for different types of human-water systems and subsystems: (1) the water subsystem, highlighting hydrological resilience to anthropogenic hazards; (2) the human subsystem, foregrounding social resilience to hydrological hazards; and (3) the coupled human-water system, exhibiting socio-hydrological resilience. We argue that these three system types and resiliences afford new insights into the evaluation of different water management challenges. The first two types address hydrological and social states, while the third type emphasises the feedbacks and interactions between human and water components within complex systems subject to internal or external disturbances. In the second part, we focus on resilience management and develop the notion of the ‘resilience canvas’, a novel heuristic device to identify possible pathways and to facilitate the design of bespoke strategies for enhancing resilience in the socio-hydrological context. The ‘resilie
Grainger S, Mao F, Buytaert W, 2016, Environmental data visualisation for non-scientific contexts: Literature review and design framework, Environmental Modelling & Software, Vol: 85, Pages: 299-318, ISSN: 1364-8152
Environmental science is an applied discipline, which therefore requires interacting with actors outside of the scientific community. Visualisations are increasingly seen as powerful tools to engage users with unfamiliar and complex subject matter. Despite recent research advances, scientists are yet to fully harness the potential of visualisation when interacting with non-scientists. To address this issue, we review the main principles of visualisation, discuss specific graphical challenges for environmental science and highlight some best practice from non-professional contexts. We provide a design framework to enhance the communication and application of scientific information within professional contexts. These guidelines can help scientists incorporate effective visualisations within improved dissemination and knowledge exchange platforms. We conclude that the uptake of science within environmental decision-making requires a highly iterative and collaborative design approach towards the development of tailored visualisations. This enables users to not only generate actionable understanding but also explore information on their own terms.
Ochoa-Tocachi B, Buytaert W, De Bièvre B, 2016, Regionalization of land-use impacts on streamflow using a network of paired catchments, Water Resources Research, Vol: 52, Pages: 6710-6729, ISSN: 1944-7973
Quantifying the impact of land use and cover (LUC) change on catchment hydrological response is essential for land-use planning and management. Yet hydrologists are often not able to present consistent and reliable evidence to support such decision-making. The issue tends to be twofold: a scarcity of relevant observations, and the difficulty of regionalizing any existing observations. This study explores the potential of a paired catchment monitoring network to provide statistically robust, regionalized predictions of LUC change impact in an environment of high hydrological variability. We test the importance of LUC variables to explain hydrological responses and to improve regionalized predictions using 24 catchments distributed along the Tropical Andes. For this, we calculate first 50 physical catchment properties, and then select a subset based on correlation analysis. The reduced set is subsequently used to regionalize a selection of hydrological indices using multiple linear regression. Contrary to earlier studies, we find that incorporating LUC variables in the regional model structures increases significantly regression performance and predictive capacity for 66% of the indices. For the runoff ratio, baseflow index, and slope of the flow duration curve, the mean absolute error reduces by 53% and the variance of the residuals by 79%, on average. We attribute the explanatory capacity of LUC in the regional model to the pairwise monitoring setup, which increases the contrast of the land-use signal in the data set. As such, it may be a useful strategy to optimize data collection to support watershed management practices and improve decision-making in data-scarce regions.
Ochoa-Tocachi B, Buytaert W, De Bièvre B, et al., 2016, Impacts of land use on the hydrological response of tropical Andean catchments, Hydrological Processes, Vol: 30, Pages: 4074-4089, ISSN: 1099-1085
Changes in land use and land cover are major drivers of hydrological alteration in the tropical Andes. However, quantifying their impacts is fraught with difficulties because of the extreme diversity in meteorological boundary conditions, which contrasts strongly with the lack of knowledge about local hydrological processes. Although local studies have reduced data scarcity in certain regions, the complexity of the tropical Andes poses a big challenge to regional hydrological prediction.This study analyses data generated from a participatory monitoring network of 25 headwater catchments covering three of the major Andean biomes (páramo, jalca, and puna), and link their hydrological responses to main types of human interventions (cultivation, afforestation and grazing). A paired catchment setup was implemented to evaluate the impacts of change using a “trading space-for-time” approach. Catchments were selected based on regional representativeness and contrasting land use types. Precipitation and discharge have been monitored and analysed at high temporal resolution for a time period between 1 and 5 years.The observed catchment responses clearly reflect the extraordinarily wide spectrum of hydrological processes of the tropical Andes. They range from perennially humid páramos in Ecuador and northern Peru with extremely large specific discharge and baseflows, to highly seasonal, flashy catchments in the drier punas of southern Peru and Bolivia. The impacts of land use are similarly diverse and their magnitudes are a function of catchment properties, original and replacement vegetation, and management type. Cultivation and afforestation consistently affect the entire range of discharges, particularly low flows. The impacts of grazing are more variable, but have the largest effect on the catchment hydrological regulation. Overall, anthropogenic interventions result in increased streamflow variability and significant reductions in catchmen
Derin Y, Anagnostou E, Berne A, et al., 2016, Multiregional Satellite Precipitation Products Evaluation over Complex Terrain, Journal of Hydrometeorology, Vol: 17, Pages: 1817-1836, ISSN: 1525-755X
An extensive evaluation of nine global-scale high-resolution satellite-based rainfall (SBR) products is performed using a minimum of 6 years (within the period of 2000-13) of reference rainfall data derived from rain gauge networks in nine mountainous regions across the globe. The SBR products are compared to a recently released global reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF). The study areas include the eastern Italian Alps, the Swiss Alps, the western Black Sea of Turkey, the French Cévennes, the Peruvian Andes, the Colombian Andes, the Himalayas over Nepal, the Blue Nile in East Africa, Taiwan, and the U.S. Rocky Mountains. Evaluation is performed at annual, monthly, and daily time scales and 0.25° spatial resolution. The SBR datasets are based on the following retrieval algorithms: Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA), the NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Global Satellite Mapping of Precipitation (GSMaP). SBR products are categorized into those that include gauge adjustment versus unadjusted. Results show that performance of SBR is highly dependent on the rainfall variability. Many SBR products usually underestimate wet season and overestimate dry season precipitation. The performance of gauge adjustment to the SBR products varies by region and depends greatly on the representativeness of the rain gauge network.
O'Keeffe J, Buytaert W, Mijic A, et al., 2016, The use of semi-structured interviews for the characterisation of farmer irrigation practices, Hydrology and Earth System Sciences, Vol: 20, Pages: 1911-1924, ISSN: 1607-7938
Generating information on the behaviours, characteristics and drivers of users, as well on the resource itself, is vital in developing sustainable and realistic water security options. In this paper we present a methodology for collecting qualitative and quantitative data on water use practices through semi-structured interviews. This approach facilitates the collection of detailed information on actors' decisions in a convenient and cost-effective manner. The interview is organised around a topic guide, which helps lead the conversation in a standardised way while allowing sufficient opportunity to identify relevant issues previously unknown to the researcher. In addition, semi-structured interviews can be used to obtain certain types of quantitative data. While not as accurate as direct measurements, it can provide useful information on local practices and farmers' insights. We present an application of the methodology on two districts in the State of Uttar Pradesh in North India. By means of 100 farmer interviews, information was collected on various aspects of irrigation practices, including irrigation water volumes, irrigation cost, water source and their spatial variability. A statistical analysis of the information, along with some data visualisation is also presented, which highlights a significant variation in irrigation practices both within and between the districts. Our application shows that semi-structured interviews are an effective and efficient method of collecting both qualitative and quantitative information for the assessment of drivers, behaviours and their outcomes in a data scarce region. The collection of this type of data could significantly improve insight on water resources, leading to more realistic management options and increased water security in the future.
Rodriguez-Lloveras X, Buytaert W, Benito G, 2016, Land use can offset climate change induced increases in erosion in Mediterranean watersheds, CATENA, Vol: 143, Pages: 244-255, ISSN: 0341-8162
The aim of this paper is to assess the impacts of projected climate change on a Mediterranean catchment, and to analyze the effects of a suite of representative land use practices as an adaptation tool to reduce climate change-driven erosion and hydrologic extremes. Relevant climatic variables from the ERA-Interim global atmospheric reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) were downscaled for the study area, and perturbed with the anomalies of 23 global circulation models for three emission scenarios (B1, A1B and A2). Both a projected daily rainfall time series for the period 2010–2100, and a single precipitation event with a one-hundred year return period were used to assess the impact of climate change. The downscaled data were fed into a distributed hydro-sedimentary model (TETIS) with five land use configurations representative of future demographic tendencies, geographical characteristics and land management policies (e.g. European Union CAP). The projected changes showed a general decrease in runoff and sediment production by the end of the century regardless of land use configuration. Sediment production showed a positive relationship with an increase in agricultural land and a decrease in natural land under present day agricultural management. According to our simulations, some conservation practices in agriculture can effectively reduce net erosion while maintaining agricultural production. As such, they can play a critical role as an adaptation tool to reduce climate change impacts in the 21st century.
Bhusal JK, Chapagain PS, Regmi S, et al., 2016, Mountains under pressure: Evaluating ecosystem services and livelihoods in the Upper Himalayan Region of Nepal, International Journal of Ecology and Environmental Sciences, ISSN: 0377-015X
Almeida S, Le Vine N, McIntyre N, et al., 2016, Accounting for dependencies in regionalized signatures for predictions in ungauged catchments, Hydrology and Earth System Sciences, Vol: 20, Pages: 887-901, ISSN: 1607-7938
A recurrent problem in hydrology is the absence of streamflow data to calibrate rainfall-runoff models. A commonly used approach in such circumstances conditions model parameters on regionalized response signatures. While several different signatures are often available to be included in this process, an outstanding challenge is the selection of signatures that provide useful and complementary information. Different signatures do not necessarily provide independent information and this has led to signatures being omitted or included on a subjective basis. This paper presents a method that accounts for the inter-signature error correlation structure so that regional information is neither neglected nor double-counted when multiple signatures are included. Using 84 catchments from the MOPEX database, observed signatures are regressed against physical and climatic catchment attributes. The derived relationships are then utilized to assess the joint probability distribution of the signature regionalization errors that is subsequently used in a Bayesian procedure to condition a rainfall-runoff model. The results show that the consideration of the inter-signature error structure may improve predictions when the error correlations are strong. However, other uncertainties such as model structure and observational error may outweigh the importance of these correlations. Further, these other uncertainties cause some signatures to appear repeatedly to be misinformative.
Manz B, Buytaert W, Zulkafli Z, et al., 2016, High-resolution Satellite-Gauge Merged Precipitation Climatologies of the Tropical Andes, Journal of Geophysical Research: Atmospheres, Vol: 121, Pages: 1190-1207, ISSN: 2169-897X
Satellite precipitation products are becoming increasingly useful to complement rain gauge networks in regions where these are too sparse to capture spatial precipitation patterns, such as in the tropical Andes. The Tropical Rainfall Measuring Mission Precipitation Radar (TPR) was active for 17 years (1998 - 2014) and has generated one of the longest single-sensor, high-resolution and high-accuracy rainfall records. In this study, high-resolution (5 km) gridded mean monthly climatological precipitation is derived from the raw orbital TPR data (TRMM 2A25) and merged with 723 rain gauges using multiple satellite-gauge (S-G) merging approaches. The resulting precipitation products are evaluated by cross-validation and catchment water balances (runoff ratios) for 50 catchments across the tropical Andes. Results show that the TPR captures major synoptic and seasonal precipitation patterns and also accurately defines orographic gradients, but underestimates absolute monthly rainfall rates. The S-G merged products presented in this study constitute an improved source of climatological rainfall data, outperforming the gridded TPR product as well as a rain gauge-only product based on ordinary kriging. Among the S-G merging methods, performance of inverse-distance interpolation of satellite-gauge residuals was similar to that of geostatistical methods, which were more sensitive to gauge network density. High uncertainty and low performance of the merged precipitation products predominantly affected regions with low and intermittent precipitation regimes (e.g. Peruvian Pacific coast) and is likely linked to the low TPR sampling frequency. All S-G merged products presented in this study are available in the public domain.
Blair P, Buytaert W, 2016, Socio-hydrological modelling: a review asking “why, what and how?”, Hydrology and Earth System Sciences, Vol: 20, Pages: 443-478, ISSN: 1607-7938
Interactions between humans and the environment are occurring on a scale that has never previously been seen; the scale of human interaction with the water cycle, along with the coupling present between social and hydrological systems, means that decisions that impact water also impact people. Models are often used to assist in decision-making regarding hydrological systems, and so in order for effective decisions to be made regarding water resource management, these interactions and feedbacks should be accounted for in models used to analyse systems in which water and humans interact. This paper reviews literature surrounding aspects of socio-hydrological modelling. It begins with background information regarding the current state of socio-hydrology as a discipline, before covering reasons for modelling and potential applications. Some important concepts that underlie socio-hydrological modelling efforts are then discussed, including ways of viewing socio-hydrological systems, space and time in modelling, complexity, data and model conceptualisation. Several modelling approaches are described, the stages in their development detailed and their applicability to socio-hydrological cases discussed. Gaps in research are then highlighted to guide directions for future research. The review of literature suggests that the nature of socio-hydrological study, being interdisciplinary, focusing on complex interactions between human and natural systems, and dealing with long horizons, is such that modelling will always present a challenge; it is, however, the task of the modeller to use the wide range of tools afforded to them to overcome these challenges as much as possible. The focus in socio-hydrology is on understanding the human–water system in a holistic sense, which differs from the problem solving focus of other water management fields, and as such models in socio-hydrology should be developed with a view to gaining new insight into these dynamics. There is an es
Zulkafli Z, Buytaert W, Manz B, et al., 2016, Projected increases in the annual flood pulse of the western Amazon, Environmental Research Letters, Vol: 11, ISSN: 1748-9326
The impact of a changing climate on the Amazon basin is a subjectof intensive research because of its rich biodiversity and the significant role ofrainforests in carbon cycling. Climate change has also a direct hydrological impact,and increasing efforts have focused on understanding the hydrological dynamics atcontinental and subregional scales, such as the western Amazon. New projectionsfrom the Coupled Model Inter-comparison Project Phase 5 (CMIP5) ensemble indicateconsistent climatic warming and increasing seasonality of precipitation in the PeruvianAmazon basin. Here we use a distributed land surface model to quantify the potentialimpact of this change in the climate on the hydrological regime of the upper Amazonriver. Using extreme value analysis, historical and future projections of the annualminimum, mean, and maximum river flows are produced for a range of return periodsbetween 1 and 100 years. We show that the RCP 4.5 and 8.5 scenarios of climatechange project an increased severity of the wet season flood pulse (7.5% and 12%increases respectively for the 100-year return floods). These findings agree withpreviously projected increases in high extremes under the Special Report on EmissionsScenarios climate projections, and are important to highlight due to the potentialconsequences on reproductive processes of in-stream species, swamp forest ecology,and socio-economy in the floodplain, amidst a growing literature that more stronglyemphasises future droughts and their impact on the viability of the rainforest systemover greater Amazonia
Buytaert W, Dewulf A, De Bievre B, et al., 2016, Citizen Science for Water Resources Management: Toward Polycentric Monitoring and Governance?, Journal of Water Resources Planning and Management, Vol: 142, ISSN: 1943-5452
Moulds S, Buytaert W, Mijic A, 2015, An open and extensible framework for spatially explicit land use change modelling: the lulcc R package, Geoscientific Model Development, Vol: 8, Pages: 3215-3229, ISSN: 1991-9603
We present the lulcc software package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of alternative models; and (3) additional software is required because existing applications frequently perform only the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a data set included with the package. It is envisaged that lulcc will enable future model development and comparison within an open environment.
Nerini D, Zulkafli Z, Wang L-P, et al., 2015, A Comparative Analysis of TRMM-Rain Gauge Data Merging Techniques at the Daily Time Scale for Distributed Rainfall-Runoff Modeling Applications, Journal of Hydrometeorology, Vol: 16, Pages: 2153-2168, ISSN: 1525-755X
This study compares two nonparametric rainfall data merging methods—the mean bias correction and double-kernel smoothing—with two geostatistical methods—kriging with external drift and Bayesian combination—for optimizing the hydrometeorological performance of a satellite-based precipitation product over a mesoscale tropical Andean watershed in Peru. The analysis is conducted using 11 years of daily time series from the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) research product (also TRMM 3B42) and 173 rain gauges from the national weather station network. The results are assessed using 1) a cross-validation procedure and 2) a catchment water balance analysis and hydrological modeling. It is found that the double-kernel smoothing method delivered the most consistent improvement over the original satellite product in both the cross-validation and hydrological evaluation. The mean bias correction also improved hydrological performance scores, particularly at the subbasin scale where the rain gauge density is higher. Given the spatial heterogeneity of the climate, the size of the modeled catchment, and the sparsity of data, it is concluded that nonparametric merging methods can perform as well as or better than more complex geostatistical methods, whose assumptions may not hold under the studied conditions. Based on these results, a systematic approach to the selection of a satellite–rain gauge data merging technique is proposed that is based on data characteristics. Finally, the underperformance of an ordinary kriging interpolation of the rain gauge data, compared to TMPA and other merged products, supports the use of satellite-based products over gridded rain gauge products that utilize sparse data for hydrological modeling at large scales.
Karpouzoglou T, Zulkafli Z, Grainger S, et al., 2015, Environmental Virtual Observatories (EVOs): Prospects for knowledge co-creation and resilience in the Information Age, Current Opinion in Environmental Sustainability, Vol: 18, Pages: 40-48, ISSN: 1877-3443
Developments in technologies are shaping information access globally. This presents opportunities and challenges for understanding the role of new technologies in sustainability research. This article focuses on a suite of technologies termed Environmental Virtual Observatories (EVOs) developed for communicating observations and simulation of environmental processes. A strength of EVOs is that they are open and decentralised, thus democratising flow and ownership of information between multiple actors. However, EVOs are discussed rarely beyond their technical aspects. By evaluating the evolution of EVOs, we illustrate why it is timely to engage with policy and societal aspects as well. While first generation EVOs are primed for scientists, second generation EVOs can have broader implications for knowledge co-creation and resilience through their participatory design.
Moulds S, Buytaert W, Mijic A, 2015, Supplementary material to &quot;An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)&quot;
Vitolo C, 2014, Web technologies for environmental Big Data, Environmental Modelling & Software, Vol: 63, Pages: 185-198, ISSN: 1364-8152
Recent evolutions in computing science and web technology provide the environmental community with continuously expanding resources for data collection and analysis that pose unprecedented challenges to the design of analysis methods, workflows, and interaction with data sets. In the light of the recent UK Research Council funded Environmental Virtual Observatory pilot project, this paper gives an overview of currently available implementations related to web-based technologies for processing large and heterogeneous datasets and discuss their relevance within the context of environmental data processing, simulation and prediction. We found that, the processing of the simple datasets used in the pilot proved to be relatively straightforward using a combination of R, RPy2, PyWPS and PostgreSQL. However, the use of NoSQL databases and more versatile frameworks such as OGC standard based implementations may provide a wider and more flexible set of features that particularly facilitate working with larger volumes and more heterogeneous data sources.
Tsarouchi GM, Buytaert W, Mijic A, 2014, Coupling a land-surface model with a crop growth model to improve ET flux estimations in the Upper Ganges basin, India, Hydrol. Earth Syst. Sci., Vol: 18, Pages: 4223-4238
Buytaert W, Zulkafli Z, Grainger S, et al., 2014, Citizen science in hydrology and water resources: opportunities for knowledge generation, ecosystem service management, and sustainable development, Frontiers in Earth Science, Vol: 2, ISSN: 2296-6463
The participation of the general public in the research design, data collection and interpretation process together with scientists is often referred to as citizen science. While citizen science itself has existed since the start of scientific practice, developments in sensing technology, data processing and visualization, and communication of ideas and results, are creating a wide range of new opportunities for public participation in scientific research. This paper reviews the state of citizen science in a hydrological context and explores the potential of citizen science to complement more traditional ways of scientific data collection and knowledge generation for hydrological sciences and water resources management. Although hydrological data collection often involves advanced technology, the advent of robust, cheap, and low-maintenance sensing equipment provides unprecedented opportunities for data collection in a citizen science context. These data have a significant potential to create new hydrological knowledge, especially in relation to the characterization of process heterogeneity, remote regions, and human impacts on the water cycle. However, the nature and quality of data collected in citizen science experiments is potentially very different from those of traditional monitoring networks. This poses challenges in terms of their processing, interpretation, and use, especially with regard to assimilation of traditional knowledge, the quantification of uncertainties, and their role in decision support. It also requires care in designing citizen science projects such that the generated data complement optimally other available knowledge. Lastly, using 4 case studies from remote mountain regions we reflect on the challenges and opportunities in the integration of hydrologically-oriented citizen science in water resources management, the role of scientific knowledge in the decision-making process, and the potential contestation to established community institut
Exbrayat J-F, Buytaert W, Timbe E, et al., 2014, Addressing sources of uncertainty in runoff projections for a data scarce catchment in the Ecuadorian Andes, CLIMATIC CHANGE, Vol: 125, Pages: 221-235, ISSN: 0165-0009
- Author Web Link
- Cite
- Citations: 17
Zulkafli Z, Buytaert W, Onof C, et al., 2014, A Comparative Performance Analysis of TRMM 3B42 (TMPA) Versions 6 and 7 for Hydrological Applications over Andean-Amazon River Basins, JOURNAL OF HYDROMETEOROLOGY, Vol: 15, Pages: 581-592, ISSN: 1525-755X
Tsarouchi GM, Mijic A, Moulds S, et al., 2014, Historical and future land-cover changes in the Upper Ganges basin of India, International Journal of Remote Sensing, Vol: 35, Pages: 3150-3176
The green revolution represents one of the greatest environmental changes in India over the last century. The Upper Ganges (UG) basin is experiencing rapid rates of change of land cover and irrigation practices. In this study, we investigated the historical rate of change and created future scenario projections by means of 30 m-resolution multi-temporal Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus data of the UG basin. Post-classification change analysis methods were applied to Landsat images in order to detect and quantify land-cover changes in the UG basin. Subsequently, Markov chain analysis was applied to project future scenarios of land-cover change. Fifteen different scenarios were generated based on historic land-cover change. These scenarios diverged in terms of future projections, highlighting the dynamic nature of the changes. This study has shown that between the years 1984 and 2010 the main land-cover change trends are conversion from shrubs to forest (+4.7%), urbanization (+5.8%), agricultural expansion (+1.3%), and loss of barren land (–9.5%). The land-cover change patterns in the UG basin were mapped and quantified, showing the capability of Landsat data in providing accurate land-cover maps. These results, in combination with those derived from the Markov model, provide the necessary evidence base to support regional land-use planning and develop future-proof water resource management strategies.
Hollaender HM, Bormann H, Blume T, et al., 2014, Impact of modellers' decisions on hydrological a priori predictions, HYDROLOGY AND EARTH SYSTEM SCIENCES, Vol: 18, Pages: 2065-2085, ISSN: 1027-5606
- Author Web Link
- Cite
- Citations: 20
Almeida S, Bulygina N, McIntyre N, et al., 2013, Improving parameter priors for data-scarce estimation problems, Water Resources Research
Holländer HM, Bormann H, Blume T, et al., 2013, Impact of modellers' decisions on hydrological a priori predictions
<jats:p>Abstract. The purpose of this paper is to stimulate a re-thinking of how we, the catchment hydrologists, could become reliable forecasters. A group of catchment modellers predicted the hydrological response of a man-made 6 ha catchment in its initial phase (Chicken Creek) without having access to the observed records. They used conceptually different model families. Their modelling experience differed largely. The prediction exercise was organized in three steps: (1) for the 1st prediction modellers received a basic data set describing the internal structure of the catchment (somewhat more complete than usually available to a priori predictions in ungauged catchments). They did not obtain time series of stream flow, soil moisture or groundwater response. (2) Before the 2nd improved prediction they inspected the catchment on-site and attended a workshop where the modellers presented and discussed their first attempts. (3) For their improved 3rd prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step 1. Here, we detail the modeller's decisions in accounting for the various processes based on what they learned during the field visit (step 2) and add the final outcome of step 3 when the modellers made use of additional data. We document the prediction progress as well as the learning process resulting from the availability of added information. For the 2nd and 3rd step, the progress in prediction quality could be evaluated in relation to individual modelling experience and costs of added information. We learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and m
Holländer HM, Bormann H, Blume T, et al., 2013, Supplementary material to &quot;Impact of modellers' decisions on hydrological a priori predictions&quot;
Tovar C, Alberto Arnillas C, Cuesta F, et al., 2013, Diverging Responses of Tropical Andean Biomes under Future Climate Conditions, PLOS ONE, Vol: 8, ISSN: 1932-6203
- Author Web Link
- Cite
- Citations: 66
McIntyre N, Ballard C, Bruen M, et al., 2013, Modelling the hydrological impacts of rural land use change, Hydrology Research, ISSN: 0029-1277
Zulkafli Z, Buytaert W, Onof C, et al., 2013, A critical assessment of the JULES land surface model hydrology for humid tropical environments, HYDROLOGY AND EARTH SYSTEM SCIENCES, Vol: 17, Pages: 1113-1132, ISSN: 1027-5606
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.