Publications
196 results found
Moulds S, Buytaert W, Mijic A, 2018, A spatio-temporal land use and land cover reconstruction for India from 1960-2010, Scientific Data, Vol: 5, ISSN: 2052-4463
In recent decades India has undergone substantial land use/land cover change as a result of population growth and economic development. Historical land use/land cover maps are necessary to quantify the impact of change at global and regional scales, improve predictions about the quantity and location of future change and support planning decisions. Here, a regional land use change model driven by district-level inventory data is used to generate an annual time series of high-resolution gridded land use/land cover maps for the Indian subcontinent between 1960-2010. The allocation procedure is based on statistical analysis of the relationship between contemporary land use/land cover and various spatially explicit covariates. A comparison of the simulated map for 1985 against remotely-sensed land use/land cover maps for 1985 and 2005 reveals considerable discrepancy between the simulated and remote sensing maps, much of which arises due to differences in the amount of land use/land cover change between the inventory data and the remote sensing maps.
Mao F, Clark J, Buytaert W, et al., 2018, Water sensor network applications: Time to move beyond the technical?, HYDROLOGICAL PROCESSES, Vol: 32, Pages: 2612-2615, ISSN: 0885-6087
Ochoa-Tocachi BF, Buytaert W, Antiporta J, et al., 2018, High-resolution hydrometeorological data from a network of headwater catchments in the tropical Andes, Scientific Data, Vol: 5, ISSN: 2052-4463
This article presents a hydrometeorological dataset from a network of paired instrumented catchments, obtained by participatory monitoring through a partnership of academic and non-governmental institutions. The network consists of 28 headwater catchments (<20 km2) covering three major biomes in 9 locations of the tropical Andes. The data consist of precipitation event records at 0.254 mm resolution or finer, water level and streamflow time series at 5 min intervals, data aggregations at hourly and daily scale, a set of hydrological indices derived from the daily time series, and catchment physiographic descriptors. The catchment network is designed to characterise the impacts of land-use and watershed interventions on the catchment hydrological response, with each catchment representing a typical land use and land cover practice within its location. As such, it aims to support evidence-based decision making on land management, in particular evaluating the effectiveness of catchment interventions, for which hydrometeorological data scarcity is a major bottleneck. The data will also be useful for broader research on Andean ecosystems, and their hydrology and meteorology.
O'Keeffe J, Moulds S, Bergin E, et al., 2018, Including farmer irrigation behavior in a sociohydrological modeling framework with application in north India, Water Resources Research, Vol: 54, Pages: 4849-4866, ISSN: 0043-1397
Understanding water user behavior and its potential outcomes is important for the development of suitable water resource management options. Computational models are commonly used to assist water resource management decision making; however, while natural processes are increasingly well modeled, the inclusion of human behavior has lagged behind. Improved representation of irrigation water user behavior within models can provide more accurate and relevant information for irrigation management in the agricultural sector. This paper outlines a model that conceptualizes and proceduralizes observed farmer irrigation practices, highlighting impacts and interactions between the environment and behavior. It is developed using a bottom‐up approach, informed through field experience and farmer interaction in the state of Uttar Pradesh, northern India. Observed processes and dynamics were translated into parsimonious algorithms, which represent field conditions and provide a tool for policy analysis and water management. The modeling framework is applied to four districts in Uttar Pradesh and used to evaluate the potential impact of changes in climate and irrigation behavior on water resources and farmer livelihood. Results suggest changes in water user behavior could have a greater impact on water resources, crop yields, and farmer income than changes in future climate. In addition, increased abstraction may be sustainable but its viability varies across the study region. By simulating the feedbacks and interactions between the behavior of water users, irrigation officials and agricultural practices, this work highlights the importance of directly including water user behavior in policy making and operational tools to achieve water and livelihood security.
Buytaert W, Ochoa Tocachi B, Hannah DM, et al., 2018, Co-generating knowledge on ecosystem services and the role of new technologies, Ecosystem Services and Poverty Alleviation: Trade-offs and Governance, Editors: Schreckenberg, Mace, Poudyal, London, Publisher: Taylor & Francis Group, Pages: 174-188, ISBN: 9780429016295
Policy makers are increasingly aware that decision-making in the context of ecosystem services management, and of development, can benefit from collaborative and inclusive approaches to knowledge generation and the design of intervention strategies, such as by providing a more prominent role for indigenous knowledge in decision-making and by using participatory methods for data collection and knowledge generation. In this chapter, we discuss how technologies such as mobile phones, low-cost and robust sensors, and increasingly pervasive remote-sensing satellites and drones can be particularly transformative in the way they facilitate the creation, access and transmission of information about ecosystem services, and support evidence-based decision-making. Furthermore, we discuss how these technologies can be used to promote stakeholder involvement in the knowledge generation process and to make it more inclusive and participatory. While we highlight potential risks related to the use of new technologies, such as exploitation by specific stakeholders to support specific agendas or interests, we identify opportunities for an increasing diversification and tailoring of knowledge creation, moving away from a top-down process dominated by scientists and toward more decentralised, bottom-up and iterative approaches that can have a transformative impact on local ecosystem services management, making it more inclusive, polycentric, evidence-based and robust.
Tsarouchi G, Buytaert W, 2018, Land-use change may exacerbate climate change impacts on water resources in the Ganges basin, Hydrology and Earth System Sciences, Vol: 22, Pages: 1411-1435
<jats:p>Abstract. Quantifying how land-use change and climate change affect water resources isa challenge in hydrological science. This work aims to quantify how futureprojections of land-use and climate change might affect the hydrologicalresponse of the Upper Ganges river basin in northern India, which experiencesmonsoon flooding almost every year. Three different sets of modellingexperiments were run using the Joint UK Land Environment Simulator (JULES) land surface model (LSM) and covering theperiod 2000–2035: in the first set, only climate change is taken intoaccount, and JULES was driven by the CMIP5 (Coupled Model IntercomparisonProject Phase 5) outputs of 21 models, under two representative concentrationpathways (RCP4.5 and RCP8.5), whilst land use was held fixed at the year2010. In the second set, only land-use change is taken into account, andJULES was driven by a time series of 15 future land-use pathways, based onLandsat satellite imagery and the Markov chain simulation, whilst themeteorological boundary conditions were held fixed at years 2000–2005. Inthe third set, both climate change and land-use change were taken intoconsideration, as the CMIP5 model outputs were used in conjunction with the15 future land-use pathways to force JULES. Variations in hydrologicalvariables (stream flow, evapotranspiration and soil moisture) are calculatedduring the simulation period. Significant changes in the near-future (years 2030–2035) hydrologic fluxesarise under future land-cover and climate change scenarios pointing towards asevere increase in high extremes of flow: the multi-model mean of the 95thpercentile of streamflow (Q5) is projected to increase by 63 % underthe combined land-use and climate change high emissions scenario (RCP8.5).The changes in all examined hydrological components are greater in thecombined land-use and climate change experiment. Results are furtherpresented in a water resources context, aiming to address
Tsarouchi G, Buytaert W, 2018, Land-use change may exacerbate climate change impacts on water resources in the Ganges basin, Hydrology and Earth System Sciences Discussions, Vol: 22, Pages: 1411-1435, ISSN: 1812-2108
Quantifying how land-use change and climate change affect water resources is a challenge in hydrological science. This work aims to quantify how future projections of land-use and climate change might affect the hydrological response of the Upper Ganges river basin in northern India, which experiences monsoon flooding almost every year. Three different sets of modelling experiments were run using the Joint UK Land Environment Simulator (JULES) land surface model (LSM) and covering the period 2000–2035: in the first set, only climate change is taken into account, and JULES was driven by the CMIP5 (Coupled Model Intercomparison Project Phase 5) outputs of 21 models, under two representative concentration pathways (RCP4.5 and RCP8.5), whilst land use was held fixed at the year 2010. In the second set, only land-use change is taken into account, and JULES was driven by a time series of 15 future land-use pathways, based on Landsat satellite imagery and the Markov chain simulation, whilst the meteorological boundary conditions were held fixed at years 2000–2005. In the third set, both climate change and land-use change were taken into consideration, as the CMIP5 model outputs were used in conjunction with the 15 future land-use pathways to force JULES. Variations in hydrological variables (stream flow, evapotranspiration and soil moisture) are calculated during the simulation period.Significant changes in the near-future (years 2030–2035) hydrologic fluxes arise under future land-cover and climate change scenarios pointing towards a severe increase in high extremes of flow: the multi-model mean of the 95th percentile of streamflow (Q5) is projected to increase by 63 % under the combined land-use and climate change high emissions scenario (RCP8.5). The changes in all examined hydrological components are greater in the combined land-use and climate change experiment. Results are further presented in a water resources context, aiming to address potential i
Appel M, Lahn F, Buytaert W, et al., 2018, Open and scalable analytics of large Earth observation datasets: from scenes to multidimensional arrays using SciDB and GDAL, ISPRS Journal of Photogrammetry and Remote Sensing, Vol: 138, Pages: 47-56, ISSN: 0924-2716
Earth observation (EO) datasets are commonly provided as collection of scenes, where individual scenes represent a temporal snapshot and cover a particular region on the Earth's surface. Using these data in complex spatiotemporal modeling becomes difficult as soon as data volumes exceed a certain capacity or analyses include many scenes, which may spatially overlap and may have been recorded at different dates. In order to facilitate analytics on large EO datasets, we combine and extend the geospatial data abstraction library (GDAL) and the array-based data management and analytics system SciDB. We present an approach to automatically convert collections of scenes to multidimensional arrays and use SciDB to scale computationally intensive analytics. We evaluate the approach in three study cases on national scale land use change monitoring with Landsat imagery, global empirical orthogonal function analysis of daily precipitation, and combining historical climate model projections with satellite-based observations. Results indicate that the approach can be used to represent various EO datasets and that analyses in SciDB scale well with available computational resources. To simplify analyses of higher-dimensional datasets as from climate model output, however, a generalization of the GDAL data model might be needed. All parts of this work have been implemented as open-source software and we discuss how this may facilitate open and reproducible EO analyses.
Pascual U, Howe C, 2018, Seeing the wood for the trees: Exploring the evolution of frameworks of ecosystem services for human wellbeing, Ecosystem Services and Poverty Alleviation: Trade-Offs and Governance, Pages: 3-21, ISBN: 9781138580831
Ecosystem service frameworks connect with different societal goals and priorities regarding ecosystem management and development planning, and thus reflect the different epistemic communities from which they arise. Since the publication of the Millennium Ecosystem Assessment (MA), ecosystem service framing has undergone a significant evolution and this evolution has, in turn, continued to reshape the epistemic communities and their take on policy instruments, including for example payments for ecosystem services. This chapter explores the development of ecosystem services framings over the last decade, focusing on how the ecosystem service frameworks, such as the UN-led Economics of Ecosystems and Biodiversity (TEEB), the UK-led Ecosystem Services for Poverty Alleviation (ESPA) programme and the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES), have significantly influenced how we conceptualise and use the ecosystem service approach. Through an exploration of the evolution of ecosystem service and well-being framings, the chapter highlights that there has been a substantial shift towards seeing ecosystem services through a richer lens, departing from a mostly supply (biophysical) perspective to a more balanced social-ecological perspective, including the issues of equity and justice in ecosystem governance, and a pluralistic conceptualisation of values.
Vuille M, Carey M, Huggel C, et al., 2018, Rapid decline of snow and ice in the tropical Andes - Impacts, uncertainties and challenges ahead, EARTH-SCIENCE REVIEWS, Vol: 176, Pages: 195-213, ISSN: 0012-8252
Ochoa-Tocachi BF, Buytaert W, De Bievre B, 2018, Participatory Monitoring of the Impact of Watershed Interventions in the Tropical Andes, ANDEAN HYDROLOGY, Editors: Rivera, GodoyFaundez, LilloSaavedra, Publisher: CRC PRESS-TAYLOR & FRANCIS GROUP, Pages: 127-164, ISBN: 978-1-4987-8840-3
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Paul JD, Buytaert W, 2018, Citizen Science and Low-Cost Sensors for Integrated Water Resources Management, ADVANCED TOOLS FOR INTEGRATED WATER RESOURCES MANAGEMENT, Vol: 3, Pages: 1-33, ISSN: 2468-9289
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- Citations: 12
Ochoa Tocachi BF, Buytaert W, De Bièvre B, 2017, Participatory monitoring of the impact of watershed interventions in the tropical Andes, Andean Hydrology, Editors: Rivera, Godoy-Faundez, Lillo Saavedra, Publisher: CRC Press (Taylor & Francis Group), Pages: 126-163, ISBN: 9781498788403
This chapter documents the motivations and methods of the Regional Initiative for Hydrological Monitoring of Andean Ecosystems (iMHEA). First, it introduces the context that led to the formation of a diverse consortium of institutions with a joint interest in Andean ecosystems and water. The methodological approach adopted by the monitoring network is then presented in detail. Lastly, this chapter shows preliminary main results, the most relevant milestones and breakthroughs, and the major remaining challenges and perspectives in the scientific, technological and social domains. The objective of the monitoring, as promoted by iMHEA, is to generate standardized data that can be used to increase the knowledge about hydrological ecosystem services in Andean watersheds and the impacts of watershed interventions. The correct use of the generated knowledge, from community level to national governance entities, proves crucial to increase catchment intervention efficiency and improve decision-making on water resources management in data-scarce regions, with potential application to other regions of the world.
Fernanda Cardenas M, Tobon C, Buytaert W, 2017, Contribution of occult precipitation to the water balance of paramo ecosystems in the Colombian Andes, HYDROLOGICAL PROCESSES, Vol: 31, Pages: 4440-4449, ISSN: 0885-6087
Buytaert W, Moulds S, Acosta L, et al., 2017, Glacier melt content of water use in the tropical Andes, Environmental Research Letters, Vol: 12, ISSN: 1748-9326
Accelerated glaciers melt is expected to affect negatively the water resources of mountain regions and their adjacent lowlands, with tropical mountain regions being among the most vulnerable. In order to quantify those impacts, it is necessary to understand the changing dynamics of glacier melting, but also to map how glacier melt water contributes to current and future water use, which often occurs at considerable distance downstream of the glacier terminus. While the dynamics of tropical glacier melt are increasingly well understood and documented, major uncertainty remains on how tropical glacier meltwater contribution propagates through the hydrological system, and hence how it contributes to various types of human water use in downstream regions. Therefore, in this paper we present a detailed regional mapping of current water demand in regions downstream of the major tropical glaciers. We combine these maps with a regional water balance model to determine the dominant spatiotemporal patterns of glacier meltwater contribution to human water use at unprecedented scale and resolution. We find that the number of users relying continuously on water resources with a high (>25%) long-term average glacier melt contribution is low (391 000 domestic users, 398 km2 of irrigated land, and 11 MW of hydropower production). But this reliance increases sharply during drought conditions (up to 3.92 million domestic users, 2096 km2 of irrigated land, and 732 MW of hydropower production in the driest month of a drought year). A large share of domestic and agricultural users is located in rural regions where climate adaptation capacity tends to be low. Therefore, we suggest that adaptation strategies should focus on increasing the natural and artificial water storage and regulation capacity to bridge dry periods.
Arnillas CA, Tovar C, Cadotte MW, et al., 2017, From patches to richness: assessing the potential impact of landscape transformation on biodiversity, ECOSPHERE, Vol: 8, ISSN: 2150-8925
Paul JD, Buytaert W, Allen S, et al., 2017, Citizen science for hydrological risk reduction and resilience building, Wiley Interdisciplinary Reviews: Water, Vol: 5, ISSN: 2049-1948
In disaster risk management (DRM), an emerging shift has been noted from broad-scale, top-down assessments toward more participatory, community-based, bottom-up approaches. Arguably, nonscientist local stakeholders have always played an important role in knowledge risk management and resilience building within a hydrological context, such as flood response and drought alleviation. However, rapidly developing information and communication technologies such as the Internet, smartphones, and social media have already demonstrated their sizeable potential to make knowledge creation more multidirectional, decentralized, diverse, and inclusive. Combined with technologies for robust and low-cost sensor networks, a ‘citizen science’ approach has recently emerged as a promising direction in the provision of extensive, real-time information for risk management. Such projects work best when there is community buy-in, when their purpose(s) are clearly defined at the outset, and when the motivations and skillsets of all participants and stakeholders are well understood. They have great potential to enhance knowledge creation, not only for data collection, but also for analysis or interpretation. In addition, they can serve as a means of educating and empowering communities and stakeholders that are bypassed by more traditional knowledge generation processes. Here, we review the state-of-the-art of citizen science within the context of hydrological risk reduction and resilience building. Particularly when embedded within a polycentric approach toward risk governance, we argue that citizen science could complement more traditional knowledge generation practices, and also enhance innovation, adaptation, multidirectional information provision, risk management, and local resilience building.
Shukla AK, Ojha CSP, Mijic A, et al., 2017, Population Growth–Land Use/Land Cover Transformations–Water Quality Nexus in Upper Ganga River Basin
<jats:p>Abstract. For sustainable development in a river basin it is crucial to understand population growth–Land Use/Land Cover (LULC) transformations–water quality nexus. This study investigates effects of demographic changes and LULC transformations on surface water quality of Upper Ganga River basin. River gets polluted in both rural and urban area. In rural area, pollution is because of agricultural practices mainly fertilizers, whereas in urban area it is mainly because of domestic and industrial wastes. First, population data was analyzed statistically to study demographic changes in the river basin. LULC change detection was done over the period of February/March 2001 to 2012 [Landsat 7 Enhanced Thematic Mapper (ETM+) data] using remote sensing and Geographical Information System (GIS) techniques. Further, water quality parameters viz. Biological Oxygen Demand (BOD), Dissolve Oxygen (DO) %, Flouride (F), Hardness CaCO3, pH, Total Coliform bacteria and Turbidity were studied in basin for pre-monsoon (May), monsoon (July) and Post-monsoon (November) seasons. Non-parametric Mann–Kendall rank test was done on monthly water quality data to study existing trends. Further, Overall Index of Pollution (OIP) developed specifically for Upper Ganga River basin was used for spatio-temporal water quality assessment. From the results, it was observed that population has increased in the river basin. Therefore, significant and characteristic LULC changes are observed in the study area. Water quality degradation has occurred in the river basin consequently the health status of the rivers have also changed from range of acceptable to slightly polluted in urban areas. </jats:p>
Manz B, Paez-Bimos S, Horna N, et al., 2017, Comparative Ground Validation of IMERG and TMPA at Variable Spatiotemporal Scales in the Tropical Andes, Journal of Hydrometeorology, Vol: Sept 2017, Pages: 2469-2489, ISSN: 1525-7541
An initial ground validation of the Integrated Multisatellite Retrievals for GPM (IMERG) Day-1 product from March 2014 to August 2015 is presented for the tropical Andes. IMERG was evaluated along with the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) against 302 quality-controlled rain gauges across Ecuador and Peru. Detection, quantitative estimation statistics, and probability distribution functions are calculated at different spatial (0.1°, 0.25°) and temporal (1 h, 3 h, daily) scales. Precipitation products are analyzed for hydrometeorologically distinct subregions. Results show that IMERG has a superior detection and quantitative rainfall intensity estimation ability than TMPA, particularly in the high Andes. Despite slightly weaker agreement of mean rainfall fields, IMERG shows better characterization of gauge observations when separating rainfall detection and rainfall rate estimation. At corresponding space–time scales, IMERG shows better estimation of gauge rainfall probability distributions than TMPA. However, IMERG shows no improvement in both rainfall detection and rainfall rate estimation along the dry Peruvian coastline, where major random and systematic errors persist. Further research is required to identify which rainfall intensities are missed or falsely detected and how errors can be attributed to specific satellite sensor retrievals. The satellite–gauge difference was associated with the point-area difference in spatial support between gauges and satellite precipitation products, particularly in areas with low and irregular gauge network coverage. Future satellite–gauge evaluations need to identify such locations and investigate more closely interpixel point-area differences before attributing uncertainties to satellite products.
Mathez-Stiefel S-L, Peralvo M, Baez S, et al., 2017, Research priorities for the conservation and sustainable governance of Andean Forest landscapes, Mountain Research and Development, Vol: 37, Pages: 323-339, ISSN: 0276-4741
The long-term survival of Andean forest landscapes (AFL) and of their capacity to contribute to sustainable development in a context of global change requires integrated adaptation and mitigation responses informed by a thorough understanding of the dynamic and complex interactions between their ecological and social components. This article proposes a research agenda that can help guide AFL research efforts for the next 15 years. The agenda was developed between July 2015 and June 2016 through a series of workshops in Ecuador, Peru, and Switzerland and involved 48 researchers and development experts working on AFL from different disciplinary perspectives. Based on our review of current research and identification of pressing challenges for the conservation and sustainable governance of AFL, we propose a conceptual framework that draws on sustainability sciences and social–ecological systems research, and we identify a set of high-priority research goals and objectives organized into 3 broad categories: systems knowledge, target knowledge, and transformation knowledge. This paper is intended to be a reference for a broad array of actors engaged in policy, research, and implementation in the Andean region. We hope it will trigger collaborative research initiatives for the continued conservation and sustainable governance of AFL.
Mao F, Clark J, Karpouzoglou T, et al., 2017, HESS Opinions: A conceptual framework for assessing socio-hydrological resilience under change, HYDROLOGY AND EARTH SYSTEM SCIENCES, Vol: 21, Pages: 3655-3670, ISSN: 1027-5606
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 opinion paper, we propose a novel conceptual framework for understanding and assessing resilience in coupled socio-hydrological contexts, and encourage debate on the inter-connections between socio-hydrology and resilience. Taking a systems perspective, we argue that 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 existing framings of resilience for different types of human–water systems and subsystems, which have been used in different fields: (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 clarification and 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 pa
Arora H, Ojha CSP, Buytaert W, et al., 2017, Spatio-temporal trends in observed and downscaled precipitation over Ganga Basin
<jats:p>Abstract. This paper focuses on the spatio-temporal trends of precipitation over the Ganga Basin in India for over 2 centuries. Trends in precipitation amounts are detected using observed data for historical period in 20th century and using downscaled precipitation data from 37 GCMs for 21st century. The ranking of 37 GCMs (from CMIP5 archive) is done employing a statistics based skill score. The best ranked GCM output is then bias corrected with observed precipitation prior to further analysis. The direction and magnitude of trend in annual and seasonal precipitation series is determined using Mann Kendall’s test statistic (ZMK) and Thiel Sen’s Slope estimator (β). The plots depicting the spatial variation of ZMK and β are prepared which provides a comprehensive inter-scenario comparison of spatio-temporal trends in precipitation series. Highly non-uniform spatio-temporal trends are detected for observed precipitation series. It is observed that the precipitation for annual and southwest monsoon season is indicating a rising trend for all future emission scenarios in the region adjacent to Himalayas (northeast side of study area) but shows falling trends in the plains away from the Himalayas. Insignificant trends are observed in pre-monsoon and winter season precipitation. An inter-emission-scenario comparison shows that for higher emission scenarios the annual and southwest monsoon precipitation is showing rising trends with increasing spatial dominance i.e. the area under rising trends increases as we observe it from low to high emission scenarios. </jats:p>
Ocio D, Le Vine N, Westerberg I, et al., 2017, The role of rating curve uncertainty in real-time flood forecasting, Water Resources Research, Vol: 53, Pages: 4197-4213, ISSN: 0043-1397
Data assimilation has been widely tested for flood forecasting, although its use in operational systems is mainly limited to a simple statistical error correction. This can be due to the complexity involved in making more advanced formal assumptions about the nature of the model and measurement errors. Recent advances in the definition of rating curve uncertainty allow estimating a flow measurement error that includes both aleatory and epistemic uncertainties more explicitly and rigorously than in the current practice. The aim of this study is to understand the effect such a more rigorous definition of the flow measurement error has on real-time data assimilation and forecasting. This study, therefore, develops a comprehensive probabilistic framework that considers the uncertainty in model forcing data, model structure, and flow observations. Three common data assimilation techniques are evaluated: (1) Autoregressive error correction, (2) Ensemble Kalman Filter, and (3) Regularized Particle Filter, and applied to two locations in the flood-prone Oria catchment in the Basque Country, northern Spain. The results show that, although there is a better match between the uncertain forecasted and uncertain true flows, there is a low sensitivity for the threshold exceedances used to issue flood warnings. This suggests that a standard flow measurement error model, with a spread set to a fixed flow fraction, represents a reasonable trade-off between complexity and realism. Standard models are therefore recommended for operational flood forecasting for sites with well-defined stage-discharge curves that are based on a large range of flow observations.
Buytaert W, 2017, Climate Change Adaptation Strategies-An Upstream-Downstream Perspective, Mountain Research and Development, Vol: 37, Pages: 240-241, ISSN: 0276-4741
Huss M, Bookhagen B, Huggel C, et al., 2017, Toward mountains without permanent snow and ice, EARTHS FUTURE, Vol: 5, Pages: 418-435, ISSN: 2328-4277
Pandeya B, Buytaert W, 2017, Citizen science and web-based modelling tools for managing freshwater
The use of low-cost hydrological sensors in Nepal allowed local stakeholders to generate useful data on freshwater resources in partnership with scientists, and to apply this data more effectively in participatory decision making.It is important to use the right mapping and modelling methods for ecosystem services (the benefits people obtain from ecosystems) so that information on service production, distribution and consumption is expressed at a spatial scale that is relevant to decision making. These methods are even more important in regions where limited data is available.The integration of appropriate citizen science practices as well as mapping and modelling tools into water and land resources based decision making could facilitate sustainable development activities, particularly in the Himalayan region.
Vitolo C, Fry M, Buytaert W, 2017, rnrfa: An R package to Retrieve, Filter and Visualize Data from the UK National River Flow Archive, The R Journal, Vol: 8, Pages: 102-116, ISSN: 2073-4859
The UK National River Flow Archive (NRFA) stores several types of hydrological data and metadata: daily river flow and catchment rainfall time series, gauging station and catchment informa tion. Data are served through the NRFA web services via experimental RESTful APIs. Obtaining NRFA data can be unwieldy due to complexities in handling HTTP GET requests and parsing responses in JSON and XML formats. The rnrfa package provides a set of functions to programmatically access, filter, and visualize NRFA data using simple R syntax. This paper describes the structure of the rnrfa package, including examples using the main functions gdf() and cmr() for flow and rainfall data, respectively. Visualization examples are also provided with a shiny web application and functions provided in the package. Although this package is regional specific, the general framework and structure could be applied to similar databases.
Vitolo C, Wells P, Dobias M, et al., 2016, fuse: An R package for ensemble Hydrological Modelling, The Journal of Open Source Software, Vol: 1, Pages: 52-52
Zulkafli Z, Perez K, Vitolo C, et al., 2016, User-driven design of decision support systems for polycentric environmental resources management, Environmental Modelling & Software, Vol: 88, Pages: 58-73, ISSN: 1364-8152
Open and decentralized technologies such as the Internet provide increasing opportunities to create knowledge and deliver computer-based decision support for multiple types of users across scales. However, environmental decision support systems/tools (henceforth EDSS) are often strongly science-driven and assuming single types of decision makers, and hence poorly suited for more decentralized and polycentric decision making contexts. In such contexts, EDSS need to be tailored to meet diverse user requirements to ensure that it provides useful (relevant), usable (intuitive), and exchangeable (institutionally unobstructed) information for decision support for different types of actors. To address these issues, we present a participatory framework for designing EDSS that emphasizes a more complete understanding of the decision making structures and iterative design of the user interface. We illustrate the application of the framework through a case study within the context of water-stressed upstream/downstream communities in Lima, Peru.
Pandeya B, Buytaert W, Zulkafli Z, et al., 2016, A comparative analysis of ecosystem services valuation approaches for application at the local scale and in data scarce regions, Ecosystem Services, Vol: 22, Pages: 250-259, ISSN: 2212-0416
Despite significant advances in the development of the ecosystem services concept across the science and policy arenas, the valuation of ecosystem services to guide sustainable development remains challenging, especially at a local scale and in data scarce regions. In this paper, we review and compare major past and current valuation approaches and discuss their key strengths and weaknesses for guiding policy decisions. To deal with the complexity of methods used in different valuation approaches, our review uses multiple entry points: data vs simulation, habitat vs system vs place-based, specific vs entire portfolio, local vs regional scale, and monetary vs non-monetary. We find that although most valuation approaches are useful to explain ecosystem services at a macro/system level, an application of locally relevant valuation approaches, which allows for a more integrated valuation relevant to decision making is still hindered by data-scarcity. The advent of spatially explicit policy support systems shows particular promise to make the best use of available data and simulations. Data collection remains crucial for the local scale and in data scarce regions. Leveraging citizen science-based data and knowledge co-generation may support the integrated valuation, while at the same time making the valuation process more inclusive, replicable and policy-oriented.
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