Citizen science:A new perspective to advance spatial pattern evaluation in hydrology

Citizen science opens new pathways that can complement traditional scientific practice. Intuition and reasoning often make humans more effective than computer algorithms in various realms of problem solving. In particular, a simple visual comparison of spatial patterns is a task where humans are often considered to be more reliable than computer algorithms. However, in practice, science still largely depends on computer based solutions, which inevitably gives benefits such as speed and the possibility to automatize processes. However, the human vision can be harnessed to evaluate the reliability of algorithms which are tailored to quantify similarity in spatial patterns. We established a citizen science project to employ the human perception to rate similarity and dissimilarity between simulated spatial patterns of several scenarios of a hydrological catchment model. In total, the turnout counts more than 2500 volunteers that provided over 43000 classifications of 1095 individual subjects. We investigate the capability of a set of advanced statistical performance metrics to mimic the human perception to distinguish between similarity and dissimilarity. Results suggest that more complex metrics are not necessarily better at emulating the human perception, but clearly provide auxiliary information that is valuable for model diagnostics. The metrics clearly differ in their ability to unambiguously distinguish between similar and dissimilar patterns which is regarded a key feature of a reliable metric. The obtained dataset can provide an insightful benchmark to the community to test novel spatial metrics

Governance Struggles and Policy Processes in Disaster Risk Reduction: A Case Study from Nepal

In the neo-liberal climate of reduced responsibility for the state, alongside global platforms established to implement the Hyogo Framework for Action, a new arena opens for a multitude of stakeholders to engage in disaster risk reduction (DRR). The key role that the state can play in instituting effective DRR tends to receive little attention, yet in situations where the state apparatus is weak, such as in Nepal, it becomes evident that integrating DRR into development is a particularly challenging task. Due to the political situation in Nepal, progress has been stalled in providing a legislative context conducive to effective DRR. This paper traces the evolution of key DRR initiatives that have been developed in spite of the challenging governance context, such as the National Strategy for Disaster Risk Management and the Nepal Risk Reduction Consortium. Informed by in-depth interviews with key informants, the argument is made that the dedicated efforts of national and international non-governmental organisations, multilateral agencies and donors in mainstreaming DRR demonstrate that considerable progress can be made even where government departments are protective of their own interests and are slow to enact policies to support DRR. The paper suggests however, that without stronger engagement of key political actors the prospects for further progress in DRR may be limited. The findings have implications for other post-conflict countries or weak states engaging in DRR

Spatial validation of large-scale land surface models against monthly land surface temperature patterns using innovative performance metrics

Land surface models (LSMs) are a key tool to enhance process understanding and to provide predictions of the terrestrial hydrosphere and its atmospheric coupling. Distributed LSMs predict hydrological states and fluxes, such as land surface temperature (LST) or actual evapotranspiration (aET), at each grid cell. LST observations are widely available through satellite remote sensing platforms that enable comprehensive spatial validations of LSMs. In spite of the great availability of LST data, most validation studies rely on simple cell to cell comparisons and thus do not regard true spatial pattern information. The core novelty of this study is the development and application of two innovative spatial performance metrics, namely, empirical orthogonal function (EOF) and connectivity analyses, to validate predicted LST patterns by three LSMs (Mosaic, Noah, Variable Infiltration Capacity (VIC)) over the contiguous United States. The LST validation data set is derived from global High-Resolution Infrared Radiometric Sounder retrievals for a30 year period. The metrics are bias insensitive, which is an important feature in order to truly validate spatial patterns. The EOF analysis evaluates the spatial variability and pattern seasonality and attests better performance to VIC in the warm months and to Mosaic and Noah in the cold months. Further, more than 75% of the LST variability can be captured by a single pattern that is strongly correlated to air temperature.The connectivity analysis assesses the homogeneity and smoothness of patterns. The LSMs are most reliable at predicting cold LST patterns in the warm months and vice versa. Lastly, the coupling between aET and LST is investigated at flux tower sites and compared against LSMs to explain the identified LST shortcomings<br/

Exploring needs, barriers to, and facilitators of rehabilitation exercise following revision hip replacement - a grounded theory study

Purpose: Evidence on rehabilitation after revision total hip replacement (THR) is inadequate and development of rehabilitation interventions is warranted. Even so, little is known about patients’ experiences with revision THR rehabilitation. This study aimed to explore patients' rehabilitation exercise experiences after revision THR.Materials and methods: Using constructivist grounded theory, we conducted semi-structured qualitative interviews with twelve patients with completed or almost completed rehabilitation exercise after revision THR. Data collection and analysis were a constant comparative process conducted in three phases; initial, focused, and theoretical.Findings: From the data, we generated a substantial theory of the participant’s circumstances and ability to integrate rehabilitation exercise into their everyday life after revision THR. Four categories were constructed based on patients’ experiences in different contexts: hesitance, fear avoidance, self-commitment, and fidelity.Conclusions: This study highlighted that patients’ expectations, past experiences, attitudes, trusts, engagement, and circumstances interact to influence engagement and adherence to rehabilitation exercise and described four categories relating to the integration of THR rehabilitation exercise into their everyday life. Clinicians should be aware of and account for these categories during rehabilitation exercise. Tailored individual rehabilitation exercise interventions and clinician approaches to optimize commitment and adherence are needed among patients with revision THR