Flood estimation for ungauged catchments in the Philippines

Abstract. Flood magnitude and frequency estimation are essential for the design of structural and nature-based flood risk management interventions and water resources planning. However, the global geography of hydrological observations is uneven; in many regions, such as the Philippines, data are spatially and/or temporary sparse, limiting the choice of statistical methods for flood estimation. We evaluate the potential of pooling short historical data series for ungauged catchment flood estimation. Daily mean river discharge data were collected from 842 sites, with data spanning from 1908 to 2018. Of these, 513 candidate sites met criteria to estimate a reliable annual maximum flood. Using the index flood approach, a range of controls were assessed at national and regional scales using land cover and rainfall datasets, and GIS-derived catchment characteristics. Multivariate analysis for predictive equations for 2 to 100 year recurrence interval floods based on catchment area only have R2 ≤ 0.59. Additionally, adding a rainfall variable, the median annual maximum 1-day rainfall, increases R2 to between 0.56 for Q100 and 0.66 for Q2. Very few other variables were significant when added to multiple regression equations. Although the Philippines exhibits regional climate variability, there is limited spatial structure in predictive equation residuals and region-specific predictive equations do not perform significantly better than national equations. Relatively low R2 values are typical of studies from tropical regions. The predictive equations are suitable for use as design equations for the Philippines but uncertainties must be assessed. Our approach demonstrates how combining individually short historical records, after careful screening and exclusion of erroneous data, generates large data sets that can produce consistent results. Extension of continuous flood records is required to reduce uncertainties but national-scale consistency suggests that extrapolation from a small number of carefully selected catchments could provide nationally reliable predictive equations with reduced uncertainties. </jats:p

River Styles and stream power analysis reveal the diversity of fluvial morphology in a Philippine tropical catchment

Characterisation of hydromorphological attributes is crucial for effective river management. Such information is often overlooked in tropical regions such as the Philippines where river management strategies mainly focus on issues around water quality and quantity. We address this knowledge gap using the River Styles Framework as a template to identify the diversity of river morphodynamics. We identify eight distinct River Styles (river types) in the Bislak catchment (586 km2) in the Philippines, showing considerable geomorphic diversity within a relatively small catchment area. Three River Styles in a Confined valley setting occupy 57% of the catchment area, another three in a partly confined valley setting occupy 37%, and two in the remaining 6% are found in a laterally unconfined valley setting. Five characteristic downstream patterns of River Styles were identified across the catchment. We observe that variation in channel slope for a given catchment area (i.e., total stream power) is insufficient to differentiate between river types. Hence, topographic analyses should be complemented with broader framed, catchment-specific approaches to river characterisation. The outputs and understandings from the geomorphic analysis of rivers undertaken in this study can support river management applications by explicitly incorporating understandings of river diversity and dynamics. This has the potential to reshape how river management is undertaken, to shift from reactive, engineering-based approaches that dominate in the Philippines, to more sustainable, ecosystem-based approaches to management

Climate data used to study the potential impacts of climate change on future hydrological regimes and water resources (2010-2050) in the Philippines

The collection contains downscaled ERA-Interim and climate scenario data, derived from three global climate models (BCM2, CNCM3 and MPEH5), for the Philippines. ERA-Interim (1979-2010) is the reanalysis dataset used to generate climate data in the absence of actual climate observations

Кум до кумы

Ой, шоў ж кум до кумы/ І нэс куль соломы, / А у той соломе / Черевічкі куме

Gamification in a Virtual Ecology (GIVE): Enhancing Classroom Engagement in Physical Education among Senior High School Students

The study was geared toward determining the influence of integrating Gamification in a Virtual Ecology (GIVE) in enhancing classroom engagement in physical education among senior high school students in a state university in Pampanga, Philippines. This qualitative-descriptive study included a complete enumeration of the Grade 12 Technical-Vocational-Livelihood (TVL) students who voluntarily participated in this qualitative investigation (n = 58) by responding to open-ended questions. Results of the open-ended questionnaire decipher the influence of gamification on students’ level of engagement and the barriers encountered upon its inclusion. The study utilized Braun and Clarke's Thematic Analysis strategy, which was aided by computer-assisted qualitative analysis software, MAXQDA Analytics Pro 2022. The study revealed two emerging themes that described the influence of gamification in the students' virtual ecology, namely: (1) the effects of the integration of gamified instruction on students’ engagement; and (2) students' problems in using gamified instruction. The findings of this study may predate the institutionalization of the prospective enhancement of the teacher’s capabilities through the aid of gamification to improve the classroom engagement of the students in a virtual ecology towards a better understanding of the lessons in physical education settings

For each basin under each scenario, the minimum, median, maximum and upper and lower quintiles were calculated and compared with the baseline scenario.

<p>An increase in streamflow was indicated with a green bar and a decrease with a red bar. The different lengths of the horizontal bars indicate the number of scenarios with an increase or decrease for the dry (left) and wet (right) season.</p

Yearly average water balance produced by the BCM2, CNCM3 and MPEH5 GCMs for A1B (top row) and A2 (bottom row) scenarios in comparison with the baseline.

<p>A positive number (%) indicates an increase of available water, a negative number indicates a decrease. The (<i>μ</i>_1/2) and <i>β</i> of the Gumbel distribution were determined for all basins using <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0163941#pone.0163941.e003" target="_blank">Eq 3</a>. An increase or decrease in median streamflow compared to the baseline is displayed with a percentage in the box-plot, while an increase (+) or decrease (-) in variability (<i>β</i>) is also shown in the box-plot.</p

Water balance for the four different seasons according to the interpolated Eraint dataset is shown in the middle.

<p>The four figures show the water balance for Dec-Feb (top-left), Mar-May (top-right), Jun-Aug (bottom-left) and Sep-Nov (bottom-right). Surrounding this are the plotted model calibration results that compares the measured data series (blue shading) with modelled ones (box-plots). The blue lines represent the median of the measured data series, whereas the blue shaded areas represent the inter-quartile range. <i>R</i>² and volumetric efficiency (<i>VE</i>) are also presented in each of the plots.</p

The 2 (black, blue), 10 (red, turquoise) and 100 (green, pink) year return flows were calculated for all scenarios in the 24 basins.

<p>An increase or decrease in return flow is expressed as a percentage compared to the baseline scenario. Return flows for the dry period are shown in the white box and return periods of the wet season in the gray box (note the difference in scale). The dots on the right of each plot indicate the GCM and scenario used (refer to the legend).</p