The 99.74% Question – On the Monterrazas de Cebu Brouhaha

The study is a presentation deck, not a research paper, and the data came from the developer

Before examining the findings themselves, the nature of the document must be clearly established. The UP-IESM study, now available for review, is a 27-slide PowerPoint-style presentation produced by the UPD-CS-IESM Environmental Hydrology Laboratory. It is not a peer-reviewed research paper. (there is none available so far) It does not carry a methodology section with full technical specifications. It does not disclose the hydrological model parameters, calibration data, or validation procedures that would normally accompany a publishable scientific study.

More significantly, the cover page of the presentation states plainly:

This disclosure, which received virtually no attention in media coverage of the study's findings, means the hydrological model was built using data supplied by the very developer whose project was under investigation. The second sentence of that disclaimer, that methodology and conclusions are independent of the data provider, was written by the researchers themselves. There is no third party that verified this independence claim. In formal scientific and legal contexts, independence is not established by the party conducting the study declaring themselves independent. It is established through transparent disclosure of methodology, independent verification of input data, and external peer review. None of those mechanisms are present in this presentation.

Furthermore, this type of disclaimer is standard boilerplate language used in commissioned studies and consulting reports. It essentially means the researchers drew their own conclusions and were not told what to find. It does not mean the researchers independently verified all input data, conducted their own site surveys, or confirmed the accuracy of the information provided to them. Those are very different levels of independence, and only the latter would justify the characterization of this study as truly independent science.

The alleged claim of "independence" does not survive the study's own cover page disclosure

In his video statement, Slater Young told the public that the UP study was done by "scientists with no connection to the project, no stake in the project." This is a specific, verifiable factual claim and it is directly contradicted by the study's own first slide, which states that development and site data were provided by MONT Property Group for modeling purposes.

The scientists may have had no financial stake in the project. That is accepted in good faith. But a hydrological simulation model is only as good as the data that goes into it. The foundational inputs of the model, specifically the pond dimensions and capacities, the site topography and drainage configurations, the land cover classifications, the detention pond locations and specifications, and the development footprint, all came from the developer. That is a data connection to the project that goes to the very heart of the model's outputs.

A hydrological simulation model works in a simple sequence: input data leads to model methodology which leads to output conclusions. The researchers may have applied their methodology completely independently and in perfect good faith. But if the input data did not accurately reflect actual site conditions on the night of November 4, 2025, the conclusions will reflect those inaccuracies regardless of how rigorously the methodology was applied. The independence of the methodology does not rescue the accuracy of the output if the data was wrong, incomplete, or optimistic.

The connection that matters in a simulation model is not whether the researchers had a financial stake. It is whether the data they were given accurately represented reality. On the night of Typhoon Tino, reality included heavily silted ponds, two collapsed structures, fewer functioning ponds than the approved design required, and a hillside stripped of 734 of its 745 trees. Whether the developer's data reflected any of those conditions is unknown because the data inputs were never disclosed.

The study never disclosed its runoff coefficient or any equivalent parameter, yet no hydrological simulation can exist without one

This is arguably the strongest single technical argument in this entire examination, and it has gone completely unnoticed in all public discourse about the study. To understand why it matters, it is necessary to first understand a fundamental and non-negotiable principle of hydrological science.

Every hydrological simulation that involves rainfall and surface runoff must, by definition, use some parameter that determines how much of the rainfall is absorbed by the ground and how much becomes surface runoff. This is not optional. It is not a supplementary technical detail. It is not something that can be assumed away or left to default settings without consequence. It is physically impossible to simulate runoff without first making an explicit assumption about how much of the rainfall becomes runoff in the first place. That assumption is the foundation upon which every discharge figure, every pond performance result, and every percentage in the study is built.

In different hydrological modeling methodologies and software platforms, this parameter appears under different names and in different forms, but it is always present in some form:

The Runoff Coefficient (C) is the simplest and most direct expression, used in the Rational Method formula Q = CiA, where Q is peak runoff discharge, C is the runoff coefficient, i is rainfall intensity, and A is the catchment area. A value of C = 0.85 means 85% of rainfall becomes runoff and only 15% is absorbed. A value of C = 0.30 means 70% is absorbed and only 30% becomes runoff. The difference between these two values, applied to 428mm of rain over 140 hectares, is the difference between roughly 180,000 m³ and 509,000 m³ of runoff, a gap of over 300,000 m³ that dwarfs the entire pond capacity of 52,468 m³.

The SCS Curve Number (CN) is another widely used approach developed by the United States Department of Agriculture Soil Conservation Service. It is a dimensionless number ranging from 0 to 100 that captures soil type, land cover classification, and antecedent moisture conditions and produces a result functionally equivalent to the runoff coefficient. A curve number of CN = 70 corresponds roughly to a runoff coefficient of 0.40 to 0.50 under normal conditions. A curve number of CN = 90 corresponds to a runoff coefficient of 0.75 to 0.85, appropriate for saturated, compacted, or impervious surfaces. The antecedent moisture condition at the time of rainfall, specifically whether the soil was dry, normal, or already saturated, is a critical adjustment factor that can shift the effective curve number by 15 to 25 points, dramatically increasing the modeled runoff volume.

Infiltration parameters such as the Green-Ampt infiltration rate or the Horton infiltration decay equation are used in more complex physically-based models and serve the same fundamental purpose of determining the rate at which soil absorbs water versus the rate at which water becomes surface runoff. Under saturated soil conditions, these parameters approach zero absorption, meaning virtually all rainfall becomes runoff regardless of land cover.

Land cover and soil type inputs in distributed hydrological models such as HEC-HMS, SWAT, or similar watershed modeling software automatically generate equivalent runoff estimates based on classified land cover and soil data fed into the model. These inputs are not neutral technical choices. They are the primary determinants of how much runoff the model generates, and they must come from somewhere.

Whatever method the UP-IESM researchers used, and the 27-slide presentation does not identify which software or methodology was employed, the model had to make this determination somewhere. The simulation produced specific discharge values measured in cubic meters per second for individual ponds across specific time periods. Those numbers could not have been generated without the model first determining how much of the 428mm of rainfall became surface runoff flowing into those ponds. There is no simulation methodology in existence that bypasses this step.

Yet across all 27 slides of the UP-IESM presentation, not one of these parameters is disclosed in any form. The study shows the results of the simulation but never shows the inputs that produced those results.

What the numbers actually look like across the full range of possible runoff coefficients

To understand the significance of this undisclosed parameter, consider what happens to the required pond storage capacity when the runoff coefficient is varied across its full realistic range for the Monterrazas site. The total rainfall volume over 140 hectares from 428mm of rain is 599,436 m³. The table below shows what 99.74% capture would require at each coefficient, compared against the only publicly confirmed pond capacity figure of 52,468 m³ for the current 23-pond post-typhoon system:

* 52,468 m³ is the capacity of the current expanded 23-pond system reported after post-typhoon remediation. The actual capacity of the original 18 ponds during Typhoon Tino has not been confirmed in any publicly available document. Using the larger post-typhoon figure here is deliberately generous to the developer. Rows highlighted in red represent the professionally defensible range for the documented site conditions. Even so, the ponds remain insufficient at every runoff coefficient across the entire range.

The verdict is the same at every single value across the entire range. The ponds were insufficient at every conceivable runoff coefficient. The gap between required storage and actual capacity grows from 7,320 m³ at the most generous impossible assumption to 485,395 m³ at the most realistic upper end. At the professionally defensible minimum of C = 0.85, the shortfall alone, 455,516 m³, is nearly nine times the entire capacity of the pond system.

This range matters because without knowing what runoff coefficient or equivalent parameter the UP study used, we do not know where on this table the study's model was operating. The choice of this single undisclosed parameter is the difference between a study that appears to support the developer's defense and one that would devastate it.

Why this matters beyond mere technical completeness

The land cover classification that almost certainly served as the primary source of the equivalent runoff parameter in this study was identified on page 7 of the presentation. The site was classified as grassland before development. This classification, which came from developer-provided site data, would automatically generate a curve number and equivalent runoff coefficient in any standard modeling software corresponding roughly to C = 0.35 to 0.50, placing the model somewhere in the middle rows of the table above.

Here is the critical technical problem. The study itself confirms on page 13 that the soil was fully saturated during Typhoon Tino. In standard hydrological modeling practice, saturated antecedent moisture conditions require the curve number to be adjusted upward significantly, typically by 15 to 25 points. A grassland curve number of CN = 70 under normal conditions becomes CN = 87 to 92 under saturated conditions, corresponding to a runoff coefficient of C = 0.75 to 0.85 or higher, placing the realistic model value firmly in the lower rows of the table above where the shortfall runs into the hundreds of thousands of cubic meters.

If the model did not apply this saturation adjustment, it would have systematically and substantially underestimated the volume of runoff the ponds needed to manage. Furthermore, using a grassland classification on a site where 734 trees had been removed and heavy earthmoving equipment had been operating across 140 hectares is itself questionable. Compacted soil from heavy machinery can have infiltration rates as low as 10% to 20% of undisturbed soil, pushing the effective runoff coefficient well above even the saturated grassland value.

The study showed the public an answer but concealed the question. It produced discharge figures and pond performance percentages without disclosing the single most consequential class of assumptions that determined those figures. The table above makes the stakes of this undisclosed parameter impossible to ignore. The public, the affected communities, and the regulators who lifted the stoppage order deserved to know where on that table the UP study was operating. They were never told.

The developer's engineer misrepresented the study's own conditional 99.74% finding

This is the most technically provable counter-argument, and the study's own text now makes it inarguable. The UP-IESM presentation states on pages 18 through 21, in its own words:

Three words that appeared in the study were never repeated at the press conference: if they are big enough.

The study itself acknowledged this conditional explicitly. The 99.74% was not a statement of what actually happened. It was a statement of what the model showed could happen under conditions where the ponds had sufficient capacity. The developer's construction head then presented this conditional finding as an accomplished fact, with no mention of the qualifying condition that the researchers themselves included.

Furthermore, the study's own page 15 directly contradicts the impression of near-perfect performance by stating explicitly: "If it rains too much and the ponds become too full, like what happened in Ponds 3 and 4, the extra water cannot be contained anymore. Basically, water keeps coming in and water keeps flowing out."

The study therefore simultaneously contains evidence of pond overflow during the actual typhoon event and a conditional 99.74% figure that only applies when the ponds are large enough. The engineer presented only the latter to the public, and Slater Young repeated the same selective presentation in his April 19 video.

The realistic runoff coefficient for Monterrazas de Cebu was most likely 0.85 or even higher

The runoff coefficient is not an arbitrary assumption. It is determined by documented site conditions. Every single known characteristic of Monterrazas during Typhoon Tino pushed the coefficient toward the upper extreme of the table presented in section 3.

734 out of 745 trees were removed, leaving essentially bare denuded earth, pushing C toward 0.60 to 0.80. The steep mountain slope at approximately 1,000 feet elevation accelerates runoff and reduces infiltration time, pushing C toward 0.70 to 0.85. Heavy earthmoving equipment operating across 140 hectares compacted the soil and dramatically reduced natural infiltration capacity, pushing C toward 0.70 to 0.85. The ground was fully saturated, a condition confirmed by the UP study itself on page 13, meaning the soil behaved almost like an impervious surface regardless of other factors, pushing C toward 0.85 to 0.95. The 428mm of rain falling in 24 hours meant rainfall intensity exceeded natural infiltration rates at virtually every point on the site, pushing C toward 0.80 to 0.90.

There is not a single documented site condition pulling the coefficient downward. A professionally defensible estimate for Monterrazas during Typhoon Tino is C = 0.85 as a conservative minimum, yielding a required pond capacity of approximately 507,984 m³ as shown in the table in section 3, roughly 9.7 times the actual confirmed capacity of 52,468 m³. At C = 0.90, the shortfall reaches 485,395 m³, nearly ten times the pond capacity.

The study's baseline comparison ignored the loss of 734 trees

One of the most revealing findings from reviewing the actual study document is on page 7. In establishing the pre-development baseline for comparison, the study classified the Monterrazas site as "grassland before development." This is the land cover condition against which all scenarios were modeled and compared.

This single methodological choice has enormous implications. The DENR confirmed that a 2022 tree inventory recorded 745 trees on the site, of which only 11 remained at the time of inspection after the typhoon. The study's model did not attempt to reconstruct what the site's hydrological condition would have been with those trees present. It simply used grassland as the baseline.

Grassland and forested or partially wooded land have very different hydrological properties. A hillside with tree cover absorbs rainfall significantly more effectively than bare grassland through canopy interception, root absorption, and organic soil matter. By using grassland as the baseline rather than the condition the site was in before development began in earnest, the study potentially understated the degree to which the development changed the site's runoff characteristics. The site that should have been the comparison point was not bare grassland. It was a hillside with 745 recorded trees that were progressively removed as development proceeded. That hillside would have absorbed significantly more rainfall than bare grassland, and its loss represents a genuine hydrological change that the study's baseline choice effectively erased from the analysis.

This baseline choice also directly affects how the study's most cited figures should be understood. The developer and Slater Young repeatedly cited two figures in every public statement and press conference: 99.74% and 78%. Both figures come from the study. Both figures carry conditional qualifiers that were never mentioned publicly.

The 99.74% appears on slides 18 through 21 with the explicit qualifier "if they are big enough," meaning it only applies when the ponds have sufficient storage capacity, a condition the study itself acknowledges was not met when ponds 3 and 4 overflowed during the actual typhoon event.

The 78% appears on slide 14 with an equally important qualifier. The study states the ponds were able to lessen flow by about 78% "when rainfall levels remained within what the ponds were designed to handle." That condition, rainfall remaining within design capacity, was explicitly not met during Typhoon Tino. The study itself shows this on slide 15 where it describes ponds 3 and 4 becoming overwhelmed with water continuously flowing in and out uncontrolled.

So both figures, 99.74% and 78%, describe performance under conditions that the study itself confirms did not exist during the actual typhoon event. Both were cited publicly without their qualifying conditions. And both were cited prominently and repeatedly while the developer and Slater Young never once mentioned the finding that appears on slide 22.

Slide 22, titled "From a bird's eye view," states explicitly that the development had little to no effect on flooding and that flood extents slightly decreased by approximately 2% compared to when the area was undeveloped grassland. This finding is repeated on the Summary of Findings slide, slide 24. The 2% figure refers specifically to a comparison between the development with its detention ponds versus the same land left as undeveloped grassland with no intervention whatsoever. It does not mean flooding decreased compared to what the site would have been like before development began. It means the entire 140-hectare engineered development with all its detention ponds achieved a net basin-wide flood reduction of approximately 2% compared to simply leaving a degraded grassland hillside alone.

A 2% improvement over bare grassland, achieved through a 140-hectare development with an engineered detention pond system, is not evidence of exceptional flood mitigation. It is the minimum conceivable benchmark. And it is a benchmark against a baseline that itself understated the site's pre-development absorption capacity by ignoring the 745 trees that were there before large-scale earthworks began.

The developer repeatedly cited 99.74% and 78%, both conditional figures that did not apply to actual typhoon-night conditions, in every public statement while never once mentioning slide 22's finding that the development's net effect on basin-wide flooding was a mere 2% improvement over leaving the land as bare grassland. The public was given the best-case conditional pond performance figures but never the overall flood impact finding that appeared in the same document on slide 22 and again on slide 24. That omission, in the context of a regulatory decision affecting public safety, is not a minor oversight. It is the difference between an accurate public understanding of what the science actually found and the impression that was deliberately constructed in its place.

The study's own saturation finding undermines the engineer's claim

This is perhaps the sharpest internal contradiction in the developer's defense. The study states clearly on page 13 that flooding during Typhoon Tino was primarily driven by rainfall intensity and rapid soil saturation, and explains that once the soil becomes saturated it cannot absorb more rain and the extra water flows over the surface just like water flows over concrete and asphalt surfaces.

But full ground saturation also means the runoff coefficient approaches its maximum value, placing it firmly in the lower rows of the table in section 3, which means almost all 428mm became surface runoff, which in turn means the volume the ponds needed to capture to reach 99.74% becomes enormous, far beyond their physical storage capacity.

Either the ground absorbed most of the rainfall, in which case saturation was not the primary flood cause, or the ground was saturated and most rainfall became runoff, in which case the ponds were nowhere near sufficient to capture 99.74% of it. Slater Young's video statement repeats both claims without acknowledging this contradiction.

The ponds' effective capacity was further reduced by siltation and structural collapse, and the pre-typhoon capacity itself remains unverified

The 52,468 m³ figure represents the nominal design capacity of the current 23-pond system, the theoretical maximum under ideal conditions after post-typhoon expansion and remediation. Critically, this is not the capacity that existed during Typhoon Tino. The combined capacity of the 18 ponds present during the typhoon has never been independently confirmed in any publicly available document. The only publicly reported capacity figure is 52,468 m³ for the subsequently expanded system. The actual storage capacity of the original 18-pond configuration at the time of the typhoon therefore remains unverified, which is itself a significant gap in the public record.

Whatever that pre-typhoon capacity was, the actual usable capacity during the storm was further and significantly reduced by three additional documented failures. First, DENR inspectors confirmed the ponds were heavily silted at the time of the typhoon, directly reducing usable storage volume below even the nominal design figure. Second, two of the 18 ponds physically collapsed during the typhoon, removing a confirmed portion of total system capacity at the precise moment it was most critically needed. The study's own page 15 acknowledges that Ponds 3 and 4 became overwhelmed during the event. Third, DENR inspectors found the site had fewer and smaller ponds than indicated in the approved engineering designs, with only 12 functioning ponds found against an approved plan of 17, meaning the system was already operating below its permitted design specification before the storm even arrived.

Taken together, these three factors mean that the analysis in this examination is already generous to the developer in using the post-typhoon 52,468 m³ figure as a baseline. The real effective storage available during the height of Typhoon Tino was almost certainly substantially lower than any figure currently in the public record.

The study only modeled 9 of the 18 ponds in detail

A careful review of the study's appendices on pages 26 and 27 reveals that the detailed pond-by-pond analysis covers only Ponds 3 through 9. The study does not present individual modeling results for all 18 ponds that were present during the typhoon.

This raises a question the presentation does not answer: what were the performance characteristics of the remaining ponds that were not individually modeled? The overall conclusions about pond effectiveness are drawn from a subset of the system, and it is not clear from the presentation whether the unmodeled ponds performed similarly, better, or worse than those that were analyzed. A study used to justify the resumption of construction and the lifting of regulatory orders should account for the full system, not a selected subset of it.

The project violated 10 of 33 ECC conditions, the study most likely models compliance, not reality

Perhaps the most fundamental counter-argument is this: the UP study simulated the detention pond system as designed and as fully functioning under ideal compliance conditions. But the DENR found the project was violating 10 of 33 ECC conditions at the very time of the typhoon. A hydrological model that assumes full engineering compliance cannot legitimately be used to defend a project that was demonstrably and documentably non-compliant at the time of the disaster.

The site itself has a documented history of posing flood and landslide risks to downstream communities

The Typhoon Tino flooding was not the first time this specific hillside triggered regulatory sanctions for causing downstream harm. The site's permit was temporarily revoked in 2008 following a mudslide in Barangay Guadalupe, and again in 2011 following flooding in nearby lowland areas. Both incidents occurred under prior ownership and cannot be attributed to the current owners and developers, which entered the picture around the year 2019. This history is raised here not as evidence of misconduct by the current developer but as evidence of something more fundamental: this particular hillside has a documented track record of posing flood and landslide risks to downstream communities under conditions of development. The geology and hydrology of the site did not change when ownership changed. The steep slopes, the drainage patterns, the relationship between upland disturbance and downstream flooding, all of these are characteristics of the land itself, not of any particular developer. That history should have informed the risk assessment for any subsequent development on the same site. It raises legitimate questions about whether the site's inherent geological and hydrological risks were adequately weighed when the current development was approved, and whether a site with two prior regulatory sanctions for causing downstream harm was an appropriate candidate for a 140-hectare upland residential development in the first place. The fact that Typhoon Tino produced a third such incident, this time far more deadly than the previous two, suggests that the warnings embedded in that history were not taken seriously enough by anyone involved in approving, developing, or regulating this site.