Dulcepamba River Hydrologic and Hydraulic Analysis *

Transcription

1 Dulcepamba River Hydrologic and Hydraulic Analysis * Jeanette Newmiller 1 Wesley Walker 1 William Fleenor 2 Nicholas Pinter 3 August 8, Graduate Student Researcher, Center for Watershed Sciences, University of California, Davis 2 Senior Hydraulic Modeling Researcher, Center for Watershed Sciences, University of California, Davis, corresponding author, wefleenor@ucdavis.edu 3 Professor, Department of Geology, Center for Watershed Sciences, University of California, Davis * Original report prepared in English; the authors are not responsible for any errors or other changes in translation DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS

2 Abstract On March 19, 2015 a storm impacted the Dulcepamba watershed in the Andean foothills of Ecuador. The ensuing runoff and discharge produced a severe flood, which caused damage and fatalities in the village of San Pablo de Amalí. Hidrotambo S.A., owner of the hydroelectric plant adjacent to the village, produced a report stating that river flow at San Pablo de Amalí during this event was 400 cms (cubic meters per second), lasted for 4 days, and that a flood of this magnitude has a return interval of 33 years. Eyewitness accounts, along with precipitation and discharge measurements, conflict with the statements in the Hidrotambo report. Residents and a locally commissioned group of researchers and volunteers referred to in this report as the Dulcepamba Project Team (see Appendix E Figure 37), hypothesized that the damage produced by the flood resulted from construction of an intake structure for the Hidrotambo S.A. hydroelectric plant, which required rerouting the river channel closer to the town. The Dulcepamba Project Team and townspeople requested that researchers from the Center for Watershed Sciences (CWS) at the University of California, Davis (UC Davis) analyze the available data and complete a forensic analysis of the March 2015 flood. UC Davis researchers developed (1) a hydrologic model to characterize the Dulcepamba basin hydrologic and streamflow responses to meteorological events; and (2) a hydraulic model to assess the hydraulic and geomorphic processes that occurred prior to, during, and after the March 2015 event. The hydrologic model analyzed the time period that discharge and precipitation data were available ( ), along with studies of different calibration events throughout the period of record and the March 2015 event. Analysis of the model results determined that the March 2015 event peaked at a daily average flow of cms, lasted for DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS ii

3 less than 1 day, and has a return interval of 6 years (i.e., has a 1 in 6 chance of occurring in any year). The Dulcepamba hydrologic model was also used to estimate daily and monthly flow available for water diversion. The model indicates that when Hidrotambo s use right is added to required environmental minimum flows, referred to on page 49 and 50 of the companies' Environmental Impact Statement, Actualizacion del Estudio de Impacto Ambiental Proyecto Hidroelectrico San Jose del Tambo, approved by CONELEC in 2012, the total exceeded average daily flows at San Pablo de Amalí on 69.25% of days during the period of record. A two-dimensional (2D) hydraulic model was built using spatial data from a survey performed by the Facultad de Ingeniería, Pontificia Universidad Católica del Ecuador. Flow data recorded by the Dulcepamba Project Team were used to calibrate the model. Hydraulic model simulations were run using flows for the March 2015 flood from the hydrologic analyses in this report. Because spatial data were not available for the Hidrotambo intake facility, the hydraulic simulation of the 2015 event was run as if the full flow volume was passed through the reach with zero blockage. The result of this modeling was a water elevation approximately 2 m lower than the water surface elevation measured during the 2015 flood. This 2 m difference demonstrates the approximate impact of blockage in and near the Hidrotambo intake facility. Modeling also provided a 2D distribution of velocities that were used to calculate the size of boulder where motion would occur. It was determined that the peak flow of the March 2015 event was capable of moving submerged boulders up to 1 m in diameter. Hydraulic simulations were also run using a synthetic hydrograph with flow rates up to 500 cms. These flows were modeled in order to assess the very large flow estimate (400 cms) for the 2015 flood event suggested in the Hidrotambo S.A. report. The model results indicate that DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS iii

4 unobstructed flows, even up to 500 cms, would not have overtopped the left bank and inundated the town of San Pablo de Amalí. The results produced by the hydrologic and hydraulic modeling completed here indicate that the March 2015 flood event on the Dulcepamba River would not have caused the damage that ultimately occurred in San Pablo de Amalí but for other human activities at the site, in particular construction within the channel, diversion of flow, and obstruction by debris. The runoff and flow generated in the March 2015 event was smaller than other historical storms and recent flow events that did not result in the extent of damage produced during the March 2015 event. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS iv

5 Contents Abstract... ii Figures... viii Tables... xi Acknowledgments... xii Acronyms and Abbreviations... xiii 1. Dulcepamba River Basin and Flooding...1 Basin Overview... 3 Available Data... 3 Basin Data... 4 Precipitation Data... 4 Discharge Data... 5 Spatial Data... 7 March 2015 Flood Event Dulcepamba Hydrologic Model...10 Hydrologic Modeling System (HEC-HMS) HMS Meteorology Model Overview Sub-Basins and Land Use DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS v

6 Sub-Basin Parameters Canopy Surface Loss Methods Transform Baseflow Flow Network Sources Sinks Model Calibration Historical Event Studies Historical Record Study Results and Discussion April 1970, Mar. 1989, Jan. 1993, and Feb Runoff Events March 2015 Flood Historical Record February 2017 Event Historic High-Flow Events Estimating Water Availability and Low-Flow Conditions Conclusions from Hydrologic Analyses DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS vi

7 3. Dulcepamba Hydraulic Modeling...39 River Modeling System (HEC-RAS) Model Overview Spatial Data Hydrologic Data Model Calibration Time Step Surface Roughness Calibration Results Model Limitations Hydraulic Modeling Results and Discussion Incipient Motion Analysis Conclusions from Hydraulic Analyses Future Work Appendix A. Maps...62 Appendix B. Hidrotambo March 2015 Flood Report...63 Appendix C. Rainfall Isohyets...64 Appendix E. Definition of the Dulcepamba Project...65 References...66 About the Authors...67 DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS vii

8 Figures Figure 1. Dulcepamba watershed,ecuador Figure 2. Dulcepamba River location: (a) before construction, (b) after construction, and (c) after the flood event of March Figure 3. Dulcepamba watershed gage locations Figure 4. Debris blockage of the Hidrotambo intake structure. Photo provided by the Dulcepamba Team taken following the March 2015 event Figure 5. Screenshot of Dulcepamba HMS model basin Figure 6. April 1970 event - Flow at Sicoto Figure 7. April 1970 event - Flow at San Jose del Tambo Figure 8. March 1989 event - Flow at Sicoto Figure 9. January 1993 event - Flow at Sicoto Figure 10. February 2008 event - Flow at Sicoto Figure 11. March 2015 flood - Flow at Sicoto Figure 12. March 2015 flood Flow at San Pablo de Amalí Figure 13. Sicoto flood frequency relationship from observed data, annual peak flows, Figure 14. Amalí flood frequency relationship from modeled data, annual peak flows, DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS viii

9 Figure 15. February 2017 flood Flow at Sicoto Figure 16. February 2017 flood Flow at San Pablo de Amalí Figure 17. March 1983 event Flow at San Pablo de Amalí Figure 18. February 2008 event Flow at San Pablo de Amalí Figure 19. April 2010 event Flow at San Pablo de Amalí Figure 20. Average, 90% exceedance, and 10% exceedance flows by calendar date at Amalí ( ) Figure 21. San Pablo de Amalí hydrograph, , showing the environmental flow requirement and Hidrotambo s previous wet and dry season use rights Figure 22. HEC-RAS calibration profiles, comparing measured data from the Amalí station to three modeled cross sections near the measurement location Figure 23. Velocities for peak flood wave, 4:05 a.m. March 20, Note that maximum scale is 10 m/s Figure 24. Depths for peak flood wave, 4:05 a.m. March 20, Note that maximum scale is 5 m Figure 25. Water Surface Elevation (WSEL) for peak of March 2015 flood event. Positions of the intake facility and three of the lost properties are shown. Lines marked "Group 1, 2, and 3" are the locations of the cross sections in Figure Figure 26. Water Surface Elevation (WSEL) profiles; locations shown in Figure 25. Group 2 includes the WSEL estimation produced by the blockage provided by the Dulcepamba Project Team DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS ix

10 Figure 27. Flow capacity test, with pre-flood geometry and velocity distributions for flow rates up to 500 cms Figure 28. WSEL at 500 cms relative to the observed WSEL Figure 29. Flow capacity test, with pre-flood geometry and depth for flow rates up to 500 cms. 54 Figure 30. Representative boulders before and after the 2016 wet season (Photo provided by the Dulcepamba Project Team) Figure 31. Particle-stability diagram for rocks with an angle of repose of 40, from Julien (2002, p. 245) Figure 32. Calculated particle stability during the March 2015 peak flow for representative angles of repose using Eq 8.4 from Julien (2002, p. 244), c (see text) Figure 33. Velocity vectors for study reach (a), and for the area highlighted in red (b) Figure 34. Catholic University contour map, January Figure 35. Hidrotambo S.A. March 2015 flood report Figure 36. Isohyets for the Chillanes County Figure 37. Definition of the Dulcepamba Project Team provided by the team DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS x

11 Tables Table 1. Precipitation Gages... 5 Table 2. Hydrologic Model Parameters Table 3. Calibration Event Error Analysis Table 4. Sicoto and Amalí Flood Flow Return Intervals Table 5. Monthly Average and 90% Exceedance Flows at San Pablo de Amalí Table 6 Estimation of Manning's n Table 7. Measured and Modeled Flows, Depths, and Velocities used for Pre-Flood Conditions Calibration Table 8. Flow Capacity Test Results. Boulder Diameter for Incipient Motion Calculated based on Mean Depth and Velocity DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS xi

12 Acknowledgments The Center for Watershed Sciences at the University of California, Davis supported this work as part of an international outreach pilot program. Special thanks and gratitude to Rachel Conrad and the Dulcepamba Project Team for supplying data, files, and photos and for quick answers to countless questions. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS xii

13 Acronyms and Abbreviations DSS Data Storage System HEC Hydrologic Engineer Center HMS Hydrologic Modeling System INAMHI Instituto Nacional de Meteorología e Hidrología RAS River Analysis Software USACE United States Army Corps of Engineers NASA National Air and Space Administration STRM Shuttle Radar Topography Mission cms cubic meters per second 1D one-dimensional 2D two-dimensional NextGen HEC Next Generation software WSEL Water Surface Elevation USGS United States Geological Survey GPS Global Positioning System DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS xiii

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15 1. Dulcepamba River Basin and Flooding The Dulcepamba River Basin (Figure 1) is located in central Ecuador in Bolívar Province. The basin extends from the highlands of the Andean plateau to the coastal foothills. The majority of annual precipitation occurs from December to April and typically ranges from about 1500 mm to 2000 mm throughout the basin, as shown by the isohyet map in Appendix C. A storm and flood event occurred on March 19-20, Deaths, property damage, and erosion occurred in the town of San Pablo de Amalí, which is located along the south bank of the river. In 2012, Hidrotambo, S.A. began construction of a water intake facility for a run-ofthe-river hydroelectric plant. The intake facility is located on the opposite bank from the village and directly in the original flood conveyance path of the river. Photographs and eyewitness accounts suggest complete or near-complete blockage of the Hidrotambo intake by coarse sediment and other debris during the March 2015 flood event. Construction of the Hidrotambo facility involved relocation of the stream channel closer to San Pablo de Amalí. A comparison of the river location pre- and post-construction as well as post-flood conditions can be seen in Figure 2. For reference, the locations of the intake facility, observed blockage, and damaged homes are superimposed on all three images. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 1

16 ± Dulcepamba Watershed Kilometers 16 Study Area Rivers and Streams 1 N 0 Esri, HERE, DeLorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community 1 S 2 S 3 S 4 S Kilometers 280 Esri, HERE, DeLorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community 81 W 80 W 79 W 78 W 77 W 76 W Figure 1. Dulcepamba watershed,ecuador. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 2

17 ± Kilometers Estimated Blockage Lost Houses Intake Facility ( a ) ( b ) ( c ) Figure 2. Dulcepamba River location: (a) before construction, (b) after construction, and (c) after the flood event of March Basin Overview The Dulcepamba watershed is nearly 500 km 2 in size and ranges in elevation from 100 m to 3200 m above sea level. The northern and eastern areas are particularly steep, mountainous, and largely forested or covered with shrub brush. In the flatter, more downstream locations, land use is dominated by a variety of agricultural uses. The Dulcepamba River flows in a southwesterly direction, with several smaller tributaries joining the main channel. The basin outlet is in the flat plains of the coastal region. Available Data Data used in the study were provided by Rachel Conrad and her team (Dulcepamba Project Team) or from government sources. This includes shapefiles, channel geometries, precipitation and discharge data, survey data, and eyewitness accounts. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 3

18 Basin Data Shapefiles of the watershed boundaries, stream paths, land use, soil type, and vegetative cover were used to delineate sub-basins within the watershed and to estimate the initial hydrologic infiltration, storage, and loss parameters. The land use, soil type, and vegetative cover shapefiles and raster images were obtained through the Municipal Government of Chillanes (Chillanes 2012a&b) and from the Dulcepamba Project Team. Cross-section data were provided by the Dulcepamba Project Team for several reaches in the watershed, including: Dulcepamba Amalí, Chima Guapo, Chima Pesqueria, Congon Tendal, Limon, and Sicoto. The cross-sectional data were used in the hydrologic model as input geometry for the hydraulic routing. Precipitation Data Rainfall data were available for several locations within and near the watershed. Precipitation gages used in the study are listed in Table 1. Data for Chillanes (Code# M0130), San Pablo de Atenas (Code# M0131), and San Jose Del Tambo (Code# M0384) were available from the Instituto Nacional de Meteorología e Hidrología (INAMHI). Data from Chillanes and San Pablo de Atenas were particularly useful for the historical study, as records go back to January 1, 1963 and August 1, 1968 respectively. Data for the remaining sites were recorded and provided by the Dulcepamba Project Team. The sites maintained by the Dulcepamba Project Team also contained evapotranspiration (ET) data, which was useful for verification of ET modeling, and as input for the more recent historical simulation events. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 4

19 Table 1. Precipitation Gages Name Latitude ( ) Longitude ( ) Data Frequency Chillanes Daily San Pablo de Atenas Daily Sanabanan Daily San Pablo de Amalí min San Vicente Daily San Jose del Tambo Daily Discharge Data Consistent historical discharge data were available for only one gage site in the basin, Sicoto (located at , ). The gage site (Code# H0334) and data are maintained and reported by INAMHI. Daily average flow rates (cms) are available beginning January 1, Although there are several days of missing data, sufficient data exist for calibration and analysis. The gage site is located nearly 12 km upstream of, and about 1500 m higher in elevation, than San Pablo de Amalí. Daily flow data were also available for a gage site at San Jose del Tambo (located at , ), also maintained by INAMHI (Code# H0395). Although measurements are only available from , these data were still useful for calibrating the historical period of record, as well as providing an expectation of typical flow magnitudes downstream of San Pablo de Amalí. The Dulcepamba Project Team has taken instantaneous discharge measurements for additional sites (Chima Guapo, Chima Pesqueria, Chima Biloban, Chima Changuil, Chima Villa Mora, Congon Tendal, Dulcepamba Limon, San Pablo de Amalí) located throughout the watershed. For most of the period of study, these measurements were intermittent, instantaneous measurements that missed significant time periods. These data provided helpful DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 5

20 snapshots, but they were not used for calibration. Two exceptions were measurements from the Congon Tendal tributary and for San Pablo de Amalí. Data of representative dry season and storm events were available for Congon Tendal, which allowed for an appropriate estimate of Congon Tendal discharge estimates. Reasonably consistent flow discharge measurements were available for San Pablo de Amalí from March 2014 to February 2017, which allowed for use of this dataset in simulations during this time period. A basin map with all of the precipitation and discharge gage sites used in the study is shown in Figure 3. Figure 3. Dulcepamba watershed gage locations. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 6

21 Spatial Data Detailed spatial data are limited to a survey completed by the Facultad de Ingeniería, Pontificia Universidad Católica del Ecuador in January 2016 (Catholic University). The survey consisted of 176 surveyed points within an area of approximately 300 meters by 400 meters. The points are primarily along the Dulcepamba River and overbank areas adjacent to the Hidrotambo intake and extending both up and downstream. The surveyed points are representative of the post-erosion terrain. The steep bank on the San Pablo de Amalí side of the river and the main road through the village are defined. The data were provided as both an Excel file and a PDF file of the contour map produced from field measurements. The San Pablo de Amalí cross-section provided by the Dulcepmaba Project Team is near the north end of the Catholic University data. While it is not georeferenced precisely, it provides a representation of the channel shape, allowing snapshots of depth, velocity, and flow rate for calibrating the hydraulic model. March 2015 Flood Event The storm that occurred on March 19-20, 2015 produced a flood that caused significant damage and the death of three residents of San Pablo de Amalí. The maximum water elevation during the flood was observed by members of the community and referenced to fixed point on the gate of the intake structure. At a later date the Dulcepamba Team measured the elevation of that point, thus reconstructing the maximum water surface elevation during the event, useful information for calibrating modeling of the March 2015 flood. Eyewitness accounts and photographic evidence during and after the March 2015 event also highlight that the flood mobilized large volumes of coarse sediment and other debris on the DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 7

22 Dulcepamba channel and floodplain. This sediment and debris blocked the Hidrotambo intake structure within the Dulcepamba channel (Figure 4). Blockage as illustrated in the photograph would displace flow from the channel, creating new flow pathways, higher water levels, and potentially contributing to erosion and other damages in the inundation area. Figure 4. Debris blockage of the Hidrotambo intake structure. Photo provided by the Dulcepamba Team taken following the March 2015 event. A report produced by Hidrotambo S.A. (Soria, 2015) suggests that a flow of 400 cms (cubic meters per second) through San Pablo de Amalí began on March 20 and lasted four days. The report also states that the return interval of this event is 33 years, suggesting the storm event and flood wave was an extraordinary event. In contrast, eyewitness accounts and the available precipitation and discharge measurements indicate that the flood wave traveled through San Pablo de Amalí beginning March 19 and did not last as long as the Hidrotambo report states. Furthermore, available observed precipitation and flow data suggest that the DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 8

23 March 2015 storm and flood flows were not particularly extreme or rare, but in fact were typical of rainstorms observed and measured repeatedly in recent years. The Dulcepamba Project Team contacted researchers from the UC Davis Center for Watershed Sciences in 2015 and 2016 and requested that they analyze available data and complete a forensic analysis of the March 2015 flood event. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 9

24 2. Dulcepamba Hydrologic Model A hydrologic model was developed to inform the hydrologic and streamflow conditions for the historical record in the Dulcepamba River basin. The Hydrologic Modeling System software HEC-HMS (HEC, 2016) was used to analyze the period of record (continuous simulation), several historic events, and the March 2015 flood event. Model results were generated for two main purposes. First, results were used to determine the recurrence interval of the March 2015 flood. Second, modeled flow results were input to a hydraulic model to create a more detailed analysis of the hydraulic and geomorphic processes that occurred prior, during, and after the March 2015 event. Hydrologic Modeling System (HEC-HMS) The Hydrologic Modeling System (HEC-HMS) software is produced and maintained by the United States Army Corps of Engineers Hydrologic Engineering Center. The software is designed to simulate the complete hydrologic processes of dendritic watershed systems, and includes many hydrologic procedures such as event infiltration, unit hydrographs, and hydrologic routing (HEC 2016). HMS utilizes a graphical user interface, integrates seamlessly with HEC-DSS (Data Storage System), has a strong computation engine, and contains quick and useful reporting tools. HMS results are stored within HEC-DSS files, thereby allowing for easy import of stage and hydrograph data into a HEC-RAS (River Analysis System) hydraulic model. Both software packages are widely used both in the USA and internationally. The physical representation of a watershed in HMS is accomplished with a basin model. Hydrologic elements (sub-basins, stream reaches, junctions, reservoirs, diversions, sources, and DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 10

25 sinks) are connected in a dendritic network to simulate runoff processes. Computation begins at the most upstream element and proceeds in a downstream direction. The software simulates the following hydrologic processes: infiltration losses (including canopy and surface components for interception/transpiration and depression storage, respectively), transform of excess precipitation into surface runoff, baseflow contributions to sub-basin outflow, and open channel flow routing (HEC, 2016). The appropriate use of the different methods depends on the physical characteristics of the modeled watershed and on the data available. The methods used in this study are discussed in the Model Overview section. HMS Meteorology The purpose of meteorological analysis in HMS is to prepare meteorological boundary conditions for sub-basins. The model is also responsible for computing the potential evapotranspiration over the land surface. Evapotranspiration can often be ignored for shortterm simulations, but becomes critical for longer simulations (HEC, 2016). For the Dulcepamba model, published monthly evapotranspiration values were used for the historical simulations (Beck, 2008). Evapotranspiration data were also available for 2014-present at the meteorological sites maintained by the Dulcepamba Project Team. These data were used directly in the more recent simulation runs, but also served to verify the monthly values used in the historical simulations. The limited availability of precipitation data prohibited the use of many of the available HMS meteorological models. Given the available gages and data availability, the inverse distance method was most appropriate. The inverse distance method creates a depth-averaged storm over a sub-basin based on the weighted distance from the nearest precipitation gages. This method was designed for real-time forecasting systems. As such, it addresses dynamic DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 11

26 data problems and availability by switching from using nearby gages to using more distant gages when the closer gages stop reporting data. A search distance can be applied to each precipitation gage to limit the radius of influence to a particular sub-basin (HEC, 2016). Model Overview The main component of the HMS model is the basin model, which is made-up of the hydrologic elements of the physical watershed. These elements are connected in a dendritic network to form a representation of the watershed stream system. The hydrologic elements represent the response and conversion of atmospheric conditions into streamflow (runoff) at specific locations in the watershed. The HMS basin schematic for the Dulcepamba watershed is shown in Figure 5. Figure 5. Screenshot of Dulcepamba HMS model basin. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 12

27 Sub-Basins and Land Use The available land use and vegetation data were used in conjunction with precipitation isohyets and topographic data to delineate the watershed into smaller sub-basins. Differences in vegetative cover, topographic slope, and soil type will yield different physical responses to rainfall runoff. By delineating the watershed into smaller sub-basins, the model is able to produce a more accurate physical response to a given runoff event. The Dulcepamba model was split into three sub-basins, Upper, Middle, and Lower. Sub-Basin Parameters A brief description of the physical parameters, their values, and their significance as inputs to the hydrologic model is provided in the following sections. Canopy Canopy storage determines the amount of precipitation intercepted by vegetation. All potential evapotranspiration is used to empty the canopy storage until the water in storage is eliminated. The potential evapotranspiration is multiplied by the crop coefficient to determine the amount of evapotranspiration from canopy storage. Canopy storage limits the amount of precipitation that will be available as runoff. Smaller values of canopy storage produce greater volumes of runoff. As such, it is necessary to input an accurate estimate of canopy storage for each sub-basin (HEC, 2016). For the Dulcepamba model, the simple canopy method was most appropriate for two reasons: the available vegetation coverage data, and the seamless integration with the deficit constant loss rate method. Two parameters are required for model input: initial storage percent DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 13

28 and maximum storage. Maximum storage is the effective maximum depth of water available in the canopy storage, and the initial storage percent sets the depth of storage filled at the beginning of the simulation. The maximum canopy storage in a sub-basin varies dependent on land cover and vegetation type(s) within the sub-basin (Dunne and Leopold, 1978). Maximum canopy storage and crop coefficient values used in the model were determined by land use and crop cover shapefiles provided by the Dulcepamba Project Team and the municipal government, and raster images provided from the company PlanetLabs through their Planet Ambassadors Program. Surface Surface storage measures the amount of precipitation and runoff that is stored in land surface depressions. Surface runoff will begin when the precipitation rate exceeds the infiltration rate and after surface storage is filled. Precipitation stored in the surface can infiltrate when the soil has the capacity to accept water or can evaporate. Surface storage functions in a similar manner as canopy storage. Smaller volumes of surface storage will produce greater runoff volumes. Accordingly, it is also necessary to accurately estimate surface storage for the model to accurately predict surface runoff. Two parameters are required for model input: initial storage percent and maximum storage. Maximum storage is the maximum effective depth of water available in surface storage, and the initial storage percent sets the depth of storage filled at the beginning of the simulation. The maximum surface storage in a sub-basin depends on topographic slope and land cover (Bennett, 2000). For the Dulcepamaba model, topographic data and a digital elevation model were used to estimate the average slope for each sub-basin, while land-use shapefiles and raster images were used to determine land cover. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 14

29 Loss Methods A loss method is necessary and describes the amount of precipitation that infiltrates the soil in each sub-basin. This method impacts surface runoff by determining how the sub-basin absorbs, processes, and releases water into and from the soil. When the soil has reached its infiltration capacity, all liquid precipitation is converted to surface runoff. Given the available soil and land use data and the simulation intervals, the deficit constant method was determined to be most appropriate for the Dulcepamba model. The deficit constant method uses a single soil layer to account for continuous changes in moisture content, including evapotranspiration to the canopy and percolation when the soil is fully saturated. For this method, three parameters are necessary for input: initial deficit, maximum deficit, and constant rate. The initial deficit is the initial condition for this method, reflecting the effective depth of water required to fill the maximum storage of the soil layer. The maximum deficit specifies the effective depth of water that the soil layer can hold. The constant rate describes the rate at which water is removed from storage when the soil layer is saturated (HEC, 2016). Transform The transform method calculates the timing and storage of surface runoff within a subbasin. This parameter dictates how and when excess precipitation is converted to surface runoff. The transform method controls the timing and distribution of surface runoff flow. The Clark Unit Hydrograph (CUH) method was selected for the Dulcepamba model because it can be easily and accurately calibrated. The program develops a translation hydrograph (the time DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 15

30 of concentration) resulting from a burst of precipitation. This translation is routed through a linear reservoir to account for storage attenuation effects across the sub-basin (the storage coefficient) (HEC, 2016). The time of concentration and the storage coefficient are both required as input parameters. The values are largely dependent on sub-basin area and slope and are both determined through model calibration. Baseflow A baseflow calculation is needed to account for the interaction with infiltration and surface runoff of water transferred to the subsurface. The baseflow produced by the model simulates flow in the basin during dry periods, and how flow in the basin resets following storm flows (HEC, 2016). The recession baseflow method was selected for the Dulcepamba model because of its simplicity, performance, and accurate portrayal of observed historic baseflow behavior. Three input parameters are required with the baseflow method: initial baseflow, recession constant, and ratio reset. The initial baseflow was calculated as an initial discharge per area, as this method allows for simple calibration with the observed data. The recession constant is a calibrated value that describes the rate at which baseflow recedes between storm events. Finally, the ratio to peak method was chosen to determine when baseflow is reset after a storm event. Flow Network The flow network acts as the skeleton of the model, connecting the hydrologic elements into a representation of the stream system in the basin. Flow from one element to the next is computed by routing methods for simulating open channel flow (HEC, 2016). In several of the very short reaches in the Dulcepamba watershed, the lag routing method was applied, as this DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 16

31 method only requires reach travel time and does not account for attenuation or diffusion. For the longer reaches, physical data and stream cross-sections allowed use of the Muskingum- Cunge routing method. The Muskingum-Cunge method requires total reach length, average slope, average Manning s roughness coefficient (n) for channel and overbank areas, cross section shape and geometry, and side slope ratio. Sources A source is a model element with no inflow and one outflow. Sources are typically used to represent boundary conditions to basin models, such as measured outflow from reservoirs or un-modeled headwater regions (HEC, 2016). For the Dulcepamba model, a source was used for the tributary (Congon Tendal) that enters the river just north of San Pablo de Amalí. Although several instantaneous discharge measurements were available for this tributary, it was not enough to fully calibrate sub-basin input. However, given the proximity to the town, it was determined that this flow needed to be included. Given the available data, a discharge of 4.0 m 3 /s was estimated for flood events and a discharge of 2.2 m 3 /s was estimated for the period of record simulation. Sinks A sink is a model element with one of more inflows but no outflow. Sinks are often used to represent the lowest point of an interior drainage or at the outlet of the basin model (HEC, 2016). For the Dulcepamba watershed model, a sink was placed at the location of the Hidrotambo hydroelectric outflow. For the purpose of the hydrologic study, the hydroelectric plant outflow is considered the outlet of the basin. This configuration still provides the necessary flow data at this stream location, without requiring additional, unnecessary calculations further downstream. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 17

32 Model Calibration The HEC-HMS model was calibrated to historical rainfall-runoff events and to the periodof-record data. Model parameters were adjusted (within known acceptable limits) until the model reproduced, as accurately as possible, the observed discharge at the available gage locations. Historical Event Studies Several historical events were modeled to further refine the calibration parameters and demonstrate the model accuracy. Studies were completed for runoff events in April 1970, March 1989, January 1993, February 2008, and February These events were chosen to demonstrate the model response to a range of hydrologic and meteorological conditions. Model parameters related to baseflow levels and soil moisture conditions were slightly adjusted to account for antecedent basin conditions for each simulation run. All simulations were run at a daily time step to provide an appropriate comparison to the available observed flow data. Historical Record Study A period-of-record study (continuous simulation) was completed with two objectives. The first was to determine baseline model parameter values that produced accurate model results compared to the historically observed flow data at Sicoto and San Jose del Tambo. A summary of the finalized model parameter values is listed in Table 2. The second objective was to perform a flood frequency analysis at San Pablo de Amalí by developing a historical hydrograph. A simulation was completed for the period of record from January 1, 1969 to DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 18

33 December 31, Results were produced at a daily time-step to properly compare with the available historical data. Table 2. Hydrologic Model Parameters Sub-basin Parameter Upper Middle Lower Area (km 2 ) Max Canopy Storage (mm) Max Surface Storage (mm) Max Deficit (mm) Constant Loss Rate (mm/hr.) % Impervious Time of Concentration (hr.) Storage Coefficient (hr.) Baseflow Recession Const Baseflow Ratio Results and Discussion Results of the calibration events, the continuous simulation, and the March 2015 flood simulation are presented and discussed below. April 1970, Mar. 1989, Jan. 1993, and Feb Runoff Events The April 1970 simulation ran from April 1 to April 30, 1970 at a daily time step. Observed results were available for Sicoto and for San Jose del Tambo. The hydrographs of observed and modeled flows for both locations are shown in Figure 6 and Figure 7, respectively. The timing and magnitude of some of the precipitation data are not perfect, as the model generates lower than observed flows at Sicoto for April 18 through 23, an early peak on April 16, and a larger than observed peak on April 8. Nonetheless, the model accurately DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 19

34 predicts the magnitude of the peak flow (5.41% error) and provides a good calculation of the overall flow volume (2.27% error). Error analysis data are available in Table 3. Figure 6. April 1970 event - Flow at Sicoto. Modeled results at San Jose del Tambo also agree well with the observed values for both the first flood peak (3.14% error) and the overall flow volume (2.34% error). The precipitation data again appear to suggest lower than expected magnitudes for April As such, the modeled flow for the second and third flood peaks is lower than observed. However, modeled flow is still within the same magnitude of the observed and demonstrates similar flow behavior. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 20

35 Figure 7. April 1970 event - Flow at San Jose del Tambo. The March 1989 simulation ran from March 1 to 31, 1989 at a daily time step. Observed results were only available for Sicoto, and the observed versus modeled hydrograph is shown in Figure 8. This event was chosen to portray the model's ability to handle a double-peak event, as well as to demonstrate the model's accuracy for volume calculations. The modeled results are in good agreement with the observed flows, with only 6.4% error against the peak magnitude, and 1.24% error in the total flow volume. The model also demonstrates comparable flood peak recession behavior and baseflow magnitude. Error analysis data are available in Table 3. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 21

36 Figure 8. March 1989 event - Flow at Sicoto. The January 1993 simulation ran from January 1 to 24, 1993 at a daily time step. Observed results were only available for Sicoto, and the observed versus modeled hydrograph is shown in Figure 9. This event demonstrated the model's capability to simulate low-flow events, and further demonstrated baseflow modeling. Although the timing of the peak event is slightly off, the modeled peak magnitude is highly accurate, with 0% error. The flow volume has 19.95% error, however it must be noted that the differences in flow volume for a small event will have much greater relative error. The model again reasonably mimics the pattern of the event, as well as demonstrating appropriate recession and baseflow behavior. Error analysis data are available in Table 3. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 22

37 Figure 9. January 1993 event - Flow at Sicoto. The February 2008 simulation ran from February 1 to 29, 2008 at a daily time step. Observed results were only available for Sicoto, and the observed versus modeled hydrograph is shown in Figure 10. This event was the second largest peak on record for this gage. Similar to the other events modeled, the model accurately simulated the baseflow, recession behavior, and magnitude of the peak flow (7.75% error). Overall modeled flow volume was off by 9.15%, however the error appears to be largely a result of the missing precipitation and reduced flow magnitudes on Feb. 14, 15, and 19. Although the timing of the flow peak is off by two days, the model follows the general pattern of the event. There is also some question to the accuracy of the observed data. The behavior is not typical of other flow in the basin. Error analysis data are available in Table 3. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 23

38 Figure 10. February 2008 event - Flow at Sicoto. The peak flow value and total flow volume for each calibration event, including the March 2015 event, are summarized in Table 3. As seen in the hydrographs for each event, the model consistently produced an accurate value for the peak flow, compared to the observed flow. Total flow volume was also modeled with more than acceptable accuracy. As was previously noted, the timing of the modeled peak flow was slightly off for some of the events. This is likely a result of errors in the precipitation and flow data, poor data availability (only daily data available), or error in the meteorological model. For some of the events, precipitation data were only available from one gage location, which introduces magnitude and timing errors into the meteorological model. Nonetheless, the results of these simulations demonstrate the model's ability to replicate, accurately and realistically, the observed flow hydrographs and peak flow magnitudes. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 24

39 The result of all of these event simulations is that the model successfully calculates peak flows and determines flood frequency return intervals for the Dulcepamba watershed. Table 3. Calibration Event Error Analysis Discharge at Sicoto Event Computed Peak (cms) Observed Peak (cms) Percent Error Computed Volume (1000 m 3 ) Observed Volume (1000m 3 ) Percent Error April % % March % % January % % February % % March % % Discharge at San Jose del Tambo Event Computed Peak (cms) Observed Peak (cms) Percent Error Computed Volume (1000 m 3 ) Observed Volume (1000m 3 ) Percent Error April % % March 2015 Flood Subsequent to calibration, the model was then set to run for the period of March 1 to 31, 2015, which captures the March 2015 flood event. Model results were again produced at a daily time step to provide appropriate comparison to the available gage data at Sicoto. The observed and modeled hydrographs are shown in Figure 11. The whole month was modeled to demonstrate: model portrayal of antecedent conditions in the basin, response to pre-storm conditions, response to the peak event, and the flow recession after the storm. The model produces highly accurate results of the event for the Sicoto gage location. Peak flow error is DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 25

40 only 1.56%, total flow volume error is 0.86%, and the model accurately reflects the timing of the peak and flow recession. Figure 11. March 2015 flood - Flow at Sicoto. The modeled hydrograph at San Pablo de Amalí is shown in Figure 12. The results in this plot are also at a daily time step. An additional simulation was run for the same time period with results at an hourly time step to use as input to the hydraulic model, the description and results of which will be further reviewed later in this report. Error analysis data of the modeled results are in Table 3. The results at Amalí follow a similar pattern to the Sicoto hydrograph, although at a greater flow magnitude, as expected. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 26

41 Figure 12. March 2015 flood Flow at San Pablo de Amalí. Historical Record A Log-Pearson III Distribution is commonly used for fitting frequency distribution data to predict the design flood for a river. Once the analysis is complete, the probabilities of floods of various sizes can be extracted from the curve (OSU, 2005). A Log-Pearson III Distribution was computed for the observed Sicoto data to determine the expected recurrence interval of various flood flows at Sicoto. The results, shown in Figure 13 and Table 4, suggest a return interval of about 15 years for the March 2015 event. While the return interval is greater than calculated for Amalí, the flow at Sicoto on March 20, 2015 was still significantly lower than the flow of record, observed on March 28, 1983 (26.94 cms), and a more recent event on February 19, 2008 (25.84 cms). Flood damage from either of those events did not approach what occurred in March DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 27

42 28.00 Discharge ( m 3 s) March 2015 = Return Period (years) Figure 13. Sicoto flood frequency relationship from observed data, annual peak flows, As previously noted, one of the primary goals of the historical record simulation was to generate a historical hydrograph for San Pablo de Amalí. After completing calibration of the historical record, the daily peak flow for each year of the analysis ( ) was calculated. A flood frequency analysis was then completed on the peak flows using a Log-Pearson Type III distribution (Figure 14; Table 4). For the March 2015 event, the frequency analysis indicates a return interval of about 6 years for the flow at San Pablo de Amalí (Dulcepamba-Salunguiri model gage). This is a shorter return interval than suggested by the historical record at Sicoto, and further confirms the eyewitness and other local reports that the March 2015 event was not an extraordinary storm. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 28

43 Discharge ( m 3 s) March 2015 = Return Period (years) Figure 14. Amalí flood frequency relationship from modeled data, annual peak flows, Location Table 4. Sicoto and Amalí Flood Flow Return Intervals 50% (2-yr) Percent Chance Exceedance Event (flow cms) 20 % (5-yr) 10 % (10-yr) 4% (25-yr) 2% (50-yr) 1% (100-yr) 0.5% (200-yr) Sicoto* Amalíi** *Observed Data **Modeled Data Synthetic precipitation data were input to the model to estimate the magnitude of rainfall necessary to produce a streamflow of 400 cms, as stated in the Hidrotambo S.A. report. This simulation found that over 300 mm of rain would have to fall in one day. A similar rainfall rate would have to be maintained for several days to maintain this flow magnitude for four days. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 29

44 February 2017 Event A large storm affected the southern half of the Dulcepamba watershed on February 11, The town of San Pablo de Amalí again suffered significant flood damage, fortunately residents had sufficient warning to evacuate, and no casualties occurred. Precipitation and discharge measurements are sufficient to complete a simulation for this event. However, the discharge gage at San Pablo de Amalí was swept away by the high stream flows on the night of February 11, so that only daily rainfall data were available over this time period. A simulation run was completed with the Dulcepamba model for January 25 to February 20, 2017 at a daily time step. Plots of the hydrographs at Sicoto and San Pablo de Amalí are shown in Figure 15and Figure 16. This event was largely confined to the southern half of the Dulcepamba watershed. As such, there was little runoff near Sicoto. The discrepancy between the observed and modeled flow at Sicoto is likely because the flows for this period were estimated from a stage-discharge equation and were not direct measurements. Nonetheless, the model produces good results at San Pablo de Amalí compared to the observed. Although the observed data at Amalí are instantaneous measurements and the modeled result is a daily average, the model simulates flows of the appropriate magnitude, along with the correct hydrograph trend and response to earlier storm events. The peak daily flow for this event at San Pablo de Amalí was nearly 20 cms higher than the March 2015 event, and elevated flows lasted for a longer period of time. The results of this simulation provide further evidence of two important facts related to the March 2015 event. First, the March 2015 storm and subsequent peak flow that traveled through San Pablo de Amalí was not exceptional. Second, given the relatively minimal damage that occurred from the February 2017 event, the March 2015 flood was likely exacerbated by additional complications, such as a blockage. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 30

45 Figure 15. February 2017 flood Flow at Sicoto. Figure 16. February 2017 flood Flow at San Pablo de Amalí. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 31

46 Historic High-Flow Events To provide additional comparison to the March 2015 flood, several historic high-flow events were also modeled. The following figures include modeled hydrographs for San Pablo de Amalí during the March 1983, February 2008, and April 2010 floods. The March 1983 event was the highest observed flow in the period of record for the Sicoto gage. The San Pablo de Amalí gage was modeled at a daily time step over the period March 17-April 15, 1983 to demonstrate the peak flow and the recession hydrograph (Figure 17). The daily peak flow observed was 84.5 cms, significantly higher than the flow observed during the March 2015 event. Flow was above 40 cms for almost 10 days, but followed a predictable recession compared to other large flow events. Figure 17. March 1983 event Flow at San Pablo de Amalí. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 32

47 The February 2008 event was the second highest observed flow in the period of record for the Sicoto gage. The San Pablo de Amalí gage was modeled at a daily time step over the period February 1-29, 2008 to demonstrate the peak flow and the recession hydrograph (Figure 18). The peak daily flow observed was 86.1 cms, again significantly higher than the flow observed during the March 2015 event. Flow was above 50 cms for nearly 15 days, largely due to continued precipitation after the peak. Despite the extended period of high flows (near the March 2015 event flow), no reports of damage exist in or near the town during this event. Figure 18. February 2008 event Flow at San Pablo de Amalí. The April 2010 event was the fifth highest modeled flow in the period of record for San Pablo de Amalí. The San Pablo de Amalí gage was modeled at a daily time step over the period April 5-30, 2010 to demonstrate an event with a similar hydrograph to the March 2015 event DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 33

48 (Figure 19). The peak daily flow observed was 76.1 cms, again significantly higher than the flow observed during the March 2015 flood. Although of greater magnitude, this event followed a very similar pattern to the March 2015 event. Again, no reports of damage exist in or near the town during this event. Figure 19. April 2010 event Flow at San Pablo de Amalí. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 34

49 Estimating Water Availability and Low-Flow Conditions The Dulcepamba hydrologic model can also be used to estimate monthly flow volumes and daily flows available for water diversion. Cyclical analysis was completed for the modeled discharge at San Pablo de Amalí for average, 90%, and 10% exceedance levels for daily and monthly flows over the period of Figure 20 displays the 90% and 10% exceedance flows, along with the average daily flow at San Pablo de Amalí, while Table 5 indicates the 90% and 10% exceedance flows, along with the average monthly flow at San Pablo de Amalí. Exceedance values describe the frequency that observed flows have been greater than different threshold values over the period of record. For example, the 90% exceedance flow for any given calendar day is the flow exceeded, on average, in 90% of years. Analysis such as this could potentially be extended to other locations in the Dulcepamba watershed. Figure 20. Average, 90% exceedance, and 10% exceedance flows by calendar date at Amalí ( ). DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 35

50 Table 5. Monthly Average and 90% Exceedance Flows at San Pablo de Amalí Monthly Flow Averages at Amalí (cms) Jan. Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Monthly Average % Monthly Avg. Exceedance Flow 10% Monthly Avg. Exceedance Flow To further quantify local water availability, a hydrograph showing flow at San Pablo de Amalí, along with the minimum environmental flow requirement of cms and Hidrotambo s previous wet season (6.50 cms; December 15 June 15) and dry season (1.96 cms; June 15 December 15) water right is shown in Figure 21. The period of January 2010 through February 2017 was chosen to demonstrate recent flow patterns given current land use and hydrologic conditions. Also shown is the absolute minimum flow that occurred during this period (2.26 cms; labeled caudal minimo ) and the exceedance frequency describing how often actual daily average flow has not exceeded the environmental flow plus Hidrotambo s previous use right. The model indicates that average daily flow at San Pablo de Amalí is below the environmental flow plus Hidrotambo s previous use right (both wet and dry season) 69% of days during this period. While this report analyzes available water supply, it should be noted that the hydrologic model does not account for human water use. Actual flows might be lower especially during the dry season when agricultural irrigation is highest. The Dulcepamba Project Team is currently gathering upstream water demand estimates to establish a water balance for the watershed. This effort will help inform the responsible repartition of water rights in the watershed. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 36

51 Hidrograma San Pablo de Amalí 100 Caudal (m 3 s) Días solicitado + ecologico excede caudal = 69% 6 Caudal (m 3 s) 4 2 Mínimo Caudal = 2.26 m 3 s Año Caudal Hidrograma Solicitado + Ecologico Ecologico Figure 21. San Pablo de Amalí hydrograph, , showing the environmental flow requirement and Hidrotambo s previous wet and dry season use rights. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 37

52 Conclusions from Hydrologic Analyses Hydrologic modeling of the Dulcepamba watershed calibrates well with observed data for past flood events and reliably generates accurate flow hydrographs. Results of this modeling for period-of-record simulation and simulations of specific flood events demonstrate that the March 2015 flood event was not a record flood, nor even a particularly rare event. The model results tend to confirm eyewitness accounts (Conrad, 2015, 2017, pers. comm.) for the March 2015 and February 2017 events. The model results and statistical flood analysis contradict the results suggested by the Hidrotambo S.A. report (Soria, 2015). The modeled daily peak flow was 58.6 cms (compared to Hidrotambo s suggestion of 400 cms), and the peak flow only lasted 1 day (compared to the 4 days suggested by Hidrotambo). Furthermore, the Hidrotambo report indicates a return interval of 33 years for the 2015 flood event, while the hydrologic model indicates a return interval of just 6 years. The hydrologic model ultimately demonstrates that flooding and damage in San Pablo de Amalí cannot be ascribed simply to extremely rare and extreme meteorological or hydrologic conditions in the watershed. The Dulcepamba hydrologic model was also used to inform water availability and flow exceedance levels. As noted in Figure 21, 69.25% of daily flows at San Pablo de Amalí between January 2010 February 2017 did not meet minimum environmental flow requirements plus the use rights Hidrotambo had between 2005 and DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 38

53 3. Dulcepamba Hydraulic Modeling A hydraulic model was developed to inform the hydraulic and geomorphic process that occurred during the March 2015 flood event. The River Modeling System software, HEC-RAS, was used to complete the analysis using the output from the hydrologic modeling here. The hydraulic model simulations were then used to determine the flow depth, velocity, and shear stress for an unobstructed flow. River Modeling System (HEC-RAS) Computational hydraulic modeling involves the mathematical representation of the flow of a fluid though a river system. The River Analysis System (HEC-RAS) software is produced and maintained by the United States Army Corps of Engineers Hydrologic Engineering Center (HEC). The software is capable of performing steady-state calculations in one-dimension (1-D), unsteady flow in both 1D and two-dimensional (2D) simulations, sediment transport/mobile bed computations, and water temperature/water quality modeling. HEC-RAS is capable of modeling subcritical, critical, and mixed flow regimes. The software is part of the HEC Next Generation (NextGen) hydrologic engineering software, so that it can read and write hydrologic data to HEC-DSS files for exchange between the various NextGen modules (HEC- RAS 2016). HEC-RAS was selected for its ability to perform a 1D/2D, mixed flow regime, unsteady flow simulation. The methods used in the hydraulic study are discussed in the following sections. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 39

54 Model Overview A HEC-RAS model is comprised of spatial and hydrologic data. Spatial data include river cross sections, which can extend to the overbank flood plain for one-dimensional (1D) model elements and topographic raster files for two-dimensional (2D) areas. Steady and unsteady hydrologic data are required for all boundary conditions and can be provided as flow rate or river stage hydrographs. The following paragraphs describe the spatial and hydrologic data employed by model in this study as well as a brief discussion of the relevant theory used for developing the model computational mesh. Spatial Data Spatial data for the area to be studied are limited. A topological survey was performed by students and Engineering Professor Eddy Sanchez S. at the Facultad de Ingeniería, Pontificia Universidad Católica del Ecuador (Catholic University) and produced a map dated January 9, 2016 (see Appendix A, Figure 34). This topography was deemed to be representative of the spatial conditions after the March 2015 event of concern. Aerial drone photographs and satellite imagery from Planet Labs provided information about the location of the channel before construction of the Hidrotambo intake facility, after construction but before the March 2015 event, and after the March 2015 event. Public domain topography is limited to 30-meter resolution data from the National Aeronautic and Space Administration s Shuttle Radar Topography Mission (NASA STRM). The Catholic University topographic map provided elevation contour lines and 177 surveyed data points covering an approximately 430-meter long reach of the Dulcepamba River and the adjacent village of San Pablo de Amalí. The map specifies the location of the channel centerline at the time of the survey, the road through the village of San Pablo de Amalí as well DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 40

55 as one structure near the eroded bank. The data provide enough information to establish the general slope of the channel and banks. The contour lines and surveyed points were digitized and georeferenced to produce a raster elevation model representative of the post March 2015 event. The raster was imported into HEC-RAS for 2D modeling. The drone and satellite images provided information on how the channel centerline and banks have moved over time. A drone image dated November 2, 2014 was georeferenced by tie points to established satellite imagery using ArcMap GIS software to provide better detail than the satellite imagery alone. The drone image provided the pre-2015 event location of the channel centerline and banks. Guidelines for these features were created in ArcMap and imported into HEC-RAS. Channel geometry tools within HEC-RAS were used with the location guidelines produced in ArcMap to approximate the pre-flood terrain. Eyewitness accounts and photographs during and after the March 2015 flood provide also help to inform hydraulic modeling of the event. As noted previously, coarse sediment and other debris blocked the Hidrotambo intake structure within the Dulcepamba channel (Figure 4). In addition, the maximum flood height was observed by members of the community at a fixed point on the downstream gate of the intake structure. The Dulcepamba Team later measured the elevation of that point, providing the maximum water surface elevation (WSEL) during the event. Hydrologic Data Hydrologic data for the upstream boundary of the hydraulic model were entered through DSS file into the unsteady flow editor for model calibration, flood simulation, and flood capacity testing. Four measured flows provided by the Dulcepamba Project Team were used as calibration flows. Modeled flows for the March 2015 event (in Chapter 2) were used in the DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 41

56 hydraulic modeling. Finally, a flood capacity test was run from a synthetic flow by incrementing inflow rates from 20 to 500 cms over a seven-hour period of time. Model Calibration Time Step The computational mesh cell size and timestep are related to each other through the definition of Courant number. Each cell has a single representative WSEL applied at the center of the cell. Cell size is therefore adjusted such that the slope of the line connecting the WSEL of two adjacent cell centers is minimal and is estimated by the slope of the terrain. The estimated average velocity and the average cell size are used to calculate the time step such that the Courant number has a value of 1. The cell size was initially set to 5.0 m squared. The model was run with the diffusion method and the time step adjusted until the solution was mathematically stable. The model was then run with the full momentum equations and the sizes of the cells contributing to a significant error in the calculated WSEL were decreased as required to produce reasonable tolerances. Surface Roughness Roughness is quantified in HEC-RAS and most other hydraulic modeling packages using Manning s n coefficients. There are two frequently used references used to establish a Manning s n value: either (1) a Manning s n table from Chow (1959), which contains physical descriptions for various channels, or (2) from Barns (1987), which provides a list of previously measured Manning s n values for specific rivers. The closest fitting description in Chow s table is for mountain streams and includes submerged bank vegetation but not channel vegetation, DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 42

57 steep banks, and a channel bed covered in cobbles and large boulders. The flow depth and slope are not specified. This table recommends a roughness value between 0.04 and The closest match from Barns (1987) is for Rock Creek near Darby, Montana. The study reach had an average slope of 0.04 and 50% of the boulders would be classified as 0.22 m or smaller (d 50). The HEC-RAS Users Manual references a commonly used equation derived from the Chezy and Manning s equations and dependent on roughness height and hydraulic radius. Assuming that the average boulder size (d 50) in the river is 0.5 meters, this method recommends a Manning s n between 0.06 and 0.08, which is consistent with the reference tables cited above. Due to the channel slope of the reach modeled in this study, an additional method developed by Jarret (1984) for steep slopes was considered. The Dulcepamba study reach has an average slope of 0.125, which is beyond the verified range of and 0.04 for Jarret s method. Using Jarret s method, the resulting Manning s values are between 0.23 and 0.25, considerably larger than what is suggested above. The results of the two calculated methods are summarized in Table 6. A uniform Manning s n was applied to the entire domain of the 2D area and calibration began with a value of Calibration is limited to the one measured cross section near the up-stream end of the domain. Four measured flow rates ranging from 2.77 to cms were used to calibrate the model. Manning s n values were adjusted within the recommended range until the calculated velocity and channel depths were in close agreement with the measured values. Calibration Results The final model was run with a computational grid with 5-meter cells, reduced to as small as 1 m in areas with the steepest slopes. The computational time step was 0.5 seconds, and the DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 43

58 Manning s n was set to 0.1 uniformly. Establishing matching longitudinal profiles between the measured and modeled data was not possible due discrepancies in spatial data. The Catholic University survey did not include measurements for the riverbed, and the cross-section measurements provided by the Dulcepamba Project Team indicated that the profile changes over time. Additionally, the location of the velocity and depth measurements was acquired using a GPS unit of unknown precision. Therefore, the Manning s n calibration focused on average velocity and depth at channel cross-sections. The model was run with four of the Dulcepamba Project Team s measured flows. From each run, three cross-section profiles were extracted from the approximate location of the measured data for comparison (Figure 22). A Manning s n value of 0.1 resulted in the closest match. Table 7 summarizes the mean and maximum velocity and depth values experienced in the reach for each of the calibration flows. Table 6 Estimation of Manning's n. Date Flow Rate (cms) Manning's n (roughness) Manning's n (slope) 07 Jan Jan Mar Oct Table 7. Measured and Modeled Flows, Depths, and Velocities used for Pre-Flood Conditions Calibration Date Flow Rate (cms) Measured Mean Calculated Mean Calculated Maximum Depth (m) Velocity (m/s) Depth (m) Velocity (m/s) Depth (m) Velocity (m/s) 07 Jan Jan Mar Oct DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 44

59 Depth (m) Velocity (m/s) 07JAN JAN Depth (m) Velocity (m/s) Depth (m) 25MAR Velocity (m/s) OCT Depth (m) Velocity (m/s) Station (m) Cross Section ID Calculated Mean Measured Measured Mean One_a One_b One_c Figure 22. HEC-RAS calibration profiles, comparing measured data from the Amalí station to three modeled cross sections near the measurement location. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 45

60 Model Limitations HEC-RAS uses shallow-water equations for both 1D and 2D modeling. These equations make the assumption that the channel slope is less than 1:10 (vertical:horizontal). The overall slope of this reach is 1:8, which is greater than the recommended maximum slope. HEC-RAS, currently utilizes sub-grid bathymetry to provide a more detailed cell volume and cell face area than other 2D models. We determined that by using relatively small cells in the steepest areas and utilizing higher values of Manning s n, as suggested by Jarret (1984), the model could provide reliable approximations for the purpose of this study. The model is mathematically stable while utilizing the more complex momentum equations, as discussed in the section on time-step calibration above. Stability is achieved while using a Manning s n value that is within the generally accepted guidance range as discussed in the section on surface roughness above. The limited quality of the terrain detail, as discussed in the spatial data section, is reflected in shape of the velocity and depth cross sections as seen in the calibration plots (Figure 22). While the curve shape is not an exact match, the overall depth and velocity values closely align with the measured values. Additionally, spatial or flow data were not available for the intake facility. Hydraulic modeling here assumed that the full flow volume was passed through the reach, neglecting the facility. This assumption included zero obstruction of the intake by sediment or debris, despite evidence such as shown in Figure 4. As a result, the modeling here is fundamentally conservative, necessarily underestimating water surface elevations and increased flood heights resulting from any geometrical constraints and/or blockage of the Hidrotambo facility or adjacent riverbed. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 46

61 Hydraulic Modeling Results and Discussion According to the hydrograph for the March 2015 event, the peak flood wave entered the upstream end of the modeled reach at approximately 3:55 am on March 20, 2015 and has a maximum 15-minute flow rate of 82.5 cms (58 cms daily average). Figure 23 and Figure 24 represent the flow velocity and depth distributions throughout the modeled reach as the crest of the flood wave passes. Figure 25 and Figure 26 provide the WSEL distribution and crosssection profiles, respectively. The locations of the cross sections are noted on Figure 25The cross sections for Group 1 are at the upstream end of the reach and were used for model calibration. The cross sections for Group 2 are located at the site of the blockage, as identified by the Dulcepamba Project Team. The team also provided an estimate of the WSEL during the peak of the flood even by referencing a fixed point on the gate of the intake structure. Their observed WSEL is included in the profile plot for Group 2. The cross sections for Group 3 are at the downstream end of the study area. There is no indication of inundation over the left bank at this flow rate and only small amounts over the right bank at the downstream end of the reach in the area of Group 3. In a report dated September 30, 2015 from Ing. Diego Soria Re, Gerente General, Hidrotambo S.A to Señora Doctora Gabriela Sanchez (see Appendix B), the March 2015 flood peak is estimated at 400 cms. This value is significantly higher than the 82.5 cms calculated by the modeling completed here. In order to assess the 400 cms flow suggested in the above report, a synthetic hydrograph with flows increasing to 500 cms was simulated with the model (Figure 27, Figure 29, Figure 28, Table 8). Even for this extreme flow rate, an unobstructed flow is not in danger of inundating the left bank and village of San Pablo de Amalí. It is noted that the mean velocity over the study area at 420 cms is 4.01 m/s, which is capable of inducing motion in boulders up to 1 m in diameter. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 47

62 20MAR2015 Velocity (m/s) Preflood Geometry Velocity (m/s) Figure 23. Velocities for peak flood wave, 4:05 a.m. March 20, Note that maximum scale is 10 m/s. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 48

63 20MAR2015 Depth (m) Preflood Geometry Depth (m) Figure 24. Depths for peak flood wave, 4:05 a.m. March 20, Note that maximum scale is 5 m. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 49

64 20MAR2015 WSEL (m) Pre flood Geometry Group 1 C B A Intake Facility Group 2 A C B Lost Property Group C B A WSEL (m) Figure 25. Water Surface Elevation (WSEL) for peak of March 2015 flood event. Positions of the intake facility and three of the lost properties are shown. Lines marked "Group 1, 2, and 3" are the locations of the cross sections in Figure 26. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 50

65 Group 1 Elevation (m) A B C Group 2 Elvevation (m) A B C Group 3 Elvevation (m) A B C Station (m) Observed Terrain WSEL Figure 26. Water Surface Elevation (WSEL) profiles; locations shown in Figure 25. Group 2 includes the WSEL estimation produced by the blockage provided by the Dulcepamba Project Team. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 51

66 27 cms 100 cms 180 cms 200 cms cms 340 cms 420 cms 500 cms Velocity (m/s) Figure 27. Flow capacity test, with pre-flood geometry and velocity distributions for flow rates up to 500 cms. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 52

67 Group 2 Elvevation (m) A B C Station (m) 500 cms Observed Terrain Figure 28. WSEL at 500 cms relative to the observed WSEL DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 53

68 27 cms 100 cms 180 cms 200 cms cms 340 cms 420 cms 500 cms Depth (m) Figure 29. Flow capacity test, with pre-flood geometry and depth for flow rates up to 500 cms. Table 8. Flow Capacity Test Results. Boulder Diameter for Incipient Motion Calculated based on Mean Depth and Velocity. Flow Rate (cms) Depth (m) Max Mean Boulder Diameter (m) for Angle of Repose Velocity (m/s) Depth (m) Velocity (m/s) 20º 30º 36º DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 54

69 Incipient Motion Analysis Julien (2002) contains a discussion on river stabilization, bank erosion, and riverbank riprap revetment. Equation 8.4 on page 244 is provided as a method to calculate the critical velocity of water to move boulders in the river. The equation is dependent on the depth of the flow, the angle of repose of the boulder, and the side slope of the bank if the rock is on the bank. A plot of velocity vs. stone diameter is provided for boulders with an angle of repose of 40 (Figure 31). There are six curves on the plot representing the critical velocity for five different bank slopes and the river bottom. The angularity of boulders can be defined by its angle of repose, which is defined by the number of vertices a cross-section of the boulder contains. Rounder rocks have a lower angle of repose than those with shaper angles. The photographs in Figure 30 show a representative sample of the sizes and angularity of boulders in the Dulcepamba River. The sizes range from small gravel to boulders about 1 m in diameter. Since many of these rocks have a smaller angle of repose than is provided on Figure 31, the peak flow of the March 2015 event was applied to Equation 8.4 above. The distribution of depths for the peak flow were applied together with a bank slope of 0, to represent the riverbed, and three angle of repose values, 20, 30, and 36. Critical velocities needed to move stones with diameters ranging from 0.1 to 1.0 m were calculated. These critical velocities were compared to peak velocities modeled for the March 2015 flood event to assess the largest diameter stone for each angle of repose that could achieve incipient motion (Figure 32). The results of this analysis are that the depths and velocities generated during the March 2015 flood were sufficient to move large boulders, up to ~1 m in diameter. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 55

70 Figure 30. Representative boulders before and after the 2016 wet season (Photo provided by the Dulcepamba Project Team). DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 56

71 Figure 31. Particle-stability diagram for rocks with an angle of repose of 40, from Julien (2002, p. 245). DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 57

72 Angle of Repose Boulder Diameter (m) Figure 32. Calculated particle stability during the March 2015 peak flow for representative angles of repose using Eq 8.4 from Julien (2002, p. 244), c (see text). The movement of large rocks during the 2015 flood event may have: (1) damaged any existing bank stabilization measures, (2) led to the observed obstruction of the Dulcepamba channel, and (3) subsequent mass wasting. The flow produced by the March 2015 event would not have produced the WSEL observed by the people of San Pablo De Amalí as seen in Figure 26, Group 2 without some additional contributing factor such as the observed obstruction. A closer look at the velocity vector diagram in Figure 33 indicates a 9 to 10 meter segment of the left bank near the location of the upstream boundary of the erosion event with relatively high velocities. This would indicate an area of interest as the shear stress in this segment would be the maximum experienced along the left bank and adjacent to the village. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 58

73 (a) (b) Figure 33. Velocity vectors for study reach (a), and for the area highlighted in red (b). Conclusions from Hydraulic Analyses Spatial data for the Hidrotambo intake facility was not made available for this study. Due to this, the model is representative of river conditions without the influence of the water passing through the intake facility. The photo in Figure 4is looking upstream from within the intake facility. The amount and location of the debris in the photo are an indication of the peak water level and in agreement with the water surface elevation measured by the Dulcepamba Team. Additionally the debris would have reduced the flow of water through the facility forcing it into the adjacent riverbed, as it is modeled for this study. The difference in observed vs. modeled water surface elevation can be seen in the cross sections in Figure 25 Group 2. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 59

74 Future Work The Dulcepamba Project Team recently located a topographic map of pre-construction conditions produced by Hidrotambo S.A. It appears that the topography would provide additional information about preconstruction conditions. This would allow a better direct comparison of any changes in the depth and velocity of the river through the study area. A hydraulic model of the pre-construction conditions could provide additional insight into the role the redirection of the river played in erosion, property loss, and fatalities that occurred during the March 2015 flood. Additionally, this information could help to inform future bank stabilization measures. The Dulcepamba Team has requested the complete digitized topography from government agencies. Future modeling would benefit from spatial data for the water intake facility. This data would allow the facility to be included in the model and would aid in understanding the flow conditions during the March 2015 flood. In addition, a model including these data would better inform engineering design of future bank stabilization measures. Additionally, in order to inform engineering design of bank and foundation stabilization measures the following investigations would be helpful: A geotechnical investigation be conducted to establish subterranean conditions A detailed land survey of the current conditions including the area covered by the intake facility Flow gages upstream and downstream of the intake facility Measurements of flow through the hydropower facility DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 60

75 Respectfully submitted, Center for Watershed Sciences University of California at Davis Jeanette Newmiller Wesley Walker Wesley Walker William Fleenor Nicholas Pinter DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 61

76 Appendix A. Maps PUNTO COTA PUNTO COTA Figure 34. Catholic University contour map, January DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 62

77 Appendix B. Hidrotambo March 2015 Flood Report HIDROTAMBO Energía limpia para todos HTSA AVDA. AMAZONAS N Y NN.UU FAX: 593 (2) Quito - Ecuador Ambato, 30 de septiembre de 2015 Señora doctora Gabriela Sanchez Dirección Nacional de Derechos Colectivos, Naturaleza y Ambiente DEFENSORIA DEL PUEBLO Presente: DISEÑO DE PROTECCIÓN HIDRÁULICA PARA SAN PABLO DE AMALÍ. ANTECEDENTES En Marzo 20 de 2015, se presentó en el río Dulcepamba una avenida torrencial con un caudal estimado de 400 m 3 /s que duró 4 días, precedida por un torrente. San Pablo de Amalí se encuentre en la confluencia de los ríos Dulcepamba y Salunguire, donde morfológicamente termina la cuenca de recepción e inicia el canal de desagüe. El último torrente amplió el cauce del río, al descender la crecida el cauce presenta anastomosis, cauce cruzado. Este cauce cruzado se convertirá en cause meandrico, hasta la próxima avenida en la que se repetirá el ciclo. Por la pendiente del cauce el río Dulcepamba en este sector (4,96%) es un río torrencial, razón por la que cuando aparecen avenidas tienden a ser siempre torrenciales. El período de ocurrencia de las avenidas en el río Dulcepamba es de 33 años y las de su afluente, el río Salunguire 15 años. En estío el río Dulcepamba es más caudaloso que el Salunguire, pero la parte proporcional de la cuenca que corresponde al Salunguire es mayor, razón por la que en invierno el río Salunguire es más caudaloso. DE LA PROTECCIÓN La mejor alternativa de protección en este cauce de avenidas es una escollera a pié de talud de 2,5 m de altura de dos capas con una pendiente de 45, entre la confluencia del río Salunguire en el Dulcepamba y el estero que desemboca en el río al sur del poblado. Con espigones para entarquinar el cauce meandrico. Sin más por el momento, aprovecho la oportunidad para enviarle un muy atento saludo. Ing. Diego Soria Re Gerente General HIDROTAMBO S.A. Figure 35. Hidrotambo S.A. March 2015 flood report. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 63

78 Appendix C. Rainfall Isohyets Figure 36. Isohyets for the Chillanes County. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 64

79 Appendix E. Definition of the Dulcepamba Project THE DULCEPAMBA PROJECT The Dulcepamba Project has partnered with University of California, Davis Center for Watershed Sciences to conduct hydrologic and hydraulic analyses of the Dulcepamba watershed, located on the southwestern slopes of the Andes in Bolívar Province, Ecuador. The Dulcepamba Project was commissioned by the community of San Pablo de Amalí in 2013 to conduct a water balance study of the Dulcepamba micro-watershed to better inform water use planning and allocation petitions in accordance with the Ecuadorian Water Law. The goals of the Project upon initiation were to: 1. Conduct a water availability study using data collected from hydrological and meteorological stations placed throughout the Dulcepamba watershed. 2. Conduct a water needs study through a survey of a representative 10% of the population of the watershed and by mapping current land use using satellite imagery, geographic information system (GIS) and remote sensing technologies. The Project has also looked at the risks farmers in the watershed face if they lose their legal rights to water. The scope of the Dulcepamba Project expanded to include an assessment of flood causes and ongoing flood risk below the San José del Tambo Hydroelectric Project intake works after the Dulcepamba River flooded on March 20, 2015, causing devastating damages to the Community of San Pablo de Amalí. The Dulcepamba Project team is made up of a group of dedicated researchers and volunteers from many academic and professional backgrounds including: Rachel Conrad, BA, Environmental Analysis, BA, Latin American Environment and Society, Pitzer College (May 2013 Present) Ramiro Trujillo, Lic., Law, Universidad Central de Ecuador Former Mayor of Cantón Chillanes, the cantón where the majority of the watershed is located (July 2017 Present) Pablo Tapia, MSc, Environment and Development, London School of Economics BS, Economics, Potificia Universidad Católica del Ecuador (September 2015 Present) Julio Sardan Muiba, MA, Local and Territorial Development, Facultad Latinoamericana deciencias Sociales Sede (FLACSO) (July 2015 December 2015) Manuel Trujillo, Local farmer and President of the Community of San Pablo de Amalí (May 2013 Present) Darwin Paredes, Local farmer and community engagement lead (January 2015 Present) Emily Conrad, BA, Environmental Studies, Connecticut College (September 2016 Present) Isiah Johnson, BS, Plant Sciences, University of Maryland (May 2014 August 2014) Ian Reichardt, BS, Communications, University of Maryland (January 2014 November 2016) Beatriz Stambuk, BA, Environmental Analysis, Pitzer College (May 2015 August 2016) Interns in their 3 rd or 4 th years of undergraduate studies in Biology, Environmental Studies, Environmental Analysis, Economics and Policy, and Journalism. (Various 3-4 month periods) The Project is supported by the University of Maryland Department of Plant Sciences through the donation and installation of four meteorological stations placed in the four micro-climates of the Dulcepamba watershed, and through the development of the Project s localized crop water demand calculations, which are based off of data collected by the meteorological stations and the Penmann-Monteith evapotranspiration and crop coefficient methodology. The Project has also partnered with the Potificia Universidad Católica of Ecuador to conduct technical studies such as developing a topographic survey of the area affected by the flood of March 20, The Dulcepamba Project is currently principally funded by the Conservation Food and Health Foundation and partners with the Instituto de Estudios Ecologistas del Tercer Mundo as its fiscal sponsor. Figure 37. Definition of the Dulcepamba Project Team provided by the team. DULCEPAMBA RIVER HYDROLOGIC AND HYDRAULIC ANALYSIS 65