Resilient Design with Distributed Rainfall-Runoff Modeling (2023)

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30 Aligned with the objective of the synthesis, which is to document state DOT use of DRRMs, a questionnaire was distributed to the state hydraulic engineer (or equivalent position) at the 50 state DOTs, Puerto Rico DOT, and the District of Columbia DOT. Forty-seven state DOTs and Puerto Rico DOT responded (a survey response rate of 92%) and provided input on current hydrological modeling practices and the current state of the use of DRRMs, as presented in Fig- ure 10. The survey questions and a summary of the survey results are presented in Appendix A and Appendix B, respectively. This chapter is organized into six sections: (1) description of the questionnaire rationale, (2) current status of DRRM use by state DOTs, (3) factors determining the use of DRRMs, (4) characteristics of DRRM implementation within agencies, (5) assessment of costs and benefits of DRRMs, and (6) barriers for implementation of DRRMs. Questionnaire Rationale The structure of the questionnaire was fairly simple, and its logic enabled respondents from state DOTs that do not use DRRMs to spend less time responding to the questions. The first two questions were common to all respondents; if a respondent indicated in Question 2 that DRRMs were not used, the next question was 3(A); otherwise the next question was 3(B), and the respon- dent would go over all the remaining questions—a total of 20. Current Status of DRRM Use: Questions 2–5 As indicated in Figure 11, 47 states and Puerto Rico responded to the question about the hydrological modeling techniques that are used for roadway projects; 16 transportation agencies (33%) reported using the DRRMs, and a majority of 32 agencies (67%) reported they do not use DRRMs. Figure 12 indicates that 43 agencies (90%) reported using either gage data analysis or regression equations, and 41 agencies (85%) reported using the Rational Method to determine peak discharges. Sixteen state DOTs (33%) reported using other methods for hydrologic modeling for roadway projects. Each state DOT that reported not using DRRMs was then directed to answer Question 3(A). As shown in Figure 13, according to 26 agencies (81%), advantages of regression equations and/or the Rational Method to estimate peak flow are that it is easier to use, requires less input of data, and their personnel are familiar with the techniques. Economic feasibility was reported as a factor by nine agencies (28%) for using these methods. For eight agencies (25%), the use of regression equations and/or the Rational Method is required by state regulations. Other factors/ advantages of agencies not using DRRMs to estimate peak flows are presented in Table 4. C H A P T E R   3 Survey of State Practices for Distributed Rainfall-Runoff Modeling

Survey of State Practices for Distributed Rainfall-Runoff Modeling 31 Figure 10. Map indicating the state DOTs that have responded to the questionnaire. Question 3(B) was presented only to the respondents who indicated that their state DOTs adopt DRRMs in roadway projects. Because this question and the subsequent ones were directed only to the group of 16 state DOTs that apply DRRMs, the percentages that are reported are with respect to this smaller group of DOTs instead of the entire group of respondents of the questionnaire. Question 3(B) asked which modeling tools are used. HEC-HMS (USACE) was the DRRM most used by the state DOTs—75% of the group that reported using DRRMs. The second model that was most used (44%) were SWMM-based models, including commercial implementations such as XP-SWMM. HEC-RAS 2D, with the rain-on-grid approach, is used by 31% of the agen- cies. Other gridded models, such as 2D unsteady flow (TUFLOW) and MIKE-SHE, had a smaller number of users, whereas GSSHA and FLO-2D were not used by any of the respondents. The distribution of the DRRMs or model components used by the state agencies is shown in Fig- ure 14. Table 5 provides information on the other DRRMs or modeling tools reported by state DOTs for roadway projects. The last question formulated about the status of DRRM use by state DOTs was linked to the workforce developing the modeling work. Fourteen (88%) state DOTs reported using private consultants when doing distributed rainfall-runoff modeling for roadway projects, and 13 (81%) state DOTs use in-house engineers. A minority of the agencies reported using another state or federal agency or some type of partnership with universities. Figure 15 presents the workforce currently using DRRMs for roadway infrastructure projects at state DOT agencies.

32 Resilient Design with Distributed Rainfall-Runoff Modeling Figure 11. Map with the state DOTs that have indicated the use of DRRMs in their hydrological designs and studies. States where follow-up interviews occurred are marked with a circle. Question 5 inquired about the guidance used in the application of DRRMs for a given roadway project. For this synthesis, a model user’s manual can be considered as a software user’s manual, and the National Engineering Handbook (NEH) is a federal design guidance. A total of 11 agencies (69%) reported using federal design guidance published by the organization, such as the FHWA or USACE, and models’ user manuals. The other most popular types of guidance were software training materials (nine agencies) and model training workshops and state drainage manuals (eight agencies). Figure 16 shows the guidance reported by state DOTs when developing/utilizing DRRMs. Table 6 provides information on the other guidance used by state agencies when developing/utilizing DRRMs. Factors Determining the Use of DRRMs in Hydrological Design: Questions 6–9 The following questions focused on the factors that determined the application of DRRMs for a specific project. Of the 16 state DOTs using DRRMs, 11 (69%) determined the use of DRRMs based on the advantage of defining watershed characteristics (e.g., soil type, slope, land use), and 9 (56%) agencies reported the ability to define the watershed basin size [drainage area (DA)],

Survey of State Practices for Distributed Rainfall-Runoff Modeling 33 Figure 12. Hydrological modeling techniques DOTs use for roadway projects. Survey respondents were allowed to select multiple answers. Figure 13. The factors/advantages of the use of regression equations and/or the Rational Method for hydrological estimates of peak flow for state DOTs not using DRRMs. Survey respondents were allowed to select multiple answers.

Figure 14. DRRMs or model components used by DOTs for roadway infrastructure projects. Survey respondents were allowed to select multiple answers. Other answers for Question 3(A) Recommendation from HEC Documents Rainfall distribution data is limited in rural areas. Also, rain-on-snow events are common and are represented by gage data. Regression analysis used in areas with no data, rational method is used for drainage areas less than 2 square miles in our state. We use drainage area size to help determine whether to use regional regression equations or the rational method. Past look in to using rain on grid type approach tended to higher discharge values when compared to regression equations. Since regression equations were more the standard at the time, it was deemed more economical to stay with those. Dam rules & wetland permits for coastal area require added precipitation scenarios. Supporting research. Basin area and applicability. Our Hydraulics Manual describes the criteria in selecting a method. Table 4. Other factors and advantages of the use of regression equations and/or the Rational Method for hydrological estimates of peak flow reported by state DOTs not using the DRRMs. Other Answers for Question 3(B) Count Percent WMS 2 13% WinTR-20 built into GISHydroWEB 1 6% HydroCAD 2 13% A specific distributed rainfall distribution method based on quartiles (probability) 1 6% TR-55 1 6% NCRS Model 1 6% Table 5. Other DRRMs or model components reported by state DOTs used for roadway infrastructure projects.

Figure 15. Who uses DRRMs at DOTs for roadway infrastructure projects? Survey respondents were allowed to select multiple answers. Figure 16. Guidance used by DOTs when developing/utilizing DRRMs. Survey respondents were allowed to select multiple answers. Other Answers for Question 5 On-the-job training Model user’s manual NEH Manual Table 6. Other guidance used by state DOTs when developing/ utilizing DRRMs.

36 Resilient Design with Distributed Rainfall-Runoff Modeling better spatial representation using grids, sub-catchments or hydrologic response units, and better representation/estimates of rainfall loss, runoff transformation, and routing as factors/advantages. Further descriptions of factors/advantages that state DOTs consider for determining the use of DRRMs are presented in Figure 17. Other factors/advantages reported by state DOTs are pre- sented in Table 7. Question 7 inquired about the perceived improvement the implementation of DRRMs brought to hydrological predictions. For 14 state DOTs (88%), there was an improvement in hydrological studies (e.g., peak discharge and hydrograph determination), and 10 (63%) reported improvements in hydraulic design of roadway infrastructure. Improvements in roadway resiliency assessment were reported by six agencies (38%), and improvements in short- and long-term planning were reported by four agencies (25%). Other applications were reported by two or fewer agencies and are presented in Figure 18. Table 8 contains other applications/areas reported as improved by the state agencies with the use of DRRMs. Questions 8 and 9 focused on the timeline of the DRRM use in state DOTs and whether the application of these tools has evolved over time. Of the 16 states responding, the majority 10 (63%) reported using DRRMs for 15 or more years. Fewer agencies have a more recent adoption of these models, with two (13%) using between 10 and 15 years, two (13%) using DRRMs within the past 10 years, and one within the past 5 years, as shown in Figure 19. Figure 17. Factors/advantages reported by state DOTs that determine the use of DRRMs. Survey respondents were allowed to select multiple answers. Other Answers for Question 6 Produce more effective flood risk vulnerability for network of roads. Complexity of question being asked for which modeling is being used to support response. Availability of existing data. Only when we need to account for hydrographs and storage. Project-specific needs/requirements. Table 7. Other factors/advantages reported by state DOTs when determining the use of DRRMs.

Survey of State Practices for Distributed Rainfall-Runoff Modeling 37 Figure 18. Hydrological predictions applications/areas improved with the use of DRRMs reported by DOTs. Survey respondents were allowed to select multiple answers. Other Answers for Question 7 Hydraulic design of highway bridges and culverts; flooding complaints, forensic investigations. Table 8. Other hydrological predictions applications/areas improved with the use of DRRMs. Figure 19. States using the distributed rainfall-runoff modeling techniques indicated for how many years the techniques have been implemented in their agency.

38 Resilient Design with Distributed Rainfall-Runoff Modeling Regarding the evolution of the application of DRRMs over time, eight agencies (50%) reported that these tools are being applied for the applications they initially envisioned. Four agencies (25%) reported that DRRMs are being utilized with new applications or that research on the use of these models has been conducted, and the remaining agencies (25%) stated that DRRMs have rarely been used in their agency since its implementation (Figure 20). Characteristics of DRRM Implementation Within Agencies: Questions 10–18 The subsequent group of questions focused on technical details on the application of the DRRMs within state DOTs. Questions 10 and 11 inquired about the minimum and maximum DAs for the watersheds in which DRRMs are used. The options presented for Question 10 were not representa- tive of the variability of what the practice is in state DOTs; thus, most respondents used the “Other” option for these two questions, with four agencies (25%) responding that the minimum size of the DA was 1 square mile. The other options varied from 50 acres up to 26 square miles. There were also three respondents that indicated that the minimum DA is either not a factor or is defined on a project basis. The responses for Question 10 are presented in Figure 21 and Table 9. Question 11 is analogous to Question 10 but instead focuses on the criteria of the maximum DA for selecting/utilizing DRRMs. Similar to Question 10, a minority of agencies (5, or 31%) selected among the options on the questionnaire, and most respondents selected the “Other” option. Among the options reported, the maximum size of watershed ranged from 1 to 600 square miles. Other responses indicated that the maximum size was unknown or unspecified or was not a driver in the analysis. The responses for Question 11 are presented in Figure 22 and Table 10. When asked about the data requirements they use to divide the study watershed into smaller elements for DRRMs, most agencies (15, or 94%) reported using stream network data, and 13 (81%) use DEMs. Land use/land cover and soil property data requirements were reported by nine and Figure 20. State DOTs reported DRRM usage in their agency since the models’ implementation.

Survey of State Practices for Distributed Rainfall-Runoff Modeling 39 Figure 21. DOTs’ minimum drainage area for selecting/utilizing DRRMs. Other Answers for Question 10 No minimum size, all structures have to be analyzed based on ultimate development land use. Research - One square mile. Design - 26 square miles to date. Not Specified. 100 acres. DA size is not a driver. 250 acres. 200 acres. 50 acres. 0.5 sq mi (320 acres). Project/stream specific - depends on what is being analyzed and for what reason. Table 9. DOTs’ other minimum drainage areas/criteria for selecting/ using DRRMs.

40 Resilient Design with Distributed Rainfall-Runoff Modeling Figure 22. DOTs’ maximum drainage area for selecting/utilizing DRRMs. Other Answers for Question 11 300 sq mi. 500 sq mi. To date 600 square miles. May use hybrid too. Large drainage area determined by gage information and use the DRRM for project area to facilitate pluvial flooding analysis. Not Specified. 1 sq mi. DA size is not a driver. I am not aware of a maximum. Just to keep things correct, we typically use StreamStats for most everything except pump station design. Table 10. DOTs’ other maximum areas/criteria for selecting/using DRRMs.

Survey of State Practices for Distributed Rainfall-Runoff Modeling 41 six agencies (56% and 38%, respectively), as presented in Figure 23, and “Other” data requirements are presented in Table 11. Questions 13 and 14 inquired about the types and sources of rainfall data used in DRRMs, respectively. Regarding the types of rainfall data used, the two most common were design rainfall depths for different return periods and the design rainfall distribution over time. Other options were also selected by the state DOTs. The responses are presented in Figure 24, with a single “Other” option selected and presented in Table 12. When asked about the sources of rainfall data to use in DRRMs, most agencies (81%) reported synthetic rainfall for different return periods (e.g., TP40, Atlas 14), with the least common source being downscaled data from Global Circulation Model (GCM) projections. Further information about the sources of rainfall data used by state DOTs in distributed rainfall-runoff modeling is presented in Figure 25. Table 13 contains other sources of rainfall data reported by six state DOTs. Questions 15 and 16 of the survey addressed the approach for the abstractions used in the DRRMs. The rainfall loss method most commonly used for models in roadway infrastructure projects by state DOTs is the SCS CN, reported by 15 (94%) agencies. The other alternatives more commonly cited to compute abstractions are based on depression storage and the Green- Ampt model, both reported by four (25%) agencies. Other alternatives are presented in Figure 26, with the “Other” option presented in Table 14. Figure 23. DOTs’ data requirements to divide watershed into smaller elements for DRRMs usage. Other Answers for Question 12 Existing hydraulic controls, existing adopted data, Existence of dam or obstructions. Table 11. Other data requirements to divide watersheds into smaller elements for DRRMs usage.

42 Resilient Design with Distributed Rainfall-Runoff Modeling Figure 24. Rainfall data used by DOTs in DRRMs. Other Answers for Question 13 Hydrology Panel is currently evaluating ways to account for precipitation changes due to climate changes. Table 12. Other rainfall data reported by state DOTs when using DRRMs. Figure 25. Sources of rainfall data used by state DOTs when using DRRMs.

Survey of State Practices for Distributed Rainfall-Runoff Modeling 43 Other Answers for Question 14 NOAA. Hydrology Panel is currently evaluating ways to account for precipitation changes due to climate changes. Rainfall data from Pseudo Global Warming Model Simulations. Regulatory Rainfall Distribution. Further criteria used for the selection of an appropriate storm duration. Table 13. Other sources of rainfall data used by state DOTs when using DRRMs. Figure 26. Infiltration or rainfall loss models/methods for DRRMs reported by DOTs for roadway infrastructure projects. Other Answers for Question 15 Modelers usually select the one that is most appropriate for the project. Table 14. Other infiltration or rainfall loss models/methods for DRRMs reported by state DOTs for roadway infrastructure projects.

44 Resilient Design with Distributed Rainfall-Runoff Modeling Question 16 inquired about the alternatives to calculate effective rainfall transformation or runoff models/methods for DRRMs. Similar to Question 15, the SCS/NRCS-based UH approach was the most commonly used by state DOTs (14, or 88%). The other three methods most commonly used were based on the kinematic wave (31%), the Clark UH (31%), and the Snyder UH (25%). Figure 27 presents the complete set of answers to this question, and Table 15 presents the results for the “Other” alternative selected for question 16. The survey also sought information about the type of stream/reservoir routing models/methods for DRRMs used for roadway infrastructure projects. As illustrated in Figure 28, kinematic wave and Muskingum methods were the two most reported by state DOTs. Other stream/reservoir routing models/methods for DRRMs reported by five state DOTs are listed in Table 16. The last question on the technical details of DRRM implementation was about model param- eters used for DRRM sensitivity analysis. Of the 16 state DOTs using DRRMs, a large majority (15, or 94%) reported that UH parameters were the most commonly used in the sensitivity analysis. As shown in Figure 29, the other two parameters reported included rainfall loss parameters and flow routing parameters. Table 17 provides information on other model parameters for DRRM sensitivity analysis for roadway infrastructure projects from three state DOTs. Dhakal et al. (2014) studied 80 watersheds in Texas and concluded that in predicting peak discharges and direct Figure 27. Effective rainfall transformation or runoff models/methods for DRRMs used by state DOTs for roadway infrastructure projects. Other Answers for Question 16 Need verification from modelers. S-Graphs adopted by local agencies. Note: S-hydrograph can be converted to UHs with different durations and can be considered as agency-adapted UHs. Table 15. Other effective rainfall transformation or runoff models/methods for DRRMs used by state DOTs for roadway infrastructure projects.

Figure 28. DOTs that reported stream/reservoir routing models/methods for DRRMs used for roadway infrastructure projects. Other Answers for Question 17 Count Percent Muskingum-Cunge. 2 13% WinTR-20 Reservoir subroutine. 1 6% Need verification from modelers. 1 6% TR-20. 1 6% Table 16. Other stream/reservoir routing models/methods for DRRMs used for roadway infrastructure projects reported by state DOTs. Figure 29. Model parameters for DRRM sensitivity analysis for roadway infrastructure projects reported by state DOTs.

46 Resilient Design with Distributed Rainfall-Runoff Modeling runoff hydrographs for engineering design, rainfall loss estimation results in greater uncertainty and contributes more model errors than variations of UH methods and model parameters for UH. Assessing Costs and Benefits of DRRMs The survey sought to obtain the components/metrics used by state DOTs when assessing cost– benefit analysis when utilizing DRRMs. The top components reported (56% for both) were the accurate design to size drainage structures in order to reduce project cost and the importance/ criticality of the roadway project that demands more precise hydrological simulations. The added resiliency was the next component most cited (31%), as shown in Figure 30 along with compo- nents linked to added costs to perform analysis and training. Other components and metrics reported are presented in Table 18. Barriers for Implementation of DRRMs The final question on the survey inquired about barriers state DOTs face in implementing/using DRRMs. As illustrated in Figure 31, the lack of training opportunities, insufficient in-house exper- tise for model creation or reviewing modeling results, and turnaround of the workforce were the most frequently reported barriers. Other barriers reported by eight state DOTs are presented in Table 19. Other Answers for Question 18 Muskingum Cunge. Models are quasi calibrated until peak flows are within the positive range of the 67% confidence interval established via modified Tasker approach. Need additional input from modelers. Table 17. Other model parameters for DRRM sensitivity analysis for roadway infrastructure projects reported by state DOTs. Figure 30. Reported components/metrics included by state DOTs when assessing the cost–benefit analysis of the use of DRRMs.

Survey of State Practices for Distributed Rainfall-Runoff Modeling 47 Other Answers for Question 19 Division uses an automated hydrology system called GISHydroNXT/WEB. DRRM in some situations is the only alternative to effectively answer flood vulnerabilities. The infrastructure investment value is a determination as to when to use as well. Level of hydraulic design needed. If we don’t have the flows or if we are increasing the hydraulic capacity of the bridge or culvert, we need to develop a runoff hydrograph. We only use DRRM when we need full hydrographs and storage, or when we have a large watershed with significant development. Table 18. Other components/metrics included by state DOTs when assessing the cost–benefit analysis of the use of DRRMs. Figure 31. Barriers reported by state DOTs when implementing/utilizing DRRMs. Other Answers for Question 20 Not specified. All of the above has been addressed by developing the GISHydro software. Time it takes to set up and run models. Unfamiliarity with process. Efficient data preparation workflow, i.e., establishment of DEM and model mesh. Most projects do not require that level of complexity of analysis. Not specified. No real barriers. We use them as needed, which is rarely. Use StreamStats for most downstate bridge and culvert hydrology. Table 19. Other barriers reported by state DOTs when implementing/ utilizing DRRMs.