HYDROLOGIC DESIGN CRITERIA

The techniques of hydrologic analysis described in Chapters 4-13 are useful in hydro-logic design and hydrologic forecasting. In hydrologic design, the objective is to predict the behavior of hydrologic variables under a hypothetical extreme condition such as the 100-y flood or the probable maximum flood. In hydrologic forecasting the aim is to predict the behavior of hydrologic variables within a shorter time frame, either daily, monthly, seasonally, or annually. These two types of hydrologic applications are quite different, paralleling the differences between event-driven and continuous-process catchment models (Section 13.1).

Hydrologic design precedes hydraulic design; i.e., the output of hydrologic de-sign is the input to hydraulic design. Hydrologic design determines streamflows, dis-charges, and headwater levels, from which hydraulic design derives flow depths, veloc-ities, and pressures acting on hydraulic structures and systems. Actual sizing of structures and appurtenances is obtained by balancing efficiency, practicality, and economy. In practice, hydrologic design translates into hydrologic design criteria, i.e., a set of rules and procedures used by federal, state, or local agencies having cognizance with water resources projects. Of necessity, these criteria are likely to vary widely, reflecting the charter and jurisdiction of each agency, and the size and scope of individual projects.

The following federal agencies are actively engaged in developing and using hy-drologic design criteria for engineering applications:

  1. NOAA National Weather Service

  2. U.S. Army Corps of Engineers

  3. USDA Soil Conservation Service

  4. U.S. Bureau of Reclamation

  5. Tennessee Valley Authority

  6. U.S. Geological Survey

This chapter describes selected design criteria and procedures used by these agencies. This information is intended to complement the subjects presented in Chapters 4 to 13. 14.1 NOAA NATIONAL WEATHER SERVICE Probable Maximum Precipitation

The National Oceanic and Atmospheric Administration's (NOAA) National Weather Service (NWS) is the federal agency responsible for the development of design criteria to estimate probable maximum precipitation. The concepts and related methodologies are described in the NOAA Hydrometeorological Report (HMR) series. Reports of current applicability begin with HMR 36: Probable Maximum Precipitation in California, revised in 1969 [15-30].

In the United States, the use of extreme values of precipitation for hydrologic design dates back to the 1930s, as documented in the early issues of the HMR series (Nos. 1 to 35). The probable maximum precipitation (PMP) is the theoretically greatest depth of precipitation for a given duration that is physically possible over a given size storm area at a particular geographic location at a certain time of the year [26]. The probable maximum flood (PMF) is the flood associated with the PMP.

PMP values obtained from hydrometeorological reports are generalized estimates, that is, estimates that can be obtained by areal averaging of PMP values depicted on isoline maps (i.e., maps showing contours of equal PMP). The basic approach to generalized PMP estimates is described in the literature [37, 50, 52, 53, 54]. Procedures described in this section are applicable to (1) nonorographic regions, (2) orographic regions, and (3) regions without meteorological data.

PMP Estimates for Nonorographic Regions. For nonorographic regions, PMP estimates involve three operations on observed areal storm precipitation:

  1. moisture maximization,

  2. transposition, and

  3. envelopment.

    Moisture maximization consists of increasing the storm precipitation to a value that is consistent with the maximum moisture in the atmosphere for the given geographic location and month of the year. Transposition refers to the relocation of storm precipitation within a meteorologically homogeneous region, with the aim of increasing the available data for evaluating maximum rainfall potential. Envelopment refers to the smooth interpolation between precipitation maxima for different durations and/or areas, intended to compensate for the random occurrence of large rainfall events.

    PMP Estimates for Orographic Regions.

    Topography plays an important role in the production of rainfall, either by intensifying rainfall or sheltering regions from it. Usually, the forced lifting of air on the windward slope of a mountain range produces an increase in rainfall with elevation. The magnitude of this effect varies with wind velocity and direction, amount of moisture and temperature of the air masses, and height, extent, and slope of the mountain range. Precipitation due to horizontal convergence (i.e., convergence precipitation) is important in both orographic and nonorographic regions. Therefore, PMP estimates for orographic regions consist of two components:

    1. orographic precipitation, which is dependent on topo-graphic influences, and

    2. convergence precipitation, which is presumed to be inde-pendent of topographic influences.
    Statistical Estimates of PMP.

  4. An alternate way to estimate PMP is to use the statistical frequency formula

    xT = + KTs„ (14-1)

    in which xT. is the rainfall associated with a return period T, in and sn are the mean and standard deviation of a series of n annual maxima, and KT is the frequency factor associated with T (Chapter 6).

    In terms of maximum rainfall, Eq. 14-1 can be expressed as follows: xm = Kms„ (14-2)

  5. in which xM is the maximum rainfall and KM is the number of standard deviations that must be added to the mean in order to obtain xM. An empirical estimate of KM can be obtained by enveloping a value of KM based on a large number of computed values. The value KM = 15 was considered initially by Hershfield [8] to be an appropriate enveloping value. This analysis was based on data from 2600 stations, approximately 90% of which were located in the United States. However, Hershfield's later studies [9] have shown that KM actually varies with mean annual maximum rainfall and storm duration, as shown in Fig. 14-1. This procedure gives point estimates of PMP; areal estimates can be obtained through the use of an appropriate depth-area relation.

    The step-by-step procedure to estimate the D-hr PMP based on statistical data is the following:

    1. Compile the D-hour annual-maxima rainfall series.

    2. Calculate the mean and standard deviation of the D-hour annual-maxima rainfall series.

    3. Using Fig. 14-1, determine the value of KM as a function of mean annual maximum rainfall and D-hour duration.

    4. Using Eq. 14-2, calculate the D-hour point PMP.

    5. For basins in excess of 25 km2, determine the areal PMP by reducing the point PMP using an appropriate depth-area relation. Generalized PMP Estimates.

      Generalized PMP estimates are obtained from isohyetal maps contained in the HMR series, which encompass the entire United States [15-30]. Figure 14-1 Frequency factor as a function of mean annual maximum rainfall and storm duration [9].

      The procedure used for obtaining generalized PMP estimates in nonorographic regions involves storm transposition and maximization, requiring the analysis of a large number of major storms. Generalized estimates for large areas require both depth-area arid depth-duration smoothing so that consistency can be maintained within and between the various charts. This is accomplished by determining PMP values for selected grid points, for several durations and areas, and smoothly envelop-ing the point values to determine PMP isolines.

      For orographic regions, difficulties with storm transposition require the use of a number of indicators of orographic effects. For example, a chart of 2-y, 24-h rainfall may be compiled. Theoretical PMP values are then determined and related to the 2-y, 24-h indicator chart. Additional adjustments such as distance from the moisture source, direction of primary moisture inflow, barrier to moisture inflow, slope, and elevation, can be considered. Generalized PMP estimates for orographic regions tend to be less reliable indicators of the actual PMP than those of nonorographic regions. This is specifically the case for small basins whose topographic features may be very different from those of the large basins for which the generalized estimates are normally prepared.

      In the United States, generalized PMP estimates for drainage basins located east of the 105th meridian are obtained using HMR 51 and HMR 52 [25, 26]. For the Tennessee valley region in particular, PMP estimates are developed using HMR 56 1301. PMP estimates for drainage basins located west of the Continental Divide are developed using HMR 36 (California) [15], HMR 43 (Northwest States) [19], and HMR 49 (Colorado River and Great Basin drainages) [24]. PMP estimates for drainage basins located between the Continental Divide and the 103rd meridian are developed using HMR 55 [29]. Either HMR 51/HMR 52 or HMR 55 can be used for the overlapping area between the 103rd and 105th meridians (see Fig. 14-20).

      PMP Estimates for Regions East of the 105th Meridian.

      Procedures for estimating PMP in U.S. locations east of the 105th meridian are described in HMR 51 and HMR 52 [25, 26]. HMR 51 contains a total of 30 maps, corresponding to combi-nations of five durations (6, 12, 24, 48, and 72 h) and six basin areas (10, 200, 1000, 5000, 10,000 and 20,000 mi2). The 24-h PMP maps are shown in Fig. 14-2. Generalized PMP estimates can be obtained by the following steps [51]:

      1. Determine the geographic location and size of the drainage basin under study.

      2. Using the maps, prepare a table of PMP depths applicable to the given geographic location. Use the maps of all five durations and of at least four areas surrounding the drainage basin size. For instance, for a basin size of 11,300 mi2, tabulate 5 X 4 = 20 PMP depths (obtained from the 6-, 12-, 24-, 48-, and 72-hr maps, and from the 1000-, 5000-, 10,000-, and 20,000-mi2 area maps).

      3. For each duration, plot PMP depths versus basin area on semilogarithmic pa-per, with PMP depth in the abscissas (arithmetic scale) and basin area in the ordinates (logarithmic scale), to obtain a PMP depth-area-duration relation for the given geographic Iodation.

      4. Using the PMP depth-area-duration relation developed in step 3, determine, for the given basin area, the PMP depth for each duration.

      5. Plot PMP depth versus duration on arithmetic scales, and draw a smooth curve connecting these points to determine the PMP depth-duration relation for the given basin area and geographic location. If necessary, interpolate to find the PMP depth for any intermediate duration.

      6. The 6-h incremental PMP (i.e., the PMP expressed in 6-h increments) can be determined from the PMP depth-duration relation developed in step 5. This is accomplished by evaluating the PMP for successive durations in multiples of 6 h, and subtracting two consecutive PMP depths to determine an incremental PMP value. For instance, the difference between the 24- and 18-h PMP is the 6-h incremental PMP associated with the 18- to 24-h interval.

        The application of HMR 51 to specific drainage basins, including the temporal and spatial distribution of the probable maximum storm is described in HMR 52 [26]. PMP Estimates for Regions West of the Continental Divide. The procedures for estimating PMP in U.S. locations west of the Continental Divide are de-scribed in HMR 36 (California) [15], HMR 43 (Northwest States) [19], and HMR 49 (Colorado River and Great Basin drainages) [24] (see Fig. 14-20). In these regional-ized studies, the local storm (thunderstorm) is not enveloped with general storm depth-duration data, as in the case of the regions east of the 105th meridian.

        To compute general storm PMP, the drainage basin characteristics such as size, width, elevation, and location must be known. Generally, the PMP estimate consists of two parts: (1) orographic component and (2) convergence component. The orographic component is determined by obtaining an orographic PMP index from a regional map and adjusting it to account for basin size, width, seasonal, and/or tempo-ral variations. The convergence component is determined by obtaining a convergence PMP index from a regional map and adjusting it to account for basin size and tempo Figure 14-2(a) All-season PMP (in.) for 24-h 10-mi2 rainfall [25]. Figure 14-2(b) All-season PMP (in.) for 24-h 200-mi2 rainfall [25]. Figure 14-2(c) All-season PMP (in.) for 24-h 1000-mi2 rainfall [25]. Figure 14-2(d) All-season PMP (in.) for 24-h 5000-mi2 rainfall [25]. Figure 14-2(e) All-season PMP (in.) for 24-h 10,000-mi2 rainfall [25]. Figure 14-2(f) All-season PMP (in.) for 24-h 20,000-mi2 rainfall [25].