GEOS 4430/5310 Lecture Notes: Quantification and Measurement of the Hydrologic Cycle Dr. T. Brikowski Fall 2013 0 file:hydro_cycle.tex,v (1.36), printed October 1, 2013
Hydrologic Budget Misc. information and data sources: Texas Regional Water planning homepage Region C 2011 water plan (see Executive Summary)
Hydrologic Budget Hydrologic budget is simply an H 2 O mass balance { rate of mass in } { rate of mass out } = { change in storage } (1) usually assume density of water constant, then make a volume balance instead estimating these components is a large part of hydrology, and can sometimes be quite difficult
Hydrologic Budget (cont.) For a watershed (topographic basin) water balance is (Fig. 1): { rate of mass in { rate of mass out } } = P }{{} Precipitation = Q s }{{} Runoff + E + T }{{} Evapotranspiration + Q g }{{} Groundwater Discharge + R }{{} Recharge (2) (3)
Basin Hydrologic Cycle Figure 1: Hydrologic cycle for a watershed, after Domenico and Schwartz (Fig. 1.2, 1990).
Evaporation Misc. information and data sources: U.S. Evaporation climatology (calculated) U.S. raw evaporation data Dailyevaporation at DFW lakes (based on pan) moisture sensor rebate for NTMWD customers
Importance of Evapotranspiration 2/3 of precipitation in the U.S. returns to the atmosphere by evapotranspiration in arid regions ouptput by ET can exceed 90% of basin water inputs in humid regions (e.g. Western Washington) ET can be as little as 10% of input
Evaporation: Physical Process endothermic process (requires energy input) (Fig. 2) requires relative humidity 100 (relative humidity) = humidity = (absolute humidity) (saturation humidity) 100 (kg water) (m 3 air) absolute humidity is the current moisture content of the air saturation humidity is temperature dependent, the dewpoint is the temperature at which saturation humidity becomes equal to the absolute humidity. See Fetter (Table 2.1, 2001)
Water Phase Diagram Figure 2: Phase diagram for H 2 O, after Tindall and Kunkel (1999). Energy (e.g. heating) is required to drive water across the two-phase boundary into the vapor field (area to right of curve).
Evaporation: Measurement Direct methods: pan evaporation (land pan, Figs. 3 4): observe evaporation from a standard-sized shallow metal pan best to measure precipitation input separately (i.e. make a quantitative water balance for pan) apply empirical relationship to estimate lake or plant evaporation (Fig. 6) lysimeter (Fig. 5) Indirect methods: a cannister containing natural soil, installed at ground level weigh (and perform water balance) to determine moisture content changes due to evaporation
Evaporation: Measurement (cont.) Energy budget. 540 cal gm energy required to transform water to vapor at room temperature. Not all energy recieved by surface water is used for evaporation though: Q }{{} s Q }{{} rs incoming solar rad. reflected solar rad. Q }{{} h turbulent exchange Q v }{{} heat brought in by water flow Q lw }{{} IR radiation out Q e }{{} latent heat of vap. Q e }{{} heat carried out by vapor Q θ }{{} change in heat content + = (4) Bowen energy ratio: monitor soil T profile, incoming solar radiation and heat radiated to atmosphere at soil surface (combines Q h & Q e in Eqn. 4, see Hillel (p. 290, 1980) Eddy correlation method
Evaporation: Measurement (cont.) directly measure water vapor flux using wind speed, humidity measurements, i.e. micro-meteorology more recently used to measure CO 2 fluxes, e.g. ABLE experiment soil chloride profile (Cl mass balance, e.g. paleoclimate studies)
NOAA Evaporation Pan Figure 3: Example of NOAA standard evaporation pan, from Wikipedia.
U.S. Pan Evaporation Contours Figure 4: U.S. Pan Evaporation Contours, showing general distribution of open-water evaporation. See original data at NWS.
Weighing Lysimeter Figure 5: Example of commercial weighing lysimeter. Note variety of sensors, and monitoring of natural and lysimeter conditions. See UMS for installation details.
Transpiration Transpiration is evaporation from plants underside of leaves contain pores (stoma) which open for photosynthesis during the day water drawn into plant by roots to provide support and transport nutrients is lost via stoma hence length of day is an important constraint on transpiration see animation for a helpful visualization
Evapotranspiration: Physical Process Transpiration is evaporation from plants underside of leaves contain pores (stoma) which open for photosynthesis during the day water drawn into plant by roots to provide support and transport nutrients is lost via stoma hence length of day is an important constraint on transpiration ET is combined bare soil evaporation and plant transpiration transpiration predominant mechanism for water loss from soil in all but the driest climates (can be 15-80% of basin water losses, Fetter, 2001) (Fig. 6) phreatophytes (plants with roots to water table) are generally most important, except in agricultural settings for shallow-rooted plants, ET ceases when soil moisture drops below wilting point (plant root suction less than soil suction)
ET From Cornfield Figure 6: ET From Cornfield, showing ratio of ET to open-pan evaporation. Recall that actual evaporation from open water is usually about 0.7 times the pan evaporation. After (Fig. 5-1, Dunne and Leopold, 1978).
Evapotranspiration: Estimation/Measurement Measurement Lysimeters (containing soil and plants) phytometer - plant-in-a-box, airtight transparent enclosure (lab or field), monitor humidity of air; unnatural conditions and therefore questionable data Estimation Thornthwaite Method (empirical formula, inputs are T, latitude, season; emphasizes meteorological controls, ignores soil moisture changes, Fig. 7) [ ] a 10Ta E t = 1.6 (5) I where E t is potential evaporation in cm mo, T a is mean monthly air temperature in C, I is an annual heat index, and a is a cubic polynomial in I
Evapotranspiration: Estimation/Measurement (cont.) Blaney-Criddle method, adds a crop factor (empirical estimate of vegetative growth and soil moisture effects); most popular method, calibrated for U.S. only E t = (0.142T a + 1.095)(T a + 17.8)kd (6) where k is an empirical crop factor (bigger for thirsty crops or fast-growth periods), d is the monthly fraction of daylight hours. Penman Equation: use vapor pressure, net radiation, T to calculate fairly popular, but inaccurte (most parameters estimated) intended to mimic pan evaporation, so tends to over-estimate ET (e.g. Fig. 9). Note (Fig. 2.1 Fetter, 2001) is essentially a graphical solution of this equation see various Ag. schools for free software (e.g. U. Idaho). Remote sensing:
Evapotranspiration: Estimation/Measurement (cont.) early efforts developed species-specific ET rates for a locale, estimate distribution, growth rate, etc. from multi-spectral images, calculate spatially-variable ET rates Czarnecki (e.g. 1990); Owen-Joyce and Raymond (e.g. 1996) more recently use energy balance approach, e.g. China study comparison with lysimeter data
Thornthwaite Method Figure 7: Graphical solution of Thornthwaite Method, indicating primary dependence on mean air temperature and heat index (a U.S.-calibrated indicator of daily temperature range). After (Fig. 5-4, Dunne and Leopold, 1978). See also online calculator.
FAO Penman-Montieth Equation worldwide standard method developed by UN Food and Agriculture Organization envisions a reference crop, accounts for energy balance and resistance to ET (i.e. computes reduction from open-water evaporation rate, Fig. 8) computes potential evaporation (i.e. maximum possible) schematic version of equation: ET o = (net energy flux) + (wind) (RH) resistances where the energy flux is solar input minus infrared radiation and reflection out, resistances are r s and r a as shown in Fig. 8
Setting: FAO Penman-Monteith Equation Figure 8: Penman-Monteith setting, showing origin of resistance terms. After FAO.
ET Method Comparison Figure 9: Comparison of ET estimation methods. After (Fig. 5-3, Dunne and Leopold, 1978). See also Castañeda-Rao-2005.
ET Estimation Review As hydrogeologists, you ll probably consider the following methods to predict ET, in order of increasing difficulty and accuracy (see also FAO Summary) and FAO training manuals: Land pan evaporation data: apply appropriate pan coefficients and nearby pan data to estimate reservoir, or even crops (rarely). See Wikipedia summary Forms of energy balance Thornthwaite: meteorology/climate only, ignore vegetation effects. OK for annual average Blaney-Criddle: adds crop effect. Simple, widely used and broadly inaccurate, better at monthly variations, good when only temperature data is known Penman: original Penman eqn. mimics pan evaporation curve, accounts for radiation and convective (wind) flux, i.e. most terms in (4) Penman-Monteith: world standard, assumes realistic reference crop. Provides most inter-comparable results. Examples of regional ET effects: India lake shrinkage
Typical ET Values Figure 10: Typical values for ET o, in mm day for climate types and temperature range. After UN FAO. See current UTD/TAMU values.
ET Example: Colorado River Colorado River basin (Fig. 11) over-allocated (Fig. 13), so components of water balance there are very important (17.5 Mac ft yr allocated, actual flow averages 14.5 Mac ft yr ) very difficult-to-measure aspect of this is ET Tamarisk (salt cedar) introduced as decorative plant in 1870 s, has spread through most of watershed (colonization rate 3 km2 yr ) individual ET rates 2.5 m yr 1984 total consumptive use, Lower Basin 7x10 6 acre ft yr (Owen-Joyce and Raymond, 1996) of that 15% lost through ET, 6% by natural phreatophytes (primarily tamarisk), 18% exported to AZ, 67% exported to CA see USGS biennial consumptive use studies
Tamarisk Invasion/Control current distribution monitored by USGS other organizations organize remediation (e.g. Tamarisk Coalition) natural predators introduced to help (Glen Canyon Nat. Rec. Area many states helping eradication efforts to preserve water supplies (e.g. CO, CA, UT)
Colorado River Hydrologic Basin Figure 11: Colorado River Basin Compact states, and important localities, from (Barnett and Pierce, 2008).
Colorado River Profile Figure 12: Topographic profile of Colorado River, showing river gradient and major impoundments. After Keller (p. 281, 1996).
Colorado River Water Allocation Figure 13: Colorado River Basin Compact allocation and average discharge. After Keller (p. 282, 1996). See Wikipedia summary of shortage plans.
Pan Evaporation Declining Figure 14: Temporal trends in pan evaporation. Across the US and most of the world pan evaporation rates have declined since the 1940 s. Numbers are precipitation trends in mm decade, (Lawrimore and Peterson, 2000). See pan evaporation paradox (?).
Global Humidity Increasing Figure 15: Temporal trends in global specific humidity, increasing over land and sea. From 2012 State of Climate, raw data plottable at NCDC, based on analysis of GPS satellite signals.
Evaporation and Global Dimming/Brightening Figure 16: Observed and modeled global warming and dimming. Essentially that despite observed decrease in solar insolation at surface (caused by incresed particulates, matched by models), warming has and will continue. After (Schmidt et al., 2007). See Wild (2009) for good summary of brightening/dimming observations.
Climate Forcings Figure 17: Model results of 20th century climate, with contributions from various forcings. Observed warming best matched by effect of greenhouse gas emissions, moderated through 1990 by particulates ( sulfate, combined natural and anthropogenic effects). See also Wikipedia summary.
Precipitation Useful data sources: National Weather Service flood prediction data Intellicast TX-OK 7-day cumulative precip from NEXRAD data Intellicast current hourly lightning strikes
Precipitation: Physical Process condensation caused by cooling of the air mass, usually during lifting In Texas mostly during frontal storms ( blue norther s ) (Fig. 18) See example of March 3, 2000 frontal storm: radar animation, surface weather map, and lightning record local climate effects can be important in hydrology frontal precipitation (most common precip. in winter, see Texas annual precip. distribution, Fig. 19) convective precipitation (thunderstorms, most common in summer) e.g. in temperate arid regions snow is predominant recharge contributer, even if not predominant form of precip. orographic effect: heavier precip. on upwind side of topographic highs, lower than average on downwind side coastal states often affected by tropical cyclones (e.g. similar effect from upper atmosphere low at DFW 2009, Fig. 20)
Frontal Precipitation Model Figure 18: Cross-section through frontal storm, showing the special case of an occluded front. After Dingman (2002).
North Texas Monthly Normal Climate Figure 19: North Texas monthly normals (after RSSWeather). See also NOAA Southern Regional Climate Data Center.
4-Day Storm Event Cumulative Precipitation Figure 20: Cumulative precipitation is often highly heterogeneous. 7 day cumulative precipitation from high-level low pressure system in North Texas. Sept. 7-14, 2009 (from Intellicast).
Precipitation: Measurement One of the most easily measured hydrologic cycle fluxes NOAA uses a variety of automated gauges (Fig. 21) see modern summary at Wikipedia and summary of automated airport weather stations, the gold standard of weather data worldwide Two basic station networks: primary monitoring stations (usually major airports) and cooperative stations (usually not run by NOAA, data quality uncertain). See Fig. 22 this data accessible for free from.edu IP addresses at National Climate Data Center (NCDC)
Rain Gauge Examples Figure 21: Examples of recording rain gauges, after Dunne and Leopold (1978).
NOAA Weather Station Network Figure 22: NOAA Weather Station Network, after Dingman (2002).
Treating Precipitation Heterogeneity Precipitation usually extremely variable in space and time. Hard to go from point measurements to regional input, must use: arithmetic average, assumes uniform density of precip. or stations Theissen polygon method: area-weighted average. Equivalent of natural-neighbor interpolation Isohyetal: contouring, includes some concept of local meteorology NEXRAD radar: use to estimate areal variability of rainfall, calibrate with ground measurements, accuracy can be controversial, but now standard for runoff models (see Applied Surface Water Modeling Notes re: NEXRAD) cumulative estimates avaliable nationwide (intended for flood prediction) at NCDC Hydro Prediction Service
Theissen Polygon Method Figure 23: Determining areal average rainfall using Theissen polygons (same as natural neighbor interpolation) and isohyetal weighting. After McCuen (2004).
Recharge Physical processes infiltration - losses = recharge infiltration = precipitation - runoff runoff occurs when precip. exceeds infiltration capacity of soil (Hortonian overland flow) Measurement Direct: lysimeters Indirect: Water table fluctuation assumes changes in water level in shallow wells reflect recharge see USGS summary also computer program to develop Master Recession Curve for well water levels Indirect: Chemical mass balance: Cl, 3 H, δd, δ 18 O
Recharge (cont.) Cl method (assumes all input is atmospheric, OK if no Cl-sediments in basin; N.B. Cl = 0 in evaporated water) (Dettinger, 1989) C I I }{{} + C P P }{{} Infiltrated mass Precipitation + C Q Q }{{} Runoff = 0 I = PC P C I QC Q C I (7) Also note that in many desert basins the runoff is 0, simplifying (7) Determine Baseflow (hydrograph separation) Use empirical relations based on other basins: e.g. Maxey-Eakin (Watson et al., 1976), uses rainfall and elevation maps to estimate recharge, calibrated to basins of known recharge see excellent summary of methods and results for desert basins (Hogan et al., 2004) (and online review)
References Barnett, T.P., Pierce, D.W.: When will Lake Mead go dry? Water Resour. Res. 44(W03201) (29 Mar 2008), http://www.agu.org/journals/pip/wr/2007wr006704-pip.pdf Brutsaert, W.: Indications of increasing land surface evaporation during the second half of the 20th century. Geophys. Res. Lett. 33, 4 (Oct 2006) Czarnecki, J.B.: Geohydrology and evapotranspiration at franklin lake playa, inyo county, california. Ofr 90-356, Denver, CO (1990) Dettinger, M.D.: Reconnaissance estimates of natural recharge to desert basins in nevada, u.s. a., by using chloride-balance calculations. J. Hydrol. 106, 55 78 (1989) Dingman, S.L.: Physical Hydrology. Prentice Hall, Upper Saddle River, NJ, 07458, 2nd edn. (2002) Domenico, P.A., Schwartz, F.W.: Physical and Chemical Hydrogeology. John Wiley & Sons, New York (1990), isbn 0-471-50744-X Dunne, T., Leopold, L.B.: Water in Environmental Planning. W. H. Freeman, New York (1978)
References (cont.) Fetter, C.W.: Applied Hydrogeology. Prentice Hall, Upper Saddle River, NJ, 4th edn. (2001), http://vig.prenhall.com/catalog/ academic/product/0,1144,0130882399,00.html Hillel, D.: Applications of soil physics. Academic Press, New York (1980) Hogan, J.F., Phillips, F.M., Scanlon, B.R. (eds.): Groundwater Recharge in a Desert Environment: The Southwestern United States, Water Science and Application, vol. 9. Amer. Geophys. Union (2004), http://www.agu.org/cgi-bin/agubooks?topic=al&book= HYWS0093584&search=Scanlon Keller, E.A.: Environmental Geology. Prentice Hall, Upper Saddle River, NJ (1996), 7th Ed., ISBN 0-02-363281-X Lawrimore, J.H., Peterson, T.C.: Pan evaporation trends in dry and humid regions of the united states. Journal of Hydrometeorology 1(6), 543 (2000), http://search.ebscohost.com/login.aspx?direct= true&db=a9h&an=5716377&site=ehost-live McCuen, R.H.: Hydrologic Analysis and Design. Prentice Hall, Upper Saddle River, New Jersey, 07458, 3rd edn. (2004), http://www.prenhall.com
References (cont.) Owen-Joyce, S.J., Raymond, L.H.: An accounting system for water and consumptive use along the colorado river, hoover dam to mexico. Water-supply paper, U.S. Geol. Survey, Washington, D.C. (1996) Schmidt, G.A., Romanou, A., Liepert, B.: Further comment on a perspective on global warming, dimming, and brightening. EOS 88(45), 473 (11 2007) Tindall, J.A., Kunkel, J.R.: Unsaturated Zone Hydrology for Scientists and Engineers. Prentice-Hall, Upper Saddle River, N.J. (1999) Watson, P., Sinclair, P., Waggoner, R.: Quantitative evaluation of a method for estimating recharge to the desert basins of nevada. J. Hydrol. 31, 335 357 (1976) Wild, M.: Global dimming and brightening: A review. J. Geophys. Res. 114 (2009)