A Peer Review of IWFM and MODFLOW-Farm Process

Transcription

1 A Peer Review of IWFM and MODFLOW-Farm Process California Water and Environmental Modeling Forum Asilomar Conference Center, California February 22-24, 2010 Tariq Kadir (California Department of Water Resources) and Randall Hanson (US Geological Survey)

2 Outline IWFM and MODFLOW-FarmProcess Background on collaborative effort between DWR and USGS Technical work comparing IWFM and MODFLOW-FMP USGS peer review process and selection of reviewers Highlights of reviewers comments and responses by agencies Final thoughts on the peer review process and future direction

3 IWFM and MODFLOW-FP Both Integrated Hydrologic Models Chronology: IWFM IGSM 1990 IWFM (DWR) 2002 Current version 3.1 MODFLOW-FP MODFLOW 1988 Farm Process 2006 Current version MODFLOW2005 and Farm Process v.2 Main focus is computation of land-use based demands and associated physical processes (runoff, deep percolation, etc) Limitations placed on full capabilities of both models to compare using hypothetical simulation examples

4 IWFM and MODFLOW-FMP as Integrated Hydrological Models Rainfall Runoff Root Zone (Farm Process) Stream_aquifer Ground Water Supply-Demand Unsaturated Zone Subsidence Others: Tile drains, Lakes, etc

5 Conceptual Diagram of Landscape Process IWFM (Root Zone) MODFLOW-FMP(Farm Process)

6 Background on Collaborative Effort DWR/USGS Preliminary contacts dating back to late 2005 Initial thoughts of migrating to MODFLOW for modeling ground water in CalSim-3 Contract DWR-USGS to compare: Phase-1: IWFM and MODFLOW-FarmProcess (academic) Phase-2: Application to Central Valley (CVHM and C2VSIM) DWR assistance to USGS in the development of CVHM Phase-1 resulted in two sets of draft documents (each composed of a Technical Information Report and a journal paper): Outlining the theoretical bases of each model Comparing the two models using hypothetical examples USGS Peer Review process

7 Hypothetical Example

8 Hypothetical Example Details 4-layers, one unconfined aquifer and 3 confined aquifers No-flow boundaries are defined along the northern and southern boundaries for all layers and for the eastern and western boundaries of the confined aquifers in layers two, three, and four. General-head boundaries are specified for the eastern and western boundaries of the unconfined aquifer in layer 1 network of streams, canals, and tributaries are used Simulation 2 years with 8 3-month stress periods and weekly time steps Six farms (subregions) and 12 farm wells six crop or land-use types (alfalfa, pecans, onions, urban landscape, native vegetation, and riparian vegetation) 3 soil types: silt, silty clay and sand loam Urban areas outdoor only

9 Results: Head Distribution on Layer 1 (MF-FMP) Peak season in year 2 (stress period 7, time step 13)

10 Results: Head Distribution on Layer 1 (IWFM) Peak season in year 2 (stress period 7, time step 13)

11 Results: Head Distribution on Layer 2 (MF-FMP) Peak season in year 2 (stress period 7, time step 13)

12 Results: Head Distribution on Layer 2 (IWFM) Peak season in year 2 (stress period 7, time step 13)

13 Results: Hydrographs at Observation Wells Hydrographs of observation wells in layers 1 and 2 inside Farm 2 and north of Farm 4

14 Results: Inflows into and outflows out of farm diversion reaches MF-FMP IWFM

15 Results: Inflows and outflows out of farm return flow reaches MF-FMP IWFM

16 Peer Review Process & Selection of Reviewers Need for the peer review process What constitutes peer review per USGS guidelines Four reviewers selected by DWR and USGS: Theoretical Dr. Graham Fogg (UC Davis) Dr. Richard Snyder (UC Davis) Comparison using hypothetical problem Dr. Thomas Harter (UC Davis) Dr. Devin Galloway (USGS) Review period: Sept 1-30, 2009 All reviewers comments received by Jan 29, 2010

17 Reviewers Comments and Responses by Agencies DWR Responses to Rick Snyder on IWFM Comment Response Changes in the soil moisture due to deep percolation should not have any effect on the evapotranspirative demand. The meaning of demand was clarified. This is the irrigation water demand that includes water to meet the evapotranspirative demand as well as the losses due to deep percolation and return flow. For a specified crop and ETc, irrigation water demand for a sandy soil will be larger than the demand for a clayey soil due larger deep percolation. This is not true in general and depends on many farm irrigation factors. It is true that in real world farmers can adjust their irrigation methods (e.g. apply less water with higher frequency) to minimize Deep Percolation. However, in IWFM one irrigation logic is used: When the soil moisture is depleted to maximum allowable depletion, IWFM computes I that will increase the soil moisture to field capacity. Under this logic, since DP will be higher in a more permeable soil, I will also be higher to increase the moisture to field capacity.

18 USGS Responses to Rick Snyder on MODFLOW-FMP Comment Confusion about Kt fractions and coefficients (e.g. Kt to compute T from ET) used in MF-FMP. Response FAO publishes Basal Crop Coefficients Kcb to derive evaporative part of ET in Kc that allows splitting the Kt from Kc to compute T from ET (FAO-56). Kt is fraction = Kc/Kcb. What is basis of FMP crop transpiration concept? In FMP1 the course of transpiration with changing water level can vary from a known maximum T cpot and ET ref - to zero and be linearly approximated based on results from numerous numerical Richard's-equation-based experiments run in HYDRUS. What is meaning of inactive root zone? What is meant by an upper transpiration extinction depth and lower transpiration extinction depth? Root Zone pressure heads below at particular pressure head specified in a stress response function are considered part of the inactive root zone which ARE specific for particular crop types (see Simunek et al., 1999). The upper extinction of ET with a rising water table (Baird & Maddock, 2005) The lower transpiration extinction depth = sum of the root zone + the capillary fringe. For "LOWER" extinction, FMP also allows an extinction of transpiration for water levels in the UPPER ranges of the root zone, when the anoxia fringe above the water level "crops out" at the surface.

19 DWR Responses to Graham Fogg on IWFM Comment For many flow processes, pros and cons of IWFM s approach versus MF-FMP s not discussed. Response Not the goal of this project. The goal of this work was to discuss the approaches of the two models in a common framework and provide a guide for the similarities and differences between the two models so that their results can be better interpreted. Water budget comparison numbers in the theory paper do not reflect well on models (or agencies). Use of Kozeny equation to distribute well pumping to aquifer layers is not appropriate. Not simulating ET from groundwater is a drawback. No comparison of model numbers to see the consequences of each model s approach. No discussion on how individual model components were linked to each other and convergence among these components were achieved. SCS curve number method is an event-based approach. How are the temporal and spatial issues resolved? Misunderstanding for what number represent. These numbers are from the second part of this project in which the two model results were compared for a simple hypothetical problem. Comparison of results for Central Valley applications next phase. Most IWFM applications are regional applications and use element pumping option. Kozeny equation is only used when individual wells are modeled. With element pumping option, the total pumping at an element is distributed vertically to aquifer layers using user-specified fractions. Kozeny equation option to be modified in the future. Will be included in the future as the need arises. Included in the hypothetical example TIR/Paper. A short discussion on this was added. Physically-based simulation of rainfall-runoff process possible; may not be practical for regional applications. IWFM adopts methods in EPA s HELP model to convert the event-based approach to time-continuous approach. Solution: shorter time steps (daily or less), calibration of curve numbers (monthly). Version 4.0 of IWFM (2010) will allow rainfall-runoff simulations at each element to resolve the spatial issues.

20 USGS Responses to Graham Fogg on MODFLOW-FMP Comment Lack of references to scholarly literature to support MF- FMP s ET methods in computing E and T separately from precipitation, irrigation and groundwater. Are they "plowing new ground with these formulations? How is the inter process coupling accomplished to assure joint convergence of processes? The assumption that change in soil moisture is negligible at time steps used for the simulation of the groundwater dynamics sounds like the tail wagging the dog: Is it possible to demonstrate that the upscaling of root zone processes stick with large delta-t that is used in groundwater simulations. Not simulating the change in soil moisture in MF-FMP might be a disadvantage for non-farm landscapes. Is the goal to model adequately the surface and subsurface hydrology, or is to tack on a surface hydrology module without disturbing the usual work flow of the groundwater modeling? Response Farm Process was part of the original work performed by Dr. Schmid as part of FMP1 and CVHM development. Different hydrologic settings within the Central Valley support that this approach yields considerable insight into how water demand is satisfied differently in different settings. Others have split E and T such as Feddes et al (1976) or Guan and Wilson (2009) as well as Simunek et al. (1999) which is based on Richards Eqn. Yes this represents new approaches to previous traditional lumped approaches. MF-FMP contains both head and flow dependent linkages and performs additional iterations and even has additional optional closure criteria to insure better mass balance (ex water rights and multi-aquifer wells). Shown in the FMP1 document. Fundamental to all models that simulate landscape processes couple to surface-water and groundwater flow and not just MF-FMP. The lack of soil moisture for native vegetation that is not connected to groundwater uptake could be an issue for vegetation types that cannot survive multi-year or decadal droughts. Part of our future research and proposed enhancements to MF-FMP as part of our ongoing Climate-change research. No codes deal with the consequences of sustained deficit of soilmoisture deficits currently. MF-FMP was designed to accommodate flow-dependent dependencies between groundwater, surface-water and landscape process for a wide range of applications. The current option was designed based on Hydrus 2-D validation of steady-state flow through the soil zone for various soil, plant, and water-table configurations. Future versions of FMP will include the option for soil moisture storage.

21 DWR Responses to Thomas Harter on IWFM Comment Increased deep percolation with higher permeability leads to higher irrigation water demand in IWFM. By modifying the frequency and amount of irrigation, deep percolation can be controlled (similar to Richard Snyder s comment). Setting MAD in IWFM to zero for farms 1-5 to replicate MF-FP s approach as much as possible makes the example set-up an unfair comparison from IWFM s perspective. Why not allow both models to be used as they are intended and then compare the results? Response Farmers can modify the irrigation practices to control deep percolation. IWFM, however, simulates one type of irrigation logic regardless of the soil type: if the moisture depletion is less than maximum allowable depletion (MAD) (specified by the user), than the crop is irrigated up to field capacity. In a soil with higher permeability, the deep percolation will be higher drawing the moisture to MAD faster, requiring higher frequency of irrigation. The goal of this work was to track down the differences between the two models particularly in their approach to compute irrigation water demands. If the two models were allowed to be used as they were intended, the sources of the differences quickly became intractable. Setting MAD in IWFM to zero generates large irrigation demands compared to MF-FP which then generates large deep percolation and surface runoff. This is an unfair comparison. Questions applicability of either IWFM or MF-FMP for climate change studies based on the language indicating that IWFM can only use actual ET but MF_FMP uses potential ET. Setting MAD=0 in IWFM is not the cause of excessive water demands computed in IWFM. Table 2 shows that total deep perc (Q-dp-out) for each farm are not too different between the two models. It is the difference in the ET values (Table 2, Q-et-out) that causes IWFM to apply more water than MF-FMP. This is because MF_FMP reduces the user-specified ET values due to anoxia and other factors. Setting MAD to zero zooms in on this difference nicely. IWFM doesn t need actual ET values as input. It is only one input option IWFM can use, if such data is available from satellite images, etc. IWFM can use potential ET values as input just like MF-FMP. Howevev, IWMF does not simulate reductions due to anoxia, nonuniform distribution of irrigation etc.

22 USGS Responses to Thomas Harter on MODFLOW-FMP Comment MF-FMP neglects the role of root zone soil moisture storage to carry forward water from the time of precipitation and irrigation to the time of consumptive use uptake by crops. It has been shown that soil moisture storage is key to controlling the hydrologic balance of a groundwater basin and a watershed. Response MF-FMP uses soil moisture but does not simulate changes in soil moisture as most agricultural areas have fairly well managed soil moisture during the growing season from applied water. Based on this assumption and the requirement to use time steps longer than a week (based on the Hydrus-2D analysis for various soil types and changing groundwater conditions) for regional simulations. Are reductions in ET due to anoxia, wilting and nonuniform distribution of irrigation in any way related to what happens in real systems? Yes and there is considerable literature on this. Tile drain fields exemplify fundamental evidence farmers are concerned with eliminating poor drainage in the root zones of crops and related anoxic conditions for many decades. Non-uniform irrigation only pertains to the fact that irrigation does not occur over an entire model cell (regardless of cell size) and this proration is needed to ensure that the application of the potential or actual ET demand is not overestimated during the simplification of the model structure. References to support ET computation methods in MF-FMP as well as sources to obtain data for input parameters to separate ET into E and T from different sources are lacking. We have extensive databases that we have complied from other databases such as FAO for the input data.

23 DWR Responses to Devin Galloway Comment Response Publishing TIRs may impede publication of journal papers. TIRs are DWR s internal documentation for State related work and are a requirement (BDO) prior to submitting to journals. Done in past and should not affect publication in journals

24 Final Thoughts about Peer Review Process Vigorous (but healthy) scientific debates between modelers Great learning experience by both agencies Features of models limited to make them comparable Reviewers comments pointed to areas of further investigations to improve both models In hindsight: provide all documents to all reviewers Next phase comparing C2VSIM (DWR) and CVHM (USGS)

25 Future Directions Explore selected code enhancements together ex. Physically-based Runoff Investigate streamlining data acquisition for data sets commonly used by C2VSIM and CVHM ex. Diversions, streamflows, & land use Streamline model updates and redescritization to more detailed water-balance subregions Explore common mechanisms for linkages with other types of models ex. CALSIM, CALVIN, HEC-RAS, etc. Additional comparisons based on climate change applications DWR and USGS committed to continue collaborative work

26 Acknowledgements Can Dogrul, CA-DWR Wolfgang Schmid, University of Arizona (USGS) Charles Brush, CA-DWR

27 Thank you