Method and apparatus for determining runoff using remote geographic sensing

• US 5,323,317 A
• Filed: 03/05/1991
• Issued: 06/21/1994
• Est. Priority Date: 03/05/1991
• Status: Expired due to Fees

• Current Assignee: Mettel M. Carson, Terry L. Hampton
• Original Assignee: Mettel M. Carson, Terry L. Hampton
• Inventors: Hampton, Terry L., Mettel, M. Carson
• Primary Examiner(s): Envall, Jr., Roy N.
• Assistant Examiner(s): Poinvil, Frantzy
• Application Number:
  US07/664,564
• Time in Patent Office: 1,204 Days
• Field of Search: 73/170 R, 364/420, 364/422, 358/109
• US Class Current: 702/3
• CPC Class Codes: B64G 1/66 Arrangements or adaptations of apparatus or instruments, not otherwise provided for
• CPC Class Codes: G01S 13/86 Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
• CPC Class Codes: G01S 13/89 for mapping or imaging
• CPC Class Codes: G01S 13/955 mounted on satellite
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

Images of a selected geographic region are obtained using remote sensing apparatus and are processed to determine characteristic spectral reflectance patterns associated with different ground covers and soil types in the region. The image processing means compares the spectral reflectance patterns to image pixel values in order to classify each pixel in a ground cover or soil type class, the corresponding spectral reflectance pattern for which matches the pixel value. In a preferred embodiment of the invention, Geographic Information System (GIS) software is utilized to combine a remotely sensed image providing ground cover classifications for a geographic region with a remotely sensed image providing soil type classifications for the same region in order to generate a rainfall loss function. The rainfall loss function can then be used to determine a runoff curve number (RCN) for the region, to determine probable maximum flood (PMF), or to generate various design flood hydrographs corresponding to different precipitation events using a computer water shed model.

Claims

1. A computer-implemented method for determining the interaction between precipitation and runoff in a selected geographic region, comprising the steps of:

sensing electromagnetic energy patterns indicative of ground cover in said geographic region by remote sensing to obtain ground cover data relating to said geographic region;

sensing electromagnetic energy patterns indicative of soil characteristics in said geographic region by remote sensing to obtain soil characteristic data relating to said geographic region; and

inputting said group cover data and said soil characteristic data into a computer for performing the following steps;

analyzing said ground cover data and said soil characteristic data to indentify a plurality of different ground covers and a plurality of different soil characteristics in said geographic region;

classifying said geographic region in accordance with a plurality of ground cover classification data, and storing said ground cover classification data in memory of said computer;

classifying said geographic region in accordance with a plurality of soil characteristic classes corresponding to said different soil characteristics to obtain soil characteristic classification data, and storing said soil characteristic classification data in memory of said computer;

combining said ground cover classification data and said soil characteristic classification data and storing the combined classification data in memory of said computer; and

determining from said combined classification data an expected runoff in said geographic region as a result of precipitation.

2. The method as claimed in claim 1, wherein said soil characteristic data comprises a hydrologic soil group classification.

3. The method of claim 1, wherein said soil characteristic data corresponds to a rate of fluid infiltration for soil.

4. An apparatus for determining the interaction between precipitation and runoff in a selected geographic region, comprising:

memory means;

data gathering means coupled to said memory means for obtaining data relating to ground cover in said geographic region;

remote sensing means coupled to said memory means for remotely sensing an electromagnetic energy pattern indicative of a soil characteristic in said geographic region; and

processing means coupled to said memory means for combining said ground cover data and said soil characteristic data to obtain an indication of expected runoff in said geographic region as a result of precipitation.

5. A method for determining the interaction between precipitation and runoff in a selected geographic region, comprising the steps of:

obtaining data relating to ground cover in said geographic region;

sensing an electromagnetic energy pattern indicative of a soil characteristic in said geographic region with remote sensing means to obtain soil characteristic data relating to said geographic region; and

combining said ground cover data and said soil characteristic data to determine expected runoff in said geographic region as a result of precipitation.

6. The method of claim 5, wherein said step of obtaining ground cover data comprises the step of analyzing field data taken for at least a portion of said geographic region.

7. The method of claim 5, wherein said step of obtaining ground cover data comprises the step of analyzing a map of at least a portion of said geographic region which comprises land use data.

8. The method of claim 5, wherein said step of obtaining ground cover data comprises the step of sensing the ground cover in said geographic region using remote sensing means.

9. The method of claim 5, wherein said combining step comprises the steps of:

analyzing said ground cover data and said soil characteristic data to identify a plurality of different ground covers and a plurality of different ground covers and a plurality of different soil characteristics in said geographic region;

designating each of said plurality of different ground covers and each of said plurality of different soil characteristics as a ground cover class and a soil characteristic class, respectively;

classifying said geographic region in accordance with said ground cover classes and storing ground cover classification data for said geographic region in memory means;

classifying said geographic region in accordance with said soil characteristic classes and storing soil characteristic classification data for said geographic area in said memory means;

combining said ground cover classification data and said soil characteristic data associated with said geographic region and storing the combined classification data in said memory means; and

determining from said combined classification data a rainfall loss function for characterizing runoff in said geographic region.

10. The method of claim 9, further comprising the step of generating a hydrograph of said geographic region from hydrograph determination factors comprising said rainfall loss function and precipitation data.

11. The method of claim 9, wherein said determining step comprises the step of analyzing said combined classification data to identify portions of said geographic region characterized by different combinations of said ground cover classes and said soil characteristic classes.

12. The method of claim 11, wherein said soil characteristic classes correspond to different hydrologic soil groups.

13. The method of claim 12, wherein said determining step further comprises the steps of:

selecting a runoff curve number factor which corresponds to each of said combinations of said ground cover classes and said hydrologic soil groups;

calculating a runoff curve number for each of said portions of said geographic region by multiplying the area of said portion with a corresponding runoff curve number factor; and

calculating the runoff curve number for said geographic region by summing the runoff curve numbers for each of said portions of said geographic region and dividing the sum by the area of said geographic region.

14. The method of claim 13, further comprising the step of modifying said runoff curve number for said geographic region using an antecedent moisture condition factor which represents the effect of antecedent precipitation on the runoff characteristics of said geographic region.

15. The method of claim 13, further comprising the step of generating a hydrograph of said geographic region from hydrograph determination factors comprising said runoff curve number for said geographic region and precipitation data.

16. The method of claim 13, wherein said selecting step comprises the step of selecting distinct runoff curve number factors for national forest and commercial forest ground cover classes.

17. A method for discriminating between areas in a geographic region which are characterized by a selected soil characteristic, comprising the steps of:

sensing the electromagnetic energy patterns in said geographic region with remote sensing means to obtain image data relating to said geographic region;

determining for at least one test location in said geographic region a soil characteristic which substantially characterizes said test location and storing test location data relating to said soil characteristic in memory means;

comparing that portion of said image data which corresponds to said test location with corresponding test location data and generating relationship data which indicates correlation between said image data and said soil characteristic at said test location; and

analyzing said image data for said geographic region using said relationship data to locate other areas in said geographic region which are substantially characterized by said soil characteristic.

18. The method of claim 17, wherein a plurality of pixels constituting said image data are associated with a plurality of binary data values, said binary values corresponding to levels of radiation reflected from said geographic region and detected by a plurality of electromagnetic sensors operable to sense different wavelength bands of electromagnetic radiation.

19. The method of claim 18, wherein said soil characteristic comprises fluid infiltration potential and said comparing step comprises the step of analyzing different combinations of said binary values which correspond to different ones of said electromagnetic radiation wavelength bands to determine which of said combinations substantially distinguishes soil having a first fluid infiltration potential from soil having a second fluid infiltration potential.

20. The method of claim 19, wherein said comparing step comprises the step of comparing said image data with said test location data which corresponds to a group of electromagnetic radiation wavelength bands comprising a band extending approximately from 2.08 micrometers to 2.35 micrometers, a band extending approximately from 0.76 micrometers to 0.90 micrometers, and a band extending approximately from 0.45 micrometers to 0.52 micrometers.

21. The method of claim 19, wherein said comparing step comprises the step of comparing said image data with said test location data which corresponds to a group of electromagnetic radiation wavelength bands comprising a band extending approximately from 2.08 micrometers to 2.35 micrometers, a band extending approximately form 0.76 micrometers to 0.90 micrometers, and a band extending approximately form 0.52 micrometers to 0.60 micrometers.

22. The method of claim 19, wherein said comparing step comprises the step of comparing said image data with said test location data which corresponds to a group of electromagnetic radiation wavelength bands comprising a band extending approximately from 0.76 micrometers to 0.90 micrometers, a band extending approximately from 1.55 micrometers to 1.75 micrometers, and a band extending approximately from 0.63 micrometers to 0.69 micrometers.

23. The method of claim 18, wherein said comparing step comprises the step of analyzing different combinations of said binary values which correspond to different ones of said electromagnetic radiation wavelength bands to determine which of said combinations substantially distinguishes soil having a predetermined fluid infiltration characteristic from other soil in said geographic region.

24. The method of claim 23, wherein said comparing step comprises the step of comparing said image data with said test location data which corresponds to a group of electromagnetic radiation wavelength bands comprising a band extending approximately from 0.76 micrometers to 0.90 micrometers, a band extending approximately from 0.63 micrometers to 0.69 micrometers, and a band extending approximately from 0.52 micrometers to 0.60 micrometers.

25. A method for determining a fluid infiltration potential of soil in a geographic region, comprising the steps of:

sensing electromagnetic energy patterns in said geographic region with remote sensing means to obtain image data relating to said geographic region;

storing said image data in a memory means; and

analyzing the stored image data to determine a fluid infiltration potential of soil in said geographic region.

26. The method of claim 25, wherein a plurality of pixels constituting said image data are associated with a plurality of binary data values, said binary values corresponding to levels of radiation reflected from said geographic region and detected by a plurality of electromagnetic sensors operable to sense different wavelength bands of electromagnetic radiation.

27. The method of claim 25, wherein said fluid infiltration potential comprises a hydrologic soil group classification.

28. The method of claim 27, wherein:

a plurality of pixels constituting said image data are associated with a plurality of binary data values, said binary values corresponding to levels of radiation reflected from said geographic region and detected by a plurality of electromagnetic sensors operable to sense different wavelength bands of electromagnetic radiation; and

said analyzing step comprises the step of analyzing binary values which correspond to more than one of said electromagnetic radiation wavelength bands to distinguish soil having a first hydrologic soil group classification from soil having a second hydrologic soil group classification.

29. The method of claim 28, wherein said electromagnetic radiation wavelength bands comprise a band extending approximately from 2.08 micrometers to 2.35 micrometers, a band extending approximately from 0.76 micrometers to 0.90 micrometers, and a band extending approximately from 0.45 micrometers to 0.52 micrometers.

30. The method of claim 28, wherein said electromagnetic radiation wavelength bands comprise a band extending approximately from 2.08 micrometers to 2.35 micrometers, a band extending approximately from 0.76 micrometers to 0.90 micrometers, and a band extending approximately from 0.52 micrometers to 0.60 micrometers.

31. The method of claim 28, wherein said electromagnetic radiation wavelength bands comprise a band extending approximately from 0.76 micrometers to 0.90 micrometers, a band extending approximately from 1.55 micrometers to 1.75 micrometers, and a band extending approximately from 0.63 micrometers to 0.69 micrometers.

32. The method of claim 28, wherein said electromagnetic radiation wavelength bands comprise a band extending approximately from 0.76 micrometers to 0.90 micrometers, a band extending approximately from 0.63 micrometers to 0.69 micrometers, and a band extending approximately from 0.52 micrometers to 0.60 micrometers.