Our new study estimates satellite-based soil moisture basin & sub-grid variability
We estimate the soil moisture variability for basin and SMAP sub-grid using radar rainfall and soil properties.
We drive the statistical information for dry-down and wetting of soils and we use this information to estimate the spatial and temporal variability of soil moisture at the basin and satellite sub-grid. Our methods and results is useful where higher resolution soil moisture data is needed. On the other hand, we show that the variance (and standard deviation) of a bounded variable should be bounded. However, our methodology leads to an estimation of variability and skewness of soil moisture. As there is precipitation event over the basin, the soil moisture tends to increase and the mean value increases. At the same time, standard deviation of soil moisture decreases for wetter conditions. This phase is more rapid than dry-downs and changes the state of the soils faster. I have created these a video for a demonstration of how the soil moisture distribution changes over time as the wetting and dry-down events occur.
For example, in here I am showing an animation of the soil moisture distribution over time for Turkey River basin, located in North East of State of Iowa, USA.
While satellite-based soil moisture estimations are coarse in spatial resolution, our methods could be used for estimating variability of soil moisture at a given pixel or watershed.
For more details, you can download our paper in the attachment.
Data-driven stochastic model for basin and sub-grid variability of SMAPsatellite soil moisture.pdf
Here is a list of references used in this paper.
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@article{Rondinelli2015, abstract = {AbstractSoil moisture affects the spatial variation of land–atmosphere interactions through its influence on the balance of latent and sensible heat flux. Wetter soils are more prone to flooding because a smaller fraction of rainfall can infiltrate into the soil. The Soil Moisture and Oceanic Salinity (SMOS) satellite carries a remote sensing instrument able to make estimates of near–surface soil moisture on a global scale. One way to validate satellite observations is by comparing them with observations made with sparse networks of in situ soil moisture sensors that match the extent of satellite footprints. We found that the rate of soil drying after significant rainfall observed by SMOS is higher than the rate observed by a United States Department of Agriculture (USDA) soil moisture network in the watershed of the South Fork of the Iowa River. We conclude that SMOS and the network observe different layers of the soil: SMOS observes a layer of soil at the soil surface that is a few cm thick, while the n...}, author = {Rondinelli, Wesley J and Hornbuckle, Brian K and Patton, Jason C and Cosh, Michael H and Walker, Victoria A and Carr, Benjamin D and Logsdon, Sally D}, doi = {10.1175/JHM-D-14-0137.1}, isbn = {1525-755x}, issn = {1525-755X}, journal = {Journal of Hydrometeorology}, keywords = {Remote sensing,Soil moisture}, month = {apr}, number = {2}, pages = {889--903}, title = {{Different Rates of Soil Drying after Rainfall Are Observed by the SMOS Satellite and the South Fork in situ Soil Moisture Network}}, volume = {16}, year = {2015} } @article{Kim2013, author = {Kim, Seungbum}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Kim - 2013 - Ancillary Data Report Landcover Classification.pdf:pdf}, number = {SMAP Science Document no. 042}, title = {{Ancillary Data Report: Landcover Classification}}, year = {2013} }
@Article{Western1999, author = {Western, Andrew W. and Bl{\"{o}}schl, G{\"{u}}nter}, journal = {Journal of Hydrology}, title = {{On the spatial scaling of soil moisture}}, year = {1999}, issn = {00221694}, number = {3-4}, pages = {203--224}, volume = {217},
doi = {10.1016/S0022-1694(98)00232-7}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Western - 1999 - On the spatial scaling of soil moisture ¨.pdf:pdf}, keywords = {Sampling,Scale,Soil moisture,Variogram}, }
@Article{Neelam2015, author = {Neelam, Maheshwari and Mohanty, Binayak P.}, journal = {Water Resources Research}, title = {{Global sensitivity analysis of the radiative transfer model}}, year = {2015}, issn = {19447973}, number = {4}, pages = {2428--2443}, volume = {51},
doi = {10.1002/2014WR016534}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Neelam, Mohanty - Unknown - Global sensitivity analysis of the radiative transfer model(2).pdf:pdf}, keywords = {SMAPVEX12,SMEX02,radiative transfer,remote sensing,sensitivity,soil moisture}, } @article{Dorigo2011, author = {Dorigo, W. A. and Wagner, W. and Hohensinn, R. and Hahn, S. and Paulik, C. and Xaver, A. and Gruber, A. and Drusch, M. and Mecklenburg, S. and van Oevelen, P. and Robock, A. and Jackson, T.}, doi = {10.5194/hess-15-1675-2011}, issn = {1607-7938}, journal = {Hydrology and Earth System Sciences}, month = {may}, number = {5}, pages = {1675--1698}, title = {{The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements}}, volume = {15}, year = {2011} } @article{Entekhabi2010, author = {Entekhabi, Dara and Njoku, Eni G and O'Neill, Peggy E and Kellogg, Kent H and Crow, Wade T and Edelstein, Wendy N and Entin, Jared K and Goodman, Shawn D and Jackson, Thomas J and Johnson, Joel and Kimball, John and Piepmeier, Jeffrey R and Koster, Randal D and Martin, Neil and McDonald, Kyle C and Moghaddam, Mahta and Moran, Susan and Reichle, Rolf and Shi, J C and Spencer, Michael W and Thurman, Samuel W and Tsang, Leung and {Van Zyl}, Jakob}, doi = {10.1109/JPROC.2010.2043918}, isbn = {0018-9219}, issn = {00189219}, journal = {Proceedings of the IEEE}, keywords = {Freeze/thaw,Geoscience,Microwave,Remote sensing,Soil moisture}, month = {may}, number = {5}, pages = {704--716}, title = {{The soil moisture active passive (SMAP) mission}}, volume = {98}, year = {2010} } @article{Harrison2009, author = {Harrison, D. L. and Scovell, R. W. and Kitchen, M.}, doi = {10.1680/wama.2009.162.2.125}, isbn = {1741-7589}, issn = {1741-7589}, journal = {Proceedings of the Institution of Civil Engineers - Water Management}, keywords = {flood {\&} floodworks,hydrology {\&} water resource,weather}, month = {apr}, number = {2}, pages = {125--135}, publisher = {Thomas Telford Ltd}, title = {{High-resolution precipitation estimates for hydrological uses}}, volume = {162}, year = {2009} } @article{Bhatia2000, author = {Bhatia, Rajendra and Davis, Chandler}, doi = {10.2307/2589180}, issn = {00029890}, journal = {American Mathematical Monthly}, month = {apr}, number = {4}, pages = {353--357}, title = {{A better bound on the variance}}, url = {}, volume = {107}, year = {2000} } @article{Sivapalan1987, author = {Sivapalan, M. and Beven, Keith and Wood, Eric F.}, doi = {10.1029/WR023i012p02266}, issn = {19447973}, journal = {Water Resources Research}, number = {12}, pages = {2266--2278}, title = {{On hydrologic similarity: 2. A scaled model of storm runoff production}}, volume = {23}, year = {1987} }
@Article{Brocca2012, author = {Brocca, L. and Tullo, T. and Melone, F. and Moramarco, T. and Morbidelli, R.}, journal = {Journal of Hydrology}, title = {{Catchment scale soil moisture spatial-temporal variability}}, year = {2012}, issn = {00221694}, month = {feb}, pages = {63--75}, volume = {422-423}, abstract = {The characterization of the spatial-temporal variability of soil moisture is of paramount importance in many scientific fields and operational applications. However, due to the high variability of soil moisture, its monitoring over large areas and for extended periods through in situ point measurements is not straightforward. Usually, in the scientific literature, soil moisture variability has been investigated over short periods and in large areas or over long periods but in small areas. In this study, an effort to understanding soil moisture variability at catchment scale ({\textgreater}100km2), which is the size needed for some hydrological applications and for remote sensing validation analysis, is done. Specifically, measurements were carried out in two adjacent areas located in central Italy with extension of 178 and 242km2and over a period of 1year (35 sampling days) with almost weekly frequency except for the summer period because of soil hardness. For each area, 46 sites were monitored and, for each site, 3 measurements were performed to obtain reliable soil moisture estimates. Soil moisture was measured with a portable Time Domain Reflectometer for a layer depth of 0-15cm. A statistical and temporal stability analysis is employed to assess the space-time variability of soil moisture at local and catchment scale. Moreover, by comparing the results with those obtained in previous studies conducted in the same study area, a synthesis of soil moisture variability for a range of spatial scales, from few square meters to several square kilometers, is attempted. For the investigated area, the two main findings inferred are: (1) the spatial variability of soil moisture increases with the area up to {\~{}}10km2and then remains quite constant with an average coefficient of variation equal to {\~{}}0.20; (2) regardless of the areal extension, the soil moisture exhibits temporal stability features and, hence, few measurements can be used to infer areal mean values with a good accuracy (determination coefficient higher than 0.88). These insights based on in situ soil moisture observations corroborate the opportunity to use point information for the validation of coarse resolution satellite images. Moreover, the feasibility to use coarse resolution data for hydrological applications in small to medium sized catchments is confirmed. {\textcopyright} 2012 Elsevier B.V.}, doi = {10.1016/j.jhydrol.2011.12.039}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Brocca et al. - 2012 - Catchment scale soil moisture spatial–temporal variability.pdf:pdf}, isbn = {0022-1694}, keywords = {Catchment scale,In situ measurements,Soil moisture,Spatial variability}, publisher = {Elsevier}, } @article{Hardie2013, author = {Hardie, Marcus and Lisson, Shaun and Doyle, Richard and Cotching, William}, doi = {10.1016/j.jconhyd.2012.10.008}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Hardie et al. - 2013 - Determining the frequency, depth and velocity of preferential flow by high frequency soil moisture monitoring.pdf:pdf}, isbn = {0169-7722}, issn = {18736009}, journal = {Journal of Contaminant Hydrology}, keywords = {Agrochemical mobilisation,Antecedent soil moisture,Finger flow,Hydrophobic,Macropore flow,Soil moisture probe}, number = {1}, pages = {66--77}, pmid = {23159761}, publisher = {Elsevier B.V.}, title = {{Determining the frequency, depth and velocity of preferential flow by high frequency soil moisture monitoring}}, volume = {144}, year = {2013} } @article{Peel2007, archivePrefix = {arXiv}, arxivId = {hal-00298818}, author = {Peel, M C and Finlayson, B L and McMahon, T A}, doi = {10.5194/hess-11-1633-2007}, eprint = {hal-00298818}, isbn = {09412948}, issn = {16077938}, journal = {Hydrology and Earth System Sciences}, number = {5}, pages = {1633--1644}, pmid = {2614}, title = {{Updated world map of the K{\"{o}}ppen-Geiger climate classification}}, volume = {11}, year = {2007} } @article{Zarlenga2018, author = {Zarlenga, A. and Fiori, A. and Russo, D.}, doi = {10.1002/2017WR021304}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Approach - 2018 - Water Resources Research.pdf:pdf}, issn = {0043-1397}, journal = {Water Resources Research}, keywords = {geostatistical analysis,scaling,soil moisture}, month = {mar}, number = {3}, pages = {1765--1780}, title = {{Spatial Variability of Soil Moisture and the Scale Issue: A Geostatistical Approach}}, volume = {54}, year = {2018} }
@Article{Brocca2017, author = {Brocca, Luca and Ciabatta, Luca and Massari, Christian and Camici, Stefania and Tarpanelli, Angelica}, journal = {WATER}, title = {{Soil Moisture for Hydrological Applications: Open Questions and New Opportunities}}, year = {2017}, issn = {2073-4441}, month = {feb}, number = {2}, volume = {9}, abstract = {Soil moisture is widely recognized as a key parameter in the mass and energy balance between the land surface and the atmosphere and, hence, the potential societal benefits of an accurate estimation of soil moisture are immense. Recently, scientific community is making great effort for addressing the estimation of soil moisture over large areas through in situ sensors, remote sensing and modelling approaches. The different techniques used for addressing the monitoring of soil moisture for hydrological applications are briefly reviewed here. Moreover, some examples in which in situ and satellite soil moisture data are successfully employed for improving hydrological monitoring and predictions (e.g., floods, landslides, precipitation and irrigation) are presented. Finally, the emerging applications, the open issues and the future opportunities given by the increased availability of soil moisture measurements are outlined.}, address = {ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND}, doi = {10.3390/w9020140}, file = {:C\(\backslash\):/Users/njadidoleslam/Downloads/water-09-00140-v2.pdf:pdf}, keywords = {hydrology,in situ measurements,re,soil moisture}, publisher = {MDPI AG}, } @article{Njoku1996, author = {Njoku, Eni G. and Entekhabi, Dara}, doi = {10.1016/0022-1694(95)02970-2}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Njoku, Entekhabi - 1996 - Passive microwave remote sensing of soil moisture.pdf:pdf}, isbn = {0022-1694}, issn = {00221694}, journal = {Journal of Hydrology}, month = {oct}, number = {1-2}, pages = {101--129}, publisher = {Elsevier}, title = {{Passive microwave remote sensing of soil moisture}}, volume = {184}, year = {1996} }
@Article{CampbellScientific2012, author = {{Campbell Scientific Inc.}}, title = {{CS650 and CS655 Water Content Reflectometers Instruction Manual}}, year = {2012}, pages = {56}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Unknown - Unknown - INSTRUCTION MANUAL CS650 and CS655 Water Content Reflectometers.pdf:pdf}, url = {www.campbellsci.com.}, } @article{Entekhabi1996, address = {PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}, author = {Entekhabi, Dara and Rodriguez-Iturbe, Ignacio and Castelli, Fabio}, doi = {10.1016/0022-1694(95)02965-6}, issn = {00221694}, journal = {Journal of Hydrology}, month = {oct}, number = {1-2}, pages = {3--17}, publisher = {ELSEVIER SCIENCE BV}, title = {{Mutual interaction of soil moisture state and atmospheric processes}}, volume = {184}, year = {1996} } @article{Famiglietti2008, address = {2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA}, author = {Famiglietti, James S. and Ryu, Dongryeol and Berg, Aaron A. and Rodell, Matthew and Jackson, Thomas J.}, doi = {10.1029/2006WR005804}, file = {:E\(\backslash\):/Files/OneDrive - University of Iowa/Publication/Pub 2-Model Development/references/Famiglietti{_}et{_}al-2008-Water{_}Resources{_}Research.pdf:pdf}, isbn = {0043-1397}, issn = {00431397}, journal = {Water Resources Research}, month = {jan}, number = {1}, publisher = {AMER GEOPHYSICAL UNION}, title = {{Field observations of soil moisture variability across scales}}, volume = {44}, year = {2008} }
@Article{Zhang2016, author = {Zhang, Jian and Howard, Kenneth and Langston, Carrie and Kaney, Brian and Qi, Youcun and Tang, Lin and Grams, Heather and Wang, Yadong and Cockcks, Stephen and Martinaitis, Steven and Arthur, Ami and Cooper, Karen and Brogden, Jeff and Kitzmillller, David}, journal = {Bulletin of the American Meteorological Society}, title = {{Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimation: Initial operating capabilities}}, year = {2016}, issn = {00030007}, month = {apr}, number = {4}, pages = {621--638}, volume = {97},
doi = {10.1175/BAMS-D-14-00174.1}, }
@Article{Huffman2015, author = {Huffman, George J. and Bolvin, David T. and Braithwaite, Dan and Hsu, Kuo and Joyce, Robert and Kidd, Christopher and Nelkin, Eric J. and Xie, Pingping}, journal = {Algorithm Theoretical Basis Document (ATBD) Version 4.5}, title = {{NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG)}}, year = {2015}, number = {November}, pages = {26}, } @article{Chen2018, author = {Chen, Quan and Zeng, Jiangyuan and Cui, Chenyang and Li, Zhen and Chen, Kun Shan and Bai, Xiaojing and Xu, Jia}, doi = {10.1109/TGRS.2017.2762462}, issn = {01962892}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, keywords = {Active microwave,Error analysis,Passive microwave,Soil Moisture Active Passive (SMAP),Soil moisture,Validation}, month = {mar}, number = {3}, pages = {1398--1408}, title = {{Soil Moisture Retrieval from SMAP: A Validation and Error Analysis Study Using Ground-Based Observations over the Little Washita Watershed}}, volume = {56}, year = {2018} } @article{Babaeian2019, author = {Babaeian, Ebrahim and Sadeghi, Morteza and Jones, Scott B. and Montzka, Carsten and Vereecken, Harry and Tuller, Markus}, doi = {10.1029/2018RG000618}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Babaeian et al. - 2019 - Ground, Proximal and Satellite Remote Sensing of Soil Moisture.pdf:pdf}, issn = {8755-1209}, journal = {Reviews of Geophysics}, keywords = {Climate Change,Data Assimilation,Electromagnetic Sensors,Hydrology,Proximal Sensing,Remote Sensing,Soil Moisture}, month = {mar}, pages = {2018RG000618}, publisher = {John Wiley {\&} Sons, Ltd}, title = {{Ground, Proximal and Satellite Remote Sensing of Soil Moisture}}, year = {2019} } @article{Topp1980, author = {Topp, G C and Davis, J L and Annan, A P}, doi = {10.1029/WR016i003p00574}, isbn = {1944-7973}, issn = {19447973}, journal = {Water Resources Research}, number = {3}, pages = {574--582}, title = {{Electromagnetic determination of soil water content: Measurements in coaxial transmission lines}}, volume = {16}, year = {1980} } @article{Shellito2016, author = {Shellito, Peter J. and Small, Eric E. and Colliander, Andreas and Bindlish, Rajat and Cosh, Michael H. and Berg, Aaron A. and Bosch, David D. and Caldwell, Todd G. and Goodrich, David C. and McNairn, Heather and Prueger, John H. and Starks, Patrick J. and van der Velde, Rogier and Walker, Jeffrey P.}, doi = {10.1002/2016GL069946}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Shellito et al. - 2016 - SMAP soil moisture drying more rapid than observed in situ following rainfall events.pdf:pdf}, isbn = {0094-8276}, issn = {19448007}, journal = {Geophysical Research Letters}, keywords = {Soil Moisture Active Passive (SMAP),drydown,in situ monitoring,validation}, month = {aug}, number = {15}, pages = {8068--8075}, publisher = {Wiley-Blackwell}, title = {{SMAP soil moisture drying more rapid than observed in situ following rainfall events}}, volume = {43}, year = {2016} } @article{Ciach1999, author = {Ciach, Grzegorz J. and Krajewski, Witold F.}, doi = {10.1016/S0309-1708(98)00043-8}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Ciach, Krajewski - 1999 - On the estimation of radar rainfall error variance.pdf:pdf}, isbn = {0309-1708}, issn = {03091708}, journal = {Advances in Water Resources}, month = {feb}, number = {6}, pages = {585--595}, publisher = {Elsevier}, title = {{On the estimation of radar rainfall error variance}}, volume = {22}, year = {1999} }
@Article{Romano2014, author = {Romano, Nunzio}, journal = {Journal of Hydrology}, title = {{Soil moisture at local scale: Measurements and simulations}}, year = {2014}, issn = {0022-1694}, month = {aug}, pages = {6--20}, volume = {516}, abstract = {Soil moisture refers to the water present in the uppermost part of a field soil and is a state variable controlling a wide array of ecological, hydrological, geotechnical, and meteorological processes. The literature on soil moisture is very extensive and is developing so rapidly that it might be considered ambitious to seek to present the state of the art concerning research into this key variable. Even when covering investigations about only one aspect of the problem, there is a risk of some inevitable omission. A specific feature of the present essay, which may make this overview if not comprehensive at least of particular interest, is that the reader is guided through the various traditional and more up-to-date methods by the central thread of techniques developed to measure soil moisture interwoven with applications of modeling tools that exploit the observed datasets. This paper restricts its analysis to the evolution of soil moisture at the local (spatial) scale. Though a somewhat loosely defined term, it is linked here to a characteristic length of the soil volume investigated by the soil moisture sensing probe. After presenting the most common concepts and definitions about the amount of water stored in a certain volume of soil close to the land surface, this paper proceeds to review ground-based methods for monitoring soil moisture and evaluates modeling tools for the analysis of the gathered information in various applications. Concluding remarks address questions of monitoring and modeling of soil moisture at scales larger than the local scale with the related issue of data aggregation. An extensive, but not exhaustive, list of references is provided, enabling the reader to gain further insights into this subject.}, doi = {10.1016/J.JHYDROL.2014.01.026}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Romano - 2014 - Soil moisture at local scale Measurements and simulations.pdf:pdf}, publisher = {Elsevier}, } @article{Cho2014, author = {Cho, Eunsang and Choi, Minha}, doi = {10.1016/j.jhydrol.2013.12.053}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Cho, Choi - 2014 - Regional scale spatio-temporal variability of soil moisture and its relationship with meteorological factors over the.pdf:pdf}, isbn = {0022-1694}, issn = {00221694}, journal = {Journal of Hydrology}, keywords = {Meteorological factors,Regional scale,Soil moisture,Spatial variability,Temporal stability}, month = {aug}, pages = {317--329}, publisher = {Elsevier}, title = {{Regional scale spatio-temporal variability of soil moisture and its relationship with meteorological factors over the Korean peninsula}}, volume = {516}, year = {2014} } @article{Chaney2015, author = {Chaney, Nathaniel W. and Roundy, Joshua K. and Herrera-Estrada, Julio E. and Wood, Eric F.}, doi = {10.1002/2013WR014964}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Chaney et al. - 2015 - High-resolution modeling of the spatial heterogeneity of soil moisture Applications in network design.pdf:pdf}, issn = {19447973}, journal = {Water Resources Research}, keywords = {land surface modeling,network design,soil moisture,topography}, month = {jan}, number = {1}, pages = {619--638}, publisher = {John Wiley {\&} Sons, Ltd}, title = {{High-resolution modeling of the spatial heterogeneity of soil moisture: Applications in network design}}, volume = {51}, year = {2015} } @article{Koster2004, author = {Koster, Randal D. and Dirmeyer, Paul A. and Guo, Zhichang and Bonan, Gordon and Chan, Edmond and Cox, Peter and Gordon, C. T. and Kanae, Shinjiro and Kowalczyk, Eva and Lawrence, David and Liu, Ping and Lu, Cheng Hsuan and Malyshev, Sergey and McAvaney, Bryant and Mitchell, Ken and Mocko, David and Oki, Taikan and Oleson, Keith and Pitman, Andrew and Sud, Y. C. and Taylor, Christopher M. and Verseghy, Diana and Vasic, Ratko and Xue, Yongkang and Yamada, Tomohito}, doi = {10.1126/science.1100217}, isbn = {1095-9203 (Electronic)\(\backslash\)r0036-8075 (Linking)}, issn = {00368075}, journal = {Science}, number = {5687}, pages = {1138--1140}, pmid = {15326351}, title = {{Regions of strong coupling between soil moisture and precipitation}}, volume = {305}, year = {2004} }
@Article{Rosenbaum2012, author = {Rosenbaum, U. and Bogena, H. R. and Herbst, M. and Huisman, J. A. and Peterson, T. J. and Weuthen, A. and Western, A. W. and Vereecken, H.}, journal = {Water Resources Research}, title = {{Seasonal and event dynamics of spatial soil moisture patterns at the small catchment scale}}, year = {2012}, issn = {00431397}, month = {oct}, number = {10}, volume = {48}, doi = {10.1029/2011WR011518}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Rosenbaum et al. - 2012 - Seasonal and event dynamics of spatial soil moisture patterns at the small catchment scale.pdf:pdf}, keywords = {geostatistics,seasonal and event dynamics,soil moisture,spatial patterns,spruce,wireless sensor networks}, publisher = {Wiley-Blackwell}, }
@Article{Teuling2005, author = {Teuling, Adriaan J. and Troch, Peter A.}, journal = {Geophysical Research Letters}, title = {{Improved understanding of soil moisture variability dynamics}}, year = {2005}, issn = {00948276}, month = {mar}, number = {5}, pages = {1--4}, volume = {32}, abstract = {Different trends of soil moisture variability with mean moisture content have been reported from field observations. Here we explain these trends for three different data sets by showing how vegetation, soil and topography controls interact to either create or destroy spatial variance. Improved understanding of these processes is needed for the transformation of point-scale measurements and parameterizations to scales required for climate studies, operational weather forecasting, and large scale hydrological modeling.}, doi = {10.1029/2004GL021935}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Teuling, Troch - 2005 - Improved understanding of soil moisture variability dynamics(4).pdf:pdf}, publisher = {John Wiley {\&} Sons, Ltd}, }
@Article{Boone1998, author = {Boone, Richard D. and Nadelhoffer, Knute J. and Canary, Jana D. and Kaye, Jason P.}, journal = {Nature}, title = {{Roots exert a strong influence on the temperature sensitivity of soil respiration}}, year = {1998}, issn = {00280836}, number = {6711}, pages = {570--572}, volume = {396}, abstract = {The temperature sensitivity of soil respiration will largely determine the effects of a warmer world on net carbon flux from soils to the atmosphere. CO2 flux from soils to the atmosphere is estimated to be 50–70 petagrams of carbon per year and makes up 20–38{{}{\%}{}} of annual inputs of carbon (in the form of CO2) to the atmosphere from terrestrial and marine sources1,2. Here we show that, for a mixed temperate forest, respiration by roots plus oxidation of rhizosphere carbon, which together produce a large portion of total effluxed soil CO2, is more temperature-sensitive than the respiration of bulk soil. We determine that the Q10 value (the coefficient for the exponential relationship between soil respiration and temperature, multiplied by ten) is 4.6 for autotrophic root respiration plus rhizosphere decomposition, 2.5 for respiration by soil lacking roots and 3.5 for respiration by bulk soil. If plants in a higher-CO2 atmosphere increase their allocation of photosynthate to roots3, 4, 5, 6 these findings suggest that soil respiration should be more sensitive to elevated temperatures, thus limiting carbon sequestration by soils.}, doi = {10.1038/25119}, isbn = {0028-0836}, pmid = {77466800056}, publisher = {Nature Publishing Group}, }
@Article{Brocca2014, author = {Brocca, L. and Zucco, G. and Mittelbach, H. and Moramarco, T. and Seneviratne, S. I.}, journal = {Water Resources Research}, title = {{Absolute versus temporal anomaly and percent of saturation soil moisture spatial variability for six networks worldwide}}, year = {2014}, issn = {00431397}, month = {jul}, number = {7}, pages = {5560--5576}, volume = {50}, doi = {10.1002/2014WR015684}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Brocca et al. - 2014 - Absolute versus temporal anomaly and percent of saturation soil moisture spatial variability for six networks wor.pdf:pdf}, keywords = {absolute soil moisture,large‐scale networks,soil moisture,spatial‐temporal variability,statistical analysis,temporal anomalies}, publisher = {John Wiley {\&} Sons, Ltd}, }
@Article{Choi2007, author = {Choi, Minha and Jacobs, Jennifer M.}, journal = {Advances in Water Resources}, title = {{Soil moisture variability of root zone profiles within SMEX02 remote sensing footprints}}, year = {2007}, issn = {03091708}, month = {apr}, number = {4}, pages = {883--896}, volume = {30},
doi = {10.1016/j.advwatres.2006.07.007}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd/Mendeley Desktop/Downloaded/Choi, Jacobs - 2007 - Soil moisture variability of root zone profiles within SMEX02 remote sensing footprints.pdf:pdf}, isbn = {0309-1708}, keywords = {Coefficient of variation,Normal and Log-normal distributions,Physical model,SMEX02,Soil moisture variability,Time stability}, type = {Article}, } @article{Stevens2018, annote = {https://www.stevenswater.com/resources/documentation/hydraprobe/HydraProbe{_}Manual{_}Jan{_}2018.pdf}, author = {Stevens}, title = {{Soil Sensor {\textregistered}Users Manual}}, year = {2018} }
@Article{Western2004, author = {Western, Andrew W. and Zhou, Sen-Lin and Grayson, Rodger B. and McMahon, Thomas A. and Bl{\"{o}}schl, G{\"{u}}nter and Wilson, David J.}, journal = {Journal of Hydrology}, title = {{Spatial correlation of soil moisture in small catchments and its relationship to dominant spatial hydrological processes}}, year = {2004}, issn = {00221694}, month = {jan}, number = {1-4}, pages = {113--134}, volume = {286}, abstract = {The geostatistical properties of soil moisture patterns from five different sites in Australia (Tarrawarra and Point Nepean) and New Zealand (three sites from the Mahurangi River Basin - Carran's, Clayden's and Satellite Station) are analysed here. The soil moisture data were collected using time domain reflectometry and consistent methods for all sites, thereby allowing comparisons to be drawn between sites without the complication of methodological differences. The sites have contrasting climatic and soils characteristics. Soil moisture in the top 30 cm of the soil profile was measured using time domain reflectometry on 6-8 occasions at each site. The variance and correlation structure of the patterns was analysed. Typical correlation scales lie between 30 and 60 m. We found that there was a seasonal evolution in the spatial soil moisture variance that was related to changes in the spatial mean moisture content at all sites. At the Australian sites there was also a seasonal evolution in the correlation length related to changes in the spatial mean moisture, but not at the New Zealand sites. The seasonal evolution of the correlation length in the Australian catchments is likely to be associated with a seasonal change in the processes controlling the soil moisture pattern. The more humid climate at the New Zealand sites leads to more consistent spatial controls over the year. Similarities between the correlation structure of the moisture and topographic indices representing lateral flow and topographically modulated evaporative forcing were found at Tarrawarra, Carran's and Clayden's. At Point Nepean the correlation structure of the soil moisture pattern is controlled by a larger (than the topography) scale variation in soils, properties and at Satellite Station a smaller scale source of variability is apparent in the data (although there were also topographical effects apparent, associated with valley features). The results demonstrate that the processes controlling spatial patterns can change between places and over time with catchment moisture status; however, when similar general conditions reoccur in a catchment, similar spatial patterns result. Soil characteristics and climate do provide a general pointer to what we might expect but the results also show subtleties specific to place. {\textcopyright} 2003 Elsevier B.V. All rights reserved.}, doi = {10.1016/j.jhydrol.2003.09.014}, isbn = {0022-1694}, keywords = {Correlation structure,Soil moisture,Time domain reflectometry,Topography,Variogram}, pmid = {5827930}, publisher = {Elsevier}, }
@Article{MartinezGarcia2014, author = {{Mart{\'{i}}nez Garc{\'{i}}a}, Gonzalo and Pachepsky, Yakov A. and Vereecken, Harry}, journal = {Journal of Hydrology}, title = {{Effect of soil hydraulic properties on the relationship between the spatial mean and variability of soil moisture}}, year = {2014}, issn = {0022-1694}, month = {aug}, pages = {154--160}, volume = {516}, abstract = {Knowledge of spatial mean soil moisture and its variability over time is needed in many environmental applications. We analyzed dependencies of soil moisture variability on average soil moisture contents in soils with and without root water uptake using ensembles of non-stationary water flow simulations by varying soil hydraulic properties under different climatic conditions. We focused on the dry end of the soil moisture range and found that the magnitude of soil moisture variability was controlled by the interplay of soil hydraulic properties and climate. The average moisture at which the maximum variability occurred depended on soil hydraulic properties and vegetation. A positive linear relationship was observed between mean soil moisture and its standard deviation and was controlled by the parameter defining the shape of soil water retention curves and the spatial variability of saturated hydraulic conductivity. The influence of other controls, such as variable weather patterns, topography or lateral flow processes needs to be studied further to see if such relationship persists and could be used for the inference of soil hydraulic properties from the spatiotemporal variation in soil moisture.}, doi = {10.1016/J.JHYDROL.2014.01.069}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Mart{\'{i}}nez Garc{\'{i}}a, Pachepsky, Vereecken - 2014 - Effect of soil hydraulic properties on the relationship between the spatial mean and vari.pdf:pdf}, publisher = {Elsevier}, } @article{Wang2015, author = {Wang, Tiejun and Franz, Trenton E. and Zlotnik, Vitaly A. and You, Jinsheng and Shulski, Martha D.}, doi = {10.1016/j.jhydrol.2015.03.019}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Wang et al. - 2015 - Investigating soil controls on soil moisture spatial variability Numerical simulations and field observations.pdf:pdf}, isbn = {0022-1694}, issn = {00221694}, journal = {Journal of Hydrology}, keywords = {Climate,Soil hydraulic properties,Soil moisture,Spatial variability,Vegetation}, pages = {576--586}, title = {{Investigating soil controls on soil moisture spatial variability: Numerical simulations and field observations}}, type = {Article}, volume = {524}, year = {2015} }
@Article{Yang2016, author = {Yang, Kai and Wang, Chenghai and Bao, Hongyan}, journal = {Journal of Geophysical Research: Atmospheres}, title = {{Contribution of soil moisture variability to summer precipitation in the Northern Hemisphere}}, year = {2016}, issn = {2169897X}, month = {oct}, number = {20}, pages = {12,108--12,124}, volume = {121}, doi = {10.1002/2016JD025644}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Yang, Wang, Bao - 2016 - Contribution of soil moisture variability to summer precipitation in the Northern Hemisphere.pdf:pdf}, keywords = {model simulations,spring soil moisture variability,summer precipitation}, publisher = {John Wiley {\&} Sons, Ltd}, }
@Article{Gebler2017, author = {Gebler, S. and {Hendricks Franssen}, H.-J. and Kollet, S.J. and Qu, W. and Vereecken, H.}, journal = {Journal of Hydrology}, title = {{High resolution modelling of soil moisture patterns with TerrSysMP: A comparison with sensor network data}}, year = {2017}, issn = {0022-1694}, month = {apr}, pages = {309--331}, volume = {547}, abstract = {The prediction of the spatial and temporal variability of land surface states and fluxes with land surface models at high spatial resolution is still a challenge. This study compares simulation results using TerrSysMP including a 3D variably saturated groundwater flow model (ParFlow) coupled to the Community Land Model (CLM) of a 38ha managed grassland head-water catchment in the Eifel (Germany), with soil water content (SWC) measurements from a wireless sensor network, actual evapotranspiration recorded by lysimeters and eddy covariance stations and discharge observations. TerrSysMP was discretized with a 10×10m lateral resolution, variable vertical resolution (0.025–0.575m), and the following parameterization strategies of the subsurface soil hydraulic parameters: (i) completely homogeneous, (ii) homogeneous parameters for different soil horizons, (iii) different parameters for each soil unit and soil horizon and (iv) heterogeneous stochastic realizations. Hydraulic conductivity and Mualem-Van Genuchten parameters in these simulations were sampled from probability density functions, constructed from either (i) soil texture measurements and Rosetta pedotransfer functions (ROS), or (ii) estimated soil hydraulic parameters by 1D inverse modelling using shuffle complex evolution (SCE). The results indicate that the spatial variability of SWC at the scale of a small headwater catchment is dominated by topography and spatially heterogeneous soil hydraulic parameters. The spatial variability of the soil water content thereby increases as a function of heterogeneity of soil hydraulic parameters. For lower levels of complexity, spatial variability of the SWC was underrepresented in particular for the ROS-simulations. Whereas all model simulations were able to reproduce the seasonal evapotranspiration variability, the poor discharge simulations with high model bias are likely related to short-term ET dynamics and the lack of information about bedrock characteristics and an on-site drainage system in the uncalibrated model. In general, simulation performance was better for the SCE setups. The SCE-simulations had a higher inverse air entry parameter resulting in SWC dynamics in better correspondence with data than the ROS simulations during dry periods. This illustrates that small scale measurements of soil hydraulic parameters cannot be transferred to the larger scale and that interpolated 1D inverse parameter estimates result in an acceptable performance for the catchment.}, doi = {10.1016/J.JHYDROL.2017.01.048}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Gebler et al. - 2017 - High resolution modelling of soil moisture patterns with TerrSysMP A comparison with sensor network data.pdf:pdf}, publisher = {Elsevier}, } @article{Chaney2016, author = {Chaney, Nathaniel W. and Wood, Eric F. and McBratney, Alexander B. and Hempel, Jonathan W. and Nauman, Travis W. and Brungard, Colby W. and Odgers, Nathan P.}, doi = {10.1016/j.geoderma.2016.03.025}, isbn = {0016-7061}, issn = {00167061}, journal = {Geoderma}, keywords = {Digital soil mapping,Environmental modeling,High performance computing}, month = {jul}, pages = {54--67}, title = {{POLARIS: A 30-meter probabilistic soil series map of the contiguous United States}}, volume = {274}, year = {2016} } @article{Famiglietti1998, author = {Famiglietti, J. S. and Rudnicki, J. W. and Rodell, M.}, doi = {10.1016/S0022-1694(98)00187-5}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Famiglietti, Rudnicki, Rodell - 1998 - Variability in surface moisture content along a hillslope transect Rattlesnake Hill, Texas(2).pdf:pdf}, isbn = {0022-1694}, issn = {00221694}, journal = {Journal of Hydrology}, keywords = {Correlation coefficient,Field studies,Hydrology,Soil moisture,Statistical analysis}, number = {1-4}, pages = {259--281}, title = {{Variability in surface moisture content along a hillslope transect: Rattlesnake Hill, Texas}}, volume = {210}, year = {1998} }
@Article{Ryu2005, author = {Ryu, Dongryeol and Famiglietti, James S.}, journal = {Water Resources Research}, title = {{Characterization of footprint-scale surface soil moisture variability using Gaussian and beta distribution functions during the Southern Great Plains 1997 (SGP97) hydrology experiment}}, year = {2005}, issn = {00431397}, month = {dec}, number = {12}, volume = {41}, doi = {10.1029/2004WR003835}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Ryu, Famiglietti - 2005 - Characterization of footprint-scale surface soil moisture variability using Gaussian and beta distribution fun.pdf:pdf}, keywords = {probability density function,soil moisture,soil moisture variability}, publisher = {John Wiley {\&} Sons, Ltd}, } @article{Qu2015, author = {Qu, W and Bogena, H R and Huisman, J A and Vanderborght, J and Schuh, M and Priesack, E and Vereecken, H}, doi = {10.1002/2014GL062496}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Qu et al. - Unknown - Predicting subgrid variability of soil water content from basic soil information.pdf:pdf}, issn = {00948276}, journal = {Geophysical Research Letters}, month = {feb}, number = {3}, pages = {789--796}, title = {{Predicting subgrid variability of soil water content from basic soil information}}, volume = {42}, year = {2015} } @article{Kerr2007, author = {Kerr, Yann H.}, doi = {10.1007/s10040-006-0095-3}, file = {:E\(\backslash\):/Files/OneDrive - University of Iowa/Publication/Pub 2-Model Development/references/Kerr2007{_}Article{_}SoilMoistureFromSpaceWhereAreW.pdf:pdf}, isbn = {1431-2174}, issn = {14312174}, journal = {Hydrogeology Journal}, keywords = {L band,Passive microwaves,Remote sensing,Soil moisture,Unsaturated zone}, number = {1}, pages = {117--120}, pmid = {755}, title = {{Soil moisture from space: Where are we?}}, volume = {15}, year = {2007} } @article{Chan2016, author = {Chan, Steven K. and Bindlish, Rajat and O'Neill, Peggy E. and Njoku, Eni and Jackson, Tom and Colliander, Andreas and Chen, Fan and Burgin, Mariko and Dunbar, Scott and Piepmeier, Jeffrey and Yueh, Simon and Entekhabi, Dara and Cosh, Michael H. and Caldwell, Todd and Walker, Jeffrey and Wu, Xiaoling and Berg, Aaron and Rowlandson, Tracy and Pacheco, Anna and McNairn, Heather and Thibeault, Marc and Martinez-Fernandez, Jose and Gonzalez-Zamora, Angel and Seyfried, Mark and Bosch, David and Starks, Patrick and Goodrich, David and Prueger, John and Palecki, Michael and Small, Eric E. and Zreda, Marek and Calvet, Jean Christophe and Crow, Wade T. and Kerr, Yann}, doi = {10.1109/TGRS.2016.2561938}, isbn = {0196-2892 VO - 54}, issn = {01962892}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, keywords = {Brightness temperature,L-band,Level 2 Passive Soil Moisture Product (L2-SM-P),Level 3 Daily Composite Version (L3-SM-P),Soil Moisture Active Passive (SMAP),land emission,passive microwave remote sensing,soil moisture,tau-omega(\(\tau\)-\(\omega\)) model,validation}, month = {aug}, number = {8}, pages = {4994--5007}, title = {{Assessment of the SMAP Passive Soil Moisture Product}}, volume = {54}, year = {2016} } @inproceedings{Chaubell2016, author = {Chaubell, Julian and Yueh, S. and Entekhabi, D. and Peng, J.}, booktitle = {2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)}, doi = {10.1109/IGARSS.2016.7729065}, isbn = {978-1-5090-3332-4}, keywords = {Backus-Gilbert theory,Resolution enhancement}, month = {jul}, pages = {284--287}, publisher = {IEEE}, title = {{Resolution enhancement of SMAP radiometer data using the Backus Gilbert optimum interpolation technique}}, volume = {2016-Novem}, year = {2016} } @article{Grillakis2016, author = {Grillakis, M. G. and Koutroulis, A. G. and Komma, J. and Tsanis, I. K. and Wagner, W. and Bl{\"{o}}schl, G.}, doi = {10.1016/j.jhydrol.2016.03.007}, isbn = {0022-1694}, issn = {00221694}, journal = {Journal of Hydrology}, keywords = {Austria,Crete,Flood generation,Initial soil moisture,Soil water index}, pages = {206--217}, publisher = {Elsevier}, title = {{Initial soil moisture effects on flash flood generation – A comparison between basins of contrasting hydro-climatic conditions}}, volume = {541}, year = {2016} } @book{Guo2018, author = {Guo, Li and Lin, Henry}, booktitle = {Advances in Agronomy}, doi = {10.1016/bs.agron.2017.10.002}, edition = {1}, isbn = {9780128152836}, issn = {00652113}, keywords = {Flow mechanisms,Hydropedology,Near-surface hydrogeophysics,Soil moisture sensor network,Soil water movement,Subsurface hydrology}, pages = {1--59}, publisher = {Elsevier Inc.}, title = {{Addressing Two Bottlenecks to Advance the Understanding of Preferential Flow in Soils}}, volume = {147}, year = {2018} }
@Article{Yang2017, author = {Yang, Yang and Dou, Yanxing and Liu, Dong and An, Shaoshan}, journal = {Journal of Hydrology}, title = {{Spatial pattern and heterogeneity of soil moisture along a transect in a small catchment on the Loess Plateau}}, year = {2017}, issn = {00221694}, pages = {466--477}, volume = {550}, abstract = {Spatial pattern and heterogeneity of soil moisture is important for the hydrological process on the Loess Plateau. This study combined the classical and geospatial statistical techniques to examine the spatial pattern and heterogeneity of soil moisture along a transect scale (e.g. land use types and topographical attributes) on the Loess Plateau. The average values of soil moisture were on the order of farmland {\textgreater} orchard {\textgreater} grassland {\textgreater} abandoned land {\textgreater} shrubland {\textgreater} forestland. Vertical distribution characteristics of soil moisture (0–500 cm) were similar among land use types. Highly significant (p {\textless} 0.01) negative correlations were found between soil moisture and elevation (h) except for shrubland (p {\textgreater} 0.05), whereas no significant correlations were found between soil moisture and plan curvature (Kh), stream power index (SPI), compound topographic index (CTI) (p {\textgreater} 0.05), indicating that topographical attributes (mainly h) have a negative effect on the soil moisture spatial heterogeneity. Besides, soil moisture spatial heterogeneity decreased from forestland to grassland and farmland, accompanied by a decline from 15° to 1° alongside upper to lower slope position. This study highlights the importance of land use types and topographical attributes on the soil moisture spatial heterogeneity from a combined analysis of the structural equation model (SEM) and generalized additive models (GAMs), and the relative contribution of land use types to the soil moisture spatial heterogeneity was higher than that of topographical attributes, which provides insights for researches focusing on soil moisture varitions on the Loess Plateau.}, doi = {10.1016/j.jhydrol.2017.05.026}, isbn = {0022-1694}, keywords = {Catchment,Loess Plateau,Soil moisture,Spatial heterogeneity,Transect scale}, publisher = {Elsevier}, }
@Article{Cornelissen2014, author = {Cornelissen, Thomas and Diekkr{\"{u}}ger, Bernd and Bogena, Heye R.}, journal = {Journal of Hydrology}, title = {{Significance of scale and lower boundary condition in the 3D simulation of hydrological processes and soil moisture variability in a forested headwater catchment}}, year = {2014}, issn = {00221694}, month = {aug}, pages = {140--153}, volume = {516}, abstract = {The measurement and simulation of soil moisture patterns and their spatio-temporal variability are current challenges in hydrology. This study investigated the capability of the three-dimensional model HydroGeoSphere to simulate hydrological processes, soil moisture dynamics and patterns at 25 and 100. m resolutions with daily and hourly time steps in a forested headwater catchment. All simulations reproduced discharge dynamics well, calculated a dominance of the baseflow component but missed macropore driven discharge peaks in the summer and slightly overestimated the discharge. A comparison of discharge and water balance results between daily and hourly time steps revealed considerable scaling issues of saturated conductivity values and in the model's interception module. Temporally and spatially highly resolved soil moisture measurements were used to calibrate residual saturations and porosities at daily time steps. Therefore, all model setups simulated the long-term temporal soil moisture dynamics well, but short-term soil moisture dynamics were poorly simulated because the simulation did not take into account the effect of macropore flow. The spatial soil moisture patterns of the topsoil were well reproduced except for certain parts in the western part of the catchment. A correlation analysis revealed that the influence of the topography was overestimated in the simulated soil moisture pattern. The spatial scale dependency of all aforementioned results was small due to independent calibration. The consideration of bedrock damped discharge peaks, increased low flow and slightly improved temporal soil moisture simulation.}, doi = {10.1016/j.jhydrol.2014.01.060}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Cornelissen, Diekkr{\"{u}}ger, Bogena - 2014 - Significance of scale and lower boundary condition in the 3D simulation of hydrological process.pdf:pdf}, keywords = {3D soil moisture simulation,Bedrock influence,Forested ecosystem,Headwater catchment,HydroGeoSphere,Scale effects}, publisher = {Elsevier}, }
@Article{Famiglietti1999, author = {Famiglietti, J. S. and Devereaux, J. A. and Laymon, C. A. and Tsegaye, T. and Houser, P. R. and Jackson, T. J. and Graham, S. T. and Rodell, M. and van Oevelen, P. J.}, journal = {Water Resources Research}, title = {{Ground-based investigation of soil moisture variability within remote sensing footprints During the Southern Great Plains 1997 (SGP97) Hydrology Experiment}}, year = {1999}, issn = {00431397}, month = {jun}, number = {6}, pages = {1839--1851}, volume = {35}, doi = {10.1029/1999WR900047}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Famiglietti et al. - 1999 - Ground-based investigation of soil moisture variability within remote sensing footprints During the South(2).pdf:pdf}, publisher = {Wiley-Blackwell}, } @misc{Beven1982, author = {Beven, K and Germann, P F}, booktitle = {Wat. Resour. Res.}, doi = {10.1029/WR018i005p01311}, file = {:C\(\backslash\):/Users/njadidoleslam/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Unknown - Unknown - Macropores{_}and{_}water{_}flow{_}in{_}soils.pdf.pdf:pdf}, isbn = {1944-7973}, issn = {00431397}, keywords = {macropores,solute transport,unsaturated/sat flo}, number = {5}, pages = {1311--1325}, pmid = {43}, title = {{Macropores and water flows in soils}}, volume = {18}, year = {1982} } @article{Orchard1983, author = {Orchard, Valerie A. and Cook, F. J.}, doi = {10.1016/0038-0717(83)90010-X}, isbn = {0038-0717}, issn = {00380717}, journal = {Soil Biology and Biochemistry}, number = {4}, pages = {447--453}, pmid = {17763719}, title = {{Relationship between soil respiration and soil moisture}}, volume = {15}, year = {1983} }
