Measurement and modeling of soil water regime in a lowland paddy field showing preferential transport

Paddy is commonly grown under flooded or submerged condition in which substantial amount of water is lost by different processes. Puddling is traditionally done to reduce water loss from lowland rice fields. Since the very step of puddling, rice root zone undergoes structural changes leading to the formation of a layered profile having a hydraulically less-conductive plow sole below the root zone. However, studies have shown that soil cracking and the presence of preferential flow paths in puddle fields defeat this purpose. Description of soil water regime in such a dynamic soil requires an in situ measurement method for soil hydraulic properties. A field experiment was conducted in twelve 30 m2 plots during the rainy seasons (June to October) of 2004 and 2005 to evaluate a suitable method for estimating soil hydraulic properties of lowland paddy soil. Results showed that piezometric (pressure) heads installed in different soil layers responded to the drying and wetting cycles typically followed in transplanted rice and are observed as a part of monsoon climate in eastern India. The Marquardt-Levenberg algorithm built in the HYDRUS-1D simulation environment was used to inversely estimate soil hydraulic parameters. Estimated parameters revealed larger hydraulic conductivity for the compacted plow sole than those published in literature, which may have resulted from alternate wetting and drying typically observed under monsoon climate and earthworm burrows observed in our experimental field. Results from simulation studies suggest that both the single- and dual-porosity models could simulate water flow considerably well in lowland paddy field although the latter described pressure head time series data slightly better in about 50% of simulations. Similar performance of the single- vs. dual-porosity model may have resulted from estimating a seasonally mean soil hydraulic properties which include the effect of both preferential flow and matrix flow as the specific soil and boundary conditions prevailed. While water may have preferentially transported through the macropores during the wetting cycles in a near-saturated soil, it would have dominantly moved through soil matrix during the drying cycles. This study shows that simple piezometers may be combined with a simulation model to estimate hydraulic properties of different soil layers in a lowland paddy field

Spatially distributed water-balance and meteorological data from the rain–snow transition, southern Sierra Nevada, California

We strategically placed spatially distributed sensors to provide representative measures of changes in snowpack and subsurface water storage, plus the fluxes affecting these stores, in a set of nested headwater catchments. The high temporal frequency and distributed coverage make the resulting data appropriate for process studies of snow accumulation and melt, infiltration, evapotranspiration, catchment water balance, (bio)geochemistry, and other critical-zone processes. We present 8 years of hourly snow-depth, soil-moisture, and soil-temperature data, as well as 14 years of quarter-hourly streamflow and meteorological data that detail water-balance processes at Providence Creek, the upper part of which is at the current 50&thinsp;% rain versus snow transition of the southern Sierra Nevada, California. Providence Creek is the long-term study cooperatively run by the Southern Sierra Critical Zone Observatory (SSCZO) and the USDA Forest Service Pacific Southwest Research Station's Kings River Experimental Watersheds (KREW). The 4.6&thinsp;km2 montane Providence Creek catchment spans the current lower rain–snow transition elevation of 1500–2100&thinsp;m. Two meteorological stations bracket the high and low elevations of the catchment, measuring air temperature, relative humidity, solar radiation, precipitation, wind speed and direction, and snow depth, and at the higher station, snow water equivalent. Paired flumes at three subcatchments and a V-notch weir at the integrating catchment measure quarter-hourly streamflow. Measurements of meteorological and streamflow data began in 2002. Between 2008 and 2010, 50 sensor nodes were added to measure distributed snow depth, air temperature, soil temperature, and soil moisture within the top 1&thinsp;m below the surface. These sensor nodes were installed to capture the lateral differences of aspect and canopy coverage. Data are available at hourly and daily intervals by water year (1 October–30 September) in nonproprietary formats from online data repositories. Data for the Southern Sierra Critical Zone Observatory distributed snow and soil datasets are at https://doi.org/10.6071/Z7WC73. Kings River Experimental Watersheds meteorological data are available from https://doi.org/10.2737/RDS-2018-0028 and stream-discharge data are available from https://doi.org/10.2737/RDS-2017-0037.</p

Introduction of flat ribbon cable (FRC) sensor for density measurement of road materials using time domain reflectometry (TDR)

Moisture content and density of unbound granular pavement materials are important properties for compaction control providing a great influence on pavement performance. Time domain reflectometry (TDR) usually uses rod probe sensors, which can provide pointwise readings of density. However, pointwise readings might not be representative enough for a complete road section. This paper introduces the application of flat ribbon cable (FRC) sensor, which can be extended up to 6 meter to measure moisture and density of road materials. Soil specific calibration is done in the laboratory considering the variation of moisture and density of materials where sensors of three different lengths are considered to enable the development of length normalized calibration. The electric parameter used to derive soil density is the voltage drop, which occurs after the passage of an electromagnetic wave along the sensor embedded in the soil. Soil moisture is related to the permittivity of the soil sample, which is obtained from the travel time of the TDR signal. Laboratory results indicate that calibration functions are independent of moisture and density. These soil specific calibration functions are useful in measuring long term pavement performance and managing rutting of roads

Hillslope Hydrology in Global Change Research and Earth System Modeling

Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope-scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid-level water, energy, and biogeochemical fluxes. In contrast to the one-dimensional (1-D), 2- to 3-m deep, and free-draining soil hydrology in most ESM land models, we hypothesize that 3-D, lateral ridge-to-valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions. Plain Language Summary Hillslopes are key landscape features that organize water availability on land. Valley bottoms are wetter than hilltops, and sun-facing slopes are warmer and drier than shaded ones. This hydrologic organization leads to systematic differences in soil and vegetation between valleys and hilltops, and between sunny and shady slopes. Although these patterns are fundamental to understanding the structures and functions of water and terrestrial ecosystems, they are too fine grained to be represented in global-scale Earth System Models. Here we bring together Critical Zone scientists who study the interplay of vegetation, the porous upper layer of the continental crust from vegetation to bedrock, and moisture dynamics deep into the weathered bedrock underlying hillslopes and Earth System Model scientists who develop global models, to ask: Do hillslope-scale processes matter to predicting global change? The answers will help scientists understand where and why hillslopes matter, and to better predict how terrestrial ecosystems, including societies, may affect and be affected by our rapidly changing planet.National Science Foundation [NSF-EAR-1528298, NSF-EAR-0753521]6 month embargo; published online: 27 February 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Hillslope Hydrology in Global Change Research and Earth System Modeling

Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid‐level water, energy, and biogeochemical fluxes. In contrast to the one‐dimensional (1‐D), 2‐ to 3‐mdeep, and free‐draining soil hydrology in most ESM land models, we hypothesize that 3‐D, lateral ridge‐to‐valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions

Adjusting Temperature and Salinity Effects on Single Capacitance Sensors

Several newly developed capacitance sensors have simplified real-time determination of soil water content. Previous work has shown that salinity and temperature can affect these sensors, but relatively little has been done to correct these effects. The objectives of this study were to evaluate the effect of media temperature and salinity on the apparent water content measured with a single capacitance sensor (SCS), and to mitigate this effect using a temperature dependent scaled voltage technique under laboratory conditions. A column study was conducted containing two media: pure deionized water and quartz sand under varying water contents (0.05 to 0.30 cm3 cm-3) and salinity (0 to 80 mmol L-1). Media temperature was varied between 5 and 45 °C using an incubator. The SCS probes and thermocouples were placed in the middle of the columns and were logged at an interval of 1 minute. There was strong negative correlation between sensor reading and temperature of deionized water with a rate of -0.779 mV °C-1. Rates of SCS apparent output were 0.454 and 0.535 mV °C-1 for air in heating and cooling cycles, respectively. A similar positive correlation with temperature was observed in sand at different water contents. The SCS probe was less sensitive to temperature as salinity and water content increased. Using a temperature-corrected voltage calibration model, the effect of temperature was reduced by 98%. An analytical model for salinity correction was able to minimize the error as low as ± 2% over the salinity level tested. © 2009 Soil Science Society of China

Temperature impacts on the water year 2014 drought in California

©2015. American Geophysical Union. California is experiencing one of the worst droughts on record. We use a hydrological model and risk assessment framework to understand the influence of temperature on the water year (WY) 2014 drought in California and examine the probability that this drought would have been less severe if temperatures resembled the historical climatology. Our results indicate that temperature played an important role in exacerbating the WY 2014 drought severity. We found that if WY 2014 temperatures resembled the 1916-2012 climatology, there would have been at least an 86% chance that winter snow water equivalent and spring-summer soil moisture and runoff deficits would have been less severe than the observed conditions. We also report that the temperature forecast skill in California for the important seasons of winter and spring is negligible, beyond a lead time of 1month, which we postulate might hinder skillful drought prediction in California

Sensitivity of Oregon Watersheds to Streamflow Changes Due to Climate Warming: A Geohydrological Approach

A key challenge for resource and landscape managers is to predict the consequences of climate warming on streamflows and water resources. Different approaches are being developed to forecast the direction, magnitude, and timing of future streamflow changes in specific landscapes. One approach that is being utilized in the Pacific Northwest involves coupling downscaled climate predictions to macroscale hydrologic models, such as the Variable Infiltration Capacity (VIC) model. VIC is typically parameterized and calibrated in selected watersheds, and then applied to a regional scale that includes larger population of uncalibrated watersheds. Summer streamflows are sensitive to both changes in the timing of snowpack accumulation and melt, and intrinsic, geologically-mediated differences in the efficiency of landscapes in transforming recharge (either as rain or snow) into discharge. Here we explore the importance of this effect by using geologically focused “bottom-up” approach to empirically characterize the sensitivity of late-summer streamflows to climate warming for a range of basins across Oregon. We define sensitivity as the slope of the relation between annual precipitation and summer streamflow, characterized as 7-day low flow and total summer flow. Drainage efficiency was defined in terms of the: 1) rate of recession (K) of the streamflow hydrograph; and 2) ratio of base flow to total flow (Base Flow Index or BFI). We compare our sensitivity results with those derived from VIC simulated streamflow. Using the bottom-up approach, we found that the both K and BFI are good predictors for streamflow sensitivity to climate change. Fast-draining basins (high K / low BFI) are much less sensitive to changes in annual precipitation, whereas slow-draining basins (low K / high BFI) are much more sensitive. For basins where VIC was calibrated, downscaled VIC simulations are similar to empirical data. Uncalibrated basins, however, do not show a clear relationship with drainage efficiency, meaning that VIC may under predict sensitivity of summer stramflows to climate change in uncalibrated groundwater-dominated watersheds. This implies that spatial heterogeneity in aquifer properties must be explicitly incorporated into parameterization and calibration schemes if the full range of hydrologic response to warming is to be captured across the landscape.Presented at The Oregon Water Conference, May 24-25, 2011, Corvallis, OR