Rezaul Mahmood

Soil moisture: A central and unifying theme in physical geography

Soil moisture is a critical component of the earth system and plays an integrative role among the various subfields of physical geography. This paper highlights not just how soil moisture affects atmospheric, geomorphic, hydrologic, and biologic processes but that it lies at the intersection of these areas of scientific inquiry. Soil moisture impacts earth surface processes in such a way that it creates an obvious synergistic relationship among the various subfields of physical geography. The dispersive and cohesive properties of soil moisture also make it an important variable in regional and microclimatic analyses, landscape denudation and change through weathering, runoff generation and partitioning, mass wasting, and sediment transport. Thus, this paper serves as a call to use research in soil moisture as an integrative and unifying theme in physical geography.

Impacts of land use/land cover change on climate and future research priorities.

Several recommendations have been proposed for detecting land use and land cover change (LULCC) on the environment from, observed climatic records and to modeling to improve its understanding and its impacts on climate. Researchers need to detect LULCCs accurately at appropriate scales within a specified time period to better understand their impacts on climate and provide improved estimates of future climate. The US Climate Reference Network (USCRN) can be helpful in monitoring impacts of LULCC on near-surface atmospheric conditions, including temperature. The USCRN measures temperature, precipitation, solar radiation, and ground or skin temperature. It is recommended that the National Climatic Data Center (NCDC) and other climate monitoring agencies develop plans and seek funds to address any monitoring biases that are identified and for which detailed analyses have not been completed.

An Analysis of Simulated Long-Term Soil Moisture Data for Three Land Uses under Contrasting Hydroclimatic Conditions in the Northern Great Plains

Abstract Soil moisture (SM) plays an important role in land surface and atmosphere interactions. It modifies energy balance near the surface and the rate of water cycling between land and atmosphere. The lack of observed SM data prohibits understanding of SM variations at climate scales under varying land uses. However, with simulation models it is possible to develop a long-term SM dataset and study these issues. In this paper a water balance model is used to provide a quantitative assessment of SM climatologies for three land uses, namely, irrigated corn, rain-fed corn, and grass, grown under three hydroclimatic regimes in Nebraska. These regimes are stops along an east–west decreasing precipitation gradient of the Great Plains. The simulated SM climatologies are provided for the root zone as a whole and for the five layers of the soil profile to a depth of 1.2 m. As expected, the soil water content in the root zone of irrigated corn was higher than rain-fed corn or grass. The lowest levels of soil wate...

Increase in Near-Surface Atmospheric Moisture Content due to Land Use Changes: Evidence from the Observed Dewpoint Temperature Data

Abstract Land use change can significantly affect root zone soil moisture, surface energy balance, and near-surface atmospheric temperature and moisture content. During the second half of the twentieth century, portions of the North American Great Plains have experienced extensive introduction of irrigated agriculture. It is expected that land use change from natural grass to irrigated land use would significantly increase near-surface atmospheric moisture content. Modeling studies have already shown an enhanced rate of evapotranspiration from the irrigated areas. The present study analyzes observed dewpoint temperature (Td) to assess the affect of irrigated land use on near-surface atmospheric moisture content. This investigation provides a unique opportunity to use long-term (1982–2003) mesoscale Td data from the Automated Weather Data Network of the high plains. Long-term daily Td data from 6 nonirrigated and 11 irrigated locations have been analyzed. Daily time series were developed from the hourly da...

Investigating diurnal and seasonal climatic response to land use and land cover change over monsoon Asia with the Community Earth System Model

Land use and land cover change (LULCC) is primarily characterized as forest conversion to cropland for the development of agriculture. Previous climate modeling studies have demonstrated the LULCC impacts on mean climate and its long-term trends. This study investigates the diurnal and seasonal climatic response to LULCC in monsoon Asia through two numerical experiments with potential and current vegetation cover using the fully coupled Community Earth System Model. Results show that LULCC leads to a reduced diurnal temperature range due to the enhanced (reduced) diurnal cycle of the ground heat flux (sensible heat flux). Daily minimum surface air temperature (Tmin) exhibits a clear seasonality over India as it increases most in the premonsoon season and least during the summer monsoon season. Similarly, a strong anticyclonic anomaly is present at 850 hPa over India in spring and over eastern China in autumn, but weak changes in circulation appear in winter and summer. In addition, the LULCC results in significant changes in the variability of the 2 m air temperature, as characterized by an enhanced variability in India and a reduced variability in northern China to eastern Mongolia in autumn and winter. Possible land-atmosphere feedback loops involving surface albedo, soil moisture, evapotranspiration, atmospheric circulation, and precipitation are offered as biogeophysical mechanisms that are responsible for the region-specific LULCC-induced diurnal and seasonal response.

A Coupled MM5-NOAH Land Surface Model-based Assessment of Sensitivity of Planetary Boundary Layer Variables to Anomalous Soil Moisture Conditions

The sensitivity of the near-surface weather variables and small-scale convection to soil moisture for Western Kentucky was investigated with the aide of the MM5 Penn State/NCAR mesoscale atmospheric model for three different synoptic conditions in June 2006. The model was initialized with FNL reanalysis from NCEP containing soil moisture data calculated with the Noah land surface model. Dry and wet experiments were performed in order to find the influence of soil moisture specification on boundary layer atmospheric variables. Dry experiments showed less available atmospheric moisture (between 2 and 6 g kg-1) at near-surface levels during all synoptic events consistent with slightly deeper boundary layers, higher lifting condensation levels and a larger Bowen ratio. As expected, precipitation rates were generally smaller than those of the control simulation. However, during a moderately strong synoptic event in early June, the dry experiments displayed larger precipitation rates compared to the control experiment (up to 5 mm in 3 hr) as the soil volumetric fraction was decreased from 0.05 to 0.15 (m3 m-3) with respect to the control simulation. Precipitation rates in wet experiments were also modulated by characteristics of synoptic conditions. In early June, precipitation rates slightly were larger than the control run (from 0.2 mm 3 h-1 to 1.4 mm 3 h-1) while in the other periods precipitation was reduced significantly. Both dry and wet anomaly experiments experienced reduced precipitation for different reasons. It was found, lifting condensation level, CAPE and low Bowen ratio were not sensitive markers of changes in soil moisture. Equivalent potential temperature was a better indicator of precipitation changes among all experiments. The controlling factor in these responses was the soil moisture content forcing vertical velocities. Thermodynamic conditions such as local stability played a less substantial role in controlling the precipitation processes. It was found that the response of planetary boundary layer variables under a variety of soil moisture conditions can be modified due to degree of synoptic forcing. Weak-to-moderate forcing favored convection while strong synoptic forcing tended to suppress it under dry soil moisture conditions. Wetter soils did not produce a response in horizontal wind fields as large as under the drier soils.

Equilibrium Sampling Used to Monitor Malodors in a Swine Waste Lagoon

The concentrations of malodorous compounds in a 0.4-ha anaerobic lagoon that received waste from approximately 2000 sows were monitored during the late summer to late fall of 2006 to gain insight into the factors influencing their concentrations. Selected malodorous compounds were measured by the use of equilibrium samplers consisting of submersible stir plates and stir bar sorbtive sampling with polydimethylsiloxane-coated magnetic stir bars. During the same period, air and water temperatures, suspended solids, total organic carbon and nitrogen content, and wastewater pH were recorded. Concentrations of malodorous compounds were higher at the surface of the lagoon than at the middle or bottom of the lagoon. Skatole concentration, for instance, averaged 54, 24, and 38 microg L(-1) near the surface, in the middle, and at the lowest sampling depths, respectively. While the lagoon was being pumped down during field application of wastewater, concentrations of malodorous compounds fluctuated widely, increased 16-fold as compared with the sampling period before pumping, and continued to increase as fall progressed and temperatures cooled. Suspended solids, volatile suspended solids, and total organic carbon increased near the bottom of the lagoon during this same period. The increases in the concentrations of malodorous compounds in the wastewater during the fall could have been due to a combination of several factors. These factors include reduced degradation by lagoon bacteria, less wind stripping of volatile compounds from the lagoon surface due to lowering of the lagoon surface after crop application, and/or reduced evaporation of malodorous compounds due to falling temperatures.

Land use/land cover changes and regional climate over the Loess Plateau during 2001–2009. Part II: interrelationship from observations

Afforestation efforts in China resulted in significant changes in vegetation coverage over the Loess Plateau during 2001–2009. While regional climate conditions dominate the distribution of major vegetation types, human activities, primarily afforestation/reforestation and the resultant land use/land cover (LULC) changes (LULCC) and their impacts, are the focus of this study. A new attribution method was developed and applied to observed data for investigating the interrelationships between climate variation and LULCC. Regional climate (temperature and precipitation) changes are attributed to climate variation and LULCC; LULCC is attributed to climate variation and human activities. Climate attribution analysis indicated a larger contribution ratio (based on comparison of standard deviations of each contributing factor-induced climate changes and that of total change) from climate variation than from LULCC (0.95 from climate variation vs. 0.35 from LULCC) for variations in temperature. Impacts on precipitation indicated more spatial variations than those on temperature. The spatial variation of LULCC impacts on precipitation implied that human activities might have larger impacts on precipitation in the region’s arid north than in its humid south. Using both leaf area index (LAI) and areal coverage of each of the major land types, LULCC attribution analysis suggested that LULCC observed in the 2000s resulted primarily from human activities rather than climate variations (0.99 contribution ratio from human activities vs. 0.26 from climate variation).

Scale issues in soil moisture modelling: problems and prospects

Soil moisture storage is an important component of the hydrological cycle and plays a key role in land-surface-atmosphere interaction. The soil-moisture storage equation in this study considers precipitation as an input and soil moisture as a residual term for runoff and evapotranspiration. A number of models have been developed to estimate soil moisture storage and the components of the soil-moisture storage equation. A detailed discussion of the impli cation of the scale of application of these models reports that it is not possible to extrapolate processes and their estimates from the small to the large scale. It is also noted that physically based models for small-scale applications are sufficiently detailed to reproduce land-surface- atmosphere interactions. On the other hand, models for large-scale applications oversimplify the processes. Recently developed physically based models for large-scale applications can only be applied to limited uses because of data restrictions and the problems associated with land surface characterization. It is reported that remote sensing can play an important role in over coming the problems related to the unavailability of data and the land surface characterization of large-scale applications of these physically based models when estimating soil moisture storage.

Quality Control of Soil Water Data in Applied Climate Information System—Case Study in Nebraska

Soil moisture is a key state variable from both climate and hydrologic cycle assessment perspectives. Recently, automated measurements of soil moisture with sensors deployed at sites in a real-time monitoring network have provided valuable new data to monitor the soil water resource. However, to assure the quality of the data, quality control QC tools are needed. Earlier studies left little literature on the QC of soil water data as measurements were generally not part of a network that routinely collected measurements. This paper presents a systematic QC analysis and methodology to evaluate the performance of candidate QC techniques using a spatially- extensive soil water data set. The six tests included are based on the general behavior of soil moisture, the statistical characteristics of the measurements, the soil properties, and the precipitation measurements. The threshold, step change, and spatial regression test proved most effective in identifying data problems. The results demonstrate that these methods will lead to early identification of potential instrument failures and other disturbances to the soil water measurements.