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In-situ field monitoring networks generate vast quantities of continuous data can help to improve the design, management, operation and maintenance of Green Infrastructure (GI) systems. However, such actions require efficient and reliable quality assurance quality control (QAQC). In this paper, we develop a rule-based learning algorithm involving Dynamic Time Warping (DTW) to investigate the feasibility of detecting anomalous responses from soil moisture probes using data collected from a GI site in Milwaukee, WI. As an enhancement to traditional QAQC methods which rely on individual time steps, this method converts the continuous time series into event sequences from which response patterns can be detected. Association rules are developed on both environmental features and event features. The results suggest that this method could be used to identify abnormal change patterns as compared to intra-site historical observations. Though developed for soil moisture, this method could easily be extended to apply on other continuous environmental datasets. [ABSTRACT FROM AUTHOR]

Subsurface irrigation has been achieved by using ceramic emitters, pitchers, pots and ceramic tubes, which have gained a certain degree of interest in arid regions due to their efficient use of water. Research on the formation of wetting patterns around the ceramic emitter is essential for the design of irrigation system. In this study, numerical simulations were carried out to investigate the effects of emitter installation method, emitter buried depth, emitter structural parameters, irrigation doses and initial soil water content on the wetting patterns in clay loam with Hydrus-2D. Finally, two field application experiments were conducted to test the practicality and reliability of simulation results. The simulation results were in good agreement with the experimental data. Results showed, emitter installation method had the least effect on the wetting pattern. A 25 cm buried depth would be suit for irrigating vegetables, a 45 cm deep buried depth would suit for irrigating fruit trees. The structure parameters had a significant effect on cumulative fluxes and horizontal wetting front, the structural parameters (emitter length is 7.00 cm, emitter external diameter is 1.25 cm, and emitter inner diameter is 0.60 cm) would be a better fabricate parameters for ceramic emitter. Wetting front increased with increasing irrigation doses and initial water content. To prevent percolation, when the initial water content was high, it should be better to cut down the irrigation duration of ceramic emitter. The field results indicated that Hydrus-2D could be used to investigate the suitable parameters for ceramic emitter in subsurface irrigation systems and determine the suitable arrangement and operation mode of ceramic emitter. [ABSTRACT FROM AUTHOR]

Recent launch of space-borne systems to estimate surface soil moisture may expand the capability to map soil moisture deficit and drought with global coverage. In this study, we use Soil Moisture Active Passive (SMAP) soil moisture geophysical retrieval products from passive L-band radiometer to evaluate its applicability to forming agricultural drought indices. Agricultural drought is quantified using the Soil Water Deficit Index (SWDI) based on SMAP and soil properties (field capacity and available water content) information. The soil properties are computed using pedo-transfer function with soil characteristics derived from Harmonized World Soil Database. The SMAP soil moisture product needs to be rescaled to be compatible with the soil parameters derived from the in situ stations. In most locations, the rescaled SMAP information captured the dynamics of in situ soil moisture well and shows the expected lag between accumulations of precipitation and delayed increased in surface soil moisture. However, the SMAP soil moisture itself does not reveal the drought information. Therefore, the SMAP based SWDI (SMAP_SWDI) was computed to improve agriculture drought monitoring by using the latest soil moisture retrieval satellite technology. The formulation of SWDI does not depend on longer data and it will overcome the limited (short) length of SMAP data for agricultural drought studies. The SMAP_SWDI is further compared with in situ Atmospheric Water Deficit (AWD) Index. The comparison shows close agreement between SMAP_SWDI and AWD in drought monitoring over Contiguous United States (CONUS), especially in terms of drought characteristics. The SMAP_SWDI was used to construct drought maps for CONUS and compared with well-known drought indices, such as, AWD, Palmer Z-Index, sc-PDSI and SPEI. Overall the SMAP_SWDI is an effective agricultural drought indicator and it provides continuity and introduces new spatial mapping capability for drought monitoring. As an agricultural drought index, SMAP_SWDI has potential to capture short term moisture information similar to AWD and related drought indices. [ABSTRACT FROM AUTHOR]

A modern computer-based simulation tool ( WaterMan) in the form of a game for on-farm water management was developed for application in training events for farmers, students, and irrigators. The WaterMan game utilizes an interactive framework, thereby allowing the user to develop scenarios and test alternatives in a convenient, risk-free environment. It includes a comprehensive soil water and salt balance calculation algorithm. It also employs heuristic capabilities for modeling all of the important aspects of on-farm water management, and to provide quantitative performance evaluations and practical water management advice to the trainees. Random events (both favorable and unfavorable) and different strategic decisions are included in the game for more realism and to provide an appropriate level of challenge according to player performance. Thus, the ability to anticipate the player skill level, and to reply with random events appropriate to the anticipated level, is provided by the heuristic capabilities used in the software. These heuristic features were developed based on a combination of two artificial intelligence approaches: (1) a pattern recognition approach and (2) reinforcement learning based on a Markov decision processes approach, specifically the Q-learning method. These two approaches were combined in a new way to account for the difference in the effect of actions taken by the player and action taken by the system in the game world. The reward function for the Q-learning method was modified to reflect the suggested classification of the WaterMan game as what is referred to as a partially competitive and partially cooperative game. [ABSTRACT FROM AUTHOR]

The article discusses the potential impact of the North American Soil Moisture Database (NSMD) to in situ soil moisture observations. Topics discussed include the integration of NSMD for the data contributed from observation networks, the use of quality assurance and quality controls (QAQC) algorithm to users via web-based portal and data products such as volumetric soil water content.

The present study has developed the time series database surface soil moisture over India, for June, July and August months for the period of 20 years from 1991 to 2010, using data products generated under Climate Change Initiative Programme of European Space Agency. These three months represent the crop sowing period in the prime cropping season in the country and the soil moisture data during this period is highly useful to detect the drought conditions and assess the drought impact. The time series soil moisture data which is in 0.25 degree spatial resolution was analyzed to generate different indicators. Rainfall data of same spatial resolution for the same period, generated by India Meteorological Department was also procured and analyzed. Geospatial analysis of soil moisture and rainfall derived indicators was carried out to study (1) inter annual variability of soil moisture and rainfall, (2) soil moisture deviations from normal during prominent drought years, (3) soil moisture and rainfall correlations and (4) drought exposure based on soil moisture and rainfall variability. The study has successfully demonstrated the potential of these soil moisture time series data sets for generating regional drought surveillance information products, drought hazard mapping, drought exposure analysis and detection of drought sensitive areas in the crop planting period. [ABSTRACT FROM AUTHOR]

Evaluates the relationship between effect of hysteresis and use of computer simulation models on microbial activity discernment in soils. Exhibition of hysteresis in soil water content; Occurrence of 15 percent bias in simulated mineralization compared to mean annual mineralization by harvest; Influence of severe wetting and drying cycles on soil.

Studies a computer simulation which shows the mechanism of plant root influence on soil water conditions across time and soil depth parameters. Inverse proportionality of hydraulic properties with varied soil water content; Demonstration of the technique using field data for cotton; Comparison with other studies.