Temporal Variability Of Soil Moisture Research Articles

微尺度下城市公园人造绿地土壤水分的时空分异格局及其驱动机制

PDF HTML阅读 XML下载 导出引用 引用提醒 微尺度下城市公园人造绿地土壤水分的时空分异格局及其驱动机制 DOI: 10.5846/stxb201807061479 作者: 作者单位: 中国科学院生态环境研究中心城市与区域生态国家重点实验室,中国科学院大学,中国科学院生态环境研究中心城市与区域生态国家重点实验室,中国科学院生态环境研究中心城市与区域生态国家重点实验室,中国科学院生态环境研究中心城市与区域生态国家重点实验室 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41571482，71734006）；国家重点研发计划重点专项（2016YFC0502804） Pattern and mechanism of microscale spatial-temporal variation in soil moisture at an artificial grassland in an urban park Author: Affiliation: State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences,,,,State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:水是生态系统的基本非生物组成要素，土壤水分对生态系统结构和功能有重要影响。微地形改造被证明能有效涵养水源、防止水土流失，并被广泛应用在生态恢复工程中。然而，在微尺度下人造生态系统土壤水分的时空分异格局及其驱动机制仍不明确。选择北京奥林匹克森林公园一处集合了4种不同地形的草地作为研究对象，对表层（0-10 cm）和深层（10-25 cm）土壤水分开展了长期的研究工作。研究结果表明，不同地形上土壤水分的季节变化特征没有显著差异，土壤温度是影响土壤水分季节变化的主要因素。在植被覆盖均匀的条件下，微地形对土壤表层水分的空间分布格局有显著影响，除洼地和冲沟两种特殊地形外，坡度决定的生态水文过程是主要的驱动机制；土壤深层水分没有明显的空间分布格局。研究结果说明在微尺度下，微地形通过影响土壤水分的空间分布格局，可能会对生态系统结构和功能产生潜在影响，应当在景观改造和生态恢复相关研究和工程应用中给予更多的关注。 Abstract:Water is the most basic element of ecosystem and is crucial to ecosystem structure and function. The transformation of microtopography has been widely used in ecological restoration to conserve soil water. However, the pattern and mechanisms of spatial-temporal variation in soil moisture at the micro-scale remain unclear. In this study, both topsoil (0-10 cm) and subsoil (10-25 cm) water content of four microtopographic types, which were located on an artificial grassland inside Beijing Olympic forest park, were monitored for one year. Only the topsoil water content was significantly affected by microtopography. Through eco-hydrological processes, slope gradient was an important impact factor for the spatial distribution of soil moisture. However, temporal variation in soil moisture showed no response to microtopography and was significantly affected by soil temperature. Therefore, further study is needed to reveal the potential effects of artificial microtopography on ecosystem structure and function, especially in the field of landscape transformation and ecological restoration. 参考文献 相似文献 引证文献

Monitoring of soil moisture in Long-Term Ecological Research (LTER) sites of Romanian Carpathians

Understanding soil moisture and its relationship with different climatic and soil characteristics is essential for better analysing the interactions between forest and soil water dynamics, allowing us to more precisely predict climatic changes. The present paper investigates the temporal variability of soil moisture in three different forest ecosystems (LTER – long term ecological research site) with the same soil type (Eutric Cambisol). Soil moisture was measured daily from 2011 to 2016 by using three sensors at three different depths (20, 40, 70 cm). We identified the interactions between soil properties, vegetation type, local climatic conditions and soil moisture. In order to establish the temporal variability of the soil moisture content, we have applied two procedures, namely the Fourier series and the neural network fitting. A high variability in time and depth for soil volumetric water content was identified. The highest soil moisture levels were recorded at higher depths (70 cm) for almost all surfaces, with the exception of the Fundata surface because of the occurrence of limestone. In the mountainous areas, with higher precipitation (Fundata and Predeal sites), volumetric soil water content was mainly influenced by soil physical characteristics. Soil moisture levels below the drought level were only recorded for the Stalpeni site from September to October 2012. There was a delay between the precipitation event and soil humidification of 0.4-0.8 time units (days). We also found a significant correlation between soil moisture and soil texture and a weak correlation with vegetation type. Temperature influenced soil moisture levels at almost all depths, while precipitation only had an impact when there was a delay of 1 or 2 days. Our results can serve as a scientific base in the monitoring and analysing of soil moisture against the background of a changing climate.

Disaggregating Soil Moisture to Finer Spatial Resolutions: A Comparison of Alternatives

AbstractThe spatial and temporal variability in soil moisture modulates runoff generation and the degree of land‐atmosphere coupling. Numerous statistical and modeling approaches have been implemented to characterize soil moisture spatial heterogeneity at fine spatial resolution using data from sparse observational networks or distributed model simulations. This characterization has been subsequently employed to translate coarse model simulations (of the order of a few hundred meters or kilometers) to finer spatial scales for a range of ensuing applications that rely on high‐resolution characterization of soil moisture. One common feature of these disaggregation methods is that the impact of soil moisture memory is ignored. This results in both spatial and temporal persistence being poorly simulated, leading to poorer specifications of cropping and irrigation plans. To overcome this shortcoming, we developed a hybrid disaggregation method that uses the first‐order autoregressive model (AR1) constructed from fine‐resolution (60 m) soil moisture simulations to disaggregate catchment mean soil moisture obtained from remote sensing or semidistributed model simulations. Soil moisture simulations from an integrated land surface‐groundwater model, ParFlow‐Common Land Model in Baldry subcatchment, Australia, are used as virtual observations. We examined the AR1 method performance against topographic wetness index‐based methods and those developed from temporal stability method. Results illustrate that the disaggregation schemes calibrated to a 10‐day fine‐scale model simulation perform better than the topographic‐based methods in approximating soil moisture distribution at a 60‐m resolution in the catchment. Furthermore, the AR1 model is the best model (Nash‐Sutcliffe efficiency [NSE] > 0.45) among various alternatives explored here. Applying the hybrid univariate AR1 model is promising for disaggregating semidistributed models' soil moisture simulations while significantly reducing the computational time.

AMSR2 Soil Moisture Downscaling Using Temperature and Vegetation Data

Soil moisture (SM) applications in terrestrial hydrology require higher spatial resolution soil moisture products than those provided by passive microwave remote sensing instruments (grid resolution of 9 km or larger). In this investigation, an innovative algorithm that uses visible/infrared remote sensing observations to downscale Advanced Microwave Scanning Radiometer 2 (AMSR2) coarse spatial resolution SM products was developed and implemented for use with data provided by the Advanced Microwave Scanning Radiometer 2 (AMSR2). The method is based on using the Normalized Difference Vegetation Index (NDVI) modulated relationships between day/night SM and temperature change at corresponding times. Land surface model output variables from the North America Land Data Assimilation System (NLDAS), remote sensing data from the Moderate-Resolution Imaging Spectroradiometer (MODIS), and Advanced Very High Resolution Radiometer (AVHRR) were used in this methodology. The functional relationships developed using NLDAS data at a grid resolution of 12.5 km were applied to downscale AMSR2 JAXA (Japan Aerospace Exploration Agency) SM product (25 km) using MODIS land surface temperature (LST) and NDVI observations (1 km) to produce the 1 km SM estimates. The downscaled SM estimates were validated by comparing them with ISMN (International Soil Moisture Network) in situ SM in the Black Bear–Red Rock watershed, central Oklahoma between 2015–2017. The overall statistical variables of the downscaled AMSR2 SM validation R2, slope, RMSE and bias, demonstrate good accuracy. The downscaled SM better characterized the spatial and temporal variability of SM at watershed scales than the original SM product.

Spatial and temporal variability of soil moisture in relation with topographic and meteorological factors in south of Ardabil Province, Iran

This research has been tried to evaluate the spatial and temporal variability of surface soil moisture (SM) in a semi-arid and cold region of Ardabil Province in Iran with an area of about 10,000km2. The used SM data is the SMAP Enhanced L2 Radiometer Half-Orbit 9km Soil Moisture, provided by NASA. The study area was subdivided into 120 locations consisting 10 × 12 grids, matching with the pixels of the SMAP images. In order to evaluate the spatial variations of SM, the relation of mean SM with coefficient of variation and standard deviation has been evaluated and, then, the representative location for mean SM of the area has been identified using the index of temporal stability. Moreover, the effect of topographic factors (elevation, slope, and aspect) on spatial variations of SM, and the effect of meteorological factors (rainfall, sunshine hours, temperature, relative humidity, wind speed, and number of dry days) on temporal variations of SM have been investigated. The relation of mean SM with the coefficient of variation and standard deviation represented an exponentially negative and upper convex shape, respectively. The SM content of the representative location had a correlation with the mean SM of the area with the coefficient of determination value of 0.91. Of the three topographic factors, only the slope factor, and of the meteorological factors all of them except the wind speed have showed a significant relationship with SM spatial and temporal variations respectively.

Spatial and temporal variability of soil moisture based on multifractal analysis

Based on the experimental data collected from 2002 to 2010 in Jilin province, we performed multifractal analysis to investigate the spatial variability of soil moisture during 9 years from 2002 to 2010 and about 60 days from April 21 to June 21 in 2010, and analyzed the relationship between soil moisture and precipitation. The results showed that the soil moisture was multifractal. It was intermediate variability in the soil sample. From 2002 to 2010, the spatial variation of soil moisture was charactered by long distance in 2004, 2006, and 2009 and short distance in 2002, 2003, and 2008. The spatial variation of soil moisture was charactered by long distance from April 21 to May 11 and late June. It was charactered by short distance from May 11 to June 21. From April 11 to July 1, 2010, the spatial variation of soil moisture was mainly affected by the spatial variation of precipitation. From 2002 to 2010, the spatial variation of soil moisture was mainly affected by precipitation in 2006, 2009, and 2010. The spatial variation of precipitation had little effect on soil moisture during 2002 to 2005 and 2007 to 2008. This study analyzed the multifractal characteristic of soil moisture from the perspective of water resources divisions, which can provide references for soil water resources evaluation and water resources allocation.

Detecting Trends in Wetland Extent from MODIS Derived Soil Moisture Estimates

A soil wetness index for optical satellite images, the Transformed Wetness Index (TWI) is defined and evaluated against ground sampled soil moisture. Conceptually, TWI is formulated as a non-linear normalized difference index from orthogonalized vectors representing soil and water conditions, with the vegetation signal removed. Compared to 745 ground sites with in situ measured soil moisture, TWI has a globally estimated Random Mean Square Error of 14.0 (v/v expressed as percentage), which reduces to 8.5 for unbiased data. The temporal variation in soil moisture is significantly captured at 4 out of 10 stations, but also fails for 2 to 3 out of 10 stations. TWI is biased by different soil mineral compositions, dense vegetation and shadows, with the latter two most likely also causing the failure of TWI to capture soil moisture dynamics. Compared to soil moisture products from microwave brightness temperature data, TWI performs slightly worse, but has the advantages of not requiring ancillary data, higher spatial resolution and a relatively simple application. TWI has been used for wetland and peatland mapping in previously published studies but is presented in detail in this article, and then applied for detecting changes in soil moisture for selected tropical regions between 2001 and 2016. Sites with significant changes are compared to a published map of global tropical wetlands and peatlands.

Soil moisture decline following the plantation of Robinia pseudoacacia forests: Evidence from the Loess Plateau

Abstract Soil moisture is the foundation of ecosystem sustainability in arid and semi-arid regions, and the spatial–temporal details of soil moisture dynamics of afforested areas can benefit for land use management in water-shortage regions such as the Loess Plateau of China. In this study, spatial–temporal variations in soil moisture under Robinia pseudoacacia plantations on the Loess Plateau were analyzed. A total of 147 observations of soil moisture content (SMC) data to a depth of 500 cm soil profile were collected in 23 counties via field transect surveys and analyses of published literature. The results suggested that (1) the depth-averaged SMC was generally lower under forest sites than under cropland, both in the shallow layers and in the deep profiles. This finding implied that, compared with the native vegetation, the introduced R. pseudoacacia plantations caused intense reductions in soil moisture. (2) SMC was positively correlated with climatic factors (mean annual precipitation (MAP), mean annual temperature (MAT), and the Palmer drought severity index (PDSI)), indicating that the SMC under R. pseudoacacia plantations was highly consistent with the hydrothermal conditions at the regional scale. (3) The decreasing amplitude of SMC was linearly related to the increasing number of restoration years, especially in the areas below the 500–550 mm precipitation threshold. This finding showed that the restoration ageing sequence was an influential factor that affected the regional SMC variation in R. pseudoacacia plantations on the Loess Plateau. Our results suggest that afforestation activities should be avoided if the local total precipitation is insufficient for replenishing the soil moisture and that local tree species with a lower demand for water resources should be considered a top priority for further afforestation of the Loess Plateau.

Determining hydrological regimes in an agriculturally used tropical inland valley wetland in Central Uganda using soil moisture, groundwater, and digital elevation data

AbstractInadequate knowledge exists on the distribution of soil moisture and shallow groundwater in intensively cultivated inland valley wetlands in tropical environments, which are required for determining the hydrological regime. This study investigated the spatial and temporal variability of soil moisture along 4 hydrological positions segmented as riparian zone, valley bottom, fringe, and valley slope in an agriculturally used inland valley wetland in Central Uganda. The determined hydrological regimes of the defined hydrological positions are based on soil moisture deficit calculated from the depth to the groundwater table. For that, the accuracy and reliability of satellite‐derived surface models, SRTM‐30m and TanDEM‐X‐12m, for mapping microscale topography and hydrological regimes are evaluated against a 5‐m digital elevation model (DEM) derived from field measurements. Soil moisture and depth to groundwater table were measured using frequency domain reflectometry sensors and piezometers installed along the hydrological positions, respectively. Results showed that spatial and temporal variability in soil moisture increased significantly (p < .05) towards the riparian zone; however, no significant difference was observed between the valley bottom and riparian zone. The distribution of soil hydrological regimes, saturated, near‐saturated, and nonsaturated regimes does not correlate with the hydrological positions. This is due to high spatial and temporal variability in depth to groundwater and soil moisture content across the valley. Precipitation strongly controlled the temporal variability, whereas microscale topography, soil properties, distance from the stream, anthropogenic factors, and land use controlled the spatial variability in the inland valley. TanDEM‐X DEM reasonably mapped the microscale topography and thus soil hydrological regimes relative to the Shuttle Radar Topography Mission DEM. The findings of the study contribute to improved understanding of the distribution of hydrological regimes in an inland valley wetland, which is required for a better agricultural water management planning.

Examining the Spatial and Temporal Variability of Soil Moisture in Kentucky Using Remote Sensing Data

Examining the Spatial and Temporal Variability of Soil Moisture in Kentucky Using Remote Sensing Data

Spatial and temporal distribution of soil moisture using remote sensing techniques

The determination of soil moisture distribution is complex and timely, making it unable to describe the behavior of its spatial and temporal distribution on a regional scale. The objective of this study was to estimate and evaluate the spatial and temporal variability of soil moisture by means of the instantaneous evaporative fraction in the semi-arid region using remote sensing data. Three images of the Landsat 5 sensor satellite TM were used on September 21, 2008, June 20, 2009 and August 29, 2011, covering the area of study: Iguatu, Brazilian semiarid. These images were processed from the ERDAS imagine 9.1 software, where the radiometric calibration and the conversion to radiance and reflectance were performed through complementary surface data using the SEBAL algorithm. The thematic maps of the energy balance biophysical parameters: instantaneous evaporative fraction (FE) and the degree of soil moisture saturation (θ / θsat) were processed by ArcGis® 10.2.2 software. The descriptive statistics was used to determine the differences of FE and θ / θsat in relation to the anthropological actions and the local climate of the region. Therefore, the monitoring of these biophysical parameters, especially the degree of soil moisture saturation, showed to be an effective part of the energy balance, configuring before them the power to make decisions regarding environmental aspects. The estimation of the spatial pattern of the degree of soil moisture saturation presented consistent values for the different uses and occupations of the soil, showing a great relation with the values of the evaporative fraction in all the images studied.

A potential predictor of multi-season droughts in Southwest China: soil moisture and its memory

During the last decade, several high intensity and long duration droughts happened in Southwest China (SWC) and resulted in tremendous socioeconomic losses. Meanwhile, it is well known that soil moisture (SM) plays a key role in land–atmosphere interaction and weather/climate prediction and is a direct drought index. Thus, a general analysis of SM is beneficial to drought research and prediction over this region. Based on the SM data of Global Land Data Assimilation System V2.0, we examined the temporal variations in SM in SWC during 1961–2012. Results show that significant soil drying trend happened in autumn accompanied by an evident abrupt change in 1991. Moreover, SM exhibits a strong and season-dependent persistence. Particularly, the autumn SM anomaly shows the strongest memory that can be sustained to the next spring. Along with the decadal shift of SM, the memory time of autumn SM can extend from 3 months before 1991 to 6 months in recent years. We further used the Standardized Precipitation Evapotranspiration Index (SPEI) at multiple time scales to identify the droughts in different seasons over SWC, and the inter-annual change patterns of autumn SM and SPEIs are generally in agreement with each other, which confirms that SM is suitable for indicating the droughts. Our results suggest that the autumn SM can be a potential predictor of persistent droughts over SWC, especially for those multi-season persistent drought events started in autumn.

Temporal variability in soil moisture after thinning in semi-arid Picea crassifolia plantations in northwestern China

Soil moisture controls the functioning of semi-arid ecosystems. The response of soil moisture to forest stand thinning determines planting density and sustainability of forest development. However, consequences of stand thinning are poorly known in semi-arid ecosystems of the Qilian Mountains of China. We investigated long-term effects of three thinning intensities in Picea crassifolia plantations on soil hydrological responses and soil moisture dynamics at 10, 20, 40, 60, and 80cm depths, and compared them to those of a natural Picea crassifolia forest.Results revealed that soil hydrological response may be temporarily modified by thinning according to changes in canopy structure, precipitation properties, and antecedent soil moisture conditions. Soil moisture in natural forest rapidly infiltrated into deep soil, which greatly improved the efficiency of precipitation use. Thinning significantly increased the capacity for soil infiltration, and moderate thinning intensity may be conducive to deep soil-water recharge. Soil moisture content changed drastically after thinning, with a significant decrease near-surface (10cm), and a significant increase in sub-surface (60 and 80cm) soil. High planting density was the main cause of severe soil moisture deficits in the long-term, but it could be mitigated by 20–40% thinning (∼3139 trees ha−1). Changes in precipitation patterns that include larger but less frequent rainfall events during the growing season will benefit the growth of vegetation planted at high densities in this semi-arid region.

Soil moisture in forage cactus plantations with improvement practices for their resilience

ABSTRACT The present study evaluated soil moisture (θ) in forage cactus plantations under resilience practices such as irrigation, mulching and intercropping with sorghum. The experiment was arranged in a randomized block design with five water availability conditions (0, 8.75, 17.5, 26.25 and 35% of the reference evapotranspiration), and three planting systems: forage cactus exclusive system (PE), forage cactus with mulch (PC) and intercropping between forage cactus and sorghum (PS). Water content was measured until a depth of 0.60 m. Meteorological data were recorded between June 2012 and June 2013. Water content was not affected by different resilience practices and the variation coefficient was low to medium (4.0 to 22.1%). The temporal variation of soil moisture was more affected by the changes in rainfall, while the physical properties (soil density, porosity and grain size) were decisive in the vertical variation. It was concluded that periods with rainfall events favor the alternation of practices to improve forage cactus resilience (irrigation, mulch and intercropping).

Evaluation of SMAP, SMOS, and AMSR2 soil moisture retrievals against observations from two networks on the Tibetan Plateau

AbstractTwo soil moisture and temperature monitoring networks were established in the Tibetan Plateau (TP) during recent years. One is located in a semihumid area (Naqu) of central TP and consists of 56 soil moisture and temperature measurement (SMTM) stations, the other is located in a semiarid area (Pali) of southern TP and consists of 21 SMTM stations. In this study, the station data are used to evaluate soil moisture retrievals from three microwave satellites, i.e., the Soil Moisture Active Passive (SMAP) of NASA, the Soil Moisture and Ocean Salinity (SMOS) of European Space Agency, and the Advanced Microwave Scanning Radiometer 2 (AMSR2) of Japan Aerospace Exploration Agency. It is found that the SMAP retrievals tend to underestimate soil moisture in the two TP networks, mainly due to the negative biases in the effective soil temperature that is derived from a climate model. However, the SMAP product well captures the amplitude and temporal variation of the soil moisture. The SMOS product performs well in Naqu network with acceptable error metrics but fails to capture the temporal variation of soil moisture in Pali network. The AMSR2 products evidently exaggerate the temporal variation of soil moisture in Naqu network but dampen it in Pali network, suggesting its retrieval algorithm needs further improvements for the TP.

Soil moisture retrieval from AMSR-E and ASCAT microwave observation synergy. Part 2: Product evaluation

A neural network (NN) soil moisture retrieval product computed from the synergy of AMSR-E brightness temperature and ASCAT backscatter observations is evaluated against in situ soil moisture observations from the International Soil Moisture Network (ISMN). The skill of the NN retrieval is compared to that of the ESA-CCI soil moisture retrieval as well as modeled soil moisture fields from ERA-interim/land. The NN retrieval is able to capture the observed soil moisture temporal variations with a station-average correlation and anomaly correlation of 0.45 and 0.35, respectively. For most ground stations the model obtained a higher temporal correlation skill, with average correlation and anomaly correlation values of 0.53 and 0.46, respectively. For stations in data-sparse regions, the NN retrieval showed a slightly better performance than the model, illustrating the potential of soil moisture retrievals to inform models in data-sparse areas. A time series analysis further showed that the retrieval is well able to capture soil moisture variability outside of active precipitation phases, such as the soil moisture behavior during the dry down phase. Compared to the ESA-CCI retrieval, the NN methodology obtained higher correlations, as a result of its ability to use the complementary information provided by the active and passive microwave sensors. A global evaluation of the retrieval errors through a triple collocation analysis with SMOS and GLDAS soil moisture estimates showed that the errors are high in energy limited regions, where the NN retrieval appears to be lacking input information. In the data-sparse regions of Africa and South America, the triple collocation analysis confirmed the higher skill of the NN retrieval compared to the model.

Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper‐resolution model

AbstractAccurate global mapping of soil moisture is the goal of the Soil Moisture Active Passive (SMAP) mission, which is expected to improve the estimation of water, energy, and carbon exchanges between the land and the atmosphere. Like other satellite products, the SMAP soil moisture retrievals need to be validated, with the validation relying heavily on in situ measurements. However, a one‐to‐one comparison is ill advised due to the spatial mismatch of the large SMAP footprint (∼40 km) and the point scale in situ measurements. This study uses a recently developed hyper‐resolution land surface model—HydroBlocks—as a tool to upscale in situ soil moisture measurements for the SMAPVEX15 (SMAP Validation Experiment 2015) field campaign during 2–18 August 2015. Calibrated against in situ observation, HydroBlocks shows a satisfactory Kling‐Gupta efficiency (KGE) of 0.817 and RMSE of 0.019 m3/m3 for the calibration period. These results indicate that HydroBlocks can be used to upscale in situ measurements for this site. Different from previous studies, here in situ measurements are upscaled using a land surface model without bias correction. The upscaled soil moisture is then used to evaluate SMAP (passive) soil moisture products. The comparison of the upscaled network to SMAP shows that the retrievals are generally able to capture the areal‐averaged soil moisture temporal variations. However, SMAP appears to be oversensitive to summer precipitation. We expect these findings can be used to improve the SMAP soil moisture product and thus facilitate its usage in studying the water, energy, and carbon cycles.

Soil Moisture Variation in a Farmed Dry-Hot Valley Catchment Evaluated by a Redundancy Analysis Approach

Farmed catchments have greater temporal and spatial heterogeneity of soil moisture than natural catchments. Increased knowledge about the variation of soil moisture in farmed catchments has important implications for the adoption of appropriate tillage measures for agriculture. The purpose of this study was to determine the spatial and temporal variability of soil moisture as controlled by the environment on a farmed catchment in a typical dry-hot valley (DHV) by integrating geostatistical and redundancy analysis (RDA). We monitored soil moisture in topsoil (0–20 cm) and subsoil (20–40 cm) layers at 51 points on eight occasions from July 2012 to March 2014, and determined the environmental factors of soil particle-size distribution, soil organic matter, slope aspect, slope gradient, elevation, and a topographic wetness index (WI) modified for semiarid conditions at each point. The results showed that, under the influence of high evaporation, soil moisture in the topsoil was significantly lower than that of subsoil in the DHV. In this study, we observed a strong temporal variation of soil moisture, which was influenced by the seasonal variation of crop cover and lagged behind that of rainfall. Relatively high soil moisture levels were found on the watershed divide and hillside sites of the catchment, and lower on the valleyside sites. Different from other studies, RDA analysis indicated that the WI was not correlated with soil moisture in the DHV; instead, clay and sand levels were the dominant control factor of soil moisture in the farmed DHV. We proposed that soil erosion in the DHV could lead to such increases of sand and decreases of clay content, thus influencing soil moisture content. Soil and water conservation measures will be especially important for valleyside sites with steep slopes.

English

Increasing trend in the frequency of natural events like floods and drought, etc. due to increasing urbanisation has led to degradation of the ecosystems. A major flood in year 1981 in Jaipur district resulted into huge erosion of the top fertile soil and leaving the land unproductive for agriculture production. The present study was carried in Jaipur district of Rajasthan state to measure physical characteristics of the soil samples from different districts of Jaipur. Soils samples were taken at 5 and 15 cm below the top surface and have taken 3 samples per site in each month. The soil physical parameters like sieve analysis, dry density, liquid limit, specific gravity and moisture content were analysed by standard techniques for different months in a year. Analysed results revels that, land cover having different characteristics has an impact on the temporal variability of soil moisture and other physical variables. The result of this will help to understand the variation of physical properties and thus to better planning to work in agricultural field. Further to say that, findings of the study can be used for altered case studies, concentrating on the soil variability effects for geotechnical issues. Key words: Flood, physico-chemical, water content, specific gravity, geotechnical.

Uncertainty assessment of a dominant-process catchment model of dissolved phosphorus transfer

Abstract. We developed a parsimonious topography-based hydrologic model coupled with a soil biogeochemistry sub-model in order to improve understanding and prediction of soluble reactive phosphorus (SRP) transfer in agricultural headwater catchments. The model structure aims to capture the dominant hydrological and biogeochemical processes identified from multiscale observations in a research catchment (Kervidy–Naizin, 5 km2). Groundwater fluctuations, responsible for the connection of soil SRP production zones to the stream, were simulated with a fully distributed hydrologic model at 20 m resolution. The spatial variability of the soil phosphorus content and the temporal variability of soil moisture and temperature, which had previously been identified as key controlling factors of SRP solubilization in soils, were included as part of an empirical soil biogeochemistry sub-model. The modelling approach included an analysis of the information contained in the calibration data and propagation of uncertainty in model predictions using a generalized likelihood uncertainty estimation (GLUE) "limits of acceptability" framework. Overall, the model appeared to perform well given the uncertainty in the observational data, with a Nash–Sutcliffe efficiency on daily SRP loads between 0.1 and 0.8 for acceptable models. The role of hydrological connectivity via groundwater fluctuation and the role of increased SRP solubilization following dry/hot periods were captured well. We conclude that in the absence of near-continuous monitoring, the amount of information contained in the data is limited; hence, parsimonious models are more relevant than highly parameterized models. An analysis of uncertainty in the data is recommended for model calibration in order to provide reliable predictions.