An overview of hydrometeorological datasets from a small agricultural catchment (Nučice) in the Czech Republic

We introduce the freely available web-based Water in an Agricultural Landscape—NUčice Database (WALNUD) dataset that includes both hydrological and meteorological records at the Nučice experimental catchment (0.53 km²), which is representative of an intensively farmed landscape in the Czech Republic. The Nučice experimental catchment was established in 2011 for the observation of rainfall–runoff processes, soil erosion processes, and water balance of a cultivated landscape. The average altitude is 401 m a.s.l., the mean land slope is 3.9%, and the climate is humid continental (mean annual temperature 7.9°C, annual precipitation 630 mm). The catchment is drained by an artificially straightened stream and consists of three fields covering over 95% of the area which are managed by two different farmers. The typical crops are winter wheat, rapeseed, and alfalfa. The installed equipment includes a standard meteorological station, several rain gauges distributed across the basin, and a flume with an H-type facing that is used to monitor stream discharge, water turbidity, and basic water quality indicators. Additionally, the groundwater level and soil water content at various depths near the stream are recorded. Recently, large-scale soil moisture monitoring efforts have been introduced with the installation of two cosmic-ray neutron sensors for soil moisture monitoring. The datasets consist of observed variables (e.g. measured precipitation, air temperature, stream discharge, and soil moisture) and are available online for public use. The cross-seasonal, open access datasets at this small-scale agricultural catchment will benefit not only hydrologists but also local farmers.     

Quantifying terrain controls on runoff retention and routing in the Northern Prairies

The role of hummocky terrain in governing runoff routing and focussing groundwater recharge in the Northern Prairies of North America is widely recognised. However, most hydrological studies in the region have not effectively utilised information on the surficial geology and associated landforms in large-scale hydrological characterization. The present study uses an automated digital elevation model (DEM) analysis of a 6500-km² area in the Northern Prairies to quantify hydrologically relevant terrain parameters for the common types of terrains in the prairies with different surficial deposits widespread in the prairies, namely, moraines and glaciolacustrine deposits. Runoff retention (and storage) capacity within depressions varies greatly between different surficial deposits and is comparable in magnitude with a typical amount of seasonal snowmelt runoff generation. The terrain constraint on potential runoff retention varies from a few millimetres in areas classified as moraine to tens of millimetres in areas classified as stagnant ice moraine deposits. Fluted moraine and glaciolacustrine deposits have intermediate storage capacity values. The study also identified the probability density function describing a number of immediate upstream neighbours for each depression in a fill-and-spill network. A relationship between depression parameters and surficial deposits, as well as identified depression network structure, allows parametrisation of hydrologic models outside of the high-resolution DEM coverage, which can still account for terrain variation in the Prairies.     

Effects of antecedent moisture and macroporosity on infiltration and water flow in frozen soil

Infiltration into frozen soil plays an important role in soil freeze–thaw and snowmelt-driven hydrological processes. To better understand the complex thermal energy and water transport mechanisms involved, the influence of antecedent moisture content and macroporosity on infiltration into frozen soil was investigated. Ponded infiltration experiments on frozen macroporous and non-macroporous soil columns revealed that dry macroporous soil produced infiltration rates reaching 10³ to 10⁴ mm day⁻¹, two to three orders of magnitude larger than dry non-macroporous soil. Results suggest that rapid infiltration and drainage were a result of preferential flow through initially air-filled macropores. Using recorded flow rates and measured macropore characteristics, calculations indicated that a combination of both saturated flow and unsaturated film flow likely occurred within macropores. Under wet conditions, regardless of the presence of macropores, infiltration was restricted by the slow thawing rate of pore ice, producing infiltration rates of 2.8 to 5.0 mm day⁻¹. Reduced preferential flow under wet conditions was attributed to a combination of soil swelling, due to smectite-rich clay (that reduced macropore volume), and pore ice blockage within macropores. In comparison, dry soil column experiments demonstrated that macropores provided conduits for water and thermal energy to bypass the frozen matrix during infiltration, reducing thaw rates compared with non-macroporous soils. Overall, results showed the dominant control of antecedent moisture content on the initiation, timing, and magnitude of infiltration and flow in frozen macroporous soils, as well as the important role of macropore connectivity. The study provides an important data set that can aid the development of hydrological models that consider the interacting effects of soil freeze–thaw and preferential flow on snowmelt partitioning in cold regions.     

Rainstorm-generated sediment yield model based on soil moisture proxies (SMP)

This study develops improved Soil Moisture Proxies (SMP) based suspended sediment yield (SMPSY) models corresponding to three antecedent moisture conditions (AMCs) (i.e., AMC-I-AMC-III) by coupling the improved initial abstraction (I_a-λ) model, the SMA procedure and the SMP concept for modelling the rainfall generated suspended sediment yield. The SMPSY models specifically incorporate a watershed storage index (S) model to accentuate the transformation from storm to storm and to avoid the sudden jumps in sediment yield computation. The workability of the SMPSY models is tested using a large dataset of rainfall and sediment yield (98 storm events) from twelve small watersheds and a comparison has been made with the existing MSY model. The goodness-of-fit (GOF) statistics is evaluated in terms of the Nash Sutcliffe efficiency (NSE), and error indices, i.e., root mean square error (RMSE), normalized root mean square error (nRMSE), standard error (SE), mean absolute error (MAE), and RMSE-observations standard deviation ratio (RSR). The NSE values vary from 74.31% to 96.57% and from 75.21% to 91.78%, respectively for the SPMSY and MSY model. The NSE statistics indicate that the SMPSY model has lower uncertainty in simulating sediment yield as compared to the MSY model. The error indices are lower for the SMPSY model than the MSY model for most of the watersheds. These results show that the SMPSY model has less uncertainty and performs better than the MSY model. A sensitivity analysis of the SMPSY model shows that the parameter β is most sensitive followed by parameter S, α and A. Overall, the results show that the characterization of soil moisture variability in terms of SMPs and incorporation of improved delivery ratio and runoff coefficient relationship improves the simulation of the erosion and sediment yield generation process.     

基于Sentinel-1和Sentinel-2协同反演干旱区地表土壤水分--以格尔木河中下游为例

摘要：土壤水分是全球水循环的重要组成成分,对研究土壤水分的空间分布、农作物长势和产量 、气候变化、水资源时空分布等有着重要意义 。本文利用Sentinel（哨兵）系列主动微波雷达卫星SAR（Sentinel-1）结合光学卫星（Sentinel-2）对格尔木中下游低矮植被覆盖下的地表土壤水分进行反演研究, 探讨不同极化组合方式和水云模型前后的土壤水分含量反演方法的适用性。结果表明：其中VV (VV Polarization) 极化对比VH (VH Polarization) 极化更加适用该区域,VV极化结合归一化水指数 (NDWI）反演地表土壤水分精度达到42.6%,拟合精度最高,VH极化仅为22.6%;利用水云模型去除植被覆盖后对地表土壤水分的反演精度有所提升,其中,VV极化精度提高约3.5%,VH极化提高1.5%;Sentinel系列卫星影像对于干旱区的土壤水分的反演具有较好的适用性。本文旨在探索一种适用于该研究区乃至柴达木盆地土壤水分实现大面积实时监测的可靠依据和手段。     

基于地面三维激光扫描强度数据的潮滩表层含水量估算

大面积潮滩表层含水量的测定是潮滩研究中的难题,传统的测量方法难以同时满足高效和精度的要求。地面三维激光扫描技术凭借其高精度、高分辨率以及主动性强等优点,已经高效运用在潮滩地形研究中。但是,对潮滩含水量进行有效分析,仅利用点云的空间几何信息是不够的,还需要对点云的强度数据进行挖掘。地面激光扫描仪提供了包含目标表面光谱反射特性的点云强度数据,利用强度数据可以有效地进行目标表面特性提取。本文提出了一种新的长距离地面激光扫描仪强度数据改正方法,对入射角和距离效应进行有效改正。利用Riegl VZ-4000长距离地面激光扫描仪建立室内含水量模型并对上海市崇明岛一处潮滩进行测试分析,同时收集26个潮滩沉积物样品并利用传统干湿称重法进行含水量验证计算。结果表明：相比于传统技术,利用改正后的激光强度值估算大面积潮滩沉积物表层含水量是一种精确和高效的方法。改正后的激光强度值与潮滩表层含水量存在幂函数关系,相关系数为0.961,估算精度为91.94%。     

Contrasting Regional Responses of Indian Summer Monsoon Rainfall to Exhausted Spring and Concurrently Emerging Summer El Ni?o Events

The inverse relationship between the warm phase of the El Ni?o Southern Oscillation(ENSO) and the Indian Summer Monsoon Rainfall(ISMR) is well established. Yet, some El Ni?o events that occur in the early months of the year(boreal spring) transform into a neutral phase before the start of summer, whereas others begin in the boreal summer and persist in a positive phase throughout the summer monsoon season. This study investigates the distinct influences of an exhausted spring El Ni?o(springtime)...     

Circulation Patterns Linked to the Positive Sub-Tropical Indian Ocean Dipole

The positive phase of the subtropical Indian Ocean dipole(SIOD) is one of the climatic modes in the subtropical southern Indian Ocean that influences the austral summer inter-annual rainfall variability in parts of southern Africa. This paper examines austral summer rain-bearing circulation types(CTs) in Africa south of the equator that are related to the positive SIOD and the dynamics through which specific rainfall regions in southern Africa can be influenced by this relationship. Four austral...     

GNSS-R土壤水分遥感的适宜性分析

利用GNSS-R(Global Navigation Satellite System-Reflectometry)技术探测土壤水分是近年来一个新兴的研究方向。目前GNSS-R遥感观测中反射信号的接收与处理方式包括单天线与多天线两种模式,面向实际应用需求,GNSS-R遥感正在实现从最初的地基观测向空基、星载观测的转变。在推进GNSS-R土壤水分遥感技术业务化应用的过程中,必须首先进行适宜性分析,确定该技术探测的地理位置、空间分辨率与探测深度,然而目前对此尚未有系统、全面、定量的论述。本文针对适宜性分析中的3个关键因子分别进行理论分析与公式推导,明确相关概念的定义,并实现定量化描述,最终通过实际应用分析进一步诠释其应用价值。对于单天线模式地基观测,以美国板块边界观测计划PBO(Plate Boundary Observatory)土壤水分产品为例,分析镜面反射点的相对位置、第一级Fresnel反射椭圆簇的面积与时间序列土壤水分所代表的探测深度;对于多天线模式,以郑州上街区农田空基观测试验为例,得到基于航迹的栅格土壤水分空间分布并探讨其探测深度。本文能够为未来两种观测模式下地基、空基和星载GNSS-R遥感观测、北斗反射信号遥感,以及GNSS-R在农业、水文、生态等领域的实际应用提供理论指导。     

Estimation of hourly and daily evapotranspiration and soil moisture using downscaled LST over various urban surfaces

Surface moisture is important to link land surface temperature (LST) to people’s thermal comfort. In urban areas, the surface roughness from buildings and urban trees impacts wind speed, and consequently surface moisture. To find the role of surface roughness in surface moisture estimation, we developed methods to estimate daily and hourly evapotranspiration (ET) and soil moisture, based on a case study of Indianapolis, Indiana, USA. In order to capture the spatial and temporal variations of LST, hourly and daily LST was produced by downscaling techniques. Given the heterogeneity in urban areas, fractions of vegetation, soil, and impervious surfaces were calculated. To describe the urban morphology, surface roughness parameters were calculated from digital elevation model (DEM), digital surface model (DSM), and Terrestrial Light Detection and Ranging (LiDAR). Two source energy balance (TSEB) model was employed to generate ET, and the temperature vegetation index (TVX) method was used to calculate soil moisture. Stable hourly soil moisture fluctuated from 15% to 20%, and daily soil moisture increased due to precipitation and decreased due to seasonal temperature change. ET over soil, vegetation, and impervious surface in the urban areas yielded different patterns in response to precipitation. The surface roughness from high-rise has bigger influence on ET in central urban areas.