基于SWAT模型的细河流域土地利用/覆被变化对径流影响的研究

土地利用/覆被变化对细河流域的水文过程影响显著。为研究不同土地利用/覆被情景对流域水文要素的影响情况,本文构建了适用于细河流域的SWAT分布式水文模型,并拟算出不同情景下的流域多年平均月径流量、多年平均地表径流深度、多年平均蒸发量以及多年平均土壤侧流。模拟结果显示:当流域农林用地增加时,平均月径流量增加了8.40%;当建设用地增加时,平均月径流量减少了4.11%;当旱地及其他未利用地增加时,平均月径流量减少了1.93%。综上所述,细河流域农林用地变化对径流产量的影响相对最大,其增加导致径流量增加;旱地及其他未利用对径流产量的影响相对最小,建设用地和旱地及其他未利用地的增加导致径流量减少。     

基于GIS的乌江流域地表径流模拟研究

基于GIS平台，建立了数字乌江流域。在此基础上，选择5个典型子流域，利用流域1956-2000年的降雨和水文资料及流域2000年土地利用数据，分别计算5个子流域的年均降雨量、年均地表径流量和土地利用百分比；用多元回归分析工具建立流域年均地表径流量与年均降雨量和土地利用百分比之间的关系式，得到不同土地利用方式下的降雨径流模型；通过实测资料对模型进行验证的结果表明，模型模拟精度较高，相对误差在7％以内。     

Annual variations in water storage and precipitation in the Amazon Basin

We combine satellite gravity data from the gravity recovery and climate experiment (GRACE) and precipitation measurements from the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center’s (CPC) Merged Analysis of Precipitation (CMAP) and the Tropical Rainfall Measuring Mission (TRMM), over the period from mid-2002 to mid-2006, to investigate the relative importance of sink (runoff and evaporation) and source (precipitation) terms in the hydrological balance of the Amazon Basin. When linear and quadratic terms are removed, the time-series of land water storage variations estimated from GRACE exhibits a dominant annual signal of 250 mm peak-to-peak, which is equivalent to a water volume change of ~1,800 km³. A comparison of this trend with accumulated (i.e., integrated) precipitation shows excellent agreement and no evidence of basin saturation. The agreement indicates that the net runoff and evaporation contributes significantly less than precipitation to the annual hydrological mass balance. Indeed, raw residuals between the de-trended water storage and precipitation anomalies range from ±40 mm. This range is consistent with stream-flow measurements from the region, although the latter are characterized by a stronger annual signal than our residuals, suggesting that runoff and evaporation may act to partially cancel each other.     

MEDICAL GEOGRAPHIC MAPPING AND THE ASSESSMENT OF THE INFLUENCE OF SURFACE WATER POLLUTION ON THE HUMAN ORGANISM

The paper presents results of applied medical-geographic mapping work by the Uzbek SSR Academy of Sciences in support of public health studies in Central Asian areas where water supplies are contaminated by runoff from irrigated fields. The final product of the work is a map depicting surface water quality in aggregate terms and according to indices for specific pollutants (for water quality monitoring points), which is described both in terms of its content and methods of data compilation and transformation. Translated by Elliott B. Urdang, Providence, RI 02906 from: Izvestiya vysshikh uchebnykh zavedeniy: Geodeziya i aerofotos “yemka, 1989, No. 2, pp. 166–171.     

CryoSheds: a GIS modeling framework for delineating land-ice watersheds for the Greenland Ice Sheet

Choice of watershed delineation technique is an important source of uncertainty for cryo-hydrologic studies of the Greenland Ice Sheet (GrIS), with different methods yielding different watersheds for a common pour point. First, this paper explores this uncertainty for the Akuliarusiarsuup Kuua River Northern Tributary, Western Greenland. Next, a standardized, semi-automated modeling framework for generating land-ice watersheds for GrIS land-terminating ice (henceforth referred to as CryoSheds) using geographic information systems (GIS) hydrologic modeling tools is presented. The framework uses ArcGIS and the ArcPy geoprocessing library to delineate two types of land-ice watersheds, namely those defined by: (1) a hydraulic pressure potential with varying water to ice overburden pressure ratios (k-value), which determines theoretical flow paths from the hydrostatic equation, using surface and bedrock digital elevation models (DEMs) and (2) a surface topography DEM alone. Lastly, a demonstration of the CryoSheds method is presented for seven remotely sensed proglacial pour points along the Aussivigssuit River (AR), Western Greenland, and its largest tributaries. GrIS meltwater runoff from these seven nested land-ice watersheds is estimated using Modele Atmospherique Regional (MAR) v.3.2 and runoff uncertainties due to watershed delineation parameter selection is estimated.     

Estimation of surface runoff in Malattar sub-watershed using SCS-CN method

Nowadays watershed management plays a vital role in water resources engineering. Watershed based on water resources management is necessary to plan and conserve the available resources. Remote Sensing (RS) and Geographic Information System (GIS) techniques can be effectively used to manage spatial and non spatial database that represent the hydrologic characteristics of the watershed use as realistically as possible. The present study area is Malattar subwatershed (4C2B2) lies in the region Gudiyattam Block, Vellore District, Tamil Nadu. The daily rainfall data of Gudiyattam rain gauge station (1971–2007) was collected and used to predict the daily runoff from the watershed using Soil Conservation Service — Curve Number (SCS — CN) method (USDA, 1972) and GIS. Monthly and annual runoff have been calculated from the monthly rainfall data for the years of 1971 to 2007 in the watershed area. The average minimum and maximum rainfall for the years of 1971 to 2007 is 35.30 mm and 111.61 mm respectively and average runoff for the year of 1971 to 2007 is 31.87 mm³ and 47.04 mm³ respectively. The developed rainfall-runoff model is used to understand the watershed and its runoff flow characteristics.     

一种基于DEM汇水累积量的径流节点提取方法

快速有效地提取径流节点,对进行水系的形态和属性特征研究具有重要意义。已有的研究发现:径流节点在汇水累积量上具有显著的突变性和多向汇集性特征,在充分考虑此水文特征的基础上,本文运用GIS窗口分析的方法原理,设计了可行的基于高精度DEM数据的径流节点提取方法,完成了对实验样区DEM数据的径流节点提取。通过与实测的径流节点数量和分布的结果对比,验证了该方法具有理想的精度,同时具有较高的执行效率。     

Identification of basin characteristics influencing spatial variation of river flows

The selection of basin characteristics that explain spatial variation of river flows is important for hydrological regionalization as this enables estimation of flow statistics of ungauged basins. A direct gradient analysis method, redundancy analysis, is used to identify basin characteristics, which explain the variation of river flows among 52 selected basins in Zimbabwe. Flow statistics considered are mean annual runoff, coefficient of variation of annual runoff, average number of days per year without flow and selected percentile flows. Basin characteristics investigated are those likely to reflect climatological, topographical and hydrogeological influences including that of land cover on river flows. The first ordination axis of flow statistics is strongly correlated with mean annual precipitation, mean annual potential evaporation and median slope. This ordination axis explains 64% of the variation of selected flow statistics among the selected drainage basins. The proportions of a basin under cultivation, and that with grasslands are correlated with the second ordination axis, which explains 6% of the variation of selected flow statistics. Mean annual precipitation is the most important basin characteristic, and this alone explains 50% of the variation of flow statistics. Median slope is the second most important basin characteristic. Proportions of a basin underlain by different lithological types had no effect on flow characteristics of selected basins. The paper has demonstrated the ability of redundancy analysis to identify basin characteristics that explain the variation of river flows among basins, including estimating the relative importance of these basin characteristics.     

Defining optimal DEM resolutions and point densities for modelling hydrologically sensitive areas in agricultural catchments dominated by microtopography

Defining critical source areas (CSAs) of diffuse pollution in agricultural catchments depends upon the accurate delineation of hydrologically sensitive areas (HSAs) at highest risk of generating surface runoff pathways. In topographically complex landscapes, this delineation is constrained by digital elevation model (DEM) resolution and the influence of microtopographic features. To address this, optimal DEM resolutions and point densities for spatially modelling HSAs were investigated, for onward use in delineating CSAs. The surface runoff framework was modelled using the Topographic Wetness Index (TWI) and maps were derived from 0.25 m LiDAR DEMs (40 bare-earth points m⁻²), resampled 1 m and 2 m LiDAR DEMs, and a radar generated 5 m DEM. Furthermore, the resampled 1 m and 2 m LiDAR DEMs were regenerated with reduced bare-earth point densities (5, 2, 1, 0.5, 0.25 and 0.125 points m⁻²) to analyse effects on elevation accuracy and important microtopographic features. Results were compared to surface runoff field observations in two 10 km² agricultural catchments for evaluation. Analysis showed that the accuracy of modelled HSAs using different thresholds (5%, 10% and 15% of the catchment area with the highest TWI values) was much higher using LiDAR data compared to the 5 m DEM (70–100% and 10–84%, respectively). This was attributed to the DEM capturing microtopographic features such as hedgerow banks, roads, tramlines and open agricultural drains, which acted as topographic barriers or channels that diverted runoff away from the hillslope scale flow direction. Furthermore, the identification of ‘breakthrough’ and ‘delivery’ points along runoff pathways where runoff and mobilised pollutants could be potentially transported between fields or delivered to the drainage channel network was much higher using LiDAR data compared to the 5 m DEM (75–100% and 0–100%, respectively). Optimal DEM resolutions of 1–2 m were identified for modelling HSAs, which balanced the need for microtopographic detail as well as surface generalisations required to model the natural hillslope scale movement of flow. Little loss of vertical accuracy was observed in 1–2 m LiDAR DEMs with reduced bare-earth point densities of 2–5 points m⁻², even at hedgerows. Further improvements in HSA models could be achieved if soil hydrological properties and the effects of flow sinks (filtered out in TWI models) on hydrological connectivity are also considered.     

基于DEM汇流模拟的鞍部点提取改进方法

鞍部点是重要的地形控制点之一,由于其特殊的形态特征,基于DEM的鞍部点提取算法较山顶点、山谷点提取更为困难.本文提出一种基于DEM汇流模拟的鞍部点快速提取改进算法.该算法利用DEM地表汇流模拟的方法提取山脊线,利用地形倒置得到的反地形地表汇流模拟提取反地形流域边界线,获得能自动实现地形部分的原始地形汇水线,进而通过特征...     

Tracking desertification on the Mongolian steppe through NDVI and field-survey data

Abstract

Changing environmental and socio-economic conditions make land degradation, a major concern in Central and East Asia. Globally satellite imagery, particularly Normalized Difference Vegetation Index (NDVI) data, has proved an effective tool for monitoring land cover change. This study examines 33 grassland water points using vegetation field studies and remote sensing techniques to track desertification on the Mongolian plateau. Findings established a significant correlation between same-year field observation (line transects) and NDVI data, enabling an historical land cover perspective to be developed from 1998 to 2006. Results show variable land cover patterns in Mongolia with a 16% decrease in plant density over the time period. Decline in cover identified by NDVI suggests degradation; however, continued annual fluctuation indicates desertification – irreversible land cover change – has not occurred. Further, in situ data documenting greater cover near water points implies livestock overgrazing is not causing degradation at water sources. In combination of the two research methods – remote sensing and field surveys – strengthen findings and provide an effective way to track desertification in dryland regions.     

An integrated study of geospatial information technologies for surface runoff estimation in an agricultural watershed,India

Runoff is one of the important hydrologic variables used in most of the water resources applications. The Soil Conservation Service-Curve Number (SCS-CN) method is adopted for the estimation of surface runoff in the Mehadrigedda watershed area, Visakhapatnam district, India using multispectral remote sensing data, curve number approach and normal rainfall data. The main source of water in the Mehadrigedda watershed area is by rain, most of it drains off and only a little percolates into ground. The weighted curve number is determined based on antecedent moisture condition (AMC)-II with an integration of hydrologic soil groups (HSGs) and land use/land cover LULC categories. An integrated approach is applied to delineate the land use/land cover information as adopted from NRSA classification. The recording of daily rainfall data during the years 1997–2006 is collected from Indian Meteorological Department (IMD) rainguage center at Kottavalasa. It is observed that the annual rainfall-runoff relationship during 1997–2006, which is indicating that the overall increase in runoff with the rainfall of the watershed area. Integration of remote sensing (RS) and geographical infomation system (GIS) techniques provide reliable, accurate and up-to-date information on land and water resources.     

动态数据驱动模式下的湖泊流域降雨径流模拟

湖泊流域汇水径流过程的模拟预测是一种复杂系统中的时间序列分析问题。模型选择上,现有的机理模型法与辨识模型法各有利弊。同时,现有的模型多采用静态数据驱动模拟,不能有效利用传感网实时观测数据来改善模拟不确定性的问题。本文基于深度循环神经网络技术,提出一种适应动态数据驱动的模式,可融合遥感数据与原位传感器站点数据的DTSM(Dynamic Data Driven Time Series Model)时序模拟预测模型,并在观测值与数值模拟之间建立了一种能动态反馈、自适应调整的模拟框架,解决了传统辨识模型法对时序信息挖掘较弱导致模拟精度较低的问题。通过在鄱阳湖多个子流域入湖径流的案例中验证,显示静态数据驱动模式下,以不同数据源作为输入模拟时,本文DTSM模型的纳希效率系数Ens精度比机理模型提高10个百分点以上;相比静态模式,动态数据驱动模式的模拟精度有进一步提高,尤其是对于静态模式精度较低的流域,提高更为明显。     

GRASS GIS-embedded Decision Support Framework for Flood Simulation and Forecasting

This study presents a spatiotemporal analysis tool, called Shyska. This tool allows the simulation and prediction of flash floods in semiarid basins. Shyska has been developed by Geographical Information System (GIS)‐embedded functions, allowing the integration of hydrometeorological information from modern technologies of data acquisition in real time. A Digital Elevation Model (DEM) is used in order to obtain the relevant parameters from the integrated rainfall‐runoff models. Some of its most relevant modules and methodology employed for its development are described. Case studies in basins of south‐east Spain illustrate the applicability of the proposed techniques.     

An Assessment of the Effects of Cell Size on AGNPS Modeling of Watershed Runoff

This study investigates the changes in simulated watershed runoff from the Agricultural NonPoint Source (AGNPS) pollution model as a function of model input cell size resolution for eight different cell sizes (30 m, 60 m, 120 m, 210 m, 240 m, 480 m, 960 m, and 1920 m) for the Little River Watershed (Georgia, USA). Overland cell runoff (area-weighted cell runoff), total runoff volume, clustering statistics, and hot spot patterns were examined for the different cell sizes and trends identified. Total runoff volumes decreased with increasing cell size. Using data sets of 210-m cell size or smaller in conjunction with a representative watershed boundary allows one to model the runoff volumes within 0.2 percent accuracy. The runoff clustering statistics decrease with increasing cell size; a cell size of 960 m or smaller is necessary to indicate significant high-runoff clustering. Runoff hot spot areas have a decreasing trend with increasing cell size; a cell size of 240 m or smaller is required to detect important hot spots. Conclusions regarding cell size effects on runoff estimation cannot be applied to local watershed areas due to the inconsistent changes of runoff volume with cell size; but, optimal cells sizes for clustering and hot spot analyses are applicable to local watershed areas due to the consistent trends.     

Catchment infiltration II: Contributing areas

This study considers two issues of interest to the hydrologic and geographical information systems community. One deals with identifying the spatial distribution of infiltration and runoff contributing areas. The other addresses process modelling within a GIS framework. The study operates on the premise that partitioning of precipitation into runoff or infiltration depends on rainfall intensity and on soil properties. The problem is that neither local rainfall intensity, nor soil properties such as infiltration capacity and macroporosity are known well enough for all points of a catchment and need to be estimated. We infer local intensity from the interpolated distribution of cumulated rain depths over the catchment and record duration at the official met site. Measured values of sorptivity and hydraulic conductivity define infiltration. Negative head infiltration describes macroporosity. To scale-up measured point values to larger areas and to model infiltration and macropore continuity at a catchment scale we use geostatistical kriging and conditional simulation together with standard GIS techniques of overlay manipulation. Results delineate areas contributing to runoff and infiltration and relate them to macroporosity. By intersecting overlays of precipitation with those of infiltration we create alternate GIS masks targeting specific portions of the watershed as either runoff or infiltration contributing zones. Choice of cell size and time interval define the scales of averaging for the application. Kriged surfaces illustrate the distribution of catchment infiltration, while conditional simulation provides a mechanism to define model uncertainty.     

Impact of Climate Change on Runoff of the Major River Basins of India Using Global Circulation Model (HadCM3) Projected Data

The effects of climate change on hydrological regimes have become a priority area for water and catchment management strategies. The terrestrial hydrology driven by monsoon rainfall plays a crucial role in shaping the agriculture, surface and ground water scenario in India. Thus, it is imperative to assess the impact of the changing climatic scenario projected under various climate change scenario towards the hydrological aspects for India. Runoff is one of the key parameters used as an indicator of hydrological process. A study was taken up to analyse the climate change impact on the runoff of river basins of India. The global circulation model output of Hadley centre (HADCM3) projected climate change data was used. Scenario for 2080 (A2 scenario indicating more industrial growth) was selected. The runoff was modeled using the curve number method in spatial domain using satellite derived current landuse/cover map. The derived runoff was compared with the runoff using normal climatic data (1951–1980). The results showed that there is a decline in the future climatic runoff in most of the river basins of India compared to normal climatic runoff. However, significant reduction was observed for the river basins in the eastern region viz: lower part of Ganga, Bahamani-Baitrani, Subarnrekha and upper parts of the Mahanadi. The mean projected runoff reduction during monsoon season (June–September) were 18 Billion Cubic Meter (BCM), 3.2 BCM, 3.5 BCM and 5.9 BCM for Brahmaputra-Barak Subarnrekha, Subarnarekha and Brahmini-Baitrani basin, respectively in comparison to normal climatic runoff. Overall reduction in seasonal runoff was high for Subarnrekha basin (54.1%). Rainfall to runoff conversion was high for Brahmaputra-Barak basin (72%), whereas coefficient of variation for runoff was more for Mahanadi basin (1.88) considering the monsoon season. Study indicates that eastern India agriculture may be affected due to shortage of surface water availability.     

南京城市降雨淹没模拟及径流分析

针对强降雨引起的城市积涝以及相应次生灾害等问题,提出了一种基于暴雨洪水管理模型、GIS技术以及DEM数据、排水管网数据、降雨数据等数据的建立南京市暴雨积涝模型的方法,并利用该模型模拟了径流及淹没效果。结果显示:该模型是利用经验值率定方法对模型参数进行率定,率定结果较为符合实际情况,因此该模型能较好地模拟南京市的降雨积涝情况。通过对不同类型的降雨数据进行模拟分析,得出径流量的大小与降雨量强烈正相关,相关系数达0.9以上。径流的产生量还与降雨历时和平均降雨强度等其他因素有关。虽然南京主要降雨为峰值小、平均强度低的小雨,但是当降雨量超过设计排涝能力时,在地势低洼的地区容易出现积涝。     

Prioritization of watersheds using morphometric parameters and assessment of surface water potential using remote sensing

In the present study, prioritization of sub-watersheds was carried out on the basis of sediment production rate. Further, basic hydrologic information such as peak rate of runoff and annual surface water potential were also assessed for the study watersheds and these are essential requisites for effective watershed management. The 10 sub watersheds of Tarai development project area are selected for the present study. Morphometric parameters pertaining to study area are used in the estimation of sediment production rate. The sediment production rate in the study area varies between 2.45 to 11.0 ha-m/100 km²/year. The remote sensing data has been utilized for generating land use/land cover data which is an essential prerequisite for land and water resource planning and development. The remote sensing data can especially play significant role in collection of real time information from remote areas of river basins for generation of parameters required for hydrologic modeling.