Catchment infiltration I: Distribution of variables

Environmental modelling usually requires spatially distributed inputs for model operation. We propose that such inputs are best obtained from field measured data. Geographic information systems (GIS) provide a logical framework to distribute measured inputs spatially, to manipulate ensuing data fields during analysis, and to display the results. This paper describes a study conducted on a 123 km² catchment in Pennsylvania. The purpose was to evaluate how spatial variability of macroporosity affects distribution of other infiltration-related parameters. We measured sorptivity, conductivity and macroporosity at specific points within a catchment, and interpolated their spatial distributions by kriging. The measurements were made with ring and disk infiltrometers, sampling locations were geo-referenced with a global positioning system (GPS), and data were analysed using geostatistical techniques in a GIS context. Field values ( hard data ) were supplemented by soft data derived from cumulative distribution functions (cdfs) and available soil maps. Results showed that, when spatial variability associated with macroporosity was removed, infiltration parameters became less variable. Observed correlation among measured parameters suggested a form of potential transfer functions. We conclude that infiltration can be modelled at either the farm or catchment scale if macroporosity and spatial variability of infiltration parameters are adequately defined, and we suggest approaches which can be used in a GIS context to attain that goal.     

A GIS for hydrological modelling in the semi-arid, HAPEX-Sahel experiment area of Niger, Africa

During the HAPEX-Sahel experiment (1991–94), water redistribution processes were studied at the meso-scale (10 000 km²) near Niamey, Niger. A project now under way at ORSTOM aims at modelling the regional water balance through a spatial approach combining GIS data organization and distributed hydrological modelling. The main objective is to extend the surface water balance, by now available only on a few, small (around 1 km²) unconnected endoreic catchments, to a more significant part of the HAPEX-Sahel square degree, a 1500 km² region called SSZ that includes most of the environmental and hydrology measurement sites. GIS architecture and model design consistently consider data and processes at the local, catchment scale, and at the regional scale. The GIS includes spatial and temporal hydrological data (rainfall, surface runoff, ground water), thematic maps (topography, soil, geomorphology, vegetation) and multi-temporal remote sensing data (SPOT, aerial pictures). The GIS supports the simulation of the composite effect at the regional scale of highly variable and discontinuous component hydrologic processes operating at the catchment scale, in order to simulate inter-annual aquifer recharge and response to climatic scenarios at the regional scale.     

Hydrological modelling of a small watershed using satellite data and gis technique

A distributed parameter model Soil and Water Assessment Tool (SWAT) has been tested on daily and monthly basis for estimating surface runoff and sediment yield from a small watershed “Chhokeranala” in eastern India using satellite data and Geographical Information System (GIS). Several maps like watershed and sub-watershed boundaries, drainage network, landuse/cover and soil texture have been generated. The SWAT model has been verified for the initial phase of monsoon season in the year 2002 using daily rainfall and air temperature. Performance of the model has been also evaluated to simulate the surface runoff and sediment yield on sub-watershed basis for two months (July-August 2002). The results show a good agreement between observed and simulated runoff and sediment yield during the study period. Capability of the model for generating rainfall has been evaluated for 10 years (1992 - 2001) period. The model simulated daily rainfall shows close agreement with the observed rainfall. The present results show that the SWAT model can be used for satisfactory simulation of daily and monthly rainfall, runoff and sediment yield.     

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。     

Investigating flash floods potential areas using ASCAT and TRMM satellites in the Western Cape Province,South Africa

The aim of the study was to evaluate flash flood potential areas in the Western Cape Province of South Africa, by integrating remote sensing products of high rainfall intensity, antecedent soil moisture and topographic wetness index (TWI). Rainfall has high spatial and temporal variability, thus needs to be quantified at an area in real time from remote sensing techniques unlike from sparsely distributed, point gauge network measurements. Western Cape Province has high spatial variation in topography which results in major differences in received rainfall within areas not far from each other. Although high rainfall was considered as the major cause of flash flood, also other contributing factors such as topography and antecedent soil moisture were considered. Areas of high flash flood potential were found to be associated with high rainfall, antecedent precipitation and TWI. Although TRMM 3B42 was found to have better rainfall intensity accuracy, the product is not available in near real time but rather at a rolling archive of three months; therefore, Multi- sensor precipitation estimate rainfall estimates available in near real time are opted for flash flood events. Advanced Scatterometer (ASCAT) soil moisture observations were found to have a reasonable r value of 0.58 and relatively low MAE of 3.8 when validated with in situ soil moisture measurements. The results of this study underscore the importance of ASCAT and TRMM satellite datasets in mapping areas at risk of flooding.     

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。     

Risk assessment of soil erosion in semi-arid mountainous watershed in Saudi Arabia by RUSLE model coupled with remote sensing and GIS

Soil erosion is the most important factor in land degradation and influences desertification in semi-arid areas. A comprehensive methodology that integrates revised universal soil loss equation (RUSLE) model and GIS was adopted to determine the soil erosion risk (SER) in semi-arid Aseer region, Saudi Arabia. Geoenvironmental factors viz. rainfall (R), soil erodibility (K), slope (LS), cover management and practice factors were computed to determine their effects on average annual soil loss. The high potential soil erosion, resulting from high denuded slope, devoid of vegetation cover and high intensity rainfall, is located towards the north western part of the study area. The analysis is investigated that the SER over the vegetation cover including dense vegetation, sparse vegetation and bushes increases with the higher altitude and higher slope angle. The erosion maps generated with RUSLE integrated with GIS can serve as effective inputs in deriving strategies for land planning/management in the environmentally sensitive mountainous areas.     

Rainfall-runoff and soil erosion modeling using Remote Sensing and GIS technique — a case study of tons watershed

In the present study, the rainfall-runoff relationship is determined using USDA Soil Conservation Service (SCS) method. The coefficient of determination (R2) is 0.99, which indicates a high correlation between rainfall and runoff. The runoff potential map was prepared by assigning individual class weight and scores input map. Annual spatial soil loss estimation was computed using Morgan, Morgan and Finney mathematical model in conjunction with remote sensing and GIS techniques. Higher soil erosion was found to occur in the northern part of the Tons watershed. The soil texture in the affected area is coarse loamy to loamy skeletal and soil detachment is higher. Moreover the land use has open forests, which does not reduce the impact of rainfall. The average soil loss for all the four sub-watersheds was calculated, and it was found that the maximum average soil loss of 24.1 t/ha occurred in the sub-watershed 1.     

Evaluation of hydrologic components of community land model 4 and bias identification

Runoff and soil moisture are two key components of the global hydrologic cycle that should be validated at local to global scales in Earth System Models (ESMs) used for climate projection. We have evaluated the runoff and surface soil moisture output by the Community Climate System Model (CCSM) along with 8 other models from the Coupled Model Intercomparison Project (CMIP5) repository using satellite soil moisture observations and stream gauge corrected runoff products. A series of Community Land Model (CLM) runs forced by reanalysis and coupled model outputs was also performed to identify atmospheric drivers of biases and uncertainties in the CCSM. Results indicate that surface soil moisture simulations tend to be positively biased in high latitude areas by most selected CMIP5 models except CCSM, FGOALS, and BCC, which share similar land surface model code. With the exception of GISS, runoff simulations by all selected CMIP5 models were overestimated in mountain ranges and in most of the Arctic region. In general, positive biases in CCSM soil moisture and runoff due to precipitation input error were offset by negative biases induced by temperature input error. Excluding the impact from atmosphere modeling, the global mean of seasonal surface moisture oscillation was out of phase compared to observations in many years during 1985–2004. The CLM also underestimated runoff in the Amazon, central Africa, and south Asia, where soils all have high clay content. We hypothesize that lack of a macropore flow mechanism is partially responsible for this underestimation. However, runoff was overestimated in the areas covered by volcanic ash soils (i.e., Andisols), which might be associated with poor soil porosity representation in CLM. Our results indicate that CCSM predictability of hydrology could be improved by addressing the compensating errors associated with precipitation and temperature and updating the CLM soil representation.     

区域群发性滑坡灾害概率预报系统

根据覆盖浙江全部陆地区域数年降雨量数据,在同时期内有明确日期、位置记录的609处滑坡(泥石流)灾害数据,通过对地质、土壤、土地利用类型、人文等资料的综合分析,研制了集GIS与ANN于一体的区域群发性滑坡灾害概率预报系统(LAPS)。该系统可以通过宽带网络与气象、水文观测等有关部门相连接,在雨季根据雨量观测站的实时观测数据和降雨预报,对全省区域范围内滑坡灾害发生概率进行快速评价,实现对灾害发生的空间范围、强度及其分布概率的实时预警预报,具有维护方便、操作简单、可视化强等特点,可以作为其它滑坡易发地区的预报系统原型。     

Diurnal rainfall variability over the Upper Blue Nile Basin: A remote sensing based approach

In this study we aim to assess the diurnal cycle of rainfall across the Upper Blue Nile (UBN) basin using satellite observations from Tropical Rainfall Measuring Mission (TRMM). Seven years (2002–2008) of Precipitation Radar (PR) and TRMM Microwave Imager (TMI) data are used and analyses are based on GIS operations and simple statistical techniques. Observations from PR and TMI reveal that over most parts of the basin area, the rainfall occurrence and conditional mean rain rate are highest between mid- and late-afternoon (15:00–18:00 LST). Exceptions to this are the south-west and south-eastern parts of the basin area and the Lake Tana basin where midnight and early morning maxima are observed. Along the Blue Nile River gorge the rainfall occurrence and the conditional mean rain rate are highest during the night (20:00–23:00 LST). Orographic effects by large scale variation of topography, elevation and the presence of the UBN river gorge were assessed taking two transects across the basin. Along transects from north to south and from east to west results indicate increased rainfall with increase of elevation whereas areas on the windward side of the high mountain ranges receive higher amount of rainfall than areas on the leeward side. As such, mountain ranges and elevation affect the rainfall distribution resulting in rain shadow effect in the north-eastern parts of Choke-mountain and the ridges in the north-east of the basin. Moreover, a direct relation between rainfall occurrence and elevation is observed specifically for 17:00–18:00 LST. Further, results indicate that the rainfall distribution in the deeply incised and wide river gorge is affected with relatively low rainfall occurrence and low mean rainfall rates in the gorge areas. Seasonal mean rainfall depth is highest in the south-west area and central highlands of the basin while areas in the north, north-east and along the Blue Nile gorge receive the least amount of rainfall. Statistical results of this work show that the diurnal cycle of rainfall occurrence from TRMM estimates show significant correlation with the ground observations at 95% confidence level. In the UBN basin, the PR conditional mean rain rate estimates are closer to the ground observations than the TMI. Analysis on mean wet season rainfall amount indicates that PR generally underestimates and TMI overestimates the ground observed rainfall.     

基于水文-气象阈值的区域降雨型滑坡预测研究

目前区域降雨型滑坡预测主要依赖降雨阈值开展,然而从降雨诱发滑坡机理可知,除降雨入渗导致的土壤含水量变化外,降雨入渗前的土壤含水量也是影响边坡失稳的重要因素,无法考虑降雨入渗前的土壤湿度情况,被认为是降雨阈值在滑坡预测中表现差的主要原因。针对这一问题,本文以四川省都江堰地区作为试验区域,提出考虑前期土壤湿度的区域降雨型滑坡预测思路,通过统计分析历史滑坡数据,构建了基于前期土壤湿度和近期降雨情况的水文-气象阈值模型,其中前期土壤湿度情况由改进的前期有效降雨指数刻画,近期降雨情况由最近的累积降雨量表示。试验结果表明:在试验区域的降雨型滑坡预测中,水文-气象阈值模型表现出较好的命中率和较低的误报率。本文构建的水文-气象阈值模型,可同时考虑前期土壤湿度和近期降雨对滑坡发生的影响,模型所需数据少、所用方法简单易操作且预测性能较优,适合在区域降雨型滑坡预测中推广应用。     

Morphometric analysis to determine floods in the Upper Krishna basin using Cartosat DEM

The evaluation of basin characteristics from the morphometric parameters helps in understanding the physical behaviour of the catchments with respect to floods. The advanced technologies, such as Remote sensing and Geographic Information System (GIS), were used for extraction of drainage networks using Cartosat Digital Elevation Model (DEM) for the Upper Krishna basin, to evaluate the morphometric analysis. Basin morphometric parameters were applied to assess the major influencing catchments which cause flooding in the main Krishna River. The morphometric analysis for the ten major potential flood prone river catchments of the basin reveals that, the river catchments such as Krishna, Koyna, Yerla having the greater tendency to peak discharge in a short period of time to the main Krishna River because of high relief ratio (Rh), high ruggedness number and less time of concentration (Tc). The Don catchment having the highest drainage density (Dd), stream frequency, mean bifurcation ratio and infiltration number causes greater runoff influence on the main Krishna River. The Dudhganga and Panchaganga catchments having highest form factor, medium Dd, texture ratio, Rh and time of concentration causes moderate runoff influence towards main Krishna River. The study indicates that systematic analysis of morphometric parameters derived from Cartosat DEM using GIS provide useful information about catchment characteristics with respect to floods management.     

A comparative assessment of catchment runoff generation and forest productivity in a semi-arid environment

Understanding the dynamic interactions between forest ecosystems and water in the Mediterranean region is essential for increasing ecosystem services. Even if many studies were implemented to analyse the variations of water and net primary productivity (NPP) in the last decade, this is still an important research question especially for the Eastern Mediterranean, where the research attempts are limited. The main objective of this study was to carry out a comparative analysis of catchment runoff generation and forest NPP and to reveal their temporal dynamics at basin scale in a semi-arid Mediterranean environment. The methodology consisted three steps: (i) estimating catchment runoff generation by implementing process-based J2000 modelling suite, (ii) modelling NPP of the land cover/use types by adapting an ecosystem-process model (BIOME-Biogeochemical cycles) and (iii) assessing the spatio-temporal variability of NPP and runoff dynamics by incorporating the modelling results with multiple regression analysis. Model simulations showed that temperature highly contributed to NPP variations of needle-leaf forests and grasslands. The multiple regression analysis also indicated that runoff was influenced by elevation, precipitation and forest cover. This relationship showed that the inter-annual variability in forest NPP would relate to the variations in runoff distribution across a small Mediterranean subcatchment.     

An integrated approach for prioritization of reservoir catchment using remote sensing and geographic information system techniques

This study is aimed at evolving a watershed prioritization of reservoir catchment based on vegetation, morphological and topographical parameters, and average annual soil loss using geographic information system (GIS) and remote sensing techniques. A large multipurpose river valley project, Upper Indravati reservoir, situated in the state of Orissa, India, has been chosen for the present work. Watershed prioritization is useful to soil conservationist and decision makers. This study integrates the watershed erosion response model (WERM) and universal soil loss equation (USLE) with a geographic information system (GIS) to estimate the erosion risk assessment parameters of the catchment. The total catchment is divided into 15 sub-watersheds. Various erosion risk parameters are determined for all the sub-watersheds separately. Average annual soil loss is also estimated for the sub-watersheds using USLE. The integrated effect of all these parameters is evaluated to recommend the priority rating of the watersheds for soil conservation planning.     

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.     

西安市城市内涝模拟与损失灰色关联度研究

综合GIS技术与城市内涝基本原理,基于DEM、水文学原理、不透水面并考虑下渗、排水情况,模拟水流沿格网单元从高到低流动,按照坡度比例分配流量,形成不同降雨强度的城市内涝情景模拟,提取西安市几个典型的积水点淹没风险范围和分布特征等信息,并进行空间分析与数据验证,结果与实际相符。再叠加地表覆盖分类成果和统计年鉴数据,获取不同淹没风险范围内的人口、经济、交通、建筑物等数据,引入灰色关联理论对降雨量和损失因子的关联程度进行定量化,探讨综合影响因素中城市内涝损失的大小问题。结果表明：降雨量与经济损失因子的关联度最大,达到了0.823,与人口损失因子的关联度最小,为0.725,从大到小的顺序为：经济>建筑物>淹没面积>道路>人口。因此,提出充分考虑人为可控的城市内涝影响因子,合理控制城市用地扩展速度,提高土地利用效率的建议,旨在对城市内涝的管理、预测、决策等提供参考。     

面向防汛应急的重庆市洼地积涝预测模型研究

针对重庆市城市防汛应急的需要,在传统内涝模型的基础上,结合GIS空间分析与可视化技术,建立了一个运算快、实时性强的洼地积涝分析预测模型.该模型首先利用空间分析方法建立数字高程模型、城市洼地模型等数据模型,然后采用数值计算方法构建降雨模型、汇水模型、排水模型等分析模型,最后预测出洼地的积水面积、深度等.采用重庆市主城区的...     

基于GIS的土壤重金属污染分析与模拟系统设计

作为环境质量评估的重要指标之一,土壤重金属污染程度对环境质量具有重要影响。为了了解土壤重金属污染现状以及评价重金属污染对环境的影响,利用GIS平台、MySQL数据库、空间分析方法、土壤重金属污染扩散模型等关键技术和方法,设计并开发了基于GIS的土壤重金属污染分析与模拟系统。系统实现了重金属污染分析、二维扩散模拟等功能,可为大面积土壤重金属污染的预防与治理提供技术支持。