矿业城市土地利用/覆被变化的水文效应研究

矿业城市受到矿山开发与城市扩张的双重影响,生态环境遭到严重破坏,水环境问题尤为突出。本文以煤矿城市河南省鹤壁市为研究区,根据汤河流域1970—2015年土地利用覆被时空变化特征设定5种不同时期土地利用情景,采用SWAT模型模拟分析5期土地利用/覆被变化的水文效应以及变化规律。研究结果显示,1970—2015年间,土地利用变化引起流域内蒸散发量、土壤下渗量和地下径流量年均分别减少-1. 48 mm、-0.38 mm、-0.29 mm,地表径流量年均增加0.76 mm,汛期与非汛期径流增加;在不同水文年份,土地利用变化对平水年的年径流影响最为明显,对枯水年年径流的影响大于丰水年。本文主要提出了以矿业城市土地利用变化对水循环的影响,该方法对矿区范围内水资源的科学管理具有一定的参考意义。     

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SWAT模型的汉江上游流域径流情景预测研究

气候变化和土地利用是影响径流变化的主要驱动因素,为了精确预测未来汉江上游流域径流量变化趋势,基于SWAT模型、天气发生器BCC/RCG-WG以及CA-Markov模型预测了未来2种土地利用变化模式下的径流量变化,土地利用情景的设置建立在CA-Markov模型预测结果的基础之上,结合全国林地保护利用规划目标以及汉江上游林...     

基于GIS的金沙江流域(云南段)地形差异对降水空间分布影响研究

金沙江流域水资源丰富,流域径流补给以降水和雪山冰雪融水为主,降水量的多少直接影响区域水量的大小。本文以金沙江流域(云南段)为研究区域,利用气象观测站降水资料、2014—2018年月平均降水量数据,运用ArcGIS获得研究区年平均降水估算量,利用金沙江流域站点降水数据、DEM数据分析地形对降水量分布的影响和时空特征。研究表明：春季研究区降水分布呈现出西高东低的分布特征,受到地形影响,降水主要集中在流域上段区域,经纬度对降雨有促进作用。夏季研究区降雨显著增加,降雨量受季风影响较大,流域降水量整段都有上升趋势,经纬度和坡度对降雨量的影响较大。秋季研究区降雨量呈下降趋势,降雨量分布特征为西低东高。冬季研究区降雨有所减少。     

近50a延河流域水文要素变化特征分析

对延河流域1960~2011年的水文要素从年际变化、年代际变化、年内变化以及线性变化趋势4个方面进行分析。结果表明,降水是影响延河流域径流量的主要因素。径流变化除受到降雨量的影响外,还受到其他气象要素及人类活动的影响。     

2000—2020年亚马孙流域地表覆盖时空变化分析

针对亚马孙流域地表覆盖变化对当地生态系统以及全球气候变化具有重要意义这一问题，该文基于国家基础地理信息中心牵头研制的、经一致性处理的全球30 m地表覆盖产品(GlobeLand30)三期地表覆盖数据产品，采用景观格局指数和转移矩阵，分析了2000—2020年亚马孙流域地表覆盖的空间格局分布以及时空变化，并对其变化原因做出分析。结果表明：2000—2020年亚马孙流域林地和湿地面积逐渐减少，耕地、草地和人造地表的面积逐渐增加，水体先减少后增加。亚马孙流域2000—2010年和2010—2020年的地表覆盖类型转变方向基本保持一致；人造地表在地表覆盖类别中破碎现象最为显著，但其破碎化指数持续降低。亚马孙流域地表覆盖的变化主要受人类活动的影响，其中城市扩张和人口增加是林地减少的最主要因素。相关研究成果可为亚马孙流域未来的社会经济发展和生态系统保护提供重要支撑。     

海河流域NDVI对气候变化的响应研究

以海河流域为研究区,利用8 km分辨率AVHRR/NDVI数据和气象资料,逐像元对1981-2000年时段的流域NDVI值、年降水量和年均气温的变化率进行分析,计算了NDVI和年降水量、年均气温的相关关系.结果表明,1981-2000年时段内,海河流域年降水量变化总体呈现北部和南部增加,中部减少的趋势,其变化范围在-8...     

延河流域土地利用变化特征分析

研究土地利用时空变化特征对促进区域生态经济协调发展具有重要意义.以延河流域为例,基于不同时期遥感影像,借助RS、GIS和ENVI软件平台技术,获取了1980-2015年延河流域土地利用变化状况,并进行了土地利用转移分析;在此基础上解译了不同时期的土地利用类型,分析了延河流域土地利用时空变化特征和影响因素.结果表明,1980-2000年流域内土地利用结构整体变化较小,耕地、林地、草地3类土地利用面积相互转化频繁但整体面积趋于稳定,建筑用地面积增加了1.25倍;2000-2015年流域内耕地、林地和草地发生了显著变化,其中耕地面积减少了28％,林地面积增加了40％,草地面积增加了15％,建筑用地面积增加了近两倍,但比例很小,未利用地和水体变化幅度不明显;2000年前后流域内土地利用变化空间特征存在明显不同,2000年之前各土地利用类型变化主要发生在延安市区,2000年之后整个流域地区均有不同土地利用类型的转移;2000-2015年国家"退耕还林、草"生态修复政策、产业经济生产总值不断上升、人口数量稳定增长、城镇化发展迅速等均对流域土地利用结构产生了影响.     

2021年8月汉中—广元降雨过程的BDS数据分析

针对降雨形成原因十分复杂，准确地预报极端天气十分重要且较为困难这一问题，该文以汉中—广元地区发生的持续时间长涉及范围广的降雨为例，采用该地区2年的探空数据建立的T_m模型，利用2021年8月19日—23日汉中—广元地区降雨时的北斗卫星导航系统(BDS)观测站数据解算大气可降水量(PWV)。研究表明：19日开始该地区PWV值不断增加，水汽开始聚集；一直到20日和21日在PWV达到峰值1～2 h后小时降雨量达到最大值；22日和23日降雨逐渐减弱，水汽供应减少，PWV开始缓慢下降；整个降雨过程中PWV先增大后减小。PWV峰值越大对应的降雨等级也越大；在PWV达到峰值1～2 h后小时降雨量才会达到最大值。在暴雨时该地区PWV峰值普遍超过50 mm。     

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。     

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.     

Runoff modelling of a small watershed using satellite data and GIS

This study was conducted for the Nagwan watershed of the Damodar Valley Corporation (DVC), Hazaribagh, Bihar, India. Geographic Information System (GIS) was used to extract the hydrological parameters of the watershed from the remote sensing and field data. The Digital Elevation Model (DEM) was prepared using contour map (Survey of India, 1:50000 scale) of the watershed. The EASI/PACE GIS software was used to extract the topographic features and to delineate watershed and overland flow-paths from the DEM. Land use classification were generated from data of Indian Remote Sensing Satellite (IRS-1B—LISS—II) to compute runoff Curve Number (CN). Data extracted from contour map, soil map and satellite imagery, viz. drainage basin area, basin shape, average slope of the watershed, main stream channel slope, land use, hydrological soil groups and CN were used for developing an empirical model for surface runoff prediction. It was found that the model can predict runoff reasonably well and is well suited for the Nagwan watershed. Design of conservation structures can be done and their effects on direct runoff can be evaluated using the model. In broader sense it could be concluded that model can be applied for estimating runoff and evaluating its effect on structures of the Nagwan watershed.     

Modelling of non-point source pollution in a watershed using remote sensing and gis

Assessment of the environmental impact of Non Point Source (NPS) pollutants on a global, regional and localized scale is the key component for achieving sustainability of agriculture as well as preserving the environment. The knowledge and information required to address the problem of assessing the impact of NPS pollutants like Nitrogen (N), Phosphorus (P), etc., on the environment crosses several sub-disciplines like remote sensing, Geographical Information System (GIS), hydrology and soil science. The remote sensing data, by virtue of its potential like synopticity, multi-spectral and multi-temporal capability, computer compatibility, besides providing almost real time information, has enhanced the scope of automation of mapping dynamic elements, such as land use/land cover, degradation profile and computing the priority categorisation of sub-watersheds. The present study demonstrates the application of remote sensing, GIS and distributed parameter model Agricultural Non-Point Source Pollution Model (AGNPS) in the assessment of hazardous non-point source pollution in a watershed. The ARC-INFO GIS and remote sensing provided the input data to support modelling, while the AGNPS model predicted runoff, sediment and pollutant (N and P) transport within a watershed. The integrated system is used to evaluate the sediment pollution in about 2700 ha Karso watershed located in Hazaribagh area of Jharkhand State, India. The predicted values of runoff and sediment yield copared reasonably well with the measured values. It is important to emphasize that this study is not intended to characterise, in an exhaustive manner. Instead, the goal is to illustrate the implications and potential advantages of GIS and remote sensing based Hydrology and Water quality (H/WQ) modelling framework.     

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.     

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.     

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.     

Using remote sensing imagery to determine the impact of land cover changes on potential runoff for the Mid-Cibolo Creek watershed,Texas

Land cover changes within watersheds have the potential to produce dramatic changes in surface hydrology, namely runoff, in the event of storms. The Mid-Cibolo Creek watershed in south-central Texas has experienced extensive land-cover change in the past two decades due to mass residential development and land clearing in the wake of urban growth along the I-35 corridor. This study determined land-cover changes within the basin using supervised classification to classify land cover from LANDSAT images for the years 1986 and 1999. Changes in runoff volume were then calculated using the Soil Conservation Service (SCS) runoff equation for a series of rainfall scenarios. The results showed that an overall increase in impervious cover and decrease in natural vegetative cover has occurred leading to larger runoff volumes for all storm scenarios. The findings are important for watershed scale urban expansion and land clearing practices as current methods suggest that flood risk is increased.     

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.