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1.
Comparing satellite derived precipitation datasets using the Hillslope River Routing (HRR) model in the Congo River Basin 总被引：1，自引：0，他引：1
R. E. Beighley R. L. Ray Y. He H. Lee L. Schaller K. M. Andreadis M. Durand D. E. Alsdorf C. K. Shum 《水文研究》2011,25(20):3216-3229
In this paper, three satellite derived precipitation datasets (TRMM, CMORPH, PERSIANN) are used to drive the Hillslope River Routing (HRR) model in the Congo Basin. The precipitation data are compared spatially and temporally in two forms: (1) precipitation magnitudes, and (2) resulting streamflow and water storages. Simulated streamflow is assessed using historical monthly discharge data from in situ stream gauges and recent stage data based on water surface elevations derived from ENVISAT radar altimetry data. Simulated total water storage is assessed using monthly storage change values derived from GRACE data. The results show that the three precipitation datasets vary significantly in terms of magnitudes but generally produce a reasonable hydrograph throughout much of the basin, with the exception of the equatorial regions of the watershed. The satellite datasets provide unreasonably high values for specific periods (e.g. all three in Oct–Nov; only CMORPH and PERSIANN in Mar–Apr) in the equatorial regions. Overall, TRMM (3B42) provides the best spatial and temporal distributions and magnitudes or rainfall based on the assessment measures used here. Both CMORPH and PERSIANN tend to overestimate magnitudes, especially in the equatorial regions of the Basin. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
2.
This study developed a correction approach to improve the rainfall field estimation using the TRMM rainfall product in a sparsely-gauged mountainous basin. First, Thiessen polygons were generated to define the measurement domain of each raingauge. Second, the rainfall of TRMM pixels in each Thiessen polygon was corrected using a benchmark method based on the difference between the monthly rainfall estimated by a raingauge and the TRMM pixel that possessed a gauge station (referred to as a gauged pixel). Third, the rainfall values in the gauged pixels were adjusted to the weighted average value of the gauge rainfall and corrected pixel rainfall. Finally, the rainfall in the non-gauged TRMM pixels was corrected as the sum of two terms. The first term is the adjusted rainfall in the corresponding gauged pixel in the same Thiessen polygon, and the second term is the rainfall (after benchmark correction) difference between the current pixel and the gauged pixel. Our results indicate that the corrected rainfall data outperforms the original TRMM product in the simulations of moderate and low flows and outperforms the sparse raingauges in the simulations of both peak and low flows.
EDITOR A. Castellarin; ASSOCIATE EDITOR S. Huang 相似文献
3.
Effects of temporal scales and space mismatches on the TRMM 3B42 v7 precipitation product in a remote mountainous area 
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下载免费PDF全文 Shiva Ebrahimi Cheng Chen Qiuwen Chen Yinsheng Zhang Ning Ma Qammerul Zaman 《水文研究》2017,31(24):4315-4327
The accurate measurement of precipitation is essential to understanding regional hydrological processes and hydrological cycling. Quantification of precipitation over remote regions such as the Tibetan Plateau is highly unreliable because of the scarcity of rain gauges. The objective of this study is to evaluate the performance of the satellite precipitation product of tropical rainfall measuring mission (TRMM) 3B42 v7 at daily, weekly, monthly, and seasonal scales. Comparison between TRMM grid precipitation and point‐based rain gauge precipitation was conducted using nearest neighbour and bilinear weighted interpolation methods. The results showed that the TRMM product could not capture daily precipitation well due to some rainfall events being missed at short time scales but provided reasonably good precipitation data at weekly, monthly, and seasonal scales. TRMM tended to underestimate the precipitation of small rainfall events (less than 1 mm/day), while it overestimated the precipitation of large rainfall events (greater than 20 mm/day). Consequently, TRMM showed better performance in the summer monsoon season than in the winter season. Through comparison, it was also found that the bilinear weighted interpolation method performs better than the nearest neighbour method in TRMM precipitation extraction. 相似文献
4.
Abstract A novel approach is presented for combining spatial and temporal detail from newly available TRMM-based data sets to derive hourly rainfall intensities at 1-km spatial resolution for hydrological modelling applications. Time series of rainfall intensities derived from 3-hourly 0.25° TRMM 3B42 data are merged with a 1-km gridded rainfall climatology based on TRMM 2B31 data to account for the sub-grid spatial distribution of rainfall intensities within coarse-scale 0.25° grid cells. The method is implemented for two dryland catchments in Tunisia and Senegal, and validated against gauge data. The outcomes of the validation show that the spatially disaggregated and intensity corrected TRMM time series more closely approximate ground-based measurements than non-corrected data. The method introduced here enables the generation of rainfall intensity time series with realistic temporal and spatial detail for dynamic modelling of runoff and infiltration processes that are especially important to water resource management in arid regions. Editor D. Koutsoyiannis Citation Tarnavsky, E., Mulligan, M. and Husak, G., 2012. Spatial disaggregation and intensity correction of TRMM-based rainfall time series for hydrological applications in dryland catchments. Hydrological Sciences Journal, 57 (2), 248–264. 相似文献
5.
Bruno Collischonn Walter Collischonn Carlos Eduardo Morelli Tucci 《Journal of Hydrology》2008,360(1-4):207-216
Rainfall measurements by conventional raingauges provide relatively accurate estimates at a few points of a region. The actual rainfield can be approximated by interpolating the available raingauge data to the remaining of the area of interest. In places with relatively low gauge density such interpolated rainfields will be very rough estimates of the actual events. This is especially true for tropical regions where most rainfall has a convective origin with high spatial variability at the daily level. Estimates of rainfall by remote sensing can be very useful in regions such as the Amazon basin, where raingauge density is very low and rainfall highly variable. This paper evaluates the rainfall estimates of the Tropical Rainfall Measuring Mission (TRMM) satellite over the Tapajós river basin, a major tributary of the Amazon. Three-hour TRMM rainfall estimates were aggregated to daily values and were compared with catch of ground-level precipitation gauges on a daily basis after interpolating both data to a regular grid. Both daily TRMM and raingauge-interpolated rainfields were then used as input to a large-scale hydrological model for the whole basin; the calculated hydrographs were then compared to observations at several streamgauges along the river Tapajos and its main tributaries. Results of the rainfield comparisons showed that satellite estimates can be a practical tool for identifying damaged or aberrant raingauges at a basin-wide scale. Results of the hydrological modeling showed that TRMM-based calculated hydrographs are comparable with those obtained using raingauge data. 相似文献
6.
The lack of high resolution precipitation data has posed great challenges to the study and management of extreme rainfall events. Satellite-based rainfall products with large areal coverage provide a potential alternative source of data where in situ measurements are not available. However, the mismatch in scale between these products and model requirements has limited their application and demonstrates that satellite data must be downscaled before being used. This study developed a statistical spatial downscaling scheme based on the relationships between precipitation and related environmental factors such as local topography and pre-storm meteorological conditions. The method was applied to disaggregate the Tropical Rainfall Measuring Mission (TRMM) 3B42 products, which have a resolution of 0.25° × 0.25°, to 1 × 1 km gridded rainfall fields. The TRMM datasets in accord with six rainstorm events in the Xiao River basin were used to validate the effectiveness of this approach. The downscaled precipitation data were compared with ground observations and exhibited good agreement with r2 values ranging from 0.612 to 0.838. In addition, the proposed approach provided better results than the conventional spline and kriging interpolation methods, indicating its promise in the management of extreme rainfall events. The uncertainties in the final results and the implications for further study were discussed, and the needs for additional rigorous investigations of the rainfall physical process prior to institutionalizing the use of satellite data were highlighted. 相似文献
7.
全球降水计划多卫星降水联合反演IMERG卫星降水产品在中国大陆地区的多尺度精度评估 总被引：1，自引：0，他引：1
以中国气象局逐小时地面降水数据集为参考基准,采用8种统计评价指标综合评估对比了美国NASA研发的全球降水计划（GPM）多卫星降水联合反演IMERG（Integrated Multi-satellitE Retrievals for GPM）卫星降水产品的三个不同版本的Final数据,分析了三套卫星降水在中国大陆地区多时空尺度下的反演精度,探讨了IMERG最新版本V5数据的改进情况及反演中仍然存在的问题.结果表明：IMERG数据能够准确地捕捉到中国大陆地区的降水区域特征,但是在中国西北部地面站点稀疏地区误差较大,精度较低,难以精确估测该地区的实际降水值.最新版本V5数据精度整体上优于先前的V3和V4数据,V5与地面观测数据的相关系数为0.75,均方根误差为7.03 mm/d,较V3、V4有明显提高,改善了V3、V4在中国西北部出现的降水低估问题;但是V5在冬季表现较差且没有解决前期版本存在的高估问题,整体上相对实际降水仍处于高估状态;同时V5在对高雨强事件的捕捉监测能力方面还存在一定的不足,因此建议在强降雨事件监测中需谨慎使用卫星降水IMERG数据集.目前V5系统中的校正算法还存在部分缺陷：为消除全球降水系统性低估问题,目前的校正算法整体性抬升了卫星降水值,从而导致卫星降水反演在中国地区高雨强事件下出现高误报以及高估问题,进而影响到IMERG数据回推以及后续再生数据的精度. 相似文献
8.
Waldo Sven Lavado Casimiro David Labat Josyane Ronchail Jhan Carlo Espinoza Jean Loup Guyot 《水文研究》2013,27(20):2944-2957
The hydroclimatology of the Peruvian Amazon–Andes basin (PAB) which surface corresponding to 7% of the Amazon basin is still poorly documented. We propose here an extended and original analysis of the temporal evolution of monthly rainfall, mean temperature (Tmean), maximum temperature (Tmax) and minimum temperature (Tmin) time series over two PABs (Huallaga and Ucayali) over the last 40 years. This analysis is based on a new and more complete database that includes 77 weather stations over the 1965–2007 period, and we focus our attention on both annual and seasonal meteorological time series. A positive significant trend in mean temperature of 0.09 °C per decade is detected over the region with similar values in the Andes and rainforest when considering average data. However, a high percentage of stations with significant Tmean positive trends are located over the Andes region. Finally, changes in the mean values occurred earlier in Tmax (during the 1970s) than in Tmin (during the 1980s). In the PAB, there is neither trend nor mean change in rainfall during the 1965–2007 period. However, annual, summer and autumn rainfall in the southern Andes presents an important interannual variability that is associated with the sea surface temperature in the tropical Atlantic Ocean while there are limited relationships between rainfall and El Niño‐Southern Oscillation (ENSO) events. On the contrary, the interannual temperature variability is mainly related to ENSO events. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
9.
The emergence of regional and global satellite‐based rainfall products with high spatial and temporal resolution has opened up new large‐scale hydrological applications in data‐sparse or ungauged catchments. Particularly, distributed hydrological models can benefit from the good spatial coverage and distributed nature of satellite‐based rainfall estimates (SRFE). In this study, five SRFEs with temporal resolution of 24 h and spatial resolution between 8 and 27 km have been evaluated through their predictive capability in a distributed hydrological model of the Senegal River basin in West Africa. The main advantage of this evaluation methodology is the integration of the rainfall model input in time and space when evaluated at the sub‐catchment scale. An initial data analysis revealed significant biases in the SRFE products and large variations in rainfall amounts between SRFEs, although the spatial patterns were similar. The results showed that the Climate Prediction Center/Famine Early Warning System (CPC‐FEWS) and cold cloud duration (CCD) products, which are partly based on rain gauge data and produced specifically for the African continent, performed better in the modelling context than the global SRFEs, Climate Prediction Center MORPHing technique (CMORPH), Tropical Rainfall Measuring Mission (TRMM) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). The best performing SRFE, CPC‐FEWS, produced good results with values of R2NS between 0·84 and 0·87 after bias correction and model recalibration. This was comparable to model simulations based on traditional rain gauge data. The study highlights the need for input specific calibration of hydrological models, since major differences were observed in model performances even when all SRFEs were scaled to the same mean rainfall amounts. This is mainly attributed to differences in temporal dynamics between products. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
10.
ABSTRACTA regionalized rain/no-rain classification (RNC) based on scattering index methodology is developed for detecting rainfall signatures over the land regions of the Mahanadi basin (India), using data products from the passive and active sensors onboard the Tropical Rainfall Measuring Mission (TRMM), namely the TRMM Microwave Imager (TMI) and Precipitation Radar (PR). The proposed model, developed using data for two years from the orbital database, was validated using PR and in-situ data for selected case study events in 2011 and 2012. Performance evaluation of the model is discussed using 10 metrics derived from the contingency table. Overall, the results show superior performance, with an average probability of detection of 0.83, bias of 1.10 and odds ratio skill score greater than 0.93. Accurate rainfall detection is obtained for 95% of case study events. The relative performance of the proposed model is dependent on rainfall type, but it should be useful in rainfall retrieval algorithms for current missions such as the Global Precipitation Measurement Mission.
Editor M.C. Acreman; Associate editor Y. Gyasi-Agyei 相似文献
11.
Data from the Tropical Rainfall Measuring Mission (TRMM) satellite sensors, the Microwave Imager (TMI, 3A12 V6) and other satellite sources (3B43 V6) have been used to derive the thunderstorm ratio β, total rain accumulation M, and 1-min rainfall rates, R1min, for 37 stations in Nigeria, for 0.001–1% of an average year, for the period 1998–2006. Results of the rain accumulations from the TRMM satellite (1998–2006) were compared with the data collected from 14 ground stations in Nigeria for the period 1991–2000. The two data sets are reasonably positively correlated, with correlation coefficients varying from 0.64 to 0.99. Deduced 1-min rainfall rates compared fairly well with the previous ground data of Ajayi and Ezekpo (1988. Development of climatic maps of rainfall rate and attenuation for microwave applications in Nigeria. The Nigerian Engineering 23(4), 13–30) with correlation coefficients varying from 0.17 to 0.97 in all 37 stations. The agreement was much better when compared with the International Telecommunications Union Radio communication Study group 3 digital maps with correlation coefficients varying from 0.84 to 0.98 in 23 locations; however there were negative correlation coefficient (of 0.2 in 7 stations) in the Middle Belt and a weak positive coefficient (of 0.09 in 6 stations) in the South South. Regionally the inferred mean annual 1-min rainfall rates are the highest in the South-East region with values between 111 and 125 mm/h throughout the 9 years, followed by the South-South region (105–124 mm/h). The lowest rainfall rate and rainfall accumulation occur in the North-West region (60–86 mm/h) followed, in ascending order, by the North-East (66–95 mm/h) region, the Middle-Belt region (76–102 mm/h) and the South-West region (77–110 mm/h). The present results were also compared with 9 tropical stations around the world and there was positive correlation between the results. The present results will be very useful for satellite rain attenuation modeling in the tropics and subtropical stations around the world.It is useful to note that one country, particularly one as large as Nigeria, can have significant variations in its rainfall characteristics for a variety of reasons, and this is borne out by the results presented. 相似文献
12.
《水文科学杂志》2012,57(2):296-310
ABSTRACTHydrological models require different inputs for the simulation of processes, among which precipitation is essential. For hydrological simulation, four different precipitation products – Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE); European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim); Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) real time (RT); and Precipitation Estimation from Remotely Sensed Information using Arti?cial Neural Networks (PERSIANN) – are compared against ground-based datasets. The variable infiltration capacity (VIC) model was calibrated for the Sefidrood River Basin (SRB), Iran. APHRODITE and ERA-Interim gave better rainfall estimates at daily time scale than other products, with Nash-Sutcliffe efficiency (NSE) values of 0.79 and 0.63, and correlation coefficient (CC) of 0.91 and 0.82, respectively. At the monthly time scale, the CC between all rainfall datasets and ground observations is greater than 0.9, except for TMPA-RT. Hydrological assessment indicates that PERSIANN is the best rainfall dataset for capturing the streamflow and peak flows for the studied area (CC: 0.91, NSE: 0.80). 相似文献
13.
An adequately tested soil and water assessment tool (SWAT) model was applied to the runoff and sediment yield of a small agricultural watershed in eastern India using generated rainfall. The capability of the model for generating rainfall was evaluated for a period of 18 years (1981–1998). The watershed and subwatershed boundaries, drainage networks, slope, soil series and texture maps were generated using a geographical information system (GIS). A supervised classification method was used for land‐use/cover classification from satellite imageries. Model simulated monthly rainfall for the period of 18 years was compared with observations. Simulated monthly rainfall, runoff and sediment yield values for the monsoon season of 8 years (1991–1998) were also compared with their observed values. In general monthly average rainfall predicted by the model was in close agreement with the observed monthly average values. Also, simulated monthly average values of surface runoff and sediment yield using generated rainfall compared well with observed values during the monsoon season of the years 1991–1998. Results of this study revealed that the SWAT model can generate monthly average rainfall satisfactorily and thereby can produce monthly average values of surface runoff and sediment yield close to the observed values. Therefore, it can be concluded that the SWAT model could be used for developing a multiple year management plan for the critical erosion prone areas of a small watershed. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
14.
Evaluation and hydrological application of precipitation estimates derived from PERSIANN‐CDR,TRMM 3B42V7, and NCEP‐CFSR over humid regions in China 下载免费PDF全文
下载免费PDF全文 Satellite‐based and reanalysis quantitative precipitation estimates are attractive for hydrologic prediction or forecasting and reliable water resources management, especially for ungauged regions. This study evaluates three widely used global high‐resolution precipitation products [Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks‐Climate Data Record (PERSIANN‐CDR), Tropical Rainfall Measuring Mission 3B42 Version 7 (TRMM 3B42V7), and National Centers for Environment Prediction‐Climate Forecast System Reanalysis (NCEP‐CFSR)] against gauge observations with seven statistical indices over two humid regions in China. Furthermore, the study investigates whether the three precipitation products can be reliably utilized as inputs in Soil and Water Assessment Tool, a semi‐distributed hydrological model, to simulate streamflows. Results show that the precipitation estimates derived from TRMM 3B42V7 outperform the other two products with the smallest errors and bias, and highest correlation at monthly scale, which is followed by PERSIANN‐CDR and NCEP‐CFSR in this rank. However, the superiority of TRMM 3B42V7 in errors, bias, and correlations is not warranted at daily scale. PERSIANN‐CDR and 3B42V7 present encouraging potential for streamflow prediction at daily and monthly scale respectively over the two humid regions, whilst the performance of NCEP‐CFSR for hydrological applications varies from basin to basin. Simulations forced with 3B42V7 are the best among the three precipitation products in capturing daily measured streamflows, whilst PERSIANN‐CDR‐driven simulations underestimate high streamflows and high streamflow simulations driven by NCEP‐CFSR mostly are overestimated significantly. In terms of extreme events analysis, PERSIANN‐CDR often underestimates the extreme precipitation, so do extreme streamflow simulations forced with it. NCEP‐CFSR performs just the reverse, compared with PERSIANN‐CDR. The performance pattern of TRMM 3B42V7 on extremes is not certain, with coexisting underestimation and overestimation. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
15.
Waldo Sven Lavado Casimiro David Labat Jean Loup Guyot Sandra Ardoin‐Bardin 《水文研究》2011,25(24):3721-3734
In this article, we propose an investigation of the modifications of the hydrological response of two Peruvian Amazonas–Andes basins in relationship with the modifications of the precipitation and evapotranspiration rates inferred by the IPCC. These two basins integrate around 10% of the total area of the Amazonian basin. These estimations are based on the application of two monthly hydrological models, GR2M and MWB3, and the climatic projections come from BCM2, CSMK3 and MIHR models for A1B and B1 emission scenarios (SCE A1B and SCE B1). Projections are approximated by two simple scenarios (anomalies and horizon) and annual rainfall rates, evapotranspiration rates and discharge were estimated for the 2020s (2008–2040), 2050s (2041–2070) and 2080s (2071–2099). Annual discharge shows increasing trend over Requena basin (Ucayali river), Puerto Inca basin (Pachitea river), Tambo basin (Tambo river) and Mejorada basin (Mantaro river) while discharge shows decreasing trend over the Chazuta basin (Huallaga river), the Maldonadillo basin (Urubamba river) and the Pisac basin (Vilcanota river). Monthly discharge at the outlet of Puerto Inca, Tambo and Mejorada basins shows increasing trends for all seasons. Trends to decrease are estimated in autumn discharge over the Requena basin and spring discharge over Pisac basin as well as summer and autumn discharges over both the Chazuta and the Maldonadillo basins. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
16.
降雨对地电阻率干扰的分析 总被引：8，自引：0，他引：8
在一些地电阻率观测台站受本身台址条件的限制，观测深度较浅，因此，观测值受到降雨等气象因素的影响。本文选取昌黎台ＥＷ向１９８３－１９９４年观测资料月均值，用褶积滤波和多元回归方法对ρｓ进行了降雨校正，将将之作为一个灰箱系统，将资料外推至１９９５４上，然后与原始观测值作残差分析，取得了一定效果。 相似文献
17.
No study has systematically evaluated streamflow modelling between monthly and daily time scales. This study examines streamflow from seven watersheds across the USA where five different precipitation products were used as primary input into the Soil and Water Assessment Tool (SWAT) to generate simulated streamflow. Time scales examined include monthly, dekad (10 days), pentad (5 days), triad (3 days), and daily. The seven basins studied are the San Pedro (Arizona), Cimarron (north‐central Oklahoma), mid‐Nueces (south Texas), mid‐Rio Grande (south Texas and northern Mexico), Yocano (northern Mississippi), Alapaha (south Georgia), and mid‐St. Francis (eastern Arkansas). The precipitation products used to drive simulations include rain gauge, NWS Multisensor Precipitation Estimator, Tropical Rainfall Measurement Mission (TRMM), Multi‐Satellite Precipitation Analysis, TRMM 3B42‐V6, and Climate Prediction Center Morphing Method (CMORPH). Understanding how streamflow varies at sub‐monthly time scales is important because there are a host of hydrological applications such a flood forecast guidance and reservoir inflow forecasts that reside in a temporal domain between monthly and daily time scales. The major finding of this study is the quantification of a strong positive correlation between performance metrics and time step at which model performance deteriorates. Better performing simulations, with higher Nash–Sutcliffe values of 0.80 and above can support modeling at finer time scales to at least daily and perhaps beyond into the sub‐daily realm. These findings are significant in that they clearly document the ability of SWAT to support modeling at sub‐monthly time steps, which is beyond the capability for which SWAT was initially designed. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
18.
Hamzeh H. Ramadan 《水文科学杂志》2013,58(8):1516-1529
Abstract Streamflow variability in the Upper and Lower Litani basin, Lebanon was modelled as there is a lack of long-term measured runoff data. To simulate runoff and streamflow, daily rainfall was derived using a stochastic rainfall generation model and monthly rainfall data. Two distinct synthetic rainfall models were developed based on a two-part probabilistic distribution approach. The rainfall occurrence was described by a Markov chain process, while the rainfall distribution on wet days was represented by two different distributions (i.e. gamma and mixed exponential distributions). Both distributions yielded similar results. The rainfall data were then processed using water balance and routing models to generate daily and monthly streamflow. Compared with measured data, the model results were generally reasonable (mean errors ranging from 0.1 to 0.8?m3/s at select locations). Finally, the simulated monthly streamflow data were used to investigate discharge trends in the Litani basin during the 20th century using the Mann-Kendall and Sen slope nonparametric trend detection methods. A significant drying trend of the basin was detected, reaching a streamflow reduction of 0.8 and 0.7 m3/s per decade in January for the Upper and Lower basin, respectively. Editor D. Koutsoyiannis; Associate editor Sheng Yue Citation Ramadan, H.H., Beighley, R.E., and Ramamurthy, A.S., 2012. Modelling streamflow trends for a watershed with limited data: case of the Litani basin, Lebanon. Hydrological Sciences Journal, 57 (8), 1516–1529. 相似文献
19.
Abstract The study of precipitation trends is critically important for a country like India whose food security and economy are dependent on the timely availability of water. In this work, monthly, seasonal and annual trends of rainfall have been studied using monthly data series of 135 years (1871–2005) for 30 sub-divisions (sub-regions) in India. Half of the sub-divisions showed an increasing trend in annual rainfall, but for only three (Haryana, Punjab and Coastal Karnataka), this trend was statistically significant. Similarly, only one sub-division (Chattisgarh) indicated a significant decreasing trend out of the 15 sub-divisions showing decreasing trend in annual rainfall. In India, the monsoon months of June to September account for more than 80% of the annual rainfall. During June and July, the number of sub-divisions showing increasing rainfall is almost equal to those showing decreasing rainfall. In August, the number of sub-divisions showing an increasing trend exceeds those showing a decreasing trend, whereas in September, the situation is the opposite. The majority of sub-divisions showed very little change in rainfall in non-monsoon months. The five main regions of India showed no significant trend in annual, seasonal and monthly rainfall in most of the months. For the whole of India, no significant trend was detected for annual, seasonal, or monthly rainfall. Annual and monsoon rainfall decreased, while pre-monsoon, post-monsoon and winter rainfall increased at the national scale. Rainfall in June, July and September decreased, whereas in August it increased, at the national scale. Citation Kumar, V., Jain, S. K. & Singh, Y. (2010) Analysis of long-term rainfall trends in India. Hydrol. Sci. J. 55(4), 484–496. 相似文献
20.
Drought is a recurring feature of the climate, responsible for social and economic losses in India. In the present work, attempts were made to estimate the drought hazard and risk using spatial and temporal datasets of Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS) in integration with socio-economic vulnerability. The TRMM rainfall was taken into account for trend analysis and Standardized Precipitation Index (SPI) estimation, with aim to investigate the changes in rainfall and deducing its pattern over the area. The SPI and average rainfall data derived from TRMM were interpolated to obtain the spatial and temporal pattern over the entire South Bihar of India, while the MODIS datasets were used to derive the Normalized Difference Vegetation Index (NDVI) deviation in the area. The Geographical Information System (GIS) is taken into account to integrate the drought vulnerability and hazard, in order to estimate the drought risk over entire South Bihar. The results indicated that approximately 36.90% area is facing high to very high drought risk over north-eastern and western part of South Bihar and need conservation measurements to combat this disaster. 相似文献