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1.
Impact of warmer climate on melt and evaporation for the rainfed, snowfed and glacierfed basins in the Himalayan region 总被引：9，自引：0，他引：9
The impact of warmer climate on melt and evaporation was studied for rainfed, snowfed and glacierfed basins located in the western Himalayan region. Hydrological processes were simulated under current climatic conditions using a conceptual hydrological model, which accounts for the rainfall–runoff, evaporation losses, snow and glacier melt. After simulations of daily observed streamflow (R2=0.90) for 6 years, the model was used to study the impact of warmer climate on melt and evaporation. Based on the future projected climatic scenarios in the study region, three temperature scenarios (T+1, T+2 and T+3 °C) were adopted for quantifying the effect of warmer climate. The comparison of the effect of warmer climate on different types of basins indicated that the increase in evaporation was the maximum for snowfed basins. For a T+2 °C scenario, the annual evaporation for the rainfed basins increased by about 12%, whereas for the snowfed basins it increased by about 24%. The high increase of the evaporation losses would reduce the runoff. It was found that under a warmer climate, melt was reduced from snowfed basins, but increased from glacierfed basins. For a T+2 °C scenario, annual melt was reduced by about 18% for the studied snowfed basin, while it increased by about 33% for the glacierfed basin. Thus, impact of warmer climate on the melt from the snowfed and glacierfed basins was opposite to each other. The study suggests that out of three types of basins, snowfed basins are more sensitive in terms of reduction in water availability due to a compound effect of increase in evaporation and decrease in melt. For a complex type of basin, the decrease in melt from seasonal snow may be counterbalanced by increase in melt from glaciers. However, on long-term basis, when the areal extent of glaciers will decrease due to higher melt rate, the water availability from the complex basins will be reduced. 相似文献
2.
The assimilation of Earth observation (EO) data into crop models has proven to be an efficient way to improve yield prediction at a regional scale by estimating key unknown crop management practices. However, the efficiency of prediction depends on the uncertainty associated with the data provided to crop models, particularly climatic data and soil physical properties. In this study, the performance of the STICS (Simulateur mulTIdisciplinaire pour les Cultures Standard) crop model for predicting corn yield after assimilation of leaf area index derived from EO data was evaluated under different scenarios. The scenarios were designed to examine the impact of using fine-resolution soil physical properties, as well as the impact of using climatic data from either one or four weather stations across the region of interest. The results indicate that when only one weather station was used, the average annual yield by producer was predicted well (absolute error <5%), but the spatial variability lacked accuracy (root mean square error = 1.3 t ha−1). The model root mean square error for yield prediction was highly correlated with the distance between the weather stations and the fields, for distances smaller than 10 km, and reached 0.5 t ha−1 for a 5-km distance when fine-resolution soil properties were used. When four weather stations were used, no significant improvement in model performance was observed. This was because of a marginal decrease (30%) in the average distance between fields and weather stations (from 10 to 7 km). However, the yield predictions were improved by approximately 15% with fine-resolution soil properties regardless of the number of weather stations used. The impact of the uncertainty associated with the EO-derived soil textures and the impact of alterations in rainfall distribution were also evaluated. A variation of about 10% in any of the soil physical textures resulted in a change in dry yield of 0.4 t ha−1. Changes in rainfall distribution between two abundant rainfalls during the growing season led to a significant change in yield (0.5 t ha−1 on average). Our results highlight the importance of using fine-resolution gridded daily precipitation data to capture spatial variations of rainfall as well as using fine-resolution soil properties instead of coarse-resolution soil properties from the Canadian soil dataset, especially for regions with high pedodiversity. 相似文献
3.
Chandrashekhar M. Biradar Prasad S. Thenkabail Praveen Noojipady Yuanjie Li Venkateswarlu Dheeravath Hugh Turral Manohar Velpuri Murali K. Gumma Obi Reddy P. Gangalakunta Xueliang L. Cai Xiangming Xiao Mitchell A. Schull Ranjith D. Alankara Sarath Gunasinghe Sadir Mohideen 《International Journal of Applied Earth Observation and Geoinformation》2009
The overarching goal of this study was to produce a global map of rainfed cropland areas (GMRCA) and calculate country-by-country rainfed area statistics using remote sensing data. A suite of spatial datasets, methods and protocols for mapping GMRCA were described. These consist of: (a) data fusion and composition of multi-resolution time-series mega-file data-cube (MFDC), (b) image segmentation based on precipitation, temperature, and elevation zones, (c) spectral correlation similarity (SCS), (d) protocols for class identification and labeling through uses of SCS R2-values, bi-spectral plots, space-time spiral curves (ST-SCs), rich source of field-plot data, and zoom-in-views of Google Earth (GE), and (e) techniques for resolving mixed classes by decision tree algorithms, and spatial modeling. The outcome was a 9-class GMRCA from which country-by-country rainfed area statistics were computed for the end of the last millennium. The global rainfed cropland area estimate from the GMRCA 9-class map was 1.13 billion hectares (Bha). The total global cropland areas (rainfed plus irrigated) was 1.53 Bha which was close to national statistics compiled by FAOSTAT (1.51 Bha). The accuracies and errors of GMRCA were assessed using field-plot and Google Earth data points. The accuracy varied between 92 and 98% with kappa value of about 0.76, errors of omission of 2–8%, and the errors of commission of 19–36%. 相似文献
4.
From rainfed agriculture to stress-avoidance irrigation: I. A generalized irrigation scheme with stochastic soil moisture 总被引：1，自引：0，他引：1
With vast regions already experiencing water shortages, it is becoming imperative to manage sustainably the available water resources. As agriculture is by far the most important user of freshwater and the role of irrigation is projected to increase in face of climate change and increased food requirements, it is particularly important to develop simple, widely applicable models of irrigation water needs for short- and long-term water resource management. Such models should synthetically provide the key irrigation quantities (volumes, frequencies, etc.) for different irrigation schemes as a function of the main soil, crop, and climatic features, including rainfall unpredictability. Here we consider often-employed irrigation methods (e.g., surface and sprinkler irrigation systems, as well as modern micro-irrigation techniques) and describe them under a unified conceptual and theoretical framework, which includes rainfed agriculture and stress-avoidance irrigation as extreme cases. We obtain mostly analytical solutions for the stochastic steady state of soil moisture probability density function with random rainfall timing and amount, and compute water requirements as a function of climate, crop, and soil parameters. These results provide the necessary starting point for a full assessment of irrigation strategies, with reference to sustainability, productivity, and profitability, developed in a companion paper [Vico G, Porporato A. From rainfed agriculture to stress-avoidance irrigation: II. Sustainability, crop yield, and net profit. Adv Water Resour 2011;34(2):272-81]. 相似文献
5.
A drought index is one of the main methods used for measuring drought and represents the basis of drought monitoring, early warning, and classification. On the basis of an analysis of the advantages and limitations of the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Crop Evapotranspiration Index (SPCEI), which is a drought index of rainfed agriculture, was constructed in this study. The applicable conditions of the SPCEI were then investigated, and the results showed that the SPCEI was suitable for dryland crops under non‐irrigated conditions in arid and semi‐arid areas. The difference between the SPEI and SPCEI is analysed. Compared with the SPEI, the SPCEI considers crop evapotranspiration and the crop growth stage and was found to be more suitable for monitoring agricultural drought. Qigihar, which is located in a semi‐arid area in western Heilongjiang Province, China, was then analysed as an example. The characteristics of the spatial and temporal variability of regional agricultural drought were analysed based on maize and soybean in dryland areas. The results for the different growth stages of maize and soybean showed that drought intensity is more serious in the initial stage in the middle part. In crop development, mid‐season and late season stage, the drought conditions gradually increased from north to south. The drought degree of the two crops at the initial stage gradually increased, and the drought degree at the crop development stage gradually decreased. The main reason is that precipitation gradually increases during the crop development stage. 相似文献
6.
植被状态指数监测西北干旱的适用性分析 总被引：7，自引：2，他引：5
利用1982—2003年22年逐月GIMMS 8 km分辨率的NDVI数据和西北地区138个气象台站同期月降水数据,分析了植被状态指数(VCI)对西北地区历史干旱的监测能力。根据西北气候和植被类型的特点,选取雨养农业区、灌溉农业区和青藏高原高寒草原区为典型研究区域,研究了VCI对不同地区气象干旱的监测能力,并对VCI监测干旱的适应性进行分析。结果表明:VCI可以较好地反映西北大部分历史干旱的空间分布及其演变特征。对于不同的气候区域,VCI监测干旱的效果存在一定的差别。对于西北东部的雨养农业区,VCI能够较好地反映降水的盈亏对植被影响,是监测这一地区干旱的有效指标;在西北区西部的灌溉农业区,VCI基本不能反映这一地区降水的多寡,不能作为这些地区气象干旱监测的指标;VCI也不能反映青藏高原高寒草原区降水的亏缺,不能作为监测这些地区气象干旱的指标;在极涡干旱的戈壁、沙漠地区VCI会出现虚假的高值。 相似文献
7.
Surface soil water content plays an important role in driving the exchange of latent and sensible heat between the atmosphere and land surface through transpiration and evaporation processes, regulating key physiological processes affecting plants growth. Given the high impact of water scarcity on yields, and of irrigated agriculture on the overall withdrawal rate of freshwater, it is important to define models that help to improve water resources management for agricultural purposes, and to optimize rainfed crop yield. Recent advances in satellite-based remote sensing have led to valuable solutions to estimate soil water content based on microwave or optical/thermal-infrared data. This study aims at improving soil water content estimation at high spatial and temporal resolution, by means of the Optical Trapezoid Model (OPTRAM) driven by Copernicus Sentinel-2 data. Two different model variations were considered, based on linear and nonlinear parameters constraints, and validated against in situ soil water content measurements made with time domain reflectometry (TDR) on irrigated maize in central Italy and on rainfed maize and pasture in northern Italy. For the first site the non-linear model shows a better correlation between measured and estimated soil water content values (r = 0.80) compared to the linear model (r = 0.73). In both cases the modeled soil moisture tends to overestimate the measured values at medium to high water content level, while both models underestimate soil moisture at low water content level. Estimated versus measured normalized surface soil water for rainfed pasture plots from nonlinear OPTRAM parametrized based on irrigated maize parameterization (SIM1), and site-specific parametrization for rainfed pasture (SIM2), indicate that both models (SIM1 and SIM2) are comparable for rotational grazing pasture (RMSEsim1 = 0.0581 vs. RMSEsim2 = 0.0485 cm3 cm-3) and the continuous grazing pasture (RMSEsim1 = 0.0485 vs. RMSEsim2 = 0.0602 cm3 cm-3), while for the rainfed maize plots SIM1 shows lower RMSE (average for all plots RMSE = 0.0542 cm3 cm-3) compared to the site-specific calibration model (SIM2 – average for all plots RMSE = 0.0645 cm3 cm-3). Finally, OPTRAM estimations are close to in situ measurement values while Surface Soil Moisture at 1 km (SSM1 km) tends to underestimate the measurements during maize crop growing season. Soil moisture retrieval from high-resolution Sentinel-2 optical images allows water stress conditions to be effectively mapped, supporting decision making in irrigation scheduling and other crop management. 相似文献
8.
9.
地表反照率动态参数化对陆-气通量模拟的影响：以东北玉米农田为例 总被引：1，自引：1，他引：0
利用考虑了生物因子(叶面积指数)和环境因子(太阳高度角、表层土壤湿度)影响的地表反照率α动态参数化方案对BATS1e模型进行改进,基于2008年玉米农田生态系统的通量、气象及生物因子的连续观测资料,研究α动态参数化对玉米农田生态系统与大气间通量交换的影响.结果表明,引入α动态参数化方案后,模型实现了地表反照率α的日、季动态模拟,模型效率系数提高0.65,误差明显减小,使陆气通量交换热力作用的模拟准确性有所提高,其中,净入射短波辐射模拟改进最为明显,全年改进量为81772 kJ/m2,占年总辐射的1.7％;表层土壤温度的年均改进量为0.62 K,多数月份的改进量在1 K以上.另外,模型改进实现了叶面积指数和植被覆盖度等决定下垫面性质各参数的动态变化,使各种通量交换过程更接近于实际,感热和潜热模拟的模型效率系数分别提高0.516和0.1,模拟值对实测值的解释能力在生长季分别提高6％和9％,大于非生长季. 相似文献
10.
Environmental, biological, socio-cultural and economic status variation existing in the Central Himalaya have led to the evolution
of diverse and unique traditional agroecosystems, crop species and livestock, which facilitate the traditional mountain farming
societies to sustain themselves. Indigenous agroecosystems are highly site specific and differ from place to place, as they
have evolved along divergent lines. For maintenance of traditional agrodiversity management the farmers of the Central Himalaya
have evolved various types of crop rotations in consonance with the varied environmental conditions and agronomic requirements.
In irrigated flat lands two crops are harvested in a year with negligible fallow period but in rainfed conditions if a cropping
sequence is presumed to be starting after winter fallow phase then four major cropping seasons can be identified namely first
kharif season (first crop season), first rabi season (second crop season), second kharif season (third crop season) and second
rabi season (fourth crop season). Highest crop diversity is present in kharif season in comparison to rabi season. Traditionally
the fields are left fallow after harvest of the second kharif season crop. Important characteristics of agrodiversity management
are the use of bullocks for draught power, human energy as labour, crop residues as animal feed and animal waste mixed with
forest litter as organic input to restore soil fertility levels. Women provide most of the human labour except for ploughing
and threshing grain. The present study deals with assessment of traditional agrodiversity management such as (i) crop diversity,
(ii) realized yield under the traditional practices and (iii) assess the differences of realized yields under sole and mixed
cropping systems. It indicated that crop rotation is an important feature of the Central Himalayan village ecosystem which
helps to continue the diversity of species grown, as are the distribution of crops in the growing period and the management
of soil fertility. The cropping diversity existing and the sequences practiced by the traditional farmers seems to have achieved
high degree of specialization and thus even when the yield/biomass variations are about 60%, the farmers continue to practice
these sequences as they need to maintain diversity and synergistic relationships of crops in addition to manage the food and
labour requirements for crop husbandry. Crop yields are generally higher in irrigated systems than rainfed systems and in
sole cropping as compared with mixed cropping. However, gross biological and economic yields are higher in mixed cropping
than sole cropping systems. 相似文献