Eurasian snow cover and seasonal forecast of Indian summer monsoon rainfall

Abstract

This paper presents the relationship between Indian summer monsoon total rainfall and two parameters from Eurasian snow cover, one being the winter snow cover extent and the other the area of spring snowmelt. Satellite-derived Eurasian snow cover extent and Indian monsoon rainfall data were obtained from the NOAA/NESDIS and the India Meteorological Department (IMD) for the period 1966–1985. Seasonal cyclic variations of snow cover showed a higher swing in both the winter and the spring seasons of the cycle as compared to the remaining seasons of the year in the lower region of the cycle. The established inverse relation between winter snow cover and monsoon rainfall during June to September is further extended. Winter snow cover is very strongly correlated with spring snowmelt over Eurasia. Spring snowmelt area is obtained by subtracting the May snow cover extent from that of the previous February. The variations of spring snowmelt were also compared with Indian total monsoon rainfall. The detected correlation is stronger between snowmelt and monsoon rainfall than between the winter snow cover and the monsoon rainfall. There is also a significant multiple correlation among winter snow cover, spring snowmelt and monsoon rainfall. Lastly, a significant multiple correlation suggested a multiple regression equation which might improve the climatic prediction of monsoon rainfall over India.     

A study on rainfall,runoff,and soil loss relations at different landuses-A case in Hilkot watershed in Pakistan

Reliable field data for all hydrologic parameters are often unavailable for watersheds even for those intensively monitored.In the absence of reliable such data,verified mathematical relations for an area can be used for other areas with same hydrologic and climatic regimes.The objectives of this research were:1) to assess the total runoff and sediment loss,and 2) to develop rainfall,runoff and soil loss relations for four prominent landuses(including degraded,pasture,forest and agriculture lands) in the Hilkot watershed(Pakistan).Four experimental natural runoff plots were established on the landuses (degraded,pasture,forest and agriculture land).The field study and data collection were conducted in the Hilkot watershed from 1999 to 2005.Regression analysis was conducted to establish relations among rainfall,runoff and soil loss for all landuses using.Regression analysis indicated good correlation with field data.     

Assessing the effect of climate change on mean annual runoff in the Songhua River basin,China

Influences of climatic change on the components of global hydrological cycle, including runoff and evapotranspiration are significant in the mid‐ and high‐latitude basins. In this paper, the effect of climatic change on annual runoff is evaluated in a large basin—Songhua River basin which is located in the northeast of China. A method based on Budyko‐type equation is applied to separate the contributions of climatic factors to changes in annual runoff from 1960 to 2008, which are computed by multiplying their partial derivatives by the slopes of trends in climate factors. Furthermore, annual runoff changes are predicted under IPCC SRES A2 and B2 scenarios with projections from five GCMs. The results showed that contribution of annual precipitation to annual runoff change was more significant than that of annual potential evapotranspiration in the Songhua River basin; and the factors contributing to annual potential evapotranspiration change were ranked as temperature, wind speed, vapour pressure, and sunshine duration. In the 2020s, 2050s, and 2080s, changes in annual runoff estimated with the GCM projections exhibited noticeable difference and ranged from ? 8·4 to ? 16·8 mm a^?1 (?5·77 to ? 11·53% of mean annual runoff). Copyright © 2011 John Wiley & Sons, Ltd.     

Prediction of limestone solution rates from rainfall and runoff data: Some comments

Recent work by Láng (1977) on solutional erosion rates in limestone drainage basins in relation to rainfall contains serious errors and has a questionable logical basis. Although much sounder, Smith and Atkinson's (1976) work on erosion rates in relation to runoff also requires modification as it greatly overestimates erosion rates in two areas of New Zealand. Greater resolution could probably be obtained by relating autogenic runoff to the rate of solution by autogenic waters and by computing separate relationships for areas where solution takes place under open and closed system equilibrium conditions. These factors should be taken into account in the experimental design of future studies.     

Exploitation of Landsat data for snow zonation mapping in the Hindukush,Karakoram and Himalaya (HKH) region of Pakistan

Abstract

In the Hindukush, Karakoram and Himalaya (HKH) region of Pakistan, many glaciological variables are still not known due to the remoteness and harsh weather conditions of the area. A remote sensing technique is therefore applied to map the snow zonation in the HKH region. Landsat 7 ETM+ data for the year 2003 are used in this study. Image classification and image processing techniques are applied to map, for the first time, the major snow zones in the HKH region. Six classes are identified: the results show that the area covered by the highest-altitude snow (Snow I), lower-altitude snow (Snow II), bare ice, debris-covered ice, wet snow and shadow is 21 529.42, 22 472.58, 8696.41, 8038.75, 12 159.37 and 7322.30 km², respectively. The study also indicates that the equilibrium line altitude (ELA) lies between 5000 and 5500 m above sea level, with an accumulation area ratio (AAR) of 0.60.

Citation Butt, M.J., 2013. Exploitation of Landsat data for snow zonation mapping in the Hindukush, Karakoram and Himalaya (HKH) region of Pakistan. Hydrological Sciences Journal, 58 (5), 1088–1096.     

The implications of permafrost thaw and land cover change on snow water equivalent accumulation,melt and runoff in discontinuous permafrost peatlands

In the discontinuous permafrost zone of the Northwest Territories (NWT), Canada, snow covers the ground surface for half the year. Snowmelt constitutes a primary source of moisture supply for the short growing season and strongly influences stream hydrographs. Permafrost thaw has changed the landscape by increasing the proportional coverage of permafrost-free wetlands at the expense of permafrost-cored peat plateau forests. The biophysical characteristics of each feature affect snow water equivalent (SWE) accumulation and melt rates. In headwater streams in the southern Dehcho region of the NWT, snowmelt runoff has significantly increased over the past 50 years, despite no significant change in annual SWE. At the Fort Simpson A climate station, we found that SWE measurements made by Environment and Climate Change Canada using a Nipher precipitation gauge were more accurate than the Adjusted and Homogenized Canadian Climate Dataset which was derived from snow depth measurements. Here, we: (a) provide 13 years of snow survey data to demonstrate differences in end-of-season SWE between wetlands and plateau forests; (b) provide ablation stake and radiation measurements to document differences in snow melt patterns among wetlands, plateau forests, and upland forests; and (c) evaluate the potential impact of permafrost-thaw induced wetland expansion on SWE accumulation, melt, and runoff. We found that plateaus retain significantly (p < 0.01) more SWE than wetlands. However, the differences are too small (123 mm and 111 mm, respectively) to cause any substantial change in basin SWE. During the snowmelt period in 2015, wetlands were the first feature to become snow-free in mid-April, followed by plateau forests (7 days after wetlands) and upland forests (18 days after wetlands). A transition to a higher percentage cover of wetlands may lead to more rapid snowmelt and provide a more hydrologically-connected landscape, a plausible mechanism driving the observed increase in spring freshet runoff.     

The isotopic signature of monsoon conditions,cloud modes,and rainfall type

This work provides a comprehensive physically based framework for the interpretation of the north Australian rainfall stable isotope record (δ¹⁸O and δ²H). Until now, interpretations mainly relied on statistical relationships between rainfall amount and isotopic values on monthly timescales. Here, we use multiseason daily rainfall stable isotope and high resolution (10 min) ground‐based C‐band polarimetric radar data and show that the five weather types (monsoon regimes) that constitute the Australian wet season each have a characteristic isotope ratio. The data suggest that this is not only due to changes in regional rainfall amount during these regimes but, more importantly, is due to different rain and cloud types that are associated with the large scale circulation regimes. Negative (positive) isotope anomalies occurred when stratiform rainfall fractions were large (small) and the horizontal extent of raining areas were largest (smallest). Intense, yet isolated, convective conditions were associated with enriched isotope values whereas more depleted isotope values were observed when convection was widespread but less intense. This means that isotopic proxy records may record the frequency of which these typical wet season regimes occur. Positive anomalies in paleoclimatic records are most likely associated with periods where continental convection dominates and convection is sea‐breeze forced. Negative anomalies may be interpreted as periods when the monsoon trough is active, convection is of the oceanic type, less electric, and stratiform areas are wide spread. This connection between variability of rainfall isotope anomalies and the intrinsic properties of convection and its large‐scale environment has important implications for all fields of research that use rainfall stable isotopes.     

Use of soil moisture data and curve number method for estimating runoff in the Loess Plateau of China

The Soil Conservation Service curve number (CN) method commonly uses three discrete levels of soil antecedent moisture condition (AMC), defined by the 5‐day antecedent rainfall depth, to describe soil moisture prior to a runoff event. However, this way may not adequately represent soil water conditions of fields and watersheds in the Loess Plateau of China. The objectives of this study were: (1) to determine the effective soil moisture depth to which the CN is most related; (2) to evaluate a discrete and a linear relationship between AMC and soil moisture; and (3) to develop an equation between CN and soil moisture to predict runoff better for the climatic and soil conditions of the Loess Plateau of China. The dataset consisted of 10 years of rainfall, runoff and soil moisture measurements from four experimental plots cropped with millet, pasture and potatoes. Results indicate that the standard CN method underestimated runoff depths for 85 of the 98 observed plot‐runoff events, with a model efficiency E of only 0·243. For our experimental conditions, the discrete and linear approaches improved runoff estimation, but still underestimated most runoff events, with E values of 0·428 and 0·445 respectively. Based on the measured CN values and soil moisture values in the top 15 cm of the soil, a non‐linear equation was developed that predicted runoff better with an E value of 0·779. This modified CN equation was the most appropriate for runoff prediction in the study area, but may need adjustments for local conditions in the Loess Plateau of China. Copyright © 2006 John Wiley & Sons, Ltd.     

Long‐term change of seasonal snow cover and its effects on river runoff in the Tarim River basin,northwestern China

Spatio‐temporal variation of snow depth in the Tarim River basin has been studied by the empirical orthogonal function (EOF) based on the data collected by special sensor microwave/imager (SSM/I) and scanning multichannel microwave radiometer (SMMR) during the period from 1979 to 2005. The long‐term trend of snow depth and runoff was presented using the Mann‐Kendall non‐parametric test, and the effects of the variations of snow depth and climatic factors on runoff were analysed and discussed by means of the regression analysis. The results suggested that the snow depth variation on the entire basin was characterised by four patterns: all consistency, north–south contrast, north‐middle‐south contrast and complex. The first pattern accounting 39·13% of the total variance was dominant. The entire basin was mainly affected by one large‐scale weather system. However, the spatial and temporal differences also existed among the different regions in the basin. The significant snow depth changes occurred mainly in the Aksu River basin with the below‐normal snow depth anomalies in the 1980s and the above‐normal snow depth anomalies in the 1990s. The long‐term trend of snow depth was significant in the northwestern, western and southern parts of the basin, whereas the long‐term trend of runoff was significant in the northwestern and northeastern parts. The regression analysis revealed that the runoff of the rivers replenished by snow melt water and rainfall was related primarily to the summer precipitation, followed by the summer temperature or the maximum snow depth in the cold season. Our results suggest that snow is not the principal factor that contributes to the runoff increase in headstreams, although there was a slow increase in snow depth. It is the climatic factors that are responsible for the steady and continuous water increase in the headstreams. Copyright © 2009 John Wiley & Sons, Ltd.     

Spatiotemporal estimation of snow depth using point data from snow stakes,digital terrain models,and satellite data

Snow availability in Alpine catchments plays an important role in water resources management. In this paper, we propose a method for an optimal estimation of snow depth (areal extension and thickness) in Alpine systems from point data and satellite observations by using significant explanatory variables deduced from a digital terrain model. It is intended to be a parsimonious approach that may complement physical‐based methodologies. Different techniques (multiple regression, multicriteria analysis, and kriging) are integrated to address the following issues: We identify the explanatory variables that could be helpful on the basis of a critical review of the scientific literature. We study the relationship between ground observations and explanatory variables using a systematic procedure for a complete multiple regression analysis. Multiple regression models are calibrated combining all suggested model structures and explanatory variables. We also propose an evaluation of the models (using indices to analyze the goodness of fit) and select the best approaches (models and variables) on the basis of multicriteria analysis. Estimation of the snow depth is performed with the selected regression models. The residual estimation is improved by applying kriging in cases with spatial correlation. The final estimate is obtained by combining regression and kriging results, and constraining the snow domain in accordance with satellite data. The method is illustrated using the case study of the Sierra Nevada mountain range (Southern Spain). A cross‐validation experiment has confirmed the efficiency of the proposed procedure. Finally, although it is not the scope of this work, the snow depth is used to asses a first estimation of snow water equivalent resources.     

Evaluation and comparison of interpolated gauge rainfall data and gridded rainfall data in Florida,USA

A variety of spatially continuous rainfall products are available but little evaluation of their accuracy has been published for areas with high spatial variability in rainfall. Five gridded rainfall products (PRISM, RTMA, and the interpolated Florida Automated Weather Network, FAWN, rainfall layers based on three interpolated methods) were assessed for Florida State. Point-to-pixel and pixel-to-pixel comparisons were performed to compare the five products. On average, the PRISM and RTMA products resulted in a better fit with the daily FAWN rainfall datasets, while FAWN-based interpolated products resulted in a better fit with the monthly FAWN rainfall datasets based on point-to-pixel analysis. Inverse distance weighting and ordinary kriging methods performed slightly better than the thin plate spline method in predicting daily rainfall. In general, monthly and seasonal rainfall amounts from PRISM and RTMA products were higher and lower, respectively, than reference rainfall amounts from FAWN gauge stations and FAWN-based interpolated products.     

Projection of glacier runoff in Yarkant River basin and Beida River basin,Western China

Potential changes in glacier area, mass balance and runoff in the Yarkant River Basin (YRB) and Beida River Basin (BRB) are projected for the period from 2011 to 2050 employing the modified monthly degree‐day model forced by climate change projection. Future monthly air temperature and precipitation were derived from the simple average of 17, 16 and 17 General Circulation Model (GCM) projections following the A1B, A2 and B1 scenarios, respectively. These data were downscaled to each station employing the Delta method, which computes differences between current and future GCM simulations and adds these changes to observed time series. Model parameters calibrated with observations or results published in the literature between 1961 and 2006 were kept unchanged. Annual glacier runoff in YRB is projected to increase until 2050, and the total runoff over glacier area in 1970 is projected to increase by about 13%–35% during 2011–2050 relative to the average during 1961–2006. Annual glacier runoff and the total runoff over glacier area in 1970 in BRB is projected to increase initially and then to reach a tipping point during 2011–2030. There are prominent increases in summer, but only small increase in May and October of glacier runoff in YRB, and significant increases during late spring and early summer and significant decreases in July and late summer of glacier runoff in BRB. This study highlights the great differences among basins in their response to future climate warming. The specific runoff from areas exposed after glacier retreat relative to 1970 is projected to general increasing, which must be considered when evaluating the potential change of glacier runoff. Copyright © 2011 John Wiley & Sons, Ltd.     

Relative importance of advective heat transport and boundary layer decoupling in the melt dynamics of a patchy snow cover

For a patchy snow cover the advective heat transport and the near-surface boundary layer decoupling, which have an opposite effect on sensible heat transport onto the snow surface, are both expected to increase in magnitude. The main aim of this study is to investigate the effects of locally developing atmospheric stratification over a discontinuous snow cover which can result in a decoupling from the warm atmosphere. We are particularly interested in the effect of boundary layer decoupling on the net sensible heat flux into the snow. We therefore applied local eddy flux measurements over snow patches at three different heights above the snow surface. We identified wind velocity, turbulence intensity, fetch distance and topographical curvature as the main factors driving the boundary layer depth and the efficiency of advective heat transport to contribute to snow ablation. The atmospheric decoupling is thus shown to be a key mechanism in snow patch survival.     

Effects of rainfall intensity fluctuations on infiltration and runoff: rainfall simulation on dryland soils,Fowlers Gap,Australia

Small plots and a dripper rainfall simulator were used to explore the significance of the intensity fluctuations (‘event profile’) within simulated rainfall events on infiltration and runoff from bare, crusted dryland soils. Rainfall was applied at mean rain rates of 10 mm/h. Fourteen simulated rainfall events each involved more than 5000 changes of intensity and included multipeak events with a 25‐mm/h peak of intensity early in the event or late in the event and an event that included a temporary cessation of rain. These are all event profiles commonly seen in natural rain but rarely addressed in rainfall simulation. A rectangular event profile of constant intensity, as commonly used in rainfall simulation experiments, was also adopted for comparative purposes. Results demonstrate that event profile exerts an important effect on infiltration and runoff for these soils and rainfall event profiles. ‘Uniform’ events of unvarying intensity yielded the lowest total runoff, the lowest peak runoff rate and the lowest runoff ratio (0.13). These parameters increased for ‘early peak’ profiles (runoff ratio 0.24) and reached maxima for ‘late peak’ profiles (runoff ratio 0.50). Differences in runoff ratio and peak runoff rate between the ‘uniform’ event profile and those of varying intensity were all statistically significant at p ≤ 0.01. Compared with ‘uniform’ runs, the varying intensity runs yielded larger runoff ratios and peak runoff rates, exceeding those of the ‘uniform’ events by 85%–570%. These results suggest that for small‐plot studies of infiltration and erosion, the continued use of constant rainfall intensity simulations may be sacrificing important information and misrepresenting the mechanisms involved in runoff generation. The implications of these findings for the ecohydrology of the research site, an area of contour‐aligned banded vegetation in which runoff and runon are of critical importance, are highlighted. Copyright © 2011 John Wiley & Sons, Ltd.     

Identification of best predictors for forecasting seasonal rainfall and runoff in Australia

The first step towards developing a reliable seasonal runoff forecast is identifying the key predictors that drive rainfall and runoff. This paper investigates the lag relationships between rainfall across Australia and runoff across southeast Australia versus 12 atmospheric‐oceanic predictors, and how the relationships change over time. The analysis of rainfall data indicates that the relationship is greatest in spring and summer in northeast Australia and in spring in southeast Australia. The best predictors for spring rainfall in eastern Australia are NINO4 [sea surface temperature (SST) in western Pacific] and thermocline (20 °C isotherm of the Pacific) and those for summer rainfall in northeast Australia are NINO4 and Southern Oscillation Index (SOI) (pressure difference between Tahiti and Darwin). The relationship in northern Australia is greatest in spring and autumn with NINO4 being the best predictor. In western Australia, the relationship is significant in summer, where SST2 (SST over the Indian Ocean) and II (SST over the Indonesian region) is the best predictor in the southwest and northwest, respectively. The analysis of runoff across southeast Australia indicates that the runoff predictability in the southern parts is greatest in winter and spring, with antecedent runoff being the best predictor. The relationship between spring runoff and NINO4, thermocline and SOI is also relatively high and can be used together with antecedent runoff to forecast spring runoff. In the northern parts of southeast Australia, the atmospheric‐oceanic variables are better predictors of runoff than antecedent runoff, and have significant correlation with winter, spring and summer runoff. For longer lead times, the runoff serial correlation is reduced, especially over the northern parts, and the atmospheric‐oceanic variables are likely to be better predictors for forecasting runoff. The correlations between runoff versus the predictors vary with time, and this has implications for the development of forecast relationship that assumes stationarity in the historical data. Copyright © 2010 John Wiley & Sons, Ltd.     

Relative effects of human activities and climate change on the river runoff in an arid basin in northwest China

Understanding the mechanisms of river runoff variation is important for the effective management of water resources in arid and semi‐arid regions. This study uses long‐term observational data as a basis for examining the effects of human activities and climate change on the runoff variation of Jinghe River Basin, a typical arid inland basin in northwest China. A distributed hydrological model called the Soil and Water Assessment Tool, combined with a sequential cluster method and a separation approach, was used to quantify and distinguish the effects of human activities and climate change on runoff. The hydrological sequence before 1981 can be considered natural. However, human activities have significantly affected runoff since 1981. The runoff reduction caused by human activities between 1981 and 2008 accounted for 85.7% of the total reduction in the downstream of Jinghe River, whereas that caused by climatic variation was only 14.3%. This observation suggests that human activities are the major driver of runoff variation in the basin. Although the role of climate change in driving runoff variation has been identified to be prevalent and dominant in arid regions, this study highlights the importance of human activities. Copyright © 2013 John Wiley & Sons, Ltd.     

Validation and use of rainfall radar data to simulate water flows in the Rio Escondido basin

This paper presents a combined validation method of radar-sensed rainfall, using rain gauge data and hydrologic closure, with an application to the Rio Escondido basin (North-East of Mexico). The space–time scaling behavior of rainfall between rain gauge and radar scales is compared with the intrinsic variability of rainfall, for a statistical validation of space–time variability. For hydrological validation purposes, the CEQUEAU model is used to perform rainfall-runoff routing. It provides a basin-wide water balance, to be compared with the measured water flow at the Villa de Fuentes hydrometric station, for mean-value gauging closure. A good qualitative agreement in terms of hydrograph shape and timing is obtained between the simulated and the observed water flows, and a multiplicative correction factor of an initially proposed Z–R relationship is adopted for the watershed under study, which agrees approximately with other authors’ findings about that relationship. The results are considered particularly useful as a validation-and-correction methodology of radar rainfall estimates for areas sparsely covered by rain gauges.     

Small scale spatial variability of snow density and depth over complex alpine terrain: Implications for estimating snow water equivalent

This study analyzes spatial variability of snow depth and density from measurements made in February and April of 2010 and 2011 in three 1–2 km² areas within a valley of the central Spanish Pyrenees. Snow density was correlated with snow depth and different terrain characteristics. Regression models were used to predict the spatial variability of snow density, and to assess how the error in computed densities might influence estimates of snow water equivalent (SWE).The variability in snow depth was much greater than that of snow density. The average snow density was much greater in April than in February. The correlations between snow depth and density were generally statistically significant but typically not very high, and their magnitudes and signs were highly variable among sites and surveys. The correlation with other topographic variables showed the same variability in magnitude and sign, and consequently the resulting regression models were very inconsistent, and in general explained little of the variance. Antecedent climatic and snow conditions prior to each survey help highlight the main causes of the contrasting relation shown between snow depth, density and terrain. As a consequence of the moderate spatial variability of snow density relative to snow depth, the absolute error in the SWE estimated from computed densities using the regression models was generally less than 15%. The error was similar to that obtained by relating snow density measurements directly to adjacent snow depths.     

Infilling of missing rainfall and streamflow data in the Shire River basin,Malawi – A self organizing map approach

A major requirement for the assessment, development and sustainable use of water resources is the availability of good quality hydrological time series data of sufficiently long duration. However, it is not uncommon to find data that are riddled with gaps, characterized by questionable quality and short durations. Sometimes, the data are just not available. Such situations are most prevalent in developing countries and the consequence is a high degree of uncertainty in the assessed characteristics of water management schemes and ultimately its ineffectual performance. Thus dealing with these problems is an important exercise in hydrological analyses. This paper focuses on the multivariate infilling of gaps for rainfall and streamflow data in the Shire River basin in Malawi, using a self organizing map (SOM) approach, which is a form of unsupervised artificial neural networks. The results show that this approach can produce reliable estimates of hydro-meteorological data thus offering promise for reducing the uncertainties associated with the use of insufficient data for water resources assessment.     

Temporal and spatial variation of annual rainfall on the island of Crete,Greece

Annual rainfall records from the island of Crete in Greece were used with the aid of a geographical information system (GIS) to study the temporal and spatial rainfall characteristics. The GIS was used to produce a digital elevation model, delineate watersheds and estimate the areal rainfall from a network of raingauges by using different interpolation schemes. The rainfall–elevation correlation was significant, suggesting an orographic type of precipitation for the island. The rainfall records for the majority of the stations were found to fit the normal distribution. Deviation from normal for the rest of the records was attributed to the wettest year of 1977–1978. The year 1989–1990 was the driest, and most rainfall records showed a decrease in rainfall over 30 years with higher negative rainfall gradients at the higher elevations. Frequency analysis of the rainfall records was used to estimate areal rainfall for the island of Crete and its main watersheds for return periods of 2, 5 and 10 years. Copyright © 2003 John Wiley & Sons, Ltd.