Shabeh ul Hasson

Hydrological cycle over South and Southeast Asian river basins as simulated by PCMDI/CMIP3 experiments

Abstract. We investigate how the climate models contributing to the PCMDI/CMIP3 dataset describe the hydrological cycle over four major South and Southeast Asian river basins (Indus, Ganges, Brahmaputra and Mekong) for the 20th, 21st (13 models) and 22nd (10 models) centuries. For the 20th century, some models do not seem to conserve water at the river basin scale up to a good degree of approximation. The simulated precipitation minus evaporation (P − E), total runoff (R) and precipitation (P) quantities are neither consistent with the observations nor among the models themselves. Most of the models underestimate P − E for all four river basins, which is mainly associated with the underestimation of precipitation. This is in agreement with the recent results on the biases of the representation of monsoonal dynamics by GCMs. Overall, a modest inter-model agreement is found only for the evaporation and inter-annual variability of P − E. For the 21st and 22nd centuries, models agree on the negative (positive) changes of P − E for the Indus basin (Ganges, Brahmaputra and Mekong basins). Most of the models foresee an increase in the inter-annual variability of P − E for the Ganges and Mekong basins, thus suggesting an increase in large low-frequency dry/wet events. Instead, no considerable future change in the inter-annual variability of P − E is found for the Indus and Brahmaputra basins.

Early 21st century snow cover state over the western river basins of the Indus River system

In this paper we assess the snow cover and its dynamics for the western river basins of the Indus River system (IRS) and their sub-basins located in Afghanistan, China, India and Pakistan for the period 2001–2012. First, we validate the Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow products from Terra (MOD10A1) and Aqua (MYD10A1) against the Landsat Thematic Mapper/Enhanced Thematic Mapper plus (TM/ETM+) data set, and then improve them for clouds by applying a validated non-spectral cloud removal technique. The improved snow product has been analysed on a seasonal and annual basis against different topographic parameters (aspect, elevation and slope). Our results show a decreasing tendency for the annual average snow cover for the westerlies-influenced basins (upper Indus basin (UIB), Astore, Hunza, Shigar and Shyok) and an increasing tendency for the monsoon-influenced basins (Jhelum, Kabul, Swat and Gilgit). Seasonal average snow cover decreases during winter and autumn, and increases during spring and summer, which is consistent with the observed cooling and warming trends during the respective seasons. Sub-basins at relatively higher latitudes/altitudes show higher variability than basins at lower latitudes/middle altitudes. Northeastern and northwestern aspects feature greater snow cover. The mean end-of-summer regional snow line altitude (SLA) zones range from 3000 to 5000 m a.s.l. for all basins. Our analysis provides an indication of a descending end-of-summer regional SLA zone for most of the studied basins, which is significant for the Shyok and Kabul basins, thus indicating a change in their water resources. Such results are consistent with the observed hydro-climatic data, recently collected local perceptions and glacier mass balances for the investigated period within the UIB. Moreover, our analysis shows a significant correlation between winter season snow cover and the North Atlantic Oscillation (NAO) index of the previous autumn. Similarly, the inter-annual variability of spring season snow cover and spring season precipitation explains well the inter-annual variability of the summer season discharge from most of the basins. These findings indicate some potential for the seasonal stream flow forecast in the region, suggesting snow cover as a possible predictor.

Seasonality of the hydrological cycle in major South and Southeast Asian river basins as simulated by PCMDI/CMIP3 experiments

Abstract. In this study, we investigate how PCMDI/CMIP3 general circulation models (GCMs) represent the seasonal properties of the hydrological cycle in four major South and Southeast Asian river basins (Indus, Ganges, Brahmaputra and Mekong). First, we examine the skill of the GCMs by analysing their performance in simulating the 20th century climate (1961–2000 period) using historical forcing (20c3m experiment), and then we analyse the projected changes for the corresponding 21st and 22nd century climates under the SRESA1B scenario. The CMIP3 GCMs show a varying degree of skill in simulating the basic characteristics of the monsoonal precipitation regimes of the Ganges, Brahmaputra and Mekong basins, while the representation of the hydrological cycle over the Indus Basin is poor in most cases, with a few GCMs not capturing the monsoonal signal at all. While the model outputs feature a remarkable spread for the monsoonal precipitation, a satisfactory representation of the western mid-latitude precipitation regime is instead observed. Similarly, most of the models exhibit a satisfactory agreement for the basin-integrated runoff in winter and spring, while their spread is large for the runoff during the monsoon season. For the future climate scenarios, most models foresee a decrease in the winter P − E over all four basins, while agreement is found on the decrease of the spring P − E over the Indus and Ganges basins only. Such decreases in P − E are mainly due to the decrease in precipitation associated with the western mid-latitude disturbances. Consequently, for the Indus and Ganges basins, the runoff drops during the spring season while it rises during the winter season. Such changes indicate a shift from rather glacial and nival to more pluvial runoff regimes, particularly for the Indus Basin. Furthermore, the rise in the projected runoff, along with the increase in precipitation during summer and autumn, indicates an intensification of the summer monsoon regime for all study basins.

Recent Climate Change over High Asia

Though elevated regions have generally been spotted as climate change hotspots due to amplified signal of change observed over recent decades, such evidence for the Tibetan Plateau and its neighboring regions is supported only by a sparse observational network, less representative for the high-altitude regions. Using a larger database of widely used gridded observations (CRU and UDEL) and reanalysis datasets (NCEP-CFSR, ERA-Interim, and its downscaled variant ERA-WRF) along with high-quality homogeneous station observations, we report recent changes in mainly the mean monthly near-surface air temperature and its elevation dependence, as well as changes in precipitation over the Tibetan Plateau, its neighboring mountain ranges, and the basins of major rivers originating from them. Our station-based analysis suggests a well-agreed warming over and around the Tibetan Plateau, which is more pronounced mainly during winter and spring months and generally in agreement but higher in magnitude than that of previously reported. We found a varying skillset of considered gridded and reanalysis datasets in terms of suggesting robust spatial and elevation-dependent patterns of trends and their magnitudes. The UDEL, ERA-Interim, and CRU datasets, respectively, exhibit high- to medium-level agreement with the station observations in terms of their trend magnitudes, which are generally underestimated. We found that all datasets agree with station observations as well as among each other for a strongest warming and drying in March over the northwestern region, for wet conditions in May over the southeastern Tibetan Plateau and Myanmar regions, as well as for the general warming pattern. Similarly, a strongest EDW rate per 1000 m elevation found in January is well agreed qualitatively among all datasets, except ERA-WRF. We also confirm high inter-dataset agreement for higher warming rates for highlands (above 2000 m asl) as compared to lowlands in December and January and with a mild agreement during the growing season (April–September). Except for winter months, NCEP-CFSR reanalysis largely contradicts the elevation-dependent warming signal. Our findings suggest that well-agreed likely changes in the prevailing climate will severely impact the geo-ecosystems of the High Asia and will have substantial influence on almost all dimensions of life in the region.

Domestic water buffaloes: Access to surface water, disease prevalence and associated economic losses

Given the shortage and non-availability of freshwater in Pakistan, wastewater is being used for bathing water buffaloes; however, this has a negative impact on animal welfare. Although there is a vast literature on indirect linkages between wastewater and animal productivity, studies focusing on the direct impacts of water buffaloes bathing in wastewater on animal productivity and economic losses are rare. Therefore, using 360 domestic water buffalo farms, this study examines the expenditure and production losses associated with bathing (in wastewater and freshwater) and non-bathing water buffaloes by employing partial budgeting and resource adjustment component techniques. Furthermore, it investigates the prevalence of animal diseases and associated economic effects using correlation analysis and propensity score matching techniques, respectively. The findings reveal that compared to their counterparts (freshwater bathing and non-bathing water buffaloes), buffaloes bathing in wastewater are at increased risk of clinical mastitis, foot and mouth disease (FMD) and tick infestation. Moreover, the use of wastewater for bathing buffaloes also leads to higher economic and production losses by affecting milk productivity, causing premature culling, and reducing slaughter value. The findings of the double-log model show that economic losses are higher if buffaloes bathe in wastewater within 30 min after milking, as there are more chances that those buffaloes would be exposed to bacterial penetration in the teat ducts, which may result in intramammary infection. According to the propensity score matching method, the higher economic damages per month are associated with buffaloes bathing in wastewater and freshwater, 155 and 110 USD per farm, respectively. The study findings reference the need for policies to restrict wastewater access by water buffaloes, and a regular check of and access to cool clean water wallows for bathing during hot summer days, to reduce excess heat and economic losses, and thus improve animal welfare.