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Hydrological processes in most semiarid regions on Earth have been changing under the impacts of climate change, human activities, or combinations of the two. This paper first presents a trend analysis of the spatiotemporal changes in water resources and then diagnoses their underlying atmospheric and socio-economic causes over 10 catchments in the Laoha basin, a typical semiarid zone of northeast China. The impacts of climate variability and human activities on streamflow change were quantitatively evaluated by the VIC (Variable Infiltration Capacity) model. First, results indicate that six out of the 10 studied catch-ments have statistically significant downward trends in annual streamflow; however, there is no significant change of annual precipitation for all catchments. Two abrupt changes of annual streamflow at 1979 and 1998 are identified for the four largest catchments. Second, the Laoha basin generally experienced three evident dry-wet pattern switches during the past 50 years. Furthermore, this basin is currently suffering from unprecedented water shortages. Large-scale climate variability has affected the local natural hy-drologie system. Third, quantitative evaluation shows human activities were the main driving factors for the streamflow reduction with contributions of approximately 90% for the whole basin. A significant in-crease in irrigated area, which inevitably resulted in tremendous agricultural water consumption, is the foremost culprit contributing to the dramatic runoff reduction, especially at midstream and downstream of the Laoha basin. This study is expected to enable policymakers and stakeholders to make well-informed, short-term practice decisions and better plan long-term water resource and ecoenvironment management strategies. [ABSTRACT FROM AUTHOR]

The majority of the world's population growth to 2050 is projected to occur in the tropics. Hence, there is a serious need for robust methods for undertaking water resource assessments to underpin the sustainable management of water in tropical regions. This paper describes the largest and most comprehensive assessment of the future impacts of runoff undertaken in a tropical region using conceptual rainfall-runoff models (RRMs). Five conceptual RRMs were calibrated using data from 115 streamflow gauging stations, and model parameters were regionalized using a combination of spatial proximity and catchment similarity. Future rainfall and evapotranspiration projections (denoted here as GCMES) were transformed to catchment-scale variables by empirically scaling (ES) the historical climate series, informed by 15 global climate models (GCMs), to reflect a 1°C increase in global average surface air temperature. Using the best-performing RRM ensemble, approximately half the GCMES used resulted in a spatially averaged increase in mean annual runoff (by up to 29%%) and half resulted in a decrease (by up to 26%%). However, ~70%% of the GCMES resulted in a difference of within ±5%% of the historical rainfall (1930-2007). The range in modeled impact on runoff, as estimated by five RRMs (for individual GCMES), was compared to the range in modeled runoff using 15 GCMES (for individual RRMs). For mid- to high runoff metrics, better predictions will come from improved GCMES projections. A new finding of this study is that in the wet-dry tropics, for extremely large runoff events and low flows, improvements are needed in both GCMES and rainfall-runoff modeling. [ABSTRACT FROM AUTHOR]

Uncertainty in the calculation of a standardized precipitation index (SPI) attracted growing concerns in the hydrometeorology research community in the last decade. This issue is addressed in the present study from the perspective of candidate probability distributions, the data record length, the cumulative time scale, and the selection of a reference period with the bootstrap and Monte Carlo methods using daily precipitation data observed in four climate regions across China. The impacts of the uncertainty in an SPI calculation on drought assessment are also investigated. Results show that the gamma distribution is optimal in describing the cumulative precipitation in China; among the four time scales investigated in the present study (i.e., 10, 20, 30, and 90 days), the minimal time scale appropriate for SPI calculation is 20 days for the humid region, 30 days for the semihumid/semiarid region and Tibetan Plateau (mostly its eastern part), and 90 days for the arid region. The uncertainty in SPI calculation decreases with the increase of time scale and record length, essentially as a consequence of the decrease of the confidence interval width of gamma distribution parameters with the increase of time scale and record length. But there is little improvement for the parameter estimation with record length longer than 70 years. There is greater uncertainty for high absolute SPI values than for small ones; consequently, there is greater uncertainty in assessing extreme droughts than moderate droughts. Reference period selection has large impacts on drought assessment, especially in the context of climate change. The uncertainty of the SPI calculation has large impacts on categorizing droughts, but no impact on assessing the temporal features of drought variation. Significance Statement: The standardized precipitation index (SPI) is the most commonly used drought index over the world for drought assessment, but there are several issues not well recognized in its application, such as the uncertainty resulting from the choice of time scales, the record length, and the reference period for its calculation. A comprehensive evaluation of these issues will be helpful for better interpreting SPI values for drought assessments, especially in the context of climate change. [ABSTRACT FROM AUTHOR]

Comparison and quantification of different uncertainties of future climate change involved in the modeling of a hydrological system are highly important for both hydrological modelers and policy-makers. However, few studies have accurately estimated the relative importance of different sources of uncertainty at different spatiotemporal scales. Here, a hierarchical sensitivity analysis framework (HSAF) incorporated with a variance-based global sensitivity analysis is developed to quantify the spatiotemporal contributions of different uncertainties in hydrological impacts of climate change in two different climatic (humid and semiarid) basins in China. The uncertainty sources include three emission scenarios (ESs), 20 global climate models (GCs), three hydrological models (HMs), and the associated sensitive hydrological parameters (PAs) screened and sampled by the Morris and Latin hypercube sampling methods, respectively. The results indicate that the overall trend of uncertainty is PA > HM > GC > ES, but their uncertainties have discrepancies in projections of different hydrological variables. The HM uncertainty in annual and monthly discharge projections is generally larger than the PA uncertainty in the humid basin than semiarid basin. The PA has greater uncertainty in extreme hydrological event (annual peak discharge) projections than in annual discharge projections for both basins (particularly for the humid basin), but contributes larger uncertainty to annual and monthly discharge projections in the semiarid basin than humid basin. The GC contributes larger uncertainty in all the hydrological variables projections in the humid basin than semiarid basin, while the ES uncertainty is rather limited in both basins. Overall, our results suggest there is greater spatiotemporal variability of hydrological uncertainty in more arid regions. [ABSTRACT FROM AUTHOR]

Snow fraction has a direct impact on water resources in arid regions. The selection of proper methods for estimating snow fraction is thus essential. Two temperature-based and two humidity-based approaches to discriminate precipitation phase were evaluated using daily meteorological observations over the past six decades in Xinjiang in arid northwest China. The main findings included that 1) the finest discrimination was achieved by the wet-bulb temperature (Tw) method whereas the single temperature threshold at 0°C produces the poorest result; the performances of the Dai and humidity-dependent empirical method (TRH) methods were between them, with slightly lower error using the Dai method. Also, the Tw method is the least sensitive to regional heterogeneity and less affected by distinct changes in elevation; the other three methods, however, are biased mostly toward underestimating snow and show larger variations due to the regional discrepancies. Careful adjustment of snow discrimination thresholds based on the local properties of observation spots is needed for these methods. 2) Despite widespread warming, snow fraction perturbations in Xinjiang are characterized mainly by insignificant changes plus pronounced reductions at high mountain sites. Proxy drivers of such changes can be better explained by considering the hydrothermal diversity and changing climatic factors. Across the wetter subregions, snowfall has been significantly increasing, and the positive impact of which on snow fraction was hindered by significant warming, particularly in winter, and summer rainfall; across the drier subregions, however, insignificant change in snow fraction corresponds to a slow and insignificant increase in snowfall joined by the negative impacts of significant winter warming and summer rainfall. [ABSTRACT FROM AUTHOR]

Using tree-ring data of Pinus sylvestris var. mongolica from the Hulun Buir region in northeast China, 12 annual runoff series of the Hailar River spanning the past 202-216 years were established for the first time; these included 11 branches and one for the entire basin. These reconstructions, which could explain 29.4%-52.7% of the total variance for the measured runoffs during 1956-2006, performed well in statistical verification tests. In the whole basin's reconstruction of 212 years, 34 extreme drought years (16.0%) and 41 extreme pluvial years (19.3%) were identified; 4 of the 10 most extreme years occurred after 1980. The consistent cycle and correlation revealed that the Hailar runoff had a teleconnection with the El Niño-Southern Oscillation (ENSO). The sharply increasing variance at the end of the reconstruction, accompanied by the increasing intensity of short cycles (4-8 years), indicated that runoff variability in the Hailar River basin has enhanced in the late twentieth century. This is verified by the drastic fluctuations in water level and area of rivers and lakes, and the frequent shift of natural land cover types in the Hulun Buir area in recent decades. The intensified runoff variability can be connected with the concurrently enhanced ENSO activity. Our study is the first to identify the intensification of recent runoff variability in the semiarid to arid region in northeast China from a long-term perspective. With projected enhancement of ENSO activity, the Hailar River basin will face the increased risk of extreme hydrological events. [ABSTRACT FROM AUTHOR]

Arid and semiarid lowland areas of central Asia are largely dependent on fluvial water originating from the Tian Shan. Mountain glaciers contribute significantly to runoff, particularly in summer. With global warming, the total glacier area in the Kunma Like River catchment declined by 13.2% during 1990-2007. For future water resources, it is essential to quantify the responses of hydrologic processes to both climate change and shrinking glaciers in glacierized catchments, such as the headwaters of the Tarim River. Thus, a degree-day glacier melt algorithm was integrated into the macroscale hydrologic Variable Infiltration Capacity model (VIC). Good results were obtained for monthly runoff simulations in the Kunma Like River catchment, which suggest that the extended VIC has acceptable performance. Because of increased precipitation and air temperature, annual runoff in the catchment has increased by about 4.07 × 108 m3 decade−1 during 1984/85-2006/07. Under the assumption of the same climatic conditions, sensitivity analyses indicated that annual and summer river runoff volumes would decrease by 9.3% and 10.4%, respectively, for reductions in glacier area of 13.2%. The variation coefficient of annual runoff also increased because of shrinking glaciers. Runoff scenarios for warmer future climate and various deglaciation situations suggest that reductions in glacier area by >30% will likely produce less meltwater in summer and river runoff will decline. Consequently, the annual total discharge of the Kunma Like River is projected to decrease by 2.8%-19.4% in the 2050s scenario because of glacier shrinking. [ABSTRACT FROM AUTHOR]

Water managers across the United States face the need to make informed policy decisions regarding long-term impacts of climate change on water resources. To provide a scientifically informed basis for this, the evolution of important components of the basin-scale water balance through the end of the twenty-first century is estimated. Bias-corrected and spatially downscaled climate projections, from phase 3 of the Coupled Model Intercomparison Project (CMIP3) of the World Climate Research Programme, were used to drive a spatially distributed Variable Infiltration Capacity (VIC) model of hydrologic processes in the Salt-Verde basin in the southwestern United States. From the suite of CMIP3 models, the authors select a five-model subset, including three that best reproduce the historical climatology for the study region, plus two others to represent wetter and drier than model average conditions, so as to represent the range of GCM prediction uncertainty. For each GCM, data for three emission scenarios (A1B, A2, and B1) were used to drive the hydrologic model into the future. The projections of this model ensemble indicate a statistically significant 25% decrease in streamflow by the end of the twenty-first century. The primary cause for this change is due to projected decreases in winter precipitation accompanied by significant (temperature driven) reductions in storage of snow and increased winter evaporation. The results show that water management in central Arizona is highly likely to be impacted by changes in regional climate. [ABSTRACT FROM AUTHOR]