Statistical Assessment of the Runoff Variability of Small Rivers in the Middle Zeravshan Basin

The article deals with the issues of statistical assessment of the variability of the runoff of small rivers in the Middle Zeravshan basin. For this purpose, the average monthly and annual water discharges were used, taken into account at 11 hydrological stations located on small rivers and water resources in the Middle Zeravshan basin. Calculations to estimate the coefficient of variability of river runoff were carried out for two periods: the first calculation period includes the base climatic period (1961-1990), and the second calculation period includes 1991-2018. Based on the analysis of the results obtained, an increase in the value of the coefficient of variation (Cv) in the second calculation period relative to the first calculation period was revealed.

The Last 1200 Years of Rainfall/Runoff Variability along the Central Mexico Pacific Coast Associated with the North American Monsoon

This study presents new evidence for long-term variability in the late Holocene North American Monsoon (NAM), Pacific coast of Mexico. We have carried out a rock magnetic study on two deep-sea sediment cores from the Pacific coast Pescadero Basin. The magnetic intensities estimate total magnetic material and are a proxy for total clastic sediment. Ratios of magnetic intensities estimate the grain size of magnetic material. The rock magnetic data show a decimeter scale, multi-decadal oscillation with fourteen cycles (A-N) over the last 1200 years. These oscillations reflect alternating intervals of stronger/coarser magnetic/clastic flux to the coastal ocean and intervals of weaker/finer magnetic flux. We think these variations are caused by variations in long-term dominance of the NAM; summer (wet) monsoons produce rainy conditions (with runoff) while winter (dry) monsoons produce significant offshore winds, increased upwelling/biological productivity. We can correlate our variability to two other published studies southeast of Pescadero Basin, coastal lake sediments in Laguna de Juanacatlan and a Juxtlahuaca Cave stalagmite. Both of these studies estimate local rainfall. We see evidence of the same pattern of multi-decadal rainfall-runoff variability in these records as we see in Pescadero Basin, which is synchronous to within ±25 years over the last 1200 years. The multi-dacadal pattern of hydrologic variability in all three records varies in cycle duration from ~90-years wet/dry cycles in the Little Ice Age (1400–1850 AD) to ~60-years cycles in the Medieval Climate Optimum (1100–1400 AD). This variability in cycle duration suggests some chaotic nature to the regional NAM climate pattern or some long-term non-linear forcing (PDO?).

Long-Term Runoff Variability Analysis of Rivers in the Danube Basin

The long-term runoff variability is identified to consist of the selected large rivers with long-term data series in the Danube River Basin. The rivers were selected in different regions of the Danube River Basin and have a large basin area (Danube: Bratislava gauge with 131,338 km2; Tisza: Senta with 141,715 km2; and Sava: Sremska Mitrovica with 87,966 km2). We worked with the station Danube: Reni in the delta as well. A spectral analysis was used to identify the long-term variability of three different types of time series: (1) Average annual discharge time series, (2) Minimum annual discharge time series and (3) Maximum annual discharge time series. The results of the study can be used in a long-term forecast of the runoff regime in the future.

PISCO_HyM_GR2M: A Model of Monthly Water Balance in Peru (1981–2020)

Quantification of the surface water offer is crucial for its management. In Peru, the low spatial density of hydrometric stations makes this task challenging. This work aims to evaluate the hydrological performance of a monthly water balance model in Peru using precipitation and evapotranspiration data from the high-resolution meteorological PISCO dataset, which has been developed by the National Service of Meteorology and Hydrology of Peru (SENAMHI). A regionalization approach based on Fourier Amplitude Sensitivity Testing (FAST) of the rainfall-runoff (RR) and runoff variability (RV) indices defined 14 calibration regions nationwide. Next, the GR2M model was used at a semi-distributed scale in 3594 sub-basins and river streams to simulate monthly discharges from January 1981 to March 2020. Model performance was evaluated using the Kling–Gupta efficiency (KGE), square root transferred Nash–Sutcliffe efficiency (NSEsqrt), and water balance error (WBE) metrics. The results show a very well representation of monthly discharges for a large portion of Peruvian sub-basins (KGE ≥ 0.75, NSEsqrt ≥ 0.65, and −0.29 < WBE < 0.23). Finally, this study introduces a product of continuous monthly discharge rates in Peru, named PISCO_HyM_GR2M, to understand surface water balance in data-scarce sub-basins.

Recent Intensified Runoff Variability in the Hailar River Basin during the Past Two Centuries

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.

The GLACE-Hydrology Experiment: Effects of Land–Atmosphere Coupling on Soil Moisture Variability and Predictability

The impact of land–atmosphere anomaly coupling on land variability is investigated using a new two-stage climate model experimental design called the “GLACE-Hydrology” experiment. First, as in the GLACE-CMIP5 experiment, twin sets of coupled land–atmosphere climate model (CAM5-CLM4.5) ensembles are performed, with each simulation using the same prescribed observed sea surface temperatures and radiative forcing for the years 1971–2014. In one set, land–atmosphere anomaly coupling is removed by prescribing soil moisture to follow the control model’s seasonally evolving soil moisture climatology (“land–atmosphere uncoupled”), enabling a contrast with the original control set (“land–atmosphere coupled”). Then, the atmospheric outputs from both sets of simulations are used to force land-only ensemble simulations, allowing investigation of the resulting soil moisture variability and memory under both the coupled and uncoupled scenarios. This study finds that in midlatitudes during boreal summer, land–atmosphere anomaly coupling significantly strengthens the relationship between soil moisture and evapotranspiration anomalies, both in amplitude and phase. This allows for decreased moisture exchange between the land surface and atmosphere, increasing soil moisture memory and often its variability as well. Additionally, land–atmosphere anomaly coupling impacts runoff variability, especially in wet and transition regions, and precipitation variability, although the latter has surprisingly localized impacts on soil moisture variability. As a result of these changes, there is an increase in the signal-to-noise ratio, and thereby the potential seasonal predictability, of SST-forced hydroclimate anomalies in many areas of the globe, especially in the midlatitudes. This predictability increase is greater for soil moisture than precipitation and has important implications for the prediction of drought.

Recent anthropogenic curtailing of Yellow River runoff and sediment load is unprecedented over the past 500 y

The Yellow River (YR) is the fifth-longest and the most sediment-laden river in the world. Frequent historical YR flooding events, however, have resulted in tremendous loss of life and property, whereas in recent decades YR runoff and sediment load have fallen sharply. To put these recent changes in a longer-term context, we reconstructed natural runoff for the middle reach of the YR back to 1492 CE using a network of 31 moisture-sensitive tree-ring width chronologies. Prior to anthropogenic interference that started in the 1960s, the lowest natural runoff over the past 500 y occurred during 1926 to 1932 CE, a drought period that can serve as a benchmark for future planning of YR water allocation. Since the late 1980s, the low observed YR runoff has exceeded the natural range of runoff variability, a consequence of the combination of decreasing precipitation and increasing water consumption by direct and indirect human activities, particularly agricultural irrigation. This reduced runoff has resulted in an estimated 58% reduction of the sediment load in the upper reach of the YR and 29% reduction in the middle reach.