Hydroclimatic Variability Research Articles

Holocene Water Balance Variations in Great Salt Lake, Utah: Application of GDGT Indices and the ACE Salinity Proxy

AbstractGreat Salt Lake (GSL), Utah, is a hypersaline terminal lake in the Great Basin, and the remnant of the late glacial Lake Bonneville. Holocene hydroclimate variations cannot be interpreted from the shoreline record, but instead can be investigated by proxies archived in the sediments. GLAD1‐GSL00‐1B was cored in 2000 and recently dated by radiocarbon for the Holocene section with the top 11 m representing ∼7 ka to present. Sediment samples every 30 cm (∼220 years) were studied for the full suite of microbial membrane lipids, including those responsive to temperature and salinity. The Archaeol and Caldarchaeol Ecometric (ACE) index detects the increase in lipids of halophilic archaea, relative to generalists, as salinity increases. We find Holocene ACE values ranged from 81 to 98, which suggests persistent hypersalinity with <50 g/L variability across 7.2 ka. The temperature proxy, MBTʹ5Me, yields values similar to modern mean annual air temperature for months above freezing (MAF = 15.7°C) over the last 5.5 ka. Several glycerol dialkyl glycerol tetraether metrics show a step shift in microbial communities and limnology at 5.5 ka. Extended archaeol detects elevated salinity during the regional mid‐Holocene drought, not readily detected in the ACE record that is often near the upper limit of the index. We infer that the mid‐Holocene GSL was shallower and saltier than the late Holocene. The current drying may be returning the lake to conditions not seen since the mid‐Holocene.

Mapping long-term spatial impact of ENSO on hydroclimatic variables in China

Understanding the impact of El Niño-Southern Oscillation (ENSO) on hydroclimatic variables is critical to early warning of ENSO-induced disasters. However, most studies employed the sea surface temperature anomaly (SSTa) index of the Niño 3.4 region (hereinafter called Niño 3.4 SSTa) to assess its impact on those variables, while ignoring that of other Niño regions. This study aims to assess the long-term spatial impact of Niño 1 + 2 SSTa index on hydroclimatic variables in China. After removing seasonality, we found that the correlation between standardized surface pressure (SP)/ temperature (T)/ evapotranspiration (ET)/ terrestrial water storage (TWS) and Niño 1 + 2 SSTa was significantly better than that without removing seasonality. Niño 1 + 2 SSTa was also demonstrated to have a substantial impact on standardized precipitation index (SPI) in China, particularly during drought period. Notably, precipitation is a key driver of ET in response to Niño 1 + 2 SSTa in the time span. In addition, compared to that of Niño 3.4 SSTa, the hydroclimatic variables in response to Niño 1 + 2 SSTa are able to capture the basic geographical characteristics of China. In particular, the spatial configuration of China's terrain (TWS trend) is largely depicted by the spatial pattern of correlation coefficient between Niño 1 + 2 SSTa and SP (TWS), respectively. The above findings indicate that the spatial pattern of the long-term variations of hydroclimatic variables in China can potentially be monitored by SSTa in the Niño 1 + 2 region.

Vegetation dynamics in arid central Asia over the past two millennia linked to NAO variability and solar forcing

The role of NAO modes and solar activity, together with their potential relationship, in driving hydroclimatic variability in arid central Asia over the past two millennia remain controversial—partly due to the limitations of the resolution or time span of existing paleoclimatic records. Vegetation ecosystems at high altitudes are very sensitive to hydroclimate variations. Here, we present a vegetation history for the past two millennia based on a pollen record with an average time resolution of four years from Lake Dalongchi in the Tianshan Mountains. Our results show a millennial-scale drying trend during the past 2000 years, with the vegetation changing from forest-steppe and forest to steppe as the intensity of mid-latitude westerlies gradually decreased. We suggest that the dynamic link between the NAO and moisture variability in arid central Asia depends on the NAO phase in the context of changes in westerlies intensity. The moisture variability in arid central Asia shows a positive relationship with NAO phases when the precipitation delivered by the mid-latitude westerlies exceeded a threshold level in the period of 0–1100 CE. However, over the last millennium, the role of the NAO mode was weakened by solar forcing when the regional moisture gradually decreased below this threshold. The decline of the ancient Silk Road was possibly related to this humid-to-try climate shift at∼1100 CE.

Hybrid forecasting: blending climate predictions with AI models

Abstract. Hybrid hydroclimatic forecasting systems employ data-driven (statistical or machine learning) methods to harness and integrate a broad variety of predictions from dynamical, physics-based models – such as numerical weather prediction, climate, land, hydrology, and Earth system models – into a final prediction product. They are recognized as a promising way of enhancing the prediction skill of meteorological and hydroclimatic variables and events, including rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. Hybrid forecasting methods are now receiving growing attention due to advances in weather and climate prediction systems at subseasonal to decadal scales, a better appreciation of the strengths of AI, and expanding access to computational resources and methods. Such systems are attractive because they may avoid the need to run a computationally expensive offline land model, can minimize the effect of biases that exist within dynamical outputs, benefit from the strengths of machine learning, and can learn from large datasets, while combining different sources of predictability with varying time horizons. Here we review recent developments in hybrid hydroclimatic forecasting and outline key challenges and opportunities for further research. These include obtaining physically explainable results, assimilating human influences from novel data sources, integrating new ensemble techniques to improve predictive skill, creating seamless prediction schemes that merge short to long lead times, incorporating initial land surface and ocean/ice conditions, acknowledging spatial variability in landscape and atmospheric forcing, and increasing the operational uptake of hybrid prediction schemes.

Causality-based drought propagation analyses among meteorological drought, hydrologic drought, and water shortage

Droughts propagate through the hydrologic cycle, leading to water deficiencies in various hydro-climate variables, such as rainfall, streamflow, soil moisture, and/or groundwater. Understanding drought propagation characteristics is an essential issue in water resources planning and management. This study aims to detect the causal relationships from meteorological drought to hydrologic drought and how these natural phenomena cause water shortage using CCM (convergent cross mapping). The causal influences among the SPI (standardized precipitation index), SSI (standardized streamflow index), and SWHI (standardized water shortage index) of the Nanhua Reservoir-Jiaxian Weir system located in southern Taiwan are identified based on 1960–2019 records. Since water shortages are influenced by reservoir operation models, three different models, the SOP (standard operating policy), RC (rule-curve-based model), and OPT (optimal hedging model), are considered in this study. The results reveal that clear and strong causality is observed between SPI and SSI for both watersheds. The causality of SSI-SWHI is stronger than that of SPI-SWHI, but both causalities are weaker than that of SPI-SSI. Among the three operation models, the no hedging SOP leads to the weakest causal links of SPI/SSI-SWHI, and the strongest causality is noted for OPT since the optimally derived hedging policy uses future hydrologic information. The CCM-based causal network of drought propagation reveals that the Nanhua Reservoir and Jiaxian Weir are equally important for water supplies since nearly identical causal strengths are observed in both watersheds.

Analysis of spatial and temporal trend of hydro-climatic parameters in the Kilombero River Catchment, Tanzania

Inadequate knowledge on actual water availability, have raised social-economic conflicts that necessitate proper water management. This requires a better understanding of spatial–temporal trends of hydro-climatic variables as the main contributor to available water for use by sectors of economy. The study has analysed the trend of hydro-climatic variables viz. precipitation, temperature, evapotranspiration and river discharge. One downstream river gauge station was used for discharge data whereas a total of 9 daily observed and 29 grided satellite stations were used for climate data. Climate Hazards Group InfraRed Precipitation was used for precipitation data and Observational-Reanalysis Hybrid was used for Temperature data. Mann–Kendall Statistical test, Sen’s slope estimator and ArcMap Inverse Distance Weighted Interpolation functionality were employed for temporal, magnitude and spatial trend analysis respectively. Results confirmed that, spatially, there are three main climatic zones in the study area viz. Udzungwa escarpment, Kilombero valley and Mahenge escarpment. On temporal analysis, with exception of the declining potential evapotranspiration trend, all other variables are on increase. This is with catchment rates of 2.08 mm/year, 0.05 °C/year, 0.02 °C/year, 498.6 m3/s/year and − 2.27 mm/year for precipitation, Tmax, Tmin, river discharge and PET respectively. Furthermore, rainfalls start late by a month (November) while temperatures picks earlier by September and October for Tmax and Tmin respectively. Water availability matches farming season. However, it is recommended to improve water resources management practices to limit flow impairment as expansions in sectors of economy are expected. Furthermore, landuse change analysis is recommended to ascertain actual trend and hence future water uptake.

Temporal trends in agricultural water use and the relationships to hydroclimatic factors in the High Plains aquifer region

AbstractThe High Plains aquifer (HPA) is the primary water source for agricultural irrigation in the US Great Plains. The water levels in many locations of the aquifer have declined steadily over the past several decades because the rate of water withdrawals exceeds recharge, which has been a serious concern to the water resources management in the region. We evaluated temporal trends and variations in agricultural water use and hydroclimatic variables including precipitation, air temperature, reference evapotranspiration, runoff, groundwater level, and terrestrial water storage across the HPA region for different periods from 1985 to 2020 at the grid, county, or region scale. The results showed that water withdrawals decreased from 21.3 km3/year in 1985 to 18.2 km3/year in 2015, while irrigated croplands increased from 71,928 km2 in 1985 to 78,464 km2 in 2015 in the entire HPA. The hydroclimatic time‐series showed wetting trends in most of the northern HPA, but drying and warming trends in the southern region from 1985 to 2020. The groundwater level time‐series indicated flat trends in the north, but significant declining in the central and southern HPA. Trends in irrigation water withdrawals and irrigation area across the HPA were controlled by the advancement of irrigation systems and technologies and the management of sustainable water use, but also were affected by dynamical changes in the hydroclimatic conditions.

Holocene hydroclimatic variability recorded in sediments from Maddox Lake (northern California Coast Range)

AbstractPerspectives on past climate using lake sediments are critical for assessing modern and future climate change. These perspectives are especially important for water-stressed regions such as the western United States. One such region is northwestern California (CA), where Holocene-length hydroclimatic records are scarce. Here, we present a 9000-year, relative lake level record from Maddox Lake (CA) using a multi-indicator approach. The Early Holocene is characterized by variably low lake levels with a brief excursion to wetter climates/relative highstand ca. 8.4–8.06 cal ka BP, possibly related to the 8.2 ka cold event and changing Atlantic Meridional Overturning Circulation (AMOC). From 5.2–0.55 cal ka BP, Maddox Lake experienced a long-term regression, tracking changes in summer-winter insolation, tropical and northeast Pacific SSTs, and the southward migration of the ITCZ. This gradual regression culminated in a pronounced relative lowstand during the Medieval Climatic Anomaly (MCA). A marked relative highstand followed the MCA, correlative to the Little Ice Age. The latter reflects a far-field response to North Atlantic volcanism, solar variability, and possibly changes in AMOC and Arctic sea ice extent. Our results further confirm the hydroclimatic sensitivity of northwest California to various forcings including those emanating from the North Atlantic.

Disentangling abiotic and biotic controls of age‐0 Pacific herring population stability across the San Francisco Estuary

AbstractPacific herring (Clupea pallasii) is an ecologically and commercially valuable forage fish in the North Pacific Ocean. However, knowledge gaps exist around the abiotic and biotic drivers behind its variable population dynamics—as well as on the ability of the species to show spatially structured trends that stabilize population portfolios in the face of environmental change. Here we examined how historical hydroclimatic variability in the San Francisco Estuary (California) has driven age‐0 Pacific herring population dynamics over 35 years. First, we used wavelet analyses to examine spatiotemporal variation and synchrony in the environment, focusing on two key variables: salinity and temperature. Next, we fitted multivariate autoregressive state‐space models to environmental and abundance time series to test for spatial structure and to parse out abiotic (salinity and temperature) from biotic influences (spawning and density dependence). Finally, we examined the stabilizing effects of spatially asynchronous population fluctuations (i.e., portfolio effects) across the estuary. Our results showed that temperature, but not salinity, fluctuated synchronously across regions on seasonal and decadal timescales. The top‐ranked model showed strong evidence of regional population structure and regional variation in population responses to the environment. As expected, age‐0 herring were generally associated with cooler, saltier conditions in spring. Density dependence was strong in all regions, suggesting that local factors influencing rearing conditions limited juvenile population growth across the estuary. Additionally, age‐0 abundance fluctuations were on average 15% more stable across the estuary than in individual regions, demonstrating that portfolio effects arising from population asynchrony have helped to stabilize recruitment across the estuary over the past four decades. We contend that ecosystem‐based fishery management strategies to restore eelgrass and tidal marsh rearing habitats could increase the carrying capacity of the estuary, further stabilizing the herring population and reducing the risk of fishery closures.

Long-term hydroclimatic variability over the semi-arid Ethiopian highlands in relation to ENSO and IOD teleconnection signals

Long-term hydroclimatic variability over the semi-arid Ethiopian highlands in relation to ENSO and IOD teleconnection signals

Identifying the main factors driving groundwater stress in a semi-arid region, southern Iran

ABSTRACT Groundwater resources are the most reliable freshwater supply in arid regions where many aquifers face dramatic depletion due to natural and anthropogenic causes. The annual average rate of decline of groundwater level is about 1.65 m. This research focuses on an aquifer that suffers from severe groundwater stress, and it aims to identify the main causes of the stress and to understand the effects of climate change and human activity. Monthly data on groundwater level, precipitation, temperature, river discharge, evapotranspiration, soil moisture, and vegetation cover were collected from 2000 to 2020. The results indicate that declining groundwater levels mainly resulted from the expansion of vegetation cover rather than changes in hydro-climatic variables. Finally, this work highlights how significant financial investment in improving irrigation efficiency in the absence of socio-economic plans, education, awareness, and monitoring programmes unproductively resulted in the expansion of agricultural activities rather than preserving groundwater storage.

Predicting reference evapotranspiration based on hydro-climatic variables: comparison of different machine learning models

ABSTRACT This paper aimed to estimate the reference evapotranspiration (ET0) due to some limitations of the Food and Agriculture Organization-56 Penman-Monteith (FAO 56-PM) approach by using five alternative machine learning models. The study makes an important contribution to the ET0 estimation success for of the ET0 of 12 stations with variable climate characteristics in the Central Anatolian Region (CAR). The performances of the models were compared with the coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) metrics that are frequently cited in the literature, and also with the performance index (PI). Long short-term memory (LSTM), artificial neural networks (ANN), and multivariate adaptive regression splines (MARS) models provided the best performance in eight, three, and one stations, respectively. The R2, MAE, RMSE, and PI values of the selected models from each station vary in the range of 0.987-0.999, 1.948-4.567, 2.671-6.659, and 1.544-4.018, respectively.

Modelling future flood events under climate change scenarios in the Pungwe River Basin

Abstract This study sought to project future changes in hydroclimatic variables and to establish how climate change affects flood inundation extent in the Pungwe River Basin. Climate ensembles of 10 Regional Climate Models from the CORDEX project were selected. The historical rainfall and temperature time series and the downscaled climate data were input into the HBV model to generate streamflow for the 2022–2099 period. Flood extents for 50-, 100-and 1,000-year return periods were predicted using the HEC-RAS hydraulic model. By 2070, annual rainfall at all nine studied meteorological stations is predicted to reduce by a maximum of 61%. Temperature is expected to increase up to 1.5% over the same period. By the 2070s, simulations from HBV revealed that the peak flows for the Pungwe River Basin will increase by up to 100% and decrease by approximately 57% as projected by the model ensemble. The analyses also show that by 2070 climate change may cause a minimum of 2,784.4 km2 and a maximum of 8,235.6 km2 of flood extension. These results are essential for decision-making on flood hazard mapping and early warning systems, prompting a pathway for sustainable development.

Dynamic and thermodynamic influences on precipitation in Northeast Mexico on orbital to millennial timescales

The timing and mechanisms of past hydroclimate change in northeast Mexico are poorly constrained, limiting our ability to evaluate climate model performance. To address this, we present a multiproxy speleothem record of past hydroclimate variability spanning 62.5 to 5.1 ka from Tamaulipas, Mexico. Here we show a strong influence of Atlantic and Pacific sea surface temperatures on orbital and millennial scale precipitation changes in the region. Multiple proxies show no clear response to insolation forcing, but strong evidence for dry conditions during Heinrich Stadials. While these trends are consistent with other records from across Mesoamerica and the Caribbean, the relative importance of thermodynamic and dynamic controls in driving this response is debated. An isotope-enabled climate model shows that cool Atlantic SSTs and stronger easterlies drive a strong inter-basin sea surface temperature gradient and a southward shift in moisture convergence, causing drying in this region.

Hydroclimate reconstruction during the last 1000 years inferred from the mineralogical and geochemical composition of a sediment core from Lake-Azuei (Haiti)

This study aims to reconstruct the hydro-climatic variations over the last 1000 years in Haiti using mineralogical and geochemical composition of well dated lacustrine sediment core retrieved from Lake Azuei. The results show changes in sedimentological processes linked to environmental and climatic variations. The general pattern suggests a wetter Medieval Climate Anomaly (MCA), drier Little Ice Age (LIA), high climate variability during the MCA-LIA transition and more anthropogenic impacts that dominate natural climate during the Current Warm Period (CWP). The MCA period (~1000–1100 CE) thus appears marked by increase sedimentation rate supported by higher terrigenous input linked to erosive events particularly increases in precipitation. During the LIA, particularly from ~1450 to 1600 CE, there is a great variation toward a decrease of terrigenous input, which is related to a decrease on sedimentation rate and increase Mg-calcite precipitation, suggesting less precipitation and high evaporation respectively during dry climate conditions. The MCA-LIA transition (~1200–1400 CE) is characterized by variations between terrigenous input, Mg-calcite formation and organic matter deposition, which indicate succession of dry and humid conditions. The CWP (1800–2000 CE) shows a progressive increase on sedimentation rate and decrease of gray level, which indicate more organic matter sedimentation as consequence of anthropogenic activities in the surrounding basin of the lake. High-resolution gray level analysis, which reflects principally variations in terrigenous input, carbonate mineral formation and organic matter deposition, shows that the AMO, NAO, PDO and ENSO are the principal modes affecting the hydro-climatic changes in Haiti during the last millennium. In addition, temporal correlation of other Caribbean paleoclimate records with our geochemical and mineralogical data, suggests that trends observed in Lake Azuei were controlled by regional climate, likely associated with shifts in the position of the ITCZ.

Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical Analysis

Addressing the issue of shrinking saline lakes around the globe has turned into one of the most pressing issues for sustainable water resource management. While it has been established that natural climate variability, human interference, climate change, or a combination of these factors can lead to the depletion of saline lakes, it is crucial to investigate each case and diagnose the potential causes of this devastating phenomenon. On that note, this study aims to promote a comprehensive analytical framework that can reveal any significant depletion patterns in lakes while analyzing the potential reasons behind these observed changes. The methodology used in this study is based on statistical analysis, data mining techniques, and remote sensing-based datasets. To achieve the objective of this study, Maharlou Lake has been selected to demonstrate the application of the proposed framework. The results revealed two types of depletion patterns in the lake’s surface area: a sharp breaking point in 2007/2008 and a gradual negative trend, which was more pronounced in dry seasons and less prominent in wet seasons. Furthermore, the analysis of hydro-climatic variables has indicated the presence of abrupt and gradual changes in these variables’ time series, which could be interpreted as a signal that climate change and anthropogenic drought are changing the basin’s status quo. Lastly, analyzing the statistically significant correlation between hydro-climatic variables and the lake’s surface area showed the potential connection between the observed changing patterns. The results obtained from data mining models suggest that Maharlou Lake has undergone a morphological transformation and is currently adopting these new conditions. If preventive measures are not taken to revive Maharlou Lake, the tipping point might have been reached, and reviving the lake could be improbable, if not impossible.

Coherent Mechanistic Patterns of Tropical Land Hydroclimate Changes

AbstractChanges in tropical (30 S–30 N) land hydroclimate following CO2‐induced global warming are organized according to climatological aridity index (AI) and daily soil moisture (SM) percentiles. The transform from geographical space to this novel process‐oriented phase space allows for interpretation of local, daily mechanistic relationships between key hydroclimatic variables in the context of time‐mean and/or global‐mean energetic constraints and the wet‐get‐wetter/dry‐get‐drier paradigm. Results from 16 CMIP models show coherent patterns of change in the AI/SM phase space that are aligned with the established soil‐moisture/evapotranspiration regimes. We introduce an active‐rain regime as a special case of the energy‐limited regime. Rainfall shifts toward larger rain totals in this active‐rain regime, with less rain on other days, resulting in an overall SM reduction. Consequently, the regimes where SM constrains evapotranspiration become more frequently occupied, and corresponding hydroclimatic changes align with the position of the critical SM value in the AI/SM phase space.

Riparian cottonwood mortality following compound impacts from river water withdrawal and hydroclimatic variation

AbstractOriginating in Glacier Park, Montana, the transboundary St. Mary River has provided a focus for international water sharing for a century. It was dammed and diverted in the USA, and more extensively in Alberta, where it supports Canada's centre for agricultural irrigation. Following water withdrawals, the riparian cottonwoods (Populus angustifolia) collapsed, and we assessed the woodland decline downstream from the St. Mary Dam, through eight sets of aerial photographs over seven decades. These revealed 88% woodland loss from 1951 to 1999 (R2 = 0.984), including a steeper decline with the 1980s drought. Following the implementation of an environmental flow regime that increased minimum flows after 1993, the remnant woodlands were stabilized, with a slight recovery by 2022. Analyses of the historical hydrology revealed compound contributions to the woodland mortality. (1) Annual river flows declined with increasing water diversion, and (2) late summer flows were particularly depleted. (3) Dam operations resulted in abrupt stage recessions and irregular spikes. (4) Accompanying climate warming, the spring snowmelt advanced and late summer flows declined. (5) The greatest climatic influence involved multiple‐year clusters with high versus low flows, corresponding with the Pacific decadal oscillation (PDO) from 1920 to 1990 (R2 = 0.365), but less coupled thereafter. This long‐term study demonstrates the coordination between hydroclimatic variation, water management and the fate of riparian woodlands, which reveal ecosystem health. An environmental flow regime provided benefit, and for other regulated rivers in dry ecoregions, we recommend functional flow regimes that provide sufficient minimum flows and avoid abrupt flow recession or irregular spikes.

Multi-proxy crossdating extends the longest high-elevation tree-ring chronology from the Mediterranean

Annually precise dating is the cornerstone of dendrochronology. The accurate crossdating of relict wood is, however, frequently challenged during early chronology periods when sample replication is typically low. Here we present a multi-proxy approach in which stable carbon (δ13C) and radiocarbon (14C) isotope data are used to evaluate and correct dating errors in the early period of the longest high-elevation tree-ring chronology from the Mediterranean Basin. The record was initially developed using 878 tree-ring width (TRW) and 192 maximum latewood density (MXD) series from living and relict Bosnian pines (Pinus heldreichii) from Mt. Smolikas in Greece to reconstruct hydroclimate and temperature variability back to the 8th century. New annually resolved and non-pooled δ13C series now suggest a re-dating of first millennium relict pine samples during a period when sample replication was too low for proper TRW and/or MXD crossdating. The associated correction shifts the start of the Mt. Smolikas chronology from 575 back to 468 CE, a change independently confirmed by wiggle-matching annual 14C data along the 774/775 CE cosmic event. Our study demonstrates the importance of independent age validation for robust chronology development and shows how multi-proxy crossdating can improve dating success during periods of low sample replication.

Trend analysis of hydro-climate variables in the Jemma sub-basin of Upper Blue Nile (Abbay) Basin, Ethiopia

The change in climate elements such as rainfall and temperature are determinant factors of hydrological components (e.g., streamflow, water yield, evapotranspiration). Thus, understanding the trends of hydro-climate variables are imperative for planning water resources management measures. This study examines the trends of precipitation and temperature (1980–2014) as well as streamflow (1990–2008) changes in the Jemma sub-basin of the Upper Blue Nile (Abbay) Basin. A homogeneity test was performed for pre-processing data to inspect the statistical nature of data homogeneity viz., Pettitt’s, SNHT, Buishand range test, and Von Neumann test (VNT). The Mann–Kendall (MK) test, Modified Mann–Kendall (MMK) test, Sen’s slope estimator, and Innovative trend analysis (ITA) were applied to compute the existence of trend and the magnitude of change at an annual timescale. In a nutshell, the study portrays a change in the trends of hydro-climate variables when using different statistical tests. The result showed that the mean annual temperature in many stations depicted upward trends. There is a significant increasing trend (p < 0.05) by 0.029 °C per year in the mean annual temperature of all climatic stations. Based on Sen’s slope estimator, the annual precipitation and streamflow were increased by 1.781 mm/year and 0.085 m3/s, respectively. But no significant trends were detected in precipitation and streamflow when using Sen’s slope estimator test. The results of this study are worthwhile for evaluating the trends of hydro-climatic variables in other areas of Ethiopia in particular and elsewhere in the world in general, which are fundamental for planning water resource management measures.