Land skin temperature (LST) is one of the most important factors in the land-atmosphere interaction process. Raw measured LSTs may contain biases due to instrument replacement, changes in recording procedures, and other nonclimatic factors. This study attempts to reduce the above biases in raw daily measurements and achieves a homogenized daily LST dataset over China using 2360 stations from 1960 to 2017. The high-quality land surface air temperature (LSAT) dataset is used to correct the LST warming biases in cold months in regions north of 40ºN due to the replacement of observation instruments around 2004. Subsequently, the Multiple Analysis of Series for Homogenization (MASH) method is adopted to detect and then adjust the daily observed LST records. In total, 3.68×103 significant breakpoints in 1.65×106 monthly records are detected. A large number of these significant breakpoints are located over large parts of the Sichuan Basin and southern China. After MASH procedure, LSTs at more than 80% of the breakpoints are adjusted within +/- 0.5 ºC, and 10% of the breakpoints are adjusted over 1.5 ºC. Compared to the raw LST dataset over the whole domain, the homogenization significantly reduces the mean LST magnitude and its interannual variability as well as its linear trend at most stations. Finally, we preliminarily analyze the homogenized LST and find that the annual mean LST averaged across China shows a significant warming trend (0.22 ºC decadal-1). The homogenized LST dataset can be further adopted for a variety of applications (e.g., model evaluation and extreme event characterization).

In this study, contaminant transport behaviour in the aquifer system (140 m × 180 m × 5 m) was analyzed using a 3-D groundwater flow and contaminant transport model viz. MODFLOW2005 and MT3DMS. The impacts of hydrodynamic dispersion parameters on the conservative contaminant plume dynamics were analyzed for homogeneous and heterogeneous aquifer systems with low permeability porous media (LPPM). The spatio-temporal distribution of contaminant concentration and breakthrough curves (BTCs) at 12 observation wells were used to analyze the transport dynamics due to conservative contaminant released from a single point source over a hypothetical study area for a period of 1 year (365 days). Results from MODPATH show a significant variation in the pathway of groundwater for homogeneous and heterogeneous aquifer systems. During the source loading period, a very low value of concentration of order 10-9 mg/m3 was observed in the LPPM region. The spatial distribution of contaminant plume for aquifer system with LPPM varied largely as compared to homogeneous aquifer system. The maximum value of concentration in the aquifer with LPPM was found to be ~40% higher than the homogeneous system after source removal. After the source removal, the maximum value of 1.98 mg/m3 was observed for the homogeneous system at a location away from pumping and extraction well after 730 days; however, for a heterogeneous system with LPPM, the maximum value of 2.57 mg/m3 was observed. An early breakthrough was observed for αL= 54 m as compared to αL= 9 m for homogeneous aquifer system, clearly depicting the effect of longitudinal dispersivity on BTC. However, effects of dispersivity on the rising and falling limbs of the BTC were negligible for heterogeneous aquifer system with LPPM. Further, an impact of LPPM and longitudinal dispersivity on the peak concentration value at observation well (OBS-7) was undistinguishable. The numerical simulations carried out in this study mimic the realistic heterogeneous aquifer conditions and highlighted the relevance of LPPM and associated transport processes on contaminant transport dynamics at field-scale, which was usually overlooked.

This study presents the major ion concentrations of waters in the upper Indus River and its Tributaries with the aim to reveal the hydrochemical characteristics and its controlling factors. There is a lack of water chemistry study in the upper Indus River basin especially in the Rivers/streams flowing from and through permafrost and glaciers. Water samples were collected from mainstream and its tributaries in July 2019. The physical parameters (like pH, EC, TDS) were measured in the field, and major ions (Mg2+, K+, Ca2+, Na+, Cl−, SO42−, and NO3−) and Si were analyzed in the laboratory. The results revealed that in the study region Ca2+ and HCO3− were the dominant ions and it has diverse nature of geological formation. The total dissolved solids (TDS) within the Indus River varies from 132.0 mg/l to 217.0 mg/l generally decreasing from upstream to downstream, under the influence of the semi-arid climatic conditions and relatively lower anthropogenic interference in the UIRB. The high concentrations of Na+ and K+ in the saline lakes (Pangong lake) sample were mainly affected by evaporation. Rock weathering is the dominant controlling factor for the water chemistry of the UIRB, and more specifically crystalline rocks and sedimentary carbonates. Different methods were utilized to identify the controlling mechanism of river geochemistry in the UIRB as silicate weathering in general with variable degrees of carbonate weathering and small contribution by evaporite weathering respectively. The present study provided the foundation for the overall water chemistry characteristics of the whole Indus River basin as well as glacier-fed Himalayan Rivers.

The human health risk assessment (HHRA) of groundwater system in the vicinity of Chandigarh dumping site was conducted, assuming oral ingestion and dermal contact exposure scenarios. Observed data of lead (Pb) concentration in the leachate was used to compute cancer risk (CR) by integrating unsaturated 1-D leaching model with probabilistic HHRA framework. The 99 percentile and maximum value of lead (Pb) concentration at the water table was estimated as 0.089 mg/L and 0.506 mg/L, respectively, for pre-monsoon season, higher than the safe limit of 0.050 mg/L. In contrast, for the post-monsoon season, only the maximum value of Pb concentration exceeded the safe limit. Results from 10,000 Monte Carlo simulations showed that the 99 percentile and maximum value of CR for all the sub-populations during pre-monsoon exceeded the safe limit (>10 ) via oral ingestion exposure to Pb-contaminated groundwater. The 95 percentile value of CR for adult sub-population was estimated as 1.05 x 10 for premonsoon; however, for the post-monsoon season, only maximum values of CR exceeded the safe limit. The cancer risk estimates for the pre-monsoon and post-monsoon seasons via skin dermal contact exposure were found to be lower than the safe level, posing no danger to human health. Among sub-populations, the order of posing CR was found to be in the order as adults (>18 years) > child I (1-5 years) > teen (11-18 years) > child II (6-10 years). Uncertainty analysis showed that the lead concentration (>95% variance contribution), as a major contributor towards uncertainty in the risk estimates, while event duration (t ), exposure duration (ED), and ingestion rate (IR) were observed as minor contributors. The approach presented in this study considered the uncertainty in the unsaturated leaching model parameters along with uncertainty in the exposure model parameters, thus can help decision-makers in estimating risk from open dumping sites with minimal data availability.

At-a-station hydraulic geometry (AHG), which describes how channel width, depth, and velocity vary with discharge at a river cross section, has long been used to study fluvial processes. For example, identification of landscape and river reach drivers of hydraulic geometry can help to predict channel properties at ungaged sites and to understand channel responses to major floods. Most prior AHG studies have focused on mid-latitude, temperate regions. Tropical zones-including those affected by tropical cyclones (TCs)-have received less attention. This study analyzed spatial and temporal variability in hydraulic geometry at 24 stream gaging sites in Puerto Rico, and identified the watershed and river reach characteristics that correlate with each hydraulic geometry parameter. These characteristics were then used to build regression models of AHG parameters, with relatively high predictive power. The largest flood events from each site were found to cause systematic changes to AHG parameters; most of these floods were caused by major TCs. Upstream drainage area, average watershed elevation, watershed land cover and other characteristics were found to be significant predictors of AHG parameters. Reaches with steeper slopes were found to have limited lateral adjustability, which may reflect consolidated bank materials and valley confinement. Watersheds with high percentages of forested area showed greater changes in roughness but less vertical adjustability than more developed watersheds. These correlation results help inform whether river channel properties in Puerto Rico and similar environments are resistant to the forces of TC-induced flooding, and how these properties are affected by major floods.

Many water quality and ecosystem functions performed by streams occur in the benthic biolayer, the biologically active upper (~5 cm) layer of the streambed. Solute transport through the benthic biolayer is facilitated by bedform pumping, a physical process in which dynamic and static pressure variations over the surface of stationary bedforms (e.g., ripples and dunes) drive flow across the sediment-water interface. In this paper we derive two predictive modeling frameworks, one advective and the other diffusive, for solute transport through the benthic biolayer by bedform pumping. Both frameworks closely reproduce patterns and rates of bedform pumping previously measured in the laboratory, provided that the diffusion model’s dispersion coefficient declines exponentially with depth. They are also functionally equivalent, such that parameter sets inferred from the advective model can be applied to the diffusive model, and vice versa. The functional equivalence and complementary strengths of these two models expands the range of questions that can be answered, for example by adopting the advective model to study the effects of geomorphic processes (such as bedform adjustments to land use change) on flow-dependent processes, and the diffusive model to study problems where multiple transport mechanisms combine (such as bedform pumping and turbulent diffusion). By unifying advective and diffusive descriptions of bedform pumping, our analytical results provide a straightforward and computationally efficient approach for predicting, and better understanding, solute transport in the benthic biolayer of streams and coastal sediments.

To cope with the uncertainty of green infrastructure planning at city scale, many cities take an adaptive approach and use learning-by-doing to improve understanding of the urban systems. However, whether that learning is worth it has been a challenge to adaptive management practitioners. In this paper, we propose an evaluation and planning framework for green infrastructure (GI) to address this issue and demonstrate its use by an application to the Wingohocking water-shed, Philadelphia, PA, USA. The framework allows users to specify possible knowledge gains from near-term actions and assess the impacts of this learning on subsequent decisions, which enables evaluation of the net benefits of alternative investment plans. In the case study, we consider two types of learning: learning to reduce uncertainty and learning to improve performance. This learning can happen through investments or knowledge transfer from experience at other locations. Estimates of cost, performance, and deterioration over time of GI and the prediction of possible knowledge gains are based on the literature and expert opinions. The results propose optimal investment strategies over a 25-year planning horizon and describe tradeoffs between the risk of poor performance and reductions in expected annual stormwater runoff. Finally, by calculating differences in expected total costs between non-adaptive, passive adaptive, and active adaptive decision-making, we quantify the economic value of learning and adaptability.

The 2020 Monte Cristo Earthquake sequence in western Nevada began with a M6.5 shock on 5/15/20, and was the largest to occur in Nevada since 1954. The event exhibited left-lateral slip along an eastward extension of the Candelaria fault and extensive distributed surface faulting in the epicentral area. Groundwater monitoring and strain analysis were conducted to evaluate hydrochemical effects on the regional groundwater systems following the initial event. Physio-chemical monitoring, (started on 5/16 and still ongoing) includes measurements of temperature (temp), pH, specific conductance (SpC), flow rate, alkalinity and collection of samples for major ions and trace element analysis. Since sites had not been monitored prior to the initial shock, measurements were evaluated against a year of post-event data to gauge response to seismicity. Four sites were monitored: a well from Columbus Marsh (CM) located 5 km from the epicenter; an artesian thermal well from Fish Lake Valley (FL); a well at Willow Ranch (WR) tapping cool water above the FL waters; and a spring along Mina Dump Road (MD) located 15 km north of the Candelaria fault on the Benton Springs Fault. GPS and InSAR measurements were used to create a model of the slip from which we estimated coseismic strain at each sampling location. All but one sample site, MD, experienced positive dilation and CM experienced the greatest amount of strain (15-17 microstrains). Hydrologic and chemical changes were observed following the initial shock, varying between sites. CM had significantly lower SpC values in the week following the event, as well as changes in major ion composition. Other sites showed minor changes; MD showed fluctuations in pH values and FL experienced a slight drop in temp. These waters showed minimal changes in major ions and trace elemental composition. Clear responses were observed throughout three >M5 aftershocks (6/30/20, 11/13/20, and 12/1/20), especially in SpC and alkalinity. A remarkable change in elemental concentration (an increase in Ca, K, SO4, Fe, and decrease in Na, Cl, Li, and Ba) was observed in CM. WR experienced a transient increase in temp measured two weeks prior to the 11/13/20 earthquake. Strain analyses of the smaller (>M5) events are planned to further evaluate observed responses and to clarify factors affecting groundwater response.

The Delaware River is a major freshwater supplier of New York City (NYC). Nearly half of NYC drinking water is supplied by inter-basin transfer of surface water stored in reservoirs within the upper reaches of the Delaware River. In its lower reaches, the Delaware River is a tidal estuary, and upstream freshwater discharge provides a critical control on estuary salinity. During the record 1950–1960’s drought, NYC water withdrawals exacerbated low flows. Estuary salinity reached levels that threatened freshwater intakes and groundwater recharge, resulting in legal action and Supreme Court decrees. We revisit this classic case study in coupled human and natural systems using the Energy Exascale Earth System Model (E3SM). The E3SM water management sub-model is updated to include inter-basin water transfer and reservoir-specific operating rules. Model simulations are developed to investigate competition between NYC water demand and in-stream flow targets needed to maintain estuary salinity within regulatory guidelines under historic and future climate. To our knowledge, this is a first demonstration of an Earth System Model simulation with inter-basin water transfer, which, in this study area, provides water for nearly five million people living outside the Delaware River basin in New York City and New Jersey.

Permafrost active layer thickness (ALT) is a sensitive indicator of permafrost response to climate change. In recent decades, ALT has increased at sites across the Arctic, concurrent with observed increases in annual minimum streamflow (baseflow). The trends in ALT and baseflow are thought to be linked via: 1) increased soil water storage capacity due to an increased active layer, and 2) enhanced soil water mobility within a more continuous active layer, both of which support higher baseflow in Arctic rivers. One approach to analyzing these changes in ALT and baseflow is to use baseflow recession analysis, which is a classical method in hydrology that relates groundwater storage S to baseflow Q with a power law-like relationship Q = aSb. For the special case of a linear reservoir (b=1.0), the baseflow recession method has been extended to quantify changes in ALT from streamflow measurements alone. We test this approach at sites across the North American Arctic and find that catchments underlain by permafrost behave as nonlinear reservoirs, with scaling exponents b~1.5–3.0, undermining the key assumption of linearity that is commonly applied in this method. Despite this limitation, trends in a provide insight into the relationship between changing ALT and changing Arctic baseflow. Although care should be taken to ensure the theoretical assumptions are met, baseflow recession analysis shows promise as an empirical approach to constrain modeled permafrost change at the river basin scale.

The agricultural sector is a major consumer of water for irrigation purposes. Precise quantification of irrigation water requirements will help in achieving sustainable water management. Root water uptake (RWU) is driven by transpiration demand exerted by crops and is influenced by factors such as weather and leaf area index (LAI). The root water uptake at a particular depth in the root zone depends on the local moisture content, soil type, and root density. Under certain conditions, lack of availability of soil moisture at a certain depth may be compensated by more water being drawn into the roots from wetter portions of the soil. To incorporate this mechanism, this study presents a compensated root water uptake model (CRWU) with application to maize crops grown in Indian climatic conditions. Irrigation field experiments were conducted at seven field plots with the same soil by adjusting the irrigation supplied to simulate different degrees of water stress. Daily soil moisture data recorded at different depths in the root zone, crop yield and biomass data help in assessing model performance and identifying a critical water stress index that governs the extent of compensation in RWU.

A substantial body of research has addressed the equilibrium cross-sectional geometry of straight noncohesive channels, along with bends having fixed outer banks. However, development of a characteristic cross-section during active migration has been confounded by inaccurate treatment of noncohesive bank erosion processes. This analysis characterizes a steady-state migrating cross-section and the associated migration rate for the highly conceptualized case of an infinite bend of constant centerline radius with noncohesive lower banks consisting of uniform-sized grains mobilized as bedload. Analytical, numerical, and field analyses are presented to rationally constrain the geometry and obtain a physically based migration rate equation dependent on the following dimensionless groupings: excess Shields stress, flow depth to radius of curvature ratio, and noncohesive bank thickness to grain size ratio. Migration rate is shown to be dictated by transverse sediment flux at the thalweg due to secondary flow, not bank slope as in previous formulations developed from similar principles. Simple outward translation can result without the characteristic cyclic process observed in cohesive banks (fluvial erosion, oversteepening, and mass failure). This suggests that the linear excess shear stress formulation that applies to cohesive soils misrepresents noncohesive bank erosion processes. A numerical model of cross-sectional evolution to steady-state migration is developed; when applied to the lower Mackinaw River in Illinois, it reveals that the river behaves as if the critical shear stress is considerably larger than that indicated by the grain size distribution. This conceptualized treatment is intended to provide a canonical basis of comparison for actual meander bend geometries.

Climate data from Earth System Models are increasingly being used to study the impacts of climate change on a broad range of biogeophysical (forest fires, fisheries, etc.) and human systems (reservoir operations, urban heat waves, etc.). Before this data can be used to study many of these systems, post-processing steps commonly referred to as bias correction and statistical downscaling must be performed. “Bias correction” is used to correct persistent biases in climate model output and “statistical downscaling” is used to increase the spatiotemporal resolution of the model output (i.e. 1 deg to 1/16th deg grid boxes). For our purposes, we’ll refer to both parts as “downscaling”. In the past few decades, the applications community has developed a plethora of downscaling methods. Many of these methods are ad-hoc collections of post processing routines while others target very specific applications. The proliferation of downscaling methods has left the climate applications community with an overwhelming body of research to sort through without much in the form of synthesis guiding method selection or applicability. Motivated by the pressing socio-environmental challenges of climate change – and with the learnings from previous downscaling efforts in mind – we have begun working on a community-centered open framework for climate downscaling: scikit-downscale. We believe that the community will benefit from the presence of a well-designed open source downscaling toolbox with standard interfaces alongside a repository of benchmark data to test and evaluate new and existing downscaling methods. In this notebook, we provide an overview of the scikit-downscale project, detailing how it can be used to downscale a range of surface climate variables such as air temperature and precipitation. We also highlight how scikit-downscale framework is being used to compare existing methods and how it can be extended to support the development of new downscaling methods.

Global ocean mean salinity (GMS) is a key indicator of the Earth’s hydrological cycle and the exchanges of freshwater between land and ocean, but its determination remains a challenge. Aside from traditional methods based on gridded salinity fields derived from in situ measurements, we explore estimates of GMS based on liquid freshwater changes derived from space gravimetry data corrected for sea ice effects. For the 2005-2019 period analyzed, the different GMS series show little consistency in seasonal, interannual, and long-term variability. In situ estimates show sensitivity to choice of product and unrealistic variations. A suspiciously large rise in GMS since ~ 2015 is enough to measurably affect halosteric sea level estimates and can explain recent discrepancies in the global mean sea level budget. Gravimetry-based GMS estimates are more realistic, inherently consistent with estimated freshwater contributions to global mean sea level, and provide a way to calibrate the in situ estimates.

We present a seismo-acoustic analysis of the debris-flow activity between 2017 and 2019 at the Illgraben catchment (Switzerland). To understand fluid dynamic processes involved in the seismo-acoustic energy generation by debris-flows, seismic and acoustic amplitudes (maximum root mean square amplitude, RMSA) and peak frequencies are compared with flow measurements (front velocity, maximum flow depth and density). Front velocity, maximum depth, peak discharge and peak mass flux show a positive correlation with both infrasonic and seismic maximum RMSA, suggesting that seismo-acoustic radiation is controlled by these flow parameters. Comparison between seismo-acoustic peak frequencies and flow parameters reveal that, unlike seismic signals, characterized by a constant peak frequency regardless of the magnitude of the flow, infrasound peak frequency decreases with increasing flow velocity, depth and discharge. Based on all collected evidence, we suggest that infrasound signals of debris-flows are generated by flow waves and water splashes that develop at the free-surface of the flow, whose dimension scales with flow magnitude. According to fluid dynamics, such surface oscillations are mostly generated wherever the flow encounters significant channel irregularities, such as topographic steps and planform steep bends, that therefore likely constitute preferential sources of infrasound. As for seismic waves, results are consistent with previous theoretical models and field observations, which attribute debris-flow seismicity to solid particle collisions, friction and fluid dynamic structures. Finally, the observed positive correlations between seismo-acoustic signal features and flow parameters highlight the potential to use infrasound and seismic measurements for debris-flow monitoring and risk management.

The Yeongsan River in southwestern Korea is 150 km long and has a basin area of 3,551 km2. A number of hydraulic structures have been installed along the river, including an estuary dam and two weirs (Seungchon and Juksan). While these structures aid in regional water security and reduced flooding, they stagnate water flow and frequently cause algal blooms during the summer. This study simulated the algal bloom and water quality characteristics in the middle and downstream sections of the Yeongsan River under different weir and estuary dam operating conditions using the Environmental Fluid Dynamics Code-National Institute of Environment Research (EFDC-NIER) model. Results showed that when the management levels of the Juksan Weir and estuary dam were maintained, the simulated water levels were 3.7 and -1.2 m in the Juksan Weir and estuary dam sections, respectively. When both the Juksan Weir and estuary dam were open, the water levels varied with the tide and were maintained at an average of 0.2-0.6 m in contrast, when the Juksan Weir alone was open, the water level was between -1.2 and -0.9 m in line with the management level of the estuary dam. Opening the Juksan Weir alone reduced the algal blooms by 72-84% in the Juksan Weir section, and opening the estuary dam alone reduced the algal blooms by 83% in the estuary dam. This improvement was attributed to the reduced water retention time and dilution due to seawater inflows.

As the largest hydroelectric projects worldwide, the Three Gorges Dam (TGD) affects local precipitation because of the changes of hydrological cycle caused by the impounding and draining of the TGD. However, the influencing characteristics of the TGD on local precipitation remain elusive. In this study, we used precipitation anomaly data derived from long time-series grid precipitation datasets between 1988 and 2017 to understand the changes of precipitation caused by the TGD between 2 epochs, before and after the construction of the TGD (i.e., 1988–2002 and 2003–2017), in the Three Gorges Reservoir Area (TGRA). Results showed that the annual and dry season precipitation anomaly in the TGRA showed an increasing trend, and the flood season precipitation anomaly showed a slight decrease. After the impoundment of the TGD, the precipitation concentration degree in the TGRA was decreased, indicating that the precipitation became increasingly uniform, and the precipitation concentration period was insignificantly increased. An obvious resonance phenomenon between the monthly average water level and precipitation anomaly occurred in the TGRA after 2011 and showed a positive correlation. Our findings excavated the change of local precipitation characteristics before and after the impoundment of the TGRA and proved that this change had a close relationship with the water level.

The diatom oxygen isotope composition (δ18Odiatom) from lacustrine sediments helps tracing the hydrological and climate dynamics in individual lake catchments, and is generally linked to changes in temperature and δ18Olake. Lake Bolshoye Shchuchye (67°53’N; 66°19’ E; 186 m a.s.l) is the largest and deepest freshwater reservoir in the Polar Urals, Arctic Russia. Its δ18Odiatom record generally follows a decrease in summer insolation and the northern hemisphere (NH) temperature history. However, it displays exceptional, short-term variations exceeding 5‰, especially in Mid and Late Holocene. This centennial-scale variability occurs contemporaneously with and similarly to Holocene NH glacier advances. However, larger Holocene glacier advances in the Lake Bolshoye Shchuchye catchment are unknown and have not left any significant imprint on the lake sediment record. As Lake Bolshoye Shchuchye is deep and voluminous, about 30−50% of its volume needs to be exchanged with isotopically different water within decades to account for these shifts in the δ18Odiatom record. A plausible source of water with light isotope composition inflow is snow, known to be transported in surplus by snow redistribution from the windward to the leeward side of the Polar Urals. Here, we propose snow melt and influx changes being the dominant mechanism responsible for the observed short-term changes in the δ18Odiatom record. This is the first time such drastic, centennial-scale hydrological changes in a catchment have been identified in Holocene lacustrine diatom oxygen isotopes, which, for Lake Bolshoye Shchuchye, are interpreted as proxy for summer temperatures and palaeo precipitation.

In operational analyses of the surface moisture imbalance that defines drought, the supply aspect has generally been well characterized by precipitation; however, the same count be said of the demand side—a function of evaporative demand (E0) and surface moisture availability. In drought monitoring, E0 is often poorly parameterized by a climatological mean, by non-physically based estimates, or is neglected entirely. One problem has been a paucity of driver data—on temperature, humidity, solar radiation, and wind speed—required to fully characterize E0. This deficient E0 modeling is particularly troublesome over data-sparse regions that are also home to drought-vulnerable populations, such as across much of Africa. There is thus urgent need for global E0 estimates for physically accurate drought analyses and food security assessments; further we need an improved understanding of how E0 and drought interact and to exploit these interactions in drought monitoring. In this presentation we explore ways to meet these needs. From MERRA-2—an accurate, fine-resolution land-surface/atmosphere reanalysis—we have developed a >38-year, daily, global Penman-Monteith reference ET dataset as a fully physical metric of E0. This dataset is valuable for examining hydroclimatic changes and extremes. A novel drought index based on this dataset—the Evaporative Demand Drought Index (EDDI)—represents drought’s demand perspective, and permits early warning and ongoing monitoring of agricultural flash drought and hydrologic drought. We highlight the findings of our examination of E0-drought interactions and using EDDI in Africa. Using reference ET as an E0 metric has permitted explicit attribution of the variability of E0 across Africa, and of E0 anomalies associated with canonical droughts in the Sahel region. This analysis determines where, when, and to what relative degree each of the individual drivers of E0 affects the demand side of drought. Using independent estimates of drought across space and time—CHIRPS precipitation and the Normalized Difference Vegetation Index for 1982-2015—we examine the differences between drought and non-drought periods, and between precipitation-forced droughts and droughts forced by a combination of precipitation and E0.

Integrated management of surface water and groundwater is the key to achieve sustainable water resources and secure water availability, especially in arid and semi-arid regions of the world. With generally scarce surface water resources, groundwater often is the primary source of water supply in such regions, with significant groundwater-surface water (GW/SW) interactions often occurring in irrigated regions. The objective of this study is to quantify the variation in stream seepage and groundwater discharge fluxes in an agro-urban river basin as impacted by climate change. To achieve this goal, i) an integrated hydrologic modeling code that accounts for groundwater and surface water processes and exchanges in large regional-scale managed river basins is developed for the South Platte River Basin (72,000 km2), Colorado, and ii) possible future impacts imposed by climate change on surface water and groundwater exchange in a basin-scale complex semi-arid region is assessed. The developed updated version of SWAT-MODFLOW is forced with five different CMIP5 climate models downscaled by Multivariate Adaptive Constructed Analogs (MACA), each for two climate scenarios, RCP4.5, and RCP8.5, for 1980-2100. The projected GW/SW fluxes from 2000 through the end of the century are presented in 4 different time intervals along the South Platte River and its tributaries- current (2000-2020), near future (2021-2040), mid-century (2041-2070), and end of the century (2071-2100) in dry (February) and wet (May) months of the year. The changes in stream seepage and groundwater discharge fluxes in dry and wet months of the year follow different patterns, as groundwater discharge to streams decreases during the dry months while the water table elevation declines. Overall, under the most extreme climate condition groundwater discharge will decrease by approximately 10% by 2100.

Channels and the water they convey control the spatial extent of aquatic ecosystems and the evolution of landscapes. Over geologic time scales (millions of years), flow rates have varied with changes in climate, glacial extent and tectonics; however, over shorter time scales, flow rates have remained stable enough to permit the establishment of unique ecosystems that depend on and interact with specific flow and sediment transport regimes. On the Olympic Peninsula, that relative stability was altered when humans converted vast areas of old-growth forest to tree plantations during the 20th century; however, because of the remote location and unstable nature of the channels affected by the tree farms, exactly how stream flow has changed is unknown. This study presents preliminary flow observations in the Olympic Experimental State Forest (OESF), a 110,000 ha block of public land on the west side of the Olympic Peninsula that is presently being managed for both timber and ecosystem values. Through repeat flow measurements and channel surveys and the installation of pressure transducers and staff gages, we are developing a long-term record of flow in small, (basin area 50 to 700 ha) step-pool to cascade channels that transport pulses of sediment and violently swing between low and high flows. Preliminary flow observations indicate that the geologic setting of the basin plays a large role in hydrograph characteristics and that picking out a vegetation signal in the flow record may be difficult. Nonetheless, the long-term goal of these observations is to quantify flow trends and help humans (The Washington State Department of Natural Resources) better understand how past and present tree harvests on the Olympic Peninsula may be altering natural hydrologic and geomorphic processes. Monitoring techniques we are using to measure flow in these small, dynamic streams, including the use of BaRatin (Le Coz et al., 2013) to develop rating curves, are presented. Future monitoring goals and plans to use the flow records for geomorphic and hydrologic modeling studies are also discussed.

As sources of fresh water and critical components of the global climate system, terrestrial glaciers are important features to monitor, particularly in light of anthropogenic climate change. Remote sensing techniques are being increasingly used to gather information on Earth’s shrinking complex glacial terrains. However, these methods possess critical challenges, including capturing firn dynamics and the presence of ice lenses. Meltwater percolation and retention, as well as thermodynamic effects on snow and firn density can complicate the relationship between surface height and mass balance changes; lowering of the glacier surface may masquerade as a mass change as detected by remote sensing technologies. The St. Elias Mountains, straddling the border between Yukon Territory, Canada and Alaska, USA, are home to extensive icefields. While numerous mass balance studies have been conducted in this region using remote sensing, there is a significant lack of in situ measurements of accumulation zone processes and firn properties. Our research examines refrozen ice layers and firn densification processes in the accumulation zone of Kaskawulsh Glacier in the St. Elias Mountains. In spring 2018, we extracted two firn cores (20 m and 35 m) from the study area and conducted a snow stratigraphy and ice lens survey on both core sections. After subsampling and melting the cores, we analyzed major ion and isotope chronology to identify extreme meltwater percolation and refreezing events, both of which critically affect firn density. The snow stratigraphy analysis from both of the cores showed numerous refrozen ice layers, indicating surface melt and refreezing processes in the accumulation zone. Preliminary results from isotope chronology analysis reveal a wash-out of the glaciochemical pattern in the 35 m and the 20 m ice core at 15 m depth, thus indicating severe surface warming events and subsequent changes in the density of the firn. This may indicate errors in the assumed density of the accumulation zone snow and firn when using remote sensing technologies to infer mass balance of Kaskawulsh Glacier.

Tropical peatlands are among the most carbon-dense ecosystems on Earth, and their water storage dynamics strongly control these carbon stocks. The hydrological functioning of tropical peatlands differs from that of northern peatlands, which has not yet been accounted for in global land surface models (LSMs). Here, we integrated tropical peat-specific hydrology modules into a global LSM for the first time, by utilizing the peatland-specific model structure adaptation (PEATCLSM) of the NASA Catchment Land Surface Model (CLSM). We developed literature-based parameter sets for natural (PEATCLSMTrop,Nat) and drained (PEATCLSMTrop,Drain) tropical peatlands. The operational CLSM version (which includes peat as a soil class) and PEATCLSMTrop,Nat were forced with global meteorological input data and evaluated over the major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia. Evaluation against a unique and extensive data set of in situ water level and eddy covariance-derived evapotranspiration showed an overall improvement in bias and correlation over all three study regions. Over Southeast Asia, an additional simulation with PEATCLSMTrop,Drain was run to address the large fraction of drained tropical peatlands in this region. PEATCLSMTrop,Drain outperformed both CLSM and PEATCLSMTrop,Nat over drained sites. Despite the overall improvements of both tropical PEATCLSM modules, there are strong differences in performance between the three study regions. We attribute these performance differences to regional differences in accuracy of meteorological forcing data, and differences in peatland hydrologic response that are not yet captured by our model.

The highlands of Ethiopia are a densely populated, agriculturally active region characterized by strong topographic contrasts. These contrasts have significant implications for agricultural productivity and for vulnerability to climate variability and change. These differing vulnerabilities are evident in analyses of economic and health outcomes over time, and they were on stark display during the major El Niño drought of 2015. To provide meaningful analysis of climate vulnerability in this region and, ultimately, to support climate resilience strategies, it is necessary to account for this topographic diversity. Recognizing this, the Government of Ethiopia has applied an “adaptation zone” approach to climate change planning, in which adaptation zones are defined in large part by agroecology. Here, we present results of studies we have performed in the Ethiopian Highlands over the past decade in which agroecosystems were applied as a lens for analyzing hydrology, land management and change, agricultural production, and nutrition under climate variability. This approach has informed a number of active development initiatives in the region, including protection of high elevation zones, farmer-led initiatives on soil and water management, and introduction of new cropping strategies. Looking forward, climate projections at the scale of the agroecosystem point to emerging risks and opportunities for resilient agricultural development in the region.