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In response to a congressional mandate, the US Global Change Research Program organized a National Assessment of Climate Change focusing on geographic regions (e.g. Alaska, Great Plains) and sectors (e.g. public health, agriculture, water resources). This paper describes methodology and results of a study by researchers at the Pacific Northwest National Laboratory contributing to the water sector analysis. The subsequent paper makes use of the water supply results to estimate the climate change impacts on irrigated agriculture. The vulnerability of water resources in the conterminous US to climate changes in 10-year periods centered on 2030 and 2095 as projected by the Hadley/United Kingdom Meteorological Office (UKMO) general circulation model (GCM; HadCM2) were modeled using the Hydrologic Unit Model for the United States (HUMUS). HUMUS, a biophysically based hydrology model, consists of a Geographical Information System (GIS) that provides data on soils, land use and climate to drive the Soil Water Assessment Tool (SWAT). The modeling was done at the scale of the eight-digit United States Geological Survey (USGS) Hydrologic Unit Area (HUA) of which there are 2101 in the conterminous US. Results are aggregated to the four- and two-digit (major water resource region, MWRR) scales for various purposes. Daily records of maximum/minimum temperature and precipitation (PPT) from 1961 to 1990 provided the baseline climate. Water yields (WY), used as a measure of water supply for irrigation, increases from the 1961–1990 baseline period over most of the US in 2030 and 2095. In 2030, WY increases in the western US and decreases in the central and southeast regions. Notably, WY increases by 139 mm (35%) from baseline in the Pacific Northwest. Driven by higher temperatures and reduced precipitation, WY is projected to decrease in the Lower Mississippi and Texas Gulf basins. The HadCM2 (2095) scenario projects a climate significantly wetter than baseline, resulting in water yield increases of 38% on average. Water yield increases are projected to be significant throughout the eastern US—39% in the Ohio basin, for example. Water yields increase significantly in the western US, as well—57 and 76% in the Upper and Lower Colorado, respectively. Climate change also affects the seasonality of the hydrologic cycle. Early snowmelt is induced in western basins, leading to dramatically increased water yields in late winter and early spring. The simulations were run at current (365 ppm) and elevated (560 ppm) atmospheric CO2 concentrations [CO2] to account for the potential impacts of the ‘CO2-fertilization’ effect. The effects of climate change scenario were considerably greater than those due to elevated [CO2] but the latter, overall, decreased losses and augmented increases in water yield. [Copyright &y& Elsevier]

Forest canopy structure and associated solar radiation fluxes greatly influence snow accumulation and melt and have large implications for water availability from forested areas. The ability to efficiently and explicitly infer canopy parameters at high resolution is crucial to improve the success of large scale applications of snow water resources modeling within these areas. In this paper, the utility of estimating leaf area index (LAI), canopy closure (CC) and below canopy potential incoming solar radiation (PISR) from synthetic hemispheric photos derived from airborne LiDAR data was evaluated. LAI and CC estimates from the synthetic LiDAR images were directly compared to actual hemispherical photos taken at 16 points at 7 field areas with heterogeneous canopy stand characteristics for a total of 112 photo comparison points. The synthetic data was further analyzed against LAI and CC derived from more traditional aerial LiDAR methods using a Cartesian space which integrates values over an area rather than a point based angular viewpoint. Furthermore, the PISR estimates were directly compared to in-situ radiometer measurements taken at 30 different locations during clear sky conditions with heterogeneous canopy stand properties. When compared to the actual hemispherical photos, the CC and LAI metrics from synthetic images showed higher correlations and lower biases for all canopy coverage classes (r: 0.93 for CC and r: 0.83 for LAI) than the metrics from the Cartesian approach which displayed decreased correlations and higher biases with increasing canopy closure. Using a clear sky partitioning scheme for the direct and diffuse portions of the incoming shortwave radiation, the PISR was also accurately estimated from the synthetic images with average site correlations ranging from 0.90 to 0.94 where the timing and peak trends of both the diffuse and direct radiation components were well represented. Finally, a basic methodology for the steps toward automation of the process was presented in order to explicitly derive these metrics within similar LiDAR datasets. [ABSTRACT FROM AUTHOR]

Abstract: Crop models often simulate drought impacts with full and no irrigation scenarios, while planners are more interested in whether the current available irrigation water can cope with the future more serious droughts. This paper addresses a key constraint common to modeling studies: the limited representation of actual irrigation water supply. We present a data-driven approach to identify a benchmark for agronomic drought risk levels as defined by water availability thresholds at the baseline climate (1980–2008) using reported crop yields, climate and irrigation statistics. Then, holding the current irrigation supplies, we adopted Bayesian formula to estimate magnitude of the future water availability and the associated probability of crops yields being decreased to rainfall-deficiency under climate conditions in 2030s (2020–2040) based on the RegCM3 climate model output driven by IPCC SRES A1B scenario. Results reveal that future drought stress would overwhelm the irrigation capacity of current supplies in northern and western China, while drought remains at baseline climate levels in the central, eastern and southern regions. The largest increases in the probability of projected drought risk were in northeast and southwest, ranging from 14% to 28% above baseline climate. Regional drought impacts for grain self sufficiency are discussed. [Copyright &y& Elsevier]

Abstract: To deal with water resources crisis caused by climate change and intensified human activities, the Hetao Irrigation District of Inner Mongolia in North China has been experiencing rehabilitation for water-saving since 1999. This has significantly changed its regional hydrological cycle and thus water use patterns over different land use types. In this paper, Surface Energy Balance Algorithm for Land (SEBAL) model fed with MODIS data was applied in Hetao area from 2000 to 2010 to examine the spatial and temporal patterns of evapotranspiration (ET). The SEBAL estimated ET agreed well with that from other methods in the study area. The results indicate that inter-annual variability in ET over agricultural land, water body, woodland and irrigated grassland are primarily explained by the variation of reference ET. So it is with the seasonal variability in agricultural land ET on monthly basis. However, the inter-annual variations of ET over sandy land, Gobi desert and mountain areas are mainly controlled by precipitation. Over the study period, a reduction in river water diversion for irrigation has not reduced the agricultural land ET, indicating no significant impact on agricultural production. But ET over the non-irrigated grassland tends to decrease, which was likely caused by declining groundwater table in recent years. [Copyright &y& Elsevier]

• Spatial and temporal ET dynamics are evaluated using GLEAM, PML and MTE products • The environmental drivers of ET variability in the semi-arid Sahel are identified • Global ET products are consistent with measured in the water-limited zones • Results show significant rising trend and high ET variability in the Western Sahel • Wavelet coherence results confirm strong coupling between ET and rainfall in the Sahel This paper evaluates the atmospheric controls contributing to actual evapotranspiration (ET) variability and trends across the ecological zones in the data-scarce region of West Africa. Spatial and temporal ET dynamics in the region were analysed using three selected prognostic- and machine learning-based global ET over 1983 to 2012. In addition, the responses of annual actual ET to changes in annual rainfall, atmospheric evaporative demand (AED) and incident solar radiation were evaluated using joint time-frequency wavelet decomposition method and pixel-wise partial correlation analysis. Based on the Mann-Kendall statistics, results from the Global Land Evaporation Amsterdam Model (GLEAM) data revealed high variability (> 70 mm yr−1) and significant rising trends (> 5 mm yr−1) in annual ET in the Western Sahel. In contrast, results from CSIRO Penman-Monteith Leuning (PML) ET data showed declining trends by more than 4 mm yr−1 in some parts of the Savannah zone during the study period. Results also showed some similarities in the coupling between annual ET, rainfall and AED, particularly along the Sahelian belt time-frequency domain. This implies that these atmospheric variables largely explain the signals in ET variations across the zones. However, the atmospheric variables have different modulating powers on the ET variations in the region. Additionally, we find that other non-climatic factors may have also influenced the variations in ET during the study period. This could serve as a pointer to focusing on other non-climatic drivers, potentially affecting ET trend and variability in the study area. Therefore, the study highlights the importance of providing essential and robust information on ET variability and trend as affected by different atmospheric drivers and its potential impacts on water resources, particularly in the Sahelian zone where agricultural biomes are often threatened by water stress and drought. [ABSTRACT FROM AUTHOR]

Abstract: The energy partitioning or Bowen ratio β at the surface, can be expressed as a function of a climatic factor C (which depends on the climatic characteristics through the climatological resistance r i) and of a surface factor S (which depends on the surface characteristics through the surface resistance r c). This paper explains an approach for estimating S and therefore β as a function of standard meteorological variables. The empirical approach is then validated by estimating the latent (λE) and sensible (H) heat flux. The experimental data were measured over grass at two semiarid locations in the Ebro river valley, NE Spain, with typical Mediterranean climates: at Mas Bove, using a Bowen ratio-energy balance method from 1991 to 1993, and at Zaragoza, using a weighing lysimeter from 1999 to 2000. Results show that the surface factor S depends on the square root of the absolute value of r i/r a (where r a is the aerodynamic resistance), with two locally calibrated empirical parameters. This result is valid for the largest possible range of situations (β values) throughout the day. Using three different hypotheses for computing r a, results for β (following Hypothesis 1) indicate a good level of performance by the model, although with a high degree of variability. The estimated latent heat flux λE est,1 tends to slightly underestimate the measured values. Under the semiarid conditions of the region, λE PM estimates obtained with the Penman–Monteith equation produce relative errors that are greater than those obtained with the proposed model once it has been calibrated. On average, sensible heat flux tends to be overestimated with the proposed method. [Copyright &y& Elsevier]

Abstract: The evapotranspiration (E) of an irrigated citrus (Clementine) orchard in the Mediterranean region was measured throughout a growing season. Transpiration (T) was determined by the sap flow method. Since the measurement took place on several selected branches of the citrus trees, a statistical analysis for determining the “mean tree” has been carried out before the set up of the sap gauges. In this study the daily T measured by the sap flow method has been compared with E measured by the eddy covariance method, with very good results. In addition a model of the citrus E using a Penman–Monteith-type model is presented, where the canopy surface resistance is determined from standard microclimatic variables. The calibration coefficients of the proposed model depend only on the crop and they have general validity with respect to the site. The model''s performance was evaluated by comparison with the sap flow data. The results were satisfactory and therefore this simple model allows determination the E of a Clementine orchard grown under a Mediterranean climate. In contrast to reports by the FAO no. 56 paper, and this has practical implications, the crop growth coefficient of this Clementine orchard was not constant throughout the growing season. The highest values occurred during the vegetative stage. [Copyright &y& Elsevier]

• Improved soil moisture representation can improve performance of PM models. • Segmented resistance calibration can also improve the performance of PM models. • Separate energy exchange at canopy and soil surfaces is required for sparse canopies. • Surface aerodynamic interaction and energy partitioning is important for PM models. Increased competition for water resources for agriculture calls for improved water productivities. Improved water productivities must start with accurate estimation of crop evapotranspiration (ET). Accurate estimation of ET has been a challenge for sparsely vegetated crops especially under varying soil water conditions. In this paper, we aim to improve estimation of ET using the Penman-Monteith (PM) method by (1) improved canopy resistance estimation by better representing soil water (2) improved surface resistance estimation by implementing a segmented approach of surface resistance calibration, and (3) investigating the performance of PM models over sparse vegetation by comparing four different solutions; the standard-PM model (PM-STD), the PM-Coupled (PM-CO) single-layer interactive model, the PM Shuttleworth-Wallace (PM-SW) dual-source interactive model and the PM Two-source Patch (PM-TSP) non-interactive model. The model results are evaluated against ET measurements from in-field Bowen ratio-energy balance observations. The results show that, under water-limiting conditions, correctly representing the soil moisture during the different crop development stages enhanced a PM model's ability to accurately estimate ET. The approach raised the Nash-Sutcliffe Efficiency (NSE) of a PM-STD from 0.72 to 0.75. Applying a segmented surface resistance further improved the PM-STD to an NSE of 0.77. When these improvements were implemented on the other PM models, the PM-SW and PM-CO performed superiorly with NSE of 0.83 and RMSE of 0.07 mm hr−1. The PM-TSP followed with an NSE of 0.79 and RMSE of 0.09 mm hr−1 while the PM-STD model trailed with an NSE of 0.77 and RMSE of 0.08 mm hr−1. The performance of all models highlighted the need to separate canopy and soil resistance terms during surface resistance calibration and the value of implementing a segmented approach for resistance calibration. High performance of PM-SW especially demonstrated the need to implement surface energy partitioning and surface aerodynamics interaction for canopy and soil surfaces in PM models [ABSTRACT FROM AUTHOR]

• ET was primarily radiatively driven at the two humid alpine sites. • Water supply was both controlled by precipitation with a unity slope. • Higher bulk surface resistance accounted for lower ET and higher water yields at the upper shrub. Alpine regions are generally referred to as water towers for the lowlands, yet the water balance has not been quantified for alpine catchments with different vegetation types. This paper presented a multi-year time series of evapotranspiration (ET) and water supply (precipitation minus ET) during the warm-season (June to September), measured using eddy covariance techniques for an upper alpine shrub (3400 m) and for a lower alpine meadow (3200 m), on the northeastern Qinghai-Tibetan Plateau. The monthly ET for the shrub averaged 71.8 ± 10.1 mm (Mean ± SD), which was 22.7% lower than for the meadow. ET peaked at 89.0 ± 3.0 mm for the shrub and at 113.9 ± 2.6 mm for the meadow both in July. The monthly water supply was nearly neutral from June to July and represented a surplus in August and September at both sites. The mean warm-season ET and water supply were 287.0 ± 17.6 mm and 59.6 ± 16.3 mm for the shrub, and 352.2 ± 15.7 mm and 22.5 ± 32.5 mm for the meadow, respectively. Piecewise structural equation models showed that variability of daily ET was dominated more by net radiation (R n) than by vapor pressure deficit (VPD) at both sites. However, net radiation was 32.6% higher for the shrub than for the meadow, but this did not drive higher ET for the shrub. This was explained by the difference in the energy partitioning strategy (Bowen ratio), which was attributable to the difference in the bulk surface resistance, rather than the difference in the climatological resistance (which is proportional to VPD/ R n). The seasonal and annual variability of water supply was determined by precipitation rather than by ET. The linear slopes of water supply with precipitation were all close to one, regardless of vegetation type. This suggested that the water yield efficiency was consistent at the two sites. Our results highlighted the different effects of vegetation type on ET and water supply for humid alpine regions. The lower ET loss and consequent higher water yield, but with less digestible forage in the shrub, would present a dilemma for the balance between water supply and forage production under current shrub expansion in alpine rangeland. [ABSTRACT FROM AUTHOR]

• Conclusions in Zeng et al (2020) AFM Vol 290, 15 August 2020 are debatable • Afforestation does not cause increase in surface water areas in northern China • Rise in precipitation and building water storages increases surface water areas The paper "Large-scale afforestation significantly increases permanent surface water in China's vegetation restoration regions, Agricultural and Forest Meteorology, Volume 290, 15 August 2020, 108001" by Zeng et al. (2020) finds that northern China is greening up and that "vegetation cover is an important factor in controlling permanent water changes". They suggest that afforestation partially caused the increase in surface water areas due to the "significant positive correlations between forest covers and surface water area". The authors suggest that, except precipitation, "climatic factors were not the main factor influencing permanent water". They attribute the increase in area of surface waterbody to the increase in dams, precipitation rise, and afforestation. This commentary aims at clarifying concepts of afforestation-water yield-river flow relations and offers an alternative explanation of the observed expansion of surface water areas in northern China. Using a simple water balance-based approach, we conduct a back-of-envelope calculation and show that afforestation and 'greening up' are not likely to cause an increase in water yield and surface water storage. We argue that the detected rise of permanent surface water changes in the study regions is a result of hydraulic infrastructure construction, urbanization, and increase in precipitation, perhaps not vegetation recovery from afforestation. We believe that large-scale afforestation is not likely to increase surface water resources in northern China as implied in Zeng et al (2020). Future process-based studies are needed to understand the sources of the local precipitation and the effects of revegetation on precipitation, soil improvement, and water yield. [ABSTRACT FROM AUTHOR]