Russell. J. Qualls

Traditional snow depletion curves (SDC) fail to relate aggregated snow covered area (SCA) with the specific location of the snowline on a daily time step. This spatial uncertainty is compounded with temporal date uncertainty in cloud‐gap filling (CGF)—the process of infilling cloud covered pixels in daily remotely sensed snow cover—and limits their utility for long term forecasting. This study formalizes the spatial Snow Depletion Curve (sSDC): a dual‐model framework that anchors the temporal regression based depletion forecasts in the dynamic seasonally recurrent snow depletion pattern which is a stationary watershed characteristic. We present a dual stage architecture where Model 1 uses dynamic seasonally recurrent snow depletion patterns to resolve data uncertainty in CGF, which then serves as the foundation for Model 2—the sSDC—to convert SCA to τ * that creates a linear relationship between snow depletion and time. The ability of Model 2 to enable reliable forecasts results from the main finding of this work: that there is a linear relationship between day of year of melt out and the pixel relative timing variable ( τ *) of the dynamic seasonally recurrent snow depletion pattern. Validation across a 21‐year record demonstrates the framework's ability to track snow depletion ( R ² = 0.97) and crucially predict final melt timing within ±0.6 days more than 2 months in advance. Testing over the Upper Snake River Basin—a large and critical water tower in the Western US that experienced a range of climactic variability—confirms the framework's robustness. Our dual‐model framework provides the high fidelity snowline on a daily timestep required for snowmelt runoff models, effectively translating static watershed patterns into dynamic, predictive temporal forecasts. The framework extracts inherent watershed characteristics and provides a promising method for application in mountainous, seasonal snow cover/snowmelt basins worldwide.

This study compares four different hypotheses regarding the nature of the Priestley-Taylor parameter α. They are: 1) α is a universal constant; 2) the Bowen ratio (H/LE, where H is the sensible and LE is the latent heat flux) for equilibrium (i.e. saturated air column near the surface) evaporation is a constant times the Bowen ratio at minimal advection (Andreas et al., 2013); 3) minimal advection over a wet surface corresponds to a particular relative humidity value, and 4) α is a constant fraction of the difference from the minimum value of one to the maximum value of α proposed by Priestley and Taylor (1972). Formulas for α are developed for the last three hypotheses. Weather, radiation and surface energy flux data from 171 FLUXNET eddy covariance stations were used. The condition LE_ref/LE_p>0.90, was taken as the criterion for nearly-saturated conditions (where LE_ref is the reference and LE_p is the apparent potential evaporation rate from the Penman (1948) equation). Daily and monthly average data from the sites were obtained. All formulations for α include one model parameter which is optimized such that the root mean square error of the target variable was minimized. For each model, separate optimizations were done for predictions of the target variables α, wet surface evaporation (α multiplied by equilibrium evaporation rate) and actual evaporation (the latter using a highly-successful version of the complementary relationship of evaporation). Overall, the second and fourth hypotheses received the best support from the data.

This study compares four different hypotheses regarding the nature of the Priestley-Taylor parameter α. They are: 1) α is a universal constant; 2) the Bowen ratio (H/LE, where H is the sensible and LE is the latent heat flux) for equilibrium (i.e. saturated air column near the surface) evaporation is a constant times the Bowen ratio at minimal advection (Andreas et al., 2013); 3) minimal advection over a wet surface corresponds to a particular relative humidity value, and 4) α is a constant fraction of the difference from the minimum value of one to the maximum value of α proposed by Priestley and Taylor (1972). Formulas for α are developed for the last three hypotheses. Weather, radiation and surface energy flux data from 171 FLUXNET eddy covariance stations were used. The condition LE_ref/LE_p>0.90, was taken as the criterion for nearly-saturated conditions (where LE_ref is the reference and LE_p is the apparent potential evaporation rate from the Penman (1948) equation). Daily and monthly average data from the sites were obtained. All formulations for α include one model parameter which is optimized such that the root mean square error of the target variable was minimized. For each model, separate optimizations were done for predictions of the target variables α, wet surface evaporation (α multiplied by equilibrium evaporation rate) and actual evaporation (the latter using a highly-successful version of the complementary relationship of evaporation). Overall, the second and fourth hypotheses received the best support from the data.

This study compares four different hypotheses regarding the nature of the Priestley-Taylor parameter α. They are: 1) α is a universal constant; 2) the Bowen ratio (H/LE, where H is the sensible and LE is the latent heat flux) for equilibrium (i.e. saturated air column near the surface) evaporation is a constant times the Bowen ratio at minimal advection (Andreas et al., 2013); 3) minimal advection over a wet surface corresponds to a particular relative humidity value, and 4) α is a constant fraction of the difference from the minimum value of one to the maximum value of α proposed by Priestley and Taylor (1972). Formulas for α are developed for the last three hypotheses. Weather, radiation and surface energy flux data from 171 FLUXNET eddy covariance stations were used. The condition LE_ref/LE_p>0.90, was taken as the criterion for nearly-saturated conditions (where LE_ref is the reference and LE_p is the apparent potential evaporation rate from the Penman (1948) equation). Daily and monthly average data from the sites were obtained. All formulations for α include one model parameter which is optimized such that the root mean square error of the target variable was minimized. For each model, separate optimizations were done for predictions of the target variables α, wet surface evaporation (α multiplied by equilibrium evaporation rate) and actual evaporation (the latter using a highly-successful version of the complementary relationship of evaporation). Overall, the second and fourth hypotheses received the best support from the data.

This study compares four different hypotheses regarding the nature of the Priestley-Taylor parameter α. They are: 1) α is a universal constant; 2) the Bowen ratio (H/LE, where H is the sensible and LE is the latent heat flux) for equilibrium (i.e. saturated air column near the surface) evaporation is a constant times the Bowen ratio at minimal advection (Andreas et al., 2013); 3) minimal advection over a wet surface corresponds to a particular relative humidity value, and 4) α is a constant fraction of the difference from the minimum value of one to the maximum value of α proposed by Priestley and Taylor (1972). Formulas for α are developed for the last three hypotheses. Weather, radiation and surface energy flux data from 171 FLUXNET eddy covariance stations were used. The condition LE_ref/LE_p>0.90, was taken as the criterion for nearly-saturated conditions (where LE_ref is the reference and LE_p is the apparent potential evaporation rate from the Penman (1948) equation). Daily and monthly average data from the sites were obtained. All formulations for α include one model parameter which is optimized such that the root mean square error of the target variable was minimized. For each model, separate optimizations were done for predictions of the target variables α, wet surface evaporation (α multiplied by equilibrium evaporation rate) and actual evaporation (the latter using a highly-successful version of the complementary relationship of evaporation). Overall, the second and fourth hypotheses received the best support from the data.

The linear form of the nondimensional complementary relationship (CR) follows from an isenthalpic process of evaporation under a constant surface available energy and unchanging wind. Mixing of external moisture into the boundary layer (BL) alters the dry‐end second‐type boundary condition yielding a polynomial that can be further generalized into a three‐parameter (Priestley‐Taylor α, a, b) power function (PF₃), capable of responding to the level of such admixing. With the help of FLUXNET data and setting a = 2 for a possible recapture of the linear and/or polynomial versions of the CR, it is demonstrated that the resulting two‐parameter PF (i.e., PF₂) excels among the CR‐based two‐parameter models considered in this study. PF₂ is then employed with a globally set constant value of α = 1.1 and 0.5° monthly data across Australia, while calibrating b against the multiyear water‐balance evaporation rate on a cell‐by‐cell basis. The resulting bi‐modal histogram peaks first near b = 2 (recapturing the polynomial CR) when moisture admixing is significant, and then at b → 1 (yielding the linear CR) when mixing effects are negligible. Unlike the linear or polynomial CR versions, PF₂ can respond to the general efficiency of external moisture admixing through its parameter b, making it applicable even near sudden discontinuities in surface moisture. A new duality emerges with the PF₂: while α accounts for the effect of entrainment of free tropospheric drier air into the BL on the resulting wet‐environment evaporation rate, b does so for moisture on the drying‐environment evaporation rates.

Environmental justice and equity should include access to clean water for all. It is expensive to drill borehole wells, typically over $10,000 US dollars, and so organizations working to provide wells in developing countries have typically installed community wells at some common gathering place. This requires that many users must walk long distances to access these water sources. This limits the quantity of water available to a family, and also creates vulnerabilities for the family member, usually a woman or child, sent for the water since the journey is often made early in the morning or at night in the dark. I have been drilling wells with a Kenyan team since 2010 using a simple, manual percussion hydraulic method developed by WaterForAllinternational.org whereby we can install a well generally for less than $200 US dollars excluding labor. Through their own participation in the drilling process, this low-cost enables families to pay for and drill their own well. In this way, they gain access to a much larger supply of water at or close to home, and eliminate the need and vulnerability associated with walking long distances to procure water for their family. Both the drilling apparatus and the cased well, including the pump, is constructed from materials available off-the-shelf at local hardware stores. Over the years I have made several modifications to the pump design, other infrastructure, and manufacturing process to improve the longevity, simplicity, and interchangeability of the final product. The drilling method is primarily applicable to aquifers lying above bedrock and it is feasible to drill wells to a depth of several hundred feet. The greatest challenge in the endeavor is earning the trust and cultivating the participation of the local community. This presentation will address the drilling process, the well infrastructure, and some socio-cultural aspects of the project.